ArticleAmerican journal of human genetics2014
Joint analysis of functional genomic data and genome-wide association studies of 18 human traits.
Article in American journal of human genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 364 papers, 10 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
364 citing papers in PubMed, 10 syntheses or guidelines pooled it, 654 citations in OpenAlex.
- Pooled it
- Multi-ancestry genome-wide association analyses improve resolution of genes and pathways influencing lung function and chronic obstructive pulmonary disease risk.Nature genetics · 2023Pooled it
- Discovery and systematic characterization of risk variants and genes for coronary artery disease in over a million participants.Nature genetics · 2022Pooled it
- Multi-ancestry genome-wide association study of gestational diabetes mellitus highlights genetic links with type 2 diabetes.Human molecular genetics · 2022Pooled it
- Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation.Nature genetics · 2022Pooled it
- Incorporating functional priors improves polygenic prediction accuracy in UK Biobank and 23andMe data sets.Nature communications · 2021Pooled it
- Genome-wide meta-analysis, fine-mapping and integrative prioritization implicate new Alzheimer's disease risk genes.Nature genetics · 2021Pooled it
- A Review of Statistical Methods for Identifying Trait-Relevant Tissues and Cell Types.Frontiers in genetics · 2020Pooled it
- Exome Chip Meta-analysis Fine Maps Causal Variants and Elucidates the Genetic Architecture of Rare Coding Variants in Smoking and Alcohol Use.Biological psychiatry · 2019Pooled it
- Methods for the Analysis and Interpretation for Rare Variants Associated with Complex Traits.Current protocols in human genetics · 2019Pooled it
- Congenital heart disease risk loci identified by genome-wide association study in European patients.The Journal of clinical investigation · 2021Trial
- Alternative tandem transcription initiation links noncoding variants to human disease through translational control.Nature communications · 2026Article
- Integrating single-cell sQTL mapping with deep-learning splicing prediction identifies causal variants under influenza infection.Genome biology · 2026Article
- Evaluation of epistasis detection methods for quantitative phenotypes.Bioinformatics (Oxford, England) · 2026Article
- Extensive genetic interactions (epistasis) linked to alcohol use disorder in a high-risk population.Communications biology · 2026Article
- keju: powerful and accurate inference in Massively Parallel Reporter Assays.bioRxiv : the preprint server for biology · 2026Article
- Combining functional annotation and multi-trait fine-mapping methods improves fine-mapping resolution at glycaemic trait loci.Human molecular genetics · 2026Article
- Donor-matched iPSC model reveals context-dependent T2D genetic signals in fibro-adipogenic progenitors.bioRxiv : the preprint server for biology · 2026Article
- MIRAGE: A Bayesian statistical method for gene-level rare-variant analysis incorporating functional annotations.American journal of human genetics · 2026Article
- Causal splicing variants revealed by deep-learning integration of single-cell sQTL mapping under influenza infection.Research square · 2026Article
304 more citing papers are in PubMed but not listed here.
Corrections and comments
- Erratum issued
Authors and funding
1 author at 1 institution in 1 country.
Funding
Abstract
Annotations of gene structures and regulatory elements can inform genome-wide association studies (GWASs). However, choosing the relevant annotations for interpreting an association study of a given trait remains challenging. I describe a statistical model that uses association statistics computed across the genome to identify classes of genomic elements that are enriched with or depleted of loci influencing a trait. The model naturally incorporates multiple types of annotations. I applied the model to GWASs of 18 human traits, including red blood cell traits, platelet traits, glucose levels, lipid levels, height, body mass index, and Crohn disease. For each trait, I used the model to evaluate the relevance of 450 different genomic annotations, including protein-coding genes, enhancers, and DNase-I hypersensitive sites in over 100 tissues and cell lines. The fraction of phenotype-associated SNPs influencing protein sequence ranged from around 2% (for platelet volume) up to around 20% (for low-density lipoprotein cholesterol), repressed chromatin was significantly depleted for SNPs associated with several traits, and cell-type-specific DNase-I hypersensitive sites were enriched with SNPs associated with several traits (for example, the spleen in platelet volume). Finally, reweighting each GWAS by using information from functional genomics increased the number of loci with high-confidence associations by around 5%.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.