GWAS summary statistics

This study identifies genetic and proteomic factors influencing pediatric stature across life stages and links them to adult height and type 2 diabetes risk.

GiMat identifies gene-gene interactions across multiple dichotomous phenotypes using a statistical framework, finding four novel interaction pairs in type 2 diabetes and hypertension comorbidity.

This paper identifies drug repurposing candidates for chronic pain using genetics and transcriptomics, finding drugs with opposing gene expression effects to the disease.

GWAS SVatalog identifies structural variations linked to GWAS loci by visualizing LD between SVs and SNPs across 14,479 phenotypes.

This study identifies two genome-wide significant genetic associations with EGPA, one in SSH2 and one in RUNX1, and shows colocalization with molecular traits related to IL5RA and LYN.

The paper benchmarks four colocalization methods using protein QTL data to assess their reliability and consistency in detecting shared genetic causes.

FINEMAP-miss improves fine-mapping in GWAS meta-analyses by addressing variant-specific missingness, outperforming standard methods in low imputation information and complex settings.

This study shows that biased kinship estimation in structured populations leads to heritability estimation bias, with Popkin being the only unbiased estimator.

FlexRV improves gene discovery for complex traits by modeling nonlinear relationships between variant annotations and phenotypes, outperforming existing methods in association detection and replication.

This study links COVID-19 outcomes to brain structure and function through genetic correlations and identifies potential drug targets.

PRISM-ML integrates multi-omics and EHR data to identify drug repurposing opportunities in Alzheimer's disease by analyzing molecular heterogeneity and predicting therapeutic targets.

This study examines how genetic variants linked to gestational diabetes affect maternal glucose levels during and after pregnancy, finding consistent associations with fasting glucose but varying effects on postprandial glucose.

This paper introduces Bayesian fine-mapping methods adapted for related individuals, showing improved accuracy in pig data compared to existing tools.

This paper constructs a genomic-informed dementia risk score combining genetic and clinical factors and finds that most memory clinic patients have at least one high-risk indicator, with higher burden linked to increased dementia risk.

This paper highlights how confounding factors lead to misinterpretation in genetic studies of human behavior and socioeconomic outcomes by reanalyzing two examples.

This study uses Mendelian randomization to show that higher glycemic traits are inversely associated with thoracic aortic diameters and reduced risk of aneurysm and dissection.

This study identifies population-specific genetic strategies for agronomic traits in Coffea canephora using genomic analysis and machine learning, revealing distinct biological pathways in two populations.

This study shows that using different GWAS summary statistics in MR analyses of myopia can lead to inconsistent and misleading results.

The paper links GWAS-associated haplotype blocks to lncRNAs and their mammalian orthologs, showing strong functional associations with complex traits.

This study identifies novel genetic risk loci and potential drugs for heart failure using multi-trait genome-wide analysis of GWAS data.

This paper introduces a spherical-harmonics regression method for PheWAS to detect localized genetic effects and summarize spatial complexity using rotation-invariant descriptors.

The paper identifies a 5-SNP block in the ARMS2 promoter that binds c-ABL and is associated with AMD, showing reduced transcriptional activity in reporter assays.

This study investigates the impact of Indigenous American-like ancestry on acute lymphoblastic leukemia risk in Hispanic/Latino children, finding no global association but significant local haplotype effects.

CONSILIENCE-GWAS integrates functional genomics data with human GWAS to analyze heritability and polygenic scores across species.

The paper benchmarks genomic, phenomic, and metabolomic prediction models for agronomic traits in grapevine breeding populations, finding genomic prediction most accurate and metabolomic intermediate.

This study examines genotype-treatment interactions in endocrine therapy for breast cancer using UK Biobank data and finds no significant associations between genomic variants and adverse drug effects.

The paper introduces a machine-learning framework to model disease effect sizes from GWAS data, identifying constrained regulatory variants as key functional components and improving variant prioritization.

This study identifies 77 genetic loci associated with suicidality through genome-wide association analyses across multiple cohorts and provides biological insights into its genetic architecture.

This study finds that clonal hematopoiesis (CHIP) increases stroke risk across multiple cohorts, with specific gene mutations and inflammatory markers like IL-1RAP modifying this risk.

This paper presents an analytical solution for estimating SNP-heritability in biobank-scale and distributed datasets, achieving high precision and efficiency.