Hilary K. Finucane

The paper introduces KASM to integrate functional annotations and estimate heritability of rare protein coding variants across 786,871 exomes, finding higher heritability than previous estimates.

The paper benchmarks variant effect scores using UK Biobank data on ultra-rare variant carriers, showing coding and splicing scores better predict protein abundance and traits than transcriptional regulation models.

The paper develops a framework to map rare variants onto protein structures and identifies disease-associated 3D neighborhoods in 872 genes for Mendelian disease and others for autism, epilepsy, and schizophrenia.

gnomAD v4 (730,947 exomes) brings LOFTEE-2 loss-of-function annotation (0.90 precision, strict mode), missense-aware constraint, and LLM-mined literature evidence combined with constraint to rank disease genes.

This study functionally characterizes 221,412 trait-associated variants using MPRA in 5 cell types, identifying 12,025 regulatory variants and revealing widespread epistasis and non-TF mechanisms.

The paper identifies naturally variable exons in human transcripts, showing their prevalence and impact on gene expression and genetic interpretation.

The paper integrates genetic, transcriptomic, and structural data to show that Ca2+ dysregulation via ATP2B2 missense variants contributes to neuropsychiatric disorders.

This study evaluates variant scoring methods across different selection regimes, showing their performance depends on variant-to-gene and gene-to-disease factors.

Meta-analyzing per-ancestry GWAS of 7,266 UK Biobank traits across six genetic ancestry groups adds 14,676 loci missed by European-only analysis, including ancestry-enriched CAMK2D and G6PD signals.

The paper derives cell-type-specific Alzheimer's disease polygenic risk scores and shows their associations with distinct pathological features in AD.

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.

ENCODE-rE2G, a classifier trained on K562 CRISPR perturbations, maps 13,455,443 enhancer-gene interactions across 352 biosamples, matching or exceeding prior models on CRISPR, eQTL, and GWAS benchmarks.

The paper visualises molecular QTLs to better understand genetic effects on gene expression and identifies causal genes at GWAS loci.

The paper introduces a method to prioritize causal genes for complex traits by integrating GWAS data with gene expression and biological data, achieving high precision in gene-trait pair identification.

This study evaluates polygenic risk score methods across diverse biobanks and ancestries, finding that European reference panels often yield better performance, while PRS-CS outperforms P+T for high-heritability traits.

This paper shows that meta-analysis fine-mapping is often miscalibrated due to cohort heterogeneity and introduces a QC method to identify suspicious loci.

The paper maps coronary artery disease risk loci to endothelial cell gene programs, identifying convergence on the CCM pathway and a new CAD gene, TLNRD1.

Meta-analysis of harmonized GWAS from up to 18 biobanks (six ancestry groups) across 14 endpoints replicated 320 known loci and identified 188 apparently novel loci.

This study identifies 114 genome-wide significant rare CNV-disease associations across 30 neurological disorders, revealing 38 novel triplosensitive genes and developing a model to predict dosage sensitivity.

This study identifies shared immune pathways between coronary artery disease and pneumonia through genome-wide pleiotropy analysis, highlighting ADAMTS7 and IL6R as key genes with opposing effects on the two conditions.

This paper introduces PolyPred and PolyPred+ to improve cross-population polygenic risk score accuracy by addressing LD, MAF, and causal effect size differences using fine-mapping and non-European training data.

Finnish-enriched low-frequency variants, often coding, underlie many GWAS signals across 1,932 register endpoints in 218,792 Finns; a 15-disease meta-analysis with Estonian and UK biobanks adds 30 unreported associations.

Fine-mapping 148 complex traits in three biobanks with combined n = 811,261 yields 4,518 causal variant-trait pairs, 285 of them repeating in more than one population.

The paper identifies causal 3'UTR variants linked to human disease and evolution using a new high-throughput assay and functional analysis.

The paper uses supervised learning to fine-map cis-eQTLs, identifying 20,913 additional putative causal eQTLs and 310 candidate genes.

A coronary artery disease GWAS of 181,522 cases among 1,165,690 participants yields 241 associations (54 new); an eight-predictor consensus nominates 185 candidate causal genes, 94 with ≥3 predictors.

The paper shows that S-LDSC's significance testing fails for small annotations, leading to inflated type 1 error, and proposes thresholds to control this error.

Tractor improves GWAS power and resolution by including admixed individuals through local ancestry-aware analysis.

This paper introduces cov-LDSC, a method to estimate heritability and its enrichment in tissue-specific gene sets in admixed populations, showing high concordance across populations but population-specific differences for some traits.