ReviewCurrent genetic medicine reports2018
Using High-Throughput Animal or Cell-Based Models to Functionally Characterize GWAS Signals.
Review in Current genetic medicine reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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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.
- The Utility of Genome-Wide Association Studies in Inherited Arrhythmias and Cardiomyopathies.Genes · 2025Review
- GPR139, an Ancient Receptor and an Emerging Target for Neuropsychiatric and Behavioral Disorders.Molecular neurobiology · 2025Review
- SpG and SpRY variants expand the CRISPR toolbox for genome editing in zebrafish.Nature communications · 2022Article
- New insights into the genetic etiology of Alzheimer's disease and related dementias.Nature genetics · 2022Article
- Modeling dopamine dysfunction in autism spectrum disorder: From invertebrates to vertebrates.Neuroscience and biobehavioral reviews · 2022Review
- Cutting-edge genetics in obsessive-compulsive disorder.Faculty reviews · 2020Review
- Potential Therapeutic Approaches to Alzheimer's Disease By Bioinformatics, Cheminformatics And Predicted Adme-Tox Tools.Current neuropharmacology · 2020Review
- Novel hypotheses emerging from GWAS in migraine?The journal of headache and pain · 2019Review
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purpose of reviewThe advent of genome-wide association studies (GWASs) constituted a breakthrough in our understanding of the genetic architecture of multifactorial diseases. For Alzheimer's disease (AD), more than 20 risk loci have been identified. However, we are now facing three new challenges: (i) identifying the functional SNP or SNPs in each locus, (ii) identifying the causal gene(s) in each locus, and (iii) understanding these genes' contribution to pathogenesis. RECENT
findingsTo address these issues and thus functionally characterize GWAS signals, a number of high-throughput strategies have been implemented in cell-based and whole-animal models. Here, we review high-throughput screening, high-content screening, and the use of the SUMMARY: We describe how these strategies have been successfully used to functionally characterize the genes in GWAS-defined risk loci. In the future, these strategies should help to translate GWAS data into knowledge and treatments.
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Registered trials
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