ArticleBMC genomics2022
Leveraging family history in genetic association analyses of binary traits.
Article in BMC genomics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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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Who cites it
3 citing papers in PubMed, 3 citations in OpenAlex.
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- Intraindividual variability in brain activation-A novel correlate of obesity risk among female college students.Brain and cognition · 2023Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
Abstract
backgroundConsidering relatives' health history in logistic regression for case-control genome-wide association studies (CC-GWAS) may provide new information that increases accuracy and power to detect disease associated genetic variants. We conducted simulations and analyzed type 2 diabetes (T2D) data from the Framingham Heart Study (FHS) to compare two methods, liability threshold model conditional on both case-control status and family history (LT-FH) and Fam-meta, which incorporate family history into CC-GWAS.
resultsIn our simulation scenario of trait with modest T2D heritability (h
conclusionsOverall, LT-FH and Fam-meta had higher power than CC-GWAS in simulations, especially using phenotypes that were more prevalent in older age groups, and both methods detected known genetic variants with lower P-values in real data application, highlighting the benefits of including family history in genetic association studies.
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Registered trials
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