Shared Genetic Loci Research Articles

Association between 25(OH) vitamin D and multiple sclerosis: cohort, shared genetics, and Causality

BackgroundMultiple Sclerosis (MS), an autoimmune disorder causing demyelination and neurological damage, has been linked to 25-hydroxyvitamin D (25OHD) levels, suggesting its role in immune response and MS onset. This study used GWAS datasets to investigate genetic associations between 25OHD and MS.MethodsWe utilized a large-scale prospective cohort to evaluate serum 25OHD levels and MS risk. Linkage Disequilibrium Score Regression (LDSC) assessed genetic correlations between 25OHD levels and MS. Cross-trait genome-wide pleiotropy analysis revealed shared genetic loci. MAGMA analysis identified pleiotropic genes, enriched tissues, and gene sets. Stratified LDSC estimated tissue-specific and cell-specific heritability enrichment, and multi-trait co-localization analysis identified shared immune cell subsets. Bidirectional Mendelian Randomization (MR) assessed the causal association between 25OHD and MS risk.ResultsThe observational study found a nonlinear relationship between 25OHD levels and MS risk, with the lowest quartile showing significant risk elevation. Our findings revealed shared genetic structure between 25OHD levels and MS, suggesting a common biological pathway involving immune function and CNS integrity. We found 24 independent loci shared between 25OHD levels and MS risk, enriched in brain tissues and involved in pathways like LDL, HDL, and TG metabolism. Four loci (6p24.3, 6p22.2, 12q14.1, and 19p13.2) had strong co-localization evidence, with mapped genes as potential drug targets. Bidirectional MR analysis supported a causal effect of 25OHD levels on MS risk, suggesting 25OHD supplementation could modulate MS risk.ConclusionThis study reveals the complex relationship between 25OHD levels and MS, indicating that higher levels are not always advantageous and recommending moderation in supplementation. We identified SMARCA4 as a potential therapeutic target and detailed key pathways influencing this interaction.Graphical

Multi-trait association analysis reveals shared genetic loci between Alzheimer’s disease and cardiovascular traits

Several cardiovascular traits and diseases co-occur with Alzheimer’s disease. We mapped their shared genetic architecture using multi-trait genome-wide association studies. Subsequent fine-mapping and colocalisation highlighted 16 genetic loci associated with both Alzheimer’s and cardiovascular diseases. We prioritised rs11786896, which colocalised with Alzheimer’s disease, atrial fibrillation and expression of PLEC in the heart left ventricle, and rs7529220, which colocalised with Alzheimer’s disease, atrial fibrillation and expression of C1Q family genes. Single-cell RNA-sequencing data, co-expression network and protein-protein interaction analyses provided evidence for different mechanisms of PLEC, which is upregulated in left ventricular endothelium and cardiomyocytes with heart failure and in brain astrocytes with Alzheimer’s disease. Similar common mechanisms are implicated for C1Q in heart macrophages with heart failure and in brain microglia with Alzheimer’s disease. These findings highlight inflammatory and pleomorphic risk determinants for the co-occurrence of Alzheimer’s and cardiovascular diseases and suggest PLEC, C1Q and their interacting proteins as potential therapeutic targets.

Gastroesophageal reflux disease increases predisposition to severe COVID-19: Insights from integrated Mendelian randomization and genetic analysis.

This study aims to investigate the potential causal relationship, shared genomic loci, as well as potential molecular pathways and tissue-specific expression patterns between gastroesophageal reflux disease (GERD) and the risk of hospitalized/severe 2019 coronavirus disease (COVID-19). We employed linkage disequilibrium score regression and bidirectional Mendelian randomization (MR) analysis to explore potential genetic associations between GERD (N=602,604) and hospitalized COVID-19 (N=2095,324) as well as severe COVID-19 (N=1086,211). Additionally, shared genomic loci were extracted from common pivotal regions, further confirmed through corresponding colocalization analyses. GERD-driven molecular pathway network was constructed using extensive literature data mining to understand the molecular-level impacts of GERD on COVID-19. Our results revealed a significant positive genetic correlation between GERD and both hospitalized (rg = 0.418) and severe COVID-19 (rg = 0.314). Furthermore, the MR analysis demonstrated a unidirectional causal effect of genetic predisposition to GERD on COVID-19 outcomes, including hospitalized COVID-19 (odds ratio [OR]: 1.33, 95% confidence interval [CI]: 1.27-1.44, p=9.17e-12) and severe COVID-19 (OR: 1.27, 95% CI: 1.18-1.37, p=1.20e-05). Additionally, GERD and both COVID-19 conditions shared one genomic locus with lead-SNPs rs1011407 and rs1123573, corresponding to the transcription factor BCL11A. Colocalization analysis further demonstrated a significant positive correlation between genome-wide association study and expression quantitative trait locus (eQTL) abnormalities, including rs1011407 (eQTL_p=2.35e-07) and rs1123573 (eQTL_p=2.74e-05). Molecular pathway analysis indicated that GERD might promote the progression of COVID-19 by inducting immune-activated and inflammation-related pathways. These findings confirm that genetically determined GERD may increase the susceptibility to hospitalized/severe COVID-19. The shared genetic loci and the potential molecular pathways offer valuable insights into causal connections between GERD and COVID-19.

Exploring the relationship between polycystic ovarian syndrome, testosterone, and multiple sclerosis in women: A nationwide cohort study and genome-wide cross-trait analysis

Background: Women have a higher risk of developing multiple sclerosis (MS), potentially due to hormonal factors. Elevated testosterone levels, common in polycystic ovary syndrome (PCOS), might influence MS risk. Objective: To investigate the relationship between PCOS, as a proxy for elevated testosterone levels, and MS risk through phenotypic and genomic analysis. Methods: Cox regression models analysed the association between PCOS and MS risk. The genome-wide cross-trait analysis examined the genetic architecture. Results: In a Swedish cohort of 1,374,529 women, 77 (0.3%) with PCOS and 3,654 (0.3%) without PCOS were diagnosed with MS. After adjusting for birth year and obesity, no association was found between PCOS and MS (HR = 0.91, 95% CI = 0.72–1.15), which was confirmed by Mendelian randomization analysis, where genetically predicted PCOS propensity, sex hormone-binding globulin (SHBG), or testosterone levels did not causally affect MS risk (all p-values > 0.05). By exploring horizontal pleiotropy, we identified shared genetic regions and 19 independent pleiotropic SNPs for SHBG with MS and 11 for testosterone with MS. Conclusion: We did not find evidence for a causal role of PCOS, as a proxy of elevated testosterone, in reducing the risk of MS in women. The shared genetic loci between testosterone, SHBG, and MS provide biological insights.

Dissecting shared genetic architecture between depression and body mass index

BackgroundA growing body of evidence supports the comorbidity between depression (DEP) and obesity, yet the genetic mechanisms underlying this association remain unclear. Our study explored the shared genetic architecture and causal associations of DEP with BMI.MethodsWe investigated the multigene overlap and genetic correlation between DEP (N > 1.3 million) and BMI (N = 806,834) based on genome-wide association studies (GWAS) and using the bivariate causal mixture model and linkage disequilibrium score regression (LDSC). The causal association was explored by bi-directional Mendelian randomization (MR). Common risk loci were identified through cross-trait meta-analyses. Stratified LDSC and multi-marker gene annotation analyses were applied to investigate single-nucleotide polymorphisms enrichment across tissue types, cell types, and functional categories. Finally, we explored shared functional genes by Summary Data-Based Mendelian Randomization (SMR) and further detected differential expression genes (DEG) in brain tissues of individuals with depression and obesity.ResultsWe found a positive genetic correlation between DEP and BMI (rg = 0.19, P = 4.07 × 10−26), which was more evident in local genomic regions. Cross-trait meta-analyses identified 16 shared genetic loci, 5 of which were newly identified, and they had influence on both diseases in the same direction. MR analysis showed a bidirectional causal association between DEP and BMI, with comparable effect sizes estimated in both directions. Combined with gene expression information, we found that genetic correlations between DEP and BMI were enriched in 6 brain regions, predominantly in the nucleus accumbens and anterior cingulate cortex. Moreover, 6 specific cell types and 23 functional genes were found to have an impact on both DEP and BMI across the brain regions. Of which, NEGR1 was identified as the most significant functional gene and associated with DEP and BMI at the genome-wide significance level (P < 5 × 10−8). Compared with healthy controls, the expression levels of NEGR1 gene were significant lower in brain tissues of individuals with depression and obesity.ConclusionsOur study reveals shared genetic basis underpinnings between DEP and BMI, including genetic correlations and common genes. These insights offer novel opportunities and avenues for future research into their comorbidities.

Antidepressants account for the causal effect of major depressive disorder on type 2 diabetes

BackgroundPatients with major depressive disorder (MDD) face an elevated risk of type 2 diabetes (T2D). However, the contribution of the disease itself versus the side effects of antidepressants to this increased risk remains unclear. ObjectiveThis study aimed to investigate the overall and independent effects of MDD and exposure to antidepressants on T2D risk. MethodsSummary genome-wide association study datasets were utilized for the Mendelian randomization (MR) and multivariable MR (MVMR) analyses, including ones for MDD (N = 500,199), antidepressants (N = 175,161), and T2D (N = 933,970). Bayesian colocalization analysis was used to reveal shared genetic variation between MDD, antidepressants, and T2D. ResultsWe found that both MDD (OR: 1.15, CI: 1.03–1.30, P = 0.016) and antidepressants (OR: 1.37, CI: 1.22–1.53, P = 2.75E-08) have overall causal effects on T2D. While T2D was associated with the risk of antidepressant use (OR: 1.08, CI: 1.06–1.11, P = 8.80E-10), but not with the risk of MDD (OR: 1.00, CI: 0.98–1.01, P = 0.661). Our MVMR analysis showed that the use of antidepressants is associated with higher risks of T2D (OR: 1.21, CI: 1.07–1.37, P = 7.19E-04), while MDD is not linked to the risk of T2D (OR: 1.01, CI: 0.86–1.18, P = 0.799). Colocalization analysis identified two shared genetic loci between antidepressants and T2D. ConclusionsThe elevated T2D risk in MDD patients is chiefly caused by antidepressant use. These findings emphasize the importance of considering the impact of antidepressants on metabolic health in individuals with MDD.

Investigating the shared genetic links between hypothyroidism and psychiatric disorders: a large-scale genomewide cross-trait analysis

BackgroundAssociations between thyroid diseases and psychiatric disorders have been mainly described before. However, the genetic mechanism behind hypothyroidism and psychiatric disorders remains unexplained. MethodsWe examined the genetic architecture of hypothyroidism and 8 psychiatric disorders. Firstly, the global and local genetic relationship between the paired traits was explored. Secondly, cross-trait analysis was performed to investigate the genomic loci and genes between psychiatric disorders and hypothyroidism. Thirdly, the significant expression of these genes and the causal relationships were investigated. Lastly, enrichment analysis was conducted on these genes to explore their biological mechanisms. ResultsWe observed significant positive genetic correlations between psychiatric disorders and hypothyroidism. The cross-trait meta-analysis identified 62 shared genetic loci between hypothyroidism and psychiatric disorders. The colocalization analysis additionally revealed 15 potential pleiotropic loci with a posterior probabilities.H4 (PP·H4) value >0.7. We also found 2308 genes shared between both traits, which were highly enriched in biological pathways such as immune cell differentiation and autoimmune diseases, as well as in tissue structures like the frontal cortex and cerebral cortex. Especially, many pleiotropic genes were significantly expressed for multiple pairwise traits, such as BCL11B, RERE, and SUOX. Lastly, the Latent causal variable model (LCV) analysis did not find any causal components in the genetic structure between them. LimitationsThe limitations of this study include that the conclusions were drawn from a European population. ConclusionsThese findings not only deepens our understanding of their biological mechanisms but also has significant implications for the intervention and treatment of these diseases.

Shared Genetic Architectures between Coronary Artery Disease and Type 2 Diabetes Mellitus in East Asian and European Populations.

Coronary artery disease (CAD) is a common comorbidity of type 2 diabetes mellitus (T2DM). However, the pathophysiology connecting these two phenotypes remains to be further understood. Combined analysis in multi-ethnic populations can help contribute to deepening our understanding of biological mechanisms caused by shared genetic loci. We applied genetic correlation analysis and then performed conditional and joint association analyses in Chinese, Japanese, and European populations to identify the genetic variants jointly associated with CAD and T2DM. Next, the associations between genes and the two traits were also explored. Finally, fine-mapping and functional enrichment analysis were employed to identify the potential causal variants and pathways. Genetic correlation results indicated significant genetic overlap between CAD and T2DM in the three populations. Over 10,000 shared signals were identified, and 587 were shared by East Asian and European populations. Fifty-six novel shared genes were found to have significant effects on both CAD and T2DM. Most loci were fine-mapped to plausible causal variant sets. Several similarities and differences of the involved genes in GO terms and KEGG pathways were revealed across East Asian and European populations. These findings highlight the importance of immunoregulation, neuroregulation, heart development, and the regulation of glucose metabolism in shared etiological mechanisms between CAD and T2DM.

Genome-wide association analysis reveals potential genetic correlation and causality between circulating inflammatory proteins and amyotrophic lateral sclerosis.

Amyotrophic Lateral Sclerosis (ALS), a fatal neurodegenerative disease, continues to elude complete comprehension of its pathological underpinnings. Recent focus on inflammation in ALS pathogenesis prompts this investigation into the genetic correlation and potential causal relationships between circulating inflammatory proteins and ALS. Genome-wide association study (GWAS) data encompassing 91 circulating inflammatory protein measures from 14,824 individuals of European ancestry, alongside records from 27,205 ALS cases and 110,881 controls, were employed. Assessment of genetic correlation and overlap utilized LD score regression (LDSC), high-definition likelihood (HDL), and genetic analysis integrating pleiotropy and annotation (GPA) methodologies. Identification of shared genetic loci involved pleiotropy analysis, functional mapping and annotation (FUMA), and co-localization analysis. Finally, Mendelian randomization was applied to probe causal relationships between inflammatory proteins and ALS. Our investigation revealed significant genetic correlation and overlap between ALS and various inflammatory proteins, including C-C motif chemokine 28, Interleukin-18, C-X-C motif chemokine 1, and Leukemia inhibitory factor receptor (LIFR). Pleiotropy analysis uncovered shared variations at specific genetic loci, some of which bore potential harm. Mendelian randomization analysis suggested that alterations in specific inflammatory protein levels, notably LIFR, could impact ALS risk. Our findings uncover a genetic correlation between certain circulating inflammatory proteins and ALS, suggesting their possible causal involvement in ALS pathogenesis. Moreover, the identification of LIFR as a crucial protein may yield new insights into ALS pathomechanisms and offer a promising avenue for therapeutic interventions. These discoveries provide novel perspectives for advancing the comprehension of ALS pathophysiology and exploring potential therapeutic avenues.

Dissecting the shared genetic landscape of anxiety, depression, and schizophrenia

BackgroundNumerous studies highlight the genetic underpinnings of mental disorders comorbidity, particularly in anxiety, depression, and schizophrenia. However, their shared genetic loci are not well understood. Our study employs Mendelian randomization (MR) and colocalization analyses, alongside multi-omics data, to uncover potential genetic targets for these conditions, thereby informing therapeutic and drug development strategies.MethodsWe utilized the Consortium for Linkage Disequilibrium Score Regression (LDSC) and Mendelian Randomization (MR) analysis to investigate genetic correlations among anxiety, depression, and schizophrenia. Utilizing GTEx V8 eQTL and deCODE Genetics pQTL data, we performed a three-step summary-data-based Mendelian randomization (SMR) and protein–protein interaction analysis. This helped assess causal and comorbid loci for these disorders and determine if identified loci share coincidental variations with psychiatric diseases. Additionally, phenome-wide association studies, drug prediction, and molecular docking validated potential drug targets.ResultsWe found genetic correlations between anxiety, depression, and schizophrenia, and under a meta-analysis of MR from multiple databases, the causal relationships among these disorders are supported. Based on this, three-step SMR and colocalization analyses identified ITIH3 and CCS as being related to the risk of developing depression, while CTSS and DNPH1 are related to the onset of schizophrenia. BTN3A1, PSMB4, and TIMP4 were identified as comorbidity loci for both disorders. Molecules that could not be determined through colocalization analysis were also presented. Drug prediction and molecular docking showed that some drugs and proteins have good binding affinity and available structural data.ConclusionsOur study indicates genetic correlations and shared risk loci between anxiety, depression, and schizophrenia. These findings offer insights into the underlying mechanisms of their comorbidities and aid in drug development.

Characterizing the polygenic overlap and shared loci between rheumatoid arthritis and cardiovascular diseases

BackgroundDespite substantial research revealing that patients with rheumatoid arthritis (RA) have excessive morbidity and mortality of cardiovascular disease (CVD), the mechanism underlying this association has not been fully known. This study aims to systematically investigate the phenotypic and genetic correlation between RA and CVD.MethodsBased on UK Biobank, we conducted two cohort studies to evaluate the phenotypic relationships between RA and CVD, including atrial fibrillation (AF), coronary artery disease (CAD), heart failure (HF), and stroke. Next, we used linkage disequilibrium score regression, Local Analysis of [co]Variant Association, and bivariate causal mixture model (MiXeR) methods to examine the genetic correlation and polygenic overlap between RA and CVD, using genome-wide association summary statistics. Furthermore, we explored specific shared genetic loci by conjunctional false discovery rate analysis and association analysis based on subsets.ResultsCompared with the general population, RA patients showed a higher incidence of CVD (hazard ratio [HR] = 1.21, 95% confidence interval [CI]: 1.15–1.28). We observed positive genetic correlations of RA with AF and stroke, and a mixture of negative and positive local genetic correlations underlying the global genetic correlation for CAD and HF, with 13 ~ 33% of shared genetic variants for these trait pairs. We further identified 23 pleiotropic loci associated with RA and at least one CVD, including one novel locus (rs7098414, TSPAN14, 10q23.1). Genes mapped to these shared loci were enriched in immune and inflammatory-related pathways, and modifiable risk factors, such as high diastolic blood pressure.ConclusionsThis study revealed the shared genetic architecture of RA and CVD, which may facilitate drug target identification and improved clinical management.

Genetic correlations and causal relationships between cardio-metabolic traits and sepsis

Cardio-metabolic traits have been reported to be associated with the development of sepsis. It is, however, unclear whether these co-morbidities reflect causal associations, shared genetic heritability, or are confounded by environmental factors. We performed three analyses to explore the relationships between cardio-metabolic traits and sepsis. Mendelian randomization (MR) study to evaluate the causal effects of multiple cardio-metabolic traits on sepsis. Global genetic correlation analysis to explore the correlations between cardio-metabolic traits and sepsis. Local genetic correlation (GC) analysis to explore shared genetic heritability between cardio-metabolic traits and sepsis. Some loci were further examined for related genes responsible for the causal relationships. Genetic associations were obtained from the UK Biobank data or published large-scale genome-wide association studies with sample sizes between 200,000 to 750,000. In MR, we found causality between BMI and sepsis (OR: 1.53 [1.4–1.67]; p < 0.001). Body mass index (BMI), which is confirmed by sensitivity analyses and multivariable MR adjusting for confounding factors. Global GC analysis showed a significant correlation between BMI and sepsis (rg = 0.55, p < 0.001). More cardio-metabolic traits were identified to be correlated to the sepsis onset such as CRP (rg = 0.37, p = 0.035), type 2 diabetes (rg = 0.33, p < 0.001), HDL (rg = − 0.41, p < 0.001), and coronary artery disease (rg = 0.43, p < 0.001). Local GC revealed some shared genetic loci responsible for the causality. The top locus 1126 was located at chromosome 7 and comprised genes HIBADH, JAZF1, and CREB5. The present study provides evidence for an independent causal effect of BMI on sepsis. Further detailed analysis of the shared genetic heritability between cardio-metabolic traits and sepsis provides the opportunity to improve the preventive strategies for sepsis.

Genetic overlap between schizophrenia and cognitive performance

Schizophrenia (SCZ), a highly heritable mental disorder, is characterized by cognitive impairment, yet the extent of the shared genetic basis between schizophrenia and cognitive performance (CP) remains poorly understood. Therefore, we aimed to explore the polygenic overlap between SCZ and CP. Specifically, the bivariate causal mixture model (MiXeR) was employed to estimate the extent of genetic overlap between SCZ (n = 130,644) and CP (n = 257,841), and conjunctional false discovery rate (conjFDR) approach was used to identify shared genetic loci. Subsequently, functional annotation and enrichment analysis were carried out on the identified genomic loci. The MiXeR analyses revealed that 9.6 K genetic variants are associated with SCZ and 10.9 K genetic variants for CP, of which 9.5 K variants are shared between these two traits (Dice coefficient = 92.8%). By employing conjFDR, 236 loci were identified jointly associated with SCZ and CP, of which 139 were novel for the two traits. Within these shared loci, 60 exhibited consistent effect directions, while 176 had opposite effect directions. Functional annotation analysis indicated that the shared genetic loci were mainly located in intronic and intergenic regions, and were found to be involved in relevant biological processes such as nervous system development, multicellular organism development, and generation of neurons. Together, our findings provide insights into the shared genetic architecture between SCZ and CP, suggesting common pathways and mechanisms contributing to both traits.

Dissecting the genetic overlap between severe mental disorders and markers of cellular aging: Identification of pleiotropic genes and druggable targets.

Patients with severe mental disorders such as bipolar disorder (BD), schizophrenia (SCZ) and major depressive disorder (MDD) show a substantial reduction in life expectancy, increased incidence of comorbid medical conditions commonly observed with advanced age and alterations of aging hallmarks. While severe mental disorders are heritable, the extent to which genetic predisposition might contribute to accelerated cellular aging is not known. We used bivariate causal mixture models to quantify the trait-specific and shared architecture of mental disorders and 2 aging hallmarks (leukocyte telomere length [LTL] and mitochondrial DNA copy number), and the conjunctional false discovery rate methodto detect shared genetic loci. We integrated gene expression data from brain regions from GTEx and used different tools to functionally annotate identified loci and investigate their druggability. Aging hallmarks showed low polygenicity compared with severe mental disorders. We observed a significant negative global genetic correlation between MDD and LTL (rg = -0.14, p = 6.5E-10), and no significant results for other severe mental disorders or for mtDNA-cn. However, conditional QQ plots and bivariate causal mixture models pointed to significant pleiotropy among all severe mental disorders and aging hallmarks. We identified genetic variants significantly shared between LTL and BD (n = 17), SCZ (n = 55) or MDD (n = 19), or mtDNA-cn and BD (n = 4), SCZ (n = 12) or MDD (n = 1), with mixed direction of effects. The exonic rs7909129 variant in the SORCS3 gene, encoding a member of the retromer complex involved in protein trafficking and intracellular/intercellular signaling, was associated with shorter LTL and increased predisposition to all severe mental disorders. Genetic variants underlying risk of SCZ or MDD and shorter LTL modulate expression of several druggable genes in different brain regions. Genistein, a phytoestrogen with anti-inflammatory and antioxidant effects, was an upstream regulator of 2 genes modulated by variants associated with risk of MDD and shorter LTL. While our results suggest that shared heritability might play a limited role in contributing to accelerated cellular aging in severe mental disorders, we identified shared genetic determinants and prioritized different druggable targets and compounds.

Genome-wide analysis reveals extensive genetic overlap between childhood phenotypes and later-life type 2 diabetes

Observational studies have indicated a potential influence of childhood phenotypes on the later development of type 2 diabetes (T2D). However, the underlying biological mechanisms remain unclear. In this study, we conducted a comprehensive genome-wide analysis to investigate the shared genetic architecture and genetic loci between nine childhood phenotypes (N = 4202–620,26) and later-life T2D (N = 80,154) using genetic correlation, mendelian randomization (MR), and conjunctional false discovery rate (conjFDR) statistical frameworks. Our findings demonstrated substantial genetic correlations and pleiotropic enrichment between childhood obesity, body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), and later-life T2D. Childhood obesity exhibited a significant association with increased later-life T2D risk through 10 mediators, 6 of which were adulthood obesity-related phenotypes. Additionally, we identified 69, 83, 3, 5, 10, 5, 3, and 7 loci shared between childhood obesity, BMI, SBP, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), triglycerides (TG), apolipoprotein A-I (ApoA-I), apolipoprotein B (ApoB), and T2D at conjFDR <0.05, with the majority of these loci being novel discoveries. Overall, our study reveals extensive genetic overlap between childhood obesity-related phenotypes and T2D with concordant effect directions, shedding new light on variants and phenotypes with lifelong effects.

Psychiatric disorders and brain white matter exhibit genetic overlap implicating developmental and neural cell biology.

Improved understanding of the shared genetic architecture between psychiatric disorders and brain white matter may provide mechanistic insights for observed phenotypic associations. Our objective is to characterize the shared genetic architecture of bipolar disorder (BD), major depression (MD), and schizophrenia (SZ) with white matter fractional anisotropy (FA) and identify shared genetic loci to uncover biological underpinnings. We used genome-wide association study (GWAS) summary statistics for BD (n = 413,466), MD (n = 420,359), SZ (n = 320,404), and white matter FA (n = 33,292) to uncover the genetic architecture (i.e., polygenicity and discoverability) of each phenotype and their genetic overlap (i.e., genetic correlations, overlapping trait-influencing variants, and shared loci). This revealed that BD, MD, and SZ are at least 7-times more polygenic and less genetically discoverable than average FA. Even in the presence of weak genetic correlations (range = -0.05 to -0.09), average FA shared an estimated 42.5%, 43.0%, and 90.7% of trait-influencing variants as well as 12, 4, and 28 shared loci with BD, MD, and SZ, respectively. Shared variants were mapped to genes and tested for enrichment among gene-sets which implicated neurodevelopmental expression, neural cell types, myelin, and cell adhesion molecules. For BD and SZ, case vs control tract-level differences in FA associated with genetic correlations between those same tracts and the respective disorder (rBD = 0.83, p = 4.99e-7 and rSZ = 0.65, p = 5.79e-4). Genetic overlap at the tract-level was consistent with average FA results. Overall, these findings suggest a genetic basis for the involvement of brain white matter aberrations in the pathophysiology of psychiatric disorders.

Association between ovarian reserve and spontaneous miscarriage and their shared genetic architecture.

Can potential mechanisms involved in the likely concurrence of diminished ovarian reserve (DOR) and miscarriage be identified using genetic data? Concurrence between ovarian reserve and spontaneous miscarriage was observed, and may be attributed to shared genetic risk loci enriched in antigen processing and presentation and autoimmune disease pathways. Previous studies have shown that lower serum anti-Müllerian hormone (AMH) levels are associated with increased risk of embryo aneuploidy and spontaneous miscarriage, although findings have not been consistent across all studies. A recent meta-analysis suggested that the association between DOR and miscarriage may not be causal, but rather a result of shared underlying causes such as clinical conditions or past exposure. Motivated by this hypothesis, we conducted the present analysis to explore the concurrence between DOR and miscarriage, and to investigate potential mechanisms using genetic data. Three data sources were used in the study: the clinical IVF data were retrospectively collected from an academically affiliated Reproductive Medicine Center (17786 cycles included); the epidemiological data from the UK Biobank (UKB), which is a large-scale, population-based, prospective cohort study (35 316 white women included), were analyzed; and individual-level genotype data from the UKB were extracted for further analysis. There were three modules of analysis. First, clinical IVF data were used to test the association between ovarian reserve biomarkers and the subsequent early spontaneous miscarriage risk. Second, the UKB data were used to test the association of spontaneous miscarriage history and early menopause. Third, individual-level genotype data from the UKB were analyzed to identify specific pleiotropic genes which affect the development of miscarriage and menopause. In the analysis of clinical IVF data, the risk of early spontaneous miscarriage was 1.57 times higher in the group with AMH < 1.1 ng/ml group (P < 0.001), 1.62 times for antral follicular count <5 (P < 0.001), and 1.39 times for FSH ≥10 mIU/ml (P < 0.001) in comparison with normal ovarian reserve groups. In the analysis of UKB data, participants with a history of three or more miscarriages had a one-third higher risk of experiencing early menopause (odds ratio: 1.30, 95% CI 1.13-1.49, P < 0.001), compared with participants without spontaneous miscarriage history. We identified 158 shared genetic risk loci that affect both miscarriage and menopause, which enrichment analysis showed were involved in antigen processing and presentation and autoimmune disease pathways. The analyses of the UKB data were restricted to participants of European ancestry, as 94.6% of the cohort were of white ethnicity. Further studies are needed in non-white populations. Additionally, maternal age at the time of spontaneous miscarriage was not available in the UKB cohort, therefore we adjusted for age at baseline assessment in the models instead. It is known that miscarriage rate in IVF is higher compared to natural conception, highlighting a need for caution when generalizing our findings from the IVF cohort to the general population. Our findings have implications for IVF clinicians in terms of patient counseling on the prognosis of IVF treatment, as well as for genetic counseling regarding miscarriage. Our results highlight the importance of further research on the shared genetic architecture and common pathophysiological basis of DOR and miscarriage, which may lead to new therapeutic opportunities. This work was supported by the Hunan Youth Science and Technology Innovation Talent Project (2020RC3060), the International Postdoctoral Exchange Fellowship Program (Talent-Introduction Program, YJ20220220), the fellowship of China Postdoctoral Science Foundation (2022M723564), and the Natural Science Foundation of Hunan Province, China (2023JJ41016). This work has been accepted for poster presentation at the 39th Annual Meeting of ESHRE, Copenhagen, Denmark, 25-28 June 2023 (Poster number: P-477). The authors declare no conflict of interest. N/A.

Genome-wide association study of esophageal squamous cell cancer identifies shared and distinct risk variants in African and Chinese populations

Esophageal squamous cell carcinoma (ESCC) has a high disease burden in sub-Saharan Africa and has a very poor prognosis. Genome-wide association studies (GWASs) of ESCC in predominantly East Asian populations indicate a substantial genetic contribution to its etiology, but no genome-wide studies have been done in populations of African ancestry. Here, we report a GWAS in 1,686 African individualswith ESCC and 3,217 population-matched control individuals to investigate its genetic etiology. We identified a genome-wide-significant risk locus on chromosome 9 upstream of FAM120A (rs12379660, p= 4.58×10-8, odds ratio= 1.28, 95% confidence interval= 1.22-1.34), as well as a potential African-specific risk locus on chromosome 2 (rs142741123, p= 5.49×10-8) within MYO1B. FAM120A is a component of oxidative stress-induced survival signals, and the associated variants at the FAM120A locus co-localized withhighly significant cis-eQTLs in FAM120AOS in both esophageal mucosa and esophageal muscularis tissue. A trans-ethnic meta-analysis was then performed with the African ESCC study and a Chinese ESCC study in a combined total of 3,699 ESCC-affected individuals and 5,918 control individuals, which identified three genome-wide-significant loci on chromosome 9 at FAM120A (rs12379660, pmeta= 9.36×10-10), chromosome 10 at PLCE1 (rs7099485, pmeta= 1.48×10-8), and chromosome 22 at CHEK2 (rs1033667, pmeta= 1.47×10-9). This indicates the existence of both shared and distinct genetic risk loci for ESCC in African and Asian populations. Our GWAS of ESCC conducted in a population of African ancestry indicates a substantial genetic contribution to ESCC risk in Africa.

Cross-trait genome-wide association analysis of C-reactive protein level and psychiatric disorders

C-reactive protein (CRP) tends to be elevated in individuals with psychiatric disorders. Recent findings have suggested a protective effect of the genetic liability to elevated CRP on schizophrenia risk and a causative effect on depression despite weak genetic correlations, while causal relationships with bipolar disorder were inconclusive. We investigated the shared genetic underpinnings of psychiatric disorders and variation in CRP levels. Genome-wide association studies for CRP (n = 575,531), bipolar disorder (n = 413,466), depression (n = 480,359), and schizophrenia (n = 130,644) were used in causal mixture models to compare CRP with psychiatric disorders based on polygenicity, discoverability, and genome-wide genetic overlap. The conjunctional false discovery rate method was used to identify specific shared genetic loci. Shared variants were mapped to putative causal genes, which were tested for overrepresentation among gene ontology gene-sets. CRP was six to ten times less polygenic (n = 1400 vs 8600–14,500 variants) and had a discoverability one to two orders of magnitude higher than psychiatric disorders. Most CRP-associated variants were overlapping with psychiatric disorders. We identified 401 genetic loci jointly associated with CRP and psychiatric disorders with mixed effect directions. Gene-set enrichment analyses identified predominantly CNS-related gene sets for CRP and each of depression and schizophrenia, and basic cellular processes for CRP and bipolar disorder. In conclusion, CRP has a markedly different genetic architecture to psychiatric disorders, but the majority of CRP associated variants are also implicated in psychiatric disorders. Shared genetic loci implicated CNS-related processes to a greater extent than immune processes, which may have implications for how we conceptualise causal relationships between CRP and psychiatric disorders.

P-477 Bidirectional association between ovarian reserve and spontaneous miscarriage: findings from the clinical IVF data to epidemiological evidence and genetic links

Abstract Study question To determine whether the association between ovarian reserve and spontaneous miscarriage risk is bidirectional and caused by shared genetic risk loci. Summary answer Bidirectional association between ovarian reserve and spontaneous miscarriage was observed. This may be attributed to five shared risk genes (SYCP2L, TP63, GSPT1, RIF1, and PRRC2A). What is known already Previous studies have shown that women with lower serum anti-Müllerian hormone (AMH) had an increased risk of embryo aneuploidy or spontaneous miscarriage risk, compared to women with higher AMH concentration, although not all studies agree. The most recent meta-analysis postulated that the association between diminished ovarian reserve (DOR) and miscarriage may be not causal, but that the two occurrences merely share a common cause, such as other systematic clinical conditions or past exposure. Inspired by this hypothesis, we conducted the present analyses to clarify this bidirectional association between DOR and miscarriage and further elucidate plausible mechanisms by using genetic data. Study design, size, duration There were four data sources. 1) The Clinical IVF data were retrospectively collected from an academically affiliated Reproductive Medicine Center (17,786 cycles included). 2) We further analyzed data from the UK Biobank (UKB) which is a large-scale, population-based, prospective cohort study (35,316 white women included). 3) The GWAS summary statistics for age at natural menopause (ANM) and spontaneous miscarriage were obtained from published GWAS studies. 4) The individual-level genotype data were also extracted from UKB. Participants/materials, setting, methods There were four analysis modules, 1) IVF data to test the association of ovarian reserve and miscarriage risk by using logistic regression models, 2) UKB data to test the association of spontaneous miscarriage history and ANM by using linear regression models, 3) GWAS summary data to test the overall genetic enrichment between miscarriage and ANM by plotting Q-Q plot, and 4) individual-level genotype data to identify specific shared genes by using ‘pleio’ R package. Main results and the role of chance In the analysis of clinical data, the risk of miscarriage was 1.5 (95% CI: 1.22-1.85, p &amp;lt; 0.001) times in the group with AMH&amp;lt;1.1 ng/ml, compared to the group with AMH &amp;gt; =1.1 ng/ml after adjustment. In the analysis of UK Biobank data, one more spontaneous miscarriage history would lead to 0.02 (95% CI: 0.00-0.03, p = 0.032) years earlier in the standardized ANM after adjustment. Participants with &amp;gt; =2 spontaneous miscarriage history would have 0.05 (95% CI:0.01-0.08, p = 0.011) years earlier in standardized ANM, compared with participants with &amp;lt; =1 spontaneous miscarriage. In the analysis of GWAS summary statistics, we found that there were 11,736,532 single nucleotide polymorphisms (SNPs) tested by both GWAS studies of ANM and miscarriage. In the stratified conditional Q-Q plot, successive leftward deflections did not show which suggested that an overall genetic overlap between miscarriage and ANM was not observed. In the analysis of the individual-level genotype data, we identified five shared genetic risk loci that affect both miscarriage and menopause. They were all novel risk genes for spontaneous miscarriage. Of these five genes, SYCP2L, TP63, GSPT1, and RIF1 were associated with congenital malformations and PRRC2A was associated with autoimmune disease, which are factors that possibly play a role in the occurrence of miscarriage. Limitations, reasons for caution The UKB epidemiology data and genetic data were restricted to participants of European ancestry. Further studies are needed in non-white populations. Second, the predictive value of GWAS summary data for miscarriage may be limited which results in a null finding in the conditional Q-Q plot. Wider implications of the findings Our findings could be of interest to IVF clinicians in patient counseling regarding the prognosis of IVF treatment and genetic counseling for miscarriage. Our findings encourage further research focus on the shared genetic architecture and common pathophysiological basis of diminished ovarian reserve and miscarriage which may bring new therapeutic opportunities. Trial registration number not applicable