Linkage Disequilibrium Score Regression Research Articles

Causality of Genetically Determined Metabolites on Chronic Kidney Disease: A Two-Sample Mendelian Randomization Study In Silico.

Introduction: Chronic kidney disease (CKD) is associated with metabolic disorders. However, the evidence for the causality of circulating metabolites to promote or prevent CKD is still lacking. Methods: The two-sample Mendelian randomization (MR) analysis was conducted to evaluate the latent causal relationship between the genetically proxied 486 blood metabolites and CKD. Genome-wide association study (GWAS) data for exposures were derived from 7824 European GWAS on metabolite levels, which have been extensively utilized in the medical field to elucidate the mechanisms underlying disease onset and progression. The random inverse variance weighted (IVW) is the primary analysis for causality analysis while MR-Egger and weighted median as complementary analyses. For the further identification of metabolites, reverse MR and linkage disequilibrium score regression were performed for further evaluation. The drug target for N-acetylornithine was subsequently supplemented into the analysis, with MR and colocalization analysis being utilized. Key metabolic pathways were identified via MetaboAnalyst 4.0 (https://www.metaboanalyst.ca/) online website. Results: N-acetylornithine was identified as a reliable metabolite that increases the susceptibility to estimated glomerular filtration rate (eGFR) decrease (β = 0.047; 95% confidence interval: -0.068 to -0.026; PIVW = 1.5E-5). The "glyoxylate and dicarboxylate metabolism" pathway showed significant relevance to CKD development (P = 6E-4), whereas the "glycine, serine, and threonine metabolism" pathway was also recognized as associated with CKD by general practitioners (P = 7E-4). Colocalization analysis revealed a robust genetic link between N-acetylornithine and both CKD and eGFR, with 85.1% and 99.4% colocalization rates, respectively. IVW-MR analysis substantiated these findings with a significant positive association for CKD (odds ratio = 1.43, P = 4.7E-5) and a negative correlation with eGFR (b = -0.04, P = 1.13E-31). Conclusions: MR was utilized to explore the potential causal links between 61 genetic serum metabolites and CKD. N-acetylornithine and NAT8 were further explored as a potential therapeutic target for CKD treatment.

Causal association between epilepsy and its DNA methylation profile and atrial fibrillation

BackgroundThe "epileptic heart" concept is emerging, but the causal relationship between epilepsy and atrial fibrillation (AF) remains unclarified. ObjectiveThis study explores the genetic correlations and bidirectional causality between various epilepsy phenotypes and AF. MethodsGenome-wide association study (GWAS) statistics for 10 epilepsy subtypes (29,944 cases, 52,538 controls) and AF (60,620 cases, 970,216 controls) were sourced from the International League Against Epilepsy (ILAE) and HGRI-EBI Catalog-GWAS, respectively. Linkage disequilibrium score regression (LDSC) and genome-wide Mendelian Randomization (MR) evaluated genetic correlations and bidirectional causal relationships. Epilepsy-related DNA methylation data (N= ∼800) from EWAS catalog were analyzed to identify causal CpG sites influencing AF risk through epigenetic MR. ResultsLDSC revealed significant genetic correlations between four epilepsy subtypes and AF (rg from 0.116 to 0.241). Forward MR suggested a significant causal effect of focal epilepsy with hippocampal sclerosis (FE with HS) on AF risk (IVW and MR-PRESSO: OR = 1.046, P ≤ 0.004), with results robust against heterogeneity, horizontal pleiotropy, and outliers. Epigenetic MR indicated that lower methylation at cg06222062 (OR = 0.994, P = 3.16E-04) mapped to PLA2G5 and cg08461451 mapped to SPPL2B gene (OR = 0.954, P = 1.19E-03), and higher cg10541930 in the C10orf143 promoter (OR = 1.043, P = 4.18E-22) increases AF risk. Sensitivity analyses affirmed no pleiotropic bias. ConclusionFE with HS significantly increases AF risk, highlighting the natural neural-cardiac connection and the need for cardiac monitoring in epilepsy patients. Specific methylated CpG sites may serve as biomarkers and preventive targets for AF susceptibility.

Genetic analysis from multiple cohorts implies causality between 2200 druggable genes, telomere length, and leukemia

BackgroundClinical therapeutic targets for leukemia remain to be identified and the causality between leukemia and telomere length is unclear. MethodsThis work employed cis expression quantitative trait locus (eQTL) for 2,200 druggable genes from the eQTLGen Consortium and genome-wide association studies (GWAS) summary data for telomere length in seven blood cell types from the UK Biobank, Netherlands Cohort as exposures. GWAS data for lymphoid leukemia (LL) and myeloid leukemia (ML) from FinnGen and Lee Lab were used as outcomes for discovery and replication cohorts, respectively. Robust Mendelian randomization (MR) findings were generated from seven MR models and a series of sensitivity analyses. Summary-data-based MR (SMR) analysis and transcriptome-wide association studies (TWAS) were further implemented to verify the association between identified druggable genes and leukemia. Single-cell type expression analysis was employed to identify the specific expression of leukemia casual genes on human bone marrow and peripheral blood immune cells. Multivariable MR analysis, linkage disequilibrium score regression (LDSC), and Bayesian colocalization analysis were performed to further validate the relationship between telomere length and leukemia. Mediation analysis was used to assess the effects of identified druggable genes affecting leukemia via telomere length. Phenome-wide MR (Phe-MR) analysis for assessing the effect of leukemia causal genes and telomere length on 1,403 disease phenotypes. ResultsCombining the results of the meta-analysis for MR estimates from two cohorts, SMR and TWAS analysis, we identified five LL causal genes (TYMP, DSTYK, PPIF, GDF15, FAM20A) and three ML causal genes (LY75, ADA, ABCA2) as promising drug targets for leukemia. Univariable MR analysis showed genetically predicted higher leukocyte telomere length increased the risk of LL (odds ratio [OR] = 2.33, 95 % confidence interval [95 % CI] 1.70–3.18; P = 1.33E-07), and there was no heterogeneity and horizontal pleiotropy. Evidence from the meta-analysis of two cohorts strengthened this finding (OR = 1.88, 95 % CI 1.06–3.05; P = 0.01). Multivariable MR analysis showed the causality between leukocyte telomere length and LL without interference from the other six blood cell telomere length (OR = 2.72, 95 % CI 1.88–3.93; P = 1.23E-07). Evidence from LDSC supported the positive genetic correlation between leukocyte telomere length and LL (rg = 0.309, P = 0.0001). Colocalization analysis revealed that the causality from leukocyte telomere length on LL was driven by the genetic variant rs770526 in the TERT region. The mediation analysis via two-step MR showed that the causal effect from TYMP on LL was partly mediated by leukocyte telomere length, with a mediated proportion of 12 %. ConclusionOur study identified several druggable genes associated with leukemia risk and provided new insights into the etiology and drug development of leukemia. We also found that genetically predicted higher leukocyte telomere length increased LL risk and its potential mechanism of action.

Exploring the shared genetic basis of major depressive disorder and frailty

BackgroundMajor depressive disorder (MDD) and frailty impose substantial health and economic burdens. MDD is recognized as a significant risk factor for frailty, but the genetic associations between these conditions remain unclear. This study investigates the genetic correlation, shared pleiotropic loci, causal relationships, and comorbid genes between MDD and frailty. MethodsThe genetic correlation between MDD and frailty was assessed using linkage disequilibrium score regression (LDSC) based on data from genome-wide association studies (GWAS). A detailed analysis was performed to identify shared pleiotropic loci and causal relationships through cross-phenotype association tests and Mendelian randomization. Additionally, tissue enrichment analysis was conducted using stratified LDSC, gene-based associations with both conditions were assessed using Multimarker Analysis of Genomic Annotation (MAGMA), and pathway analysis of comorbid genes was performed using the g: GOSt tool. ResultsOur findings revealed a significant positive genetic correlation between MDD and frailty (rg = 0.65, P = 1.49E-219). We identified 57 shared risk SNPs between the two conditions, including 6 novel SNPs. Mendelian randomization analyses indicated robust causal effects of MDD on frailty and vice versa. Furthermore, we observed tissue-specific heritability enrichment in 9 brain tissues. By combining MAGMA and CPASSOC analyses, we identified 10 comorbid genes associated with both MDD and frailty, primarily involved in synapse formation, modulation, plasticity, and desaturase activity. ConclusionThis study provides strong evidence for a shared genetic basis between MDD and frailty. The identification of comorbid genes offers new insights into the mechanisms underlying the relationship between these conditions.

The shared genetic etiology of antisocial behavior and psychiatric disorders: Insights from pleiotropy and causality analysis

BackgroundAntisocial behavior (ASB) infringes on the rights of others and significantly disrupts social order. Studies have shown that ASB is phenotypically associated with various psychiatric disorders. However, these studies often neglected the importance of genetic foundations. MethodsThis study utilized genome-wide association studies and pleiotropy analysis to explore the genetic correlation between ASB and psychiatric disorders. Linkage disequilibrium score regression (LDSC) and high-definition likelihood (HDL) methods were employed to assess genetic correlations, and the PLACO method was used for pleiotropy analysis. Functional annotation and biological pathway analysis of identified pleiotropic genes were performed using enrichment analysis. Furthermore, Mendelian randomization (MR) analysis was conducted to validate these causal relationships. ResultsLDSC and HDL analysis showed that significant positive genetic correlations were between ASB and attention deficit hyperactivity disorder (ADHD), schizophrenia (SCZ), major depressive disorder (MDD), and post-traumatic stress disorder (PTSD). Multiple potential pleiotropic genetic loci were identified, particularly the FOXP2 and MDFIC genes located at the 7q31.1 locus. Enrichment analysis showed that these pleiotropic genes are highly expressed in several brain regions (such as the hypothalamus, cerebellar hemisphere, cortex, and amygdala) and immune-related cells. MR analysis further confirmed the causal effects ADHD, SCZ, and MDD on ASB risk. ConclusionThis study reveals significant genetic correlations and potential causal mechanisms between ASB and various psychiatric disorders. The MR analysis confirmed the causal effects of psychiatric disorders on ASB. These findings deepen our understanding of the genetic architecture of psychiatric disorders and ASB.

Unraveling the Genetic Susceptibility of Irritable Bowel Syndrome: integrative genome-wide analyses in 845,492 individuals: a diagnostic study.

Irritable bowel syndrome (IBS) significantly impacts individuals due to its prevalence and negative effect on quality of life. Current genome-wide association studies (GWAS) have only identified a small number of crucial single nucleotide polymorphisms (SNPs), not fully elucidating IBS's pathogenesis. To identify genomic loci at which common genetic variation influence IBS susceptibility. Combining independent cohorts that in total comprise 65,840 cases of IBS and 788,652 controls, we performed a meta-analysis of genome-wide association studies (GWAS) of IBS. We also carried out gene mapping and pathway enrichment to gain insights into the underlying genes and pathways through which the associated loci contribute to disease susceptibility. Furthermore, we performed transcriptome analysis to deepen our understanding. IBS risk models were developed by combining clinical/lifestyle risk factors with polygenic risk scores (PRS) derived from the GWAS meta-analysis. We detect the phenotype association for IBS utilizing PRS-based phenome-wide association (PheWAS) analyses, linkage disequilibrium score regression, and Mendelian randomization. The GWAS meta-analysis identified 10 IBS risk loci, seven of which were novel (rs12755507, rs34209273, rs34365748, rs67427799, rs2587363, rs13321176, rs1546559). Multiple methods identified nine promising IBS candidate gene (PRRC2A, COP1, CADM2, LRP1B, SUGT1, MED12L, P2RY14, PHF2, SHISA6) at 10 GWAS loci. Transcriptome validation also revealed differential expression of these genes. Phenome-wide associations between PRS-IBS and nine traits (neuroticism, diaphragmatic hernia, asthma, diverticulosis, cholelithiasis, depression, insomnia, COPD, and BMI) were identified. The six diseases (asthma, diaphragmatic hernia, diverticulosis, insomnia major depressive disorder and neuroticism) were found to show genetic association with IBS and only major depressive disorder and neuroticism were found to show causality with IBS. We identified seven novel risk loci for IBS and highlight the substantial influence on genetic risk harboured. Our findings offer novel insights into aetiology and phenotypic association of IBS and lay the foundation for therapeutic targets and interventional strategies.

Genetic relations between type 1 diabetes, coronary artery disease and leukocyte counts.

Type 1 diabetes is associated with excess coronary artery disease (CAD) risk even when known cardiovascular risk factors are accounted for. Genetic perturbation of haematopoiesis that alters leukocyte production is a novel independent modifier of CAD risk. We examined whether there are shared genetic determinants and causal relationships between type 1 diabetes, CAD and leukocyte counts. Genome-wide association study summary statistics were used to perform pairwise linkage disequilibrium score regression and heritability estimation from summary statistics (ρ-HESS) to respectively estimate the genome-wide and local genetic correlations, and two-sample Mendelian randomisation to estimate the causal relationships between leukocyte counts (335,855 healthy individuals), type 1 diabetes (18,942 cases, 501,638 control individuals) and CAD (122,733 cases, 424,528 control individuals). A latent causal variable (LCV) model was performed to estimate the genetic causality proportion of the genetic correlation between type 1 diabetes and CAD. There was significant genome-wide genetic correlation (rg) between type 1 diabetes and CAD (rg=0.088, p=8.60 × 10-3) and both diseases shared significant genome-wide genetic determinants with eosinophil count (rg for type 1 diabetes [rg(T1D)]=0.093, p=7.20 × 10-3, rg for CAD [rg(CAD)]=0.092, p=3.68 × 10-6) and lymphocyte count (rg(T1D)=-0.052, p=2.76 × 10-2, rg(CAD)=0.176, p=1.82 × 10-15). Sixteen independent loci showed stringent Bonferroni significant local genetic correlations between leukocyte counts, type 1 diabetes and/or CAD. Cis-genetic regulation of the expression levels of genes within shared loci between type 1 diabetes and CAD was associated with both diseases as well as leukocyte counts, including SH2B3, CTSH, MORF4L1, CTRB1, CTRB2, CFDP1 and IFIH1. Genetically predicted lymphocyte, neutrophil and eosinophil counts were associated with type 1 diabetes and CAD (lymphocyte OR for type 1 diabetes [ORT1D]=0.67, p=2.02-19, ORCAD=1.09, p=2.67 × 10-6; neutrophil ORT1D=0.82, p=5.63 × 10-5, ORCAD=1.17, p=5.02 × 10-14; and eosinophil ORT1D=1.67, p=5.45 × 10-25, ORCAD=1.07, p=2.03 × 10-4. The genetic causality proportion between type 1 diabetes and CAD was 0.36 ± 0.16 (pLCV=1.30 × 10-2), suggesting a possible intermediary causal variable. This study sheds light on shared genetic mechanisms underlying type 1 diabetes and CAD, which may contribute to their co-occurrence through regulation of gene expression and leukocyte counts and identifies cellular and molecular targets for further investigation for disease prediction and potential drug discovery.

No bidirectional association between serum 25-hydroxyvitamin D and erectile dysfunction: Mendelian randomization and genetic association studies

Abstract Background The causal relationship between the level of serum 25-hydroxyvitamin D [25(OH)D] and the risk of erectile dysfunction (ED) is still unclear. Aim We tried to determine the causal relationship between the level of serum 25(OH)D and ED risk. Methods In this study, we used genome-wide association study data from the UK Biobank to analyse the relationship between serum 25(OH)D (as the exposure) and ED (as the outcome). Linkage disequilibrium score regression (LDSC) was used to assess the genetic correlation between 2 traits. The CAUSE (Causal Analysis using Summary Effect estimates) method and Mendelian randomization (MR) were employed to evaluate the bidirectional causal relationship. The MRlap method was utilized to assess the impact of sample overlap on the results. To assess potential heterogeneity and horizontal pleiotropy, we utilized methods such as MR-Egger, MR-PRESSO (Mendelian Randomization Pleiotropy Residual Sum and Outlier), weighted median, and others. Outcomes The primary outcome was defined as self or physician-reported ED, or using oral ED medication, or a history of surgery related to ED. Results The LDSC analysis did not reveal a significant genetic correlation between serum 25(OH)D and ED (rg = 0.2787, P = .3536). Additionally, the CAUSE (P value testing that the causal model is a better fit >.05) and MR analyses (odds ratio, 0.8951; 95% confidence interval, 0.7480-1.0710; P = .2260) did not support a causal relationship between 25(OH)D and ED, and our study did not detect any heterogeneity and pleiotropy. Clinical implications This study provides evidence on whether vitamin D needs to be ingested to prevent or treat ED. Strengths and limitations We used LDSC and MR to avoid bias. However, the population in this study was limited to European ancestry. Conclusion No causal relationship was found between 25(OH)D and ED.

3D genomic features across >50 diverse cell types reveal insights into the genomic architecture of childhood obesity.

The prevalence of childhood obesity is increasing worldwide, along with the associated common comorbidities of type 2 diabetes and cardiovascular disease in later life. Motivated by evidence for a strong genetic component, our prior genome-wide association study (GWAS) efforts for childhood obesity revealed 19 independent signals for the trait; however, the mechanism of action of these loci remains to be elucidated. To molecularly characterize these childhood obesity loci we sought to determine the underlying causal variants and the corresponding effector genes within diverse cellular contexts. Integrating childhood obesity GWAS summary statistics with our existing 3D genomic datasets for 57 human cell types, consisting of high-resolution promoter-focused Capture-C/Hi-C, ATAC-seq, and RNA-seq, we applied stratified LD score regression and calculated the proportion of genome-wide SNP heritability attributable to cell type-specific features, revealing pancreatic alpha cell enrichment as the most statistically significant. Subsequent chromatin contact-based fine-mapping was carried out for genome-wide significant childhood obesity loci and their linkage disequilibrium proxies to implicate effector genes, yielded the most abundant number of candidate variants and target genes at the BDNF, ADCY3, TMEM18 and FTO loci in skeletal muscle myotubes and the pancreatic beta-cell line, EndoC-BH1. One novel implicated effector gene, ALKAL2 - an inflammation-responsive gene in nerve nociceptors - was observed at the key TMEM18 locus across multiple immune cell types. Interestingly, this observation was also supported through colocalization analysis using expression quantitative trait loci (eQTL) derived from the Genotype-Tissue Expression (GTEx) dataset, supporting an inflammatory and neurologic component to the pathogenesis of childhood obesity. Our comprehensive appraisal of 3D genomic datasets generated in a myriad of different cell types provides genomic insights into pediatric obesity pathogenesis.

Exploring the Genetic Risk of Childhood Daytime Urinary Incontinence: A Genome-Wide Association Study.

Childhood incontinence is stigmatized and underprioritized, and a basic understanding of its pathogenesis is missing. Our goal was to identify risk-conferring genetic variants in daytime urinary incontinence (DUI). We conducted a genome-wide association study in the Danish iPSYCH2015 cohort. Cases (3024) were identified through DUI diagnosis codes and redeemed prescriptions for DUI medication in children aged 5 to 20. Controls (30,240), selected from the same sample, were matched to cases on sex and psychiatric diagnoses, if any, and down-sampled to a 1:10 case:control ratio. Replication was performed in the Icelandic deCODE cohort (5475 cases/287,773 controls). Single-nucleotide polymorphism heritability was calculated using the genome-based restricted maximum likelihood method. Cross-trait genetic correlation was estimated using linkage disequilibrium score regression. Polygenic risk scores generated with LDpred2-auto and BOLT-LMM were assessed for association. Variants on chromosome 6 (rs12210989, OR = 1.24 [95% CI: 1.17-1.32], P = 3.21 × 10-12) and 20 (rs4809801, OR = 1.18 [95% CI: 1.11-1.25], P = 3.66 × 10-8) reached genome-wide significance and implicated the PRDM13 and RIPOR3 genes. Chromosome 6 findings were replicated (P = .024, OR = 1.09 [95% CI: 1.01-1.16]). Liability scale heritability ranged from 10.20% (95% CI: 6.40%-14.00%) to 15.30% (95% CI: 9.66%-20.94%). DUI and nocturnal enuresis showed positive genetic correlation (rg = 1.28 ± 0.38, P = .0007). DUI was associated with attention-deficit/hyperactivity disorder (OR = 1.098 [95% CI: 1.046-1.152], P < .0001) and body mass index (OR = 1.129 [95% CI: 1.081-1.178], P < .0001) polygenic risk. Common genetic variants contribute to the risk of childhood DUI and genes important in neuronal development and detrusor smooth muscle activity were implicated. These findings may help guide identification of new treatment targets.

Elucidating the role of genetically determined metabolites in Diabetic Retinopathy: insights from a mendelian randomization analysis.

Diabetic retinopathy (DR) results from complex genetic and metabolic interactions. Unraveling the links between blood metabolites and DR can advance risk prediction and therapy. Leveraging Mendelian Randomization (MR) and Linkage Disequilibrium Score Regression (LDSC), we analyzed 10,413 DR cases and 308,633 controls. Data was sourced from the Metabolomics GWAS server and the FinnGen project. Our research conducted a comprehensive MR analysis across 486 serum metabolites to investigate their causal role in DR. After stringent selection and validation of instrumental variables, we focused on 480 metabolites for analysis. Our findings revealed 38 metabolites potentially causally associated with DR. Specifically, 4-androsten-3beta,17beta-diol disulfate 2 was identified as significantly associated with a reduced risk of DR (OR = 0.471, 95% CI = 0.324-0.684, p = 7.87 × 10- 5), even after rigorous adjustments for multiple testing. Sensitivity analyses further validated the robustness of this association, and linkage disequilibrium score regression analyses showed no significant genetic correlation between this metabolite and DR, suggesting a specific protective effect against DR. Our study identifies 4-androsten-3beta,17beta-diol disulfate 2, a metabolite of androgens, as a significant protective factor against diabetic retinopathy, suggesting androgens as potential therapeutic targets.

Genetic and causal relationship between chronic gastrointestinal diseases and erectile dysfunction: a Mendelian randomization study.

Studies based on observations have indicated potential associations between chronic gastrointestinal diseases and an increased risk of erectile dysfunction (ED). However, the causality of these connections remains ambiguous. Summary data for chronic gastrointestinal diseases were extracted from public data. Summary data on ED were extracted from three distinct sources. The genetic correlations between chronic gastrointestinal diseases and ED were explored using linkage disequilibrium score regression (LDSC). The causal associations between chronic gastrointestinal diseases and ED were evaluated using Mendelian randomization (MR) analysis, followed by a meta-analysis to determine the ultimate causal effect. The LDSC results suggested significant genetic correlations between Crohn's disease (CD) and ED. Inflammatory bowel disease (IBD), ulcerative colitis (UC), and liver cirrhosis (LC) were found to have potential genetic correlations with ED. The combined multiple MR results indicate that IBD and CD have significant causal relationships with ED, while colorectal cancer (CRC) may have a potential causal effect on ED. This research provided evidence supporting a causal association between IBD, CD, CRC, and ED. The impact of chronic gastrointestinal diseases on ED warrants greater attention in clinical practice.

Causal associations between 45 dietary intake habits and urolithiasis: insights from genetic studies.

Different dietary habits can have varying effects on human health and metabolism, and these can be intervened and regulated. Kidney stones, as a disease caused by multiple factors, are largely attributed to diet and metabolism, but the potential causal relationship with dietary intake habits remains unclear. Therefore, this study aims to link the predicted dietary intake based on 45 genetic factors with urolithiasis and explore the potential causal relationship. We extracted complete genome-wide association studies (GWASs) data on 45 dietary intake traits from the UK Biobank study. Data on kidney stones were obtained from the FinnGen database. In both univariable and multivariable Mendelian randomization analyses, we used inverse variance weighted (IVW) as the primary method to calculate P values, odds ratios (ORs), and 95% confidence intervals (CIs). We examined result heterogeneity using Cochran's Q test. We also carefully investigated potential sources of horizontal pleiotropy using the Mendelian randomization (MR)-PRESSO and MR-Egger methods, and conducted linkage disequilibrium score regression (LDSC) analysis on the corrected P values. Through univariable analysis, we identified 11 dietary habits that potentially causally associate with kidney stones among the 45 examined traits, including 9 protective factors and 2 risk factors. Based on the corrected results with false discovery rate (FDR) and sensitivity analysis, we found one relatively robust evidence. We controlled for common stone risk factors, such as body mass index and smoking, as confounders in multivariable analysis, and no significant results were observed after controlling for these confounders. Based on the LDSC analysis, most of the evidence supports significant genetic correlations with urolithiasis among the 11 traits with potential causal associations. This study confirms the impact of certain dietary factors on the development of kidney stones. Our findings contribute to providing evidence for dietary adjustments in daily life or dietary guidance specifically targeting kidney stone patients.

Shared aetiology underlying multiple sclerosis and other immune mediated inflammatory diseases: Swedish familial co-aggregation and large-scale genetic correlation analyses

BackgroundWhile multiple sclerosis (MS) affects less than 1 % of the general population, immune mediated inflammatory diseases (IMIDs) collectively influence 5–10 % of the population. Understanding familial co-aggregation of MS and other IMIDs carries important clinical and public health implications that will enable early detection and personalized treatment. ObjectiveTo estimate the familial association between MS and other IMIDs and to quantify their shared genetic basis. DesignRegister-based multi-generational nested case-control familial co-aggregation study and genetic correlation study. SettingSweden. Participants24,995 individuals with MS matched with 253,870 controls and 1,283,502 first-degree relatives (mothers, fathers, full siblings, and offspring) for familial co-aggregation analysis; population of European ancestry for genetic correlation analysis. MeasurementsLogistic regressions with adjustment for covariates were used to estimate the odds ratios (ORs) of developing MS in individuals with first-degree relatives diagnosed with IMIDs compared to those without such family history. Pairwise genome-wide genetic correlations were estimated with linkage-disequilibrium score regression. ResultsWe observed an OR for familial co-aggregation of MS of 1.09 (95 % confidence interval (95%CI) = 1.07−1.11) in families with IMIDs history compared to families without. The association remained broadly consistent after stratification by sex concordance of relative pairs and by kinships. 18 IMID subtypes showed a familial association with MS, 7 of which including other acute widespread myelin destruction, encephalitis or myelitis or encephalomyelitis, inflammatory bowel disease, autoimmune thyroid diseases, systemic lupus erythematosus, other inflammatory system diseases, and sarcoidosis withstood multiple correction. Genetic correlations further revealed a shared genetic basis between 7 IMID subtypes with MS. ConclusionWe demonstrated a modest familial co-aggregation of MS with several IMIDs, and such association is likely due to shared genetic factors.

Insights from immunomics and metabolomics on the associations between prostatic diseases and coronavirus disease 2019

BackgroundThe causal associations and potential mechanisms between prostatic diseases, the predominant male urological disorders, and the course of COVID-19 remain unclear. MethodsA two-sample Mendelian randomization (MR) analysis was performed to evaluate causal associations between prostate cancer, benign prostatic hyperplasia, and prostatitis and different COVID-19 outcomes (SARS-CoV-2 infection, hospitalized COVID-19, and severe COVID-19). Reverse MR, linkage disequilibrium score regression, and Bayesian colocalization analyses were subsequently performed to strengthen the identified causal relationships. Furthermore, immunome- and metabolome-wide MR analysis was conducted to prioritize COVID-19-associated immune characteristics and metabolites. Two-step MR analysis was performed to evaluate the mediating effects of the immunome and metabolome on the associations between prostatic diseases and COVID-19. ResultsGenetically predicted prostatic diseases were not causally associated with severe COVID-19, while prostatitis was suggested to be an independent risk factor for SARS-CoV-2 infection (odds ratio (OR) = 1.11, 95% confidence interval (CI) 1.01 to 1.23; P = 0.03). Multiple sensitivity tests verified the reliability of the established causal relationships. Dozens of blood immune and metabolic features were identified to reveal the immune and metabolic profiles of different COVID-19 courses. Moreover, PDL-1 on monocyte was found to mediate the interaction between prostatitis and SARS-CoV-2 infection, with a mediation proportion of 9.2%. ConclusionOur study identified the causal relationships of prostatic diseases with COVID-19 and suggested pathways explaining these associations through alterations in the blood immunome and metabolome.

Shared genetic etiology of vessel diseases: A genome-wide multi-traits association analysis

BackgroundThe comorbidity among vascular diseases has been widely reported, however, the contribution of shared genetic components remains ambiguous. MethodsBased on genome-wide association study summary statistics, we employed statistical genetics methodologies to explore the shared genetic basis of eight vascular diseases: coronary artery disease, abdominal aortic aneurysm, ischemic stroke, peripheral artery disease, thoracic aortic aneurysm, phlebitis, varicose veins, and venous thromboembolism. We assessed global and local genetic correlations among these disorders by linkage disequilibrium score regression, high-definition likelihood, and local analysis of variant association. Cross-trait analyses conducted with CPASSOC identified pleiotropic variants and loci. Further, biological pathways at the multi-omics level were explored using multimarker analysis of genomic annotation, transcriptome-wide and proteome-wide association studies. Causal associations among the vascular diseases were evaluated by mendelian randomization and latent causal variable to assess vertical pleiotropic effects. ResultsWe found significant global genetic associations in 18 pairs of vascular diseases. Additionally, we discovered 317 unique genomic regions where at least one pair of traits demonstrated significant correlation. Multi-trait association analysis identified 19,361 significant potential pleiotropic variants in 274 independent pleiotropic loci. Multi-trait colocalization analysis revealed 56 colocalized loci in specific disease sets. Gene-based analysis identified 700 potential pleiotropic genes, which were subsequently validated at both transcriptome and protein levels. Gene-set enrichment analysis supports the role of biological pathways such as vessel wall structure, coagulation and lipid transport in vascular disease. Additionally, 7 pairs of vascular diseases have a causal relationship. ConclusionsOur study indicates a shared genetic basis and the presence of common risk genes among vascular diseases. These findings offer novel insights into potential mechanisms underlying the association between vascular diseases, as well as provide guidance for interventions and treatments of multi-vascular conditions.

An Atlas on Multitudinous Risk Factors Associated with Incident Hypertension: Comprehensive Exposome-Wide Association and Wide-angled Genetic Analyses.

Despite numerous risk factors being associated with hypertension, the breadth of research remains constrained, with a notable absence of systematic, data-driven exploration into established and novel factors across a broad spectrum of exposures. This study aims to construct an atlas on known and emerging factors for hypertension through comprehensive epidemiological and genetic analyses. We conducted exposome-wide association studies (ExWAS) via Cox regression models on two equally sized datasets for discovery and replication in UK Biobank, a large prospective cohort study. A maximum of 10,806 exposome variables were included in ExWAS and were grouped into 13 categories: genomics, sociodemographic, lifestyle, physical measure, biomarkers, medical history, imaging markers, sex-specific factors, psychosocial factors, cognitive function indicators, local environment, family history, and early life factors. The credibility of epidemiological associations was assessed through meta-analyses. The genetic underpinnings were explored through linkage-disequilibrium score regression (LDSC), quantifying global genetic correlation. Two-sample Mendelian randomization (MR) studies were conducted to investigate the causal effects of each exposure on hypertension, with co-analyses undertaken to identify associations supported by both epidemiological and genetic evidence. This study included 214,957 UK Biobank participants, hypertension-free at baseline. In our ExWAS analyses, 964 significant exposome variables were replicated. In meta-analyses, 462 were backed by convincing and highly suggestive evidence. Among 10,765 exposures in LDSC, 1923 had global genetic correlations with hypertension. The MR analyses yielded robust evidence for a causal relationship with 125 phenotypes, probable evidence for 270 phenotypes, and suggestive evidence for 718 phenotypes. Co-analyses identified 146 associations supported by strong epidemiological and genetic evidence. These primarily encompassed traits like anthropometry, lung function, lipids, and factors such as urate and walking pace. This coverage further extended from well-studied factors (like BMI and physical activity) to less explored exposures (including high light scatter reticulocyte count and age at first live). All study results are compiled in a webserver for user-friendly exploration of exposure-hypertension associations. This study provides an atlas on established and novel risk factors for hypertension, underpinned by epidemiological and causal evidence. Our findings present a multiple perspective to prioritize hypertension prevention strategies, encompassing modifiable risk factors like television watching time and walking pace. The study also emphasized the roles of urate in hypertension pathogenesis. Consequently, our study may serve as a critical guide for hypertension prevention and bear significant clinical implications.

Shared genetic correlations between kidney diseases and sepsis.

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

Causality of genetically determined blood metabolites on inflammatory bowel disease: a two-sample Mendelian randomization study

Inflammatory bowel disease (IBD) is a chronic and recurrent inflammatory disease of the gastrointestinal tract, including two subtypes: Crohn’s disease (CD) and ulcerative colitis (UC). Metabolic disorders are important factors in the development of IBD. However, the evidence for the causal relationship between blood metabolites and IBD remains limited. A two-sample MR analysis was applied to evaluate relationships between 486 blood metabolites and IBD. The inverse variance weighted method was chosen as the primary MR analysis method. False discovery rate correction was used to control for false positives in multiple testing. Following complementary and sensitivity analyses were conducted using methods such as weight median, MR-egger, weighted mode, simple mode, Cochran Q test, and MR-PRESSO. Moreover, we performed replication, meta-analysis, Steiger test, and linkage disequilibrium score regression to enhance the robustness of the results. Additionally, we performed metabolic pathway analysis to identify potential metabolic pathways. As a result, we identified four significant causal associations between four blood metabolites and two IBD subtypes. Specifically, one metabolite was identified as being associated with the development of CD (mannose: odds ratio (OR) = 0.19, 95% confidence interval (CI) 0.08–0.43, P = 8.54 × 10–5). Three metabolites were identified as being associated with the development of UC (arachidonate (20:4n6): OR = 0.18, 95% CI 0.11–0.30, P = 2.09 × 10–11; 1, 5-anhydroglucitol: OR = 2.21, 95% CI 1.47–3.34, P = 1.50 × 10–4; 2-stearoylglycerophosphocholine: OR = 2.66, 95% CI 1.53–4.63, P = 5.30 × 10–4). The findings of our study suggested that the identified metabolites and metabolic pathways can be considered as useful circulating metabolic biomarkers for the screening and prevention of IBD in clinical practice, as well as candidate molecules for future mechanism exploration and drug target selection.

Body Mass Index and Hypertension as Mediators of the Association Between Age at Menarche and Subclinical Atherosclerosis: A Sex-Specific Mendelian Randomization Analysis.

Early age at menarche (AAM) has been associated with a higher risk of carotid artery intima-media thickness (cIMT), an indicator of subclinical vascular disease, albeit the mechanisms underlying this association remain elusive. A better understanding of the relationship between AAM, modifiable cardiometabolic risk factors, and subclinical atherosclerosis may contribute to improved primary prevention and cardiovascular disease treatment. We aimed to investigate the putative causal role of AAM on cIMT, and to identify and quantify the potentially mediatory effects of cardiometabolic risk factors underlying this relationship. We conducted linkage disequilibrium score regression analyses between our exposure of interest, AAM, our outcome of interest, cIMT and potential mediators of the AAM-cIMT association to gauge cross-trait genetic overlap. We considered as mediators the modifiable anthropometric risk factors body mass index (BMI), systolic blood pressure (SBP), lipid traits (total cholesterol, triglycerides, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol), and glycemic traits (fasting glucose). We then leveraged the paradigm of Mendelian randomization to infer causality between AAM and cIMT, and to identify whether cardiometabolic risk factors served as potential mediators of this effect. Our analyses showed that genetically predicted AAM was inversely associated with cIMT, BMI, SBP, and triglycerides, and positively associated with high-density lipoprotein, low-density lipoprotein, and total cholesterol. We showed that the effect of genetically predicted AAM on cIMT may be partially mediated through BMI (20.1% [95% CI, 1.4% to 38.9%]) and SBP (13.5% [95% CI, 0.5%-26.6%]). Our cluster-specific Mendelian randomization revealed heterogeneous causal effect estimates of age at menarche on BMI and SBP. We highlight supporting evidence for a potential causal association between earlier AAM and cIMT, and almost one third of the effect of AAM on cIMT may be mediated by BMI and SBP. Early intervention aimed at lowering BMI and hypertension may be beneficial in reducing the risk of developing subclinical atherosclerosis due to earlier age at menarche.