Genome-wide Association Studies Datasets Research Articles

The relationship between emotional disorders and heart rate variability: A Mendelian randomization study.

Previous studies have shown that emotional disorders are negatively associated with heart rate variability (HRV), but the potential causal relationship between genetic susceptibility to emotional disorders and HRV remains unclear. We aimed to perform a Mendelian randomization (MR) study to investigate the potential association between emotional disorders and HRV. The data used for this study were obtained from publicly available genome-wide association study datasets. Five models, including the inverse variance weighted model (IVW), the weighted median estimation model (WME), the weighted model-based method (WM), the simple model (SM) and the MR-Egger regression model (MER), were utilized for MR. The leave-one-out sensitivity test, MR pleiotropy residual sum and outlier test (MR-PRESSO) and Cochran's Q test were used to confirm heterogeneity and pleiotropy. MR analysis revealed that genetic susceptibility to broad depression was negatively correlated with HRV (pvRSA/HF) (OR = 0.380, 95% CI 0.146-0.992; p = 0.048). However, genetic susceptibility to irritability was positively correlated with HRV (pvRSA/HF, SDNN) (OR = 2.017, 95% CI 1.152-3.534, p = 0.008) (OR = 1.154, 95% CI 1.000-1.331, p = 0.044). Genetic susceptibility to anxiety was positively correlated with HRV (RMSSD) (OR = 2.106, 95% CI 1.032-4.299; p = 0.041). No significant directional pleiotropy or heterogeneity was detected. The accuracy and robustness of these findings were confirmed through a sensitivity analysis. Our MR study provides genetic support for the causal effects of broad depression, irritable mood, and anxiety on HRV.

Association between gut microbiota and menstrual disorders: a two-sample Mendelian randomization study.

Evidence from observational studies and clinical trials suggests that the gut microbiota is associated with gynecological diseases. However, the causal relationship between gut microbiota and menstrual disorders remains to be determined. We obtained summary data of gut microbiota from the global consortium MiBio-Gen's genome-wide association study (GWAS) dataset and data on menstrual disorders from the IEU Open GWAS project. MR-Egger, weighted median, inverse variance weighted, simple mode, and weighted mode were used to examine the causal association between gut microbiota and menstrual disorders. Thorough sensitivity studies were performed to confirm the data's horizontal pleiotropy, heterogeneity, and robustness. Through MR analysis of 119 kinds of gut microbiota and 4 kinds of clinical phenotypes, it was discovered that 23 different kinds of gut microbiota were loosely connected to menstrual disorders. After FDR correction, the results showed that only Escherichia/Shigella (p = 0.00032, PFDR = 0.0382, OR = 1.004, 95%CI = 1.002-1.006) is related to menstrual disorders. According to our MR Analysis, there are indications of a causal relationship between menstrual disorders and gut microbiota. This finding could lead to new discoveries into the mechanisms behind menstrual disorders and clinical research involving the microbiota.

The causal association between circulating cytokines with the risk of frailty and sarcopenia under the perspective of geroscience.

Circulating cytokines were considered to play a critical role in the initiation and propagation of sarcopenia and frailty from observational studies. This study aimed to find the casual association between circulating cytokines and sarcopenia and frailty from a genetic perspective by two-sample Mendelian randomization (MR) analysis. Data for 41 circulating cytokines were extracted from the genome-wide association study dataset of 8,293 European participants. Inverse-variance weighted (IVW) method, MR-Egger, and weighted median method were applied to assess the relationship of circulating cytokines with the risk of aging-related syndromes and frailty. Furthermore, MR-Egger regression was used to indicate the directional pleiotropy, and Cochran's Q test was used to verify the potential heterogeneity. The "leave-one-out" method was applied to visualize whether there was a causal relationship affected by only one anomalous single-nucleotide polymorphisms. Genetic predisposition to increasing levels of interleukin-10 (IL-10), IL-12, and vascular endothelial growth factor (VEGF) was associated with the higher risk of low hand grip strength according to the IVW method [R = 1.05, 95% CI = 1.01-1.10, P = 0.028, false discovery rate (FDR)-adjusted P = 1.000; OR = 1.03, 95% CI = 1.00-1.07, P = 0.042, FDR-adjusted P = 0.784; OR = 1.02, 95% CI = 1.00-1.05, P = 0.038, FDR-adjusted P = 0.567]. Furthermore, genetically determined higher macrophage colony-stimulating factors (M-CSFs) were associated with a lower presence of appendicular lean mass (OR = 1.01, 95% CI = 1.00-1.02, P = 0.003, FDR-adjusted P = 0.103). Monokine induced by interferon-γ (MIG) and tumor necrosis factor-beta (TNF-β) were associated with a higher risk of frailty (OR = 1.03, 95% CI = 1.01-1.05, P < 0.0001, FDR-adjusted P= 0.012; OR = 1.01, 95% CI = 1.00-1.03, P = 0.013, FDR-adjusted P = 0.259). In this study, we did not find heterogeneity and horizontal pleiotropy between the circulating cytokines and the risk of frailty and sarcopenia. Genetic predisposition to assess IL-10, IL-12, and VEGF levels was associated with a higher risk of low hand grip strength and M-CSF with the presence of appendicular lean mass. The high levels of TNF-β and MIG were associated with a higher risk of frailty. More studies will be required to explore the molecular biological mechanisms underlying the action of inflammatory factors.

Causal effects of gut microbiota on autism spectrum disorder: A two-sample mendelian randomization study.

There is increasing evidence that alterations in gut microbiota (GM) composition are associated with autism spectrum disorder (ASD), but no reliable causal relationship has been established. Therefore, a 2-sample Mendelian randomization (MR) study was conducted to reveal a potential causal relationship between GM and ASD. Instrumental variables for 211 GM taxa were obtained from genome-wide association studies (GWAS) and Mendelian randomization studies to estimate their impact on ASD risk in the iPSYCH-PGC GWAS dataset (18,382 ASD cases and 27,969 controls). Inverse variance weighted (IVW) is the primary method for causality analysis, and several sensitivity analyses validate MR results. Among 211 GM taxa, IVW results confirmed that Tenericutes (P value = .0369), Mollicutes (P value = .0369), Negativicutes (P value = .0374), Bifidobacteriales (P value = .0389), Selenomonadales (P value = .0374), Bifidobacteriaceae (P value = .0389), Family XIII (P value = .0149), Prevotella7 (P value = .0215), Ruminococcaceae NK4A214 group (P value = .0205) were potential protective factors for ASD. Eisenbergiella (P value = .0159) was a possible risk factor for ASD. No evidence of heterogeneous, pleiotropic, or outlier single-nucleotide polymorphism was detected. Additionally, further sensitivity analysis verified the robustness of the above results. We confirm a potential causal relationship between certain gut microbes and ASD, providing new insights into how gut microbes mediate ASD. The association between them needs to be further explored and will provide new ideas for the prevention and treatment of ASD.

Identification of Coding Variants in 10q22.1 Associated with Vitiligo in the Chinese Han Population.

Objective: This study aims to identify causal variants associated with vitiligo in an expanded region of 10q22.1. Materials and Methods: We conducted a fine-scale deep analysis of the expanded 10q22.1 region using in a large genome-wide association studies dataset consisting of 1117 cases and 1701 controls through imputation. We selected five nominal coding single nucleotide polymorphisms (SNPs) located in SLC29A3 and CDH23 and genotyped them in an independent cohort of 2479 cases and 2451 controls in a Chinese Han population cohort using the Sequenom MassArray iPLEX1 system. Results: A missense SNP in SLC29A3, rs2252996, showed strong evidence of association with vitiligo (p = 1.34 × 10-8, odds ratio [OR] = 0.82). Three synonymous SNPs (rs1084004 in SLC29A3; rs12218559 and rs10999978 in CDH23) provided suggestive evidence of association for vitiligo (p = 1.69 × 10-6, OR = 0.84; p = 9.47 × 10-5, OR = 1.18; p = 6.90 × 10-4, OR = 1.16, respectively). Stepwise conditional analyses identified two significant independent disease-associated signals from the four SNPs (both p < 0.05; both D' = 0.03; and r2 = 0.00). Conclusion: The study identifies four genetic coding variants in SLC29A3 and CDH23 on 10q22.1 that may contribute to vitiligo susceptibility with one missense variant affecting disease subphenotypes. The presence of multiple genetic variants underscores their significant role in the genetic pathogenesis of the disease.

Associations of the circulating levels of cytokines with risk of systemic sclerosis: a bidirectional Mendelian randomized study.

Systemic sclerosis(SSc) remains unclear, studies suggest that inflammation may be linked to its pathogenesis. Hence, we conducted a bidirectional Mendelian randomization (MR) analysis to evaluate the association between cytokine and growth factor cycling levels and the risk of SSc onset. In our study, the instrumental variables(IVs) for circulating cytokines were sourced from the genome-wide association study (GWAS) dataset of 8293 Finnish individuals. The SSc data comprised 302 cases and 213145 controls, and was included in the GWAS dataset. We employed four methods for the MR analysis: MR Egger, Inverse variance weighted (IVW), Weighted medium, and Weighted Mode, with IVW being the primary analytical method. Sensitivity analyses were performed using heterogeneity testing, horizontal pleiotropy testing, and the Leave One Out (LOO) method. We also conducted a reverse MR analysis to determine any reverse causal relationship between SSc and circulating cytokines. After Bonferroni correction, MR analysis revealed that the Interleukin-5 (IL-5) cycle level was associated with a reduced risk of SSc [odds ratio (OR)=0.48,95% confidence interval (CI): 0.27-0.84, P=0.01]. It also indicated that the Stem cell growth factor beta (SCGF-β) cycling level might elevate the risk of SSc (OR = 1.36, 95% CI: 1.01-1.83, P = 0.04). However, the reverse MR analysis did not establish a causal relationship between SSc and circulating cytokine levels. Additionally, sensitivity analysis outcomes affirm the reliability of our results. Our MR study suggests potential causal relationships between IL-5, SCGF-β, and the risk of SSc. Further research is essential to determine how IL-5 and SCGF-β influence the development of SSc.

A distinct class of pan-cancer susceptibility genes revealed by an alternative polyadenylation transcriptome-wide association study

Alternative polyadenylation plays an important role in cancer initiation and progression; however, current transcriptome-wide association studies mostly ignore alternative polyadenylation when identifying putative cancer susceptibility genes. Here, we perform a pan-cancer 3′ untranslated region alternative polyadenylation transcriptome-wide association analysis by integrating 55 well-powered (n > 50,000) genome-wide association studies datasets across 22 major cancer types with alternative polyadenylation quantification from 23,955 RNA sequencing samples across 7,574 individuals. We find that genetic variants associated with alternative polyadenylation are co-localized with 28.57% of cancer loci and contribute a significant portion of cancer heritability. We further identify 642 significant cancer susceptibility genes predicted to modulate cancer risk via alternative polyadenylation, 62.46% of which have been overlooked by traditional expression- and splicing- studies. As proof of principle validation, we show that alternative alleles facilitate 3′ untranslated region lengthening of CRLS1 gene leading to increased protein abundance and promoted proliferation of breast cancer cells. Together, our study highlights the significant role of alternative polyadenylation in discovering new cancer susceptibility genes and provides a strong foundational framework for enhancing our understanding of the etiology underlying human cancers.

No potential causal link between HP infection and IBD: A 2way Mendelian randomization study.

Recent epidemiological research suggests a possible negative correlation between Helicobacter pylori infection and inflammatory bowel disease (IBD). However, conflicting studies have provided unclear evidence regarding these causal relationships. Therefore, recommending specific prevention and treatment strategies for H. pylori infection and IBD is challenging. We used various antibodies (anti-H. pylori IgG, VacA, and GroEl) related to H. pylori infection as indicators. We acquired relevant genetic variants from public databases within the Genome-wide Association Studies (GWAS) dataset using IBDs tool variables from 2 different GWAS datasets. We thoroughly examined the data and screened for IVs that fulfilled these criteria. Subsequently, Bidirectional Mendelian randomization (MR) was conducted to predict the potential causality between the 2. To ensure the accuracy and robustness of our results, we conducted a series of sensitivity analyses. Based on our comprehensive MR analysis, no potential causal relationship was observed between H. pylori infection and IBD. Across various methodologies, including IVW, MR-Egger, and weighted median, our findings showed P values > .05. The only exception was observed in the reverse MR analysis using the MR-Egger method, which yielded a P value of < .05. However, because the IVW method is considered the most statistically significant method for MR, and its P value was > .05, we do not believe that a potential causal relationship exists between them. Our sensitivity analysis did not suggest significant horizontal pleiotropism. Although heterogeneity was detected in the analysis of IBD (IIBDGC source) versus H. pylori GroEL antibody levels (MR-Egger, Qp = 0.038; IVW, Qp = 0.043), the results remained reliable because we selected IVW as a random-effects model in our MR analysis method. Based on our MR research, no direct correlation was observed between H. pylori infection and IBD risk. This implies that eradicating H. pylori may not provide substantial benefits in preventing or treating regional IBD, and vice versa. Nevertheless, the use of H. pylori serological index substitution has limitations, and further research using histological diagnosis and additional MR studies is required to comprehensively assess the link between H. pylori infection and IBD.

The gut-joint axis: Genetic evidence for a causal association between gut microbiota and seropositive rheumatoid arthritis and seronegative rheumatoid arthritis.

This study aimed to assess the causal relationship between GM and RA (seropositive RA and seronegative RA). A two-sample Mendelian randomization (MR) analysis was performed to assess the causality of GM on seropositive RA and seronegative RA. GM's genome-wide association study (GWAS) was used as the exposure, whereas the GWAS datasets of seropositive RA and seronegative RA were the outcomes. The primary analysis approach was used as inverse-variance weighted (IVW), followed by 3 additional MR methods (MR-Egger, weighted median, and weighted mode). Cochran's Q test was used to identify heterogeneity. The MR-Egger intercept test and leave-one-out analyses were used to assess horizontal pleiotropy. All statistical analyses were performed in R software. We discovered that Alloprevotella (IVW OR 0.84, 95% CI 0.71-0.99, P = .04) and Christensenellaceae R 7 group (IVW OR 0.71, 95% CI 0.52-0.99, P = .04) were negatively correlated with seropositive RA, Ruminococcaceae UCG002 (IVW OR 1.30, 95% CI 1.10-1.54, P = .002) was positively associated with seropositive RA. Actinomyces (IVW OR 0.73, 95% CI 0.54-0.99, P = .04), Christensenellaceae R 7 group (IVW OR 0.62, 95% CI 0.39-0.97, P = .04), Terrisporobacter (IVW OR 0.64, 95% CI 0.44-0.93, P = .02), Lactobacillales (IVW OR 0.65, 95% CI 0.47-0.90, P = .01) were negatively correlated with seronegative RA. The present MR analysis showed a protective effect of Alloprevotella and Christensenellaceae R 7 group and a potentially anti-protective effect of Ruminococcaceae UCG002 on seropositive RA; and a protective effect of Actinomyces, Christensenellaceae R 7 group, Terrisporobacter, and Lactobacillales on seronegative RA. Further experimental studies and randomized controlled trials are needed to validate these findings.

Multi-Ancestry Polygenic Risk Score for Coronary Heart Disease Based on an Ancestrally Diverse Genome-Wide Association Study and Population-Specific Optimization.

Predictive performance of polygenic risk scores (PRS) varies across populations. To facilitate equitable clinical use, we developed PRS for coronary heart disease (CHD; PRSCHD) for 5 genetic ancestry groups. We derived ancestry-specific and multi-ancestry PRSCHD based on pruning and thresholding (PRSPT) and ancestry-based continuous shrinkage priors (PRSCSx) applied to summary statistics from the largest multi-ancestry genome-wide association study meta-analysis for CHD to date, including 1.1 million participants from 5 major genetic ancestry groups. Following training and optimization in the Million Veteran Program, we evaluated the best-performing PRSCHD in 176,988 individuals across 9 diverse cohorts. Multi-ancestry PRSPT and PRSCSx outperformed ancestry-specific PRSPT and PRSCSx across a range of tuning values. Two best-performing multi-ancestry PRSCHD (ie, PRSPTmult and PRSCSxmult) and 1 ancestry-specific (PRSCSxEUR) were taken forward for validation. PRSPTmult demonstrated the strongest association with CHD in individuals of South Asian ancestry and European ancestry (odds ratio per 1 SD [95% CI, 2.75 [2.41-3.14], 1.65 [1.59-1.72]), followed by East Asian ancestry (1.56 [1.50-1.61]), Hispanic/Latino ancestry (1.38 [1.24-1.54]), and African ancestry (1.16 [1.11-1.21]). PRSCSxmult showed the strongest associations in South Asian ancestry (2.67 [2.38-3.00]) and European ancestry (1.65 [1.59-1.71]), lower in East Asian ancestry (1.59 [1.54-1.64]), Hispanic/Latino ancestry (1.51 [1.35-1.69]), and the lowest in African ancestry (1.20 [1.15-1.26]). The use of summary statistics from a large multi-ancestry genome-wide meta-analysis improved the performance of PRSCHD in most ancestry groups compared with single-ancestry methods. Despite the use of one of the largest and most diverse sets of training and validation cohorts to date, improvement of predictive performance was limited in African ancestry. This highlights the need for larger genome-wide association study datasets of underrepresented populations to enhance the performance of PRSCHD.

Causal Relationship Between Ferritin and Neuropsychiatric Disorders: A Two-Sample Mendelian Randomization Study.

Previous observational research has indicated a correlation between ferritin levels and neuropsychiatric disorders, although the causal relationship remains uncertain. The objective of this study was to investigate the potential causal link between plasma ferritin levels and neuropsychiatric disorders. A two-sample Mendelian randomization (MR) study was conducted, wherein genetic instruments associated with ferritin were obtained from a previously published genome-wide association study (GWAS). Summary statistics pertaining to neuropsychiatric disorders were derived from five distinct GWAS datasets. The primary MR analysis employed the inverse variance weighted (IVW) method and was corroborated by additional methods including MR-Egger, weighted median, simple mode, and weighted mode. Sensitivity analyses were employed to identify potential pleiotropy and heterogeneity in the results. The fixed effects IVW method revealed a statistically significant causal relationship between plasma ferritin level and the occurrence of Alzheimer's disease (odds ratio [OR] = 1.06, 95% confidence interval [CI]: 1.00-1.12, p = 0.037), as well as Parkinson's disease (OR = 1.06, 95% CI: 1.00-1.13, p = 0.041). Various sensitivity analyses were conducted, which demonstrated no substantial heterogeneity or pleiotropy. Conversely, no compelling evidence was found to support a causal association between ferritin and amyotrophic lateral sclerosis, schizophrenia, or major depressive disorder. This MR study provides evidence at the genetic level for a causal relationship between plasma ferritin and an increased risk of Alzheimer's disease and Parkinson's disease. The exact genetic mechanisms underlying this connection necessitate further investigation.

The causal association between serum metabolites and lung cancer based on multivariate Mendelian randomization.

This study seeks to understand the causal association between serum metabolites and different lung cancer types, an area yet to be extensively studied. We Used a two-sample Mendelian randomization (TSMR) approach, utilizing 486 blood metabolites as exposures and 3 distinct lung cancer types genome-wide association studies datasets as outcomes. We employed inverse variance weighting, MR-Egger, weighted median, simple mode, and weighted mode to estimate causal effects. We performed sensitivity analyses using Cochran Q test, MR-Egger intercept test, and MR-pleiotropy residual sum and outlier (MR-PRESSO). Linkage disequilibrium score (LDSC) analysis was conducted on the selected metabolites, and common confounding single nucleotide polymorphisms were eliminated using the human genotype-phenotype association Database. Metabolic pathway analysis was performed with MetaboAnalyst 5.0 software. Subsequently, a multivariate Mendelian randomization analysis was conducted to ascertain independent risk exposures. Our findings suggest independent risk factors for specific types of lung cancer: 7-methylxanthine and isoleucine for lung adenocarcinoma, cysteine and 1-arachidonoylglycerophosphocholine are identified as independent protective and risk factors for squamous lung cancer. Undecanoate (11:0) with Linoleate (18:2n6) showed a protective effect for small cell lung cancer. Additionally, 11 metabolic pathways were associated with lung cancer. This novel perspective offers a multidimensional understanding of lung cancer phenotypes, providing valuable guidance for identifying and screening of diverse lung cancer phenotypes.

Genetic insights into repurposing statins for hyperthyroidism prevention: a drug-target Mendelian randomization study.

Current therapeutic measures for thyroid dysfunction are limited and often accompanied by adverse effects. The use of lipid-lowering drugs like statins has recently been associated with lower thyroid eye diseases risk. To investigate the implications of genetically proxied lipid-lowering drugs on thyroid dysfunction. In this drug-target Mendelian randomization (MR) study, we utilized genetic variants within drug target genes associated with low-density lipoprotein (LDL) or triglyceride (TG), derived from a genome-wide association study (GWAS) meta-analysis (N ≤ 188,577), to simulate lifelong drug interventions. Genetic summary statistics for thyroid dysfunction outcomes were retrieved from GWAS datasets of Thyroid Omics Consortium (N ≤ 54,288) and UK Biobank (N = 484,598). Inverse-variance-weighted MR (IVW-MR) method was performed as primary analysis, followed by validation in colocalization analysis. A subsequent two-step MR analysis was conducted to identify biomarkers mediating the identified drug-outcome association. In IVW-MR analysis, genetic mimicry of 3-hydroxy-3-methylglutarylcoenzyme reductase (HMGCR) inhibitors (e.g. statins) was significantly associated with lower risk of hyperthyroidism in two independent datasets (OR1, 0.417 per 1-mmol/L lower in LDL-C; 95% CI 0.262 to 0.664; P1=2.262 × 10-4; OR2 0.996; 95% CI 0.993-0.998; P2=0.002). Two-step MR analysis revealed eighteen biomarkers linked to genetic mimicry of HMGCR inhibition, and identified insulin-like growth factor 1 (IGF-1) levels mediating 2.108% of the negative causal relationship between HMGCR inhibition and hyperthyroidism. This study supports HMGCR inhibition as a promising therapeutic strategy for hyperthyroidism and suggests its underlying mechanisms may extend beyond lipid metabolism. Further investigations through laboratory studies and clinical trials are necessary to confirm and elucidate these findings.

The causal effect of two occupational factors on osteoarthritis and rheumatoid arthritis: a Mendelian randomization study.

Osteoarthritis (OA) and rheumatoid arthritis (RA) are two common types of arthritis. We conducted a two-sample Mendelian randomization (MR) study to estimate the causal effects of two common occupational factors-job involves heavy manual or physical work and job involves mainly walking or standing-on OA and RA in individuals of European ancestry. Instruments were chosen from genome-wide association studies (GWASs) that identified independent single nucleotide polymorphisms (SNPs) robustly linked to job involves heavy manual or physical work (N = 263,615) as well as job involves mainly walking or standing (N = 263,556). Summary statistics for OA and RA were taken from the Integrative Epidemiology Unit (IEU) GWAS database; both discovery and replication GWAS datasets were considered. The primary analysis utilized the inverse variance weighted (IVW) MR method supplemented by various sensitivity MR analyses. In the IVW model, we found that genetically predicted job involves heavy manual or physical work was significantly associated with OA in both the discovery [odds ratio (OR) = 1.034, 95% confidence interval (CI): 1.016-1.053, P = 2.257 × 10-4] and replication (OR = 1.857, 95% CI: 1.223-2.822, P = 0.004) analyses. The causal associations were supported in diverse sensitivity analyses. MR analyses suggested no causal effect of genetically predicted job involves heavy manual or physical work on RA. Similarly, our data provided no evidence that genetically predicted job involves mainly walking or standing was related to OA and RA. Our MR study suggests that job involves heavy manual or physical work is a risk factor for OA. It is of utmost importance to create preventive strategies aimed at reducing its impact on OA at such work sites.

The causal effects of age at menarche and age at menopause on sepsis: A two-sample Mendelian randomization analysis.

To determine whether the age at menarche (AAM) and the age at menopause (ANM) are causally related to the development of sepsis. We performed a two-sample Mendelian randomization (MR) analysis by utilizing summary statistics from genome-wide association study (GWAS) datasets for both the exposure and outcome variables. Single nucleotide polymorphisms (SNPs) that exhibited significant associations with AAM and ANM were chosen as instrumental variables to estimate the causal effects on sepsis. Our study employed a variety of methods, including MR-Egger regression, weighted median estimation, inverse variance weighting, a simple model, and a weighted model. Odds ratios (ORs) along with their corresponding 95% confidence intervals (CIs) were used as the primary indicators for assessing causality. Furthermore, we conducted sensitivity analyses to explore the presence of genetic heterogeneity and validate the robustness of the tools employed. Our analysis revealed a significant negative causal relationship between AAM and the risk of sepsis (IVW: OR = 0.870, 95% CI = 0.793-0.955, P = 0.003). However, our Mendelian randomization (MR) analysis did not yield sufficient evidence to support a causal link between ANM and sepsis (IVW: OR = 0.987, 95% CI = 0.971-1.004, P = 0.129). Our findings suggest that an earlier AAM may be associated with an increased risk of sepsis. However, we did not find sufficient evidence to support a causal relationship between ANM and sepsis.

The cells of the sensory epithelium, and not the stria vascularis, are the main cochlear cells related to the genetic pathogenesis of age-related hearing loss

Age-related hearing loss (ARHL) is a major health concern among the elderly population. It is hoped that increasing our understanding of its underlying pathophysiological processes will lead to the development of novel therapies. Recent genome-wide association studies (GWASs) discovered a few dozen genetic variants in association with elevated risk for ARHL. Integrated analysis of GWAS results and transcriptomics data is a powerful approach for elucidating specific cell types that are involved in disease pathogenesis. Intriguingly, recent studies that applied such bioinformatics approaches to ARHL resulted in disagreeing findings as for the key cell types that are most strongly linked to the genetic pathogenesis of ARHL. These conflicting studies pointed either to cochlear sensory epithelial or to stria vascularis cells as the cell types most prominently involved in the genetic basis of ARHL. Seeking to resolve this discrepancy, we integrated the analysis of four ARHL GWAS datasets with four independent inner-ear single-cell RNA-sequencing datasets. Our analysis clearly points to the cochlear sensory epithelial cells as the key cells for the genetic predisposition to ARHL. We also explain the limitation of the bioinformatics analysis performed by previous studies that led to missing the enrichment for ARHL GWAS signal in sensory epithelial cells. Collectively, we show that cochlear epithelial cells, not stria vascularis cells, are the main inner-ear cells related to the genetic pathogenesis of ARHL.

Novel functional insights into ischemic stroke biology provided by the first genome-wide association study of stroke in indigenous Africans

BackgroundAfrican ancestry populations have the highest burden of stroke worldwide, yet the genetic basis of stroke in these populations is obscure. The Stroke Investigative Research and Educational Network (SIREN) is a multicenter study involving 16 sites in West Africa. We conducted the first-ever genome-wide association study (GWAS) of stroke in indigenous Africans.MethodsCases were consecutively recruited consenting adults (aged > 18 years) with neuroimaging-confirmed ischemic stroke. Stroke-free controls were ascertained using a locally validated Questionnaire for Verifying Stroke-Free Status. DNA genotyping with the H3Africa array was performed, and following initial quality control, GWAS datasets were imputed into the NIH Trans-Omics for Precision Medicine (TOPMed) release2 from BioData Catalyst. Furthermore, we performed fine-mapping, trans-ethnic meta-analysis, and in silico functional characterization to identify likely causal variants with a functional interpretation.ResultsWe observed genome-wide significant (P-value < 5.0E−8) SNPs associations near AADACL2 and miRNA (MIR5186) genes in chromosome 3 after adjusting for hypertension, diabetes, dyslipidemia, and cardiac status in the base model as covariates. SNPs near the miRNA (MIR4458) gene in chromosome 5 were also associated with stroke (P-value < 1.0E−6). The putative genes near AADACL2, MIR5186, and MIR4458 genes were protective and novel. SNPs associations with stroke in chromosome 2 were more than 77 kb from the closest gene LINC01854 and SNPs in chromosome 7 were more than 116 kb to the closest gene LINC01446 (P-value < 1.0E−6). In addition, we observed SNPs in genes STXBP5-AS1 (chromosome 6), GALTN9 (chromosome 12), FANCA (chromosome 16), and DLGAP1 (chromosome 18) (P-value < 1.0E−6). Both genomic regions near genes AADACL2 and MIR4458 remained significant following fine mapping.ConclusionsOur findings identify potential roles of regulatory miRNA, intergenic non-coding DNA, and intronic non-coding RNA in the biology of ischemic stroke. These findings reveal new molecular targets that promise to help close the current gaps in accurate African ancestry-based genetic stroke’s risk prediction and development of new targeted interventions to prevent or treat stroke.

Gene-based association tests in family samples using GWAS summary statistics.

Genome-wide association studies (GWAS) have led to rapid growth in detecting genetic variants associated with various phenotypes. Owing to a great number of publicly accessible GWAS summary statistics, and the difficulty in obtaining individual-level genotype data, many existing gene-based association tests have been adapted to require only GWAS summary statistics rather than individual-level data. However, these association tests are restricted to unrelated individuals and thus do not apply to family samples directly. Moreover, due to its flexibility and effectiveness, the linear mixed model has been increasingly utilized in GWAS to handle correlated data, such as family samples. However, it remains unknown how to perform gene-based association tests in family samples using the GWAS summary statistics estimated from the linear mixed model. In this study, we show that, when family size is negligible compared to the total sample size, the diagonal block structure of the kinship matrix makes it possible to approximate the correlation matrix of marginal Z scores by linkage disequilibrium matrix. Based on this result, current methods utilizing summary statistics for unrelated individuals can be directly applied to family data without any modifications. Our simulation results demonstrate that this proposed strategy controls the type 1 error rate well in various situations. Finally, we exemplify the usefulness of the proposed approach with a dental caries GWAS data set.

Identifying novel chemical-related susceptibility genes for five psychiatric disorders through integrating genome-wide association study and tissue-specific 3'aQTL annotation datasets.

The establishment of 3'aQTLs comprehensive database provides an opportunity to help explore the functional interpretation from the genome-wide association study (GWAS) data of psychiatric disorders. In this study, we aim to search novel susceptibility genes, pathways, and related chemicals of five psychiatric disorders via GWAS and 3'aQTLs datasets. The GWAS datasets of five psychiatric disorders were collected from the open platform of Psychiatric Genomics Consortium (PGC, https://www.med.unc.edu/pgc/ ) and iPSYCH ( https://ipsych.dk/ ) (Demontis et al. in Nat Genet 51(1):63-75, 2019; Grove et al. in Nat Genet 51:431-444, 2019; Genomic Dissection of Bipolar Disorder and Schizophrenia in Cell 173: 1705-1715.e1716, 2018; Mullins et al. in Nat Genet 53: 817-829; Howard et al. in Nat Neurosci 22: 343-352, 2019). The 3'untranslated region (3'UTR) alternative polyadenylation (APA) quantitative trait loci (3'aQTLs) summary datasets of 12 brain regions were obtained from another public platform ( https://wlcb.oit.uci.edu/3aQTLatlas/ ) (Cui et al. in Nucleic Acids Res 50: D39-D45, 2022). First, we aligned the GWAS-associated SNPs of psychiatric disorders and datasets of 3'aQTLs, and then, the GWAS-associated 3'aQTLs were identified from the overlap. Second, gene ontology (GO) and pathway analysis was applied to investigate the potential biological functions of matching genes based on the methods provided by MAGMA. Finally, chemical-related gene-set analysis (GSA) was also conducted by MAGMA to explore the potential interaction of GWAS-associated 3'aQTLs and multiple chemicals in the mechanism of psychiatric disorders. A number of susceptibility genes with 3'aQTLs were found to be associated with psychiatric disorders and some of them had brain-region specificity. For schizophrenia (SCZ), HLA-A showed associated with psychiatric disorders in all 12 brain regions, such as cerebellar hemisphere (P = 1.58 × 10-36) and cortex (P = 1.58 × 10-36). GO and pathway analysis identified several associated pathways, such as Phenylpropanoid Metabolic Process (GO:0009698, P = 6.24 × 10-7 for SCZ). Chemical-related GSA detected several chemical-related gene sets associated with psychiatric disorders. For example, gene sets of Ferulic Acid (P = 6.24 × 10-7), Morin (P = 4.47 × 10-2) and Vanillic Acid (P = 6.24 × 10-7) were found to be associated with SCZ. By integrating the functional information from 3'aQTLs, we identified several susceptibility genes and associated pathways especially chemical-related gene sets for five psychiatric disorders. Our results provided new insights to understand the etiology and mechanism of psychiatric disorders.

Genomics Research of Lifetime Depression in the Netherlands: The BIObanks Netherlands Internet Collaboration (BIONIC) Project.

In this cohort profile article we describe the lifetime major depressive disorder (MDD) database that has been established as part of the BIObanks Netherlands Internet Collaboration (BIONIC). Across the Netherlands we collected data on Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) lifetime MDD diagnosis in 132,850 Dutch individuals. Currently, N = 66,684 of these also have genomewide single nucleotide polymorphism (SNP) data. We initiated this project because the complex genetic basis of MDD requires large population-wide studies with uniform in-depth phenotyping. For standardized phenotyping we developed the LIDAS (LIfetime Depression Assessment Survey), which then was used to measure MDD in 11 Dutch cohorts. Data from these cohorts were combined with diagnostic interview depression data from 5 clinical cohorts to create a dataset of N = 29,650 lifetime MDD cases (22%) meeting DSM-5 criteria and 94,300 screened controls. In addition, genomewide genotype data from the cohorts were assembled into a genomewide association study (GWAS) dataset of N = 66,684 Dutch individuals (25.3% cases). Phenotype data include DSM-5-based MDD diagnoses, sociodemographic variables, information on lifestyle and BMI, characteristics of depressive symptoms and episodes, and psychiatric diagnosis and treatment history. We describe the establishment and harmonization of the BIONIC phenotype and GWAS datasets and provide an overview of the available information and sample characteristics. Our next step is the GWAS of lifetime MDD in the Netherlands, with future plans including fine-grained genetic analyses of depression characteristics, international collaborations and multi-omics studies.