GWAS summary statistics

The paper applies a variational autoencoder to multi-omics data from the UK Biobank to assess disease risk prediction and the impact of preprocessing on model performance.

This paper develops ancestry-specific and combined HLA-focused genetic risk scores for type 1 diabetes and evaluates their performance across diverse populations.

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.

GRPa-PRS identifies genetically-regulated pathways in polygenic diseases by stratifying individuals based on PRS and analyzing differential gene expression across risk strata.

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.

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

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.

This study investigates the genetic associations of early pregnancy C-reactive protein (CRP) levels with gestational diabetes mellitus (GDM) using maternal and offspring genome-wide association studies (GWAS).

The paper evaluates polygenic risk scores for Parkinson's disease in a South African cohort, finding modest predictive performance and no ancestry-specific risk variants.

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.

The paper examines linkage disequilibrium patterns in chicken QTLRs for Mareks Disease, finding chaotic LD structures that challenge GWAS interpretation.

MACHINE improves multi-ancestry fine-mapping by using a continuous prior and FDR control, identifying new causal variants in lipid traits and schizophrenia.

The paper introduces the BPC approach to improve polygenic score calibration for binary disorders, achieving better calibration than existing methods in simulated and empirical data.

This study identifies 52 genetic variants associated with adolescent-onset depression through a large GWAS, revealing age-specific mechanisms and potential drug targets.

The paper explores challenges in Mendelian randomisation with proxy exposures, demonstrating how variant effects on downstream metabolites can infer causal roles in biological processes.

This study identifies genetic variants associated with REM sleep behavior disorder in Parkinson's disease and explores genetic correlations with neuropsychiatric traits.

This study identifies 107 genetic loci associated with serum creatine kinase levels across diverse populations, highlighting genes involved in muscle structure and function.

The paper estimates genetic assortative mating using haplotype reconstruction in large biobank cohorts, revealing recent trends in mate choice and its genetic impact.

This paper introduces CATMINT, a method to estimate gene-level intolerance across variant categories, showing it outperforms existing metrics and reveals category-specific intolerance patterns in disease genes.

The paper develops and validates a 30K SNP genotyping tool for flax breeding, showing high polymorphism and genotyping accuracy.

PTL-PRS improves polygenic risk score prediction in non-European populations using pseudovalidation and software optimizations without requiring individual-level data.

This study identifies genetic risk factors for meniscus degeneration and shows they are linked to various systemic conditions through a phenome-wide association study.

This study benchmarks GWAS causal gene prioritization methods for drug discovery using 445 diseases, finding the nearest gene method performs as well as more complex approaches.

This paper introduces ELAG, an ensemble learning framework for polygenic risk prediction that improves accuracy in high-dimensional genomics data by using policy gradient methods to guide variant selection.

This study identifies OA-specific genetic effects and novel therapeutic targets by separating OA genetics from those shared with obesity using GWAS and proteomics data.

This study uses multivariate GWAS to identify shared genetic factors and pleiotropic loci across multiple carcinoma types, revealing general and cancer-specific genetic liabilities.

This study identifies two genome-wide significant loci associated with hypermobile Ehlers-Danlos syndrome, implicating neuroimmune and pain signaling pathways and highlighting genetic correlations with multiple comorbid conditions.