David W Fardo1, Laura E Gibbons2, Shubhabrata Mukherjee2, M Maria Glymour3, Wayne McCormick2, Susan M McCurry4, James D Bowen5, Eric B Larson6, Paul K Crane7. 1. Department of Biostatistics and Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY, USA. 2. Department of Medicine, University of Washington, Seattle, WA, USA. 3. Department of Epidemiology, University of California, San Francisco, San Francisco, CA, USA. 4. Department of Psychosocial and Community Health, University of Washington, Seattle, WA, USA. 5. Department of Neurology, Swedish Medical Center, Seattle, WA, USA. 6. Group Health Research Institute, Group Health, Seattle, WA, USA. 7. Department of Medicine, University of Washington, Seattle, WA, USA. Electronic address: pcrane@uw.edu.
Abstract
INTRODUCTION: Findings for genetic correlates of late-onset Alzheimer's disease (LOAD) in studies that rely solely on clinic visits may differ from those with capacity to follow participants unable to attend clinic visits. METHODS: We evaluated previously identified LOAD-risk single nucleotide variants in the prospective Adult Changes in Thought study, comparing hazard ratios (HRs) estimated using the full data set of both in-home and clinic visits (n = 1697) to HRs estimated using only data that were obtained from clinic visits (n = 1308). Models were adjusted for age, sex, principal components to account for ancestry, and additional health indicators. RESULTS: LOAD associations nominally differed for 4 of 21 variants; CR1 and APOE variants were significant after Bonferroni correction. DISCUSSION: Estimates of genetic associations may differ for studies limited to clinic-only designs. Home visit capacity should be explored as a possible source of heterogeneity and potential bias in genetic studies.
INTRODUCTION: Findings for genetic correlates of late-onset Alzheimer's disease (LOAD) in studies that rely solely on clinic visits may differ from those with capacity to follow participants unable to attend clinic visits. METHODS: We evaluated previously identified LOAD-risk single nucleotide variants in the prospective Adult Changes in Thought study, comparing hazard ratios (HRs) estimated using the full data set of both in-home and clinic visits (n = 1697) to HRs estimated using only data that were obtained from clinic visits (n = 1308). Models were adjusted for age, sex, principal components to account for ancestry, and additional health indicators. RESULTS: LOAD associations nominally differed for 4 of 21 variants; CR1 and APOE variants were significant after Bonferroni correction. DISCUSSION: Estimates of genetic associations may differ for studies limited to clinic-only designs. Home visit capacity should be explored as a possible source of heterogeneity and potential bias in genetic studies.
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