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• W2270172181 abstract "<b><i>Background/Aims:</i></b> Present-day limited resources demand DNA and phenotyping alternatives to the traditional prospective population-based epidemiologic collections. <b><i>Methods:</i></b> To accelerate genomic discovery with an emphasis on diverse populations, we - as part of the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study - accessed all non-European American samples (n = 15,863) available in BioVU, the Vanderbilt University biorepository linked to de-identified electronic medical records, for genomic studies as part of the larger Population Architecture using Genomics and Epidemiology (PAGE) I study. Given previous studies have cautioned against the secondary use of clinically collected data compared with epidemiologically collected data, we present here a characterization of EAGLE BioVU, including the billing and diagnostic (ICD-9) code distributions for adult and pediatric patients as well as comparisons made for select health metrics (body mass index, glucose, HbA1c, HDL-C, LDL-C, and triglycerides) with the population-based National Health and Nutrition Examination Surveys (NHANES) linked to DNA samples (NHANES III, n = 7,159; NHANES 1999-2002, n = 7,839). <b><i>Results:</i></b> Overall, the distributions of billing and diagnostic codes suggest this clinical sample is a mixture of healthy and sick patients like that expected for a contemporary American population. <b><i>Conclusion:</i></b> Little bias is observed among health metrics, suggesting this clinical collection is suitable for genomic studies along with traditional epidemiologic cohorts." @default.
• W2270172181 created "2016-06-24" @default.
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• W2270172181 date "2015-01-01" @default.
• W2270172181 modified "2023-10-03" @default.
• W2270172181 title "Leveraging Epidemiologic and Clinical Collections for Genomic Studies of Complex Traits" @default.
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• W2270172181 doi "https://doi.org/10.1159/000381805" @default.
• W2270172181 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/4528966" @default.
• W2270172181 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/26201699" @default.
• W2270172181 hasPublicationYear "2015" @default.
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