Linkage Disequilibrium Score Regression Research Articles

Genome-Wide Assessment of Shared Genetic Architecture Between Rheumatoid Arthritis and Cardiovascular Diseases.

Background Patients with rheumatoid arthritis (RA) have a 2- to 10-fold increased risk of cardiovascular disease (CVD), but the biological mechanisms and existence of causality underlying such associations remain to be investigated. We aimed to investigate the genetic associations and underlying mechanisms between RA and CVD by leveraging large-scale genomic data and genetic cross-trait analytic approaches. Methods and Results Within UK Biobank data, we examined the genetic correlation, shared genetics, and potential causality between RA (Ncases=6754, Ncontrols=452 384) and cardiovascular diseases (CVD, Ncases=44 238, Ncontrols=414 900) using linkage disequilibrium score regression, cross-trait meta-analysis, and Mendelian randomization. We observed significant genetic correlations of RA with myocardial infarction (rg:0.40 [95% CI, 0.24-0.56), angina (rg:0.42 [95% CI, 0.28-0.56]), coronary heart diseases (rg:0.41 [95% CI, 0.27-0.55]), and CVD (rg:0.43 [95% CI, 0.29-0.57]) after correcting for multiple testing (P<0.05/5). When stratified by frequent use of analgesics, we found increased genetic correlation between RA and CVD among participants without aspirin usage (rg:0.54 [95% CI, 0.30-0.78] for angina; Pvalue=6.69×10-6) and among participants with paracetamol usage (rg:0.75 [95% CI, 0.20-1.29] for myocardial infarction; Pvalue=8.90×10-3), whereas others remained similar. Cross-trait meta-analysis identified 9 independent shared loci between RA and CVD, including PTPN22 at chr1p13.2, BCL2L11 at chr2q13, and CCR3 at chr3p21.31 (Psingle trait<1×10-3 and Pmeta<5×10-8), highlighting potential shared pathogenesis including accelerating atherosclerosis, upregulating oxidative stress, and vascular permeability. Finally, Mendelian randomization estimates showed limited evidence of causality between RA and CVD. Conclusions Our results supported shared genetic pathogenesis rather than causality in explaining the observed association between RA and CVD. The identified shared genetic factors provided insights into potential novel therapeutic target for RA-CVD comorbidities.

Exploring the causal correlations between 486 serum metabolites and systemic lupus erythematosus: a bidirectional Mendelian randomization study.

Objective: The observational association between circulating metabolites and systemic lupus erythematosus (SLE) has been well documented. However, whether the association is causal remains unclear. In this study, bidirectional Mendelian randomization (MR) was introduced to analyse the causal relationships and possible mechanisms. Methods: We conducted a two-sample bidirectional MR study. A genome-wide association study (GWAS) with 7,824 participants provided data on 486 human blood metabolites. Outcome information was obtained from a large-scale GWAS summary, which contained 5,201 single nucleotide polymorphisms (SNPs) cases and 9,066 control cases of Europeans and yielded a total of 7,071,163 SNPs. The inverse variance weighted (IVW) model was recruited as the primary two-sample MR analysis approach, followed by sensitivity analyses such as the heterogeneity test, horizontal pleiotropy test, leave-one-out analysis, and linkage disequilibrium score (LDSC) regression. Results: In this study, we discovered that 24 metabolites belonging to the lipid, carbohydrate, xenobiotic and amino acid superpathways may increase the risk of SLE occurrence (p < 0.05). In addition, the metabolic disorders of 51 metabolites belonging to the amino acid, energy, xenobiotics, peptide and lipid superpathways were affected by SLE (p < 0.05). Palmitoleate belonging to the lipid superpathway and isobutyrylcarnitine and phenol sulfate belonging to the amino acid superpathway were factors with two-way causation. The metabolic enrichment pathway of bile acid biosynthesis was significant in the forward MR analysis (p = 0.0435). Linolenic acid and linoleic acid metabolism (p = 0.0260), betaine metabolism (p = 0.0314), and glycerolipid metabolism (p = 0.0435) were the significant metabolically enriched pathways in the reverse MR analysis. Conclusion: The levels of some specific metabolites may either contribute to the immune response inducing SLE, or they may be intermediates in the development and progression of SLE. These metabolites can be used as auxiliary diagnostic tools for SLE and for the evaluation of disease progression and therapeutic effects.

Abstract 18244: A Multi-Ancestry GWAS of Calcific Aortic Stenosis Among 2.7 Million Individuals

Introduction: Calcific aortic stenosis (CAS) is a common, progressive fibrocalcific pathology of the aortic valve without medical therapy. The genetics of CAS remain only partially understood. Methods: We performed a genome wide association study (GWAS) of CAS among 2,799,598 individuals from the International Aortic Valve Genetics Consortium (IAVGC), comprising 28 cohorts. CAS was identified using a common ICD/CPT based phenotype. GWAS were meta-analyzed using inverse variance weighting with adjustment by linkage-disequilibrium score regression (LDSR) intercept. Unique genome-wide significant (GWS) loci and causal genes were annotated by nearest gene and eQTL colocalization. Genetic correlations were performed against atherosclerotic, adiposity, and lipid traits using LDSR with publicly available GWAS (CARDIoGRAMplusC4D for coronary artery disease [CAD], Million Veteran Program for peripheral artery disease [PAD], MEGASTROKE for ischemic stroke [IS], GIANT for body mass index [BMI], and GLGC for lipids). Results: There were 85,329 individuals with CAS (79,397 White, 3,126 Black, 1,403 Hispanic, and 1,403 East Asian) among 2,799,598 individuals. Meta-analysis of GWAS resulted in 224 unique GWS genomic regions, of which 205 were novel. The majority of the GWS genomic regions (134) did not overlap with prior risk loci for CAD, PAD, IS, BMI, or lipids. Genetic correlation demonstrated modest but significant correlations between CAS and CAD ( r =0.26, p=3.3x10 -18 ), PAD ( r =0.41, p=1.4x10 -30 ), IS ( r =0.18,p=2.8x10 -7 ), BMI ( r =0.22,p=8.6x10 -30 ), and lipids (LDL-C r =0.17,p=3.6x10 -10 ;triglycerides r =0.10,p=1.9x10 -5 ; HDL-C r =-0.07,p=8.0x10 -4 ). Conclusions: This largest to-date multi-ancestry GWAS of CAS identified 205 novel genomic regions. We demonstrate that CAS is genetically distinct from cardiometabolic traits, with only modest genetic correlations and with a majority of CAS risk loci having no overlap with cardiometabolic GWAS risk loci.

Abstract 16503: C-X-C Motif Chemokine Ligand 12 is a Primary Determinant of Coronary Artery Dominance

Introduction: Left coronary dominance is associated with worse clinical outcomes in the setting of coronary artery disease (CAD). Little is known about the determinants of dominance, including whether it is solidified in utero or sometime after birth. Hypothesis: Investigating the genetic determinants of dominance will identify new arteriogenesis pathways targetable for enhancing coronary artery growth and collateralization in humans. Methods: We conducted a stratified multi-population genome-wide association study of dominance using REGENIE and TopMed-imputed genotypes available in 43813 White, 9532 Black, and 3550 Hispanic participants of the Million Veteran Program (MVP) who had undergone a cardiac catheterization. We modelled left and co-dominant combined vs. right, as well as left vs. right dominance, adjusting for sex and 10 genetic principal components. We also explored whether dominance and CAD were genetically correlated using LD score regression. Lastly, we sought to validate compelling population genetic signals in mice using whole organ imaging of the heart, which allows for the quantification of coronary anatomy and variation. Results: Thirteen loci reached genome wide significance (GWS). The most intriguing was a top hit located downstream of C-X-C Motif Chemokine Ligand 12 (CXCL12) which, remarkably, reached GWS in both White and Black Veterans. While the CXCL12 signal robustly colocalized with the signal in this region for CAD (COLOC PPH4: 87.1%), the genome wide genetic correlation of dominance with CAD was otherwise modest in both MVP (rg=-0.18, p=0.007) and CardiogramplusC4D (rg=-0.16, p=0.018). To gain evidence for causality, we modeled dominance in Cxcl12-deficient mice (n=64 wildtype; n=62 heterozygous). Murine coronary arteries develop in a field of Cxcl12 expression and choose right or left dominance during embryogenesis, a time when we found human dominance to also be evident. Reminiscent of our human GWAS, dominance was skewed away from the common phenotype in Cxcl12 heterozygous mice (p=0.038). Conclusions: CXCL12 is a primary determinant of coronary artery dominance in humans and mice. The modest negative genetic correlation between CAD and dominance supports a developmental component to CAD susceptibility.

Acute pancreatitis and metabolic syndrome: genetic correlations and causal associations.

Although there is a definite correlation between the Metabolic Syndrome (MetS) and Acute Pancreatitis (AP), cause is yet unknown. The current work combined linkage disequilibrium score (LDSC) regression and Mendelian randomization (MR) approaches to fill this important information gap. In this study, we harnessed the power of publicly available gene-wide association databases (GWAS) to explore the intricate relationship between MetS and its components with AP. The cornerstone of our analysis was the Inverse-Variance Weighted (IVW) method, serving as our primary analytical tool. In addition to IVW, we complemented our investigation with several other robust MR methods, including MR-Egger, Weighted Median, Maximum Likelihood, and MR-PRESSO. By employing this diverse set of analytical approaches, we sought to ensure the comprehensiveness and robustness of our findings. LDSC regression indicated a genetic correlation between MetS and AP. Univariate MR results indicated a genetic association between MetS (OR = 1.084; 95% CI, 1.005-1.170; P = 0.037), BMI (OR = 1.459; 95% CI, 1.325-1.606; P = 1.46E-14), WHR (OR = 1.189; 95% CI, 1.068-1.323; P = 1.56 E-03), TG (OR = 1.110; 95% CI, 1.001-1.231; P = 0.047), and FI (OR = 1.798; 95% CI, 1.245-2.595; P = 1.74E-03) were able to significantly increase the risk of AP. The results of multivariate MR analysis revealed that these causality associations still existed. Our investigation has yielded compelling evidence that substantiates the presence of both a genetic correlation and a causal relationship between MetS and AP.

Association between rheumatoid arthritis and autoimmune thyroid disease: evidence from complementary genetic methods.

To assess the causal association of Rheumatoid Arthritis (RA) with Autoimmune thyroid disease (AITD). Complementary genetic approaches, including genetic correlation, Mendelian randomization (MR) and colocalization analysis, were conducted to assess the potential causal association between RA and AITD using summary statistics from large-scale genome-wide association studies (GWASs). Various sensitivity analyses had been conducted to assess the robustness and the consistency of the findings. The linkage disequilibrium score regression revealed a shared genetic structure between RA and AITD, with the significant genetic correlation between RA and autoimmune hyperthyroidism and autoimmune hypothyroidism estimated to be 0.3945 (P = 2.83 × 10-6) and 0.2771 (P = 1.04 × 10-6) respectively. The results of MR analysis showed that RA had a positive causal relationship with autoimmune hypothyroidism and autoimmune hyperthyroidism. The odds ratio (OR) were 1.29 (95% CI, 1.17-1.42; P = 1.08 × 10-7) and 1.47 (95% CI, 1.25-1.72; P = 1.85 × 10-6), respectively. In reverse MR analysis, autoimmune hypothyroidism had a positive causal relationship with RA, OR was 1.51 (95% CI, 1.37-1.66; P = 1.10 × 10-16); autoimmune hyperthyroidism had no causal relationship with RA relationship (P = 0.22). Similar results were found using different MR methods. In addition, colocalization analysis suggested that shared causal variants existed between RA and AITD. Our study suggested a potentially causal effect of genetically predicted RA on autoimmune hyperthyroidism and a bidirectional causal relationship between RA and autoimmune hypothyroidism was also observed with complementary genetic approaches, which supports the importance and necessity of thyroid function screening and monitoring in RA patient management in clinical practice.

Causal inference of sex hormone-binding globulin on venous thromboembolism: evidence from Mendelian randomisation

BackgroundPrevious cohort studies have shown that exogenous sex hormone use, such as testosterone replacement therapy and oestrogen-containing contraceptives, can increase the risk of venous thromboembolism (VTE). However, the relationship between endogenous sex hormone levels and VTE remains unclear. The goal of the present study was to explore the causal roles of endogenous sex hormones, including hormone-binding globulin (SHBG), bioactive testosterone (BT), and total testosterone (TT), in VTE and its two subgroups, deep vein thrombosis (DVT) and pulmonary embolism (PE).MethodsWe used a genome-wide association study of sex hormones as exposure data and Finnish VTE data as the outcome. Inverse variance weighting, MR-Egger, and weighted median were used for two-sample Mendelian randomisation (MR). Sensitivity analyses included MR-Egger, MR-PRESSO, Cochrane Q test, MR Steiger, leave-one-out analysis, and funnel plot, combined with multivariate MR and replicated MR analyses using larger VTE data from the global biobank meta-analysis initiative. Linkage disequilibrium score regression (LDSC) was used to determine genetic associations and estimate sample overlap.ResultsOur findings genetically predicted that an increase in serum SHBG levels by one standard deviation (SD) caused 25% higher odds for VTE (OR: 1.25, 95% CI: 1.01−1.55) and 58% higher odds for PE (OR: 1.58, 95% CI: 1.20−2.08). LDSC supported the genetic correlation between these two traits and replicated analyses confirm SHBG’s genetic effect on VTE in both sexes (OR: 1.46, 95% CI: 1.20−1.78) and in females (OR: 1.49, 95% CI: 1.17−1.91). In addition, an increase in serum TT levels by one SD caused 32% higher odds for VTE (OR: 1.32, 95% CI: 1.08−1.62) and 31% higher odds for DVT (OR: 1.31, 95% CI: 1.01−1.69); however, LDSC and replicated analyses did not find a genetic correlation between TT and VTE or its subtypes. No significant correlation was observed between BT and all three outcome traits.ConclusionOur study provides evidence that elevated serum SHBG levels, as predicted by genetics, increase VTE risk. However, the causal effect of testosterone levels on VTE requires further investigation.

Multiple long-term conditions in people with psoriasis: alatent class and bidirectional Mendelian randomization analysis.

Coexisting long-term conditions (LTCs) in psoriasis and their potential causal associations with the disease are not well -established. To determine distinct clusters of LTCs in people with psoriasis and the potential bidirectional causal association between these LTCs and psoriasis. Using latent class analysis, cross-sectional data from people with psoriasis from the UK Biobank were analysed to identify distinct psoriasis-related comorbidity profiles. Linkage disequilibrium score regression (LDSR) was applied to compute the genetic correlation between psoriasis and LTCs. Two-sample bidirectional Mendelian randomization (MR) analysis assessed the potential causal direction using independent genetic variants that reached genome-wide significance (P < 5 × 10-8). Five comorbidity clusters were identified in a population of 10 873 people with psoriasis. LDSR revealed that psoriasis was positively genetically correlated with heart failure [genetic correlation (rg) = 0.23, P = 8.8 × 10-8], depression (rg = 0.12, P = 2.7 × 10-5), coronary artery disease (CAD; rg = 0.15, P = 2 × 10-4) and type 2 diabetes (rg = 0.19, P = 3 × 10-3). Genetic liability to CAD was associated with an increased risk of psoriasis [inverse variance weighted (IVW) odds ratio (ORIVW) 1.159, 95% confidence interval (CI) 1.055-1.274; P = 2 × 10-3]. The MR pleiotropy residual sum and outlier (MR-PRESSO; ORMR-PRESSO 1.13, 95% CI 1.042-1.228; P = 6 × 10-3) and the MR-robust adjusted profile score (RAPS) (ORMR-RAPS 1.149, 95% CI 1.062-1.242; P = 5 × 10-4) approaches corroborate the IVW findings. The weighted median (WM) generated similar and consistent effect estimates but was not statistically significant (ORWM 1.076, 95% CI 0.949-1.221; P = 0.25). Evidence for a suggestive increased risk was detected for CAD (ORIVW 1.031, 95% CI 1.003-1.059; P = 0.03) and heart failure (ORIVW 1.019, 95% CI 1.005-1.033; P = 9 × 10-3) in those with a genetic liability to psoriasis; however, MR sensitivity analyses did not reach statistical significance. Five distinct clusters of psoriasis comorbidities were observed with these findings to offer opportunities for an integrated approach to comorbidity prevention and treatment. Coexisting LTCs share with psoriasis common genetic and nongenetic risk factors, and aggressive lifestyle modification in these people is anticipated to have an impact beyond psoriasis risk. Genetically predicted CAD is possibly associated with an increased risk of psoriasis, altering our prior knowledge.

Meta-analysis of genome-wide association studies of gestational duration and spontaneous preterm birth identifies new maternal risk loci.

Preterm birth (<37 weeks of gestation) is a major cause of neonatal death and morbidity. Up to 40% of the variation in timing of birth results from genetic factors, mostly due to the maternal genome. We conducted a genome-wide meta-analysis of gestational duration and spontaneous preterm birth in 68,732 and 98,370 European mothers, respectively. The meta-analysis detected 15 loci associated with gestational duration, and four loci associated with preterm birth. Seven of the associated loci were novel. The loci mapped to several biologically plausible genes, for example HAND2 whose expression was previously shown to decrease during gestation, associated with gestational duration, and GC (Vitamin D-binding protein), associated with preterm birth. Downstream in silico-analysis suggested regulatory roles as underlying mechanisms for the associated loci. LD score regression found birth weight measures as the most strongly correlated traits, highlighting the unique nature of spontaneous preterm birth phenotype. Tissue expression and colocalization analysis revealed reproductive tissues and immune cell types as the most relevant sites of action. We report novel genetic risk loci that associate with preterm birth or gestational duration, and reproduce findings from previous genome-wide association studies. Altogether, our findings provide new insight into the genetic background of preterm birth. Better characterization of the causal genetic mechanisms will be important to public health as it could suggest new strategies to treat and prevent preterm birth.

Large-scale meta-genome-wide association study reveals common genetic factors linked to radiation-induced acute toxicities across cancer types.

This study was designed to identify common genetic susceptibility and shared genetic variants associated with acute radiation-induced toxicity across 4 cancer types (prostate, head and neck, breast, and lung). A genome-wide association study meta-analysis was performed using 19 cohorts totaling 12 042 patients. Acute standardized total average toxicity (STATacute) was modelled using a generalized linear regression model for additive effect of genetic variants, adjusted for demographic and clinical covariates (rSTATacute). Linkage disequilibrium score regression estimated shared single-nucleotide variation (SNV-formerly SNP)-based heritability of rSTATacute in all patients and for each cancer type. Shared SNV-based heritability of STATacute among all cancer types was estimated at 10% (SE = 0.02) and was higher for prostate (17%, SE = 0.07), head and neck (27%, SE = 0.09), and breast (16%, SE = 0.09) cancers. We identified 130 suggestive associated SNVs with rSTATacute (5.0 × 10‒8 < P < 1.0 × 10‒5) across 25 genomic regions. rs142667902 showed the strongest association (effect allele A; effect size ‒0.17; P = 1.7 × 10‒7), which is located near DPPA4, encoding a protein involved in pluripotency in stem cells, which are essential for repair of radiation-induced tissue injury. Gene-set enrichment analysis identified 'RNA splicing via endonucleolytic cleavage and ligation' (P = 5.1 × 10‒6, P = .079 corrected) as the top gene set associated with rSTATacute among all patients. In silico gene expression analysis showed that the genes associated with rSTATacute were statistically significantly up-regulated in skin (not sun exposed P = .004 corrected; sun exposed P = .026 corrected). There is shared SNV-based heritability for acute radiation-induced toxicity across and within individual cancer sites. Future meta-genome-wide association studies among large radiation therapy patient cohorts are worthwhile to identify the common causal variants for acute radiotoxicity across cancer types.

Circulating vitamin levels mediate the causal relationship between gut microbiota and cholecystitis: a two-step bidirectional Mendelian randomization study.

The relationship between gut microbiota and the occurrence of cholecystitis remains unclear. Existing research lacks a clear understanding of how circulating vitamin levels modulate this relationship. Therefore, our study aims to investigate whether circulating vitamin levels mediate the causal relationship between gut microbiota and cholecystitis using a two-step bidirectional Mendelian randomization approach. In this study, we initially employed Linkage Disequilibrium Score Regression (LDSC) analysis to assess the genetic correlation of five circulating vitamin level genome-wide association study (GWAS) summary datasets, thereby avoiding potential sample overlap. Subsequently, we conducted a two-step analysis to investigate the causal effects between gut microbiota and cholecystitis. In the second step, we explored the causal relationship between circulating vitamin levels and cholecystitis and identified the mediating role of vitamin D. The primary method used for causal analysis was the inverse variance-weighted approach. We performed additional sensitivity analyses to ensure result robustness, including the cML-MA method and reverse Mendelian randomization (MR) analysis. An increment of one standard deviation in RuminococcaceaeUCG003 was associated with a 25% increased risk of cholecystitis (OR = 1.25, 95%CI = 1.01-1.54, p = 0.04), along with a 3% decrease in 25-hydroxyvitamin D levels (OR = 0.97, 95%CI = 0.944-0.998, p = 0.04). However, following the rigorous Bonferroni correction, every one standard deviation decrease in circulating vitamin D levels was associated with a 33% increased risk of cholecystitis (OR = 0.67, 95%CI = 0.49-0.90, p = 0.008, Padjust = 0.04). Thus, the potential link between gut microbiota and cholecystitis risk might be mediated by circulating vitamin D levels (proportion mediated = 5.5%). Sensitivity analyses provided no evidence of pleiotropy. Our study results suggest that an elevated abundance of specific gut microbiota is associated with an increased susceptibility to cholecystitis, with the causal relationship being mediated by circulating vitamin D levels. Further large-scale randomized controlled trials are necessary to validate the causal effects of gut microbiota on cholecystitis risk. This study provides novel insights into cholecystitis prevention through the regulation of gut microbiota.

Determination of genetic correlation between tobacco smoking and coronary artery disease.

Tobacco smoking is an important risk factor for coronary artery disease (CAD), but the genetic mechanisms linking smoking to CAD remain largely unknown. We analyzed summary data from the genome-wide association study (GWAS) of the UK Biobank for CAD, plasma lipid concentrations (n = 184,305), and smoking (n = 337,030) using different biostatistical methods, which included LD score regression and Mendelian randomization (MR). We identified SNPs shared by CAD and at least one smoking behavior, the genes where these SNPs are located were found to be significantly enriched in the processes related to lipoprotein metabolic, chylomicron-mediated lipid transport, lipid digestion, mobilization, and transport. The MR analysis revealed a positive correlation between smoking cessation and decreased risk for CAD when smoking cessation was considered as exposure (p = 0.001), and a negative correlation between the increased risk for CAD and smoking cessation when CAD was considered as exposure (p = 2.95E-08). This analysis further indicated that genetic liability for smoking cessation increased the risk of CAD. These findings inform the concomitant conditions of CAD and smoking and support the idea that genetic liabilities for smoking behaviors are strongly associated with the risk of CAD.

Inference of Coalescence Times and Variant Ages Using Convolutional Neural Networks.

Accurate inference of the time to the most recent common ancestor (TMRCA) between pairs of individuals and of the age of genomic variants is key in several population genetic analyses. We developed a likelihood-free approach, called CoalNN, which uses a convolutional neural network to predict pairwise TMRCAs and allele ages from sequencing or SNP array data. CoalNN is trained through simulation and can be adapted to varying parameters, such as demographic history, using transfer learning. Across several simulated scenarios, CoalNN matched or outperformed the accuracy of model-based approaches for pairwise TMRCA and allele age prediction. We applied CoalNN to settings for which model-based approaches are under-developed and performed analyses to gain insights into the set of features it uses to perform TMRCA prediction. We next used CoalNN to analyze 2,504 samples from 26 populations in the 1,000 Genome Project data set, inferring the age of ∼80 million variants. We observed substantial variation across populations and for variants predicted to be pathogenic, reflecting heterogeneous demographic histories and the action of negative selection. We used CoalNN's predicted allele ages to construct genome-wide annotations capturing the signature of past negative selection. We performed LD-score regression analysis of heritability using summary association statistics from 63 independent complex traits and diseases (average N=314k), observing increased annotation-specific effects on heritability compared to a previous allele age annotation. These results highlight the effectiveness of using likelihood-free, simulation-trained models to infer properties of gene genealogies in large genomic data sets.

Causal Link between Gut Microbiota, Neurophysiological States, and Bone Diseases: A Comprehensive Mendelian Randomization Study.

Increasing evidence highlights a robust correlation between the gut microbiota and bone diseases; however, the existence of a causal relationship between them remains unclear. In this study, we thoroughly examined the correlation between gut microbiota and skeletal diseases using genome-wide association studies. Linkage disequilibrium score regression and Mendelian randomization were used to probe genetic causality. Furthermore, the potential mediating role of neuropsychological states (i.e., cognition, depression, and insomnia) between the gut microbiota and bone diseases was evaluated using mediation analysis, with genetic colocalization analysis revealing potential targets. These findings suggest a direct causal relationship between Ruminococcaceae and knee osteoarthritis (OA), which appears to be mediated by cognitive performance and insomnia. Similarly, a causal association was observed between Burkholderiales and lumbar pelvic fractures, mediated by cognitive performance. Colocalization analysis identified a shared causal variant (rs2352974) at the TRAF-interacting protein locus for cognitive ability and knee OA. This study provides compelling evidence that alterations in the gut microbiota can enhance cognitive ability, ameliorate insomnia, and potentially reduce the risk of site-specific fractures and OA. Therefore, strategies targeting gut microbiota optimization could serve as novel and effective preventive measures against fractures and OA.

Denture use and risk for cardiometabolic disease: observational and Mendelian randomization analyses.

Denture use may potentially increase the risk of cardiometabolic diseases (CMDs), but the casual relevance and strength of the associations are currently unknown. A total of 495 938 participants from the UK Biobank were included in the observational analyses. Linkage disequilibrium score (LDSC) regression and Mendelian randomization analyses were employed to estimate genetic correlation and the associations between the genetic liability for denture use with coronary artery disease, myocardial infarction, heart failure (HF), any stroke (AS), ischaemic stroke, haemorrhagic stroke, type 2 diabetes (T2D), and related clinical risk factors. In observational analysis, denture use was associated with 14-25% higher risks of various CMDs. The LDSC analysis found that denture use showed a positive genetic correlation with CMDs (rg 0.21-0.38). Genetic liability for denture use was associated with an elevated risk of HF [odds ratio: 1.49 (1.20-1.83)] and T2D [1.11 (1.01-1.24)]. By integrating genetic summary data of denture use with the sum of decayed, missing, and filled tooth surfaces (DMFS), a clinical measure of dental caries obtained from an independent source, genetically determined denture use/DMFS was also associated with an elevated risk of AS [1.21 (1.04-1.40)]. Furthermore, genetically predicted denture use/DMFS was significantly associated with established cardiometabolic risk factors, including HDL cholesterol, triglycerides, waist circumference, waist-to-hip ratio, and height. Our study supported potential causal associations between the genetic liability for denture use and risks for HF, AS, T2D, and related clinical risk factors. These findings may inform prevention and intervention strategies targeting dental diseases and CMDs.

Genome-wide Association Studies of Retinal Vessel Tortuosity Identify Numerous Novel Loci Revealing Genes and Pathways Associated With Ocular and Cardiometabolic Diseases.

To identify novel susceptibility loci for retinal vascular tortuosity, to better understand the molecular mechanisms modulating this trait, and reveal causal relationships with diseases and their risk factors. Genome-wide Association Studies (GWAS) of vascular tortuosity of retinal arteries and veins followed by replication meta-analysis and Mendelian randomization (MR). We analyzed 116 639 fundus images of suitable quality from 63 662 participants from 3 cohorts, namely the UK Biobank (n=62 751), the Swiss Kidney Project on Genes in Hypertension (n=397), and OphtalmoLaus (n=512). Using a fully automated retina image processing pipeline to annotate vessels and a deep learning algorithm to determine the vessel type, we computed the median arterial, venous and combined vessel tortuosity measured by the distance factor (the length of a vessel segment over its chord length), as well as by 6 alternative measures that integrate over vessel curvature. We then performed the largest GWAS of these traits to date and assessed gene set enrichment using the novel high-precision statistical method PascalX. We evaluated the genetic association of retinal tortuosity, measured by the distance factor. Higher retinal tortuosity was significantly associated with higher incidence of angina, myocardial infarction, stroke, deep vein thrombosis, and hypertension. We identified 175 significantly associated genetic loci in the UK Biobank; 173 of these were novel and 4 replicated in our second, much smaller, metacohort. We estimated heritability at ∼25% using linkage disequilibrium score regression. Vessel type specific GWAS revealed 116 loci for arteries and 63 for veins. Genes with significant association signals included COL4A2, ACTN4, LGALS4, LGALS7, LGALS7B, TNS1, MAP4K1, EIF3K, CAPN12, ECH1, and SYNPO2. These tortuosity genes were overexpressed in arteries and heart muscle and linked to pathways related to the structural properties of the vasculature. We demonstrated that retinal tortuosity loci served pleiotropic functions as cardiometabolic disease variants and risk factors. Concordantly, MR revealed causal effects between tortuosity, body mass index, and low-density lipoprotein. Several alleles associated with retinal vessel tortuosity suggest a common genetic architecture of this trait with ocular diseases (glaucoma, myopia), cardiovascular diseases, and metabolic syndrome. Our results shed new light on the genetics of vascular diseases and their pathomechanisms and highlight how GWASs and heritability can be used to improve phenotype extraction from high-dimensional data, such as images. The author(s) have no proprietary or commercial interest in any materials discussed in this article.

Genome-wide association study in 404,302 individuals identifies 7 significant loci for reaction time variability

Reaction time variability (RTV), reflecting fluctuations in response time on cognitive tasks, has been proposed as an endophenotype for many neuropsychiatric disorders. There have been no large-scale genome-wide association studies (GWAS) of RTV and little is known about its genetic underpinnings. Here, we used data from the UK Biobank to conduct a GWAS of RTV in participants of white British ancestry (n = 404,302) as well as a trans-ancestry GWAS meta-analysis (n = 44,873) to assess replication. We found 161 genome-wide significant single nucleotide polymorphisms (SNPs) distributed across 7 genomic loci in our discovery GWAS. Functional annotation of the variants implicated genes involved in synaptic function and neural development. The SNP-based heritability (h2SNP) estimate for RTV was 3%. We investigated genetic correlations between RTV and selected neuropsychological traits using linkage disequilibrium score regression, and found significant correlations with several traits, including a positive correlation with mean reaction time and schizophrenia. Despite the high genetic correlation between RTV and mean reaction time, we demonstrate distinctions in the genetic underpinnings of these traits. Lastly, we assessed the predictive ability of a polygenic score (PGS) for RTV, calculated using PRSice and PRS-CS, and found that the RTV-PGS significantly predicted RTV in independent cohorts, but that the generalisability to other ancestry groups was poor. These results identify genetic underpinnings of RTV, and support the use of RTV as an endophenotype for neurological and psychiatric disorders.

Association between COVID-19 and myasthenia gravis (MG): A genetic correlation and Mendelian randomization study.

Observational studies have suggested an association between coronavirus disease 2019 (COVID-19) and myasthenia gravis (MG). Here, we aimed to estimate the genetic correlation and causal relationship between COVID-19 susceptibility, hospitalization, severity, and MG phenotypes using linkage disequilibrium score regression (LDSC) and Mendelian randomization (MR) approach. Summary statistics of COVID-19 susceptibility, hospitalization, and severity were used as instrumental variables for exposure traits. Large-scale genome-wide association study (GWAS) data for MG were used as outcome traits. The inverse variance weighted approach was used for the main MR analysis, complemented by MR-Egger, weighted median, simple mode, and weighted mode methods. Sensitivity analysis was implemented using Cochran's Q test, MR-PRESSO method, and MR-Egger intercept test. LDSC analysis did not reveal any genetic correlation among COVID-19 susceptibility, hospitalization, severity, and MG phenotypes, including MG, early-onset MG, and late-onset MG (p>.05). Our MR analysis did not provide evidence supporting a causal effect of COVID-19 susceptibility, hospitalization, or severity on MG phenotypes (p>.05). Extensive sensitivity analysis strengthened the robustness and consistency of the MR estimates. Our study did not find evidence of a genetic correlation or causal relationship among COVID-19 susceptibility, hospitalization, severity, and MG. Future studies with more GWAS data are needed to evaluate the association between COVID-19 phenotypes and MG and its subgroups.

Distributed genetic effects of the corpus callosum subregions suggest links to neuropsychiatric disorders and related traits.

The corpus callosum (CC) is a brain structure with a high heritability and potential role in psychiatric disorders. However, the genetic architecture of the CC and the genetic link with psychiatric disorders remain largely unclear. We investigated the genetic architectures of the volume of the CC and its subregions and the genetic overlap with psychiatric disorders. We applied multivariate genome-wide association study (GWAS) to genetic and T1-weighted magnetic resonance imaging (MRI) data of 40,894 individuals from the UK Biobank, aiming to boost genetic discovery and to assess the pleiotropic effects across volumes of the five subregions of the CC (posterior, mid-posterior, central, mid-anterior and anterior) obtained by FreeSurfer 7.1. Multivariate GWAS was run combining all subregions, co-varying for relevant variables. Gene-set enrichment analyses were performed using MAGMA. Linkage disequilibrium score regression (LDSC) was used to determine Single nucleotide polymorphism (SNP)-based heritability of total CC volume and volumes of its subregions as well as their genetic correlations with relevant psychiatric traits. We identified 70 independent loci with distributed effects across the five subregions of the CC (p < 5 × 10-8). Additionally, we identified 33 significant loci in the anterior subregion, 23 in the mid-anterior, 29 in the central, 7 in the mid-posterior and 56 in the posterior subregion. Gene-set analysis revealed 156 significant genes contributing to volume of the CC subregions (p < 2.6 × 10-6). LDSC estimated the heritability of CC to (h2SNP = 0.38, SE = 0.03) and subregions ranging from 0.22 (SE = 0.02) to 0.37 (SE = 0.03). We found significant genetic correlations of total CC volume with bipolar disorder (BD, rg = -0.09, SE = 0.03; p = 5.9 × 10-3) and drinks consumed per week (rg = -0.09, SE = 0.02; p = 4.8 × 10-4), and volume of the mid-anterior subregion with BD (rg = -0.12, SE = 0.02; p = 2.5 × 10-4), major depressive disorder (MDD) (rg = -0.12, SE = 0.04; p = 3.6 × 10-3), drinks consumed per week (rg = -0.13, SE = 0.04; p = 1.8 × 10-3) and cannabis use (rg = -0.09, SE = 0.03; p = 8.4 × 10-3). Our results demonstrate that the CC has a polygenic architecture implicating multiple genes and show that CC subregion volumes are heritable. We found that distinct genetic factors are involved in the development of anterior and posterior subregions, consistent with their divergent functional specialisation. Significant genetic correlation between volumes of the CC and BD, drinks per week, MDD and cannabis consumption subregion volumes with psychiatric traits is noteworthy and deserving of further investigation.

Genetic Correlations between Migraine and Carpal Tunnel Syndrome.

Surgical deactivation of extracranial nerve trigger sites is now well established as an effective treatment for migraine headache. Parallels have been drawn to median nerve decompression for carpal tunnel syndrome (CTS), and 2 previous studies have demonstrated an association between migraine and CTS. The authors sought to (1) substantiate these findings in a considerably larger UK cohort, and (2) investigate potential genetic associations between the 2 disorders. Nested case-control studies were conducted in the UK Biobank cohort of 401,656 individuals. Odds ratios were calculated for the association between migraine and CTS in the overall cohort and sex-stratified subsets. Genetic correlation between migraine and CTS was interrogated by linkage disequilibrium score regression, leveraging data from published genomewide association studies. Regions of genetic overlap were identified by multitrait analysis of genomewide association studies and cross-phenotype association. Migraine and CTS show a significant epidemiologic association within UK Biobank (OR, 1.14, 95% CI, 1.04 to 1.25; P = 0.0058), which is specific to women (OR, 1.15; 95% CI, 1.04 to 1.28; P = 0.0057) and not men (OR, 1.07; 95% CI, 0.82 to 1.40; P = 0.61). Genetic analysis demonstrated a significant positive genetic correlation between the 2 disorders ( rg = 0.13; P = 0.0039), and implicated the TRIM32 locus on chromosome 9 as a region of genetic overlap. This study replicates past reports of an epidemiologic association between CTS and migraine, albeit in women only. This association is underpinned by a genetic correlation, with shared genetic susceptibility at the TRIM32 locus. The authors' data add credibility to the notion that an element of entrapment neuropathy underlies migraine pathophysiology. Risk, III.