ReviewFrontiers in genetics2024
Translation of genome-wide association study: from genomic signals to biological insights.
Review in Frontiers in genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed.
- SNPannotator: automated functional annotation of genetic variants and linked proxies.Bioinformatics (Oxford, England) · 2026Article
- Bridging population and cell: modelling complex diseases with human induced pluripotent stem cells.European journal of human genetics : EJHG · 2026Review
- Pathway-Level Reorganization of Genetic Signals Associated with Low Bone Mineral Density Across the Menopausal Transition.International journal of molecular sciences · 2026Article
- Article
- Twin pairs discordant for incident coronary artery disease reveal epigenetic and transcriptomic differences by gene region.Molecular genetics and genomics : MGG · 2025Article
- Use of bidirectional Mendelian randomization to unveil the association between antibody-mediated immune responses to infectious agents and allergic rhinitis.Human vaccines & immunotherapeutics · 2025Review
- Prediction of Skin Color Using Forensic DNA Phenotyping in Asian Populations: A Focus on Thailand.Biomolecules · 2025Review
- From GWAS signal to function: targeted CRISPR activation enables functional characterization of non-coding SNPs in chickens.Frontiers in genome editing · 2025Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Since the turn of the 21st century, genome-wide association study (GWAS) have successfully identified genetic signals associated with a myriad of common complex traits and diseases. As we transition from establishing robust genetic associations with diverse phenotypes, the central challenge is now focused on characterizing the underlying functional mechanisms driving these signals. Previous GWAS efforts have revealed multiple variants, each conferring relatively subtle susceptibility, collectively contributing to the pathogenesis of various common diseases. Such variants can further exhibit associations with multiple other traits and differ across ancestries, plus disentangling causal variants from non-causal due to linkage disequilibrium complexities can lead to challenges in drawing direct biological conclusions. Combined with cellular context considerations, such challenges can reduce the capacity to definitively elucidate the biological significance of GWAS signals, limiting the potential to define mechanistic insights. This review will detail current and anticipated approaches for functional interpretation of GWAS signals, both in terms of characterizing the underlying causal variants and the corresponding effector genes.
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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.