Genetic Associations and Epidemiology

SegmentQTL improves molQTL analysis in copy number-driven cancers by incorporating breakpoint information to reduce false discoveries and refine associations.

The paper introduces an IBD mapping method with multiple testing adjustment to associate genome-wide loci with complex traits, showing improved power for rare variants.

The paper shows that high genotype missingness, especially for small-effect variants, hinders accurate risk prediction for complex diseases and identifies patterns in missing data across multiple diseases.

The paper models shared genomic and environmental influences on cognitive, language, and social traits in children, identifying distinct domains with trait-specific correlations between genetic and environmental factors.

The paper introduces a method to predict the direction of phenotypic differences between individuals using genomic data, achieving over 90% accuracy in many cases.

This study identifies genetic correlations and pleiotropic loci between atopic dermatitis and five neuropsychiatric disorders, highlighting shared inflammatory pathways and potential drug targets.

This study uses sex-stratified GWAS and explainable AI to identify 184 genes associated with T2D subtypes and improve risk detection.

This study investigates genetic predictors of inpatient opioid exposure after knee or hip surgery using EHR and genotype data from 27,896 individuals across three ancestries, finding no genome-wide significant loci.

This study identifies synergistic sets of genetic risk variants in psychiatric disorders, suggesting subtypes and reinterpreting shared genetic effects.

This study identifies genetic links between clusters of immune-mediated diseases and psychiatric disorders using genomic structural equation modeling and a new heterogeneity metric.

This paper introduces PRSFNN, a neural empirical Bayesian method for polygenic prediction that outperforms existing methods on 17 of 18 traits in the UK Biobank.

The paper demonstrates how quantile regression can correct for subtle population stratification in genome-wide association studies using human height as an example.

This study identifies 93 genetic loci associated with alcohol-related diseases using FinnGen data and shows polygenic risk scores can stratify risk for these diseases and related outcomes.

The paper investigates the genetic overlap between educational attainment and substance use traits, finding distinct genetic patterns for cognitive and non-cognitive components of education.

This study compares imputation accuracy and polygenic score performance between genotyping arrays and low coverage whole-genome sequencing across diverse populations, finding that low coverage sequencing performs competitively and better in underrepresented groups.

This study evaluates polygenic score methods across diverse populations using summary statistics, finding that combining ancestry-aligned and European GWAS improves performance and computational efficiency.

The paper introduces quasar, a software for eQTL mapping that offers faster performance and better statistical models compared to existing methods.

ClipperQTL identifies eGenes efficiently by reducing permutations needed for large datasets while maintaining performance comparable to FastQTL.

This paper identifies and prioritizes drug targets for major depressive disorder using genetic methods, finding that 82% of approved depression/anxiety drugs have significant genetic targets.

This paper identifies how outcome scaling and endogenous treatment effects create spurious gene-environment interactions and proposes a diagnostic to detect these artifacts.

This study uses haplotype analysis to identify disease associations in the HLA region across 412,181 Finnish individuals, revealing pleiotropic patterns and 7,649 associations across 647 traits.

This study uses Mendelian randomization to show that genetically predicted longer telomere length causally extends healthspan, but epigenetic age acceleration biomarkers do not.

This paper introduces MRBEE-TL, a multi-ancestry MVMR method using transfer learning to improve causal effect estimation in underpowered ancestries and assess cross-ancestry heterogeneity.

The paper compares GWAS methods in admixed populations, showing standard tests are more powerful due to allele frequency heterogeneity and identifying distinct LD patterns in admixed vs. single-continental segments of the same ancestry.

The paper evaluates proteomic and polygenic risk scores for disease prediction, finding proteomic scores outperform polygenic scores in most traits and show temporal responsiveness.

This study conducts a genome-wide association analysis of generalised anxiety symptom severity, identifying 80 significant variants and showing genetic correlations with other mental and physical health traits.

Sniff improves causal variant prioritization in GWAS by integrating Borzoi-predicted variant effects with functional annotations, identifying more fine-mapped variants with higher posterior inclusion probabilities.

This study identifies novel protective genetic variants associated with TMT-B performance using a family-based GWLS approach in the Long Life Family Study.

This study links genetic liability to psychiatric disorders with quality of life outcomes in children and adults, finding ADHD and MDD PGSs significantly associated with lower quality of life factors.

This study estimates direct and indirect genetic effects on pediatric anthropometric traits in a Dutch cohort, finding significant direct effects but limited indirect genetic nurture influence.