Egg weight is a primary economic trait in poultry breeding. Putian Black duck, an excellent local laying duck breed in Fujian Province, includes two different strains, black feather strain and white feather strain. The white feather strain of Putian Black duck is also known as Putian White duck. Except for the different feather colors, these two strains differ in egg weight. In this study, whole-genome resequencing was conducted on Putian Black duck and Putian White duck to explore the differences in the genetic mechanism of egg weight. LRP8, VLDLR, and LPL were identified as key candidate genes affecting egg weight. Mass spectrometry was used to detect the SNPs of LRP8, VLDLR, and LPL. Result indicates that the SNPs of LRP8, VLDLR, and LPL in both populations exhibited moderate polymorphism, and Putian Black duck possessed higher genetic variation and potential selectivity. Association analysis indicated that in Putian Black duck, four SNPs in the LRP8 gene were significantly associated with egg weight. These loci can be used as molecular markers for improving egg weight in Putian Black duck.

It is estimated that 40-50% of severe asthma has an atopic basis, representing a clinical challenge and a significant economic burden for healthcare systems. The most effective treatment has emerged with the use of biologic therapies such as omalizumab; however, the rate of therapy switching due to loss of efficacy is high, which has a negative impact on the healthcare system. The aim was to evaluate the influence of genetic polymorphisms as predictors of omalizumab survival. We conducted a retrospective observational cohort study of 110 patients with uncontrolled severe allergic asthma treated with omalizumab in a tertiary hospital. We analyzed FCER1A (rs2251746, rs2427837), FCER1B (rs1441586, rs573790, rs1054485, rs569108), C3 (rs2230199), FCGR2A (rs1801274), FCGR2B (rs3219018, rs1050501), FCGR3A (rs10127939, rs396991), IL1RL1 (rs1420101, rs17026974, rs1921622) and GATA2 (rs4857855) by real-time PCR using Taqman probes. Drug survival was defined as the time from initiation to discontinuation of omalizumab. Cox regression analysis adjusted for the presence of respiratory disease, GERD, SAHS and years with asthma showed that the SNPs FCER1B rs573790 - CT (p < .001; HR = 3.38; CI95% = 1.66-6.87), FCGR3A rs10127939-AC (p = .018; HR = 3.85; CI95% = 1.25-11.81) and FCGR3A rs396991-CC (p = .020; HR = 2.23; CI95% = 1.14-4.38) were the independent variables associated with worse survival in patients diagnosed with asthma. A trend toward statistical significance was also found between and FCGR3A rs10127939-CC (p = .080; HR = 0.13; CI95% = 0.01-1.28) and longer drug survival. The results of this study demonstrate the potential influence of the polymorphisms studied on omalizumab survival and the clinical benefit that could be achieved by defining predictive biomarkers of drug survival.

Major depressive disorder (MDD) is a polygenic condition with substantial heritability, with genome-wide association studies (GWAS) identifying several risk loci in European populations, including the VRK2 gene. However, the association between VRK2 and MDD in non-European populations, particularly in Han Chinese, remains underexplored.

We genotyped four VRK2 SNPs (rs2678907, rs11682175, rs1568452, rs1518395) in a cohort of 1878 MDD cases and 1800 controls of Han Chinese descent. Genotyping was performed using SNaPShot, and linkage disequilibrium (LD) was assessed with SHEsis. Associations between the SNPs and MDD were evaluated via logistic regression in PLINK. VRK2 mRNA expression in the amygdala and peripheral blood was quantified by RT-qPCR, with statistical significance determined by ANCOVA and t-tests. A meta-analysis incorporating an independent East Asian GWAS cohort was also conducted.

In our Han Chinese cohort, rs2678907 was significantly associated with MDD (P = 4.17 × 10-5, OR = 1.217). Meta-analysis with independent East Asian GWAS further confirmed the associations of rs2678907 with MDD. Haplotype analysis of VRK2 SNPs in Han Chinese revealed the haplotypes (T-G for rs11682175-rs2678907 and C-G for rs1568452-rs2678907) associated with an increased MDD risk and elevated VRK2 mRNA expression. Additionally, MDD patients showed significantly higher VRK2 mRNA levels in peripheral blood than controls (P = 1.85 × 10-7).

These findings provide strong evidence for the role of VRK2 in MDD risk in Han Chinese individuals. Our results underscore the potential of VRK2 as a genetic and expression-based biomarker for MDD, highlighting the importance of accounting for population-specific genetic variations in psychiatric research. Further research is essential to explore the functional implications of VRK2 in MDD pathogenesis.

Indian-origin Gir and Ongole cattle are international transboundary breeds that are reared in Brazil, The United States, Mexico, Malaysia, Panama, and other nations to provide meat and dairy products. These breeds have shown substantial genetic diversity in recent years and well suited to the ecological niche in Brazil. 90 cattle samples of Indian Gir (n = 15), Ongole (n = 17), Brazilian Gyr (n = 27), and Nellore (n = 31) breeds were genotyped using Illumina BovineHD BeadChip. Samples were analyzed to identify selection signatures using two complementing approaches: Integrated Haplotype Score (iHS) and Fixation Index (FST). Gir versus Gyr and Ongole versus Nellore revealed Pairwise FST differences of 2.85 % and 2.35 %, respectively. Using integrated haplotype score (iHS) method, 4004, 3322, 3437, and 3485 genes were found in Gir, Gyr, Ongole, and Nellore, respectively, underlying top 1 % of selected regions. Under top 1 % of selected regions, FST based method identified1897 genes for the Ongole-Nellore pair and 1966 genes for the Gir-Gyr pair. Runs of homozygosity (ROH) analysis revealed that both recent as well as ancient inbreeding in these breeds were in range of 2.6-4.5 % indicating populations to be less inbred. Numerous candidate genes, including IER5, MILR1 (immunity related traits) in Gir; and FGF12, SV2C, JMY (average daily gain, body size, reproduction related traits) in Ongole, were found under the top-selected regions. Nellore breed had carcass/growth traits (PARP2, and KCNJ11) and genes linked to mammary gland development, udder size, and carcass (MYO16, MYO1B) were found in Gyr. Present findings reveals that Brazilian cattle population (Gyr and Nellore) is more selected for carcass and growth traits along with milk production traits, whereas in Indian cattle population (Gir and Ongole) selection signature related to immunity and adaptation were more prominent. Further, sufficient genetic diversity exist within these cattle breeds for their genetic improvement.

Angiotensin-converting enzyme inhibitor-induced angioedema (AE-ACEI) is a life-threatening adverse event; globally, it is the most common cause of emergency presentations with angioedema. Several genome-wide association studies (GWASs) have found genomic associations with AE-ACEI. However, despite African Americans having a 5-fold increased risk of AE-ACEI, there are no published GWASs from Africa.

The aim of this study was to conduct a GWAS of AE-ACEI in a South African population and perform a meta-analysis with an African American and European American population.

The GWAS included 202 South African adults with a history of AE-ACEI and 513 controls without angioedema following angiotensin-converting enzyme inhibitor (ACEI) treatment for at least 2 years. A meta-analysis was conducted with GWAS summary statistics from an African American and European American cohort (from the Vanderbilt-Marshfield cohort, which consisted of 174 case patients and 489 controls).

No single-nucleotide polymorphisms (SNPs) attained genome-wide significance; however, 26 SNPs in the postimputation standard GWAS of the South African cohort and 73 SNPs in the meta-analysis attained suggestive thresholds (P < 5.0 × 10-06). Some of these SNPs were found to be located close to the genes PRKCQ (protein kinase C theta), RAD51B (RAD51 Paralog B), and RIMS1 (regulating synaptic membrane exocytosis 1), which were previously linked with drug-induced angioedema, and also close to the CSMD1 (CUB and sushi multiple domains 1) gene, which has been linked to ACEI cough, providing replication at the gene level but with novel lead SNPs. The study also replicated SNP rs500766 on chromosome 10, which was previously found to be associated with AE-ACEI.

Our results highlight the importance of African populations for detection of novel variants in replication studies. Further increased sampling across the continent and matched functional work are needed to confirm the importance of genetic variation in understanding the biology of AE-ACEI.

The development of posttraumatic stress disorder (PTSD) is attributable to the interplay between exposure to severe traumatic events, environmental factors, and biological characteristics. Blood and brain imaging markers have been associated with PTSD. However, to our knowledge, no study has systematically investigated the genetic relationship between PTSD, metabolic biomarkers, and brainwide imaging.

We integrated genome-wide data informative of PTSD, 233 metabolic biomarkers, and 3935 brain imaging-derived phenotypes (IDPs). Pleiotropy was assessed by applying global and local genetic correlation, colocalization, and genetically inferred causality.

We observed significant genetic overlap between PTSD and glycoprotein acetyls (GlycA) (a stable inflammatory biomarker) in 2 independent cohorts (discovery r g = 0.26, p = 1.00 × 10-4; replication r g = 0.23, p = 5.99 × 10-19). Interestingly, there was no genetic correlation between anxiety and GlycA (p = .33). PTSD and GlycA were both genetically correlated with median T2∗ in the left pallidum (IDP-1444: r g = 0.14, p = 1.39 × 10-5; r g = -0.38, p = 2.50 × 10-3, respectively). Local genetic correlation between PTSD and GlycA was observed in 7 genetic regions (p < 2.0 × 10-5), mapping genes related to immune and stress response, inflammation, and metabolic processes. Furthermore, we identified 1 variant, rs12048743, with evidence of horizontal pleiotropy linking GlycA and IDP-1444 (z IDP-1444 = 17.14, z GlycA = -6.07, theta p = 2.06 × 10-8). Regional colocalization was observed among GlycA, IDP-1444, and tissue-specific transcriptomic regulation for brain frontal cortex and testis (rs12048743-chr1q32.1; posterior probability > 0.8). While we also tested causality between PTSD, metabolomic biomarkers, and brain IDPs, these were not consistent across different genetically informed causal inference methods.

Our findings highlight a new putative pleiotropic mechanism that links systemic inflammation and pallidum structure to PTSD.

Hyperglycemia and diabetes may influence GBM progression by altering tumor metabolism and the tumor microenvironment. However, the causal relationship between blood glucose levels and GBM remains unclear.

Mendelian randomization (MR) analysis was performed using GWAS data from the UK Biobank and FinnGen databases, with fasting blood glucose, plasma glucose, cerebrospinal fluid (CSF) glucose, and diabetes as exposures. Single-cell RNA sequencing of GBM mouse models on high-glucose and control diets was conducted to explore the cellular landscape of the tumor microenvironment under hyperglycemic conditions. Additionally, gene set enrichment analysis (GSEA) was performed on transcriptomic data from brain tissues of diabetic patients to assess the activity of GBM-related pathways.

MR analysis demonstrated a significant genetic relationship between elevated fasting blood glucose and GBM risk, with an odds ratio (OR) of 40.991 (95 % CI: 2.066-813.447, p = 0.015). Type 2 diabetes (T2D) also showed a potential causal link with GBM, with the Weighted Median and Inverse Variance Weighted methods yielding ORs of 2.740 (95 % CI: 1.033-7.273, p = 0.043) and 2.100 (95 % CI: 1.029-4.287, p = 0.042), respectively. Single-cell transcriptomic analysis of GBM mouse models revealed an increased proportion of GBM tumor stem cells and pro-tumorigenic M2 macrophages in the high-glucose diet (HGD) group. GSEA of diabetic patient brain tissue revealed heightened activity of GBM-related pathways, particularly in astrocytes, endothelial cells, and neurons.

These findings suggest that hyperglycemia may actively contribute to GBM progression by promoting cellular changes within the tumor microenvironment and activating GBM-related pathways in brain tissues.

In the late 1950s, Katahdin hair sheep were developed as a composite breed of medium size and moderate prolificacy, with potential to express resistance to gastrointestinal nematodes. With increasing popularity and the recent adoption of genomic prediction in their genetic evaluation, there is a risk of decreasing variation with selection based on genomically enhanced estimated breeding values. While Katahdin pedigrees are readily available for monitoring diversity, they may not capture the entirety of genetic relationships. We aimed to characterise the genomic population structure and diversity present in the breed, and how these impact the size of a reference population necessary to achieve accurate genomic predictions. Genotypes of Katahdin sheep from 81 member flocks in the National Sheep Improvement Program (NSIP) were used. After quality control, there were 9704 animals and 31,984 autosomal single nucleotide polymorphisms analysed. Population structure was minimal as a single ancestral population explained 99.9% of the genetic variation among animals. The current Ne was estimated to be 150, and despite differences in trait heritabilities, the effect of Ne on the accuracy of genomic predictions suggested the breed should aim for a reference population size of 15,000 individuals. The average degree of inbreeding estimated from runs of homozygosity (ROH) was 16.6% ± 4.7. Four genomic regions of interest, previously associated with production traits, contained ROH shared among > 50% of the breed. Based on four additional methods, average genomic inbreeding coefficients ranged from 0.011 to 0.012. The current population structure and diversity of the breed reflects genetic connectedness across flocks due to the sharing of animals. Shared regions of ROH should be further explored for incorporation of functional effects into genomic predictions to increase selection gains. Negative impacts on genetic diversity due to genomic selection are not of immediate concern for Katahdin sheep engaged in NSIP.

The comorbidity between bipolar disorder (BD) and high body mass index (BMI) is well-documented, but their shared genetic architecture remains unclear. Our study aimed to explore this genetic correlation and potential causality.

Utilizing large-scale genome-wide association study (GWAS) summary statistics, we quantified global and local genetic correlations between BD and BMI using linkage disequilibrium score regression (LDSC) and Heritability Estimation from Summary Statistics. Stratified LDSC characterized genetic overlap across functional categories. Cross-trait meta-analyses identified shared risk single nucleotide polymorphisms (SNPs), followed by colocalization analysis using Coloc. Bi-directional Mendelian randomization (MR) assessed causality, while tissue-level SNP heritability enrichment for BD and BMI was evaluated using LDSC-specific expressed genes and Multi-marker Analysis of Genomic Annotation.

We found a genetic correlation between BD and BMI, especially in localized genomic regions. Cross-trait meta-analysis identified 46 significant SNPs shared between BD and BMI, including three novel shared risk SNPs. Colocalization analysis verified two novel SNPs with shared causal variants linked to ITIH1 and TM6SF2 genes. MR analysis demonstrated a causal effect of BD on BMI, but not the reverse. Gene expression data revealed genetic correlation enrichment in five specific brain regions.

This study comprehensively analyzes the genetic correlation between BD and BMI, uncovering shared genetic architecture and identifying novel risk loci. These findings provide new insights into the interplay between BD and BMI, informing the development of diagnostic tools and therapeutic strategies.

The rising prevalence of youth depression underscores the need to identify modifiable factors for prevention and intervention. This study aims to investigate the protective role of Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) diet on depressive symptoms in adolescents.

Participants were identified from the Adolescent Brain Cognitive Development study. Adherence to the MIND diet was measured by the Child Nutrition Assessment or the Block Kids Food Screener. Depressive symptoms were measured annually using the Child Behavior Checklist's depression subscale. We utilized regression analyses and cross-lagged panel modeling (CLPM) to examine longitudinal associations. Additional analyses adjusted for polygenic risk scores for depression, and changes in Body Mass Index (BMI) and waist-to-height ratio.

Of the 8459 children (52.3 % male; mean age 10.9 [SD, 0.6] years), 2338 (27.6 %) demonstrated high MIND diet adherence, while 2120 (25.1 %) showed low adherence. High adherence was prospectively associated with reduced depressive symptoms (adjusted β, -0.64, 95 % CI, -0.73 to -0.55; p < 0.001) and 46 % lower odds of clinically relevant depression (adjusted odds ratio, 0.54, 95 % CI, 0.39 to 0.75; p < 0.001) at two-year follow-up. CLPM analyses showed significant cross-lag paths from MIND diet scores to less depressive symptoms across three time points. These associations persisted independently of changes in BMI and waist-to-height ratios, and were not significantly moderated by genetic predisposition to depression.

Higher adherence to the MIND dietary pattern was longitudinally associated with decreased risk of depressive symptoms in adolescents. Promoting MIND diet may represent a promising strategy for depression prevention in adolescent populations.

Recent studies have linked branched-chain amino acids (BCAAs) metabolism with the risk of major depressive disorder (MDD). However, it is unclear whether associations of plasma BCAA levels with MDD are causal or driven by reverse causality.

Mendelian randomization (MR) was used to investigate the causal association of genetically determined BCAA levels with the risk of MDD. The large genome-wide association study (GWAS) datasets on plasma BCAA levels (n = 115,051) were obtained from the UK Biobank. The summary GWAS dataset for MDD was obtained from the Psychiatric Genomics Consortium (n = 1,035,760). We applied the inverse variance-weighted (IVW) method to explore the causal relationships between BCAA levels and MDD, followed by multiple pleiotropy and heterogeneity tests.

Our results demonstrated that genetically determined circulating total BCAAs (odds ratio (OR): 1.05, 95 % confidence interval (CI): 1.01-1.10, P = 0.016), leucine (OR: 1.06, 95 % CI: 1.02-1.11, P = 7.22 × 10-3), and isoleucine (OR: 1.08, 95 % CI: 1.01-1.16, P = 0.032) levels were associated with an increased risk of MDD. There was suggestive evidence supporting the causal effect of valine levels on MDD (OR: 1.04, 95 % CI: 1.00-1.08, P = 0.075). Bidirectional MR analysis did not provide evidence of reverse causality.

We report evidence supporting the causal role of BCAAs in the development of MDD. This study offers new insights into the mechanisms and treatment of MDD.

The growing prevalence of dementia emphasizes the need for effective prevention strategies. Although the partial efficacy of multidomain interventions for dementia prevention has been demonstrated, understanding the characteristics of individuals who benefit most from these interventions is crucial for optimizing resource allocation. This study investigated the association between participants' genetic backgrounds and the effectiveness of multidomain interventions for preventing dementia.

This study utilized data from the Japan-Multimodal Intervention Trial for the Prevention of Dementia (J-MINT), where older adults with mild cognitive impairment underwent 18 months of multidomain intervention. The intervention included exercise, nutrition, cognitive stimulation, social participation, and vascular risk management. Participants who completed the J-MINT intervention and had genetic data, including whole-genome sequencing (WGS), were analyzed. Using Japanese polygenic risk scores (PRSs) for Alzheimer's disease, participants were stratified into high- and low-genetic-risk groups. Cognitive composite score (CPS) improvement rates at 6-, 12-, and 18-months were compared between intervention and control groups, with subgroup analyses performed by age (< 75 and ≥ 75 years). Additionally, a comprehensive variant analysis using WGS was conducted to identify genetic signals potentially associated with the intervention's effectiveness.

Among 289 participants analyzed (168 aged < 75 years; 121 aged ≥ 75 years), 99 were classified into the high-risk PRS group (56 intervention, 43 control) and 190 into the low-risk PRS group (92 intervention, 98 control). For participants aged ≥ 75 years, no statistically significant differences in CPS improvement rates were observed between the intervention and control groups, regardless of PRS classification. However, in participants aged < 75, those in the high-risk PRS group showed significant CPS improvement at the 6-month follow-up. Additionally, analysis of 9,978,605 genetic variants identified two loci, ID3 and LMO1 (rs2067053 and rs201082658), with suggestive associations (P < 1 × 10⁻4) to reduced intervention effectiveness.

This study highlighted the utility of PRS in predicting cognitive improvement following multidomain interventions and identified genetic variants that may influence the intervention's effectiveness. The findings provide a valuable foundation for personalized dementia prevention strategies.

Polygenic scores (PGS) are widely used in psychiatric genetic associations studies due to their predictive power for focal outcomes. However, they lack discriminatory power, in part due to the high degree of genetic overlap between psychiatric disorders. The lack of prediction specificity limits the clinical utility of psychiatric PGS, particularly for diagnostic applications. The goal of the study was to enhance the discriminatory power of psychiatric PGS for two highly comorbid and genetically correlated neurodevelopmental disorders in ADHD and autism spectrum disorder (ASD).

Genomic structural equation modeling (GenomicSEM) was used to generate novel PGS for ADHD and ASD by accounting for the genetic overlap between these disorders (and eight others) to achieve greater discriminatory power in non-focal outcome predictions. PGS associations were tested in two large independent samples - the Philadelphia Neurodevelopmental Cohort (N = 4,789) and the Simons Foundation Powering Autism Research for Knowledge (SPARK) ASD and sibling controls (N = 5,045) cohort.

PGS from GenomicSEM achieved superior discriminatory power in terms of showing significantly attenuated associations with non-focal outcomes relative to traditionally computed PGS for these disorders. Additionally, genetic correlations between GenomicSEM PGS for ASD and ADHD were significantly attenuated in cross-trait associations with other psychiatric disorders and outcomes.

Psychiatric PGS associations are likely inflated by the high degree of genetic overlap between the psychiatric disorders. Methods such as GenomicSEM can be used to refine PGS signals to be more disorder-specific, thereby enhancing their discriminatory power for future diagnostic applications.

Hybridization and interspecific gene flow play a substantial role in the evolution of plant taxa. The eastern North American white oak syngameon, a group of approximately 15 ecologically, morphologically and genomically distinguishable species, has long been recognised as a model system for studying introgressive hybridization in temperate trees. However, the prevalence, genomic context and environmental correlates of introgression in this system remain largely unknown. To assess introgression in the eastern North American white oak syngameon and population structure within the widespread Quercus macrocarpa, we conducted a rangewide survey of Q. macrocarpa and four sympatric eastern North American white oak species. Using a Hyb-Seq approach, we assembled a dataset of 3412 thinned single-nucleotide polymorphisms (SNPs) in 445 enriched target loci including 62 genes putatively associated with various ecological functions, as well as associated intronic regions and some off-target intergenic regions (not associated with the exons). Admixture analysis and hybrid class inference demonstrated species coherence despite hybridization and introgressive gene flow (due to backcrossing of F1s to one or both parents). Additionally, we recovered a genetic structure within Q. macrocarpa associated with latitude. Generalised linear mixed models (GLMMs) indicate that proximity to range edge predicts interspecific admixture, but rates of genetic differentiation do not appear to vary between putative functional gene classes. Our study suggests that gene flow between eastern North American white oak species may not be as rampant as previously assumed and that hybridization is most strongly predicted by proximity to a species' range margin.

Taste liking, a complex trait, plays an important role in food choice and eating behavior, thereby influencing the risk of diet-related diseases.

This study aimed to identify novel loci that could explain differences in liking of basic tastes, fat and oral sensations, represented by several food items.

Liking scores were derived using a newly developed taste liking questionnaire (TasteLQ), validated in the Danish population. We conducted a genome-wide association study (GWAS) of liking of six modalities (sweet, salty, sour, bitter-astringency, umami, and pungency) and nine factors representing modality subgroups among 6,437 Danish adults. As a secondary analysis, GWASs of 44 single food items from TasteLQ were also undertaken.

We identified one genome-wide significant variant, rs170518 (MAF=0.16), on chromosome 5, associated with liking of an umami factor characterized by glutamate-rich food items (P=3.7x10-8, beta=0.14 standard deviation (SD) (Standard error (SE)=0.03). When analyzing individual food items, four SNPs within one locus, annotated to the bitter taste receptor gene, TAS2R38, were associated with liking of bitter-tasting rocket salad. Finally, our data confirmed some of the previously associated genomic variants with taste perception, food liking, and intake.

While our findings provide insight into loci involved in taste liking, they remain preliminary and warrant additional validation due to lack of replication in an independent population and limited number of genome-wide significant associations.

Epigenetic mapping studies across individuals have identified many positions of epigenetic variation across the human genome. However the relationships between these positions, and in particular global patterns that recur in many regions of the genome, remains understudied. In this study, we use a stacked chromatin state model to systematically learn global patterns of epigenetic variation across individuals and annotate the human genome based on them. We apply this framework to histone modification data across individuals in lymphoblastoid cell lines and across autism spectrum disorder cases and controls in prefrontal cortex tissue. We find that global patterns are correlated across multiple histone modifications and with gene expression. We use the global patterns as a framework to predict trans-regulators and study a complex disorder. The frameworks for identifying and analyzing global patterns of epigenetic variation are general and we expect will be useful in other systems.

Autism spectrum disorder (ASD) presents a wide range of cognitive and language impairments. In this study, we investigated the genetic basis of non-verbal status in ASD using a comprehensive genomic approach. We identified a novel common variant, rs1944180 in CNTN5, significantly associated with non-verbal status through family-based Transmission Disequilibrium Testing. Polygenic risk score (PRS) analysis further showed that higher ASD PRS was significantly linked to non-verbal status (p = 0.034), specific to ASD and not related to other conditions such as bipolar disorder, schizophrenia and three language-related traits. Using structural equation modeling (SEM), we found two causal SNPs, rs1247761 located in KCNMA1 and rs2524290 in RAB3IL1, linking ASD with language traits. The model indicated a unidirectional effect, with ASD driving language impairments. Additionally, de novo mutations (DNMs) were found to be related with ASD and interaction between common variants and DNMs significantly impacted non-verbal status (p = 0.038). Our findings also identified 5 high-risk ASD genes, and DNMs were enriched in glycosylation-related pathways. These results offer new insights into the genetic mechanisms underlying language deficits in ASD.

Autoimmune thyroid diseases (AITD) are the most common autoimmune disorders. Identifying new biomarkers and therapeutic targets in plasma proteins is crucial. We conducted a proteome-wide Mendelian randomization (MR) and colocalization analysis to determine plasma proteins causally associated with AITD. Proteome-wide summary-level genome-wide association studies (GWAS) were collected from the UK Biobank Pharma Proteomics Project (UKB-PPP) and deCODE genetics, encompassing 2922 and 4719 plasma proteins, respectively. Genetic associations with AITD were derived from an AITD GWAS meta-analysis study (30,234 cases and 725,172 controls) and the FinnGen database (40,926 cases and 274,069 controls). MR analysis, including summary-data-based Mendelian randomization (SMR), Wald Ratio, and IVW methods, was employed to estimate the causal effects between plasma proteins and AITD. Colocalization analysis was used to assess whether identified proteins and AITD shared the common causal variants. Genetically predicted levels of 11 plasma proteins were found to have a causal association with AITD. Colocalization analysis revealed that five of these proteins had evidence of colocalization, including leukemia inhibitory factor (LIF), interleukin-7 receptor subunit alpha (IL7RA), CD226, tumor necrosis factor ligand superfamily member 11 (TNF11), and transcription factor junD (JUND). Genetically predicted levels of LIF and IL7RA were associated with an increased risk of AITD, whereas CD226, TNF11, and JUND were inversely related to AITD risk. This study has identified multiple candidate plasma proteins causally associated with AITD. Among these proteins, LIF, IL7RA, CD226, TNF11, and JUND are considered to have potential as disease biomarkers and therapeutic targets, but further clinical and experimental validation is still necessary in the future.

Recent work leveraging artificial intelligence has offered promise to dissect disease heterogeneity by identifying complex intermediate brain phenotypes, called dimensional neuroimaging endophenotypes (DNEs). We advance the argument that these DNEs capture the degree of expression of respective neuroanatomical patterns measured, offering a dimensional neuroanatomical representation for studying disease heterogeneity and similarities of neurologic and neuropsychiatric diseases. We investigate the presence of nine DNEs derived from independent yet harmonized studies on Alzheimer's disease, autism spectrum disorder, late-life depression and schizophrenia in the UK Biobank study. Phenome-wide associations align with genome-wide associations, revealing 31 genomic loci (P < 5 × 10-8/9) associated with the nine DNEs. The nine DNEs, along with their polygenic risk scores, significantly enhanced the predictive accuracy for 14 systemic disease categories, particularly for conditions related to mental health and the central nervous system, as well as mortality outcomes. These findings underscore the potential of the nine DNEs to capture the expression of disease-related brain phenotypes in individuals of the general population and to relate such measures with genetics, lifestyle factors and chronic diseases.

The All of Us Research Program (All of Us) seeks to accelerate biomedical research and address the underrepresentation of minorities by recruiting over 1 million participants across the United States. A key question is how self-identification with discrete, predefined race and ethnicity categories compares to genetic variation at continental and subcontinental levels. To contextualize the genetic variation in All of Us, we analyzed ∼2 million common variants from 230,016 unrelated whole genomes using classical population genetics methods alongside reference panels such as the 1000 Genomes Project, Human Genome Diversity Project, and Simons Genome Diversity Project. Our analysis reveals that participants within self-identified race and ethnicity groups exhibit gradients of genetic variation rather than discrete clusters. The distributions of continental and subcontinental ancestries show considerable variation within race and ethnicity, both nationally and across states, reflecting the historical impacts of US colonization, the transatlantic slave trade, and recent migrations. All of Us samples filled most gaps along the top five principal components of genetic variation in current global reference panels. Notably, Hispanic or Latino participants spanned much of the three-way (African, Native American, and European) admixture spectrum. Ancestry was significantly associated with body mass index (BMI) and height even after adjusting for socio-environmental covariates. In particular, West-Central and East African ancestries showed opposite associations with BMI. This study emphasizes the importance of assessing subcontinental ancestries, as the continental approach is insufficient to control for confounding in genetic association studies.

Although genetic variant effects often interact nonadditively, strategies to uncover epistasis remain in their infancy. Here we develop low-signal signed iterative random forests to elucidate the complex genetic architecture of cardiac hypertrophy, using deep learning-derived left ventricular mass estimates from 29,661 UK Biobank cardiac magnetic resonance images. We report epistatic variants near CCDC141, IGF1R, TTN and TNKS, identifying loci deemed insignificant in genome-wide association studies. Functional genomic and integrative enrichment analyses reveal that genes mapped from these loci share biological process gene ontologies and myogenic regulatory factors. Transcriptomic network analyses using 313 human hearts demonstrate strong co-expression correlations among these genes in healthy hearts, with significantly reduced connectivity in failing hearts. To assess causality, RNA silencing in human induced pluripotent stem cell-derived cardiomyocytes, combined with novel microfluidic single-cell morphology analysis, confirms that cardiomyocyte hypertrophy is nonadditively modifiable by interactions between CCDC141, TTN and IGF1R. Our results expand the scope of cardiac genetic regulation to epistasis.

Over three percent of people carry a dominant pathogenic variant, yet only a fraction of carriers develop disease. Disease phenotypes from carriers of variants in the same gene range from mild to severe. Here, we investigate underlying mechanisms for this heterogeneity: variable variant effect sizes, carrier polygenic backgrounds, and modulation of carrier effect by genetic background (marginal epistasis). We leveraged exomes and clinical phenotypes from the UK Biobank and the Mt. Sinai BioMe Biobank to identify carriers of pathogenic variants affecting cardiometabolic traits. We employed recently developed methods to study these cohorts, observing strong statistical support and clinical translational potential for all three mechanisms of variable carrier penetrance and disease severity. For example, scores from our recent model of variant pathogenicity were tightly correlated with phenotype amongst clinical variant carriers, they predicted effects of variants of unknown significance, and they distinguished gain- from loss-of-function variants. We also found that polygenic scores modify phenotypes amongst pathogenic carriers and that genetic background additionally alters the effects of pathogenic variants through interactions.

Extracellular lipoprotein aggregation is a critical event in age-related macular degeneration (AMD) pathogenesis. In this study, we sought to analyze associations between clinical and genetic-based factors related to lipoprotein metabolism and risk for AMD in the All of Us research program.

Cross-sectional retrospective data analysis.

A total of 5028 healthy participants and 2328 patients with AMD from All of Us.

Participants with and without AMD were age, race, and sex matched in a 1:2 ratio, respectively. Smoking status, history of hyperlipidemia, and statin use were extracted in a binary manner. Statin use was further subcategorized into hepatically versus nonhepatically metabolized statins. Laboratory values for low-density lipoprotein (LDL), high-density lipoprotein (HDL), and triglycerides (TGs) were also extracted, and outliers were excluded from analysis. The PLINK toolkit was used to extract single nucleotide polymorphisms (SNPs) associated with LDL and HDL dysregulation, as published in prior work. Odds ratio curves were computed to assess the risk between LDL, TG, and HDL versus AMD. All clinical and genetic variables were input into a multivariable logistic regression model, and odds ratios and P values were generated.

Statistical significance of risk factors for AMD, thresholded at P ≤ 0.05.

On multivariable regression analysis, statin use and low and high HDL were significantly associated with increased AMD risk (P < 0.001 for all variables). Additionally, the multivariable regression implicated HDL-associated SNP's increased risk for AMD. Last, LPA was identified (P = 0.007) as a novel SNP associated with increased AMD risk.

There exists a U-shaped relationship between HDL and AMD risk, such that high and low HDL are significantly associated with increased AMD risk. Additionally, SNPs associated with HDL metabolism are associated with AMD risk. This analysis further establishes the role of HDL in AMD pathogenesis.

Proprietary or commercial disclosure may be found after the references.

Walnut (Juglans regia L.), an important woody oil plant, is cultivated globally and has a prominent position in the world's major nuts. Heterozygosity enriches plant genetic diversity by providing a wider array of gene combinations, significantly enhancing their adaptability to the environment and consequently improving their survival ability. In this study, we found that the heterozygosity rate was significantly correlated with 21 traits. Heterogeneity rate showed the strongest positive correlation with yield and nutrition, while it showed the most significant negative correlation with tree height and precocity. Among these, 13 traits showed positive correlations, the remaining 8 traits exhibited negative correlations. We conducted an in-depth study on the characteristics of walnut whole-genome heterozygosity. By using the GWAS based on the heterozygosity rate, we successfully identified 11 significant loci and 4 candidate genes. In the analysis of local heterozygosity rate by GWAS, it was found that 63.8% exhibited trans-acting and 36.2% exhibited cis-acting. In addition, with the help of genomic residual heterozygotes, we enriched functional genes from 44 Pfam families related to growth regulation and development. Finally, it is worth mentioning that during the process of walnut improvement, we observed an increase in the heterozygosity rate of genes related to the flowering time. It is speculated that a higher level of whole-genome heterozygosity can enhance the environmental adaptability of plants and improve their growth performance. The results of this study may provide assistance for optimizing the breeding strategies of walnuts.

The online version contains supplementary material available at 10.1007/s11032-025-01572-2.

The fall armyworm (Spodoptera frugiperda, FAW) is one of the most devastating invasive pests in the world, owing to its extraordinary migration performance. Research has clarified the migratory pathways and external environmental factors affecting FAW migration. However, the internal genes and loci regulating migration or reside in FAW remain largely unknown.

In this study, we used a tethered flight mill system to distinguish migratory and resident individuals, which exhibit significant differences in flight-related traits such as flight distance, duration, and maximum speed. Selective sweep analysis of 51 resequencing FAW (23 migratory and 28 resident individuals) identified 652 candidate genes, and genome-wide association analysis (GWAS) identified 79 functional annotated genes associated with the most significant trait, flight distance. These candidate genes were mainly concentrated in amino acid metabolism, signal transduction, and environmental adaptation. The neuroendocrine convertase 2 gene was crossed between the two analyses, with 65 selective mutation loci in the intron region. Casein kinase I, which reported regulating circadian rhythm by phosphorylating the period, was simultaneously involved in several enriched signaling pathways, and had 11 selective loci in the regulatory region. These selective mutation loci may affect the expression of target genes and regulate the migration behavior of FAW.

Key loci and genes may determine the migration behavior of FAW by regulating the circadian rhythm and other signaling pathways. These findings provide a new perspective for elucidating the internal driving mechanism of migratory insects, and provide a new possibility for developing eco-friendly control strategies for migratory pests. © 2025 Society of Chemical Industry.

Plant interactions with abiotic and biotic environments are mediated by diverse metabolites, which are crucial for stress response and defense. These metabolites can not only support diversity by shaping species niche differences but also display heritable and plastic intraspecific variation, which few studies have quantified in terms of their relative contributions. To address this shortcoming, we used untargeted metabolomics to annotate and quantify foliar metabolites and restriction-site associated DNA (RAD) sequencing to assess genetic distances among 300 individuals of 10 locally abundant species from a diverse tropical community in Southwest China. We quantified the relative contributions of relatedness and the abiotic and biotic environment to intraspecific metabolite variation, considering different biosynthetic pathways. Intraspecific variation contributed most to community-level metabolite diversity, followed by species-level variation. Biotic factors had the largest effect on total and secondary metabolites, while abiotic factors strongly influenced primary metabolites, particularly carbohydrates. The relative importance of these factors varied widely across different biosynthetic pathways and different species. Our findings highlight that intraspecific variation is an essential component of community-level metabolite diversity. Furthermore, species rely on distinct classes of metabolites to adapt to environmental pressures, with genetic, abiotic, and biotic factors playing pathway-specific roles in driving intraspecific variation.

The repeated evolution of herbicide resistance in agriculture provides an unprecedented opportunity to understand how organisms rapidly respond to strong anthropogenic-driven selection pressure. We recently identified agricultural populations of the grass species Bromus tectorum L. with resistance to multiple herbicides. To understand the evolutionary origins and spread of resistance, we investigated the resistance mechanisms to acetolactate synthase (ALS) inhibitors and photosystem II inhibitors, two widely used herbicide modes of action, in 49 B. tectorum populations. We assessed the genetic diversity, structure and relatedness in a subset of 21 populations. Resistance to ALS inhibitors was associated with multiple nonsynonymous mutations in ALS, the target site gene, despite the relatively small geographic region where populations originated, suggesting ALS inhibitor resistance evolution occurred multiple times in the region. We also found evidence that mechanisms not related to the target site evolved and were common in the populations studied. Resistance to photosystem II inhibitors was confirmed in two populations and was conferred by nonsynonymous mutations in the plastid gene psbA. Population genomics analyses suggested that ALS resistance in most populations, at the nucleotide level, spread via gene flow, except for one population where we found evidence that Pro-197-His mutations may have evolved in three separate events. Our results suggest that both gene flow via pollen and/or seed dispersal and multiple local evolutionary events were involved in the spread of herbicide-resistant B. tectorum. Our results provide an empirical example of the rapid repeated evolution of a trait under strong anthropogenic selection and elucidate the evolutionary origins of herbicide resistance in a plant species of agricultural importance.

NAT2 polymorphisms affect isoniazid metabolism, but their effect on mortality among individuals with tuberculosis (TB) remains unclear.

This study used data from two TB cohorts (2005-2011, 2014-2020) and death certificate records in Thailand. Newly diagnosed Thai individuals treated with isoniazid-containing regimens were included. NAT2 genotypes-rapid, intermediate, and slow acetylator (RA, IA, SA)-were classified via haplotype inference. The primary outcome was 1-year all-cause mortality, while secondary outcomes included TB-related mortality, TB+respiratory disease-related mortality recorded in the vital registration system, and death as a TB treatment outcome. Adjusted hazard ratios (aHRs) relative to the IA type were estimated using stratified Cox proportional hazards models. Subgroup analyses targeted individuals with isoniazid-resistant TB and HIV infection.

A total of 1,065 individuals (766 males; mean age=51 years) were analyzed. Individuals with RA had a 1.70-fold greater all-cause mortality risk (95 % CI: 1.03-2.80) than IA. The aHRs for RA were 1.14 (0.43-3.03) for TB-related mortality, 1.59 (0.80-3.18) for TB+respiratory disease-related mortality, and 1.26 (0.67-2.37) for TB treatment outcome death. Among individuals with isoniazid-resistant TB, those with RA had a 4.68-fold (1.14-19.12) greater aHR for all-cause mortality.

The RA type is associated with increased 1-year all-cause mortality.

With the increasing challenges posed by global warming and climate change, heat stress has become a significant threat to the sustainable production of grapevines. However, the genetic basis of grapevine thermotolerance remains poorly understood. Here, we combine genome-wide association study with transcriptomic profiling to identify TTC4 (thermotolerance on chromosome 4), a gene encoding a WRKY transcription factor, as a key determinant of thermotolerance in grapevine. TTC4 directly activates two thermotolerance-related genes, HSP18.1 and APX3. We also identify a heat-suppressed repressor SPL13 (SQUAMOSA-promoter binding protein-like 13) that cannot bind to the GTAT element (TTC4T(7631)) in intron 2 of TTC4, but can bind to the natural variant, GTAC (TTC4C(7631)). Grapevine accessions with TTC4C/C(7631) genotype exhibit significantly lower thermotolerance compared to those with the TTC4T/T(7631) and TTC4C/T(7631) genotypes. This fine-tuned regulation contributes to thermotolerance divergence among grapevine populations. The TTC4T(7631) haplotype holds significant potential as a genetic resource for breeding thermotolerant grapevine varieties.

The Fuzhou cattle breed, native to northeast China, is widely recognized for its adaptability, disease resistance, and docility. Despite being known for these qualities, its population has declined recently, and there is a significant lack of genomic studies on this species. We sequenced 21 samples from a primary breeding farm to determine the genetic structure, diversity, and selection signature to address this. Additionally, we combined 100 published genomic datasets from diverse geographical regions to characterize the genomic variation of Fuzhou cattle. There were 53 752 978 bi-allelic SNPs retained for downstream analysis. In population structure analysis, Fuzhou cattle show a predominantly East Asian taurine ancestry, with strong genetic affinities to Hanwoo and Yanbian cattle. Despite high nucleotide diversity within the Bos taurine lineage, genetic diversity analysis also revealed significant levels of inbreeding in Fuzhou cattle populations, indicating the need for conservation. Utilizing various methods such as θπ, iHS, FST, π-ratio, and XP-EHH, we identified genes associated with traits like growth, meat quality, energy metabolism, and immunity. Several genes related to cold adaptation were identified, including PLIN5, PLB1, and CPT2. These findings provide a basis for conservation strategies to safeguard the genetic resources of Fuzhou cattle.

Systemic lupus erythematosus (SLE) is a heterogeneous disease that manifests as different subphenotypes. Distinct subphenotypes, such as lupus nephritis (LN), have been associated with increased genetic risk, but prior studies have been limited by cross-sectional and imprecisely subphenotyped cohorts. This study investigated the genetic basis for LN using a longitudinal cohort of distinctly subphenotyped patients.

SLE patients with biopsy-proven LN or never developed LN (NLN) were recruited from eight tertiary referral centres. All patients had longitudinal clinical data for at least 10 years, or died during the study period. NLN patients had no renal involvement for at least 10 years. Subjects were genotyped and polygenic risk scores (PRS) were calculated using 230 SLE-associated SNPs. Genome-wide association analyses were also conducted for LN vs control, NLN vs control, and LN vs NLN comparisons, along with heterogeneity tests to assess differences in effect size.

Among 1462 patients, 824 (56%) and 638 (44%) had LN and NLN, respectively. PRS was significantly higher in the LN cohort. Genome-wide significant variants were identified in HLA, TNFAIP3, BLK and STAT4 loci specifically for LN patients, while STAT4 also remained significant for NLN patients. Direct LN vs NLN associations showed no statistically significant variants but heterogeneity tests revealed other genetic loci, including ELF1, OX40, DUSP22 and TPCN2.

Different subphenotypes of SLE are predisposed by distinct genetic risk loci, which can only be identified in clearly subphenotyped cohorts with sufficient longitudinal data. We identified unique genetic risk loci enriched among patients with biopsy-proven LN, and postulate that individual subphenotypes may have varying genetic predisposition.

We describe FoundHaplo, an identity-by-descent algorithm that can be used to screen untyped disease-causing variants using single nucleotide polymorphism (SNP) array data. FoundHaplo leverages knowledge of shared disease haplotypes for inherited variants to identify those who share the disease haplotype and are, therefore, likely to carry the rare [minor allele frequency (MAF) ≤ 0.01%] variant. We performed a simulation study to evaluate the performance of FoundHaplo across 33 disease-harbouring loci. FoundHaplo was used to infer the presence of two rare (MAF ≤ 0.01%) pathogenic variants, SCN1B c.363C>G (p.Cys121Trp) and WWOX c.49G>A (p.E17K), which can cause mild dominant and severe recessive epilepsy, respectively, in the Epi25 cohort and the UK Biobank. FoundHaplo demonstrated substantially better sensitivity at inferring the presence of these rare variants than existing genome-wide imputation. FoundHaplo is a valuable screening tool for searching disease-causing variants with known founder effects using only SNP genotyping data. It is also applicable to nonhuman applications and nondisease-causing traits, including rare-variant drivers of quantitative traits. The FoundHaplo algorithm is available at https://github.com/bahlolab/FoundHaplo (DOI:10.5281/zenodo.8058286).

In response to global climate change, numerous taxa are expanding their living ranges. In highly migratory species such as sea turtles, this expansion may be driven by individuals from nearby or distant areas. Recent nests outside the species' typical nesting range and reports of adult-sized individuals in the western Mediterranean suggest a green turtle (Chelonia mydas) range expansion into the central and western Mediterranean. To assess the green turtles' origin in these novel habitats, we built a genomic baseline using 2bRAD sequencing on five individuals from each of three Regional Management Units (RMUs): North Atlantic, South Atlantic and Mediterranean. We then compared this baseline with genotyped hatchlings from three nests laid in new central and eastern Mediterranean sites and four mature-sized green turtles tagged with satellite telemetry in the western Mediterranean. Our analyses revealed that the Tunisia nest originated from the South Atlantic RMU, while the Crete nests were produced by turtles from the Mediterranean RMU. Additionally, the three adult-sized turtles sampled in the southwestern Mediterranean were assigned to the South Atlantic RMU, while the mature-sized individual sampled in the northwestern Mediterranean belonged to the Mediterranean RMU. These results suggest a simultaneous incipient colonisation by two geographically distant RMUs. We propose that the range expansion of green turtles into the central and western Mediterranean is likely climate driven and these populations may become globally important as temperatures rise. Finally, our results highlight the essential role of the cost-effective RAD-Seq genomic assessment combined with tagging data to understand potential new colonisations.