Impact of home visit capacity on genetic association studies of late-onset Alzheimer's disease

David W. Fardo, Laura E. Gibbons, Shubhabrata Mukherjee, M. Maria Glymour, Wayne McCormick, Susan M. McCurry, James D. Bowen, Eric B. Larson, Paul K. Crane

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

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.

Original languageEnglish
Pages (from-to)933-939
Number of pages7
JournalAlzheimer's and Dementia
Volume13
Issue number8
DOIs
StatePublished - Aug 2017

Bibliographical note

Publisher Copyright:
© 2017 the Alzheimer's Association

Keywords

  • Ascertainment bias
  • Bias
  • Cohort studies
  • Genetics
  • Genome-wide association studies
  • Genome-wide studies
  • Home research study visits
  • Inference
  • Late-onset Alzheimer's disease
  • Longitudinal studies
  • Missing data
  • Population-based studies
  • Prospective studies
  • Research clinic study visits
  • Selection bias

ASJC Scopus subject areas

  • Clinical Neurology
  • Geriatrics and Gerontology
  • Psychiatry and Mental health
  • Cellular and Molecular Neuroscience
  • Health Policy
  • Developmental Neuroscience
  • Epidemiology

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