Generalized multi-SNP mediation intersection-union test

Bile acid metabolism modulates intestinal immunity involved in ulcerative colitis progression

The bile acids (BA) in the intestine promote inflammation by interacting with immune cells, playing a crucial role in the progression of UC, but the specific mechanism between the two remains elusive. This study aims to explore the relationship between BAMand UC inflammation and determine its potential mechanisms.Firstly, we employed a hybrid approach using Lasso regression and support vector machine (SVM) feature selection in bioinformatics to identify genes linked to UC and BAM. The relationship between these genes and immune infiltration was explored, along with their correlation with immune factors in the Tumor-Immune System Interaction Database (TISIDB) database. Gene Set Enrichment Analysis (GSEA) pathway enrichment analysis was then used to predict signaling pathways associated with key genes in UC. Single-cell data from the GSE13464 dataset was also analyzed. Finally, Five differentially expressed genes (DEGs) related to BAM (APOA1, AMACR, PEX19, CH25H, and AQP9) were significantly upregulated/downregulated in UC immune cells. The expression of important genes in UC tissue was confirmed in the experimental validation section and AQP9, which showed significant differential expression, was chosen for further validation. The results showed that the AQP9 gene may regulate the IFN - γ/JAK signaling axis, thereby promoting CD8+T cell activation. This research has greatly advanced our comprehension of the pathogenesis and underlying mechanism of BAM in immune cells linked to UC.

Understanding the function of regulatory DNA interactions in the interpretation of non-coding GWAS variants

Genome-wide association studies (GWAS) have identified a vast number of variants associated with various complex human diseases and traits. However, most of these GWAS variants reside in non-coding regions producing no proteins, making the interpretation of these variants a daunting challenge. Prior evidence indicates that a subset of non-coding variants detected within or near cis-regulatory elements (e.g., promoters, enhancers, silencers, and insulators) might play a key role in disease etiology by regulating gene expression. Advanced sequencing- and imaging-based technologies, together with powerful computational methods, enabling comprehensive characterization of regulatory DNA interactions, have substantially improved our understanding of the three-dimensional (3D) genome architecture. Recent literature witnesses plenty of examples where using chromosome conformation capture (3C)-based technologies successfully links non-coding variants to their target genes and prioritizes relevant tissues or cell types. These examples illustrate the critical capability of 3D genome organization in annotating non-coding GWAS variants. This review discusses how 3D genome organization information contributes to elucidating the potential roles of non-coding GWAS variants in disease etiology.

GMEPS: a fast and efficient likelihood approach for genome-wide mediation analysis under extreme phenotype sequencing

Due to many advantages such as higher statistical power of detecting the association of genetic variants in human disorders and cost saving, extreme phenotype sequencing (EPS) is a rapidly emerging study design in epidemiological and clinical studies investigating how genetic variations associate with complex phenotypes. However, the investigation of the mediation effect of genetic variants on phenotypes is strictly restrictive under the EPS design because existing methods cannot well accommodate the non-random extreme tails sampling process incurred by the EPS design. In this paper, we propose a likelihood approach for testing the mediation effect of genetic variants through continuous and binary mediators on a continuous phenotype under the EPS design (GMEPS). Besides implementing in EPS design, it can also be utilized as a general mediation analysis procedure. Extensive simulations and two real data applications of a genome-wide association study of benign ethnic neutropenia under EPS design and a candidate-gene study of neurocognitive performance in patients with sickle cell disease under random sampling design demonstrate the superiority of GMEPS under the EPS design over widely used mediation analysis procedures, while demonstrating compatible capabilities under the general random sampling framework.

Identifying pleiotropic genes for complex phenotypes with summary statistics from a perspective of composite null hypothesis testing

Pleiotropy has important implication on genetic connection among complex phenotypes and facilitates our understanding of disease etiology. Genome-wide association studies provide an unprecedented opportunity to detect pleiotropic associations; however, efficient pleiotropy test methods are still lacking. We here consider pleiotropy identification from a methodological perspective of high-dimensional composite null hypothesis and propose a powerful gene-based method called MAIUP. MAIUP is constructed based on the traditional intersection-union test with two sets of independent P-values as input and follows a novel idea that was originally proposed under the high-dimensional mediation analysis framework. The key improvement of MAIUP is that it takes the composite null nature of pleiotropy test into account by fitting a three-component mixture null distribution, which can ultimately generate well-calibrated P-values for effective control of family-wise error rate and false discover rate. Another attractive advantage of MAIUP is its ability to effectively address the issue of overlapping subjects commonly encountered in association studies. Simulation studies demonstrate that compared with other methods, only MAIUP can maintain correct type I error control and has higher power across a wide range of scenarios. We apply MAIUP to detect shared associated genes among 14 psychiatric disorders with summary statistics and discover many new pleiotropic genes that are otherwise not identified if failing to account for the issue of composite null hypothesis testing. Functional and enrichment analyses offer additional evidence supporting the validity of these identified pleiotropic genes associated with psychiatric disorders. Overall, MAIUP represents an efficient method for pleiotropy identification.

Host Genetic Risk Factors for Chlamydia trachomatis-Related Infertility in Women

BACKGROUND

Chlamydia trachomatis (Ct) infection ascending to the upper genital tract can cause infertility. Direct association of genetic variants as contributors is challenging because infertility may not be diagnosed until years after infection. Investigating the intermediate trait of ascension bridges this gap.

METHODS

We identified infertility genome-wide association study (GWAS) loci using deoxyribonucleic acid from Ct-seropositive cisgender women in a tubal factor infertility study and Ct-infected cisgender women from a longitudinal pelvic inflammatory disease cohort with known fertility status. Deoxyribonucleic acid and blood messenger ribonucleic acid from 2 additional female cohorts with active Ct infection and known endometrial infection status were used to investigate the impact of infertility single-nucleotide polymorphisms (SNPs) on Ct ascension. A statistical mediation test examined whether multiple infertility SNPs jointly influenced ascension risk by modulating expression of mediator genes.

RESULTS

We identified 112 candidate infertility GWAS loci, and 31 associated with Ct ascension. The SNPs altered chlamydial ascension by modulating expression of 40 mediator genes. Mediator genes identified are involved in innate immune responses including type I interferon production, T-cell function, fibrosis, female reproductive tract health, and protein synthesis and degradation.

CONCLUSIONS

We identified Ct-related infertility loci and their potential functional effects on Ct ascension.