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de Ruiter SC, Tschiderer L, Grobbee DE, Ruigrok YM, Willeit P, den Ruijter HM, Schmidt AF, Peters SAE. Diabetes, glycaemic traits and cardiovascular disease in females and males: Observational and Mendelian randomisation analyses in the UK Biobank. Diabetes Obes Metab 2025. [PMID: 40259500 DOI: 10.1111/dom.16406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/24/2025] [Revised: 03/14/2025] [Accepted: 03/28/2025] [Indexed: 04/23/2025]
Abstract
INTRODUCTION Observational studies have shown that the association between type 2 diabetes and cardiovascular disease (CVD) is stronger in females than in males. It remains unclear whether the causal effects of diabetes and glycaemic traits on CVD are also different between females and males. METHODS We performed sex-stratified observational and Mendelian randomisation (MR) analyses in the UK Biobank to investigate the sex-specific associations of type 2 diabetes and HbA1c with CVD outcomes (combined CVD, coronary heart disease [CHD], myocardial infarction, stroke, ischaemic stroke, intracerebral haemorrhage and subarachnoid haemorrhage). As secondary analyses, we performed sex-stratified MR for the association of genetically proxied fasting glucose and insulin with CVD outcomes. RESULTS In observational analysis, diabetes was associated with a greater excess risk for CHD in females than in males (female-to-male ratio of hazard ratios 1.11 [95% CI 1.03, 1.21]). The association of HbA1c with CVD outcomes was similar in both sexes. In MR, the relationship between genetic liability to diabetes and CHD was similar in females and males (female-to-male ratio of odds ratios 0.98 [95% CI 0.91, 1.05]). No sex differences were found for the association between diabetes and stroke in both observational and MR analyses. Moreover, MR results on HbA1c, fasting glucose and fasting insulin were similar for females and males. CONCLUSION This study suggests that causal effects of diabetes and glycaemic traits on CVD are similar in females and males.
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Affiliation(s)
- Sophie C de Ruiter
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Lena Tschiderer
- Institute of Clinical Epidemiology, Public Health, Health Economics, Medical Statistics and Informatics, Medical University of Innsbruck, Innsbruck, Austria
| | - Diederick E Grobbee
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Ynte M Ruigrok
- UMC Utrecht Brain Center, Department of Neurology and Neurosurgery, Utrecht University, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Peter Willeit
- Institute of Clinical Epidemiology, Public Health, Health Economics, Medical Statistics and Informatics, Medical University of Innsbruck, Innsbruck, Austria
- Ignaz Semmelweis Institute, Interuniversity Institute for Infection Research, Medical University of Vienna, Vienna, Austria
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Hester M den Ruijter
- Laboratory of Experimental Cardiology, Department of Cardiology, University Medical Center Utrecht, University Utrecht, Utrecht, the Netherlands
| | - A Floriaan Schmidt
- Department of Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centres, University of Amsterdam, Amsterdam, the Netherlands
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, UK
- Division Heart and Lungs, Department of Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
- UCL British Heart Foundation Research Accelerator, London, UK
| | - Sanne A E Peters
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
- The George Institute for Global Health, School of Public Health, Imperial College London, London, UK
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Chen J, Zeng W, Dai D, Tang Y, Dong Y, Zhong Z, Zhou M, Ye J. A systematic analysis and prediction of the disease burden of ischemic heart disease caused by hyperglycemia. J Diabetes Investig 2025. [PMID: 40077954 DOI: 10.1111/jdi.70006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2024] [Revised: 01/23/2025] [Accepted: 01/29/2025] [Indexed: 03/14/2025] Open
Abstract
OBJECTIVE This study aims to analyze the disease burden of ischemic heart disease (IHD) caused by hyperglycemia and its changing trend, and to construct a visualization platform for disease burden and forecast trends on the Shiny platform. MATERIALS AND METHODS Using data from the 2021 Global Burden of Disease Study, we analyzed deaths and disability-adjusted life years (DALYs) due to IHD triggered by hyperglycemia, with detailed analysis by region, gender, and age. The age-period-cohort model was used to assess the impact of age, cohort, and period on age-standardized disease rates across different Socio-Demographic Index (SDI) regions, and decomposition analysis was employed to disentangle the contributions of population, aging, and epidemiological changes. RESULTS In 2021, approximately 14-15% of IHD's DALYs and deaths were attributed to high fasting plasma glucose (HFPG), with a nonsignificant decrease in the annual average percentage change of DALYs. In middle, low-middle, and low SDI regions, the age-standardized mortality rates caused by HFPG are increasing, particularly among males. In high-middle and high SDI regions, the effects of aging and epidemiological changes surpass population growth, whereas in low SDI regions, population growth is the main factor. By 2050, the global Age-Standardized Mortality Rate of IHD attributed to HFPG is projected to reach 16.96. More data can be accessed by visiting the disease burden visualization platform. CONCLUSION Global HFPG-induced IHD health presents significant imbalances. In low SDI regions with larger populations and more unbalanced healthcare distribution, there is a need to strengthen the construction of medical levels.
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Affiliation(s)
- Jianxing Chen
- Dongguan Hospital of Guangzhou University of Traditional Chinese Medicine, Dongguan, China
| | | | - Dandan Dai
- Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Yujin Tang
- Eighth Clinical School, Guangzhou University of Chinese Medicine, Foshan, Guangdong, China
| | - Yangwen Dong
- Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Zilan Zhong
- Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Miao Zhou
- Foshan Hospital of Traditional Chinese Medicine, Foshan, China
| | - Jianhong Ye
- Foshan Hospital of Traditional Chinese Medicine, Foshan, China
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Reed ZE, Sallis HM, Richmond RC, Attwood AS, Lawlor DA, Munafò MR. Investigating whether smoking and alcohol behaviours influence risk of type 2 diabetes using a Mendelian randomisation study. Sci Rep 2025; 15:7985. [PMID: 40055374 PMCID: PMC11889105 DOI: 10.1038/s41598-025-90437-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2024] [Accepted: 02/13/2025] [Indexed: 03/15/2025] Open
Abstract
Previous studies suggest that smoking and higher alcohol consumption are associated with greater type 2 diabetes (T2D) risk. However, studies examining whether this reflects causal relationships are limited and often do not consider continuous glycaemic traits. We conducted both two-sample and one-sample Mendelian randomisation (MR), using publicly available GWAS data and UK Biobank data, respectively, to examine the potential causal effects of lifetime smoking index (LSI) and alcoholic drinks per week (DPW) on T2D and continuous traits (fasting glucose, fasting insulin and glycated haemoglobin, HbA1c). Two-sample MR results suggested possible causal effects of higher LSI on T2D risk (OR per 1SD higher LSI: 1.42, 95% CI 1.22 to 1.64); however, sensitivity analyses did not consistently support this finding. There was no robust evidence that higher DPW influenced T2D risk (OR per 1 SD higher log-transformed DPW: 1.04, 95% CI 0.40 to 2.65). There was evidence of a potential causal effect on higher fasting glucose (difference in mean fasting glucose in mmol/l per 1SD higher log-transformed DPW: 0.34, 95% CI 0.09 to 0.59), though, this was attenuated when accounting for body mass index (BMI), suggesting BMI confounding might explain the potential effect. One-sample MR results suggested a possible causal effect of higher DPW on T2D risk (OR per 1 SD higher log-transformed DPW: 1.71, 95% CI 1.24 to 2.36), but lower HbA1c levels (difference in mean SD of log transformed HbA1c (mmol/mol) per 1 SD higher log-transformed DPW: -0.07, 95% CI -0.11 to -0.02). Our results suggest effective public health interventions to prevent and/or reduce smoking and alcohol consumption are unlikely to reduce T2D prevalence.
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Affiliation(s)
- Zoe E Reed
- School of Psychological Science, University of Bristol, Bristol, UK.
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
| | - Hannah M Sallis
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Centre for Academic Mental Health, Bristol Medical School, University of Bristol, Bristol, UK
| | - Rebecca C Richmond
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Angela S Attwood
- School of Psychological Science, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Marcus R Munafò
- School of Psychological Science, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- National Institute for Health Research Bristol Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust and University of Bristol, Bristol, UK
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Zheng X, Tian Z, Che X, Zhang X, Xiang Y, Ge Z, Zhai Z, Ma Q, Pan J. DMRdb: a disease-centric Mendelian randomization database for systematically assessing causal relationships of diseases with genes, proteins, CpG sites, metabolites and other diseases. Nucleic Acids Res 2025; 53:D1363-D1371. [PMID: 39351893 PMCID: PMC11701675 DOI: 10.1093/nar/gkae853] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2024] [Revised: 09/10/2024] [Accepted: 09/18/2024] [Indexed: 01/18/2025] Open
Abstract
Exploring the causal relationships of diseases with genes, proteins, CpG sites, metabolites and other diseases is fundamental to the life sciences. However, large-scale research using Mendelian randomization (MR) analysis is currently lacking. To address this, we introduce DMRdb (http://www.inbirg.com/DMRdb/), a disease-centric Mendelian randomization database, designed to systematically assess causal relationships of diseases with genes, proteins, CpG sites, metabolites and other diseases. The database consists of three main components: (i) 6640 high-quality disease genome-wide association studies (GWASs) from public sources that were subjected to rigorous quality filtering and standardization; (ii) over 497 billion results from MR analyses involving 6640 disease GWAS datasets, 16 238 expression quantitative trait loci (eQTLs) data, 2564 protein quantitative trait loci (pQTLs) data, 12 000 methylation quantitative trait locus (meQTLs) data and 825 metabolites data and (iii) over 380 000 causal relationship pairs from 1223 literature sources relevant to MR analyses. A user-friendly online database was developed to allow users to query, search, and download all the results. In summary, we anticipate that DMRdb will be a valuable resource for advancing our understanding of disease mechanisms and identifying new biomarkers and therapeutic targets.
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Affiliation(s)
- Xiao Zheng
- Basic Medicine Research and Innovation Center for Novel Target and Therapeutic Intervention, Ministry of Education, College of Pharmacy, and Precision Medicine Center, the Second Affiliated Hospital, Chongqing Medical University, Chongqing 400016, China
| | - Zhihao Tian
- Basic Medicine Research and Innovation Center for Novel Target and Therapeutic Intervention, Ministry of Education, College of Pharmacy, and Precision Medicine Center, the Second Affiliated Hospital, Chongqing Medical University, Chongqing 400016, China
| | - Xiaohui Che
- Basic Medicine Research and Innovation Center for Novel Target and Therapeutic Intervention, Ministry of Education, College of Pharmacy, and Precision Medicine Center, the Second Affiliated Hospital, Chongqing Medical University, Chongqing 400016, China
| | - Xu Zhang
- Basic Medicine Research and Innovation Center for Novel Target and Therapeutic Intervention, Ministry of Education, College of Pharmacy, and Precision Medicine Center, the Second Affiliated Hospital, Chongqing Medical University, Chongqing 400016, China
| | - Yu Xiang
- Basic Medicine Research and Innovation Center for Novel Target and Therapeutic Intervention, Ministry of Education, College of Pharmacy, and Precision Medicine Center, the Second Affiliated Hospital, Chongqing Medical University, Chongqing 400016, China
| | - Zhijian Ge
- Basic Medicine Research and Innovation Center for Novel Target and Therapeutic Intervention, Ministry of Education, College of Pharmacy, and Precision Medicine Center, the Second Affiliated Hospital, Chongqing Medical University, Chongqing 400016, China
| | - Zhaoyu Zhai
- Basic Medicine Research and Innovation Center for Novel Target and Therapeutic Intervention, Ministry of Education, College of Pharmacy, and Precision Medicine Center, the Second Affiliated Hospital, Chongqing Medical University, Chongqing 400016, China
| | - Qinfeng Ma
- Basic Medicine Research and Innovation Center for Novel Target and Therapeutic Intervention, Ministry of Education, College of Pharmacy, and Precision Medicine Center, the Second Affiliated Hospital, Chongqing Medical University, Chongqing 400016, China
| | - Jianbo Pan
- Basic Medicine Research and Innovation Center for Novel Target and Therapeutic Intervention, Ministry of Education, College of Pharmacy, and Precision Medicine Center, the Second Affiliated Hospital, Chongqing Medical University, Chongqing 400016, China
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Bekenova NB, Vochshenkova TA, Zhylkybekova A, Ablakimova N, Mussin NM, Albayev RK, Kaliyev AA, Tamadon A. Genome Variability for the Development of Coronary Heart Disease in Type 2 Diabetes Mellitus: A Bibliometric Analysis. J Multidiscip Healthc 2024; 17:5445-5455. [PMID: 39600715 PMCID: PMC11590629 DOI: 10.2147/jmdh.s471606] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2024] [Accepted: 11/18/2024] [Indexed: 11/29/2024] Open
Abstract
Introduction Cardiovascular diseases (CVDs) stand as the foremost global cause of mortality, accounting for 32% of total deaths in 2019, with 85% attributed to heart attacks and strokes. Individuals with Type 2 Diabetes Mellitus (T2DM) exhibit an elevated susceptibility to coronary heart disease (CHD). In numerous studies, it has been established that genetic polymorphism of genes influences the onset, progression, and complications of coronary heart disease (CHD) and type 2 diabetes mellitus (T2DM). The aims of this study are to employ bibliometric analysis methods for mapping the array of research on genome variability concerning the development of coronary heart disease in individuals with type 2 diabetes mellitus. Methods We derived the data from the Web of Science (WoS) Core Collection database and Scopus on January 6, 2023. All publications from 1987 to 2023 are exported in plain text format for WoS-CC and BibTeX format for Scopus, containing bibliographic information, keywords, and citation information. RStudio v.4.1.2 software (RStudio, PBC, Boston, MA, USA) was used for conducting bibliometric analysis. Results Our analysis of 241 articles published between 1987 and 2023 revealed a consistent increase in research output, especially after 2004, highlighting a growing academic focus on genome variability's role in coronary heart disease (CHD) development among Type 2 Diabetes Mellitus (T2DM) patients. Key contributing journals include The Lancet and Nature Genetics, indicating high-impact interest in this domain. The United States leads in research productivity and collaboration, with China also emerging as a notable contributor in recent years. Prominent authors such as S. Humphries have significantly shaped the field, contributing to a cumulative knowledge base that underscores the role of genetic factors in CHD among T2DM patients. Discussion Our findings underscore the value of bibliometric studies in guiding future research directions. This increasing scholarly attention to genome variability in CHD and T2DM may encourage deeper investigation into specific genetic polymorphisms and their mechanistic roles in disease progression. Additionally, these insights can help prioritize collaboration across leading research hubs and potentially drive innovation in therapeutic interventions targeting genetic risk factors in CHD and T2DM. Future research could build on these trends by focusing on comparative studies across populations, advancing precision medicine approaches for at-risk individuals with T2DM.
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Affiliation(s)
- Nazira B Bekenova
- Gerontology Center, Medical Center of the President’s Affairs Administration of the Republic of Kazakhstan, Astana, Kazakhstan
| | - Tamara A Vochshenkova
- Gerontology Center, Medical Center of the President’s Affairs Administration of the Republic of Kazakhstan, Astana, Kazakhstan
| | - Aliya Zhylkybekova
- Department of Evidence-Based Medicine and Scientific Management, West Kazakhstan Marat Ospanov Medical University, Aktobe, Kazakhstan
| | - Nurgul Ablakimova
- Department of Pharmacology, West Kazakhstan Marat Ospanov Medical University, Aktobe, Kazakhstan
| | - Nadiar M Mussin
- General Surgery, West Kazakhstan Marat Ospanov Medical University, Aktobe, Kazakhstan
| | - Rustam K Albayev
- Gerontology Center, Medical Center of the President’s Affairs Administration of the Republic of Kazakhstan, Astana, Kazakhstan
| | - Asset A Kaliyev
- General Surgery, West Kazakhstan Marat Ospanov Medical University, Aktobe, Kazakhstan
| | - Amin Tamadon
- Gerontology Center, Medical Center of the President’s Affairs Administration of the Republic of Kazakhstan, Astana, Kazakhstan
- Department for Natural Sciences, West Kazakhstan Marat Ospanov Medical University, Aktobe, Kazakhstan
- PerciaVista R&D Co, Shiraz, Iran
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Li Z, Kang S, Kang H. Development and validation of nomograms for predicting cardiovascular disease risk in patients with prediabetes and diabetes. Sci Rep 2024; 14:20909. [PMID: 39245747 PMCID: PMC11381537 DOI: 10.1038/s41598-024-71904-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2024] [Accepted: 09/02/2024] [Indexed: 09/10/2024] Open
Abstract
This study aimed to develop and validate distinct nomogram models for assessing CVD risk in individuals with prediabetes and diabetes. In a cross-sectional study design, we examined data from 2294 prediabetes and 1037 diabetics who participated in the National Health and Nutrition Examination Survey, which was conducted in the United States of America between 2007 and 2018. The dataset was randomly divided into training and validation cohorts at a ratio of 0.75-0.25. The Boruta feature selection method was used in the training cohort to identify optimal predictors for CVD diagnosis. A web-based dynamic nomogram was developed using the selected features, which were validated in the validation cohort. The Hosmer-Lemeshow test was performed to assess the nomogram's stability and performance. Receiver operating characteristics and calibration curves were used to assess the effectiveness of the nomogram. The clinical applicability of the nomogram was evaluated using decision curve analysis and clinical impact curves. In the prediabetes cohort, the CVD risk prediction nomogram included nine risk factors: age, smoking status, platelet/lymphocyte ratio, platelet count, white blood cell count, red cell distribution width, lactate dehydrogenase level, sleep disorder, and hypertension. In the diabetes cohort, the CVD risk prediction nomogram included eleven risk factors: age, material status, smoking status, systemic inflammatory response index, neutrophil-to-lymphocyte ratio, red cell distribution width, lactate dehydrogenase, high-density lipoprotein cholesterol, sleep disorder, hypertension, and physical activity. The nomogram models developed in this study have good predictive and discriminant utility for predicting CVD risk in patients with prediabetes and diabetes.
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Affiliation(s)
- Zhao Li
- College of Sport Science, Sungkyunkwan University, 2066 Seoburo, 16419, Jangan-gu, Suwon, Republic of Korea
| | - Seamon Kang
- College of Sport Science, Sungkyunkwan University, 2066 Seoburo, 16419, Jangan-gu, Suwon, Republic of Korea
| | - Hyunsik Kang
- College of Sport Science, Sungkyunkwan University, 2066 Seoburo, 16419, Jangan-gu, Suwon, Republic of Korea.
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Hui D, Sanford E, Lorenz K, Damrauer SM, Assimes TL, Thom CS, Voight BF. Mendelian randomization analyses clarify the effects of height on cardiovascular diseases. PLoS One 2024; 19:e0298786. [PMID: 38959188 PMCID: PMC11221663 DOI: 10.1371/journal.pone.0298786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Accepted: 01/30/2024] [Indexed: 07/05/2024] Open
Abstract
An inverse correlation between stature and risk of coronary artery disease (CAD) has been observed in several epidemiologic studies, and recent Mendelian randomization (MR) experiments have suggested causal association. However, the extent to which the effect estimated by MR can be explained by cardiovascular, anthropometric, lung function, and lifestyle-related risk factors is unclear, with a recent report suggesting that lung function traits could fully explain the height-CAD effect. To clarify this relationship, we utilized a well-powered set of genetic instruments for human stature, comprising >1,800 genetic variants for height and CAD. In univariable analysis, we confirmed that a one standard deviation decrease in height (~6.5 cm) was associated with a 12.0% increase in the risk of CAD, consistent with previous reports. In multivariable analysis accounting for effects from up to 12 established risk factors, we observed a >3-fold attenuation in the causal effect of height on CAD susceptibility (3.7%, p = 0.02). However, multivariable analyses demonstrated independent effects of height on other cardiovascular traits beyond CAD, consistent with epidemiologic associations and univariable MR experiments. In contrast with published reports, we observed minimal effects of lung function traits on CAD risk in our analyses, indicating that these traits are unlikely to explain the residual association between height and CAD risk. In sum, these results suggest the impact of height on CAD risk beyond previously established cardiovascular risk factors is minimal and not explained by lung function measures.
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Affiliation(s)
- Daniel Hui
- Graduate Program in Genomics and Computational Biology, University of Pennsylvania, Philadelphia, PA, United States of America
| | - Eric Sanford
- Medical Scientist Training Program, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America
| | - Kimberly Lorenz
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, PA, United States of America
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America
- Institute for Translational Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, United States of America
| | - Scott M. Damrauer
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, United States of America
- Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America
| | - Themistocles L. Assimes
- VA Palo Alto Health Care System, Palo Alto, CA, United States of America
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, United States of America
| | - Christopher S. Thom
- Division of Neonatology, Children’s Hospital of Philadelphia, Philadelphia, PA, United States of America
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America
| | - Benjamin F. Voight
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, PA, United States of America
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America
- Institute for Translational Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, United States of America
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Zhang W, Zhang L, Xiao C, Wu X, Cui H, Yang C, Yan P, Tang M, Wang Y, Chen L, Liu Y, Zou Y, Zhang L, Yang C, Yao Y, Li J, Liu Z, Jiang X, Zhang B. Bidirectional relationship between type 2 diabetes mellitus and coronary artery disease: Prospective cohort study and genetic analyses. Chin Med J (Engl) 2024; 137:577-587. [PMID: 38062574 DOI: 10.1097/cm9.0000000000002894] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Indexed: 03/13/2024] Open
Abstract
BACKGROUND While type 2 diabetes mellitus (T2DM) is considered a putative causal risk factor for coronary artery disease (CAD), the intrinsic link underlying T2DM and CAD is not fully understood. We aimed to highlight the importance of integrated care targeting both diseases by investigating the phenotypic and genetic relationships between T2DM and CAD. METHODS We evaluated phenotypic associations using data from the United Kingdom Biobank ( N = 472,050). We investigated genetic relationships by leveraging genomic data conducted in European ancestry for T2DM, with and without adjustment for body mass index (BMI) (T2DM: Ncase / Ncontrol = 74,124/824,006; T2DM adjusted for BMI [T2DM adj BMI]: Ncase / Ncontrol = 50,409/523,897) and for CAD ( Ncase / Ncontrol = 181,522/984,168). We performed additional analyses using genomic data conducted in multiancestry individuals for T2DM ( Ncase / Ncontrol = 180,834/1,159,055). RESULTS Observational analysis suggested a bidirectional relationship between T2DM and CAD (T2DM→CAD: hazard ratio [HR] = 2.12, 95% confidence interval [CI]: 2.01-2.24; CAD→T2DM: HR = 1.72, 95% CI: 1.63-1.81). A positive overall genetic correlation between T2DM and CAD was observed ( rg = 0.39, P = 1.43 × 10 -75 ), which was largely independent of BMI (T2DM adj BMI-CAD: rg = 0.31, P = 1.20 × 10 -36 ). This was corroborated by six local signals, among which 9p21.3 showed the strongest genetic correlation. Cross-trait meta-analysis replicated 101 previously reported loci and discovered six novel pleiotropic loci. Mendelian randomization analysis supported a bidirectional causal relationship (T2DM→CAD: odds ratio [OR] = 1.13, 95% CI: 1.11-1.16; CAD→T2DM: OR = 1.12, 95% CI: 1.07-1.18), which was confirmed in multiancestry individuals (T2DM→CAD: OR = 1.13, 95% CI: 1.10-1.16; CAD→T2DM: OR = 1.08, 95% CI: 1.04-1.13). This bidirectional relationship was significantly mediated by systolic blood pressure and intake of 3-hydroxy-3-methylglutaryl coenzyme A reductase inhibitors, with mediation proportions of 54.1% (95% CI: 24.9-83.4%) and 90.4% (95% CI: 29.3-151.5%), respectively. CONCLUSION Our observational and genetic analyses demonstrated an intrinsic bidirectional relationship between T2DM and CAD and clarified the biological mechanisms underlying this relationship.
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Affiliation(s)
- Wenqiang Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Li Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Chenghan Xiao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Xueyao Wu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Huijie Cui
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Chao Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Peijing Yan
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Mingshuang Tang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Yutong Wang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Lin Chen
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Yunjie Liu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Yanqiu Zou
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Ling Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- Department of Iatrical Polymer Material and Artificial Apparatus, School of Polymer Science and Engineering, Sichuan University, Chengdu, Sichuan 610041, China
| | - Chunxia Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Yuqin Yao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Jiayuan Li
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Zhenmi Liu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Xia Jiang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- Department of Nutrition and Food Hygiene, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm 17177, Sweden
| | - Ben Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-Peking Union Medical College C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
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9
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Silva S, Fatumo S, Nitsch D. Mendelian randomization studies on coronary artery disease: a systematic review and meta-analysis. Syst Rev 2024; 13:29. [PMID: 38225600 PMCID: PMC10790478 DOI: 10.1186/s13643-023-02442-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 12/20/2023] [Indexed: 01/17/2024] Open
Abstract
BACKGROUND Coronary artery disease (CAD) remains one of the leading causes of mortality worldwide. We aimed to summarize what is currently known with regard to causal modifiable risk factors associated with CAD in populations of diverse ancestries through conducting a systematic review and meta-analysis of Mendelian randomization (MR) studies on CAD. METHODS The databases Embase, Medline, Cochrane Library and Web of Science were searched on the 19th and 20th of December 2022 for MR studies with CAD as a primary outcome; keywords of the search strategy included "coronary artery disease" and "mendelian randomization". Studies were included if they were published in the English language, included only human participants, employed Mendelian randomization as the primary methodology and studied CAD as the outcome of interest. The exclusion criteria resulted in the removal of studies that did not align with the predefined inclusion criteria, as well as studies which were systematic reviews themselves, and used the same exposure and outcome source as another study. An ancestry-specific meta-analysis was subsequently conducted on studies which investigated either body mass index, lipid traits, blood pressure or type 2 diabetes as an exposure variable. Assessment of publication bias and sensitivity analyses was conducted for risk of bias assessment in the included studies. RESULTS A total of 1781 studies were identified through the database searches after de-duplication was performed, with 47 studies included in the quantitative synthesis after eligibility screening. Approximately 80% of all included study participants for MR studies on CAD were of European descent irrespective of the exposure of interest, while no study included individuals of African ancestry. We found no evidence of differences in terms of direction of causation between ancestry groups; however, the strength of the respective relationships between each exposure and CAD were different, with this finding most evident when blood pressure was the exposure of interest. CONCLUSIONS Findings from this review suggest that patterns regarding the causational relationship between modifiable risk factors and CAD do not differ in terms of direction when compared across diverse ancestry populations. Differences in the observed strengths of the respective relationships however are indicative of the value of increasing representation in non-European populations, as novel genetic pathways or functional SNPs relating to CAD may be uncovered through a more global analysis. SYSTEMATIC REVIEW REGISTRATION The protocol for this systematic review was registered to the International Prospective Register of Systematic Reviews (PROSPERO) and is publicly available online (CRD42021272726).
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Affiliation(s)
- Sarah Silva
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.
- The African Computational Genomics (TACG) Research Group, MRC/UVRI, and LSHTM, Entebbe, Uganda.
| | - Segun Fatumo
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.
- The African Computational Genomics (TACG) Research Group, MRC/UVRI, and LSHTM, Entebbe, Uganda.
| | - Dorothea Nitsch
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
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10
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Muniyappa R, Narayanappa SBK. Disentangling Dual Threats: Premature Coronary Artery Disease and Early-Onset Type 2 Diabetes Mellitus in South Asians. J Endocr Soc 2023; 8:bvad167. [PMID: 38178904 PMCID: PMC10765382 DOI: 10.1210/jendso/bvad167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Indexed: 01/06/2024] Open
Abstract
South Asian individuals (SAs) face heightened risks of premature coronary artery disease (CAD) and early-onset type 2 diabetes mellitus (T2DM), with grave health, societal, and economic implications due to the region's dense population. Both conditions, influenced by cardiometabolic risk factors such as insulin resistance, hypertension, and central adiposity, manifest earlier and with unique thresholds in SAs. Epidemiological, demographic, nutritional, environmental, sociocultural, and economic transitions in SA have exacerbated the twin epidemic. The coupling of premature CAD and T2DM arises from increased obesity due to limited adipose storage, early-life undernutrition, distinct fat thresholds, reduced muscle mass, and a predisposition for hepatic fat accumulation from certain dietary choices cumulatively precipitating a decline in insulin sensitivity. As T2DM ensues, the β-cell adaptive responses are suboptimal, precipitating a transition from compensatory hyperinsulinemia to β-cell decompensation, underscoring a reduced functional β-cell reserve in SAs. This review delves into the interplay of these mechanisms and highlights a prediabetes endotype tied to elevated vascular risk. Deciphering these mechanistic interconnections promises to refine stratification paradigms, surpassing extant risk-prediction strategies.
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Affiliation(s)
- Ranganath Muniyappa
- Clinical Endocrine Section, Diabetes, Endocrinology, and Obesity Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland 20892, USA
| | - Satish Babu K Narayanappa
- Department of Medicine, Sri Madhusudan Sai Institute of Medical Sciences and Research, Muddenahalli, Karnataka 562101, India
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11
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Sánchez-Valle J, Valencia A. Molecular bases of comorbidities: present and future perspectives. Trends Genet 2023; 39:773-786. [PMID: 37482451 DOI: 10.1016/j.tig.2023.06.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 06/12/2023] [Accepted: 06/12/2023] [Indexed: 07/25/2023]
Abstract
Co-occurrence of diseases decreases patient quality of life, complicates treatment choices, and increases mortality. Analyses of electronic health records present a complex scenario of comorbidity relationships that vary by age, sex, and cohort under study. The study of similarities between diseases using 'omics data, such as genes altered in diseases, gene expression, proteome, and microbiome, are fundamental to uncovering the origin of, and potential treatment for, comorbidities. Recent studies have produced a first generation of genetic interpretations for as much as 46% of the comorbidities described in large cohorts. Integrating different sources of molecular information and using artificial intelligence (AI) methods are promising approaches for the study of comorbidities. They may help to improve the treatment of comorbidities, including the potential repositioning of drugs.
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Affiliation(s)
- Jon Sánchez-Valle
- Life Sciences Department, Barcelona Supercomputing Center, Barcelona, 08034, Spain.
| | - Alfonso Valencia
- Life Sciences Department, Barcelona Supercomputing Center, Barcelona, 08034, Spain; ICREA, Barcelona, 08010, Spain.
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12
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Liu Z, Wang H, Yang Z, Lu Y, Zou C. Causal associations between type 1 diabetes mellitus and cardiovascular diseases: a Mendelian randomization study. Cardiovasc Diabetol 2023; 22:236. [PMID: 37659996 PMCID: PMC10475187 DOI: 10.1186/s12933-023-01974-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 08/25/2023] [Indexed: 09/04/2023] Open
Abstract
BACKGROUND The presence of type 1 diabetes mellitus (T1DM) has been demonstrated to pose an increased risk for developing cardiovascular diseases (CVDs). However, the causal relationships between T1DM and CVDs remain unclear due to the uncontrolled confounding factors and reverse causation bias of the observational studies. METHODS Summary statistics of T1DM and seven CVDs from the largest available genome-wide association studies (GWAS) of European ancestry and FinnGen biobank were extracted for the primary MR analysis, and the analysis was replicated using UK biobank (UKBB) for validation. Three complementary methods: inverse variance weighted (IVW), weighted median, and MR-Egger were used for the MR estimates. The potential pleiotropic effects were assessed by MR-Egger intercept and MR-PRESSO global test. Additionally, multivariable MR (MVMR) analysis was performed to examine whether T1DM has independent effects on CVDs with adjustment of potential confounding factors. Moreover, a two-step MR approach was used to assess the potential mediating effects of these factors on the causal effects between T1DM and CVDs. RESULTS Causal effects of T1DM on peripheral atherosclerosis (odds ratio [OR] = 1.06, 95% confidence interval [CI]: 1.02-1.10; p = 0.002)] and coronary atherosclerosis (OR = 1.03, 95% CI: 1.01-1.05; p = 0.001) were found. The results were less likely to be biased by the horizontal pleiotropic effects (both p values of MR-Egger intercept and MR-PRESSO Global test > 0.05). In the following MVMR analysis, we found the causal effects of T1DM on peripheral atherosclerosis and coronary atherosclerosis remain significant after adjusting for a series of potential confounding factors. Moreover, we found that hypertension partly mediated the causal effects of T1DM on peripheral atherosclerosis (proportion of mediation effect in total effect: 11.47%, 95% CI: 3.23-19.71%) and coronary atherosclerosis (16.84%, 95% CI: 5.35-28.33%). We didn't find significant causal relationships between T1DM and other CVDs, including heart failure (HF), coronary artery disease (CAD), atrial fibrillation (AF), myocardial infarction (MI) and stroke. For the reverse MR from CVD to T1DM, no significant causal relationships were identified. CONCLUSION This MR study provided evidence supporting the causal effect of T1DM on peripheral atherosclerosis and coronary atherosclerosis, with hypertension partly mediating this effect.
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Affiliation(s)
- Zirui Liu
- Department of Cardiology, First Affiliated Hospital of Soochow University, No.188 Shizi Street, Gusu District, Suzhou City, Jiangsu Province, China
| | - Haocheng Wang
- Department of Cardiology, First Affiliated Hospital of Soochow University, No.188 Shizi Street, Gusu District, Suzhou City, Jiangsu Province, China
| | - Zhengkai Yang
- Department of Cardiology, First Affiliated Hospital of Soochow University, No.188 Shizi Street, Gusu District, Suzhou City, Jiangsu Province, China
| | - Yu Lu
- Department of Cardiology, First Affiliated Hospital of Soochow University, No.188 Shizi Street, Gusu District, Suzhou City, Jiangsu Province, China
| | - Cao Zou
- Department of Cardiology, First Affiliated Hospital of Soochow University, No.188 Shizi Street, Gusu District, Suzhou City, Jiangsu Province, China.
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13
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Ren Z, Wesselius A, Stehouwer CDA, Brouwers MCGJ. Cardiovascular Implications of Metabolic Dysfunction-Associated Fatty Liver Disease. Endocrinol Metab Clin North Am 2023; 52:459-468. [PMID: 37495337 DOI: 10.1016/j.ecl.2023.01.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/28/2023]
Abstract
Both nonalcoholic fatty liver disease (NAFLD) and metabolic dysfunction-associated fatty liver disease (MAFLD) have been associated with incident cardiovascular disease (CVD), independent of confounders. Causality has recently been inferred by Mendelian randomization studies. Although these findings have contributed to current guidelines that recommend screening for and treatment of cardiovascular risk factors, it not yet clear how to position NAFLD/MAFLD in cardiovascular risk estimation scores and, consequently, which treatment targets should be used. This review aims to provide practical tools as well as suggestions for further research in order to effectively prevent CVD events in patients with NAFLD/MAFLD.
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Affiliation(s)
- Zhewen Ren
- Division of Endocrinology and Metabolic Disease, Department of Internal Medicine, Maastricht University Medical Center, P Debyelaan 25, 6229 HX Maastricht, the Netherlands; CARIM School for Cardiovascular Diseases, Maastricht University, Universiteitssingel 50, 6229 ER Maastricht, the Netherlands; Laboratory for Metabolism and Vascular Medicine, Maastricht University, Universiteitssingel 50, 6229 ER Maastricht, the Netherlands
| | - Anke Wesselius
- Department of Epidemiology, Maastricht University, Universiteitssingel 50, 6229 ER Maastricht, the Netherlands; NUTRIM School for Nutrition and Translational Research in Metabolism Maastricht University, Universiteitssingel 50, 6229 ER Maastricht, the Netherlands
| | - Coen D A Stehouwer
- Division of Endocrinology and Metabolic Disease, Department of Internal Medicine, Maastricht University Medical Center, P Debyelaan 25, 6229 HX Maastricht, the Netherlands; Division of General Internal Medicine, Department of Internal Medicine, Maastricht University Medical Centre, P Debyelaan 25, 6229 HX Maastricht, the Netherlands
| | - Martijn C G J Brouwers
- Division of Endocrinology and Metabolic Disease, Department of Internal Medicine, Maastricht University Medical Center, P Debyelaan 25, 6229 HX Maastricht, the Netherlands; CARIM School for Cardiovascular Diseases, Maastricht University, Universiteitssingel 50, 6229 ER Maastricht, the Netherlands.
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14
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Wu F, Tan Z, Li T, Zhang M, He Y, Chen S, Yu P, Ou M, Liu L, Wang X. Qualitative and quantitative analysis of the chemical components in Yuquan capsules by using ultra-performance liquid chromatography-mass spectrometry. J Sep Sci 2023; 46:e2300148. [PMID: 37415310 DOI: 10.1002/jssc.202300148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 05/21/2023] [Accepted: 06/08/2023] [Indexed: 07/08/2023]
Abstract
The Yuquan capsules is a commonly used traditional Chinese Patent Medicine used for the treatment of diabetes mellitus. In this study, a high-throughput analytical method for identifying the chemical composition of Yuquan capsules was established for the first time by using ultra-performance liquid chromatography-quadrupole time of flight mass spectrometry. The data obtained were subjected to fragment analysis and this was combined with UNIFI processing of natural products. One-hundred sixteen compounds were characterized from Yuquan capsules. Twelve of the bioactive compounds were quantitatively analyzed by ultra-performance liquid chromatography-tandem triple quadrupole mass spectrometry. This study was undertaken to obtain a comprehensive chemical profile analysis as well as to evaluate the overall quality of Yuquan capsules. The results will provide a reference for the quality evaluation of different Yuquan preparations. In addition, the data will enable basic pharmacodynamic research into these extensively used capsules.
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Affiliation(s)
- Fangfang Wu
- National Engineering Laboratory for the Development of Southwestern Endangered, Medicinal Materials, Guangxi Botanical Garden of Medicinal Plants, Nanning, P. R. China
| | - Zhien Tan
- National Engineering Laboratory for the Development of Southwestern Endangered, Medicinal Materials, Guangxi Botanical Garden of Medicinal Plants, Nanning, P. R. China
| | - Taiping Li
- National Engineering Laboratory for the Development of Southwestern Endangered, Medicinal Materials, Guangxi Botanical Garden of Medicinal Plants, Nanning, P. R. China
- National Chinmedomics Research Center, National TCM Key Laboratory of Serum Pharmacochemistry, Chinmedomics Research Center of State Administration of TCM, Laboratory of Metabolomics, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Harbin, P. R. China
| | - Mengli Zhang
- National Engineering Laboratory for the Development of Southwestern Endangered, Medicinal Materials, Guangxi Botanical Garden of Medicinal Plants, Nanning, P. R. China
| | - Yanmei He
- National Engineering Laboratory for the Development of Southwestern Endangered, Medicinal Materials, Guangxi Botanical Garden of Medicinal Plants, Nanning, P. R. China
- National Chinmedomics Research Center, National TCM Key Laboratory of Serum Pharmacochemistry, Chinmedomics Research Center of State Administration of TCM, Laboratory of Metabolomics, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Harbin, P. R. China
| | - Shimin Chen
- National Engineering Laboratory for the Development of Southwestern Endangered, Medicinal Materials, Guangxi Botanical Garden of Medicinal Plants, Nanning, P. R. China
| | - Pan Yu
- National Engineering Laboratory for the Development of Southwestern Endangered, Medicinal Materials, Guangxi Botanical Garden of Medicinal Plants, Nanning, P. R. China
| | - Min Ou
- National Engineering Laboratory for the Development of Southwestern Endangered, Medicinal Materials, Guangxi Botanical Garden of Medicinal Plants, Nanning, P. R. China
| | - Lingjie Liu
- National Engineering Laboratory for the Development of Southwestern Endangered, Medicinal Materials, Guangxi Botanical Garden of Medicinal Plants, Nanning, P. R. China
| | - Xijun Wang
- National Engineering Laboratory for the Development of Southwestern Endangered, Medicinal Materials, Guangxi Botanical Garden of Medicinal Plants, Nanning, P. R. China
- National Chinmedomics Research Center, National TCM Key Laboratory of Serum Pharmacochemistry, Chinmedomics Research Center of State Administration of TCM, Laboratory of Metabolomics, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Harbin, P. R. China
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15
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Hui D, Sanford E, Lorenz K, Damrauer SM, Assimes TL, Thom CS, Voight BF. Mendelian randomization analyses clarify the effects of height on cardiovascular diseases. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2021.12.16.21267869. [PMID: 37205563 PMCID: PMC10187353 DOI: 10.1101/2021.12.16.21267869] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
An inverse correlation between stature and risk of coronary artery disease (CAD) has been observed in several epidemiologic studies, and recent Mendelian randomization (MR) experiments have suggested causal association. However, the extent to which the effect estimated by MR can be explained by established cardiovascular risk factors is unclear, with a recent report suggesting that lung function traits could fully explain the height-CAD effect. To clarify this relationship, we utilized a well-powered set of genetic instruments for human stature, comprising >1,800 genetic variants for height and CAD. In univariable analysis, we confirmed that a one standard deviation decrease in height (~6.5 cm) was associated with a 12.0% increase in the risk of CAD, consistent with previous reports. In multivariable analysis accounting for effects from up to 12 established risk factors, we observed a >3-fold attenuation in the causal effect of height on CAD susceptibility (3.7%, p = 0.02). However, multivariable analyses demonstrated independent effects of height on other cardiovascular traits beyond CAD, consistent with epidemiologic associations and univariable MR experiments. In contrast with published reports, we observed minimal effects of lung function traits on CAD risk in our analyses, indicating that these traits are unlikely to explain the residual association between height and CAD risk. In sum, these results suggest the impact of height on CAD risk beyond previously established cardiovascular risk factors is minimal and not explained by lung function measures.
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Affiliation(s)
- Daniel Hui
- Graduate Program in Genomics and Computational Biology, University of Pennsylvania, Philadelphia, PA, USA
| | - Eric Sanford
- Medical Scientist Training Program, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Kimberly Lorenz
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Institute for Translational Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA 19104, USA
| | - Scott M. Damrauer
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA 19104, USA
- Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Themistocles L. Assimes
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Christopher S. Thom
- Division of Neonatology, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Benjamin F. Voight
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Institute for Translational Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA 19104, USA
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16
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Jansåker F, Ekström O, Memon AA, Hansson O, Johansson SE, Sundquist K. Examining the causal effect of type 2 diabetes on ischemic heart disease - A longitudinal study with four measurements (1980-2017). Diabetes Res Clin Pract 2023; 198:110595. [PMID: 36842479 DOI: 10.1016/j.diabres.2023.110595] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Revised: 01/30/2023] [Accepted: 02/21/2023] [Indexed: 02/26/2023]
Abstract
OBJECTIVE This longitudinal study examines a possible causal effect between type 2 diabetes and ischemic heart disease (IHD) by using measurements on four occasions from the Swedish Statistics on Income and Living Conditions (SILC) together with nationwide healthcare registers. METHODS This was a longitudinal study based on a random sample of men and women (n = 2014) from the Swedish population with four measurements in the SILC every eight years. Baseline was 1980/81 and the participants were followed for up to 37 years. The mean age and age range at baseline were 36.5 and 20-59 years, respectively. The study used Marginal Structural Modeling (MSM-Cox) to account for time-varying exposures by implementing inverse probability weighting (IPTW). MSM-Cox with IPTW was compared with Cox proportional hazard modelling. RESULTS The hazard ratio (HR) for IHD (369 cases) with 95% confidence interval (CI) in participants with type 2 diabetes (11.1%) compared to participants without type 2 diabetes (88.9%) was significantly higher (1.99; CI = 1.15 - 3.44) when using MSM-Cox with IPTW after adjustments for clinical and sociodemographic risk factors. When applying Cox proportional hazard models adjusted for the same variables, the HR was lower and non-significant at 1.34 (CI = 0.94 - 1.98). CONCLUSIONS This longitudinal study with four measurements assessed a possible causal association between type 2 diabetes and IHD by applying MSM-Cox with IPTW. Although causality cannot be determined due to the remaining risk of residual bias, the results may help to elucidate a potential causal relationship between type 2 diabetes and IHD. Further causal studies on possible underlying mechanisms are, however, needed.
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Affiliation(s)
- Filip Jansåker
- Center for Primary Health Care Research, Department of Clinical Sciences, Lund University, Region Skåne, Malmö, Sweden
| | - Ola Ekström
- Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Malmö, Sweden.
| | - Ashfaque A Memon
- Center for Primary Health Care Research, Department of Clinical Sciences, Lund University, Region Skåne, Malmö, Sweden
| | - Ola Hansson
- Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Malmö, Sweden; Institute for Molecular Medicine Finland (FIMM), Helsinki University, Helsinki, Finland
| | - Sven-Erik Johansson
- Center for Primary Health Care Research, Department of Clinical Sciences, Lund University, Region Skåne, Malmö, Sweden
| | - Kristina Sundquist
- Center for Primary Health Care Research, Department of Clinical Sciences, Lund University, Region Skåne, Malmö, Sweden; Department of Family Medicine and Community Health, Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, NY, USA; Center for Community-based Healthcare Research and Education (CoHRE), Department of Functional Pathology, School of Medicine, Shimane University, Japan
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17
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Genetic correlation and gene-based pleiotropy analysis for four major neurodegenerative diseases with summary statistics. Neurobiol Aging 2023; 124:117-128. [PMID: 36740554 DOI: 10.1016/j.neurobiolaging.2022.12.012] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 03/25/2022] [Accepted: 12/27/2022] [Indexed: 01/02/2023]
Abstract
Recent genome-wide association studies suggested shared genetic components between neurodegenerative diseases. However, pleiotropic association patterns among them remain poorly understood. We here analyzed 4 major neurodegenerative diseases including Alzheimer's disease (AD), Parkinson's disease (PD), frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS), and found suggestively positive genetic correlation. We next implemented a gene-centric pleiotropy analysis with a powerful method called PLACO and detected 280 pleiotropic associations (226 unique genes) with these diseases. Functional analyses demonstrated that these genes were enriched in the pancreas, liver, heart, blood, brain, and muscle tissues; and that 42 pleiotropic genes exhibited drug-gene interactions with 341 drugs. Using Mendelian randomization, we discovered that AD and PD can increase the risk of developing ALS, and that AD and ALS can also increase the risk of developing FTD, respectively. Overall, this study provides in-depth insights into shared genetic components and causal relationship among the 4 major neurodegenerative diseases, indicating genetic overlap and causality commonly drive their co-occurrence. It also has important implications on the etiology understanding, drug development and therapeutic targets for neurodegenerative diseases.
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18
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Garfield V, Salzmann A, Burgess S, Chaturvedi N. A Guide for Selection of Genetic Instruments in Mendelian Randomization Studies of Type 2 Diabetes and HbA1c: Toward an Integrated Approach. Diabetes 2023; 72:175-183. [PMID: 36669000 PMCID: PMC7614590 DOI: 10.2337/db22-0110] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Accepted: 10/24/2022] [Indexed: 01/21/2023]
Abstract
In this study we examine the instrument selection strategies currently used throughout the type 2 diabetes and HbA1c Mendelian randomization (MR) literature. We then argue for a more integrated and thorough approach, providing a framework to do this in the context of HbA1c and diabetes. We conducted a literature search for MR studies that have instrumented diabetes and/or HbA1c. We also used data from the UK Biobank (UKB) (N = 349,326) to calculate instrument strength metrics that are key in MR studies (the F statistic for average strength and R2 for total strength) with two different methods ("individual-level data regression" and Cragg-Donald formula). We used a 157-single nucleotide polymorphism (SNP) instrument for diabetes and a 51-SNP instrument (with partition into glycemic and erythrocytic as well) for HbA1c. Our literature search yielded 48 studies for diabetes and 22 for HbA1c. Our UKB empirical examples showed that irrespective of the method used to calculate metrics of strength and whether the instrument was the main one or included partition by function, the HbA1c genetic instrument is strong in terms of both average and total strength. For diabetes, a 157-SNP instrument was shown to have good average strength and total strength, but these were both substantially lesser than those of the HbA1c instrument. We provide a careful set of five recommendations to researchers who wish to genetically instrument type 2 diabetes and/or HbA1c. In MR studies of glycemia, investigators should take a more integrated approach when selecting genetic instruments, and we give specific guidance on how to do this.
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Affiliation(s)
- Victoria Garfield
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London
| | - Antoine Salzmann
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London
| | - Stephen Burgess
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK, MRC Biostatistics Unit, University of Cambridge, UK
| | - Nish Chaturvedi
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London
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Ren Z, Simons PIHG, Wesselius A, Stehouwer CDA, Brouwers MCGJ. Relationship between NAFLD and coronary artery disease: A Mendelian randomization study. Hepatology 2023; 77:230-238. [PMID: 35441719 PMCID: PMC9970021 DOI: 10.1002/hep.32534] [Citation(s) in RCA: 74] [Impact Index Per Article: 37.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 04/05/2022] [Accepted: 04/16/2022] [Indexed: 02/03/2023]
Abstract
BACKGROUND AND AIMS There is an ongoing debate on whether NAFLD is an active contributor or an innocent bystander in the pathogenesis of coronary artery disease (CAD). The aim of the present study was to assess the causal relationship between NAFLD and CAD. APPROACH AND RESULTS We performed two-sample Mendelian randomization (MR) analyses using summary-level data to assess the association between genetically predicted NAFLD (i.e., chronically elevated serum alanine aminotransferase levels [cALT], imaging-based and biopsy-confirmed NAFLD) and risk of CAD. Analyses were repeated after exclusion of NAFLD susceptibility genes that are associated with impaired VLDL secretion.Inverse-variance weighted MR analyses showed a statistically significant association between genetically predicted cALT and risk of CAD (OR: 1.116, 95% CI: 1.039, 1.199), but not for the other NAFLD-related traits (OR: 1.046, 95% CI: 0.764, 1.433 and OR: 1.014, 95% CI: 0.968, 1.062 for imaging-based and biopsy-confirmed NAFLD, respectively). MR-Egger regression revealed a statistically significant intercept, indicative of directional pleiotropy, for all traits. Repeat analyses after exclusion of genes associated with impaired VLDL secretion showed consistent associations between genetically predicted NAFLD and CAD for all traits (i.e., cALT [OR: 1.203, 95% CI: 1.113, 1.300]), imaging-based (OR: 2.149, 95% CI: 1.276, 3.620) and biopsy-confirmed NAFLD (OR: 1.113, 95% CI: 1.041, 1.189), which persisted when more stringent biopsy-confirmed NAFLD criteria were used (OR: 1.154, 95% CI: 1.043, 1.278) or when more stringent MR methods were applied. MR-Egger regression did not show a statistically significant intercept. CONCLUSION The two-sample MR analyses showed a robust association between genetically predicted NAFLD and CAD after exclusion of genetic variants that are implicated in impaired VLDL secretion.
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Affiliation(s)
- Zhewen Ren
- Division of Endocrinology and Metabolic Diseases, Department of Internal Medicine, Maastricht University Medical Center, Maastricht, The Netherlands
- Laboratory for Metabolism and Vascular Medicine, Maastricht University, Maastricht, The Netherlands
- CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands
| | - Pomme I. H. G. Simons
- Division of Endocrinology and Metabolic Diseases, Department of Internal Medicine, Maastricht University Medical Center, Maastricht, The Netherlands
- Laboratory for Metabolism and Vascular Medicine, Maastricht University, Maastricht, The Netherlands
- CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands
| | - Anke Wesselius
- NUTRIM School for Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, the Netherlands
- Department of Epidemiology, Maastricht University, Maastricht, the Netherlands
| | - Coen D. A. Stehouwer
- Laboratory for Metabolism and Vascular Medicine, Maastricht University, Maastricht, The Netherlands
- CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands
- Division of General Internal Medicine, Department of Internal Medicine, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Martijn C. G. J. Brouwers
- Division of Endocrinology and Metabolic Diseases, Department of Internal Medicine, Maastricht University Medical Center, Maastricht, The Netherlands
- CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands
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20
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Chen K, Zheng J, Shao C, Zhou Q, Yang J, Huang T, Tang YD. Causal effects of genetically predicted type 2 diabetes mellitus on blood lipid profiles and concentration of particle-size-determined lipoprotein subclasses: A two-sample Mendelian randomization study. Front Cardiovasc Med 2022; 9:965995. [PMID: 36312274 PMCID: PMC9606322 DOI: 10.3389/fcvm.2022.965995] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Accepted: 09/20/2022] [Indexed: 12/02/2022] Open
Abstract
Background Observational studies have shown inconsistent results of the associations between type 2 diabetes mellitus (T2DM) and blood lipid profiles, while there is also a lack of evidence from randomized controlled trials (RCTs) for the causal effects of T2DM on blood lipid profiles and lipoprotein subclasses. Objectives Our study aimed at investigating the causal effects of T2DM on blood lipid profiles and concentration of particle-size-determined lipoprotein subclasses by using the two-sample Mendelian randomization (MR) method. Methods We obtained genetic variants for T2DM and blood lipid profiles including high-density lipoprotein-cholesterol (HDL-C), low-density lipoprotein-cholesterol (LDL-C), triglycerides (TG), and total cholesterol (TC) from international genome-wide association studies (GWASs). Two-sample MR method was applied to explore the potential causal effects of genetically predicted T2DM on blood lipid profiles based on different databases, respectively, and results from each MR analysis were further meta-analyzed to obtain the summary results. The causal effects of genetically predicted T2DM on the concentration of different subclasses of lipoproteins that are determined by particle size were also involved in MR analysis. Results Genetically predicted 1-unit higher log odds of T2DM had a significant causal effect on a higher level of TG (estimated β coefficient: 0.03, 95% confidence interval [CI]: 0.00 to 0.06) and lower level of HDL-C (estimated β coefficient: −0.09, 95% CI: −0.11 to −0.06). The causality of T2DM on the level of TC or LDL-C was not found (estimated β coefficient: −0.01, 95% CI: −0.02 to 0.01 for TC and estimated β coefficient: 0.01, 95% CI: −0.01 to 0.02 for LDL-C). For different sizes of lipoprotein particles, 1-unit higher log odds of T2DM was causally associated with higher level of small LDL particles, and lower level of medium HDL particles, large HDL particles, and very large HDL particles. Conclusion Evidence from our present study showed causal effects of T2DM on the level of TG, HDL-C, and concentration of different particle sizes of lipoprotein subclasses comprehensively, which might be particularly helpful in illustrating dyslipidemia experienced by patients with T2DM, and further indicate new treatment targets for these patients to prevent subsequent excessive cardiovascular events from a genetic point of view.
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Affiliation(s)
- Ken Chen
- Key Laboratory of Molecular Cardiovascular Sciences, Department of Cardiology, Institute of Vascular Medicine, Ministry of Education, Peking University Third Hospital, Beijing, China,Department of Cardiology, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Jilin Zheng
- Key Laboratory of Molecular Cardiovascular Sciences, Department of Cardiology, Institute of Vascular Medicine, Ministry of Education, Peking University Third Hospital, Beijing, China
| | - Chunli Shao
- Key Laboratory of Molecular Cardiovascular Sciences, Department of Cardiology, Institute of Vascular Medicine, Ministry of Education, Peking University Third Hospital, Beijing, China,Department of Cardiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China,Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Qing Zhou
- Department of Cardiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China,Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jie Yang
- Department of Cardiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China,Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Tao Huang
- Key Laboratory of Molecular Cardiovascular Sciences, Department of Cardiology, Institute of Vascular Medicine, Ministry of Education, Peking University Third Hospital, Beijing, China,Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China,Department of Global Health, School of Public Health, Peking University, Beijing, China,Center for Intelligent Public Health, Institute for Artificial Intelligence, Peking University, Beijing, China
| | - Yi-Da Tang
- Key Laboratory of Molecular Cardiovascular Sciences, Department of Cardiology, Institute of Vascular Medicine, Ministry of Education, Peking University Third Hospital, Beijing, China,Department of Cardiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China,Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China,*Correspondence: Yi-Da Tang
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21
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Çildağ MB, Şahin T, Ceylan E, Şavk ŞÖ. The Effect of Atherosclerotic Load on Transmetatarsal Amputation Failure in Patients with Diabetic Foot. MEANDROS MEDICAL AND DENTAL JOURNAL 2022. [DOI: 10.4274/meandros.galenos.2022.68815] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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22
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Howe LJ, Tudball M, Davey Smith G, Davies NM. Interpreting Mendelian-randomization estimates of the effects of categorical exposures such as disease status and educational attainment. Int J Epidemiol 2022; 51:948-957. [PMID: 34570226 PMCID: PMC9189950 DOI: 10.1093/ije/dyab208] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/16/2021] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND Mendelian randomization has been previously used to estimate the effects of binary and ordinal categorical exposures-e.g. Type 2 diabetes or educational attainment defined by qualification-on outcomes. Binary and categorical phenotypes can be modelled in terms of liability-an underlying latent continuous variable with liability thresholds separating individuals into categories. Genetic variants influence an individual's categorical exposure via their effects on liability, thus Mendelian-randomization analyses with categorical exposures will capture effects of liability that act independently of exposure category. METHODS AND RESULTS We discuss how groups in which the categorical exposure is invariant can be used to detect liability effects acting independently of exposure category. For example, associations between an adult educational-attainment polygenic score (PGS) and body mass index measured before the minimum school leaving age (e.g. age 10 years), cannot indicate the effects of years in full-time education on this outcome. Using UK Biobank data, we show that a higher educational-attainment PGS is strongly associated with lower smoking initiation and higher odds of glasses use at age 15 years. These associations were replicated in sibling models. An orthogonal approach using the raising of the school leaving age (ROSLA) policy change found that individuals who chose to remain in education to age 16 years before the reform likely had higher liability to educational attainment than those who were compelled to remain in education to age 16 years after the reform, and had higher income, lower pack-years of smoking, higher odds of glasses use and lower deprivation in adulthood. These results suggest that liability to educational attainment is associated with health and social outcomes independently of years in full-time education. CONCLUSIONS Mendelian-randomization studies with non-continuous exposures should be interpreted in terms of liability, which may affect the outcome via changes in exposure category and/or independently.
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Affiliation(s)
- Laurence J Howe
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, University of Bristol, Bristol, UK
| | - Matthew Tudball
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, University of Bristol, Bristol, UK
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, University of Bristol, Bristol, UK
| | - Neil M Davies
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, University of Bristol, Bristol, UK
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
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23
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Walker VM, Vujkovic M, Carter AR, Davies NM, Udler MS, Levin MG, Davey Smith G, Voight BF, Gaunt TR, Damrauer SM. Separating the direct effects of traits on atherosclerotic cardiovascular disease from those mediated by type 2 diabetes. Diabetologia 2022; 65:790-799. [PMID: 35129650 PMCID: PMC8960614 DOI: 10.1007/s00125-022-05653-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Accepted: 11/22/2021] [Indexed: 12/31/2022]
Abstract
AIMS/HYPOTHESIS Type 2 diabetes and atherosclerotic CVD share many risk factors. This study aimed to systematically assess a broad range of continuous traits to separate their direct effects on coronary and peripheral artery disease from those mediated by type 2 diabetes. METHODS Our main analysis was a two-step Mendelian randomisation for mediation to quantify the extent to which the associations observed between continuous traits and liability to atherosclerotic CVD were mediated by liability to type 2 diabetes. To support this analysis, we performed several univariate Mendelian randomisation analyses to examine the associations between our continuous traits, liability to type 2 diabetes and liability to atherosclerotic CVD. RESULTS Eight traits were eligible for the two-step Mendelian randomisation with liability to coronary artery disease as the outcome and we found similar direct and total effects in most cases. Exceptions included fasting insulin and hip circumference where the proportion mediated by liability to type 2 diabetes was estimated as 56% and 52%, respectively. Six traits were eligible for the analysis with liability to peripheral artery disease as the outcome. Again, we found limited evidence to support mediation by liability to type 2 diabetes for all traits apart from fasting insulin (proportion mediated: 70%). CONCLUSIONS/INTERPRETATION Most traits were found to affect liability to atherosclerotic CVD independently of their relationship with liability to type 2 diabetes. These traits are therefore important for understanding atherosclerotic CVD risk regardless of an individual's liability to type 2 diabetes.
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Affiliation(s)
- Venexia M Walker
- MRC University of Bristol Integrative Epidemiology Unit, Bristol, UK.
- Bristol Medical School: Population Health Sciences, University of Bristol, Bristol, UK.
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
| | - Marijana Vujkovic
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Alice R Carter
- MRC University of Bristol Integrative Epidemiology Unit, Bristol, UK
- Bristol Medical School: Population Health Sciences, University of Bristol, Bristol, UK
| | - Neil M Davies
- MRC University of Bristol Integrative Epidemiology Unit, Bristol, UK
- Bristol Medical School: Population Health Sciences, University of Bristol, Bristol, UK
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Miriam S Udler
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Michael G Levin
- Division of Cardiovascular Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, USA
| | - George Davey Smith
- MRC University of Bristol Integrative Epidemiology Unit, Bristol, UK
- Bristol Medical School: Population Health Sciences, University of Bristol, Bristol, UK
| | - Benjamin F Voight
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Institute of Translational Medicine and Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Tom R Gaunt
- MRC University of Bristol Integrative Epidemiology Unit, Bristol, UK
- Bristol Medical School: Population Health Sciences, University of Bristol, Bristol, UK
| | - Scott M Damrauer
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
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24
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Morris DR, Jones GT, Holmes MV, Bown MJ, Bulbulia R, Singh TP, Golledge J. Genetic Predisposition to Diabetes and Abdominal Aortic Aneurysm: A Two Stage Mendelian Randomisation Study. Eur J Vasc Endovasc Surg 2022; 63:512-519. [PMID: 34916110 DOI: 10.1016/j.ejvs.2021.10.038] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2021] [Revised: 09/24/2021] [Accepted: 10/10/2021] [Indexed: 11/26/2022]
Abstract
OBJECTIVE Observational studies demonstrate an inverse association between type II diabetes and abdominal aortic aneurysm (AAA) for reasons that are unclear. The aim of this study was to clarify the causal association between type II diabetes predisposition and AAA using Mendelian randomisation. METHODS Effect estimates for single nucleotide polymorphisms (SNPs) associated with diabetes were obtained from the DIAbetes Meta-ANalysis of Trans-Ethnic association studies (DIAMANTE) consortium to construct a genetic instrumental variable. Corresponding effect estimates for associations of these SNPs with AAA were obtained from the International Aneurysm Consortium comprising six separate AAA genomewide association studies (4 972 cases and 99 858 controls). Mendelian randomisation estimates were calculated using inverse variance, weighted median, and MR-Egger methods, and compared against recently published observational estimates. RESULTS A genetic risk score was constructed from 206 SNPs associated with diabetes. All three Mendelian randomisation models showed no effect of genetic liability to diabetes and risk of AAA (inverse variance: odds ratio 1.04 per unit higher log odds, 95% 0.98 - 1.11, p = .19; MR-Egger slope p = .33; weighted median p = .50). Results were similar after excluding the TCF7L2 locus (inverse variance p = .075). Findings from the Mendelian randomisation analysis differed from previous observational reports of an inverse association (pdif < .001). CONCLUSION Lifelong genetic predisposition to diabetes does not appear to protect against AAA. These findings differ from traditional epidemiological studies showing an inverse association between diabetes and AAA, for reasons that remain unclear.
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Affiliation(s)
- Dylan R Morris
- Queensland Research Centre for Peripheral Vascular Disease, College of Medicine and Dentistry, James Cook University, Townsville, Queensland, Australia; The Department of Vascular and Endovascular Surgery, Townsville University Hospital, Townsville, Queensland, Australia
| | - Gregory T Jones
- Department of Surgical Sciences, University of Otago, Dunedin, New Zealand
| | - Michael V Holmes
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK; Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Matthew J Bown
- Department of Cardiovascular Sciences and National Institute of Health Research Leicester Biomedical Research Centre, University of Leicester, Leicester, UK
| | - Richard Bulbulia
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK; Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Tejas P Singh
- Queensland Research Centre for Peripheral Vascular Disease, College of Medicine and Dentistry, James Cook University, Townsville, Queensland, Australia; The Department of Vascular and Endovascular Surgery, Townsville University Hospital, Townsville, Queensland, Australia
| | - Jonathan Golledge
- Queensland Research Centre for Peripheral Vascular Disease, College of Medicine and Dentistry, James Cook University, Townsville, Queensland, Australia; The Department of Vascular and Endovascular Surgery, Townsville University Hospital, Townsville, Queensland, Australia.
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25
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Chen K, Zhuang Z, Shao C, Zheng J, Zhou Q, Dong E, Huang T, Tang YD. Roles of Cardiometabolic Factors in Mediating the Causal Effect of Type 2 Diabetes on Cardiovascular Diseases: A Two-Step, Two-Sample Multivariable Mendelian Randomization Study. Front Cardiovasc Med 2022; 9:813208. [PMID: 35282373 PMCID: PMC8909643 DOI: 10.3389/fcvm.2022.813208] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Accepted: 01/17/2022] [Indexed: 12/17/2022] Open
Abstract
ObjectiveThe objective of this study is to investigate the roles of cardiometabolic factors (including blood pressure, blood lipids, thyroid function, body mass, and insulin sensitivity) in mediating the causal effect of type 2 diabetes (T2DM) on cardiovascular disease (CVD) outcomes.DesignTwo-step, two-sample multivariable Mendelian randomization (MVMR) study.SettingInternational genome-wide association study (GWAS) consortia data.ExposureType 2 diabetes, blood pressure: systolic blood pressure (SBP), diastolic blood pressure (DBP); blood lipids: low-density lipoprotein (LDL), high-density lipoprotein (HDL), total cholesterol (TC), triglycerides (TG); thyroid function: hyperthyroidism, hypothyroidism; body mass index (BMI), waist-hip-ratio (WHR), and insulin sensitivity.Main OutcomesCardiovascular disease includes coronary heart disease (CHD), myocardial infarction (MI), and stroke.MethodsSummary-level data for exposures and main outcomes were extracted from GWAS consortia. We used two-sample MR to illustrate the causal effect of T2DM on CVD subtypes and regression-based MVMR to quantify the possible mediation effects of cardiometabolic factors on CVD.ResultsEach additional unit of log odds of T2DM increased 16% risk of CHD [odds ratio (OR): 1.16, 95% CI: 1.12–1.21], 15% risk of myocardial infarction (MI) (OR: 1.15, 95% CI: 1.10–1.20), and 10% risk of stroke (OR: 1.10, 95% CI: 1.06–1.13). In mediation analysis, SBP, DBP, and TG were found as main mediators, while the mediation effects of other cardiometabolic factors were not significant. The proportion of total effect of T2DM on CHD mediated by SBP, DBP, and TG was 16% (95% CI: 8–24%), 7% (95% CI: 1–13%) and 10% (95% CI: 2–18%), respectively. Mediation effect of SBP and DBP on MI and stroke, TG on MI was also prominent, while mediation effect of TG on stroke was not significant. The combined mediation effect of all the three mediators accounted for 29%, 26%, and 13% of the total effect of T2DM on CHD, MI, and stroke, respectively.ConclusionSystolic blood pressure, DBP, and TG mediate a substantial proportion of the causal effect of T2DM on CVD and thus interventions on these factors might reduce the considerable excess risk of CVD among patients with T2DM.
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Affiliation(s)
- Ken Chen
- Department of Cardiology, State Key Laboratory of Cardiovascular Disease, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Department of Cardiology, Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zhenhuang Zhuang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Chunli Shao
- Department of Cardiology, State Key Laboratory of Cardiovascular Disease, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Department of Cardiology, Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Department of Cardiology and Institute of Vascular Medicine, Peking University Third Hospital, Beijing, China
- Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, Beijing, China
| | - Jilin Zheng
- Department of Cardiology, State Key Laboratory of Cardiovascular Disease, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Department of Cardiology, Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Qing Zhou
- Department of Cardiology, State Key Laboratory of Cardiovascular Disease, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Department of Cardiology, Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Erdan Dong
- Department of Cardiology and Institute of Vascular Medicine, NHC Key Laboratory of Cardiovascular Molecular Biology and Regulatory Peptides, Beijing Key Laboratory of Cardiovascular Receptors Research, Peking University Third Hospital, Beijing, China
- Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, The Institute of Cardiovascular Sciences, Peking University, Beijing, China
| | - Tao Huang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, China
- Department of Global Health, School of Public Health, Peking University, Beijing, China
- Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education, Beijing, China
- Center for Intelligent Public Health, Institute for Artificial Intelligence, Peking University, Beijing, China
| | - Yi-Da Tang
- Department of Cardiology, State Key Laboratory of Cardiovascular Disease, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Department of Cardiology, Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Department of Cardiology and Institute of Vascular Medicine, Peking University Third Hospital, Beijing, China
- Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, Beijing, China
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Grace C, Hopewell JC, Watkins H, Farrall M, Goel A. Robust estimates of heritable coronary disease risk in individuals with type 2 diabetes. Genet Epidemiol 2022; 46:51-62. [PMID: 34672391 PMCID: PMC8983061 DOI: 10.1002/gepi.22434] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Revised: 08/12/2021] [Accepted: 10/04/2021] [Indexed: 11/21/2022]
Abstract
Type 2 diabetes (T2D) is an important heritable risk factor for coronary artery disease (CAD), the risk of both diseases being increased by metabolic syndrome (MS). With the availability of large-scale genome-wide association data, we aimed to elucidate the genetic burden of CAD risk in T2D predisposed individuals within the context of MS and their shared genetic architecture. Mendelian randomization (MR) analyses supported a causal relationship between T2D and CAD [odds ratio (OR) = 1.13 per log-odds unit 95% confidence interval (CI): 1.10-1.16; p = 1.59 × 10-17 ]. Simultaneously adjusting MR analyses for the effects of the T2D instrument including blood pressure, dyslipidaemia, and obesity attenuated the association between T2D and CAD (OR = 1.07, 95% CI: 1.04-1.11). Bayesian locus-overlap analysis identified 44 regions with the same causal variant underlying T2D and CAD genetic signals (FDR < 1%) at a posterior probability >0.7; five (MHC, LPL, ABO, RAI1 and MC4R) of these regions contain genome-wide significant (p < 5 × 10-8 ) associations for both traits. Given the small effect sizes observed in genome-wide association studies for complex diseases, even with 44 potential target regions, this has implications for the likely magnitude of CAD risk reduction that might be achievable by pure T2D therapies.
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Affiliation(s)
- Christopher Grace
- Division of Cardiovascular Medicine, Radcliffe Department of MedicineUniversity of OxfordOxfordUK
- Wellcome Centre for Human GeneticsUniversity of OxfordOxfordUK
| | - Jemma C. Hopewell
- Nuffield Department of Population HealthUniversity of OxfordOxfordUK
| | - Hugh Watkins
- Division of Cardiovascular Medicine, Radcliffe Department of MedicineUniversity of OxfordOxfordUK
- Wellcome Centre for Human GeneticsUniversity of OxfordOxfordUK
| | - Martin Farrall
- Division of Cardiovascular Medicine, Radcliffe Department of MedicineUniversity of OxfordOxfordUK
- Wellcome Centre for Human GeneticsUniversity of OxfordOxfordUK
| | - Anuj Goel
- Division of Cardiovascular Medicine, Radcliffe Department of MedicineUniversity of OxfordOxfordUK
- Wellcome Centre for Human GeneticsUniversity of OxfordOxfordUK
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27
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Doğruel H, Aydemir M, Balci MK. Management of diabetic foot ulcers and the challenging points: An endocrine view. World J Diabetes 2022; 13:27-36. [PMID: 35070057 PMCID: PMC8771264 DOI: 10.4239/wjd.v13.i1.27] [Citation(s) in RCA: 50] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Revised: 07/18/2021] [Accepted: 12/11/2021] [Indexed: 02/06/2023] Open
Abstract
Diabetic foot ulcers (DFU) are one of the most challenging complications of diabetes. Up to one-third of patients with diabetes mellitus (DM) may suffer from DFUs during their life. DFU is one of the leading causes of morbidity in patients with DM. The treatment period is challenging, and the recurrence rate of DFUs is high. Hence, establishing prevention strategies is the most important point to be emphasized. A multidisciplinary approach is necessary in the prevention and treatment of DFUs. Patients at risk should be identified, and prevention measures should be taken based on the risk category. Once a DFU is formed, the appropriate classification and evidence-based treatment interventions should be executed. Glycemic control, diagnosis and treatment of vascular disease, local wound care, diagnosis, and treatment of infection should be addressed along with the proper evaluation and management of general health status.
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Affiliation(s)
- Hakan Doğruel
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Akdeniz University Hospital, Konyaaltı 07059, Antalya, Turkey
| | - Mustafa Aydemir
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Akdeniz University Hospital, Konyaaltı 07059, Antalya, Turkey
| | - Mustafa Kemal Balci
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Akdeniz University Faculty of Medicine, Konyaaltı 07059, Antalya, Turkey
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28
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Fan HY, Huang YT, Chen YY, Hsu JB, Li HY, Su TC, Lin HJ, Chien KL, Chen YC. Systolic blood pressure as the mediator of the effect of early menarche on the risk of coronary artery disease: A Mendelian randomization study. Front Cardiovasc Med 2022; 9:1023355. [PMID: 36698922 PMCID: PMC9868731 DOI: 10.3389/fcvm.2022.1023355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Accepted: 12/19/2022] [Indexed: 01/11/2023] Open
Abstract
Background Menarche timing may not be directly associated with the risk of coronary artery disease (CAD). Therefore, we investigated the roles of metabolic factors in explaining the effect of age at menarche on CAD risk. Methods We identified women with age at menarche and CAD by using three analytical methods: Mendelian randomization (MR), logistic regression analysis, and Cox proportional hazard regression. The first two analyses were performed in the Taiwan Biobank (N = 71,923) study, and the last analysis was performed in the Chin-Shan Community Cardiovascular Cohort study (N = 1,598). We further investigated the role of metabolic factors in mediating the effect of age at menarche on CAD risk by using three complementary methods with mediation analyses. Results One standard deviation of earlier age at menarche was associated with a 2% higher CAD risk [odds ratio = 1.02, 95% confidence interval (CI) = 1.001-1.03] in the MR analysis, an 11% higher risk (odds ratio = 1.11, 95% CI = 1.02-1.21) in the logistic regression analysis, and a 57% higher risk (hazard ratio = 1.57, 95% CI = 1.12-2.19) in the Cox proportional hazard regression. All the analyses consistently supported the role of systolic blood pressure in mediating this effect. The MR results indicated that 29% (95% CI = 26%-32%) of the effect of genetically predicted earlier age at menarche on CAD risk was mediated by genetically predicted systolic blood pressure. Conclusion The results obtained using different analytical methods suggest that interventions aimed at lowering systolic blood pressure can reduce the cases of CAD attributable to earlier age at menarche.
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Affiliation(s)
- Hsien-Yu Fan
- Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan.,Department of Family Medicine, Taipei Medical University Hospital, Taipei Medical University, Taipei, Taiwan
| | - Yen-Tsung Huang
- Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan.,Institute of Statistical Science, Academia Sinica, Taipei, Taiwan.,Department of Mathematics, National Taiwan University, Taipei, Taiwan
| | - Yun-Yu Chen
- Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan.,Department of Medical Research, Taichung Veterans General Hospital, Taichung, Taiwan.,Cardiovascular Center, Taichung Veterans General Hospital, Taichung, Taiwan.,Heart Rhythm Center, Division of Cardiology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan.,Cardiovascular Research Center, School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Justin BoKai Hsu
- Department of Computer Science and Engineering, Yuan Ze University, Taoyuan, Taiwan
| | - Hung-Yuan Li
- Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
| | - Ta-Chen Su
- Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
| | - Hung-Ju Lin
- Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
| | - Kuo-Liong Chien
- Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan.,Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
| | - Yang-Ching Chen
- Department of Family Medicine, Taipei Medical University Hospital, Taipei Medical University, Taipei, Taiwan.,Department of Family Medicine, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan.,School of Nutrition and Health Sciences, College of Nutrition, Taipei Medical University, Taipei, Taiwan.,Graduate Institute of Metabolism and Obesity Sciences, Taipei Medical University, Taipei, Taiwan
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29
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Chen H, Qiao J, Wang T, Shao Z, Huang S, Zeng P. Assessing Causal Relationship Between Human Blood Metabolites and Five Neurodegenerative Diseases With GWAS Summary Statistics. Front Neurosci 2021; 15:680104. [PMID: 34955704 PMCID: PMC8695771 DOI: 10.3389/fnins.2021.680104] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2021] [Accepted: 11/22/2021] [Indexed: 11/13/2022] Open
Abstract
Background: Neurodegenerative diseases (NDDs) are the leading cause of disability worldwide while their metabolic pathogenesis is unclear. Genome-wide association studies (GWASs) offer an unprecedented opportunity to untangle the relationship between metabolites and NDDs. Methods: By leveraging two-sample Mendelian randomization (MR) approaches and relying on GWASs summary statistics, we here explore the causal association between 486 metabolites and five NDDs including Alzheimer’s Disease (AD), amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD), Parkinson’s disease (PD), and multiple sclerosis (MS). We validated our MR results with extensive sensitive analyses including MR-PRESSO and MR-Egger regression. We also performed linkage disequilibrium score regression (LDSC) and colocalization analyses to distinguish causal metabolite-NDD associations from genetic correlation and LD confounding of shared causal genetic variants. Finally, a metabolic pathway analysis was further conducted to identify potential metabolite pathways. Results: We detected 164 metabolites which were suggestively associated with the risk of NDDs. Particularly, 2-methoxyacetaminophen sulfate substantially affected ALS (OR = 0.971, 95%CIs: 0.961 ∼ 0.982, FDR = 1.04E-4) and FTD (OR = 0.924, 95%CIs: 0.885 ∼ 0.964, FDR = 0.048), and X-11529 (OR = 1.604, 95%CIs: 1.250 ∼ 2.059, FDR = 0.048) and X-13429 (OR = 2.284, 95%CIs: 1.457 ∼ 3.581, FDR = 0.048) significantly impacted FTD. These associations were further confirmed by the weighted median and maximum likelihood methods, with MR-PRESSO and the MR-Egger regression removing the possibility of pleiotropy. We also observed that ALS or FTD can alter the metabolite levels, including ALS and FTD on 2-methoxyacetaminophen sulfate. The LDSC and colocalization analyses showed that none of the identified associations could be driven by genetic correlation or confounding by LD with common causal loci. Multiple metabolic pathways were found to be involved in NDDs, such as “urea cycle” (P = 0.036), “arginine biosynthesis” (P = 0.004) on AD and “phenylalanine, tyrosine and tryptophan biosynthesis” (P = 0.046) on ALS. Conclusion: our study reveals robust bidirectional causal associations between servaral metabolites and neurodegenerative diseases, and provides a novel insight into metabolic mechanism for pathogenesis and therapeutic strategies of these diseases.
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Affiliation(s)
- Haimiao Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, China
| | - Jiahao Qiao
- Department of Epidemiology and Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, China
| | - Ting Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, China
| | - Zhonghe Shao
- Department of Epidemiology and Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, China
| | - Shuiping Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, China.,Center for Medical Statistics and Data Analysis, School of Public Health, Xuzhou Medical University, Xuzhou, China.,Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, China
| | - Ping Zeng
- Department of Epidemiology and Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, China.,Center for Medical Statistics and Data Analysis, School of Public Health, Xuzhou Medical University, Xuzhou, China.,Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, China
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30
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Lu H, Qiao J, Shao Z, Wang T, Huang S, Zeng P. A comprehensive gene-centric pleiotropic association analysis for 14 psychiatric disorders with GWAS summary statistics. BMC Med 2021; 19:314. [PMID: 34895209 PMCID: PMC8667366 DOI: 10.1186/s12916-021-02186-z] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Accepted: 11/10/2021] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Recent genome-wide association studies (GWASs) have revealed the polygenic nature of psychiatric disorders and discovered a few of single-nucleotide polymorphisms (SNPs) associated with multiple psychiatric disorders. However, the extent and pattern of pleiotropy among distinct psychiatric disorders remain not completely clear. METHODS We analyzed 14 psychiatric disorders using summary statistics available from the largest GWASs by far. We first applied the cross-trait linkage disequilibrium score regression (LDSC) to estimate genetic correlation between disorders. Then, we performed a gene-based pleiotropy analysis by first aggregating a set of SNP-level associations into a single gene-level association signal using MAGMA. From a methodological perspective, we viewed the identification of pleiotropic associations across the entire genome as a high-dimensional problem of composite null hypothesis testing and utilized a novel method called PLACO for pleiotropy mapping. We ultimately implemented functional analysis for identified pleiotropic genes and used Mendelian randomization for detecting causal association between these disorders. RESULTS We confirmed extensive genetic correlation among psychiatric disorders, based on which these disorders can be grouped into three diverse categories. We detected a large number of pleiotropic genes including 5884 associations and 2424 unique genes and found that differentially expressed pleiotropic genes were significantly enriched in pancreas, liver, heart, and brain, and that the biological process of these genes was remarkably enriched in regulating neurodevelopment, neurogenesis, and neuron differentiation, offering substantial evidence supporting the validity of identified pleiotropic loci. We further demonstrated that among all the identified pleiotropic genes there were 342 unique ones linked with 6353 drugs with drug-gene interaction which can be classified into distinct types including inhibitor, agonist, blocker, antagonist, and modulator. We also revealed causal associations among psychiatric disorders, indicating that genetic overlap and causality commonly drove the observed co-existence of these disorders. CONCLUSIONS Our study is among the first large-scale effort to characterize gene-level pleiotropy among a greatly expanded set of psychiatric disorders and provides important insight into shared genetic etiology underlying these disorders. The findings would inform psychiatric nosology, identify potential neurobiological mechanisms predisposing to specific clinical presentations, and pave the way to effective drug targets for clinical treatment.
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Affiliation(s)
- Haojie Lu
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Jiahao Qiao
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Zhonghe Shao
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Ting Wang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Shuiping Huang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
- Center for Medical Statistics and Data Analysis, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
- Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Ping Zeng
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
- Center for Medical Statistics and Data Analysis, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
- Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
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31
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Liu B, Mason AM, Sun L, Di Angelantonio E, Gill D, Burgess S. Genetically Predicted Type 2 Diabetes Mellitus Liability, Glycated Hemoglobin and Cardiovascular Diseases: A Wide-Angled Mendelian Randomization Study. Genes (Basel) 2021; 12:1644. [PMID: 34681038 PMCID: PMC8536164 DOI: 10.3390/genes12101644] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 10/13/2021] [Accepted: 10/17/2021] [Indexed: 11/17/2022] Open
Abstract
(1) Aim: To investigate the causal effects of T2DM liability and glycated haemoglobin (HbA1c) levels on various cardiovascular disease outcomes, both in the general population and in non-diabetic individuals specifically. (2) Methods: We selected 243 variants as genetic instruments for T2DM liability and 536 variants for HbA1c. Linear Mendelian randomization analyses were performed to estimate the associations of genetically-predicted T2DM liability and HbA1c with 12 cardiovascular disease outcomes in 367,703 unrelated UK Biobank participants of European ancestries. We performed secondary analyses in participants without diabetes (HbA1c < 6.5% with no diagnosed diabetes), and in participants without diabetes or pre-diabetes (HbA1c < 5.7% with no diagnosed diabetes). (3) Results: Genetically-predicted T2DM liability was positively associated (p < 0.004, 0.05/12) with peripheral vascular disease, aortic valve stenosis, coronary artery disease, heart failure, ischaemic stroke, and any stroke. Genetically-predicted HbA1c was positively associated with coronary artery disease and any stroke. Mendelian randomization estimates generally shifted towards the null when excluding diabetic and pre-diabetic participants from analyses. (4) Conclusions: This genetic evidence supports causal effects of T2DM liability and HbA1c on a range of cardiovascular diseases, suggesting that improving glycaemic control could reduce cardiovascular risk in a general population, with greatest benefit in individuals with diabetes.
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Affiliation(s)
- Bowen Liu
- Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; (B.L.); (A.M.M.); (L.S.); (E.D.A.)
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Amy M. Mason
- Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; (B.L.); (A.M.M.); (L.S.); (E.D.A.)
| | - Luanluan Sun
- Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; (B.L.); (A.M.M.); (L.S.); (E.D.A.)
| | - Emanuele Di Angelantonio
- Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; (B.L.); (A.M.M.); (L.S.); (E.D.A.)
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London W2 1PG, UK
- Genetics Department, Novo Nordisk Research Centre Oxford, Old Road Campus, Oxford OX3 7FZ, UK
- Clinical Pharmacology and Therapeutics Section, Institute of Medical and Biomedical Education and Institute for Infection and Immunity, St George’s, University of London, London SW17 0RE, UK
- Clinical Pharmacology Group, Pharmacy and Medicines Directorate, St George’s University Hospitals NHS Foundation Trust, London SW17 0QT, UK
| | - Stephen Burgess
- Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; (B.L.); (A.M.M.); (L.S.); (E.D.A.)
- Medical Research Council Biostatistics Unit, University of Cambridge, Cambridge CB2 0SR, UK
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32
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Fernandes Silva L, Vangipurapu J, Laakso M. The "Common Soil Hypothesis" Revisited-Risk Factors for Type 2 Diabetes and Cardiovascular Disease. Metabolites 2021; 11:metabo11100691. [PMID: 34677406 PMCID: PMC8540397 DOI: 10.3390/metabo11100691] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Revised: 09/21/2021] [Accepted: 10/07/2021] [Indexed: 12/12/2022] Open
Abstract
The prevalence and the incidence of type 2 diabetes (T2D), representing >90% of all cases of diabetes, are increasing rapidly worldwide. Identification of individuals at high risk of developing diabetes is of great importance, as early interventions might delay or even prevent full-blown disease. T2D is a complex disease caused by multiple genetic variants in interaction with lifestyle and environmental factors. Cardiovascular disease (CVD) is the major cause of morbidity and mortality. Detailed understanding of molecular mechanisms underlying in CVD events is still largely missing. Several risk factors are shared between T2D and CVD, including obesity, insulin resistance, dyslipidemia, and hyperglycemia. CVD can precede the development of T2D, and T2D is a major risk factor for CVD, suggesting that both conditions have common genetic and environmental antecedents and that they share “common soil”. We analyzed the relationship between the risk factors for T2D and CVD based on genetics and population-based studies with emphasis on Mendelian randomization studies.
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33
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Yun JS, Ko SH. Current trends in epidemiology of cardiovascular disease and cardiovascular risk management in type 2 diabetes. Metabolism 2021; 123:154838. [PMID: 34333002 DOI: 10.1016/j.metabol.2021.154838] [Citation(s) in RCA: 123] [Impact Index Per Article: 30.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Revised: 06/07/2021] [Accepted: 07/07/2021] [Indexed: 02/06/2023]
Abstract
With the advances in diabetes care, the trend of incident cardiovascular disease (CVD) in patients with type 2 diabetes mellitus (T2DM) has been decreasing over past decades. However, given that CVD is still a major cause of death in patients with diabetes and that the risk of CVD in patients with T2DM is more than twice that in those without DM, there are still considerable challenges to the prevention of CVD in diabetes. Accordingly, there have been several research efforts to decrease cardiovascular (CV) risk in T2DM. Large-scale genome-wide association studies (GWAS) and clinical cohort studies have investigated the effects of factors, such as genetic determinants, hypoglycaemia, and insulin resistance, on CVD and can account for the unexplained CV risk in T2DM. Lifestyle modification is a widely accepted cornerstone method to prevent CVD as the first-line strategy in T2DM. Recent reports from large CV outcome trials have proven the positive CV effects of sodium-glucose cotransporter-2 (SGLT-2) inhibitors and glucagon-like peptide-1 receptor agonists (GLP-1RAs) in patients with high CVD risk. Overall, current practice guidelines for the management of CVD in T2DM are moving from a glucocentric strategy to a more individualised patient-centred approach. This review will discuss the current epidemiologic trends of CVD in T2DM and the risk factors linking T2DM to CVD, including genetic contribution, hypoglycaemia, and insulin resistance, and proper care strategies, including lifestyle and therapeutic approaches.
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Affiliation(s)
- Jae-Seung Yun
- Division of Endocrinology and Metabolism, Department of Internal Medicine, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea
| | - Seung-Hyun Ko
- Division of Endocrinology and Metabolism, Department of Internal Medicine, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea.
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34
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Mohamed SH, Hassaan MMM, Ibrahim BA, Sabbah NA. PCSK9 E670G (rs505151) Variant and Coronary Artery Disease Risk Among Diabetics. Genet Test Mol Biomarkers 2021; 25:615-623. [PMID: 34550777 DOI: 10.1089/gtmb.2021.0010] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Background: Proprotein convertase subtilisin/kexin type 9 (PCSK9) is an enzyme in the family of proprotein convertases implicated in lipid metabolism and is a significant genetic risk factor in cardiovascular diseases among various populations. Aim of the Study: This study explored the correlation between the alleles of the rs505151 (E670G) locus of the PCSK9 gene and its expression levels with coronary artery disease (CAD) risk in Egyptian patients with type 2 diabetes mellitus (T2DM). Subjects and Methods: A case-control study was performed on 112 lean subjects compared to 100 T2DM patients without CAD and 84 T2DM patients with CAD to investigate the relationships among PCSK9 expression levels, the E670G (rs505151) gene variant, lipid concentrations, and CAD risk in an Egyptian diabetic population. A restriction fragment length polymorphism-polymerase chain reaction (PCR) assay was used to assess the gene polymorphism, and PCSK9 mRNA expression was determined by quantitative real-time PCR. Results: The prevalence of the E670G (rs505151) AG genotype in diabetics with CAD was significantly greater than the other two groups. The PCSK9 gene expression levels in diabetics with CAD were significantly greater than the other two groups. G allele carriers (AG+GG) had a higher relative PCSK9 expression than A allele carriers. Conclusion: PCSK9 relative expression levels and the E670G (rs505151) AG genotype are CAD risk factors among Egyptian diabetics and are linked positively to the atherogenic index of plasma.
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Affiliation(s)
- Samy H Mohamed
- Medical Biochemistry Department, and Faculty of Medicine, University of Zagazig, Zagazig, Egypt
| | - Mohamed M M Hassaan
- Internal Medicine Department, Faculty of Medicine, University of Zagazig, Zagazig, Egypt
| | - Basma A Ibrahim
- Medical Biochemistry Department, and Faculty of Medicine, University of Zagazig, Zagazig, Egypt
| | - Norhan A Sabbah
- Medical Biochemistry Department, and Faculty of Medicine, University of Zagazig, Zagazig, Egypt
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35
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Liang Y, Luo S, Schooling CM, Au Yeung SL. Genetically Predicted Fibroblast Growth Factor 23 and Major Cardiovascular Diseases, Their Risk Factors, Kidney Function, and Longevity: A Two-Sample Mendelian Randomization Study. Front Genet 2021; 12:699455. [PMID: 34367258 PMCID: PMC8343174 DOI: 10.3389/fgene.2021.699455] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Accepted: 06/21/2021] [Indexed: 12/26/2022] Open
Abstract
Introduction Fibroblast growth factor 23 (FGF23), a potential biomarker for kidney function, is related to cardiovascular disease (CVD) and diabetes, although it is unclear whether the relation is causal. This study evaluated the associations of genetically predicted FGF23 with major CVDs, their risk factors, kidney function, and longevity using Mendelian randomization (MR). Methods This is a two-sample MR study using summary statistics from large genome-wide association studies. Primary outcomes included coronary artery disease (CAD), myocardial infarction, heart failure, and atrial fibrillation. Secondary outcomes included cardiovascular risk factors, kidney function, and longevity. We used four single-nucleotide polymorphisms (SNPs) predicting FGF23, excluding rs2769071 in the ABO gene, which likely violates the MR exclusion-restriction assumption. We used inverse-variance weighted (IVW) as the primary statistical method to assess associations of FGF23 with the outcomes. Sensitivity analyses included weighted median (WM) and MR-Egger. We repeated the analyses including all five SNPs. Last, we validated the positive findings from the main analyses in a smaller study, i.e., FinnGen. Results Using IVW, genetically predicted higher FGF23 was inversely associated with risk of CAD [odds ratio (OR): 0.69 per logtransformed FGF23 (pg/ml) increase, 95% confidence interval (CI): 0.52–0.91] and type 2 diabetes mellitus (T2DM) (OR: 0.70, 95% CI: 0.52–0.96), but not with the other outcomes. The WM and MR-Egger estimates were directionally consistent. Conclusion This study suggests that genetically predicted higher FGF23 may be protective against CAD and T2DM. Future studies should explore the underlying mechanisms related to the potential protective effect of FGF23. FGF23 was unlikely a cause of poorer renal function.
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Affiliation(s)
- Ying Liang
- LKS Faculty of Medicine, School of Public Health, The University of Hong Kong, Hong Kong, China
| | - Shan Luo
- LKS Faculty of Medicine, School of Public Health, The University of Hong Kong, Hong Kong, China
| | - C Mary Schooling
- LKS Faculty of Medicine, School of Public Health, The University of Hong Kong, Hong Kong, China.,School of Public Health and Health Policy, City University of New York, New York, NY, United States
| | - Shiu Lun Au Yeung
- LKS Faculty of Medicine, School of Public Health, The University of Hong Kong, Hong Kong, China
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36
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Gill D, Zuber V, Dawson J, Pearson-Stuttard J, Carter AR, Sanderson E, Karhunen V, Levin MG, Wootton RE, Klarin D, Tsao PS, Tsilidis KK, Damrauer SM, Burgess S, Elliott P. Risk factors mediating the effect of body mass index and waist-to-hip ratio on cardiovascular outcomes: Mendelian randomization analysis. Int J Obes (Lond) 2021; 45:1428-1438. [PMID: 34002035 PMCID: PMC8236409 DOI: 10.1038/s41366-021-00807-4] [Citation(s) in RCA: 49] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Revised: 02/23/2021] [Accepted: 03/22/2021] [Indexed: 12/29/2022]
Abstract
BACKGROUND Higher body mass index (BMI) and waist-to-hip ratio (WHR) increase the risk of cardiovascular disease, but the extent to which this is mediated by blood pressure, diabetes, lipid traits, and smoking is not fully understood. METHODS Using consortia and UK Biobank genetic association summary data from 140,595 to 898,130 participants predominantly of European ancestry, Mendelian randomization mediation analysis was performed to investigate the degree to which systolic blood pressure (SBP), diabetes, lipid traits, and smoking mediated an effect of BMI and WHR on the risk of coronary artery disease (CAD), peripheral artery disease (PAD) and stroke. RESULTS The odds ratio of CAD per 1-standard deviation increase in genetically predicted BMI was 1.49 (95% CI 1.39 to 1.60). This attenuated to 1.34 (95% CI 1.24 to 1.45) after adjusting for genetically predicted SBP (proportion mediated 27%, 95% CI 3% to 50%), to 1.27 (95% CI 1.17 to 1.37) after adjusting for genetically predicted diabetes (41% mediated, 95% CI 18% to 63%), to 1.47 (95% CI 1.36 to 1.59) after adjusting for genetically predicted lipids (3% mediated, 95% -23% to 29%), and to 1.46 (95% CI 1.34 to 1.58) after adjusting for genetically predicted smoking (6% mediated, 95% CI -20% to 32%). Adjusting for all the mediators together, the estimate attenuated to 1.14 (95% CI 1.04 to 1.26; 66% mediated, 95% CI 42% to 91%). A similar pattern was observed when considering genetically predicted WHR as the exposure, and PAD or stroke as the outcome. CONCLUSIONS Measures to reduce obesity will lower the risk of cardiovascular disease primarily by impacting downstream metabolic risk factors, particularly diabetes and hypertension. Reduction of obesity prevalence alongside control and management of its mediators is likely to be most effective for minimizing the burden of obesity.
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Affiliation(s)
- Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
- Clinical Pharmacology and Therapeutics Section, Institute of Medical and Biomedical Education and Institute for Infection and Immunity, St George's, University of London, London, UK.
- Clinical Pharmacology Group, Pharmacy and Medicines Directorate, St George's University Hospitals NHS Foundation Trust, London, UK.
- Novo Nordisk Research Centre Oxford, Oxford, UK.
| | - Verena Zuber
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Medical Research Council Biostatistics Unit, University of Cambridge, Cambridge, UK
- Medical Research Council Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | - Jesse Dawson
- University of Glasgow, Institute of Cardiovascular and Medical Sciences, Glasgow, UK
| | - Jonathan Pearson-Stuttard
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Medical Research Council Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | - Alice R Carter
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Eleanor Sanderson
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Ville Karhunen
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Michael G Levin
- Division of Cardiovascular Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
| | - Robyn E Wootton
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- School of Psychological Science, University of Bristol, Bristol, UK
- National Institute for Health Research Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, UK
| | - Derek Klarin
- Malcom Randall VA Medical Center, Gainesville, FL, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Boston, MA, USA
- Division of Vascular Surgery and Endovascular Therapy, University of Florida School of Medicine, Gainesville, Fl, USA
| | - Philip S Tsao
- VA Palo Alto Health Care System, Livermore, CA, USA
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Konstantinos K Tsilidis
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece
| | - Scott M Damrauer
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Stephen Burgess
- Medical Research Council Biostatistics Unit, University of Cambridge, Cambridge, UK
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Medical Research Council Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- UK Dementia Research Institute at Imperial College London, London, UK
- Imperial Biomedical Research Centre, Imperial College London and Imperial College NHS Healthcare Trust, London, UK
- Health Data Research UK-London, London, UK
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Au Yeung SL, Borges MC, Lawlor DA, Schooling CM. Impact of lung function on cardiovascular diseases and cardiovascular risk factors: a two sample bidirectional Mendelian randomisation study. Thorax 2021; 77:164-171. [PMID: 34155093 DOI: 10.1136/thoraxjnl-2020-215600] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Revised: 04/12/2021] [Accepted: 04/19/2021] [Indexed: 01/12/2023]
Abstract
INTRODUCTION Observational studies suggested lung function is inversely associated with cardiovascular disease (CVD) although these studies could be confounded. We conducted a two sample Mendelian randomisation study using summary statistics from genome-wide association studies (GWAS) to clarify the role of lung function in CVD and its risk factors, and conversely the role of CVD in lung function. METHODS We obtained genetic instruments for forced expiratory volume in 1 s (FEV1: 260) and forced vital capacity (FVC: 320) from publicly available UK Biobank summary statistics (n=421 986) and applied to GWAS summary statistics for coronary artery disease (CAD) (n=184 305), stroke (n=446 696), atrial fibrillation (n=1 030 836) and heart failure (n=977 320) and cardiovascular risk factors. Inverse variance weighting was used to assess the impact of lung function on these outcomes, with various sensitivity analyses. Bidirectional Mendelian randomisation was used to assess reverse causation. RESULTS FEV1 and FVC were inversely associated with CAD (OR per SD increase, 0.72 (95% CI 0.63 to 0.82) and 0.70 (95%CI 0.62 to 0.78)), overall stroke (0.87 (95%CI 0.77 to 0.97), 0.90 (95% CI 0.82 to 1.00)) and some stroke subtypes. FEV1 and FVC were inversely associated with type 2 diabetes and systolic blood pressure. Sensitivity analyses produced similar findings although the association with CAD was attenuated after adjusting for height (eg, OR for 1SD FEV10.95 (0.75 to 1.19), but not for stroke or type 2 diabetes. There was no strong evidence for reverse causation. CONCLUSION Higher lung function likely protect against CAD and stroke.
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Affiliation(s)
- Shiu Lun Au Yeung
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong Special Adminstrative Region, China
| | - Maria Carolina Borges
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.,Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Debbie A Lawlor
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.,Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.,National Institute for Health Research Bristol Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust and University of Bristol, Bristol, UK
| | - C Mary Schooling
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong Special Adminstrative Region, China.,School of Public Health and Health Policy, City University of New York, New York, New York, USA
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Sundquist K, Johansson SE, Memon AA, Calling S, Ohlsson H, Szulkin R, Jimenez E, Sundquist J. Elucidating causal effects of type 2 diabetes on ischemic heart disease from observational data on middle-aged Swedish women: a triangular analytical approach. Sci Rep 2021; 11:12579. [PMID: 34131261 PMCID: PMC8206102 DOI: 10.1038/s41598-021-92071-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Accepted: 05/28/2021] [Indexed: 01/14/2023] Open
Abstract
The association between type 2 diabetes (T2D) and ischemic heart disease (IHD) is well established but the potential causal association needs further studying. In an attempt to elucidate the causal effect of T2D on IHD, we used three different analytical approaches in two different datasets. A well-defined cohort of 6047 women aged 50–59 years were included at baseline (1995 to 2000) and followed until 2015 for IHD. The median follow-up was 16.3 years. We used a Marginal Structural Cox model (MSM Cox) to account for time-varying exposure (time at onset of T2D) and for ten confounders (using inverse probability weighting, IPW). We also compared the MSM-Cox models with traditional Cox regression modelling in the cohort. Finally, we analyzed information on individuals from Swedish population-based registers with national coverage in a comprehensive co-relative design and extrapolated the results to MZ twins. The Hazard Ratio (HR) for IHD in relation to T2D at baseline and T2D occurring during the follow-up in the MSM Cox model weighted by IPW (based on the ten included confounders) was 1.43 (95% confidence interval [CI] 1.07–1.92). The corresponding HR from the traditional Cox regression model was of similar effect size. The average extrapolated MZ twin estimate from our co-relative model was 1.61 (95% CI 1.48–1.86). Our findings, based on a triangular approach, support the existence of a causal association between T2D and IHD and that preventive long-term measures in order to avoid or postpone IHD should include monitoring and treatment of both the T2D itself as well as other cardiovascular risk factors.
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Affiliation(s)
- Kristina Sundquist
- Center for Primary Health Care Research, Department of Clinical Sciences Malmö, Lund University, Lund, Region Skåne, Sweden
| | - Sven-Erik Johansson
- Center for Primary Health Care Research, Department of Clinical Sciences Malmö, Lund University, Lund, Region Skåne, Sweden
| | - Ashfaque A Memon
- Center for Primary Health Care Research, Department of Clinical Sciences Malmö, Lund University, Lund, Region Skåne, Sweden
| | - Susanna Calling
- Center for Primary Health Care Research, Department of Clinical Sciences Malmö, Lund University, Lund, Region Skåne, Sweden.
| | - Henrik Ohlsson
- Center for Primary Health Care Research, Department of Clinical Sciences Malmö, Lund University, Lund, Region Skåne, Sweden
| | | | - Eladio Jimenez
- Department of Preventive Medicine and Public Health, School of Medicine, University of Granada, Granada, Spain.,CIBERESP Spain, Chair of Teaching and Research in Family Medicine, SEMERGEN-University of Granada, Granada, Spain
| | - Jan Sundquist
- Center for Primary Health Care Research, Department of Clinical Sciences Malmö, Lund University, Lund, Region Skåne, Sweden
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Burgess S, Malik R, Liu B, Mason AM, Georgakis MK, Dichgans M, Gill D. Dose-response relationship between genetically proxied average blood glucose levels and incident coronary heart disease in individuals without diabetes mellitus. Diabetologia 2021; 64:845-849. [PMID: 33495845 PMCID: PMC7940279 DOI: 10.1007/s00125-020-05377-0] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Accepted: 11/19/2020] [Indexed: 11/17/2022]
Abstract
AIMS/HYPOTHESIS Our aim was to investigate the relationship between average blood glucose levels and incident CHD in individuals without diabetes mellitus. METHODS To investigate average blood glucose levels, we studied HbA1c as predicted by 40 variants previously shown to be associated with both type 2 diabetes and HbA1c. Linear and non-linear Mendelian randomisation analyses were performed to investigate associations with incident CHD risk in 324,830 European ancestry individuals from the UK Biobank without diabetes mellitus. RESULTS Every one mmol/mol increase in genetically proxied HbA1c was associated with an 11% higher CHD risk (HR 1.11, 95% CI 1.05, 1.18). The dose-response curve increased at all levels of HbA1c, and there was no evidence favouring a non-linear relationship over a linear one. CONCLUSIONS/INTERPRETATIONS In individuals without diabetes mellitus, lowering average blood glucose levels may reduce CHD risk in a dose-dependent way.
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Affiliation(s)
- Stephen Burgess
- Medical Research Council Biostatistics Unit, Cambridge Institute of Public Health, Cambridge, UK
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Rainer Malik
- Institute for Stroke and Dementia Research, University Hospital of Ludwig-Maximilians-University, Munich, Germany
| | - Bowen Liu
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Amy M Mason
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Marios K Georgakis
- Institute for Stroke and Dementia Research, University Hospital of Ludwig-Maximilians-University, Munich, Germany
| | - Martin Dichgans
- Institute for Stroke and Dementia Research, University Hospital of Ludwig-Maximilians-University, Munich, Germany
- Munich Cluster for Systems Neurology, Munich, Germany
- German Centre for Neurodegenerative Diseases, Munich, Germany
| | - Dipender Gill
- Clinical Pharmacology and Therapeutics Section, Institute of Medical and Biomedical Education and Institute for Infection and Immunity, St George's, University of London, London, UK.
- Clinical Pharmacology Group, Pharmacy and Medicines Directorate, St George's University Hospitals NHS Foundation Trust, London, UK.
- Novo Nordisk Research Centre Oxford, Old Road Campus, Oxford, UK.
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
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40
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Rachfal AW, Grant SFA, Schwartz SS. The Diabetes Syndrome - A Collection of Conditions with Common, Interrelated Pathophysiologic Mechanisms. Int J Gen Med 2021; 14:923-936. [PMID: 33776471 PMCID: PMC7987256 DOI: 10.2147/ijgm.s305156] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Accepted: 03/08/2021] [Indexed: 11/23/2022] Open
Abstract
The four basic pathophysiologic mechanisms which damage the β-cell within diabetes (ie, genetic and epigenetic changes, inflammation, an abnormal environment, and insulin resistance [IR]) also contribute to cell and tissue damage and elevate the risk of developing all typical diabetes-related complications. Genetic susceptibility to damage from abnormal external and internal environmental factors has been described including inflammation and IR. All these mechanisms can promote epigenetic changes, and in total, these pathophysiologic mechanisms interact and react with each other to cause damage to cells and tissues ultimately leading to disease. Importantly, these pathophysiologic mechanisms also serve to link other common conditions including cancer, dementia, psoriasis, atherosclerotic cardiovascular disease (ASCVD), nonalcoholic fatty liver disease (NAFLD), and nonalcoholic steatohepatitis (NASH). The "Diabetes Syndrome", an overarching group of interrelated conditions linked by these overlapping mechanisms, can be viewed as a conceptual framework that can facilitate understanding of the inter-relationships of superficially disparate conditions. Recognizing the association of the conditions within the Diabetes Syndrome due to common pathophysiologies has the potential to provide both benefit to the patient (eg, prevention, early detection, precision medicine) and to the advancement of medicine (eg, driving education, research, and dynamic decision-based medical practice).
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Affiliation(s)
| | - Struan F A Grant
- Center for Spatial and Functional Genomics, Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pediatrics, University of Pennsylvania, Perlman School of Medicine, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Perlman School of Medicine, Philadelphia, PA, USA
| | - Stanley S Schwartz
- Stanley Schwartz MD, LLC, Main Line Health System, Wynnewood, PA, USA
- University of Pennsylvania, Perlman School of Medicine, Philadelphia, PA, USA
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41
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Dash S, Paterson AD. Genetically determined lean mass and dietary response. Diabetes Obes Metab 2021; 23:661-663. [PMID: 33283425 DOI: 10.1111/dom.14275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2020] [Revised: 11/12/2020] [Accepted: 11/26/2020] [Indexed: 11/24/2022]
Abstract
Weight loss attenuates many obesity-related co-morbidities, but is difficult to sustain with dietary change. Dietary adherence, not macronutrient composition, is a better predictor of weight loss. Weight loss-induced endocrine changes promote food intake and increase energy efficiency, contributing to the difficulty with dietary adherence and weight regain. Macronutrient preference is partly genetically determined, suggesting that personalized dietary interventions might be more successful. In this issue, Li et al. report that a genetic risk score comprising the cumulative weighted effects of variants previously associated with increased lean mass is associated with increased satiety and weight loss 6 months after initiating a low- but not a high-fat diet. The effects were attenuated by 2 years. These findings suggest that genetic variants may influence response to specific diet. Further studies are necessary to assess whether genetically determined lean mass is causally associated with dietary response. Significant progress has recently been made in identifying additional genetic determinants of lean mass, which will enable such investigations and potentially inform future nutritional studies.
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Affiliation(s)
- Satya Dash
- Department of Medicine, University Health Network, Toronto, Ontario, Canada
- Banting & Best Diabetes Centre, University of Toronto, Toronto, Ontario, Canada
| | - Andrew D Paterson
- Banting & Best Diabetes Centre, University of Toronto, Toronto, Ontario, Canada
- Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada
- Divisions of Epidemiology and Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
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42
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Peters TM, Holmes MV, Richards JB, Palmer T, Forgetta V, Lindgren CM, Asselbergs FW, Nelson CP, Samani NJ, McCarthy MI, Mahajan A, Davey Smith G, Woodward M, O'Keeffe LM, Peters SAE. Sex Differences in the Risk of Coronary Heart Disease Associated With Type 2 Diabetes: A Mendelian Randomization Analysis. Diabetes Care 2021; 44:556-562. [PMID: 33277303 PMCID: PMC7818328 DOI: 10.2337/dc20-1137] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/14/2020] [Accepted: 10/21/2020] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Observational studies have demonstrated that type 2 diabetes is a stronger risk factor for coronary heart disease (CHD) in women compared with men. However, it is not clear whether this reflects a sex differential in the causal effect of diabetes on CHD risk or results from sex-specific residual confounding. RESEARCH DESIGN AND METHODS Using 270 single nucleotide polymorphisms (SNPs) for type 2 diabetes identified in a type 2 diabetes genome-wide association study, we performed a sex-stratified Mendelian randomization (MR) study of type 2 diabetes and CHD using individual participant data in UK Biobank (251,420 women and 212,049 men). Weighted median, MR-Egger, MR-pleiotropy residual sum and outlier, and radial MR from summary-level analyses were used for pleiotropy assessment. RESULTS MR analyses showed that genetic risk of type 2 diabetes increased the odds of CHD for women (odds ratio 1.13 [95% CI 1.08-1.18] per 1-log unit increase in odds of type 2 diabetes) and men (1.21 [1.17-1.26] per 1-log unit increase in odds of type 2 diabetes). Sensitivity analyses showed some evidence of directional pleiotropy; however, results were similar after correction for outlier SNPs. CONCLUSIONS This MR analysis supports a causal effect of genetic liability to type 2 diabetes on risk of CHD that is not stronger for women than men. Assuming a lack of bias, these findings suggest that the prevention and management of type 2 diabetes for CHD risk reduction is of equal priority in both sexes.
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Affiliation(s)
- Tricia M Peters
- Centre for Clinical Epidemiology, Lady Davis Institute for Medical Research, Montreal, Quebec, Canada
- Division of Endocrinology, Department of Medicine, Jewish General Hospital, McGill University, Montreal, Quebec, Canada
| | - Michael V Holmes
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, U.K
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K
- National Institute for Health Research, Oxford Biomedical Research Centre, Oxford University Hospital, Oxford, U.K
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, U.K
| | - J Brent Richards
- Centre for Clinical Epidemiology, Lady Davis Institute for Medical Research, Montreal, Quebec, Canada
- Division of Endocrinology, Department of Medicine, Jewish General Hospital, McGill University, Montreal, Quebec, Canada
| | - Tom Palmer
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, U.K
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, U.K
| | - Vincenzo Forgetta
- Centre for Clinical Epidemiology, Lady Davis Institute for Medical Research, Montreal, Quebec, Canada
| | - Cecilia M Lindgren
- Big Data Institute, Li Ka Shing Center for Health Information and Discovery, Oxford University, Oxford, U.K
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, U.K
- Program in Medical and Population Genetics, Broad Institute, Boston, MA
| | - Folkert W Asselbergs
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
- Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, U.K
- Health Data Research UK and Institute of Health Informatics, University College London, London, U.K
| | - Christopher P Nelson
- Department of Cardiovascular Sciences, University of Leicester, Leicester, U.K
- National Institute for Health Research Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, U.K
| | - Nilesh J Samani
- Department of Cardiovascular Sciences, University of Leicester, Leicester, U.K
- National Institute for Health Research Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, U.K
| | - Mark I McCarthy
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, U.K
- Oxford Centre for Diabetes, Endocrinology, and Metabolism, Churchill Hospital, University of Oxford, Oxford, U.K
- Oxford National Institute for Health Research Biomedical Research Centre, Oxford University Hospitals Trust, Oxford, U.K
| | - Anubha Mahajan
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, U.K
- Oxford Centre for Diabetes, Endocrinology, and Metabolism, Churchill Hospital, University of Oxford, Oxford, U.K
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, U.K
- School of Social and Community Medicine, University of Bristol, Bristol, U.K
| | - Mark Woodward
- George Institute for Global Health, University of Oxford, Oxford, U.K
- George Institute for Global Health, University of New South Wales, Sydney, New South Wales, Australia
- Department of Epidemiology, Johns Hopkins University, Baltimore, MD
| | - Linda M O'Keeffe
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, U.K
- School of Public Health, University College Cork, Cork, Ireland
| | - Sanne A E Peters
- George Institute for Global Health, University of Oxford, Oxford, U.K
- George Institute for Global Health, University of New South Wales, Sydney, New South Wales, Australia
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands
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Bell KJL, Loy C, Cust AE, Teixeira-Pinto A. Mendelian Randomization in Cardiovascular Research: Establishing Causality When There Are Unmeasured Confounders. Circ Cardiovasc Qual Outcomes 2021; 14:e005623. [PMID: 33397121 DOI: 10.1161/circoutcomes.119.005623] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Mendelian randomization is an epidemiological approach to making causal inferences using observational data. It makes use of the natural randomization that occurs in the generation of an individual's genetic makeup in a way that is analogous to the study design of a randomized controlled trial and uses instrumental variable analysis where the genetic variant(s) are the instrument (analogous to random allocation to treatment group in an randomized controlled trial). As with any instrumental variable, there are 3 assumptions that must be made about the genetic instrument: (1) it is associated (not necessarily causally) with the exposure (relevance condition); (2) it is associated with the outcome only through the exposure (exclusion restriction condition); and (3) it does not share a common cause with the outcome (ie, no confounders of the genetic instrument and outcome, independence condition). Using the example of type II diabetes and coronary artery disease, we demonstrate how the method may be used to investigate causality and discuss potential benefits and pitfalls. We conclude that although Mendelian randomization studies can usually not establish causality on their own, they may usefully contribute to the evidence base and increase our certainty about the effectiveness (or otherwise) of interventions to reduce cardiovascular disease.
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Affiliation(s)
| | - Clement Loy
- Westmead Hospital, Westmead, Australia, (C.L.)
| | | | - Armando Teixeira-Pinto
- School of Public Health, Faculty of Medicine and Health, The University of Sydney, Australia. Westmead Millennium Institute for Medical Research (A.T-P.)
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Gallerand A, Stunault MI, Merlin J, Guinamard RR, Yvan-Charvet L, Ivanov S. Myeloid Cell Diversity and Impact of Metabolic Cues during Atherosclerosis. IMMUNOMETABOLISM 2020; 2:immunometab20200028. [PMID: 39649554 PMCID: PMC7617020 DOI: 10.20900/immunometab20200028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/11/2024]
Abstract
Myeloid cells are key contributors to tissue, immune and metabolic homeostasis and their alteration fuels inflammation and associated disorders such as atherosclerosis. Conversely, in a classical chicken-and-egg situation, systemic and local metabolism, together with receptor-mediated activation, regulate intracellular metabolism and reprogram myeloid cell functions. Those regulatory loops are notable during the development of atherosclerotic lesions. Therefore, understanding the intricate metabolic mechanisms regulating myeloid cell biology could lead to innovative approaches to prevent and treat cardiovascular diseases. In this review, we will attempt to summarize the different metabolic factors regulating myeloid cell homeostasis and contribution to atherosclerosis, the most frequent cardiovascular disease.
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Affiliation(s)
- Alexandre Gallerand
- Mediterranean center of molecular medicine (C3M)-Université Côte d’Azur–INSERM U1065, Team 13, Nice, 06200, France
| | - Marion I. Stunault
- Mediterranean center of molecular medicine (C3M)-Université Côte d’Azur–INSERM U1065, Team 13, Nice, 06200, France
| | - Johanna Merlin
- Mediterranean center of molecular medicine (C3M)-Université Côte d’Azur–INSERM U1065, Team 13, Nice, 06200, France
| | - Rodolphe R. Guinamard
- Mediterranean center of molecular medicine (C3M)-Université Côte d’Azur–INSERM U1065, Team 13, Nice, 06200, France
| | - Laurent Yvan-Charvet
- Mediterranean center of molecular medicine (C3M)-Université Côte d’Azur–INSERM U1065, Team 13, Nice, 06200, France
| | - Stoyan Ivanov
- Mediterranean center of molecular medicine (C3M)-Université Côte d’Azur–INSERM U1065, Team 13, Nice, 06200, France
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Graves JS, Barcellos LF, Krupp L, Belman A, Shao X, Quach H, Hart J, Chitnis T, Weinstock-Guttman B, Aaen G, Benson L, Gorman M, Greenberg B, Lotze T, Soe M, Ness J, Rodriguez M, Rose J, Schreiner T, Tillema JM, Waldman A, Casper TC, Waubant E. Vitamin D genes influence MS relapses in children. Mult Scler 2020; 26:894-901. [PMID: 31081484 PMCID: PMC6851448 DOI: 10.1177/1352458519845842] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
OBJECTIVE The aim of this study was to determine whether a vitamin D genetic risk score (vitDGRS) is associated with 25-hydroxyvitamin D (25(OH)D) level and multiple sclerosis (MS) relapses in children. METHODS DNA samples were typed for single nucleotide polymorphisms (SNPs) from four genes previously identified to be associated with 25(OH)D levels. SNPs with strong associations with 25(OH)D after multiple comparison correction were used to create a genetic risk score (vitDGRS). Cox regression models tested associations of vitDGRS with relapse hazard. RESULTS Two independent SNPs within or near GC and NADSYN1/DHCR7 genes were strongly associated with 25(OH)D levels in the discovery cohort (n = 182) after Bonferroni correction. The vitDGRS of these SNPs explained 4.5% of the variance of 25(OH)D level after adjustment for genetic ancestry. Having the highest versus lowest vitDGRS was associated with 11 ng/mL lower 25(OH)D level (95% confidence interval (CI) = -17.5, -4.5, p = 0.001) in the discovery cohort. Adjusting for ancestry, sex, disease-modifying therapy (DMT), and HLA-DRB1*15 carrier status, the highest versus lowest vitDGRS was associated with 2.6-fold (95% CI = 1.37, 5.03, p = 0.004) and 2.0-fold (95% CI = 0.75, 5.20, p = 0.16) higher relapse hazard in the discovery and replication cohorts, respectively. CONCLUSION The vitDGRS identifies children at greater risk of relapse. These findings support a causal role for vitamin D in MS course.
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Affiliation(s)
- Jennifer S Graves
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Lisa F Barcellos
- School of Public Health, University of California, Berkeley, Berkeley, CA, USA
| | - Lauren Krupp
- Pediatric Multiple Sclerosis Center, New York University Langone Medical Center, New York, NY, USA
| | | | - Xiaorong Shao
- School of Public Health, University of California, Berkeley, Berkeley, CA, USA
| | - Hong Quach
- School of Public Health, University of California, Berkeley, Berkeley, CA, USA
| | - Janace Hart
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Tanuja Chitnis
- Partners Pediatric Multiple Sclerosis Center, Massachusetts General Hospital for Children, Boston, MA, USA
| | | | - Gregory Aaen
- Pediatric Multiple Sclerosis Center, Loma Linda University Children's Hospital, San Bernardino, CA, USA
| | - Leslie Benson
- Pediatric Multiple Sclerosis and Related Disorders Program, Boston Children's Hospital, Boston, MA, USA
| | - Mark Gorman
- Pediatric Multiple Sclerosis and Related Disorders Program, Boston Children's Hospital, Boston, MA, USA
| | | | - Timothy Lotze
- The Blue Bird Circle Clinic for Multiple Sclerosis, Texas Children's Hospital, Houston, TX, USA
| | - Mar Soe
- Pediatric MS & Demyelinating Disease Center, Washington University, St. Louis, MI, USA
| | - Jayne Ness
- Center for Pediatric-Onset Demyelinating Disease, Children's of Alabama, Birmingham, AL, USA
| | - Moses Rodriguez
- Pediatric Multiple Sclerosis Center, Mayo Clinic, Rochester, MA, USA
| | - John Rose
- Department of Neurology, The University of Utah, Salt Lake City, UT, USA
| | - Teri Schreiner
- Rocky Mountain MS Center, University of Colorado, Denver, Denver, CO, USA
| | | | - Amy Waldman
- Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - T Charles Casper
- Department of Pediatrics, The University of Utah, Salt Lake City, UT, USA
| | - Emmanuelle Waubant
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
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Abstract
Diabetes mellitus is a major risk factor for coronary heart disease (CHD). The major form of diabetes mellitus is type 2 diabetes mellitus (T2D), which is thus largely responsible for the CHD association in the general population. Recent years have seen major advances in the genetics of T2D, principally through ever-increasing large-scale genome-wide association studies. This article addresses the question of whether this expanding knowledge of the genomics of T2D provides insight into the etiologic relationship between T2D and CHD. We will investigate this relationship by reviewing the evidence for shared genetic loci between T2D and CHD; by examining the formal testing of this interaction (Mendelian randomization studies assessing whether T2D is causal for CHD); and then turn to the implications of this genetic relationship for therapies for CHD, for therapies for T2D, and for therapies that affect both. In conclusion, the growing knowledge of the genetic relationship between T2D and CHD is beginning to provide the promise for improved prevention and treatment of both disorders.
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Affiliation(s)
- Mark O. Goodarzi
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Jerome I. Rotter
- Institute for Translational Genomics and Population Sciences and Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
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Yvan-Charvet L, Ivanov S. Metabolic Reprogramming of Macrophages in Atherosclerosis: Is It All about Cholesterol? J Lipid Atheroscler 2020; 9:231-242. [PMID: 32821733 PMCID: PMC7379089 DOI: 10.12997/jla.2020.9.2.231] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2019] [Revised: 01/16/2020] [Accepted: 02/11/2020] [Indexed: 12/20/2022] Open
Abstract
Hypercholesterolemia contributes to the chronic inflammatory response during the progression of atherosclerosis, in part by favoring cholesterol loading in macrophages and other immune cells. However, macrophages encounter a substantial amount of other lipids and nutrients after ingesting atherogenic lipoprotein particles or clearing apoptotic cells, increasing their metabolic load and impacting their behavior during atherosclerosis plaque progression. This review examines whether and how fatty acids and glucose shape the cellular metabolic reprogramming of macrophages in atherosclerosis to modulate the onset phase of inflammation and the later resolution stage, in which the balance is tipped toward tissue repair.
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Affiliation(s)
- Laurent Yvan-Charvet
- Institut National de la Santé et de la Recherche Médicale (Inserm) U1065, Université Côte d'Azur, Centre Méditerranéen de Médecine Moléculaire (C3M), Atip-Avenir, Fédération Hospitalo-Universitaire (FHU) Oncoage, Nice, France
| | - Stoyan Ivanov
- Institut National de la Santé et de la Recherche Médicale (Inserm) U1065, Université Côte d'Azur, Centre Méditerranéen de Médecine Moléculaire (C3M), Atip-Avenir, Fédération Hospitalo-Universitaire (FHU) Oncoage, Nice, France
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48
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Osman W, Hassoun A, Jelinek HF, Almahmeed W, Afandi B, Tay GK, Alsafar H. Genetics of type 2 diabetes and coronary artery disease and their associations with twelve cardiometabolic traits in the United Arab Emirates population. Gene 2020; 750:144722. [PMID: 32360841 DOI: 10.1016/j.gene.2020.144722] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Revised: 04/18/2020] [Accepted: 04/29/2020] [Indexed: 01/26/2023]
Abstract
BACKGROUND The United Arab Emirates (UAE) population has a high rate of type 2 diabetes mellitus (T2DM) and other metabolic risk factors for coronary artery disease (CAD). Previous studies have indicated strong genetic associations between T2DM and CAD. The objective of this study was to replicate previously reported significant genetic associations for T2DM and CAD which were in a genome-wide significance level in a cohort from the Arab population of the UAE, and to investigate the associations of these loci with twelve cardiometabolic traits that may influence the development of T2DM and CAD. METHODS A total of nine hundreds and fourteen Emiratis were recruited to this study to investigate associations of 101 loci for T2DM (422 patients and 455 controls), and 53 loci for CAD (160 patients and 245 controls), using logistic regression models which incorporating possible confounding factors. Results are presented using odds ratios with their corresponding 95% confidence intervals and p-values. Linear regression models, which included possible covariates were applied to determine any associations between the T2DM and CAD reported loci with the twelve cardiometabolic traits and results were presented as effect sizes (beta), standard errors, and p-values. Furthermore, the overall risks for all the loci found to be associated with T2DM and CAD were determined using the cumulative effects of the risk alleles. For those found to be associated with the twelve cardiometabolic traits, risks were determined using calculations of their polygenic risk scores. RESULTS The mean age of the T2DM group was 61.5 ± 11.3 and of the CAD group was 66.2 ± 9.3 years. The prevalence of most of the cardiovascular disease risk factors in this cohort were high: mean body mass index (BMI) = 29.4, T2DM (51.9%), hypertension (60.9%), dyslipidemia (68.8%), and smoking (47.9%). All individuals who were tested for CAD (n = 405) also had a diagnosis of T2DM. The highest association variant for T2DM was in SNP rs1977833 in HHEX (p = 0.0016, OR = 0.56 for allele A), which is a multi-ethnic locus for T2DM. The strongest association with CAD was detected with SNP rs264 in LPL, which encodes lipoprotein lipase (p = 0.009, OR = 1.96 for allele A). For the cardiometabolic traits analyses, most notable associations were those of FTO with BMI and waist circumference; ABO with height; KCNK16 with diastolic blood pressure; PROX1-AS1, GCKR, and MIR129-LEP with fasting blood glucose; random blood glucose with ZEB2 and THADA; HbA1c levels with TLE1 and FAM99B loci; HDL-cholesterol levels with BRAF; and triglyceride levels with ZEB2. Furthermore, accumulation of risk alleles and polygenic scores of the associated loci was clearly associated with increased risks for all tested diseases and traits in this cohort. CONCLUSIONS The present study highlighted many known genetic loci, which are linked to T2DM and CAD and their associations with major cardiometabolic traits in Arab descendants. We confirmed that some loci are associated with T2DM, CAD, and metabolic traits independently of the ethnic background, with a novel association also detected between height and ABO.
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Affiliation(s)
- Wael Osman
- College of Arts and Sciences, Khalifa University, Abu Dhabi, United Arab Emirates; Khalifa University Center for Biotechnology, Abu Dhabi, United Arab Emirates
| | - Ahmed Hassoun
- Dubai Diabetes Centre, Dubai Health Authority, Dubai, United Arab Emirates
| | - Herbert F Jelinek
- Clinical Medicine, Macquarie University, Sydney, Australia; School of Community Health, Charles Sturt University, Albury, Australia
| | - Wael Almahmeed
- Heart and Vascular Institute, Cleveland Clinic, Abu Dhabi, United Arab Emirates; Institute of Cardiac Science, Sheikh Khalifa Medical City, Abu Dhabi, United Arab Emirates
| | - Bachar Afandi
- Endocrine Diabetes Center, Tawam Hospital, SEHA, Al-Ain, United Arab Emirates
| | - Guan K Tay
- School of Health and Medical Sciences, Edith Cowan University, Australia; School of Psychiatry and Clinical Neurosciences, University of Western Australia, Australia
| | - Habiba Alsafar
- Khalifa University Center for Biotechnology, Abu Dhabi, United Arab Emirates; Department of Biomedical Engineering, Khalifa University, United Arab Emirates; College of Medicine and Health Sciences, Khalifa University, United Arab Emirates.
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49
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Goodarzi MO, Palmer ND, Cui J, Guo X, Chen YDI, Taylor KD, Raffel LJ, Wagenknecht LE, Buchanan TA, Hsueh WA, Rotter JI. Classification of Type 2 Diabetes Genetic Variants and a Novel Genetic Risk Score Association With Insulin Clearance. J Clin Endocrinol Metab 2020; 105:dgz198. [PMID: 31714576 PMCID: PMC7059988 DOI: 10.1210/clinem/dgz198] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Accepted: 11/11/2019] [Indexed: 12/16/2022]
Abstract
CONTEXT Genome-wide association studies have identified more than 450 single nucleotide polymorphisms (SNPs) for type 2 diabetes (T2D). OBJECTIVE To facilitate use of these SNPs in future genetic risk score (GRS)-based analyses, we aimed to classify the SNPs based on physiology. We also sought to validate GRS associations with insulin-related traits in deeply phenotyped Mexican Americans. DESIGN, SETTING, AND PARTICIPANTS A total of 457 T2D SNPs from the literature were assigned physiologic function based on association studies and cluster analyses. All SNPs (All-GRS), beta-cell (BC-GRS), insulin resistance (IR-GRS), lipodystrophy (Lipo-GRS), and body mass index plus lipids (B + L-GRS) were evaluated for association with diabetes and indices of insulin secretion (from oral glucose tolerance test), insulin sensitivity and insulin clearance (from euglycemic clamp), and adiposity and lipid markers in 1587 Mexican Americans. RESULTS Of the 457 SNPs, 52 were classified as BC, 30 as IR, 12 as Lipo, 12 as B + L, whereas physiologic function of 351 was undefined. All-GRS was strongly associated with T2D. Among nondiabetic Mexican Americans, BC-GRS was associated with reduced insulinogenic index, IR-GRS was associated with reduced insulin sensitivity, and Lipo-GRS was associated with reduced adiposity. B + L-GRS was associated with increased insulin clearance. The latter did not replicate in an independent cohort wherein insulin clearance was assessed by a different method. CONCLUSIONS Supporting their utility, BC-GRS, IR-GRS, and Lipo-GRS, based on SNPs discovered largely in Europeans, exhibited expected associations in Mexican Americans. The novel association of B + L-GRS with insulin clearance suggests that impaired ability to reduce insulin clearance in compensation for IR may play a role in the pathogenesis of T2D. Whether this applies to other ethnic groups remains to be determined.
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Affiliation(s)
- Mark O Goodarzi
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California, US
| | - Nicholette D Palmer
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, US
| | - Jinrui Cui
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California, US
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, California, US
| | - Yii-Der I Chen
- Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, California, US
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, California, US
| | - Leslie J Raffel
- Division of Genetic and Genomic Medicine, Department of Pediatrics, University of California, Irvine, US
| | - Lynne E Wagenknecht
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, US
| | - Thomas A Buchanan
- Department of Physiology and Biophysics and Department of Medicine, Keck School of Medicine of USC, Los Angeles, California, US
| | - Willa A Hsueh
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Wexner Medical Center, The Ohio State University, Columbus, US
| | - Jerome I Rotter
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, US
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50
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Chen Z, Bai Y, Long X, Luo Q, Wen Z, Li Y, Huang S, Yan Y, Mo Z. Effects of Adiponectin on T2DM and Glucose Homeostasis: A Mendelian Randomization Study. Diabetes Metab Syndr Obes 2020; 13:1771-1784. [PMID: 32547139 PMCID: PMC7250315 DOI: 10.2147/dmso.s248352] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/04/2020] [Accepted: 04/19/2020] [Indexed: 12/16/2022] Open
Abstract
PURPOSE The associations of adiponectin with type 2 diabetes mellitus (T2DM), glucose homeostasis (including β-cell function index (HOMA-β), insulin resistance (HOMA-IR), fasting insulin (FI) and fasting glucose (FG)) have reported in epidemiological studies. However, the previous observational studies are prone to biases, such as reverse causation and residual confounding factors. Herein, a Mendelian Randomization (MR) study was conducted to determine whether causal effects exist among them. MATERIALS AND AND METHODS Two-sample MR analyses and multiple sensitivity analyses were performed using the summary data from the ADIPOGen consortium, MAGIC Consortium, and a meta-analysis of GWAS with a considerable sample of T2DM (62,892 cases and 596,424 controls of European ancestry). We got eight valid genetic variants to predict the causal effect among adiponectin and T2DM and glucose homeostasis after excluding the probable invalid or pleiotropic variants. RESULTS Adiponectin was not associated with T2DM (odds ratio (OR) = 1.004; 95% confidence interval (CI): 0.740, 1.363) when using MR Egger after removing the invalid SNPs, and the results were consistent when using the other four methods. Similar results existed among adiponectin and HOMA-β, HOMA-IR, FI, FG. CONCLUSION Our MR study revealed that adiponectin had no causal effect on T2DM and glucose homeostasis and that the associations among them in observational studies may be due to confounding factors.
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Affiliation(s)
- Zefeng Chen
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning530021, Guangxi, People’s Republic of China
- Guangxi Key Laboratory for Genomic and Personalized Medicine, Nanning530021, Guangxi, People’s Republic of China
- Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Nanning530021, Guangxi, People’s Republic of China
- Guangxi Key Laboratory of Colleges and Universities, Nanning530021, Guangxi, People’s Republic of China
- School of Public Health, Guangxi Medical University, Nanning530021, Guangxi, People’s Republic of China
| | - Yulan Bai
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning530021, Guangxi, People’s Republic of China
- Guangxi Key Laboratory for Genomic and Personalized Medicine, Nanning530021, Guangxi, People’s Republic of China
- Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Nanning530021, Guangxi, People’s Republic of China
- Guangxi Key Laboratory of Colleges and Universities, Nanning530021, Guangxi, People’s Republic of China
- School of Public Health, Guangxi Medical University, Nanning530021, Guangxi, People’s Republic of China
| | - Xinyang Long
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning530021, Guangxi, People’s Republic of China
- Guangxi Key Laboratory for Genomic and Personalized Medicine, Nanning530021, Guangxi, People’s Republic of China
- Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Nanning530021, Guangxi, People’s Republic of China
- Guangxi Key Laboratory of Colleges and Universities, Nanning530021, Guangxi, People’s Republic of China
- School of Public Health, Guangxi Medical University, Nanning530021, Guangxi, People’s Republic of China
| | - Qianqian Luo
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning530021, Guangxi, People’s Republic of China
- Guangxi Key Laboratory for Genomic and Personalized Medicine, Nanning530021, Guangxi, People’s Republic of China
- Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Nanning530021, Guangxi, People’s Republic of China
- Guangxi Key Laboratory of Colleges and Universities, Nanning530021, Guangxi, People’s Republic of China
- School of Public Health, Guangxi Medical University, Nanning530021, Guangxi, People’s Republic of China
| | - Zheng Wen
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning530021, Guangxi, People’s Republic of China
- Guangxi Key Laboratory for Genomic and Personalized Medicine, Nanning530021, Guangxi, People’s Republic of China
- Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Nanning530021, Guangxi, People’s Republic of China
- Guangxi Key Laboratory of Colleges and Universities, Nanning530021, Guangxi, People’s Republic of China
- School of Public Health, Guangxi Medical University, Nanning530021, Guangxi, People’s Republic of China
| | - Yuanfan Li
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning530021, Guangxi, People’s Republic of China
- Guangxi Key Laboratory for Genomic and Personalized Medicine, Nanning530021, Guangxi, People’s Republic of China
- Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Nanning530021, Guangxi, People’s Republic of China
- Guangxi Key Laboratory of Colleges and Universities, Nanning530021, Guangxi, People’s Republic of China
- School of Public Health, Guangxi Medical University, Nanning530021, Guangxi, People’s Republic of China
| | - Shengzhu Huang
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning530021, Guangxi, People’s Republic of China
- Guangxi Key Laboratory for Genomic and Personalized Medicine, Nanning530021, Guangxi, People’s Republic of China
- Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Nanning530021, Guangxi, People’s Republic of China
- Guangxi Key Laboratory of Colleges and Universities, Nanning530021, Guangxi, People’s Republic of China
- School of Public Health, Guangxi Medical University, Nanning530021, Guangxi, People’s Republic of China
| | - Yunkun Yan
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning530021, Guangxi, People’s Republic of China
- Guangxi Key Laboratory for Genomic and Personalized Medicine, Nanning530021, Guangxi, People’s Republic of China
- Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Nanning530021, Guangxi, People’s Republic of China
- Guangxi Key Laboratory of Colleges and Universities, Nanning530021, Guangxi, People’s Republic of China
- School of Public Health, Guangxi Medical University, Nanning530021, Guangxi, People’s Republic of China
| | - Zengnan Mo
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning530021, Guangxi, People’s Republic of China
- Guangxi Key Laboratory for Genomic and Personalized Medicine, Nanning530021, Guangxi, People’s Republic of China
- Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Nanning530021, Guangxi, People’s Republic of China
- Guangxi Key Laboratory of Colleges and Universities, Nanning530021, Guangxi, People’s Republic of China
- Institute of Urology and Nephrology, First Affiliated Hospital of Guangxi Medical University, Nanning530021, Guangxi, People’s Republic of China
- Correspondence: Zengnan Mo Center for Genomic and Personalized Medicine, Guangxi Medical University, 22 Shuangyong Road, Nanning530021, Guangxi, People’s Republic of ChinaTel +86771-5353342 Email
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