polygenic risk

Multi-ancestry polygenic risk scores using phylogenetic regularization

This paper introduces DendroPRS, a machine learning method that improves genotype-to-phenotype prediction across diverse ancestries by incorporating phylogenetic relationships.

Differences in polygenic score distributions in European ancestry populations: implications for breast cancer risk prediction

This study examines differences in polygenic risk score distributions across European populations and shows how country-specific calibration can improve breast cancer risk prediction.

Insights from Genetic Studies: SNP Analyses Confirm White Clover Naturalization in Brazil

This study uses SNP analysis to show that white clover populations in Brazil have high within-population genetic diversity, with some populations showing admixture with cultivars and others having distinct genetic backgrounds, confirming its naturalization.

An expression-directed linear mixed model (edLMM) discovering low-effect genetic variants

This paper introduces edLMM, a method that detects low-effect genetic variants using moderate sample sizes, improving missing heritability estimation.

The predictive capacity of polygenic risk scores for disease risk is only moderately influenced by imputation panels tailored to the target population

This study evaluates how imputation panels affect polygenic risk score accuracy across different ethnic populations, finding only marginal improvements when panels match the target population.

GWAS of ~30,000 samples with bone mineral density at multiple skeletal sites and its clinical relevance on fracture prediction, genetic correlations and prioritization of drug targets

This study performs GWAS on BMD traits and fracture risk using 30,000 UK Biobank samples, identifies novel loci, and prioritizes drug targets for osteoporosis prevention.

Concordance of whole-genome amplified embryonic DNA with the subsequently born child

This study demonstrates high concordance between whole-genome amplified embryonic DNA and the genome of the subsequently born child, validating PGT-WGS for detecting genetic variants and polygenic risk scores.

PRS-Net: Interpretable polygenic risk scores via geometric learning

PRS-Net improves disease prediction by modeling genetic nonlinearity using deep learning and identifies key genes and interactions influencing Alzheimer's and multiple sclerosis risk.

Genome-wide analyses of vocabulary size in infancy and toddlerhood: associations with Attention-Deficit/Hyperactivity Disorder and cognition-related traits

This study identifies genetic links between early vocabulary development and ADHD and cognition traits using genome-wide analyses.

Improving fine-mapping by modeling infinitesimal effects

This paper introduces improved fine-mapping methods that model infinitesimal effects, showing better calibration and increased PRS accuracy for causal variant identification in complex traits.

Cohort Profile: Genetic data in the German Socio-Economic Panel Innovation Sample (Gene-SOEP)

The paper describes the Gene-SOEP dataset, a longitudinal genetic study of 2,598 individuals in Germany, providing polygenic indices for research on genetic-environment interactions.

Dual-systems models of the genetic architecture of impulsive personality traits: Neurogenetic evidence of distinct but related factors

The paper evaluates dual-systems models of impulsive personality traits using genomic structural equation modeling and genetic correlations with neuroimaging phenotypes, finding shared and unique genetic influences.

Transfer Learning with False Negative Control Improves Polygenic Risk Prediction

This paper introduces a transfer learning framework with false negative control to improve polygenic risk prediction across heterogeneous datasets.

Analysis of associations between polygenic risk score and COVID-19 severity in a Russian population using low-pass genome sequencing

This study uses a polygenic risk score derived from genome-wide data to identify individuals at higher risk of severe COVID-19 in a Russian population.

Inferring disease architecture and predictive ability with LDpred2-auto

This paper validates LDpred2-auto for inferring genetic parameters and shows improved heritability capture and predictive performance with an expanded variant set.

Genetic basis of Arabidopsis thaliana responses to infection by naive and adapted isolates of turnip mosaic virus

The paper identifies a genetic region associated with systemic necrosis in Arabidopsis thaliana infected with turnip mosaic virus, showing a trade-off between resistance and fitness costs.

Genome-wide Association Identifies Novel Etiological Insights Associated with Parkinsons Disease in African and African Admixed Populations

Intronic GBA1 variant rs3115534-G, common in African and African admixed ancestry but rare elsewhere, raises Parkinson's disease risk (OR 1.58) and lowers onset age.

Factorizing polygenic epistasis improves prediction and uncovers biological pathways in complex traits

This paper introduces EFA, a model that factorizes polygenic epistasis to improve prediction and uncover biological pathways in complex traits.

A polygenic risk score identifies undiagnosed cases of diabetes

This paper uses a polygenic risk score to identify undiagnosed diabetes cases, finding that combining BMI and PRS captures most undiagnosed cases, including those with normal weight.

Data Simulation to Optimize the GWAS Framework in Diverse Populations

This study simulates genomic data from diverse populations to assess GWAS tool performance and proposes an optimized framework for analyzing GWAS data in non-European populations.

Prospective analysis of incident disease among individuals of diverse ancestries using genetic and conventional risk factors

The paper estimates polygenic risk scores (PRS) for 12 diseases in a diverse cohort and finds higher disease incidence and earlier clinical manifestation in top PRS individuals.

A new method for multi-ancestry polygenic prediction improves performance across diverse populations

The paper introduces CT-SLEB, a method for multi-ancestry polygenic prediction that improves performance in non-European populations using GWAS summary statistics and simulation studies.

Dopamine and schizophrenia from bench to bedside: Discovery of a striatal co-expression risk gene set that predicts in vivo measures of striatal function.

The paper identifies a striatal gene set linked to schizophrenia risk that predicts in vivo dopamine synthesis and striatal activation in neurotypical and patient cohorts.

Guidelines for Evaluating the Comparability of Down-Sampled GWAS Summary Statistics

This paper evaluates how down-sampling affects GWAS summary statistics and recommends reporting specific analyses to support their use.

Polygenic prediction across populations is influenced by ancestry, genetic architecture, and methodology

This study shows that polygenic risk scores from multi-ancestry GWAS perform better in understudied populations than single-ancestry scores, except when the understudied group is small.

Joint modelling of whole genome sequence data for human height via approximate message passing

This paper introduces gVAMP, an algorithm for analyzing whole genome sequence data to identify genetic variants associated with complex traits like height, showing improved accuracy over existing methods.

A biobank-scale test of marginal epistasis reveals genome-wide signals of polygenic epistasis

The paper tests for polygenic epistasis in biobank-scale data and finds 16 trait-loci pairs with strong evidence of interaction effects.

Pathway-Specific Polygenic Scores Improve Cross-Ancestry Prediction of Psychosis and Clinical Outcomes

This study shows pathway-specific polygenic scores improve cross-ancestry prediction of psychosis risk and clinical outcomes compared to genome-wide polygenic scores.

HAPNEST: efficient, large-scale generation and evaluation of synthetic datasets for genotypes and phenotypes

HAPNEST generates and evaluates large-scale synthetic genotype and phenotype datasets for polygenic risk score analysis.

Species-wide genomics of kakapo provides transformational tools to accelerate recovery

This paper uses whole-genome sequencing of kakapo to analyze genetic diversity and breeding values, showing how conservation management has maintained genetic diversity and providing tools for future recovery efforts.