Genetic Associations and Epidemiology

This paper introduces EPIK, a deep learning framework for detecting higher-order epistasis in GWAS data, showing improved performance on simulated and real datasets and identifying new gene interactions in Parkinson's Disease.

This study benchmarks the impact of non-additive genetic effects on polygenic prediction and machine learning approaches using simulated and real data.

The paper introduces scJLIM, a cluster-free method for single-cell colocalization testing, improving power to link GWAS loci with gene expression changes in specific cell types.

This study investigates causal links between T2D genetic clusters and non-cardiovascular comorbidities, identifying potential drug repurposing opportunities.

The paper identifies causal protein drivers and drug targets for heterogeneous kidney diseases using proteome-wide Mendelian randomization and EHR data.

The paper identifies spurious trans-QTLs caused by read mismapping from segmental duplications and estimates their prevalence in GTEx data.

The paper quantifies genetic influences across educational milestones in two Norwegian cohorts, finding stage-specific heritability and declining genetic overlap with later degrees.

The paper identifies genetic variants near SLC2A2 that influence glycemic response to glimepiride in type 2 diabetes patients.

distQTL identifies distribution QTLs using population-scale single-cell RNA sequencing data, outperforming traditional methods in capturing transcriptional regulatory heterogeneity.

This paper introduces FLEX, a method for estimating gene-level heritability from whole-exome sequencing data, showing rare coding variants contribute significantly to complex trait heritability.

The paper integrates proteomics data from Olink and SomaScan to identify pQTLs and develop a resource for transcriptome and proteome-wide association studies, with applications to inflammatory bowel disease.

KinformR provides scoring metrics to evaluate pedigrees and prioritize variants in family-based genetic studies, improving efficiency and accuracy in identifying disease-associated rare variants.

This study identifies twelve novel blood pressure loci and shows smoking modifies genetic effects on BP through immune-related pathways in over 1 million individuals.

This paper examines how genetic interactions with ancestry affect polygenic scores and shows that models of local and global ancestry interactions can be distinguished using partial polygenic scores when causal variants are known.

The paper introduces SECRET, a method to develop polygenic scores for traits with limited data, showing improved prediction power over existing methods.

This paper introduces a formal statistical replication analysis to reduce false positives in lung cancer GWAS, finding it significantly lowers false discovery rate and improves polygenic risk score efficiency.

The paper identifies USP18 as a negative regulator of interferon response at a lupus risk locus through trans-eQTL analysis in lymphoblastoid cell lines.

This study develops and evaluates HLA-ARC, a polygenic risk score for type 1 diabetes, showing improved performance over existing methods in diverse ancestry groups.

This study identifies 42 genetic loci associated with cardiac structure and contractility using a spatially-resolved genome-wide association study in 47,549 UK Biobank participants.

The paper introduces a robust mixed model association test (RoM) for gene-environment interactions in related samples, showing improved type I error control compared to existing methods.

The paper introduces gact, an R package that integrates GWAS summary statistics with genomic resources to identify causal genes and pathways, demonstrating its application in coronary artery disease and type 2 diabetes.

The paper identifies positive selection at the Neanderthal introgressed 3p21.31 locus in East Asians, linked to LZTFL1-driven ciliary changes that may influence COVID-19 severity.

This study identifies a genome-wide significant variant associated with sepsis-associated ARDS risk, linking cholesterol metabolism to ARDS susceptibility.

This paper uses haplotype components to improve GWAS by addressing population stratification, identifying more significant associations for birthplace and lifestyle traits.

The paper compares genetic effects on disease susceptibility and progression, finding limited overlap and suggesting larger samples or different progression measures are needed.

The paper uses sex-stratified analyses to explore genetic architecture of complex traits in mice and humans, finding high concordance in allelic effect directions and suggesting new methods for identifying biologically significant associations.

SAFE-LD estimates linkage disequilibrium from GWAS summary statistics using pseudo-genotypes that preserve in-sample LD while protecting privacy.

This study performs a genome-wide association study of chronic pain across six ancestries, identifying two significant loci and showing genetic correlations with mental and physical health traits.

This paper introduces RoP, a method to analyze phase effects in genetic association studies using long-read sequencing data, showing improved detection of cis and trans effects in cystic fibrosis loci.