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Naigaonkar A, Dadachanji R, Kumari M, Mukherjee S. Insight into metabolic dysregulation of polycystic ovary syndrome utilizing metabolomic signatures: a narrative review. Crit Rev Clin Lab Sci 2025; 62:85-112. [PMID: 39697160 DOI: 10.1080/10408363.2024.2430775] [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: 04/22/2024] [Revised: 07/15/2024] [Accepted: 11/12/2024] [Indexed: 12/20/2024]
Abstract
Polycystic ovary syndrome (PCOS) is a complex multifactorial endocrinopathy affecting reproductive aged women globally, whose presentation is strongly influenced by genetic makeup, ethnic, and geographic diversity leaving these affected women substantially predisposed to reproductive and metabolic perturbations. Sophisticated techniques spanning genomics, proteomics, epigenomics, and transcriptomics have been harnessed to comprehensively understand the enigmatic pathophysiology of PCOS, however, conclusive markers for PCOS are still lacking today. Metabolomics represents a paradigm shift in biotechnological advances enabling the simultaneous identification and quantification of metabolites and the use of this approach has added yet another dimension to help unravel the strong metabolic component of PCOS. Reports dissecting the metabolic signature of PCOS have revealed disparate levels of metabolites such as pyruvate, lactate, triglycerides, free fatty acids, carnitines, branched chain and essential amino acids, and steroid intermediates in major biological compartments. These metabolites have been shown to be altered in women with PCOS overall, after phenotypic subgrouping, in animal models of PCOS, and also following therapeutic intervention. This review seeks to supplement previous reviews by highlighting the aforementioned aspects and to provide easy, coherent and elementary access to significant findings and emerging trends. This will in turn help to delineate the metabolic plot in women with PCOS in various biological compartments including plasma, urine, follicular microenvironment, and gut. This may pave the way to design additional studies on the quest of unraveling the etiology of PCOS and delving into novel biomarkers for its diagnosis, prognosis and management.
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Affiliation(s)
- Aalaap Naigaonkar
- Department of Molecular Endocrinology, National Institute for Research in Reproductive and Child Health, Indian Council of Medical Research, Mumbai, India
| | - Roshan Dadachanji
- Department of Molecular Endocrinology, National Institute for Research in Reproductive and Child Health, Indian Council of Medical Research, Mumbai, India
| | - Manisha Kumari
- Department of Molecular Endocrinology, National Institute for Research in Reproductive and Child Health, Indian Council of Medical Research, Mumbai, India
| | - Srabani Mukherjee
- Department of Molecular Endocrinology, National Institute for Research in Reproductive and Child Health, Indian Council of Medical Research, Mumbai, India
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Naqvi I, Bandyopadhyay A, Panda A, Hareramadas B. Polycystic Ovarian Syndrome: A Review of Multi-omics Analyses. Reprod Sci 2025; 32:618-646. [PMID: 39875694 DOI: 10.1007/s43032-025-01789-8] [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: 03/27/2024] [Accepted: 01/09/2025] [Indexed: 01/30/2025]
Abstract
Polycystic Ovary Syndrome (PCOS) is among the most prevalent endocrinological abnormalities of young females, posing a grave public health challenge to the society. The objective of the present literature review is to analyze the enormous amount of information available by way of numerous multi-omic studies, and to explore a meaningful relationship between various factors such as genetic, proteomic, environmental etc. to understand the multifactorial metabolic disorder in a proper manner. Detailed literature search was done in various science article repositories and biomedical databases such as PubMed, Google Scholar, BioMed Central, Embase etc. by using several keywords in whole gamut of combinations. PCOS is a heritable disease. It manifests as a result of a combination of several intricately inter-linked symptoms such as anovulation, obesity, type II diabetes, hyperandrogenism, polycystic ovaries etc., the last one being the main manifestation of the disease, thus leading to infertility among several other complications. Such a multifactorial metabolic disorder with extreme symptomatic heterogeneity cannot be fully explained solely based on symptoms or genetic variations; thus, giving some space of thought to other factors such as epigenetic, microbiomic factors etc. playing a role in the causation of the disease. The present scientific survey of literature extensively reviews various aspects of PCOS by critically looking into the vast multi-omic data, and concluded with suggesting treatment options as well as lifestyle changes required to deal with the psychological/ emotional impacts of the condition on affected women.
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Affiliation(s)
- Ilmas Naqvi
- Department of Zoology, Zakir Husain Delhi College (University of Delhi), J.L.N. Marg, New Delhi, 110002, India
| | | | - Amisha Panda
- Lab. No. 115, Department of Zoology, University of Delhi, Delhi, 110007, India
| | - B Hareramadas
- Department of Zoology, Zakir Husain Delhi College (University of Delhi), J.L.N. Marg, New Delhi, 110002, India.
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Cheng S, Huang M, Liu S, Yang M. Bisphenol F and bisphenol S induce metabolic perturbations in human ovarian granulosa cells. ARAB J CHEM 2024; 17:105904. [DOI: 10.1016/j.arabjc.2024.105904] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/01/2024] Open
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Xu Y, Zhou Z, Zhang G, Yang Z, Shi Y, Jiang Z, Liu Y, Chen H, Huang H, Zhang Y, Pan J. Metabolome implies increased fatty acid utilization and histone methylation in the follicles from hyperandrogenic PCOS women. J Nutr Biochem 2024; 125:109548. [PMID: 38104867 DOI: 10.1016/j.jnutbio.2023.109548] [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: 07/10/2023] [Revised: 11/21/2023] [Accepted: 12/11/2023] [Indexed: 12/19/2023]
Abstract
Well-balanced metabolism is essential for the high-quality of oocytes, and metabolic fluctuations of follicular microenvironment potentially encourage functional changes in follicle cells, ultimately impacting the developmental potential of oocytes. Here, the global metabolomic profiles of follicular fluid from PCOS women with ovarian hyperandrogenism and nonhyperandrogenism were depicted by untargeted metabolome and transcriptome. In parallel, functional methods were employed to evaluate the possible impact of dysregulated metabolites on oocyte and embryo development. Our findings demonstrated that PCOS women exhibited distinct metabolic features in follicles, such as the increase in fatty acid utilization and the downregulation in amino acid metabolism. And intrafollicular androgen levels were positively correlated with contents of multiple fatty acids, suggesting androgen as one of the contributing factors to the metabolic abnormalities in PCOS follicles. Moreover, we further demonstrated that elevated levels of α-linolenic acid and H3K27me3 could hinder oocyte maturation, fertilization, and early embryo development. Hopefully, our data serve as a broad resource on the metabolic abnormalities of PCOS follicles, and advances in the relevant knowledge will allow the identification of biomarkers that predict the progression of PCOS and its poor pregnancy outcomes.
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Affiliation(s)
- Yue Xu
- Obstetrics and Gynecology Hospital, Institute of Reproduction and Development, Fudan University, Shanghai, China; Shanghai Key Laboratory of Reproduction and Development, Shanghai, China; Research Units of Embryo Original Diseases, Chinese Academy of Medical Sciences (No. 2019RU056), Shanghai, China
| | - Zhiyang Zhou
- Obstetrics and Gynecology Hospital, Institute of Reproduction and Development, Fudan University, Shanghai, China; Shanghai Key Laboratory of Reproduction and Development, Shanghai, China; Research Units of Embryo Original Diseases, Chinese Academy of Medical Sciences (No. 2019RU056), Shanghai, China
| | - Gaochen Zhang
- Obstetrics and Gynecology Hospital, Institute of Reproduction and Development, Fudan University, Shanghai, China; Shanghai Key Laboratory of Reproduction and Development, Shanghai, China; Research Units of Embryo Original Diseases, Chinese Academy of Medical Sciences (No. 2019RU056), Shanghai, China
| | - Zuwei Yang
- Obstetrics and Gynecology Hospital, Institute of Reproduction and Development, Fudan University, Shanghai, China; Shanghai Key Laboratory of Reproduction and Development, Shanghai, China; Research Units of Embryo Original Diseases, Chinese Academy of Medical Sciences (No. 2019RU056), Shanghai, China; The International Peace Maternal and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Yan Shi
- Obstetrics and Gynecology Hospital, Institute of Reproduction and Development, Fudan University, Shanghai, China; Shanghai Key Laboratory of Reproduction and Development, Shanghai, China; Research Units of Embryo Original Diseases, Chinese Academy of Medical Sciences (No. 2019RU056), Shanghai, China
| | - Zhaoying Jiang
- Key Laboratory of Reproductive Genetics (Ministry of Education), Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Ye Liu
- The International Peace Maternal and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Huixi Chen
- Shanghai Key Laboratory of Reproduction and Development, Shanghai, China; Research Units of Embryo Original Diseases, Chinese Academy of Medical Sciences (No. 2019RU056), Shanghai, China; The International Peace Maternal and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Hefeng Huang
- Obstetrics and Gynecology Hospital, Institute of Reproduction and Development, Fudan University, Shanghai, China; Shanghai Key Laboratory of Reproduction and Development, Shanghai, China; Research Units of Embryo Original Diseases, Chinese Academy of Medical Sciences (No. 2019RU056), Shanghai, China; The International Peace Maternal and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Key Laboratory of Reproductive Genetics (Ministry of Education), Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
| | - Yu Zhang
- Obstetrics and Gynecology Hospital, Institute of Reproduction and Development, Fudan University, Shanghai, China; Shanghai Key Laboratory of Reproduction and Development, Shanghai, China; Research Units of Embryo Original Diseases, Chinese Academy of Medical Sciences (No. 2019RU056), Shanghai, China.
| | - Jiexue Pan
- Obstetrics and Gynecology Hospital, Institute of Reproduction and Development, Fudan University, Shanghai, China; Shanghai Key Laboratory of Reproduction and Development, Shanghai, China; Research Units of Embryo Original Diseases, Chinese Academy of Medical Sciences (No. 2019RU056), Shanghai, China; The International Peace Maternal and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Key Laboratory of Reproductive Genetics (Ministry of Education), Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
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Shi J, Wu X, Qi H, Xu X, Hong S. Application and discoveries of metabolomics and proteomics in the study of female infertility. Front Endocrinol (Lausanne) 2024; 14:1315099. [PMID: 38274228 PMCID: PMC10810415 DOI: 10.3389/fendo.2023.1315099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Accepted: 12/21/2023] [Indexed: 01/27/2024] Open
Abstract
Introduction Female infertility is defined as the absence of clinical pregnancy after 12 months of regular unprotected sexual intercourse. Methods This study employed metabolomics and proteomics approaches to investigate the relationship between metabolites and proteins and female infertility. The study used metabolomics and proteomics data from the UK Biobank to identify metabolites and proteins linked to infertility. Results The results showed that GRAM domain-containing protein 1C and metabolites fibrinogen cleavage peptides ADpSGEGDFXAEGGGVR and 3-Hydroxybutyrate had a positive correlation with infertility, whereas proteins such as Interleukin-3 receptor subunit alpha, Thrombospondin type-1 domain-containing protein 1, Intestinal-type alkaline phosphatase, and platelet and endothelial cell adhesion molecule 1 exhibited a negative correlation. These findings provide new clues and targets for infertility diagnosis and treatment. However, further research is required to validate these results and gain a deeper understanding of the specific roles of these metabolites and proteins in infertility pathogenesis. Discussion In conclusion, metabolomics and proteomics techniques have significant application value in the study of infertility, allowing for a better understanding of the biological mechanisms underlying infertility and providing new insights and strategies for its diagnosis and treatment. These research findings provide a crucial biological mechanistic basis for early infertility screening, prevention, and treatment.
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Affiliation(s)
- Junhua Shi
- Nursing Department, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Xingjie Wu
- Department of Obstetrics, Hangzhou Medical College Affiliated Lin’an People’s Hospital, The First People’s Hospital of Hangzhou Lin’an District, Hangzhou, Zhejiang, China
| | - Haiou Qi
- Nursing Department, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Xin Xu
- Nursing Department, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Shihao Hong
- Department of Obstetrics and Gynecology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University; Key Laboratory of Reproductive Dysfunction Management of Zhejiang Province, Hangzhou, China
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Hu C, Wang J, Qi F, Liu Y, Zhao F, Wang J, Sun B. Untargeted metabolite profiling of serum in rats exposed to pyrraline. Food Sci Biotechnol 2023; 32:1541-1549. [PMID: 37637845 PMCID: PMC10449741 DOI: 10.1007/s10068-023-01256-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 12/27/2022] [Accepted: 01/10/2023] [Indexed: 01/27/2023] Open
Abstract
Pyrraline, one of advanced glycation end-products, is formed in advanced Maillard reactions. It was reported that the presence of pyrraline was tested to be associated with nephropathy and diabetes. Pyrraline might result in potential health risks because many modern diets are heat processed. In the study, an integrated metabolomics by ultra-high-performance liquid chromatography with mass spectrometry was used to evaluate the effects of pyrraline on metabolism in rats. Thirty-two metabolites were identified as differential metabolites. Linolenic acid metabolism, phenylalanine, tyrosine and tryptophan biosynthesis, arachidonic acid metabolism, tyrosine metabolism and glycerophospholipid metabolism were the main perturbed networks in this pathological process. Differential metabolites and metabolic pathways we found give new insights into studying the toxic molecular mechanisms of pyrraline. Supplementary Information The online version contains supplementary material available at 10.1007/s10068-023-01256-7.
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Affiliation(s)
- Chuanqin Hu
- China-Canada Joint Lab of Food Nutrition and Health (Beijing), Beijing Advanced Innovation Center for Food Nutrition and Human Health, Beijing Engineering and Technology Research Center of Food Additives, Beijing Laboratory for Food Quality and Safety, Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University (BTBU), 11 Fucheng Road, Beijing, 100048 China
| | - Jiahui Wang
- China-Canada Joint Lab of Food Nutrition and Health (Beijing), Beijing Advanced Innovation Center for Food Nutrition and Human Health, Beijing Engineering and Technology Research Center of Food Additives, Beijing Laboratory for Food Quality and Safety, Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University (BTBU), 11 Fucheng Road, Beijing, 100048 China
| | - Fangyuan Qi
- China-Canada Joint Lab of Food Nutrition and Health (Beijing), Beijing Advanced Innovation Center for Food Nutrition and Human Health, Beijing Engineering and Technology Research Center of Food Additives, Beijing Laboratory for Food Quality and Safety, Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University (BTBU), 11 Fucheng Road, Beijing, 100048 China
| | - Yingli Liu
- China-Canada Joint Lab of Food Nutrition and Health (Beijing), Beijing Advanced Innovation Center for Food Nutrition and Human Health, Beijing Engineering and Technology Research Center of Food Additives, Beijing Laboratory for Food Quality and Safety, Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University (BTBU), 11 Fucheng Road, Beijing, 100048 China
| | - Fen Zhao
- China-Canada Joint Lab of Food Nutrition and Health (Beijing), Beijing Advanced Innovation Center for Food Nutrition and Human Health, Beijing Engineering and Technology Research Center of Food Additives, Beijing Laboratory for Food Quality and Safety, Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University (BTBU), 11 Fucheng Road, Beijing, 100048 China
| | - Jing Wang
- China-Canada Joint Lab of Food Nutrition and Health (Beijing), Beijing Advanced Innovation Center for Food Nutrition and Human Health, Beijing Engineering and Technology Research Center of Food Additives, Beijing Laboratory for Food Quality and Safety, Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University (BTBU), 11 Fucheng Road, Beijing, 100048 China
| | - Baoguo Sun
- China-Canada Joint Lab of Food Nutrition and Health (Beijing), Beijing Advanced Innovation Center for Food Nutrition and Human Health, Beijing Engineering and Technology Research Center of Food Additives, Beijing Laboratory for Food Quality and Safety, Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University (BTBU), 11 Fucheng Road, Beijing, 100048 China
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Barrera FJ, Brown ED, Rojo A, Obeso J, Plata H, Lincango EP, Terry N, Rodríguez-Gutiérrez R, Hall JE, Shekhar S. Application of machine learning and artificial intelligence in the diagnosis and classification of polycystic ovarian syndrome: a systematic review. Front Endocrinol (Lausanne) 2023; 14:1106625. [PMID: 37790605 PMCID: PMC10542899 DOI: 10.3389/fendo.2023.1106625] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Accepted: 08/04/2023] [Indexed: 10/05/2023] Open
Abstract
Introduction Polycystic Ovarian Syndrome (PCOS) is the most common endocrinopathy in women of reproductive age and remains widely underdiagnosed leading to significant morbidity. Artificial intelligence (AI) and machine learning (ML) hold promise in improving diagnostics. Thus, we performed a systematic review of literature to identify the utility of AI/ML in the diagnosis or classification of PCOS. Methods We applied a search strategy using the following databases MEDLINE, Embase, the Cochrane Central Register of Controlled Trials, the Web of Science, and the IEEE Xplore Digital Library using relevant keywords. Eligible studies were identified, and results were extracted for their synthesis from inception until January 1, 2022. Results 135 studies were screened and ultimately, 31 studies were included in this study. Data sources used by the AI/ML interventions included clinical data, electronic health records, and genetic and proteomic data. Ten studies (32%) employed standardized criteria (NIH, Rotterdam, or Revised International PCOS classification), while 17 (55%) used clinical information with/without imaging. The most common AI techniques employed were support vector machine (42% studies), K-nearest neighbor (26%), and regression models (23%) were the commonest AI/ML. Receiver operating curves (ROC) were employed to compare AI/ML with clinical diagnosis. Area under the ROC ranged from 73% to 100% (n=7 studies), diagnostic accuracy from 89% to 100% (n=4 studies), sensitivity from 41% to 100% (n=10 studies), specificity from 75% to 100% (n=10 studies), positive predictive value (PPV) from 68% to 95% (n=4 studies), and negative predictive value (NPV) from 94% to 99% (n=2 studies). Conclusion Artificial intelligence and machine learning provide a high diagnostic and classification performance in detecting PCOS, thereby providing an avenue for early diagnosis of this disorder. However, AI-based studies should use standardized PCOS diagnostic criteria to enhance the clinical applicability of AI/ML in PCOS and improve adherence to methodological and reporting guidelines for maximum diagnostic utility. Systematic review registration https://www.crd.york.ac.uk/prospero/, identifier CRD42022295287.
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Affiliation(s)
- Francisco J. Barrera
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, United States
- Plataforma INVEST Medicina, Universidad Autónoma de Nuevo León- Knowledge Education Research (UANL-KER), Unit Mayo Clinic (KER Unit Mexico), Universidad Autónoma de Nuevo León, Monterrey, Mexico
| | - Ethan D.L. Brown
- Reproductive Physiology and Pathophysiology Group, Clinical Research Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, United States
| | - Amanda Rojo
- Plataforma INVEST Medicina, Universidad Autónoma de Nuevo León- Knowledge Education Research (UANL-KER), Unit Mayo Clinic (KER Unit Mexico), Universidad Autónoma de Nuevo León, Monterrey, Mexico
| | - Javier Obeso
- Plataforma INVEST Medicina, Universidad Autónoma de Nuevo León- Knowledge Education Research (UANL-KER), Unit Mayo Clinic (KER Unit Mexico), Universidad Autónoma de Nuevo León, Monterrey, Mexico
| | - Hiram Plata
- Plataforma INVEST Medicina, Universidad Autónoma de Nuevo León- Knowledge Education Research (UANL-KER), Unit Mayo Clinic (KER Unit Mexico), Universidad Autónoma de Nuevo León, Monterrey, Mexico
| | - Eddy P. Lincango
- Knowledge and Evaluation Research Unit-Endocrinology (KER-Endo), Mayo Clinic, Rochester, MN, United States
| | - Nancy Terry
- Division of Library Services, Office of Research Services, National Institutes of Health, Bethesda, MD, United States
| | - René Rodríguez-Gutiérrez
- Plataforma INVEST Medicina, Universidad Autónoma de Nuevo León- Knowledge Education Research (UANL-KER), Unit Mayo Clinic (KER Unit Mexico), Universidad Autónoma de Nuevo León, Monterrey, Mexico
- Knowledge and Evaluation Research Unit-Endocrinology (KER-Endo), Mayo Clinic, Rochester, MN, United States
- Endocrinology Division, Department of Internal Medicine, University Hospital “Dr. José E. González”, Universidad Autonoma de Nuevo Leon, Monterrey, Mexico
| | - Janet E. Hall
- Reproductive Physiology and Pathophysiology Group, Clinical Research Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, United States
| | - Skand Shekhar
- Reproductive Physiology and Pathophysiology Group, Clinical Research Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, United States
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Babu A, Ramanathan G. Multi-omics insights and therapeutic implications in polycystic ovary syndrome: a review. Funct Integr Genomics 2023; 23:130. [PMID: 37079114 DOI: 10.1007/s10142-023-01053-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Revised: 04/04/2023] [Accepted: 04/08/2023] [Indexed: 04/21/2023]
Abstract
Polycystic ovary syndrome (PCOS) is a common gynecological disease that causes adverse effects in women in their reproductive phase. Nonetheless, the molecular mechanisms remain unclear. Over the last decade, sequencing and omics approaches have advanced at an increased pace. Omics initiatives have come to the forefront of biomedical research by presenting the significance of biological functions and processes. Thus, multi-omics profiling has yielded important insights into understanding the biology of PCOS by identifying potential biomarkers and therapeutic targets. Multi-omics platforms provide high-throughput data to leverage the molecular mechanisms and pathways involving genetic alteration, epigenetic regulation, transcriptional regulation, protein interaction, and metabolic alterations in PCOS. The purpose of this review is to outline the prospects of multi-omics technologies in PCOS research by revealing novel biomarkers and therapeutic targets. Finally, we address the knowledge gaps and emerging treatment strategies for the management of PCOS. Future PCOS research in multi-omics at the single-cell level may enhance diagnostic and treatment options.
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Affiliation(s)
- Achsha Babu
- Department of Biomedical Sciences, School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore, Tamil Nadu, 632014, India
| | - Gnanasambandan Ramanathan
- Department of Biomedical Sciences, School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore, Tamil Nadu, 632014, India.
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Specific Alteration of Branched-Chain Amino Acid Profile in Polycystic Ovary Syndrome. Biomedicines 2023; 11:biomedicines11010108. [PMID: 36672616 PMCID: PMC9856032 DOI: 10.3390/biomedicines11010108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 12/09/2022] [Accepted: 12/27/2022] [Indexed: 01/03/2023] Open
Abstract
Polycystic ovary syndrome (PCOS) is one of the most common endocrinopathies in reproductive age women; it is a complex health issue with numerous comorbidities. Attention has recently been drawn to amino acids as they are molecules essential to maintain homeostasis. The aim of the study was to investigate the branch chain amino acid (BCAA) profile in women with PCOS. A total of 326 women, 208 diagnosed with PCOS and 118 healthy controls, participated in the study; all the patients were between 18 and 40 years old. Anthropometrical, biochemical and hormonal parameters were assessed. Gas-liquid chromatography combined with tandem mass spectrometry was used to investigate BCAA levels. Statistical analysis showed significantly higher plasma levels of BCAAs (540.59 ± 97.23 nmol/mL vs. 501.09 ± 85.33 nmol/mL; p < 0.001) in women with PCOS. Significant correlations (p < 0.05) were found between BCAA and BMI, HOMA-IR, waist circumference and total testosterone levels. In the analysis of individuals with abdominal obesity, there were significant differences between PCOS and controls in BCAA (558.13 ± 100.51 vs. 514.22 ± 79.76 nmol/mL) and the concentrations of all the analyzed amino acids were higher in the PCOS patients. Hyperandrogenemia in PCOS patients was associated with significantly higher leucine, isoleucine and total BCAA levels. The increase of BCAA levels among PCOS patients in comparison to healthy controls might be an early sign of metabolic alteration and a predictive factor for other disturbances.
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Rani S, Chandna P. Multiomics Analysis-Based Biomarkers in Diagnosis of Polycystic Ovary Syndrome. Reprod Sci 2023; 30:1-27. [PMID: 35084716 PMCID: PMC10010205 DOI: 10.1007/s43032-022-00863-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2021] [Accepted: 01/20/2022] [Indexed: 01/06/2023]
Abstract
Polycystic ovarian syndrome is an utmost communal endocrine, psychological, reproductive, and metabolic disorder that occurs in women of reproductive age with extensive range of clinical manifestations. This may even lead to long-term multiple morbidities including obesity, diabetes mellitus, insulin resistance, cardiovascular disease, infertility, cerebrovascular diseases, and ovarian and endometrial cancer. Women affliction from PCOS in midst assemblage of manifestations allied with menstrual dysfunction and androgen exorbitance, which considerably affects eminence of life. PCOS is recognized as a multifactorial disorder and systemic syndrome in first-degree family members; therefore, the etiology of PCOS syndrome has not been copiously interpreted. The disorder of PCOS comprehends numerous allied health conditions and has influenced various metabolic processes. Due to multifaceted pathophysiology engaging several pathways and proteins, single genetic diagnostic tests cannot be supportive to determine in straight way. Clarification of cellular and biochemical pathways and various genetic players underlying PCOS could upsurge our consideration of pathophysiology of this syndrome. It is requisite to know pathophysiological relationship between biomarker and their reflection towards PCOS disease. Biomarkers deliver vibrantly and potent ways to apprehend the spectrum of PCOS with applications in screening, diagnosis, characterization, and monitoring. This paper relies on the endeavor to point out many candidates as potential biomarkers based on omics technologies, thus highlighting correlation between PCOS disease with innovative technologies. Therefore, the objective of existing review is to encapsulate more findings towards cutting-edge advances in prospective use of biomarkers for PCOS disease. Discussed biomarkers may be fruitful in guiding therapies, addressing disease risk, and predicting clinical outcomes in future.
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Affiliation(s)
- Shikha Rani
- Department of Biophysics, University of Delhi, South Campus, Benito Juarez Road, New Delhi , 110021, India.
| | - Piyush Chandna
- Natdynamics Biosciences Confederation, Gurgaon, Haryana, 122001, India
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Jala A, Varghese B, Kaur G, Rajendiran K, Dutta R, Adela R, Borkar RM. Implications of endocrine-disrupting chemicals on polycystic ovarian syndrome: A comprehensive review. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:58484-58513. [PMID: 35778660 DOI: 10.1007/s11356-022-21612-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Accepted: 06/17/2022] [Indexed: 06/15/2023]
Abstract
Polycystic ovarian syndrome (PCOS) is a complex multifactorial disorder of unknown pathogenesis in which genetic and environmental factors contribute synergistically to its phenotypic expressions. Endocrine-disrupting chemicals (EDCs), a group of widespread pollutants freely available in the environment and consumer products, can interfere with normal endocrine signals. Extensive evidence has shown that EDCs, environmental contributors to PCOS, can frequently induce ovarian and metabolic abnormalities at low doses. The current research on environmental EDCs suggests that there may be link between EDC exposure and PCOS, which calls for more human bio-monitoring of EDCs using highly sophisticated analytical techniques for the identification and quantification and to discover the underlying pathophysiology of the disease. This review briefly elaborated on the general etiology of PCOS and listed various epidemiological and experimental data from human and animal studies correlating EDCs and PCOS. This review also provides insights into various analytical tools and sample preparation techniques for biomonitoring studies for PCOS risk assessment. Furthermore, we highlight the role of metabolomics in disease-specific biomarker discovery and its use in clinical practice. It also suggests the way forward to integrate biomonitoring studies and metabolomics to underpin the role of EDCs in PCOS pathophysiology.
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Affiliation(s)
- Aishwarya Jala
- Department of Pharmaceutical Analysis, National Institute of Pharmaceutical Education and Research (NIPER), Guwahati, Changsari, 781101, India
| | - Bincy Varghese
- Department of Pharmacy Practice, National Institute of Pharmaceutical Education and Research (NIPER), Guwahati, Changsari, 781101, India
| | - Gurparmeet Kaur
- Department of Pharmacy Practice, National Institute of Pharmaceutical Education and Research (NIPER), Guwahati, Changsari, 781101, India
| | | | - Ratul Dutta
- Down Town Hospital, Guwahati, Assam, 781106, India
| | - Ramu Adela
- Department of Pharmacy Practice, National Institute of Pharmaceutical Education and Research (NIPER), Guwahati, Changsari, 781101, India
| | - Roshan M Borkar
- Department of Pharmaceutical Analysis, National Institute of Pharmaceutical Education and Research (NIPER), Guwahati, Changsari, 781101, India.
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Brinca AT, Ramalhinho AC, Sousa Â, Oliani AH, Breitenfeld L, Passarinha LA, Gallardo E. Follicular Fluid: A Powerful Tool for the Understanding and Diagnosis of Polycystic Ovary Syndrome. Biomedicines 2022; 10:1254. [PMID: 35740276 PMCID: PMC9219683 DOI: 10.3390/biomedicines10061254] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Revised: 05/23/2022] [Accepted: 05/24/2022] [Indexed: 02/04/2023] Open
Abstract
Polycystic ovary syndrome (PCOS) represents one of the leading causes of anovulatory infertility and affects 5% to 20% of women worldwide. Until today, both the subsequent etiology and pathophysiology of PCOS remain unclear, and patients with PCOS that undergo assisted reproductive techniques (ART) might present a poor to exaggerated response, low oocyte quality, ovarian hyperstimulation syndrome, as well as changes in the follicular fluid metabolites pattern. These abnormalities originate a decrease of Metaphase II (MII) oocytes and decreased rates for fertilization, cleavage, implantation, blastocyst conversion, poor egg to follicle ratio, and increased miscarriages. Focus on obtaining high-quality embryos has been taken into more consideration over the years. Nowadays, the use of metabolomic analysis in the quantification of proteins and peptides in biological matrices might predict, with more accuracy, the success in assisted reproductive technology. In this article, we review the use of human follicular fluid as the matrix in metabolomic analysis for diagnostic and ART predictor of success for PCOS patients.
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Affiliation(s)
- Ana Teresa Brinca
- Health Sciences Research Centre, Faculty of Health Sciences, University of Beira Interior, 6200-506 Covilhã, Portugal; (A.T.B.); (Â.S.); (L.B.)
| | - Ana Cristina Ramalhinho
- Health Sciences Research Centre, Faculty of Health Sciences, University of Beira Interior, 6200-506 Covilhã, Portugal; (A.T.B.); (Â.S.); (L.B.)
- Assisted Reproduction Laboratory of Academic Hospital of Cova da Beira, 6200-251 Covilhã, Portugal;
- C4-Cloud Computing Competence Centre, University of Beira Interior, 6201-001 Covilhã, Portugal
| | - Ângela Sousa
- Health Sciences Research Centre, Faculty of Health Sciences, University of Beira Interior, 6200-506 Covilhã, Portugal; (A.T.B.); (Â.S.); (L.B.)
| | - António Hélio Oliani
- Assisted Reproduction Laboratory of Academic Hospital of Cova da Beira, 6200-251 Covilhã, Portugal;
- São José do Rio Preto School of Medicine, Gynaecology and Obstetrics, São José do Rio Preto 15090-000, Brazil
| | - Luiza Breitenfeld
- Health Sciences Research Centre, Faculty of Health Sciences, University of Beira Interior, 6200-506 Covilhã, Portugal; (A.T.B.); (Â.S.); (L.B.)
- C4-Cloud Computing Competence Centre, University of Beira Interior, 6201-001 Covilhã, Portugal
| | - Luís A. Passarinha
- Health Sciences Research Centre, Faculty of Health Sciences, University of Beira Interior, 6200-506 Covilhã, Portugal; (A.T.B.); (Â.S.); (L.B.)
- UCIBIO–Applied Molecular Biosciences Unit, Departament of Chemistry, NOVA School of Science and Technology, Universidade NOVA de Lisboa, 2829-516 Caparica, Portugal
- Associate Laboratory i4HB-Institute for Health and Bioeconomy, NOVA School of Science and Technology, Universidade NOVA de Lisboa, 2819-516 Caparica, Portugal
- Laboratório de Fármaco-Toxicologia, UBIMedical, University of Beira Interior, 6200-284 Covilhã, Portugal
| | - Eugenia Gallardo
- Health Sciences Research Centre, Faculty of Health Sciences, University of Beira Interior, 6200-506 Covilhã, Portugal; (A.T.B.); (Â.S.); (L.B.)
- Laboratório de Fármaco-Toxicologia, UBIMedical, University of Beira Interior, 6200-284 Covilhã, Portugal
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13
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He P, Zhu P, Wei P, Zhuo X, Ma Y, Chen X, Lin Y, Xu Y, Luo H, Peng J. Gonadal transcriptomic analysis and differentially expressed genes between the testes and ovaries in Trachinotus ovatus. AQUACULTURE AND FISHERIES 2022. [DOI: 10.1016/j.aaf.2020.09.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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14
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Ye Z, Zhang C, Wang S, Zhang Y, Li R, Zhao Y, Qiao J. Amino acid signatures in relation to polycystic ovary syndrome and increased risk of different metabolic disturbances. Reprod Biomed Online 2021; 44:737-746. [DOI: 10.1016/j.rbmo.2021.11.012] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2021] [Revised: 11/12/2021] [Accepted: 11/16/2021] [Indexed: 12/13/2022]
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15
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Feng T, Ding H, Wang J, Xu W, Liu Y, Kenéz Á. Alterations of Serum Metabolites and Fecal Microbiota Involved in Ewe Follicular Cyst. Front Microbiol 2021; 12:675480. [PMID: 34054784 PMCID: PMC8149755 DOI: 10.3389/fmicb.2021.675480] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Accepted: 04/16/2021] [Indexed: 12/18/2022] Open
Abstract
While the interactions of the gut microbiome and blood metabolome have been widely studied in polycystic ovary disease in women, follicular cysts of ewes have been scarcely investigated using these methods. In this study, the fecal microbiome and serum metabolome were used to compare between ewes diagnosed with ovarian cystic follicles and ewes with normal follicles, to investigate alterations of the fecal bacterial community composition and metabolic parameters in relation to follicular cystogenesis. Ewes from the same feeding and management system were diagnosed with a follicular cyst (n = 6) or confirmed to have normal follicles (n = 6) by using a B-mode ultrasound scanner. Blood serum and fresh fecal samples of all ewes were collected and analyzed. The α-diversity of fecal microbiome did not differ significantly between follicular cyst ewes and normal follicle ewes. Three genera (Bacteroides, Anaerosporobacter, and Angelakisella) were identified and their balance differentiated between follicular cyst and normal follicle ewes. Alterations of several serum metabolite concentrations, belonging to lipids and lipid-like molecules, organic acids and derivatives, organic oxygen compounds, benzenoids, phenylpropanoids and polyketides, and organoheterocyclic compounds, were associated with the presence of a follicular cyst. Correlation analysis between fecal bacterial communities and serum metabolites indicated a positive correlation between Anaerosporobacter and several fatty acids, and a negative correlation between Bacteroides and L-proline. These observations provide new insights for the complex interactions of the gut microbiota and the host serum lipid profiles, and support gut microbiota as a potential strategy to treat and prevent follicular cysts in sheep.
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Affiliation(s)
- Tao Feng
- Institute of Animal Husbandry and Veterinary Medicine (IAHVM), Beijing Academy of Agriculture and Forestry Sciences (BAAFS), Beijing, China.,Joint Laboratory of Animal Science Between IAHVM of BAAFS and Division of Agricultural Science and Natural Resource, Oklahoma State University, Beijing, China.,College of Animal Science and Technology, Henan University of Science and Technology, Luoyang, China
| | - Hongxiang Ding
- Institute of Animal Husbandry and Veterinary Medicine (IAHVM), Beijing Academy of Agriculture and Forestry Sciences (BAAFS), Beijing, China.,Joint Laboratory of Animal Science Between IAHVM of BAAFS and Division of Agricultural Science and Natural Resource, Oklahoma State University, Beijing, China.,College of Animal Science and Technology, Henan University of Science and Technology, Luoyang, China
| | - Jing Wang
- College of Animal Science and Technology, Hebei North University, Zhangjiakou, China
| | - Wei Xu
- Department of Infectious Diseases and Public Health, City University of Hong Kong, Hong Kong, China
| | - Yan Liu
- Institute of Animal Husbandry and Veterinary Medicine (IAHVM), Beijing Academy of Agriculture and Forestry Sciences (BAAFS), Beijing, China.,Joint Laboratory of Animal Science Between IAHVM of BAAFS and Division of Agricultural Science and Natural Resource, Oklahoma State University, Beijing, China
| | - Ákos Kenéz
- Department of Infectious Diseases and Public Health, City University of Hong Kong, Hong Kong, China
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16
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Alesi S, Ghelani D, Mousa A. Metabolomic Biomarkers in Polycystic Ovary Syndrome: A Review of the Evidence. Semin Reprod Med 2021; 39:102-110. [PMID: 33946122 DOI: 10.1055/s-0041-1729841] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Polycystic ovary syndrome (PCOS) is an endocrinologic condition affecting one in five women of reproductive age. PCOS is often characterized by disruptions to the menstrual cycle, development of male-pattern hair growth (hirsutism), and polycystic ovary morphology. Recently, PCOS has been linked to metabolic dysfunction, with 40 to 80% of women characterized as overweight or obese. Despite these well-known negative health effects of PCOS, 75% of sufferers remain undiagnosed. This is most likely due to the variability in symptom presentation and the lack of a definitive test for the condition. Metabolomics, which is a platform used to analyze and characterize a large number of metabolites, has recently been proposed as a potential tool for investigating the metabolic pathways that could be involved in the pathophysiology of PCOS. In doing so, novel biomarkers could be identified to improve diagnosis and treatment of PCOS. This review aims to summarize the findings of recent metabolomic studies that highlight metabolic-specific molecules which are deranged in PCOS, to identify potential biomarkers for the condition. Current limitations for metabolomic studies are discussed, as well as future directions to progress the field toward further validation and integration into clinical practice.
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Affiliation(s)
- Simon Alesi
- Monash Centre for Health Research and Implementation (MCHRI), School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Drishti Ghelani
- Monash Centre for Health Research and Implementation (MCHRI), School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Aya Mousa
- Monash Centre for Health Research and Implementation (MCHRI), School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
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17
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Asampille G, Cheredath A, Joseph D, Adiga SK, Atreya HS. The utility of nuclear magnetic resonance spectroscopy in assisted reproduction. Open Biol 2020; 10:200092. [PMID: 33142083 PMCID: PMC7729034 DOI: 10.1098/rsob.200092] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2020] [Accepted: 10/13/2020] [Indexed: 12/21/2022] Open
Abstract
Infertility affects approximately 15-20% of individuals of reproductive age worldwide. Over the last 40 years, assisted reproductive technology (ART) has helped millions of childless couples. However, ART is limited by a low success rate and risk of multiple gestations. Devising methods for selecting the best gamete or embryo that increases the ART success rate and prevention of multiple gestation has become one of the key goals in ART today. Special emphasis has been placed on the development of non-invasive approaches, which do not require perturbing the embryonic cells, as the current morphology-based embryo selection approach has shortcomings in predicting the implantation potential of embryos. An observed association between embryo metabolism and viability has prompted researchers to develop metabolomics-based biomarkers. Nuclear magnetic resonance (NMR) spectroscopy provides a non-invasive approach for the metabolic profiling of tissues, gametes and embryos, with the key advantage of having a minimal sample preparation procedure. Using NMR spectroscopy, biologically important molecules can be identified and quantified in intact cells, extracts or secretomes. This, in turn, helps to map out the active metabolic pathways in a system. The present review covers the contribution of NMR spectroscopy in assisted reproduction at various stages of the process.
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Affiliation(s)
- Gitanjali Asampille
- Department of Clinical Embryology, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal 576104, India
| | - Aswathi Cheredath
- Department of Clinical Embryology, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal 576104, India
| | - David Joseph
- NMR Research Centre, Indian Institute of Science, Bangalore 560012, India
- Solid State and Structural Chemistry Unit, Indian Institute of Science, Bangalore 560012, India
| | - Satish K. Adiga
- Department of Clinical Embryology, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal 576104, India
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18
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Rajska A, Buszewska-Forajta M, Rachoń D, Markuszewski MJ. Metabolomic Insight into Polycystic Ovary Syndrome-An Overview. Int J Mol Sci 2020; 21:ijms21144853. [PMID: 32659951 PMCID: PMC7402307 DOI: 10.3390/ijms21144853] [Citation(s) in RCA: 53] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Revised: 07/04/2020] [Accepted: 07/07/2020] [Indexed: 12/13/2022] Open
Abstract
Searching for the mechanisms of the polycystic ovary syndrome (PCOS) pathophysiology has become a crucial aspect of research performed in the last decades. However, the pathogenesis of this complex and heterogeneous endocrinopathy remains unknown. Thus, there is a need to investigate the metabolic pathways, which could be involved in the pathophysiology of PCOS and to find the metabolic markers of this disorder. The application of metabolomics gives a promising insight into the research on PCOS. It is a valuable and rapidly expanding tool, enabling the discovery of novel metabolites, which may be the potential biomarkers of several metabolic and endocrine disorders. The utilization of this approach could also improve the process of diagnosis and therefore, make treatment more effective. This review article aims to summarize actual and meaningful metabolomic studies in PCOS and point to the potential biomarkers detected in serum, urine, and follicular fluid of the affected women.
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Affiliation(s)
- Anna Rajska
- Department of Biopharmaceutics and Pharmacodynamics, Medical University of Gdańsk, Hallera 107, 80-416 Gdańsk, Poland; (A.R.); (M.B.-F.)
| | - Magdalena Buszewska-Forajta
- Department of Biopharmaceutics and Pharmacodynamics, Medical University of Gdańsk, Hallera 107, 80-416 Gdańsk, Poland; (A.R.); (M.B.-F.)
| | - Dominik Rachoń
- Department of Clinical and Experimental Endocrinology, Medical University of Gdańsk, Dębinki 7, 80-211 Gdańsk, Poland;
| | - Michał Jan Markuszewski
- Department of Biopharmaceutics and Pharmacodynamics, Medical University of Gdańsk, Hallera 107, 80-416 Gdańsk, Poland; (A.R.); (M.B.-F.)
- Correspondence:
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Ganie MA, Vasudevan V, Wani IA, Baba MS, Arif T, Rashid A. Epidemiology, pathogenesis, genetics & management of polycystic ovary syndrome in India. Indian J Med Res 2020; 150:333-344. [PMID: 31823915 PMCID: PMC6902362 DOI: 10.4103/ijmr.ijmr_1937_17] [Citation(s) in RCA: 93] [Impact Index Per Article: 18.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Polycystic ovary syndrome (PCOS) is a common endocrine disorder predominantly affecting women of reproductive age. Clinical manifestations are diverse including hyperandrogenism, anovulation, infertility and increased risk of metabolic diseases besides psychosocial dysfunction. This review provides information on the problem of PCOS in India, its pathophysiology, genetics and an overview of current management options to instigate further research in this field. Prevalence of PCOS in India ranges from 3.7 to 22.5 per cent depending on the population studied and the criteria used for diagnosis. Abnormalities in leptin-adiponectin (adipocyte biology), oxidative stress and autoimmunity are among the mechanisms studied regarding pathogenesis of PCOS. Many candidate gene studies have shown associations with PCOS in various studies. Studies have consistently demonstrated the relationship between the well-known manifestation of hyperandrogenism among Indian PCOS women and the metabolic morbidities including insulin resistance, glucose intolerance and cardiovascular risk. Management of individual components of PCOS can be achieved by medications or surgical methods, though further clarification regarding pathogenesis of PCOS is needed to sharpen our therapeutic armamentarium.
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Affiliation(s)
- Mohammad Ashraf Ganie
- Department of Endocrinology & Metabolism, Sher-i-Kashmir Institute of Medical Sciences, Srinagar, Jammu and Kashmir, India
| | - Vishnu Vasudevan
- Department of Endocrinology & Metabolism, Sher-i-Kashmir Institute of Medical Sciences, Srinagar, Jammu and Kashmir, India
| | - Imtiyaz Ahmad Wani
- Department of Endocrinology & Metabolism, Sher-i-Kashmir Institute of Medical Sciences, Srinagar, Jammu and Kashmir, India
| | - Mohammad Salem Baba
- Department of Endocrinology & Metabolism, Sher-i-Kashmir Institute of Medical Sciences, Srinagar, Jammu and Kashmir, India
| | - Tasleem Arif
- Department of Endocrinology & Metabolism, Sher-i-Kashmir Institute of Medical Sciences, Srinagar, Jammu and Kashmir, India
| | - Aafia Rashid
- Department of Endocrinology & Metabolism, Sher-i-Kashmir Institute of Medical Sciences, Srinagar, Jammu and Kashmir, India
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20
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Miller JS, Rodriguez-Saona L, Hackshaw KV. Metabolomics in Central Sensitivity Syndromes. Metabolites 2020; 10:E164. [PMID: 32344505 PMCID: PMC7240948 DOI: 10.3390/metabo10040164] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Revised: 04/11/2020] [Accepted: 04/19/2020] [Indexed: 01/09/2023] Open
Abstract
Central sensitization syndromes are a collection of frequently painful disorders that contribute to decreased quality of life and increased risk of opiate abuse. Although these disorders cause significant morbidity, they frequently lack reliable diagnostic tests. As such, technologies that can identify key moieties in central sensitization disorders may contribute to the identification of novel therapeutic targets and more precise treatment options. The analysis of small molecules in biological samples through metabolomics has improved greatly and may be the technology needed to identify key moieties in difficult to diagnose diseases. In this review, we discuss the current state of metabolomics as it relates to central sensitization disorders. From initial literature review until Feb 2020, PubMed, Embase, and Scopus were searched for applicable studies. We included cohort studies, case series, and interventional studies of both adults and children affected by central sensitivity syndromes. The majority of metabolomic studies addressing a CSS found significantly altered metabolites that allowed for differentiation of CSS patients from healthy controls. Therefore, the published literature overwhelmingly supports the use of metabolomics in CSS. Further research into these altered metabolites and their respective metabolic pathways may provide more reliable and effective therapeutics for these syndromes.
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Affiliation(s)
- Joseph S. Miller
- Department of Medicine, Ohio University Heritage College of Osteopathic Medicine, Dublin, OH 43016, USA;
| | - Luis Rodriguez-Saona
- Department of Food Science and Technology, Ohio State University, Columbus, OH 43210, USA;
| | - Kevin V. Hackshaw
- Department of Internal Medicine, Division of Rheumatology, Dell Medical School, The University of Texas, 1701 Trinity St, Austin, TX 78712, USA
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21
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Silva RA, Pereira TC, Souza AR, Ribeiro PR. 1H NMR-based metabolite profiling for biomarker identification. Clin Chim Acta 2020; 502:269-279. [PMID: 31778675 DOI: 10.1016/j.cca.2019.11.015] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Revised: 11/11/2019] [Accepted: 11/12/2019] [Indexed: 12/11/2022]
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Liu X, Liu C, Tian J, Gao X, Li K, Du G, Qin X. Plasma metabolomics of depressed patients and treatment with Xiaoyaosan based on mass spectrometry technique. JOURNAL OF ETHNOPHARMACOLOGY 2020; 246:112219. [PMID: 31494201 DOI: 10.1016/j.jep.2019.112219] [Citation(s) in RCA: 59] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/17/2019] [Revised: 09/04/2019] [Accepted: 09/04/2019] [Indexed: 06/10/2023]
Abstract
ETHNOPHARMACOLOGICAL RELEVANCE Xiaoyaosan (XYS), a famous and classic traditional Chinese prescription, has been used for long time in treating depressive disorders. XYS consists of Radix Bupleuri (Bupleurum chinense DC.), Radix Angelicae Sinensis (Angelica sinensis (Oliv.) Diels), Radix PaeoniaeAlba (Paeonia lactiflora Pall.), Rhizoma Atractylodis Macrocepha lae (Atractylodes macrocephala Koidz.), Poria (Poria cocos (Schw.)Wolf), Radix Glycyrrhizae (Glycyrrhiza uralensis Fisch.), Herba Menthae Haplocalycis (Mentha haplocalyx Briq.), and Rhizoma Zin-giberis Recens (Zingiber officinale Rosc.). AIM OF THE STUDY A GC-MS based metabolomics approach was applied to discover the potential biomarkers that were related to metabolic differences between healthy volunteers and depression cohort diagnosed by HAMD and CGI, and to demonstrate the potential utility of these biomarkers in the diagnosis of depression and pharmaceutical efficacy of XYS. MATERIALS AND METHODS A total of 17 depressed patients and the 17 age- and gender-matched healthy subjects were served as the primary cohort. The depressed patients were screened according to the Chinese Classification of Mental Disorder (CCMD-3) and the Hamilton Depression Scale (HAMD). In addition, five other depressed patients were also enrolled as the primary cohort when the final step of sample collection was conducted. Plasma samples were analyzed by Gas Chromatography-Mass Spectrometry (GC-MS). Clinical and metabolomics data were analyzed by multivariate statistics analysis, Receiver Operating Characteristic (ROC) curve and MetaboAnalyst. RESULTS We observed significant differences between depression cohort and healthy volunteers, and between patients before and after the treatment of XYS. The method was then clinically validated in an independent validation cohort. Levels of oxalic and stearic acids significantly increased in depressed patients' plasma while valine and urea significantly decreased, as compared with healthy controls. Of note, XYS reversed these metabolite changes in terms of regulating dysfunctions in glyoxylate and dicarboxylate metabolism, fatty acid biosynthesis, valine, leucine and isoleucine biosynthesis, and arginine and proline metabolism. Importantly, the combination of oxalic and stearic acids is in prospect as diagnose biomarkers. CONCLUSIONS This study highlights the clinical application of metabolomics in disease diagnose and therapy evaluation, which will help in improving our understanding of depression and will lay solid foundation for the clinic application of TCMs. In addition, it suggests that the combination of the two potential biomarkers had also achieved a high diagnostic value, which consequently could be used a diagnose biomarkers.
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Affiliation(s)
- Xiaojie Liu
- Modern Research Center for Traditional Chinese Medicine, Shanxi University, Taiyuan, 030006, PR China; Science and Technology Innovation Team of Shanxi Province, Taiyuan, 030006, PR China; Key Laboratory of Effective Substances Research and Utilization in Traditional Chinese Medicine of Shanxi Province, Taiyuan, 030006, PR China
| | - Caichun Liu
- Modern Research Center for Traditional Chinese Medicine, Shanxi University, Taiyuan, 030006, PR China; Science and Technology Innovation Team of Shanxi Province, Taiyuan, 030006, PR China; Key Laboratory of Effective Substances Research and Utilization in Traditional Chinese Medicine of Shanxi Province, Taiyuan, 030006, PR China
| | - Junsheng Tian
- Modern Research Center for Traditional Chinese Medicine, Shanxi University, Taiyuan, 030006, PR China; Science and Technology Innovation Team of Shanxi Province, Taiyuan, 030006, PR China; Key Laboratory of Effective Substances Research and Utilization in Traditional Chinese Medicine of Shanxi Province, Taiyuan, 030006, PR China
| | - Xiaoxia Gao
- Modern Research Center for Traditional Chinese Medicine, Shanxi University, Taiyuan, 030006, PR China; Science and Technology Innovation Team of Shanxi Province, Taiyuan, 030006, PR China; Key Laboratory of Effective Substances Research and Utilization in Traditional Chinese Medicine of Shanxi Province, Taiyuan, 030006, PR China
| | - Ke Li
- Modern Research Center for Traditional Chinese Medicine, Shanxi University, Taiyuan, 030006, PR China; Science and Technology Innovation Team of Shanxi Province, Taiyuan, 030006, PR China; Key Laboratory of Effective Substances Research and Utilization in Traditional Chinese Medicine of Shanxi Province, Taiyuan, 030006, PR China
| | - Guanhua Du
- Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, PR China
| | - Xuemei Qin
- Modern Research Center for Traditional Chinese Medicine, Shanxi University, Taiyuan, 030006, PR China; Science and Technology Innovation Team of Shanxi Province, Taiyuan, 030006, PR China; Key Laboratory of Effective Substances Research and Utilization in Traditional Chinese Medicine of Shanxi Province, Taiyuan, 030006, PR China.
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Govorov I, Sitkin S, Pervunina T, Moskvin A, Baranenko D, Komlichenko E. Metabolomic Biomarkers in Gynecology: A Treasure Path or a False Path? Curr Med Chem 2020; 27:3611-3622. [PMID: 30608036 DOI: 10.2174/0929867326666190104124245] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2018] [Revised: 12/21/2018] [Accepted: 12/31/2018] [Indexed: 12/27/2022]
Abstract
Omic-technologies (genomics, transcriptomics, proteomics and metabolomics) have become more important in current medical science. Among them, it is metabolomics that most accurately reflects the minor changes in body functioning, as it focuses on metabolome - the group of the metabolism products, both intermediate and end. Therefore, metabolomics is actively engaged in fundamental and clinical studies and search for potential biomarkers. The biomarker could be used in diagnostics, management and stratification of the patients, as well as in prognosing the outcomes. The good example is gynecology, since many gynecological diseases lack effective biomarkers. In the current review, we aimed to summarize the results of the studies, devoted to the search of potential metabolomic biomarkers for the most common gynecological diseases.
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Affiliation(s)
- Igor Govorov
- Institute of Perinatology and Pediatric, Almazov National Medical Research Centre, Saint-Petersburg 197341, Russian Federation
- International Research Centre "Biotechnologies of the Third Millennium", ITMO University, Saint-Petersburg 197341, Russian Federation
| | - Stanislav Sitkin
- Institute of Perinatology and Pediatric, Almazov National Medical Research Centre, Saint-Petersburg 197341, Russian Federation
- International Research Centre "Biotechnologies of the Third Millennium", ITMO University, Saint-Petersburg 197341, Russian Federation
- North-Western State Medical University named after I.I. Mechnikov, St. Petersburg 191015, Russian Federation
| | - Tatyana Pervunina
- Institute of Perinatology and Pediatric, Almazov National Medical Research Centre, Saint-Petersburg 197341, Russian Federation
- International Research Centre "Biotechnologies of the Third Millennium", ITMO University, Saint-Petersburg 197341, Russian Federation
| | - Alexey Moskvin
- International Research Centre "Biotechnologies of the Third Millennium", ITMO University, Saint-Petersburg 197341, Russian Federation
| | - Denis Baranenko
- International Research Centre "Biotechnologies of the Third Millennium", ITMO University, Saint-Petersburg 197341, Russian Federation
| | - Eduard Komlichenko
- Institute of Perinatology and Pediatric, Almazov National Medical Research Centre, Saint-Petersburg 197341, Russian Federation
- International Research Centre "Biotechnologies of the Third Millennium", ITMO University, Saint-Petersburg 197341, Russian Federation
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Song Z, Wang H, Yin X, Deng P, Jiang W. Application of NMR metabolomics to search for human disease biomarkers in blood. Clin Chem Lab Med 2019; 57:417-441. [PMID: 30169327 DOI: 10.1515/cclm-2018-0380] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2018] [Accepted: 07/16/2018] [Indexed: 02/05/2023]
Abstract
Recently, nuclear magnetic resonance spectroscopy (NMR)-based metabolomics analysis and multivariate statistical techniques have been incorporated into a multidisciplinary approach to profile changes in small molecules associated with the onset and progression of human diseases. The purpose of these efforts is to identify unique metabolite biomarkers in a specific human disease so as to (1) accurately predict and diagnose diseases, including separating distinct disease stages; (2) provide insights into underlying pathways in the pathogenesis and progression of the malady and (3) aid in disease treatment and evaluate the efficacy of drugs. In this review we discuss recent developments in the application of NMR-based metabolomics in searching disease biomarkers in human blood samples in the last 5 years.
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Affiliation(s)
- Zikuan Song
- Molecular Medicine Research Center, West China Hospital, Sichuan University, Chengdu, Sichuan, P.R. China.,West China School of Basic Medical Science and Forensic Medicine, Sichuan University, Chengdu, Sichuan, P.R. China
| | - Haoyu Wang
- Molecular Medicine Research Center, West China Hospital, Sichuan University, Chengdu, Sichuan, P.R. China.,West China School of Basic Medical Science and Forensic Medicine, Sichuan University, Chengdu, Sichuan, P.R. China
| | - Xiaotong Yin
- Molecular Medicine Research Center, West China Hospital, Sichuan University, Chengdu, Sichuan, P.R. China.,West China School of Basic Medical Science and Forensic Medicine, Sichuan University, Chengdu, Sichuan, P.R. China
| | - Pengchi Deng
- Analytical and Testing Center, Sichuan University, Chengdu, Sichuan, P.R. China
| | - Wei Jiang
- Molecular Medicine Research Center, West China Hospital, Sichuan University, Chengdu, Sichuan, P.R. China
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Chen X, Lu T, Wang X, Sun X, Zhang J, Zhou K, Ji X, Sun R, Wang X, Chen M, Ling X. Metabolic alterations associated with polycystic ovary syndrome: A UPLC Q-Exactive based metabolomic study. Clin Chim Acta 2019; 502:280-286. [PMID: 31758934 DOI: 10.1016/j.cca.2019.11.016] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2019] [Revised: 10/24/2019] [Accepted: 11/11/2019] [Indexed: 12/14/2022]
Abstract
BACKGROUND The polycystic ovary syndrome (PCOS) is the most common endocrine and metabolic disorder syndrome of women in reproductive age. Metabolomic studies of the follicular fluid can reveal the potential metabolic pathways related to PCOS. The objection of this study was to explore the changes of metabolites in the follicular fluid of PCOS. METHODS We collected follicular fluid samples of 35 patients with PCOS and 33 controls without PCOS for metabolomic analysis with UPLC Q-Exactive. The identified metabolites were annotated with KEGG and HMDB to determine the disturbances of metabolic pathways in PCOS. Based on the regression model, we conducted the ROC analysis to find the biomarker of PCOS in the follicular fluid. RESULTS Metabolomic analysis identified 21 differential metabolites in PCOS, which revealed that the Vitamin B6 metabolism, phenylalanine metabolism and carnitine synthesis were the key changed pathways. We found that 7β-Hydroxycholesterol was potential biomarker of PCOS based on the ROC analysis. CONCLUSION We identified metabolic alterations and biomarker in the follicular fluid of PCOS, providing novel ways for the diagnosis and treatment of PCOS.
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Affiliation(s)
- Xiaojiao Chen
- State Key Laboratory of Reproductive Medicine, Department of Reproduction, the Affiliated Obstetrics and Gynecology Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Jiangsu Province, Nanjing, 210004, China
| | - Ting Lu
- State Key Laboratory of Reproductive Medicine, Institute of Toxicology, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Xiaoxiao Wang
- State Key Laboratory of Reproductive Medicine, Institute of Toxicology, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Xian Sun
- State Key Laboratory of Reproductive Medicine, Institute of Toxicology, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Junqiang Zhang
- State Key Laboratory of Reproductive Medicine, Department of Reproduction, the Affiliated Obstetrics and Gynecology Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Jiangsu Province, Nanjing, 210004, China
| | - Kun Zhou
- State Key Laboratory of Reproductive Medicine, Institute of Toxicology, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Xiaoming Ji
- State Key Laboratory of Reproductive Medicine, Institute of Toxicology, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Rongli Sun
- Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing 210009, China
| | - Xinru Wang
- State Key Laboratory of Reproductive Medicine, Institute of Toxicology, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 211166, China.
| | - Minjian Chen
- State Key Laboratory of Reproductive Medicine, Institute of Toxicology, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 211166, China.
| | - Xiufeng Ling
- State Key Laboratory of Reproductive Medicine, Department of Reproduction, the Affiliated Obstetrics and Gynecology Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Jiangsu Province, Nanjing, 210004, China.
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Ghosh N, Choudhury P, Subramani E, Saha D, Sengupta S, Joshi M, Banerjee R, Roychowdhury S, Bhattacharyya P, Chaudhury K. Metabolomic signatures of asthma-COPD overlap (ACO) are different from asthma and COPD. Metabolomics 2019; 15:87. [PMID: 31165288 DOI: 10.1007/s11306-019-1552-z] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2019] [Accepted: 05/29/2019] [Indexed: 12/21/2022]
Abstract
INTRODUCTION Asthma-chronic obstructive pulmonary disease (COPD) overlap, termed as ACO, is a complex heterogeneous disease without any clear diagnostic or therapeutic guidelines. The pathophysiology of the disease, its characteristic features, and existence as a unique disease entity remains unclear. Individuals with ACO have a faster lung function decline, more frequent exacerbations, and worse quality of life than those with COPD or asthma alone. OBJECTIVES The present study aims to determine whether ACO has a distinct metabolic profile in comparison to asthma and COPD. METHODS Two different groups of patients were recruited as discovery (D) and validation (V) cohorts. Serum samples obtained from moderate and severe asthma patients diagnosed as per GINA guidelines [n = 34(D); n = 32(V)], moderate and severe COPD cases identified by GOLD guidelines [n = 30(D); 32(V)], ACO patients diagnosed by joint GOLD and GINA guidelines [n = 35(D); 40(V)] and healthy controls [n = 33(D)] were characterized using nuclear magnetic resonance (NMR) spectrometry. RESULTS Multivariate and univariate analysis indicated that 12 metabolites [lipid, isoleucine, N-acetylglycoproteins (NAG), valine, glutamate, citric acid, glucose, L-leucine, lysine, asparagine, phenylalanine and histidine] were dysregulated in ACO patients when compared with both asthma and COPD. These metabolites were further validated in a fresh cohort of patients, which again exhibited a similar expression pattern. CONCLUSIONS Our findings suggest that ACO has an enhanced energy and metabolic burden associated with it as compared to asthma and COPD. It is anticipated that our results will stimulate researchers to further explore ACO and unravel the pathophysiological complexities associated with the disease.
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Affiliation(s)
- Nilanjana Ghosh
- School of Medical Science and Technology (SMST), Indian Institute of Technology Kharagpur, Kharagpur, 721302, India
| | - Priyanka Choudhury
- School of Medical Science and Technology (SMST), Indian Institute of Technology Kharagpur, Kharagpur, 721302, India
| | - Elavarasan Subramani
- School of Medical Science and Technology (SMST), Indian Institute of Technology Kharagpur, Kharagpur, 721302, India
| | | | | | - Mamata Joshi
- National Facility for High-field NMR, Tata Institute of Fundamental Research, Mumbai, India
| | - Rintu Banerjee
- Department of Agricultural & Food Engineering, Indian Institute of Technology Kharagpur, Kharagpur, India
| | | | | | - Koel Chaudhury
- School of Medical Science and Technology (SMST), Indian Institute of Technology Kharagpur, Kharagpur, 721302, India.
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Alterations of Sphingolipid Metabolism in Different Types of Polycystic Ovary Syndrome. Sci Rep 2019; 9:3204. [PMID: 30824725 PMCID: PMC6397209 DOI: 10.1038/s41598-019-38944-6] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2018] [Accepted: 12/07/2018] [Indexed: 02/07/2023] Open
Abstract
The roles of sphingolipids in polycystic ovary syndrome (PCOS) are still unknown. This study aimed to investigate the sphingolipid characteristics for different types of PCOS using liquid chromatography-mass spectrometry (LC-MS). A total of 107 women with PCOS and 37 healthy women as normal controls were studied. PCOS patients were further classified into non-obesity with insulin resistance (IR) (NOIR), obesity with IR (OIR), and non-obesity and non-IR (NIR) subgroups. A total of 87 serum sphingolipids, including 9 sphingosines, 3 sphinganines, 1 sphingosine-1-phosphate (S1P), 19 ceramides (Cers), 1 ceramide-1-phosphate, 44 sphingomyelins (SMs), 4 hexosylceramides, and 6 lactosylceramides (LacCers) were analyzed using an improved sphingolipidomic approach based on LC-MS. Notable elevations in the levels of S1P, Cer, and SM were observed in PCOS patients when compared with healthy women, and SM species with long saturated acyl chains showed potential as novel biomarkers of PCOS. In addition, the level of LacCer was only elevated in NIR, and there was almost no change in NOIR and OIR. This study is the first to report the comprehensive sphingolipidomic profiling of different subgroups of PCOS with or without IR or obesity and suggests that serum sphingolipids might be useful as diagnostic biomarkers for different types of PCOS.
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Castiglione Morelli MA, Iuliano A, Schettini SCA, Petruzzi D, Ferri A, Colucci P, Viggiani L, Cuviello F, Ostuni A. NMR metabolic profiling of follicular fluid for investigating the different causes of female infertility: a pilot study. Metabolomics 2019; 15:19. [PMID: 30830455 DOI: 10.1007/s11306-019-1481-x] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/03/2018] [Accepted: 01/21/2019] [Indexed: 12/13/2022]
Abstract
INTRODUCTION Several metabolomics studies have correlated follicular fluid (FF) metabolite composition with oocyte competence to fertilization, embryo development and pregnancy but there is a scarcity of research examining the metabolic effects of various gynaecological diseases. OBJECTIVES In this study we aimed to analyze and correlate the metabolic profile of FF from women who were following in vitro fertilization (IVF) treatments with their different infertility pathologies. METHODS We selected 53 women undergoing IVF who were affected by: tubal diseases, unexplained infertility, endometriosis, polycystic ovary syndrome (PCOS). FF of the study participants was collected at the time of oocytes retrieval. Metabolomic analysis of FF was performed by nuclear magnetic resonance (NMR) spectroscopy. RESULTS FF presents some significant differences in various infertility pathologies. Although it was not possible to discriminate between FF of control participants and women with tubal diseases and unexplained infertility, comparison of FF metabolic profile from control women with patients with endometriosis and PCOS revealed significant differences in some metabolites that can be correlated to the causes of infertility. CONCLUSION NMR-based metabolic profiling may be successfully applied to find diagnostic biomarkers for PCOS and endometriosis and it might be also used to predict oocyte developmental potential and subsequent outcome.
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Affiliation(s)
| | - Assunta Iuliano
- Center for Reproductive Medicine of "San Carlo" Hospital, via Potito Petrone, 85100, Potenza, Italy
| | | | - Donatina Petruzzi
- Center for Reproductive Medicine of "San Carlo" Hospital, via Potito Petrone, 85100, Potenza, Italy
| | - Angela Ferri
- Center for Reproductive Medicine of "San Carlo" Hospital, via Potito Petrone, 85100, Potenza, Italy
| | - Paola Colucci
- Center for Reproductive Medicine of "San Carlo" Hospital, via Potito Petrone, 85100, Potenza, Italy
| | - Licia Viggiani
- Department of Sciences, University of Basilicata, viale Ateneo Lucano 10, 85100, Potenza, Italy
| | - Flavia Cuviello
- Department of Sciences, University of Basilicata, viale Ateneo Lucano 10, 85100, Potenza, Italy
| | - Angela Ostuni
- Department of Sciences, University of Basilicata, viale Ateneo Lucano 10, 85100, Potenza, Italy.
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Lent-Schochet D, McLaughlin M, Ramakrishnan N, Jialal I. Exploratory metabolomics of metabolic syndrome: A status report. World J Diabetes 2019; 10:23-36. [PMID: 30697368 PMCID: PMC6347655 DOI: 10.4239/wjd.v10.i1.23] [Citation(s) in RCA: 58] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2018] [Revised: 01/04/2019] [Accepted: 01/08/2019] [Indexed: 02/05/2023] Open
Abstract
Metabolic syndrome (MetS) is as a cluster of cardio-metabolic factors that greatly increase the risk of chronic diseases such as type II diabetes mellitus and atherosclerotic cardiovascular disease. In the United States, obesity, physical inactivity, aging, and genetics (to a minor extent) have arisen as risk factors for developing MetS. Although 35% of American adults suffer from MetS, its pathogenesis largely remains unknown. Worse, there is a lack of screening and optimum therapy for this disease. Researchers have consequently turned towards metabolomics to identify biomarkers to better understand MetS. The purpose of this review is to characterize various metabolites and their potential connections to MetS. Numerous studies have also characterized MetS as a disease of increased inflammation, and therefore this review also explores how metabolites play a role in various inflammatory pathways. Our review explores a broad range of metabolites including biogenic amines, branched chain amino acids, aromatic amines, phosphatidylcholines, as well as a variety of other molecules. We will explore their biochemical pathways and their potential role in serving as biomarkers.
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Affiliation(s)
- Daniella Lent-Schochet
- Metabolism and Clinical Pathology, College of Medicine, California Northstate University, Elk Grove, CA 95757, United States
| | - Matthew McLaughlin
- Metabolism and Clinical Pathology, College of Medicine, California Northstate University, Elk Grove, CA 95757, United States
| | - Neeraj Ramakrishnan
- Metabolism and Clinical Pathology, College of Medicine, California Northstate University, Elk Grove, CA 95757, United States
| | - Ishwarlal Jialal
- Metabolism and Clinical Pathology, College of Medicine, California Northstate University, Elk Grove, CA 95757, United States
- VA Medical Center, Mather CA 95655, United States
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Zou Y, Zhu FF, Fang CY, Xiong XY, Li HY. Identification of Potential Biomarkers for Urine Metabolomics of Polycystic Ovary Syndrome Based on Gas Chromatography-Mass Spectrometry. Chin Med J (Engl) 2018; 131:945-949. [PMID: 29664055 PMCID: PMC5912061 DOI: 10.4103/0366-6999.229899] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022] Open
Abstract
Background: Polycystic ovary syndrome (PCOS) is a complex endocrine and metabolic disorder, and it's diagnosis is difficult. The aim of this study was to investigate the metabolic profiles of PCOS patients by analyzing urine samples and identify useful biomarkers for diagnosis of PCOS. Methods: This study was carried out in the Department of Obstetrics and Gynecology of the Maternal and Child Health Hospital of Hunan Province from December 2014 to July 2016. In this study, the urine samples of 21 women with PCOS and 16 healthy controls were assessed through gas chromatography-mass spectrometry to investigate the urine metabolite characteristics of PCOS and identify useful biomarkers for the diagnosis of this disorder. The Student's t-test and rank sum test were applied to validate the statistical significance of the between the two groups. Results: In total, 35 urine metabolites were found to be significantly different between the PCOS patients and the controls. In particular, a significant increase in the levels of lactose (10.01 [0,13.99] mmol/mol creatinine vs. 2.35 [0.16, 3.26] mmol/mol creatinine, P = 0.042), stearic acid (2.35 [1.47, 3.14] mmol/mol creatinine vs. 0.05 [0, 0.14] mmol/mol creatinine, P < 0.001), and palmitic acid (2.13 [1.07, 2.79] mmol/mol creatinine vs. 0 [0, 0] mmol/mol creatinine, P < 0.001) and a decrease in the levels of succinic acid (0 [0, 0] mmol/mol creatinine vs. 38.94 [4.16, 51.30] mmol/mol creatinine, P < 0.001) were found in the PCOS patients compared with the controls. It was possible to cluster the PCOS patients and the healthy controls into two distinct regions based on a principal component analysis model. Of the differentially expressed metabolites, four compounds, including stearic acid, palmitic acid, benzoylglycine, and threonine, were selected as potential biomarkers. Conclusions: This study offers new insight into the pathogenesis of PCOS, and the discriminating urine metabolites may provide a prospect for the diagnosis of PCOS.
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Affiliation(s)
- Ying Zou
- Department of Obstetrics and Gynecology, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
| | - Fu-Fan Zhu
- Department of Obstetrics and Gynecology, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
| | - Chao-Ying Fang
- Department of Obstetrics and Gynecology, Maternal and Child Health Hospital of Hunan Province, Changsha, Hunan 410008, China
| | - Xi-Yue Xiong
- Department of Obstetrics and Gynecology, Maternal and Child Health Hospital of Hunan Province, Changsha, Hunan 410008, China
| | - Hong-Yun Li
- Department of Obstetrics and Gynecology, Maternal and Child Health Hospital of Hunan Province, Changsha, Hunan 410008, China
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Chang AY, Lalia AZ, Jenkins GD, Dutta T, Carter RE, Singh RJ, Nair KS. Combining a nontargeted and targeted metabolomics approach to identify metabolic pathways significantly altered in polycystic ovary syndrome. Metabolism 2017; 71:52-63. [PMID: 28521878 PMCID: PMC5520539 DOI: 10.1016/j.metabol.2017.03.002] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2016] [Revised: 02/27/2017] [Accepted: 03/01/2017] [Indexed: 01/03/2023]
Abstract
OBJECTIVE Polycystic ovary syndrome (PCOS) is a condition of androgen excess and chronic anovulation frequently associated with insulin resistance. We combined a nontargeted and targeted metabolomics approach to identify pathways and metabolites that distinguished PCOS from metabolic syndrome (MetS). METHODS Twenty obese women with PCOS were compared with 18 obese women without PCOS. Both groups met criteria for MetS but could not have diabetes mellitus or take medications that treat PCOS or affect lipids or insulin sensitivity. Insulin sensitivity was derived from the frequently sampled intravenous glucose tolerance test. A nontargeted metabolomics approach was performed on fasting plasma samples to identify differentially expressed metabolites, which were further evaluated by principal component and pathway enrichment analysis. Quantitative targeted metabolomics was then applied on candidate metabolites. Measured metabolites were tested for associations with PCOS and clinical variables by logistic and linear regression analyses. RESULTS This multiethnic, obese sample was matched by age (PCOS, 37±6; MetS, 40±6years) and body mass index (BMI) (PCOS, 34.6±5.1; MetS, 33.7±5.2kg/m2). Principal component analysis of the nontargeted metabolomics data showed distinct group separation of PCOS from MetS controls. From the subset of 385 differentially expressed metabolites, 22% were identified by accurate mass, resulting in 19 canonical pathways significantly altered in PCOS, including amino acid, lipid, steroid, carbohydrate, and vitamin D metabolism. Targeted metabolomics identified many essential amino acids, including branched-chain amino acids (BCAA) that were elevated in PCOS compared with MetS. PCOS was most associated with BCAA (P=.02), essential amino acids (P=.03), the essential amino acid lysine (P=.02), and the lysine metabolite α-aminoadipic acid (P=.02) in models adjusted for surrogate variables representing technical variation in metabolites. No significant differences between groups were observed in concentrations of free fatty acids or vitamin D metabolites. Evaluation of the relationship of metabolites with clinical characteristics showed 1) negative associations of essential and BCAA with insulin sensitivity and sex hormone-binding globulin and 2) positive associations with homeostasis model of insulin resistance and free testosterone; metabolites were not associated with BMI or percent body fat. CONCLUSIONS PCOS was associated with significant metabolic alterations not attributed exclusively to androgen-related pathways, obesity, or MetS. Concentrations of essential amino acids and BCAA are increased in PCOS, which might result from or contribute to their insulin resistance.
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Affiliation(s)
- Alice Y Chang
- Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic, Rochester, MN.
| | - Antigoni Z Lalia
- Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic, Rochester, MN
| | - Gregory D Jenkins
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN
| | - Tumpa Dutta
- Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic, Rochester, MN
| | - Rickey E Carter
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN
| | - Ravinder J Singh
- Division of Clinical Biochemistry and Immunology, Mayo Clinic, Rochester, MN
| | - K Sreekumaran Nair
- Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic, Rochester, MN
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Schofield Z, Reed MAC, Newsome PN, Adams DH, Günther UL, Lalor PF. Changes in human hepatic metabolism in steatosis and cirrhosis. World J Gastroenterol 2017; 23:2685-2695. [PMID: 28487605 PMCID: PMC5403747 DOI: 10.3748/wjg.v23.i15.2685] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/21/2016] [Revised: 01/11/2017] [Accepted: 03/15/2017] [Indexed: 02/06/2023] Open
Abstract
AIM To understand the underlying metabolic changes in human liver disease we have applied nuclear magnetic resonance (NMR) metabolomics analysis to human liver tissue.
METHODS We have carried out pilot study using 1H-NMR to derive metabolomic signatures from human liver from patients with steatosis, nonalcoholic steatohepatitis (NASH) or alcohol-related liver damage (ARLD) to identify species that can predict outcome and discriminate between alcohol and metabolic-induced liver injuries.
RESULTS Changes in branched chain amino acid homeostasis, tricarboxylic acid cycle and purine biosynthesis intermediates along with betaine were associated with the development of cirrhosis in both ARLD and nonalcoholic fatty liver disease. Species such as propylene glycol and as yet unidentified moieties that allowed discrimination between NASH and ARLD samples were also detected using our approach.
CONCLUSION Our high throughput, non-destructive technique for multiple analyte quantification in human liver specimens has potential for identification of biomarkers with prognostic and diagnostic significance.
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