GWAS summary statistics

This study evaluates the impact of Neanderthal ancestry on cancer risk by analyzing GWAS data and finds that Neanderthal variants are associated with both increased and decreased cancer risk, with some persisting due to adaptive pleiotropy.

This study identifies genetic factors associated with self-reported SSRI response in depression using genome-wide meta-analysis and polygenic scores, highlighting GABAergic and glutamatergic pathways.

This study identifies genetic loci associated with early MS severity using genome-wide association analysis and finds candidate effector genes and pathways.

This study shows that excluding low-frequency variants and indels in fine-mapping leads to false discoveries and introduces SuSiE-OUT to address this issue.

This paper improves depression prediction by integrating psychiatric traits, showing stronger associations across development, families, and populations.

LRCQ estimates phenome-wide heritability enrichment of genomic loci using GWAS summary statistics, identifying enriched regions and their functional annotations.

LRCP identifies functionally related SNPs and genes by estimating phenome-wide genetic-effect correlations from GWAS summary statistics, improving accuracy over naive methods.

This study identifies genetic risk loci for pilonidal sinus disease and finds strong genetic overlap with hidradenitis suppurativa and hair patterning, but not obesity.

This study identifies polygenic trends in morning chronotype evolution in modern humans above 20 degrees north, showing increased morningness compared to Neanderthals.

The paper benchmarks variant effect predictors using a leakage-controlled dataset and develops a gradient-boosting consensus model that outperforms existing tools.

This study conducts ancestry-specific and multi-ancestry GWAS of restless legs syndrome, identifying shared and ancestry-specific risk loci across African, Latin American, and European populations.

The paper fine-maps GWAS risk variants for PDAC and identifies candidate target genes through chromatin conformation capture, finding functional interactions and eQTLs at specific loci.

BLocPRS improves polygenic risk score prediction by combining locus-specific weights from different PRSs, achieving higher accuracy in UK Biobank and extending to non-European populations.

The paper examines how social determinants of health modify polygenic risk scores for cardiometabolic diseases and shows that integrating social and genetic factors improves disease prediction.

The paper identifies 16 genetic loci interacting with sleep duration to influence glycemic traits in over 480,000 individuals, revealing distinct biological mechanisms for short and long sleep.

Single-cell eQTL mapping in 5.4 million PBMCs from 1,925 individuals with matched WGS finds common-variant eQTLs for 83% and rare-variant signals for 47% of 21,404 genes.

The paper identifies rare SNPs associated with hypo-inflammation and adverse outcomes in trauma patients, highlighting type 17 immune responses as central to critical illness.

This study identifies two genetically distinct axes of hand and shoulder soft-tissue disorders and shows divergent responses to adiposity and incretin therapy.

The paper systematically adjudicates genetic evidence for Alzheimer's disease and related dementias, identifying 111 high-confidence loci through a tiered framework applied to large-scale genome-wide studies.

The paper shows that variant effect predictors influence ClinVar classifications, creating circularity in variant classification and prediction.

The paper introduces a family-aware benchmark for polygenic prediction using All of Us data, enabling comparison of PRS and machine learning models across 14 traits with strong predictive performance.

This study identifies five genetic loci associated with age at onset of Parkinson's disease in European populations, including novel associations at HIP1R and FSCB.

This paper develops a polygenic score for smoking persistence and finds it is associated with earlier or later cessation ages across diverse populations.

This paper introduces a haplotype-based fine-mapping method called happler to identify causal variants for complex traits, showing improved performance over traditional methods in detecting haplotype effects.

This study conducts a GWAS of Lyme disease, identifying five genetic loci and linking it to post-infectious diseases like Bell palsy and joint pain.

This study uses genomic structural equation modelling to assess the genetic overlap between insomnia, depression, and anxiety, finding insomnia is the best-supported location of the genetic overlap.

SUMMIT improves heritability and genetic correlation estimation across diverse ancestries using LD scores and GWAS summary statistics, showing better accuracy in non-European populations.

Varformer prioritizes drug targets and variants by integrating variant and gene features using a transformer model, achieving high precision across diverse benchmarks.

This paper introduces S4-Oligo, an optimized polygenic score method for clinical use, which matches or exceeds existing models' accuracy while using fewer SNPs.