Genome-wide Association Meta-analysis Research Articles

A meta-analysis and polygenic score study identifies novel genetic markers for waist-hip ratio in African populations.

Understanding the genetic underpinnings of anthropometric traits in diverse populations is crucial for gaining insights into their biological mechanisms and potential implications for health. We conducted a genome-wide association study, meta-analysis, and gene set analysis of waist-hip ratio (WHR), WHR adjusted for BMI (WHRadjBMI), waist circumference, BMI, and height using the African Collaborative Center for Microbiome and Genomics Research (ACCME)cohort (n = ~11,000) for discovery and polygenic score target analyses and the Africa America Diabetes Mellitus (AADM) study (n = ~5200) for replication and polygenic score validation. We generated and compared polygenic scores from European, African, Afro-Caribbean, and multiethnic ancestry populations. The top loci associated with each trait in the meta-analysis were in CD36 (rs3211826 [p = 5.90 × 10-12] for WHR and rs73709003 [p = 1.75 × 10-13] for WHRadjBMI), IFI27L1 (rs59775050 [p = 2.66 × 10-08] for waist circumference), INPP4B (rs2636629 [p = 1.44 × 10-09] for BMI), and HMGA1 (rs6937622 [p = 1.40 × 10-15] for height) gene regions. A novel variant rs7797157, near GNAT3, was also significantly associated with WHR (p = 2.50 × 10-10) and WHRadjBMI (p = 2.66 × 10-11). The ancestry-specific parameters for the best predictive polygenic scores were European ancestry (R2 = 0.68%; p = 1.63 × 10-16) and multiethnic ancestry (R2 = 0.06%; p = 1.29 × 10-02) for WHR; European ancestry (R2 = 1.36%; p = 2.94 × 10-31) and multiethnic ancestry (R2 = 1.12%; p = 3.52 × 10-25) for BMI; and European ancestry (R2 = 3.16%; p = 2.95 × 10-73), African ancestry (R2 = 4.16%; p = 1.75 × 10-96), and African and Afro-Caribbean ancestry (R2 = 2.67%; p = 4.35 × 10-62) for height. The discovery of a novel locus for WHR and genetic signals for each trait and the assessment of polygenic score performance underscore the importance of conducting well-powered studies in diverse populations.

Associations of genetic variants for refractive error and axial length in adults with ocular endophenotypes in children: a cross-sectional and longitudinal study

AimsTo investigate the associations of genetic variants previously linked to axial length (AL) and spherical equivalent refraction (SE) in adults with refractive error and related endophenotypes in children, at baseline...

Exploring the Link Between Genetic Predictors of Cardiovascular Disease and Psoriasis.

The epidemiological link between immune-mediated diseases (IMIDs) and cardiovascular disease has often been attributed to systemic inflammation. However, the direction of causality and the biological mechanisms linking cardiovascular disease with IMIDs are incompletely understood. Given the robust epidemiological association and the growing body of supportive mechanistic evidence, psoriasis is an exemplary IMID model for exploring this relationship. To assess the bidirectional relationships between genetic predictors of psoriasis and the 2 major forms of cardiovascular disease, coronary artery disease (CAD) and stroke, and to evaluate the association between genetic predictors of cardiovascular disease with 9 other IMIDs. This was a genetic association study using mendelian randomization (MR), a powerful genetic tool to help distinguish causation from associations observed in epidemiological studies, to provide supportive evidence for causality between traits. The study conducted 2-sample MR analyses using summary-level data from large-scale genome-wide association meta-analysis studies (GWAS) for each trait. The analysis focused on individuals of European descent from GWAS meta-analyses, involving CAD, stroke, psoriasis, and 9 other IMIDs. Data were analyzed from January 2023 to May 2024. Genetic predictors of CAD, stroke, psoriasis, and 9 other IMIDs. The primary outcomes were the associations of genetic predictors of CAD and stroke with the risk of psoriasis and 9 other IMIDs, determined using inverse-variance weighted (IVW) MR estimates. This study included 181 249 cases and 1 165 690 controls with CAD, 110 182 cases and 1 503 898 controls with stroke, 36 466 cases and 458 078 controls with psoriasis, for a total of approximately 3 400 000 individuals, and 9 other IMIDs. In contrast to previous assumptions, genetic predictors of psoriasis were found to have no association with CAD or stroke. In the reverse direction, genetic predictors of both CAD (MR estimate IVW odds ratio [OR], 1.07; 95% CI, 1.04-1.10; P = .003) and stroke (IVW OR, 1.22; 95% CI, 1.05-1.41; P = .01) were found to have risk-increasing associations with psoriasis. Adjusting for stroke rendered the associations of genetically predicted CAD with psoriasis risk nonsignificant (and vice versa), suggesting that a shared effect underlying genetic risk for CAD and stroke associates with increased psoriasis risk. No risk-increasing associations were observed for genetic predictors of cardiovascular disease with other common IMIDs, including rheumatoid arthritis and inflammatory bowel disease. Findings of this mendelian randomization study indicate that genetic predictors of cardiovascular disease were associated with increased psoriasis risk with no reciprocal effect or association with other IMIDs. Elucidating mechanisms underpinning this association could lead to novel therapeutic approaches in both diseases.

Causality of Hashimoto's Thyroiditis to Thyroid Cancer: A 2-S Mendelian Randomization Study

BackgroundObservational studies have indicated an association between Hashimoto's thyroiditis (HT) and the risk of thyroid cancer (TC); however, the causality and direction of these effects in genetics remain unclear. Therefore, our study aims to investigate the relationship between genetic susceptibility to HT and TC through a bidirectional Mendelian randomization (MR) approach using twin samples. MethodsMR analysis was conducted using genetic instruments associated with HT, selected from a comprehensive genome-wide association meta-analysis involving a total of 756 000 individuals of European and East Asian descent. The data set for TC comprised 1.486 million individuals, including both European and East Asian populations. Single nucleotide polymorphisms closely linked to HT were derived from genome-wide association studies. Two-sample bidirectional MR analyses were applied to assess the causal association between HT and TC, using inverse-variance weighted methods, and MR Egger, weighted median, simple mode, and weighted mode. Furthermore, sensitivity analyses were conducted employing the MR-Egger regression model, weighted median method, MR pleiotropy residual sum and outlier, and leave-one-out technique. ResultsMR analyses revealed no evidence of a causal relationship between HT and TC in either European or East Asian populations (all P > .1). However, bidirectional MR analysis demonstrated a causal relationship between TC and HT in the European population (odds ratio = 1.0838, 95% confidence interval: 1.0346, 11 354, P = .000686). ConclusionThis MR analysis indicates a lack of evidence supporting an association between genetically predicted HT and the risk of developing TC. In contrast, there is evidence of a causal relationship between genetically predicted TC and HT.

The genetic landscape of neuro-related proteins in human plasma.

Understanding the genetic basis of neuro-related proteins is essential for dissecting the molecular basis of human behavioural traits and the disease aetiology of neuropsychiatric disorders. Here the SCALLOP Consortium conducted a genome-wide association meta-analysis of over 12,000 individuals for 184 neuro-related proteins in human plasma. The analysis identified 125 cis-regulatory protein quantitative trait loci (cis-pQTL) and 164 trans-pQTL. The mapped pQTL capture on average 50% of each protein's heritability. At the cis-pQTL, multiple proteins shared a genetic basis with human behavioural traits such as alcohol and food intake, smoking and educational attainment, as well as neurological conditions and psychiatric disorders such as pain, neuroticism and schizophrenia. Integrating with established drug information, the causal inference analysis validated 52 out of 66 matched combinations of protein targets and diseases or side effects with available drugs while suggesting hundreds of repurposing and new therapeutic targets.

Genome-wide association meta-analysis identifies two novel loci associated with dental caries

BackgroundTooth loss significantly impacts oral function and overall health deterioration. Dental caries and periodontal disease are major contributors to tooth loss, emphasizing the critical need to prevent these conditions. Genetic studies have played a crucial role in deepening our understanding of the underlying mechanisms of these diseases. While large-scale genome-wide association studies (GWAS) on dental caries and periodontal disease have been conducted extensively, research focusing on Asian populations remains limited. Given substantial genetic and lifestyle variations across ethnicities, conducting studies across diverse populations is imperative. This study aimed to uncover new insights into the genetic mechanisms of these diseases, contributing to broader knowledge and potential targeted interventions.MethodsWe conducted a GWAS using genome data from 45,525 Japanese individuals, assessing their self-reported history of dental caries and periodontal disease. Additionally, we performed a meta-analysis by integrating our results with those from a previous large-scale GWAS predominantly involving European populations.ResultsWhile no new loci associated with periodontal disease were identified, we discovered two novel loci associated with dental caries. The lead variants of these loci were intron variant rs10974056 in GLIS3 and intron variant rs4801882 in SIGLEC5.ConclusionOur study findings are anticipated to advance understanding of the underlying mechanisms of dental caries and periodontal disease. Thes insights may inform better management strategies for patients affected by these conditions.

Ancestry-aligned polygenic scores combined with conventional risk factors improve prediction of cardiometabolic outcomes in African populations

BackgroundCardiovascular diseases (CVD) are a major health concern in Africa. Improved identification and treatment of high-risk individuals can reduce adverse health outcomes. Current CVD risk calculators are largely unvalidated in African populations and overlook genetic factors. Polygenic scores (PGS) can enhance risk prediction by measuring genetic susceptibility to CVD, but their effectiveness in genetically diverse populations is limited by a European-ancestry bias. To address this, we developed models integrating genetic data and conventional risk factors to assess the risk of developing cardiometabolic outcomes in African populations.MethodsWe used summary statistics from a genome-wide association meta-analysis (n = 14,126) in African populations to derive novel genome-wide PGS for 14 cardiometabolic traits in an independent African target sample (Africa Wits-INDEPTH Partnership for Genomic Research (AWI-Gen), n = 10,603). Regression analyses assessed relationships between each PGS and corresponding cardiometabolic trait, and seven CVD outcomes (CVD, heart attack, stroke, diabetes mellitus, dyslipidaemia, hypertension, and obesity). The predictive utility of the genetic data was evaluated using elastic net models containing multiple PGS (MultiPGS) and reference-projected principal components of ancestry (PPCs). An integrated risk prediction model incorporating genetic and conventional risk factors was developed. Nested cross-validation was used when deriving elastic net models to enhance generalisability.ResultsOur African-specific PGS displayed significant but variable within- and cross- trait prediction (max.R2 = 6.8%, p = 1.86 × 10−173). Significantly associated PGS with dyslipidaemia included the PGS for total cholesterol (logOR = 0.210, SE = 0.022, p = 2.18 × 10−21) and low-density lipoprotein (logOR = − 0.141, SE = 0.022, p = 1.30 × 10−20); with hypertension, the systolic blood pressure PGS (logOR = 0.150, SE = 0.045, p = 8.34 × 10−4); and multiple PGS associated with obesity: body mass index (max. logOR = 0.131, SE = 0.031, p = 2.22 × 10−5), hip circumference (logOR = 0.122, SE = 0.029, p = 2.28 × 10−5), waist circumference (logOR = 0.013, SE = 0.098, p = 8.13 × 10−4) and weight (logOR = 0.103, SE = 0.029, p = 4.89 × 10−5). Elastic net models incorporating MultiPGS and PPCs significantly improved prediction over MultiPGS alone. Models including genetic data and conventional risk factors were more predictive than conventional risk models alone (dyslipidaemia: R2 increase = 2.6%, p = 4.45 × 10−12; hypertension: R2 increase = 2.6%, p = 2.37 × 10−13; obesity: R2 increase = 5.5%, 1.33 × 10−34).ConclusionsIn African populations, CVD and associated cardiometabolic trait prediction models can be improved by incorporating ancestry-aligned PGS and accounting for ancestry. Combining PGS with conventional risk factors further enhances prediction over traditional models based on conventional factors. Incorporating data from target populations can improve the generalisability of international predictive models for CVD and associated traits in African populations.

Exploring antidiabetic drug targets as potential disease-modifying agents in osteoarthritis

Osteoarthritis is a leading cause of disability, and disease-modifying osteoarthritis drugs (DMOADs) could represent a pivotal advancement in treatment. Identifying the potential of antidiabetic medications as DMOADs could impact patient care significantly. We designed a comprehensive analysis pipeline involving two-sample Mendelian Randomization (MR) (genetic proxies for antidiabetic drug targets), summary-based MR (SMR) (for mRNA), and colocalisation (for drug-target genes) to assess their causal relationship with 12 osteoarthritis phenotypes. Summary statistics from the largest genome-wide association meta-analysis (GWAS) of osteoarthritis and gene expression data from the eQTLGen consortium were utilised. Seven out of eight major types of clinical antidiabetic medications were identified, resulting in fourteen potential drug targets. Sulfonylurea targets ABCC8/KCNJ11 were associated with increased osteoarthritis risk at any site (odds ratio (OR): 2.07, 95% confidence interval (CI): 1.50-2.84, P<3×10-4), while PPARG, influenced by thiazolidinediones (TZDs), was associated with decreased risk of hand (OR: 0.61, 95% CI: 0.48-0.76, P<3×10-4), finger (OR: 0.50, 95% CI: 0.35-0.73, P<3×10-4), and thumb (OR: 0.49, 95% CI: 0.34-0.71, P<3×10-4) osteoarthritis. Metformin and GLP1-RA, targeting GPD1 and GLP1R respectively, were associated with reduced risk of knee and finger osteoarthritis. In the SMR analyses, gene expression of KCNJ11, GANAB, ABCA1, and GSTP1, targeted by antidiabetic drugs, was significantly linked to at least one osteoarthritis phenotype and was replicated across at least two gene expression datasets. Additionally, increased KCNJ11 expression was related to decreased osteoarthritis risk and co-localised with at least one osteoarthritis phenotype. Our findings suggest a potential therapeutic role for antidiabetic drugs in treating osteoarthritis. The results indicate that certain antidiabetic drug targets may modify disease progression, with implications for developing targeted DMOADs. This study was funded by the Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant (2022), the Shanghai Municipal Health Commission Health Industry Clinical Research Project (Grant No. 20224Y0139), Beijing Natural Science Foundation (Grant No. 7244458), and the Postdoctoral Fellowship Program (Grade C) of China Postdoctoral Science Foundation (Grant No. GZC20230130).

Genome-wide association study and meta-analysis of phytosterols identifies a novel locus for serum levels of campesterol

Sitosterolemia is a rare inherited disorder caused by mutations in the ABCG5/ABCG8 genes. These genes encode proteins involved in the transport of plant sterols. Mutations in these genes lead to decreased excretion of phytosterols, which can accumulate in the body and lead to a variety of health problems, including premature coronary artery disease. We conducted the first genome-wide association study (GWAS) in the Middle East/North Africa population to identify genetic determinants of plant sterol levels in Qatari people. GWAS was performed on serum levels of β-sitosterol and campesterol using the Metabolon platform from Qatar Biobank (QBB) and genome sequence data provided by Qatar Genome Program. A trans-ancestry meta-analysis of data from our Qatari cohort with summary statistics from a previously published large cohort (9758 subjects) of European ancestry was conducted. Using conditional analysis, we identified two independent single nucleotide polymorphisms associated with β-sitosterol (rs145164937 and rs4299376), and two others with campesterol (rs7598542 and rs75901165) in the Qatari population in addition to previously reported variants. All of them map to the ABCG5/8 locus except rs75901165 which is located within the Intraflagellar Transport 43 (IFT43) gene. The meta-analysis replicated most of the reported variants, and our study provided significant support for the association of variants in SCARB1 and ABO with sitosterolemia. Evaluation of a polygenic risk score devised from European GWAS data showed moderate performance when applied to QBB (adjusted-R2 = 0.082). These findings provide new insights into the genetic architecture of phytosterol metabolism while showing the importance including under-represented populations in future GWAS studies.

Genomic Analysis Identifies Risk Factors in Restless Legs Syndrome.

Restless legs syndrome (RLS) is a neurological condition that causes uncomfortable sensations in the legs and an irresistible urge to move them, typically during periods of rest. The genetic basis and pathophysiology of RLS are incompletely understood. We sought to identify additional novel genetic risk factors associated with RLS susceptibility. We performed a whole-genome sequencing and genome-wide association meta-analysis of RLS cases (n = 9,851) and controls (n = 38,957) in 3 population-based biobanks (All of Us, Canadian Longitudinal Study on Aging, and CARTaGENE). Genome-wide association analysis identified 9 independent risk loci, of which 8 had been previously reported, and 1 was a novel risk locus (LMX1B, rs35196838, OR 1.14, 95% CI 1.09-1.19, p value = 2.2 × 10-9). Furthermore, a transcriptome-wide association study also identified GLO1 and a previously unreported gene, ELFN1. A genetic correlation analysis revealed significant common variant overlaps between RLS and neuroticism (rg = 0.40, se = 0.08, p value = 5.4 × 10-7), depression (rg = 0.35, se = 0.06, p value = 2.17 × 10-8), and intelligence (rg = -0.20, se = 0.06, p value = 4.0 × 10-4). Our study expands the understanding of the genetic architecture of RLS, and highlights the contributions of common variants to this prevalent neurological disorder. ANN NEUROL 2024.

A genome-wide association meta-analysis of all-cause and vascular dementia.

Dementia is a multifactorial disease with Alzheimer's disease (AD) and vascular dementia (VaD) pathologies making the largest contributions. Yet, most genome-wide association studies (GWAS) focus on AD. We conducted a GWAS of all-cause dementia (ACD) and examined the genetic overlap with VaD. Our dataset includes 800,597 individuals, with 46,902 and 8702 cases of ACD and VaD, respectively. Known AD loci for ACD and VaD were replicated. Bioinformatic analyses prioritized genes that are likely functionally relevant and shared with closely related traits and risk factors. For ACD, novel loci identified were associated with energy transport (SEMA4D), neuronal excitability (ANO3), amyloid deposition in the brain (RBFOX1), and magnetic resonance imaging markers of small vessel disease (SVD; HBEGF). Novel VaD loci were associated with hypertension, diabetes, and neuron maintenance (SPRY2, FOXA2, AJAP1, and PSMA3). Our study identified genetic risks underlying ACD, demonstrating overlap with neurodegenerative processes, vascular risk factors, and cerebral SVD. We conducted the largest genome-wide association study of all-cause dementia (ACD) and vascular dementia (VaD). Known genetic variants associated with AD were replicated for ACD and VaD. Functional analyses identified novel loci for ACD and VaD. Genetic risks of ACD overlapped with neurodegeneration, vascular risk factors, and cerebral small vessel disease.

Genome-wide association meta-analysis identifies five loci associated with postpartum hemorrhage

Bleeding in early pregnancy and postpartum hemorrhage (PPH) bear substantial risks, with the former closely associated with pregnancy loss and the latter being the foremost cause of maternal death, underscoring the severe impact on maternal–fetal health. We identified five genetic loci linked to PPH in a meta-analysis. Functional annotation analysis indicated candidate genes HAND2, TBX3 and RAP2C/FRMD7 at three loci and showed that at each locus, associated variants were located within binding sites for progesterone receptors. There were strong genetic correlations with birth weight, gestational duration and uterine fibroids. Bleeding in early pregnancy yielded no genome-wide association signals but showed strong genetic correlation with various human traits, suggesting a potentially complex, polygenic etiology. Our results suggest that PPH is related to progesterone signaling dysregulation, whereas early bleeding is a complex trait associated with underlying health and possibly socioeconomic status and may include genetic factors that have not yet been identified.

Shared genetic correlations between kidney diseases and sepsis.

Clinical studies have indicated a comorbidity between sepsis and kidney diseases. Individuals with specific mutations that predispose them to kidney conditions are also at an elevated risk for developing sepsis, and vice versa. This suggests a potential shared genetic etiology that has not been fully elucidated. Summary statistics data on exposure and outcomes were obtained from genome-wide association meta-analysis studies. We utilized these data to assess genetic correlations, employing a pleiotropy analysis method under the composite null hypothesis to identify pleiotropic loci. After mapping the loci to their corresponding genes, we conducted pathway analysis using Generalized Gene-Set Analysis of GWAS Data (MAGMA). Additionally, we utilized MAGMA gene-test and eQTL information (whole blood tissue) for further determination of gene involvement. Further investigation involved stratified LD score regression, using diverse immune cell data, to study the enrichment of SNP heritability in kidney-related diseases and sepsis. Furthermore, we employed Mendelian Randomization (MR) analysis to investigate the causality between kidney diseases and sepsis. In our genetic correlation analysis, we identified significant correlations among BUN, creatinine, UACR, serum urate, kidney stones, and sepsis. The PLACO analysis method identified 24 pleiotropic loci, pinpointing a total of 28 nearby genes. MAGMA gene-set enrichment analysis revealed a total of 50 pathways, and tissue-specific analysis indicated significant enrichment of five pairs of pleiotropic results in kidney tissue. MAGMA gene test and eQTL information (whole blood tissue) identified 33 and 76 pleiotropic genes, respectively. Notably, genes PPP2R3A for BUN, VAMP8 for UACR, DOCK7 for creatinine, and HIBADH for kidney stones were identified as shared risk genes by all three methods. In a series of immune cell-type-specific enrichment analyses of pleiotropy, we identified a total of 37 immune cells. However, MR analysis did not reveal any causal relationships among them. This study lays the groundwork for shared etiological factors between kidney and sepsis. The confirmed pleiotropic loci, shared pathogenic genes, and enriched pathways and immune cells have enhanced our understanding of the multifaceted relationships among these diseases. This provides insights for early disease intervention and effective treatment, paving the way for further research in this field.

Genetic and Non-Genetic Contributions to Eosinophilic Granulomatosis with Polyangiitis: Current Knowledge and Future Perspectives.

In this work, we present a comprehensive overview of the genetic and non-genetic complexity of eosinophilic granulomatosis with polyangiitis (EGPA). EGPA is a rare complex systemic disease that occurs in people presenting with severe asthma and high eosinophilia. After briefly introducing EGPA and its relationship with the anti-neutrophil cytoplasmic autoantibodies (ANCA)-associated vasculitis (AAVs), we delve into the complexity of this disease. At first, the two main biological actors, ANCA and eosinophils, are presented. Biological and clinical phenotypes related to ANCA positivity or negativity are explained, as well as the role of eosinophils and their pathological subtypes, pointing out their intricate relations with EGPA. Then, the genetics of EGPA are described, providing an overview of the research effort to unravel them. Candidate gene studies have investigated biologically relevant candidate genes; the more recent genome-wide association studies and meta-analyses, able to analyze the whole genome, have confirmed previous associations and discovered novel risk loci; in the end, family-based studies have dissected the contribution of rare variants and the heritability of EGPA. Then, we briefly present the environmental contribution to EGPA, reporting seasonal events and pollutants as triggering factors. In the end, the latest omic research is discussed and the most recent epigenomic, transcriptomic and microbiome studies are presented, highlighting the current challenges, open questions and suggesting approaches to unraveling this complex disease.

Genome-wide meta-analyses of non-response to antidepressants identify novel loci and potential drugs.

Antidepressants exhibit a considerable variation in efficacy, and increasing evidence suggests that individual genetics contribute to antidepressant treatment response. Here, we combined data on antidepressant non-response measured using rating scales for depressive symptoms, questionnaires of treatment effect, and data from electronic health records, to increase statistical power to detect genomic loci associated with non-response to antidepressants in a total sample of 135,471 individuals prescribed antidepressants. We performed genome-wide association meta-analyses, leave-one-out polygenic prediction, and bioinformatics analyses for genetically informed drug prioritization. We identified two novel loci associated with non-response to antidepressants and showed significant polygenic prediction in independent samples. In addition, we investigated drugs that target proteins likely involved in mechanisms underlying antidepressant non-response, and shortlisted drugs that warrant further replication and validation of their potential to reduce depressive symptoms in individuals who do not respond to first-line antidepressant medications. These results suggest that meta-analyses of GWAS utilizing real-world measures of treatment outcomes can increase sample sizes to improve the discovery of variants associated with non-response to antidepressants.

Genome-wide association study of major anxiety disorders in 122,341 European-ancestry cases identifies 58 loci and highlights GABAergic signaling.

The major anxiety disorders (ANX; including generalized anxiety disorder, panic disorder, and phobias) are highly prevalent, often onset early, persist throughout life, and cause substantial global disability. Although distinct in their clinical presentations, they likely represent differential expressions of a dysregulated threat-response system. Here we present a genome-wide association meta-analysis comprising 122,341 European ancestry ANX cases and 729,881 controls. We identified 58 independent genome-wide significant ANX risk variants and 66 genes with robust biological support. In an independent sample of 1,175,012 self-report ANX cases and 1,956,379 controls, 51 of the 58 associated variants were replicated. As predicted by twin studies, we found substantial genetic correlation between ANX and depression, neuroticism, and other internalizing phenotypes. Follow-up analyses demonstrated enrichment in all major brain regions and highlighted GABAergic signaling as one potential mechanism underlying ANX genetic risk. These results advance our understanding of the genetic architecture of ANX and prioritize genes for functional follow-up studies.

O-037 An update on the genetics of dizygotic twinning

Abstract Study question Which genes are involved in female fertility defined as giving birth to naturally conceived dizygotic (DZ) twins? Summary answer In 2016 we identified FSHB and SMAD3 as first loci for having DZ twins. We now report four additional loci: GNRH1, FSHR, ZFPM1 and IPO8. What is known already The propensity to give birth to DZ twins differs around the globe, is positively associated with body size and smoking, and runs in families. Heritability estimates tend to be low. Study design, size, duration We conducted a genome-wide association meta-analysis (GWAMA) of mothers of naturally conceived dizygotic (DZ) twins (8,265 cases, 264,567 controls) and of independent DZ twin offspring (26,252 cases, 417,433 controls). Participants were carefully screened to exclude twins born after use of Medically Assisted Reproduction (MAR) technologies. Participants/materials, setting, methods Over 700.000 participants from Australia, New Zealand, Europe and USA were included. Genetic association analyses by cohort for being a mother of DZ twins and being a DZ twin were combined by fixed-effects inverse variance methods as implemented in METAL software meta-analysis. To predict the most likely effector gene in a locus, we applied the new FLAMES framework which integrates machine learning with biological data linking SNPs to genes, and GWAS-wide convergence of gene interactions. Main results and the role of chance By enlarging sample size from previous efforts, both by including new cohorts and by combining through meta-analyses with independent DZ offspring, we identified 4 genome-wide significant loci, in addition to FSHB (follicle stimulating hormone subunit beta ) and SMAD3 (SMAD family member 3). Two novel loci GNRH1 (gonadotropin releasing hormone 1) and FSHR (follicle stimulating hormone receptor) have well-established roles in female reproduction. The 2 further novel genes were implicated by gene level enrichment analyses. Both ZFPM1 (Zinc Finger Protein, FOG Family Member 1) and IPO8 (Importin 8) have not previously been implicated. Significant genetic correlations were found with multiple aspects of female reproduction and body size as well as with a recent GWAMA of female infertility. The 26 top SNPs from our GWAMA in European-origin participants predicted the crude twinning rates in 47 non-European populations (r = 0.23 between risk score and population prevalence, p=.058) indicating that GWAS are needed in African and Asian populations to explore the causes of their respectively high and low DZ twinning rates. A Phenome-wide association study (PheWAS) based on the GWAMA, linked SNPs predisposing to DZT with reduced risk of both ovarian dysfunction and polycystic ovaries. Limitations, reasons for caution So far, our studies only included European ancestry cohorts. Inclusion of data from Africa (the highest world-wide DZ twining rates are observed in Western Africa) and Asia (lowest DZ twinning rate) will further illuminate the etiology of twinning and female fertility. Wider implications of the findings About one in 40 babies born in the world is a twin and there is still much unknown why they run in families. We hope our results will inform investigations of female fertility and infertility. Trial registration number not applicable

Predicting the potential deterioration of Barrett's esophagus based on gut microbiota: a Mendelian randomization analysis.

Esophageal adenocarcinoma (EAC) is one of the most malignant tumors in the digestive system. To make thing worse, the scarcity of treatment options is disheartening. However, if detected early, there is a possibility of reversing the condition. Unfortunately, there is still a lack of relevant early screening methods. Considering that Barrett's esophagus (BE), a precursor lesion of EAC, has been confirmed as the only known precursor of EAC. Analyzing which BE cases will progress to EAC and understanding the processes and mechanisms involved is of great significance for early screening of such patients. Considering the significant alterations in the gut microbiota of patients with BE and its potential role in the progression to EAC, this study aims to analyze the relationship between BE, EAC, and GM to identify potential diagnostic biomarkers and therapeutic targets. This study utilized comprehensive statistical data on gut microbiota from a large-scale genome-wide association meta-analysis conducted by the MiBioGen consortium (n = 18,340). Subsequently, we selected a set of single nucleotide polymorphisms (SNPs) that fell below the genome-wide significance threshold (1 × 10-5) as instrumental variables. To investigate the causal relationship between gut microbiota and BE and EAC, we employed various MR analysis methods, including Inverse Variance Weighting (IVW), MR-Egger regression, weighted median (WM), and weighted mean. Additionally, we assessed the level of pleiotropy, heterogeneity, and stability of genetic variations through MR-Egger intercept test, MR-PRESSO, Cochran's Q test, and "leave-one-out" sensitivity analysis. Furthermore, we conducted reverse MR analysis to identify the causal relationships between gut microbiota and BE and EAC. The results from the Inverse Variance-Weighted (IVW) analysis indicate that Alistipes (P = 4.86 × 10-2), Lactobacillus (P = 2.11 × 10-2), Prevotella 7 (P = 4.28 × 10-2), and RuminococcaceaeUCG004 (P = 4.34 × 10-2) are risk factors for Barrett's esophagus (BE), while Flavonifractor (P = 8.81 × 10-3) and RuminococcaceaeUCG004 (P = 4.99 × 10-2) are risk factors for esophageal adenocarcinoma (EAC). On the other hand, certain gut microbiota genera appear to have a protective effect against both BE and EAC. These include Eubacterium (nodatum group) (P = 4.51 × 10-2), Holdemania (P = 1.22 × 10-2), and Lactococcus (P = 3.39 × 10-2) in the BE cohort, as well as Eubacterium (hallii group) (P = 4.07 × 10-2) and Actinomyces (P = 3.62 × 10-3) in the EAC cohort. According to the results of reverse MR analysis, no significant causal effects of BE and EAC on gut microbiota were observed. Furthermore, no significant heterogeneity or pleiotropy was detected in the instrumental variables. We have established a causal relationship between the gut microbiota and BE and EAC. This study holds profound significance for screening BE patients who may be at risk of deterioration, as it can provide them with timely medical interventions to reverse the condition.

Genetic association of the gut microbiota with epigenetic clocks mediated by inflammatory cytokines: a Mendelian randomization analysis.

A new aging biomarker epigenetic clock has been developed. There exists a close link between aging and gut microbiota, which may be mediated by inflammatory cytokines. However, the relationship between the epigenetic clock, gut microbiota, and the mediating substances is unclear. Two large genome-wide association meta-analyses were analyzed by two-sample Mendelian randomization. The results between gut microbiota and epigenetic clock were investigated using the four methods (Inverse variance weighted, MR-Egger, weighted median, MR-PRESSO). Genetic correlation was measured by Linked disequilibrium score regression (LDSC). The correctness of the study direction was checked by the Steiger test. Cochran's Q statistic and MR-Egger intercept were used as sensitivity analyses of the study. The two-step method was used to examine the mediating role of inflammatory cytokines. We use the Benjamini-Hochberg correction method to correct the P value. After FDR correction, multiple bacterial genera were significantly or suggestively associated with four epigenetic clocks (GrimAge, HannumAge, IEAA, PhenoAge). And we detected several inflammatory factors acting as mediators of gut microbiota and epigenetic clocks. This study provides genetic evidence for a positive and negative link between gut microbiota and aging risk. We hope that by elucidating the genetic relationship and potential mechanisms between aging and gut microbiota, we will provide new avenues for continuing aging-related research and treatment.

Circulating anti-Müllerian hormone levels in pre-menopausal women: novel genetic insights from a genome-wide association meta-analysis.

Can a genome-wide association study (GWAS) meta-analysis, including a large sample of young premenopausal women from a founder population from Northern Finland, identify novel genetic variants for circulating anti-Müllerian hormone (AMH) levels and provide insights into single-nucleotide polymorphism enrichment in different biological pathways and tissues involved in AMH regulation? The meta-analysis identified a total of six loci associated with AMH levels at P < 5 × 10-8, three of which were novel in or near CHEK2, BMP4, and EIF4EBP1, as well as highlighted significant enrichment in renal system vasculature morphogenesis, and the pituitary gland as the top associated tissue in tissue enrichment analysis. AMH is expressed by preantral and small antral stage ovarian follicles in women, and variation in age-specific circulating AMH levels has been associated with several health conditions. However, the biological mechanisms underlying the association between health conditions and AMH levels are not yet fully understood. Previous GWAS have identified loci associated with AMH levels in pre-menopausal women, in or near MCM8, AMH, TEX41, and CDCA7. We performed a GWAS meta-analysis for circulating AMH level measurements in 9668 pre-menopausal women. We performed a GWAS meta-analysis in which we combined 2619 AMH measurements (at age 31 years) from a prospective founder population cohort (Northern Finland Birth Cohort 1966, NFBC1966) with a previous GWAS meta-analysis that included 7049 pre-menopausal women (age range 15-48 years) (N = 9668). NFBC1966 AMH measurements were quantified using an automated assay. We annotated the genetic variants, combined different data layers to prioritize potential candidate genes, described significant pathways and tissues enriched by the GWAS signals, identified plausible regulatory roles using colocalization analysis, and leveraged publicly available summary statistics to assess genetic and phenotypic correlations with multiple traits. Three novel genome-wide significant loci were identified. One of these is in complete linkage disequilibrium with c.1100delC in CHEK2, which is found to be 4-fold enriched in the Finnish population compared to other European populations. We propose a plausible regulatory effect of some of the GWAS variants linked to AMH, as they colocalize with GWAS signals associated with gene expression levels of BMP4, TEX41, and EIFBP41. Gene set analysis highlighted significant enrichment in renal system vasculature morphogenesis, and tissue enrichment analysis ranked the pituitary gland as the top association. The GWAS meta-analysis summary statistics are available for download from the GWAS Catalogue with accession number GCST90428625. This study only included women of European ancestry and the lack of sufficiently sized relevant tissue data in gene expression datasets hinders the assessment of potential regulatory effects in reproductive tissues. Our results highlight the increased power of founder populations and larger sample sizes to boost the discovery of novel trait-associated variants underlying variation in AMH levels, which aided the characterization of GWAS signals enrichment in different biological pathways and plausible genetic regulatory effects linked with AMH level variation for the first time. This work has received funding from the European Union's Horizon 2020 Research and Innovation Programme under the MATER Marie Sklodowska-Curie Grant Agreement No. 813707 and Oulu University Scholarship Foundation and Paulon Säätiö Foundation. (N.P.-G.), Academy of Finland, Sigrid Jusélius Foundation, Novo Nordisk, University of Oulu, Roche Diagnostics (T.T.P.). This work was supported by the Estonian Research Council Grant 1911 (R.M.). J.R. was supported by the European Union's Horizon 2020 Research and Innovation Program under Grant Agreements No. 874739 (LongITools), 824989 (EUCAN-Connect), 848158 (EarlyCause), and 733206 (LifeCycle). U.V. was supported by the Estonian Research Council grant PRG (PRG1291). The NFBC1966 received financial support from University of Oulu Grant No. 24000692, Oulu University Hospital Grant No. 24301140, and ERDF European Regional Development Fund Grant No. 539/2010 A31592. T.T.P. has received grants from Roche, Perkin Elmer, and honoraria for scientific presentations from Gedeon Richter, Exeltis, Astellas, Roche, Stragen, Astra Zeneca, Merck, MSD, Ferring, Duodecim, and Ajaton Terveys. For all other authors, there are no competing interests.