GWAS / association mapping

MultiSuSiE improves multi-ancestry fine-mapping in All of Us whole-genome sequencing data by allowing causal effect sizes to vary across ancestries, achieving higher power and lower computational costs.

The paper examines genetic diversity and structure within the Olotillo maize race in Mexico, finding that genetic clusters align with geographic origin rather than race identity, and highlights inbreeding and directional selection across scales.

The paper investigates the association between DNAJC13 variants and Parkinson's disease across diverse ancestries but finds no significant association.

This study conducts a GWAS and cross-ethnic meta-analysis of schizophrenia phenotypes in Hong Kong Chinese and European populations, identifying genetic variants and building predictive models for clinical outcomes.

This study identifies a shared genetic factor underlying brain age gaps across 30 cohorts, finding 19 SNPs and associations with health traits.

This study conducts the first XWAS in an African cohort, identifying X chromosome variants associated with Parkinson's disease susceptibility in males and females.

This study identifies a CRIP3 non-synonymous variant associated with age-related hearing loss and provides genetic, functional, and evolutionary evidence for its role in auditory function.

This study identifies 48 genetic loci and 66 fine-mapped signals associated with mono- and polyneuropathies using GWAS and meta-analysis across 983,477 individuals.

This study conducts a GWAS on Pick's disease and identifies two SNPs associated with risk, though not at genome-wide significance, suggesting potential genetic factors beyond MAPT mutations.

This study uses genetic data to show that HMGCR inhibition affects coronary artery disease and type 2 diabetes through different causal pathways, with BMI and LDL-C playing distinct roles.

The paper identifies rare protein-coding variants associated with multi-organ MRI traits using exome-wide association analysis in the UK Biobank.

The paper introduces GPSEA, a tool using GA4GH Phenopackets to analyze genotype-phenotype correlations in Mendelian disorders, identifying 225 significant associations across 85 cohorts.

The paper develops longitudinal models to identify non-additive genetic effects on developmental plasticity, finding 76 novel loci involved in regulatory interactions.

The paper examines the association between polygenic risk scores, structural brain measurements, and obsessive-compulsive symptoms in adolescents with various psychiatric diagnoses.

This study uses cross-tissue transcriptome-wide association study (TWAS) to identify genetically regulated genes associated with hepatocellular carcinoma and prioritize druggable targets.

This study examines polygenic scores for schizophrenia and major depression in Chinese adults, finding associations with various traits and highlighting ancestry-specific genetic correlations.

The paper introduces the RUMIGEN EpiChip, a DNA methylation array for cattle, demonstrating its utility in studying phenotypic variation and age prediction through methylation analysis.

This study identifies cancer risk loci and genetic architectures in African-ancestry populations using GWAS and PRS, highlighting disparities in predictive performance across cancers.

This study estimates the false sign rate in transcriptome-wide association studies (TWAS) for plasma proteins and complex traits, finding high discordance between predicted and expected gene effects.

This study identifies genetic variants associated with longevity in a Calabrian cohort, finding one genome-wide significant variant and highlighting pathways related to aging.

This paper develops a federated framework for GWAS using mixed-effects models to enable privacy-preserving analysis across distributed datasets while maintaining statistical accuracy.

This study integrates brain structure and function to identify genetic loci associated with language-related brain components using UK Biobank data.

MOKA integrates multi-omics data into GWAS using a kernel association test pipeline, identifying 89 significant genes in schizophrenia with 15.7% validation in DisGeNET.

JointMR integrates GWAS summary databases to estimate causal effects, providing unbiased and reliable results with higher power and better Type I error control than traditional methods.

This study identifies 79 QTLs for morphological and phytochemical traits in cowpea using 45 F2 mapping populations, highlighting chromosome 4 as a key region for seed-related traits and chromosome 1 for amino acids and phenolic acids.

The paper identifies host genetic effects on microbiome composition in rats and finds evidence of indirect genetic effects contributing to missing heritability.

The paper uses genetically imputed brain imaging phenotypes to find associations with psychiatric traits in a multi-ancestry cohort.

This paper evaluates age-varying genetic effects on BMI and blood pressure traits using UK Biobank data, finding trait-dependent interactions that influence cardiovascular outcomes.

This study identifies a genetic association between thromboembolism risk and long COVID in individuals of European ancestry, suggesting thromboembolism as a potential contributor to long COVID pathogenesis.