Alkes L. Price

Functionally informed cis and trans proteome-wide association studies prioritize disease-critical genes

The paper develops PolyPWAS, a framework combining cis- and trans-pQTLs to prioritize disease-critical genes by improving protein prediction with functional annotations and showing better disease heritability explanation.

Ancient DNA reveals that natural selection has upregulated the immune system over the last 10,000 years

This study uses ancient DNA and genomic data to show natural selection has strengthened the immune system over 10,000 years, with both protective and harmful effects on immune-related diseases.

Distinguishing causal from tagging enhancers using single-cell multiome data

The paper identifies and quantifies non-causal tagging effects in single-cell multiome data, showing how they distort peak-gene associations and proposing methods to mitigate their impact.

Mapping disease loci to biological processes via joint pleiotropic and epigenomic partitioning

This paper introduces J-PEP, a method that clusters GWAS loci using pleiotropy and epigenomics, improving biological interpretation of disease associations.

Per-allele disease and complex trait effect sizes are predominantly African MAF-dependent in European populations

The paper shows that per-allele effect sizes of genetic variants in European populations are better predicted by African MAF than European MAF.

MultiSuSiE improves multi-ancestry fine-mapping in All of Us whole-genome sequencing data

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.

Estimating Disorder Probability Based on Polygenic Prediction Using the BPC Approach

The paper introduces the BPC approach to improve polygenic score calibration for binary disorders, achieving better calibration than existing methods in simulated and empirical data.

Exposure accumulation drives age-dependent disease architectures and polygenic risk scores

The paper shows that environmental variance increases with age, reducing heritability and PRS accuracy for multiple traits and diseases, suggesting younger cohorts are better for risk prediction models.

Genetic regulation of cell type-specific chromatin accessibility shapes immune function and disease risk

The paper maps chromatin accessibility and genetic variation in immune cells, showing how integrating cell-type-specific data improves disease risk understanding.

Linking regulatory variants to target genes by integrating single-cell multiome methods and genomic distance

The paper introduces pgBoost, a framework that improves linking regulatory variants to genes by integrating single-cell multiome data and genomic distance, showing higher enrichment than existing methods.

Pleiotropic heritability quantifies the shared genetic variance of common diseases

This paper introduces PHBC to estimate pleiotropic heritability across diseases, finding that about half of common disease heritability is shared with other diseases.

Genome-wide association studies in a large Korean cohort identify novel quantitative trait loci for 36 traits and illuminate their genetic architectures

This study conducts GWAS in a large Korean cohort, identifying 301 novel loci and highlighting East Asian-specific genetic associations for 36 traits.

Distinct explanations underlie gene-environment interactions in the UK Biobank

The paper quantifies and distinguishes three types of gene-environment interactions using statistical methods applied to UK Biobank data, identifying significant associations across various traits and environmental variables.

Fine-mapping causal tissues and genes at disease-associated loci

This paper introduces TGFM, a method for fine-mapping causal tissues and genes at disease-associated loci using GWAS and eQTL data, identifying 147 causal elements per disease with 11% as gene-tissue pairs.

A consensus variant-to-function score to functionally prioritize variants for disease

This paper introduces a consensus variant-to-function score to prioritize disease-causing variants, showing improved performance in heritability enrichment and fine-mapping.

Pervasive findings of directional selection realize the promise of ancient DNA to elucidate human adaptation

This paper detects widespread directional selection in ancient DNA data, identifying 347 genome-wide significant loci and linking them to traits like body fat, skin color, and cognitive performance.

Tissue-specific enhancer-gene maps from multimodal single-cell data identify causal disease alleles

The paper develops SCENT, a method to create cell-type-specific enhancer-gene maps from single-cell multimodal data, identifying causal variants and genes for diseases.

Leveraging single-cell ATAC-seq to identify disease-critical fetal and adult brain cell types

The paper integrates GWAS with scATAC-seq and scRNA-seq data to identify disease-critical fetal and adult brain cell types for multiple traits.

Pervasive correlations between causal disease effects of proximal SNPs vary with functional annotations and implicate stabilizing selection

The paper introduces LDSPEC to estimate correlations between causal disease effects of proximal SNPs, finding significant correlations that vary with distance, allele frequency, LD, and functional annotations, implicating stabilizing selection.

An encyclopedia of enhancer-gene regulatory interactions in the human genome

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.

Modeling tissue co-regulation to estimate tissue-specific contributions to disease

This paper introduces TCSC, a method to identify tissue-specific disease contributions by distinguishing causal tissues from tagging tissues using GWAS and gene expression data.

Dynamic regulatory elements in single-cell multimodal data capture autoimmune disease heritability and implicate key immune cell states

Systematically characterizing the roles of E3-ligase family members in inflammatory responses with massively parallel Perturb-seq

The paper uses Perturb-seq to systematically study 1,130 E3 ligases and their roles in inflammatory responses in dendritic cells, revealing co-functional modules and genetic interactions.

Age-dependent topic modelling of comorbidities in UK Biobank identifies disease subtypes with differential genetic risk

This paper introduces an age-dependent topic modelling method to identify disease subtypes with differential genetic risk using UK Biobank and All of Us data.

Polygenic enrichment distinguishes disease associations of individual cells in single-cell RNA-seq data

This paper introduces scDRS, a method to identify disease-associated cells in scRNA-seq data using polygenic risk scores, finding novel subpopulations linked to diseases like IBD and schizophrenia.

Incorporating family history of disease improves polygenic risk scores in diverse populations

This study combines polygenic risk scores with family history to improve disease risk prediction across diverse populations, showing significant gains in accuracy.

SNP-to-gene linking strategies reveal contributions of enhancer-related and candidate master-regulator genes to autoimmune disease

The paper links SNPs to genes using functionally informed strategies, revealing enhancer-related and master-regulator genes contribute to autoimmune disease heritability.

Combining SNP-to-gene linking strategies to pinpoint disease genes and assess disease omnigenicity

The paper develops a combined SNP-to-gene linking strategy (cS2G) to improve the identification of disease-causing genes and assess disease omnigenicity using GWAS data.

Leveraging fine-mapping and non-European training data to improve cross-population polygenic risk scores

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.

Leveraging gene co-regulation to identify gene sets enriched for disease heritability

The paper introduces GCSC regression to identify gene sets enriched for disease heritability by leveraging gene co-regulation in TWAS data, finding immune-related associations in Alzheimer's disease.