Genome-wide Association Studies Catalog Research Articles

The impact of neurocognitive and psychiatric disorders on the risk of idiopathic normal pressure hydrocephalus: A bidirectional Mendelian randomization study.

Neurocognitive and psychiatric disorders have been proved that they can comorbid more often with idiopathic normal pressure hydrocephalus (iNPH) than general population. However, the potential causal association between these disorders and iNPH has not been assessed. Thus, our study aims to investigate the causal relationship between them based on a bidirectional Mendelian randomization (MR) analysis. Random effects of the inverse variance weighted (IVW) method were conducted to obtain the causal association among the neurocognitive disorders, psychiatric disorders, and iNPH. Genome-wide association studies (GWAS) of 12 neurocognitive and psychiatric disorders were downloaded via the OpenGWAS database, GWAS Catalog, and Psychiatric Genomics Consortium, whereas GWAS data of iNPH were obtained from the FinnGen consortium round 9 release, with 767 cases and 375,610 controls of European ancestry. We also conducted the sensitivity analysis in these significant causal inferences using weighted median model, Cochrane's Q test, MR-Egger regression, MR Pleiotropy Residual Sum and Outlier detect and the leave-one-out analysis. For most of the neurocognitive and psychiatric disorders, no causal association was established between them and iNPH. We have found that iNPH (odds ratio [OR]=1.030, 95% confidence interval [CI]: 1.011-1.048, p=.001) is associated with increased risk for schizophrenia, which failed in validation of sensitivity analysis. Notably, genetically predicted Parkinson's disease (PD) is associated with increased risk of iNPH (OR=1.256, 95% CI: 1.045-1.511, p=.015). Our study has revealed the potential causal effect in which PD associated with an increased risk of iNPH. Further study is warranted to investigate the association between PD and iNPH and the potential underlying mechanism.

Association of serum uric acid level with intracranial aneurysms: A Mendelian randomization study

ObjectiveNumerous studies have posited the involvement of serum uric acid (SUA) in the pathogenesis and progression of various cardiovascular diseases, particularly aortic aneurysms. However, the casual effect of SUA level on intracranial aneurysms (IAs) was rarely studied. Consequently, we aimed to explore the causal association between SUA and IAs using Mendelian randomization (MR) analysis. MethodsWe conducted a two-sample MR analysis with SUA as the exposure variable and IAs as the outcome variable. Genome-wide association study (GWAS) datasets for SUA were acquired from the Open GWAS catalog, including 389,404 European and 129,405 East Asian individuals. The dataset for IAs was sourced from a meta-analysis of GWASs comprising 317,636 individuals across different ancestral populations (European: 7495 cases and 71,934 controls; East Asian: 3259 cases and 234,948 controls). The MR analyses were performed according to populations (European and East Asian) and IAs status [unruptured IAs (uIAs) or aneurysmal subarachnoid hemorrhage (aSAH)], respectively. The inverse variance weighted (IVW) method was employed as primary analysis to discern causal estimates. ResultsOur findings revealed that an elevated genetically predicted SUA level (mg/dL) correlated with an increased risk of IAs among the European population (OR = 1.29 [95%CI:1.05–1.57], P = 0.013) and East Asian population (OR = 1.56 [95%CI: 1.27–1.92], P < 0.001). Among European individuals, subgroup analysis indicated a persistent causal association of SUA with uIAs (OR = 1.50 [95%CI: 1.08–2.08], P = 0.015) and aSAH (OR = 1.26 [95%CI: 1.00–1.60], P = 0.049). However, subgroup analysis in East Asian populations was not conducted due to the lack of separate data on uIAs and aSAH. ConclusionsOur MR analysis demonstrated a causal relationship between elevated SUA levels and an amplified risk of IAs. Further rigorous investigations are imperative to provide evidence and elucidate the underlying mechanisms.

Integrated Analysis of Genomic and Genome-Wide Association Studies Identified Candidate Genes for Nutrigenetic Studies in Flavonoids and Vascular Health: Path to Precision Nutrition for (Poly)phenols.

Flavonoids exert vasculoprotective effects in humans, but interindividual variability in their action has also been reported. This study aims to identify genes that are associated with vascular health effects of flavonoids and whose polymorphisms could explain interindividual variability in response to their intake. Applying the predetermined literature search criteria, we identified five human intervention studies reporting positive effects of flavonoids on vascular function together with global genomic changes analyzed using microarray methods. Genes involved in vascular dysfunction were identified from genome-wide association studies (GWAS). By extracting data from the eligible human intervention studies, we obtained 5807 differentially expressed genes (DEGs). The number of identified upstream regulators (URs) varied across the studies, from 227 to 1407. The search of the GWAS Catalog revealed 493 genes associated with vascular dysfunction. An integrative analysis of transcriptomic data with GWAS genes identified 106 candidate DEGs and 42 candidate URs, while subsequent functional analyses and a search of the literature identified 20 top priority candidate genes: ALDH2, APOE, CAPZA1, CYP11B2, GNA13, IL6, IRF5, LDLR, LPL, LSP1, MKNK1, MMP3, MTHFR, MYO6, NCR3, PPARG, SARM1, TCF20, TCF7L2, and TNF. In conclusion, this integrated analysis identifies important genes to design future nutrigenetic studies for development of precision nutrition for polyphenols.

A clustering approach to improve our understanding of the genetic and phenotypic complexity of chronic kidney disease

Chronic kidney disease (CKD) is a complex disorder that causes a gradual loss of kidney function, affecting approximately 9.1% of the world's population. Here, we use a soft-clustering algorithm to deconstruct its genetic heterogeneity. First, we selected 322 CKD-associated independent genetic variants from published genome-wide association studies (GWAS) and added association results for 229 traits from the GWAS catalog. We then applied nonnegative matrix factorization (NMF) to discover overlapping clusters of related traits and variants. We computed cluster-specific polygenic scores and validated each cluster with a phenome-wide association study (PheWAS) on the BioMe biobank (n = 31,701). NMF identified nine clusters that reflect different aspects of CKD, with the top-weighted traits signifying areas such as kidney function, type 2 diabetes (T2D), and body weight. For most clusters, the top-weighted traits were confirmed in the PheWAS analysis. Results were found to be more significant in the cross-ancestry analysis, although significant ancestry-specific associations were also identified. While all alleles were associated with a decreased kidney function, associations with CKD-related diseases (e.g., T2D) were found only for a smaller subset of variants and differed across genetic ancestry groups. Our findings leverage genetics to gain insights into the underlying biology of CKD and investigate population-specific associations.

Exploring the immunological landscape of osteomyelitis through mendelian randomization analysis.

Osteomyelitis is a severe bone marrow infection, whose pathogenesis is not yet fully understood. This study aims to explore the causal relationship between immune cell characteristics and osteomyelitis, hoping to provide new insights for the prevention and treatment of osteomyelitis. Based on two independent samples, this study employed a two-sample Mendelian randomization (MR) analysis to assess the causal relationship between 731 immune cell characteristics (divided into seven groups) and osteomyelitis. Genetic variants were used as proxies for risk factors to ensure that the selected instrumental variables meet the three key assumptions of MR analysis. Genome-Wide Association Studies (GWAS) data for immune characteristics were obtained from the public GWAS catalog, while data for osteomyelitis was sourced from the FinnGen. At a significance level of 0.05, 21 immune phenotypes were identified as having a causal relationship with osteomyelitis development. In the B cell group, phenotypes such as Memory B cell % B cell (percentage of memory B cells within the total B cell population, % finger cell ratio), CD20- %B cell (percentage of B cells that do not express the CD20 marker on their surface), and Memory B cell % lymphocyte showed a positive causal relationship with osteomyelitis, while Naive-mature B cell %B cell and IgD-CD38-absolute cell counts (AC) phenotypes showed a negative causal relationship. In addition, specific immune phenotypes in the conventional dendritic cells (cDCs) group, Myeloid cell group, TBNK (T cells, B cells, natural killer cells) cell group, T cell maturation stage, and Treg cell group also showed significant associations with osteomyelitis. Through reverse MR analysis, it was found that osteomyelitis had no significant causal impact on these immune phenotypes, suggesting that the occurrence of osteomyelitis may not affect these immune cell phenotypes. To our knowledge, this is the first study to shed light on the causal relationship between specific immune cell characteristics and the development of osteomyelitis, thereby providing a new perspective to understand the immune mechanism of osteomyelitis. These findings are significant for formulating targeted prevention and treatment strategies, and hold promise to improve the treatment outcomes for patients with osteomyelitis.

Eating disorder and bipolar mental illness through genome wide association studies

IntroductionBesides the role played by environmental factors and their epigenetic influences, scientific researchers showed that the susceptibility to develop an eating disorder among bipolar people is due to genetic factors.ObjectivesTo review the genetic factors behind eating disorders, highlight the role of genetics and epigenetics in the comorbidity of bipolar and eating disorders.Methods To delineate the role of genetics and epigenetics in eating disorders and bipolar disorders as two related mental illness, we comprehensively reviewed the scientific literature using GWAS (genome wide association studies) catalog databases to find genome-wide association studies carried out on patients with bipolar disorder EFO_0005203 and eating disorder comorbid condition (anorexia nervosa, binge eating, bulimia nervosa) EFO_0005203.Results GWAS of eating disorders were found in 33 studies with 324 associations whereas those of bipolar disorder were found in 114 studies with 1469 associations. GWAS of eating disorders within bipolar disorders revealed 182 and 134 associations, as well as 10 and 8 publications respectively. Only anorexia nervosa and binge eating were studied in association with bipolar disorders. The genetic variants were protein coding genes (CUBN, FAM228B, FXR1, etc.), non-coding RNA genes (SOX2-OT, MMADHC-DT, etc.), and pseudo-genes (RNU1-23P, CACYBPP2, etc.).ConclusionsAbout 300 genetic variants are associated with eating disorder as a comorbid condition of bipolar disorders. These variants may play a crucial role in the causes and mechanisms of eating disorders and should be more investigated towards more precise clinical and genetic entities.Disclosure of InterestNone Declared

Vitamin D-associated genetic variants in the Brazilian population: Investigating potential instruments for Mendelian randomization.

Vitamin D is required for bone and mineral metabolism and participates in the regulation of the immune response. It is also linked to several chronic diseases and conditions, usually in populations of European descent. Brazil presents a high prevalence of vitamin D deficiency and insufficiency despite the widespread availability of sunlight in the country. Thus, it is important to investigate the role of vitamin D as a risk factor for disease and to establish causal relationships between vitamin D levels and health-related outcomes in the Brazilian population. To examine genetic variants identified as determinants of serum vitamin D in genome-wide association studies of European populations and check whether the same associations are present in Brazil. If so, these single nucleotide polymorphisms (SNPs) could be developed locally as proxies to use in genetically informed causal inference methods, such as Mendelian randomization. We extracted SNPs associated with vitamin D from the genomewide association studies catalog. We did a literature search to select papers ascertaining these variants and vitamin D concentrations in Brazil. GC was the gene with the strongest association with vitamin D levels, in agreement with existing findings in European populations. However, VDR was the most investigated gene, regardless of its non-existing association with vitamin D in the genomewide association studies. More research is needed to validate sound proxies for vitamin D levels in Brazil, for example, prioritizing GC rather than VDR.

Cross-ancestry genetic architecture and prediction for cholesterol traits.

While cholesterol is essential, a high level of cholesterol is associated with the risk of cardiovascular diseases. Genome-wide association studies (GWASs) have proven successful in identifying genetic variants that are linked to cholesterol levels, predominantly in white European populations. However, the extent to which genetic effects on cholesterol vary across different ancestries remains largely unexplored. Here, we estimate cross-ancestry genetic correlation to address questions on how genetic effects are shared across ancestries. We find significant genetic heterogeneity between ancestries for cholesterol traits. Furthermore, we demonstrate that single nucleotide polymorphisms (SNPs) with concordant effects across ancestries for cholesterol are more frequently found in regulatory regions compared to other genomic regions. Indeed, the positive genetic covariance between ancestries is mostly driven by the effects of the concordant SNPs, whereas the genetic heterogeneity is attributed to the discordant SNPs. We also show that the predictive ability of the concordant SNPs is significantly higher than the discordant SNPs in the cross-ancestry polygenic prediction. The list of concordant SNPs for cholesterol is available in GWAS Catalog. These findings have relevance for the understanding of shared genetic architecture across ancestries, contributing to the development of clinical strategies for polygenic prediction of cholesterol in cross-ancestral settings.

Potential biomarker signatures in male infertility: integrative genomic analysis

BackgroundStudies have attributed 50% of infertility cases to male infertility, 15% of which is caused by idiopathic genetic factors. Currently, no specific biomarkers have been revealed for male infertility. Furthermore, research on genetic factors causing male infertility is still limited. As with other multifactorial genetic disorders, numerous risk loci for male infertility have been identified by genome-wide association studies (GWAS), although their clinical significance remains uncertain. Therefore, we utilized an integrative bioinformatics-based approach to identify biomarkers for male infertility. Bioinformatics analysis was performed using Open Targets Platform, DisGeNet, and GWAS Catalog. After that, the STRING database and the Cytoscape program were used to analyze protein–protein interaction. CytoHubba was used to determine the most significant gene candidates. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses were used to assess biological functions that correspond to the male infertility disease pathway.ResultsWe identified 305 genes associated with male infertility and highlighted 10 biological risk genes as potential biomarkers for male infertility such as TEX11, SPO11, SYCP3, HORMAD1, STAG3, MSH4, SYCP2, SYCE1, RAD21L1, and AMH. Of all the genes, we took the top three genes, namely, TEX11, SPO11, and SYCP3 as the genes that have the most potential as biomarkers.ConclusionsTEX11, SPO11, and SYCP3 are involved in meiosis and spermatogenesis. We propose that further research in regarding these genes in detecting male infertility.

The causal effect of inflammatory proteins and immune cell populations on diabetic nephropathy: evidence from Mendelian randomization.

Diabetic nephropathy (DN) is one of the diabetic microvascular complications with complex pathophysiology, and exploring the landscape of immune dysregulation in DN is valuable for pathogenesis and disease treatment. We crystallized possible inflammatory exposures into 91 circulating inflammatory proteins and 109 blood immune cells; and assessed the causal relationship between inflammation and DN using Mendelian randomization (MR). Based on publicly available genetic data, we explored causal associations between inflammation and DN risk by two-sample MR analysis. Genome-wide association study (GWAS) summary statistics for 91 circulating inflammatory proteins, 109 immune cells absolute counts, and DN were acquired from the GWAS Catalog. Inverse Variance Weighted (IVW) was the main MR method, while MR-Egger and MR-pleiotropy residuals and outliers (MR-PRESSO) were utilized for sensitivity analysis. Cochrane's Q was used to test for heterogeneity. The leave-one-out method ensured the stability of the MR results. This study revealed that higher levels of TNF-related activation-induced cytokine and tumor necrosis factor ligand superfamily member 14 were possibly associated with the increased risk of DN according to the IVW approach, with estimated odds ratios (OR) of 1.287 (95% confidence interval [CI] 1.051 to 1.577, P = 0.015) and 1.249 (95% CI 1.018 to 1.532, P = 0.033). Five immune cell traits were identified that might be linked to increased DN risk, including the higher absolute counts of HLA DR+ natural killer cell (OR = 1.248, 95% CI 1.055 to 1.476, P = 0.010), IgD+ CD38+ B cell (OR = 1.148, 95% CI 1.033 to 1.276, P = 0.010), CD25++ CD8+ T cell (OR = 1.159, 95% CI 1.032 to 1.302, P = 0.013), CD4- CD8- T cell (OR = 1.226, 95% CI 1.032 to 1.457, P = 0.020), and IgD- CD38- B cell (OR = 1.182, 95% CI 1.009 to 1.386, P = 0.039). In addition, elevated levels of interleukin-1 alpha (OR = 0.712, 95% CI 0.514 to 0.984, P = 0.040) and unswitched memory B cell (OR = 0.797, 95% CI 0.651 to 0.974, P = 0.027) may reduce the risk of developing DN. We identified inflammation-related exposures that may be associated with the risk of DN at the level of genetic prediction, which contributes to a better understanding of the etiologic of DN and facilitates the development of targeted therapies for DN.

Abstract P250: Vascular Contributions to Alzheimer's Disease

Introduction: Alzheimer’s disease (AD) is a debilitating neurodegenerative disorder that affects over 50 million people worldwide. The role of vascular risk factors have been described as a contributor to and a major comorbidity of AD pathogenesis; yet there is discordant evidence of this complex relationship between cardiovascular diseases (CVD) and its risk factors (like hypertension, hyperlipidemia, obesity, etc.) with AD pathophysiology and cognitive decline. AD associated Genome-wide association studies (GWAS) and derived polygenic risk scores (AD PRS) have uncovered some significant common genetic variants relating to CVD risk factors; however, we are still yet to unravel the comprehensive impact of these vascular genetic contributions to AD pathogenesis and cognitive decline. Method: In this study, we used 1800 participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort spanning the full spectrum of clinical and pathological diagnoses of the AD spectrum, as our target dataset used for polygenic risk score calculation. Thereafter, we obtained GWAS summary statistics for cumulative cardiovascular risk by searching the Polygenic Score (PGS) GWAS Catalog using CVD as the ‘mapped trait” and then calculated cardiovascular-based PRS using HRS-based imputed GWAS data of the ADNI cohort. We conducted association analysis using a multivariate linear regression model with appropriate covariates (age, sex, APOE, education, etc.) between CVD-related polygenic risk score (CVD-PRS) with the different clinical AD diagnoses groups (Cognitively Normal/CN, Significant Memory Concerns/SMC, Mild Cognitive Impairment/MCI, Alzheimer's Disease/AD). We also performed association analysis of this CVD-PRS with white matter hyperintensity (WMHI) values, a vascular biomarker, at baseline using a linear regression model. Furthermore, we extended our analyses of CVD-related PRS with cognitive performance at baseline using composite scores for memory (MEM) and executive functioning (EF). Results and Conclusion: We found significantly strong correlation of CVD-related PRS with only certain AD Diagnoses groups (Significant Memory Concerns: SMC and Alzheimer's: AD) in the AD continuum. Additionally, we found strong associations (p &lt; 0.05) of this cardiovascular based- polygenic risk score with baseline memory as well as White Matter Hyperintensity (WMH) in our sample, specifically the group with a clinical diagnosis of AD. Furthermore, we are performing longitudinal association analysis of CVD-related PRS with longitudinal cognitive decline using a linear mixed effects model. Our findings will help us understand 1) how a cumulative CVD-related PRS associates with different AD diagnoses subgroups as well as vascular biomarkers for AD and 2) how CVD-related PRS associates with cognitive performance and longitudinal cognitive decline.

Mendelian randomization supports genetic liability to hospitalization for COVID-19 as a risk factor of pre-eclampsia.

Pre-eclampsia and eclampsia are among the major threats to pregnant women and fetuses, but they can be mitigated by prevention and early screening. Existing observational research presents conflicting evidence regarding the causal effects of coronavirus disease 2019 (COVID-19) on pre-eclampsia risk. Through Mendelian randomization (MR), this study aims to investigate the causal effect of three COVID-19 severity phenotypes on the risk of pre-eclampsia and eclampsia to provide more rigorous evidence. Two-sample MR was utilized to examine causal effects. Summary-level data from genome-wide association studies (GWAS) of individuals of European ancestry were acquired from the GWAS catalog and FinnGen databases. Single-nucleotide polymorphisms associated with COVID-19 traits at p < 5 × -8 were obtained and pruned for linkage disequilibrium to generate instrumental variables for COVID-19. Inverse variance weighted estimates were used as the primary MR results, with weighted median and MR-Egger as auxiliary analyses. The robustness of the MR findings was also evaluated through sensitivity analyses. Bonferroni correction was applied to primary results, with a p < 0.0083 considered significant evidence and a p within 0.083-0.05 considered suggestive evidence. Critical ill COVID-19 [defined as hospitalization for COVID-19 with either a death outcome or respiratory support, OR (95% CI): 1.17 (1.03-1.33), p = 0.020] and hospitalized COVID-19 [defined as hospitalization for COVID-19, OR (95% CI): 1.10 (1.01-1.19), p = 0.026] demonstrated suggestive causal effects on pre-eclampsia, while general severe acute respiratory syndrome coronavirus 2 infection did not exhibit a significant causal effect on pre-eclampsia. None of the three COVID-19 severity phenotypes exhibited a significant causal effect on eclampsia. Our investigation demonstrates a suggestive causal effect of genetic susceptibility to critical ill COVID-19 and hospitalized COVID-19 on pre-eclampsia. The COVID-19 severity exhibited a suggestive positive dose-response relationship with the risk of pre-eclampsia. Augmented attention should be paid to pregnant women hospitalized for COVID-19, especially those needing respiratory support.

Association between gut microbiota and Hirschsprung disease: a bidirectional two-sample Mendelian randomization study.

Several studies have pointed to the critical role of gut microbiota (GM) and their metabolites in Hirschsprung disease (HSCR) pathogenesis. However, the detailed causal relationship between GM and HSCR remains unknown. In this study, we used two-sample Mendelian randomization (MR) analysis to investigate the causal relationship between GM and HSCR, based on the MiBioGen Consortium's genome-wide association study (GWAS) and the GWAS Catalog's HSCR data. Reverse MR analysis was performed subsequently, and the sensitivity analysis, Cochran's Q-test, MR pleiotropy residual sum, outlier (MR-PRESSO), and the MR-Egger intercept were used to analyze heterogeneity or horizontal pleiotropy. 16S rDNA sequencing and targeted mass spectrometry were developed for initial validation. In the forward MR analysis, inverse-variance weighted (IVW) estimates suggested that Eggerthella (OR: 2.66, 95%CI: 1.23-5.74, p = 0.01) was a risk factor for HSCR, while Peptococcus (OR: 0.37, 95%CI: 0.18-0.73, p = 0.004), Ruminococcus2 (OR: 0.32, 95%CI: 0.11-0.91, p = 0.03), Clostridiaceae1 (OR: 0.22, 95%CI: 0.06-0.78, p = 0.02), Mollicutes RF9 (OR: 0.27, 95%CI: 0.09-0.8, p = 0.02), Ruminococcaceae (OR: 0.16, 95%CI: 0.04-0.66, p = 0.01), and Paraprevotella (OR: 0.45, 95%CI: 0.21-0.98, p = 0.04) were protective factors for HSCR, which had no heterogeneity or horizontal pleiotropy. However, reverse MR analysis showed that HSCR (OR: 1.02, 95%CI: 1-1.03, p = 0.049) is the risk factor for Eggerthella. Furthermore, some of the above microbiota and short-chain fatty acids (SCFAs) were altered in HSCR, showing a correlation. Our analysis established the relationship between specific GM and HSCR, identifying specific bacteria as protective or risk factors. Significant microbiota and SCFAs were altered in HSCR, underlining the importance of further study and providing new insights into the pathogenesis and treatment.

Causal role of immune cells in obstructive sleep apnea hypopnea syndrome: Mendelian randomization study

BACKGROUND Despite being one of the most prevalent sleep disorders, obstructive sleep apnea hypoventilation syndrome (OSAHS) has limited information on its immunologic foundation. The immunological underpinnings of certain major psychiatric diseases have been uncovered in recent years thanks to the extensive use of genome-wide association studies (GWAS) and genotyping techniques using high-density genetic markers (e.g. , SNP or CNVs). But this tactic hasn't yet been applied to OSAHS. Using a Mendelian randomization analysis, we analyzed the causal link between immune cells and the illness in order to comprehend the immunological bases of OSAHS. AIM To investigate the immune cells' association with OSAHS via genetic methods, guiding future clinical research. METHODS A comprehensive two-sample mendelian randomization study was conducted to investigate the causal relationship between immune cell characteristics and OSAHS. Summary statistics for each immune cell feature were obtained from the GWAS catalog. Information on 731 immune cell properties, such as morphologic parameters, median fluorescence intensity, absolute cellular, and relative cellular, was compiled using publicly available genetic databases. The results' robustness, heterogeneity, and horizontal pleiotropy were confirmed using extensive sensitivity examination. RESULTS Following false discovery rate (FDR) correction, no statistically significant effect of OSAHS on immunophenotypes was observed. However, two lymphocyte subsets were found to have a significant association with the risk of OSAHS: Basophil %CD33dim HLA DR- CD66b- (OR = 1.03, 95%CI = 1.01-1.03, P &lt; 0.001); CD38 on IgD+ CD24- B cell (OR = 1.04, 95%CI = 1.02-1.04, P = 0.019). CONCLUSION This study shows a strong link between immune cells and OSAHS through a gene approach, thus offering direction for potential future medical research.

Causal relationship between gut microbiota and risk of esophageal cancer: evidence from Mendelian randomization study.

The causative implications remain ambiguous. Consequently, this study aims to evaluate the putative causal relationship between gut microbiota and Esophageal cancer (EC). The genome-wide association study (GWAS) pertaining to the microbiome, derived from the MiBioGen consortium-which consolidates 18,340 samples across 24 population-based cohorts-was utilized as the exposure dataset. Employing the GWAS summary statistics specific to EC patients sourced from the GWAS Catalog and leveraging the two-sample Mendelian randomization (MR) methodology, the principal analytical method applied was the inverse variance weighted (IVW) technique. Cochran's Q statistic was utilized to discern heterogeneity inherent in the data set. Subsequently, a reverse MR analysis was executed. Findings derived from the IVW technique elucidated that the Family Porphyromonadaceae (P = 0.048) and Genus Candidatus Soleaferrea (P = 0.048) function as deterrents against EC development. In contrast, the Genus Catenibacterium (P = 0.044), Genus Eubacterium coprostanoligenes group (P = 0.038), Genus Marvinbryantia (P = 0.049), Genus Ruminococcaceae UCG010 (P = 0.034), Genus Ruminococcus1 (P = 0.047), and Genus Sutterella (P = 0.012) emerged as prospective risk contributors for EC. To assess reverse causal effect, we used EC as the exposure and the gut microbiota as the outcome, and this analysis revealed associations between EC and seven different types of gut microbiota. The robustness of the MR findings was substantiated through comprehensive heterogeneity and pleiotropy evaluations. This research identified certain microbial taxa as either protective or detrimental elements for EC, potentially offering valuable biomarkers for asymptomatic diagnosis and prospective therapeutic interventions for EC.

Interactive data sharing for multiple questionnaire-based exposome-wide association studies and exposome correlations in the Personalized Environment and Genes Study.

The correlations among individual exposures in the exposome, which refers to all exposures an individual encounters throughout life, are important for understanding the landscape of how exposures co-occur, and how this impacts health and disease. Exposome-wide association studies (ExWAS), which are analogous to genome-wide association studies (GWAS), are increasingly being used to elucidate links between the exposome and disease. Despite increased interest in the exposome, tools and publications that characterize exposure correlations and their relationships with human disease are limited, and there is a lack of data and results sharing in resources like the GWAS catalog. To address these gaps, we developed the PEGS Explorer web application to explore exposure correlations in data from the diverse North Carolina-based Personalized Environment and Genes Study (PEGS) that were rigorously calculated to account for differing data types and previously published results from ExWAS. Through globe visualizations, PEGS Explorer allows users to explore correlations between exposures found to be associated with complex diseases. The exposome data used for analysis includes not only standard environmental exposures such as point source pollution and ozone levels but also exposures from diet, medication, lifestyle factors, stress, and occupation. The web application addresses the lack of accessible data and results sharing, a major challenge in the field, and enables users to put results in context, generate hypotheses, and, importantly, replicate findings in other cohorts. PEGS Explorer will be updated with additional results as they become available, ensuring it is an up-to-date resource in exposome science.

Protein–protein interaction network-based integration of GWAS and functional data for blood pressure regulation analysis

BackgroundIt is valuable to analyze the genome-wide association studies (GWAS) data for a complex disease phenotype in the context of the protein–protein interaction (PPI) network, as the related pathophysiology results from the function of interacting polyprotein pathways. The analysis may include the design and curation of a phenotype-specific GWAS meta-database incorporating genotypic and eQTL data linking to PPI and other biological datasets, and the development of systematic workflows for PPI network-based data integration toward protein and pathway prioritization. Here, we pursued this analysis for blood pressure (BP) regulation.MethodsThe relational scheme of the implemented in Microsoft SQL Server BP-GWAS meta-database enabled the combined storage of: GWAS data and attributes mined from GWAS Catalog and the literature, Ensembl-defined SNP-transcript associations, and GTEx eQTL data. The BP-protein interactome was reconstructed from the PICKLE PPI meta-database, extending the GWAS-deduced network with the shortest paths connecting all GWAS-proteins into one component. The shortest-path intermediates were considered as BP-related. For protein prioritization, we combined a new integrated GWAS-based scoring scheme with two network-based criteria: one considering the protein role in the reconstructed by shortest-path (RbSP) interactome and one novel promoting the common neighbors of GWAS-prioritized proteins. Prioritized proteins were ranked by the number of satisfied criteria.ResultsThe meta-database includes 6687 variants linked with 1167 BP-associated protein-coding genes. The GWAS-deduced PPI network includes 1065 proteins, with 672 forming a connected component. The RbSP interactome contains 1443 additional, network-deduced proteins and indicated that essentially all BP-GWAS proteins are at most second neighbors. The prioritized BP-protein set was derived from the union of the most BP-significant by any of the GWAS-based or the network-based criteria. It included 335 proteins, with ~ 2/3 deduced from the BP PPI network extension and 126 prioritized by at least two criteria. ESR1 was the only protein satisfying all three criteria, followed in the top-10 by INSR, PTN11, CDK6, CSK, NOS3, SH2B3, ATP2B1, FES and FINC, satisfying two. Pathway analysis of the RbSP interactome revealed numerous bioprocesses, which are indeed functionally supported as BP-associated, extending our understanding about BP regulation.ConclusionsThe implemented workflow could be used for other multifactorial diseases.

The causal effect of triglyceride and high blood pressure on IgA nephropathy: a Mendelian randomization study.

It has been reported that high blood pressure (HBP) and triglyceride (TG) are considered risk factors in immunoglobulin A nephropathy (IgAN). This study aimed to explore the causalities between HBP and TG, and IgAN on the basis of Mendelian randomization (MR) analysis. Firstly, the genome-wide association study (GWAS) summary data of IgAN (GCST90018866) and two exposure factors, TG (ukb-d-30870_raw) and HBP (ukb-a-437), were sourced from the GWAS Catalog and Integrative Epidemiology Unit (IEU) OpenGWAS databases, respectively. In this study, five methods were utilized to perform MR analysis after picking out single nucleotide polymorphisms (SNPs) as instrumental variables, including MR-Egger, weighted median, simple mode, weighted mode, and inverse variance weighted (IVW), followed by the sensitivity analysis containing the heterogeneity, horizontal pleiotropy test and leave-one-out (LOO) analysis. Finally, the enrichment analysis and interaction network construction of genes corresponding to SNPs of HBP and TG were performed. The univariate MR results revealed that HBP and TG regarded as risk factors were causally related to IgAN [TG: p = 0.046, odds ratio (OR) = 1.065, 95% confidence interval (CI) = 1.001-1.133; HBP: p = 7.09 × 10-7, OR = 1.970, 95% CI = 1.507-2.575] based on random-effect IVM method, of which TG had a weaker impact. The reliability of these univariate MR results was certified by the sensitivity analysis, in which there was no horizontal pleiotropy and exaggerated influence of each SNP. Furthermore, HBP was markedly causally related to IgAN (p = 0.000512) with the help of multivariate MR analysis, rather than TG (p = 0.332). Therefore, when HBP and TG occur simultaneously, HBP is a direct influencing factor on IgAN. Ultimately, a total of 208 and 153 genes separately corresponding to SNPs of TG and HBP were included in enrichment analysis, and thereinto, genes relevant to TG were mainly enriched in lipid homeostasis and cholesterol metabolism, while genes concerned with HBP played their roles in regulation of cell growth, aldosterone synthesis and secretion and so forth. TG and HBP as risk factors were causally connected with IgAN, of which HBP was strongly related to the onset of IgAN, providing more reliable evidence for further exploring the relationship between TG and HBP and IgAN.

Inflammatory cytokines and oral lichen planus: a Mendelian randomization study.

Inflammatory cytokines have long been considered closely related to the development of oral lichen planus (OLP), and we further explored the causal relationship between the two by Mendelian randomization (MR) method. We performed bidirectional MR analyses by large genome-wide association studies (GWAS). The data included a large-scale OLP dataset, as well as datasets of 41 inflammatory cytokines. All data were obtained from the University of Bristol database, which includes 41 inflammatory cytokines, and the GWAS Catalog database, which includes 91 inflammatory cytokines. OLP data were obtained from the Finngen database, which includes 6411 cases and 405770 healthy controls. We used the inverse variance weighted (IVW) method, MR-Egger method, weighted median method, simple mode method and weighted mode method to analyze the causal relationship between inflammatory cytokines and OLP, and we also combined with sensitivity analysis to further verify the robustness of the results. We performed a meta-analysis of positive or potentially positive results for the same genes to confirm the reliability of the final results. We primarily used the IVW analysis method, corrected using the Benjamin Hochberg (BH) method. When p<0.00038 (0.05/132), the results are significantly causal; when 0.00038<p<0.05, the results are potentially causal. We found a total of 7 inflammatory cytokines with significant or potential associations with OLP (University of Bristol database: 2, GWAS Catalog database: 5). In the reverse analysis, we found that a total of 30 inflammatory cytokines were significantly or potentially associated with OLP (University of Bristol database: 5, GWAS Catalog database: 25). After sensitivity analysis and meta-analysis, we finally determined that there was a causal relationship between a total of 3 inflammatory cytokines and OLP in the forward analysis, the most significant of which was FGF21 (p=0.02954, odds ratio (OR): 1.113, 95% confidence interval (95%CI): 1.011-1.226). In the reverse analysis, 14 inflammatory cytokines were causally associated with OLP, the most significant of which was PLAU (p=0.00002, OR: 0.951, 95%CI: 0.930-0.973). There is a causal association between OLP and some inflammatory cytokines, which may play an important role in the pathogenesis of OLP and require further attention.

Mendelian Randomization Highlights Gut Microbiota of Short-chain Fatty Acids' Producer as Protective Factor of Cerebrovascular Disease.

Recent research advancements have indicated a potential association between gut microbiota and cerebrovascular diseases, although the precise causative pathways and the directionality of this association remain to be fully elucidated. This study utilized a bidirectional two-sample Mendelian Randomization (MR) methodology to explore the causal impact of gut microbiota compositions on the risk of cerebrovascular disease. Genome-wide Association Study (GWAS) data pertaining to gut microbiota were obtained from the MiBioGen consortium. For Ischemic Stroke (IS), Transient Ischemic Attack (TIA), Vascular Dementia (VD), and Subarachnoid Hemorrhage (SAH), GWAS summary data were sourced from the FinnGen consortium, the IEU Open GWAS project, and the GWAS catalog, respectively. Our MR analyses identified that specific bacterial strains, notably those involved in the production of Short-chain Fatty Acids (SCFAs), including Barnesiella, Ruminococcus torques group, and Coprobacter, serve as protective factors against IS, TIA, and SAH. Linkage Disequilibrium Score Regression (LDSC) analysis corroborated a significant genetic correlation between these gut microbiota strains and various forms of cerebrovascular disease. In contrast, reverse MR analysis failed to establish a bidirectional causal relationship between genetically inferred gut microbiota profiles and these cerebrovascular conditions. This investigation has pinpointed particular strains of gut microbiota that play protective or detrimental roles in cerebrovascular disease pathogenesis. These findings offer valuable insights that could be pivotal for the clinical management, prevention, and treatment of cerebrovascular diseases.