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    Identification of Novel Alzheimer's Disease Loci Using Sex-Specific Family-Based Association Analysis of Whole-Genome Sequence Data.

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    Author
    Prokopenko, D; Hecker, J; Kirchner, R; Chapman, BA; Hoffman, O; Mullin, K; Hide, W; Bertram, L; Laird, N; DeMeo, DL; ...
    Date
    2020-03-19
    Source Title
    Scientific Reports
    Publisher
    Springer Science and Business Media LLC
    University of Melbourne Author/s
    Hofmann, Oliver
    Affiliation
    Clinical Pathology
    Metadata
    Show full item record
    Document Type
    Journal Article
    Citations
    Prokopenko, D., Hecker, J., Kirchner, R., Chapman, B. A., Hoffman, O., Mullin, K., Hide, W., Bertram, L., Laird, N., DeMeo, D. L., Lange, C. & Tanzi, R. E. (2020). Identification of Novel Alzheimer's Disease Loci Using Sex-Specific Family-Based Association Analysis of Whole-Genome Sequence Data.. Sci Rep, 10 (1), pp.5029-. https://doi.org/10.1038/s41598-020-61883-6.
    Access Status
    Open Access
    URI
    http://hdl.handle.net/11343/251454
    DOI
    10.1038/s41598-020-61883-6
    Open Access at PMC
    http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7081222
    Abstract
    With the advent of whole genome-sequencing (WGS) studies, family-based designs enable sex-specific analysis approaches that can be applied to only affected individuals; tests using family-based designs are attractive because they are completely robust against the effects of population substructure. These advantages make family-based association tests (FBATs) that use siblings as well as parents especially suited for the analysis of late-onset diseases such as Alzheimer's Disease (AD). However, the application of FBATs to assess sex-specific effects can require additional filtering steps, as sensitivity to sequencing errors is amplified in this type of analysis. Here, we illustrate the implementation of robust analysis approaches and additional filtering steps that can minimize the chances of false positive-findings due to sex-specific sequencing errors. We apply this approach to two family-based AD datasets and identify four novel loci (GRID1, RIOK3, MCPH1, ZBTB7C) showing sex-specific association with AD risk. Following stringent quality control filtering, the strongest candidate is ZBTB7C (Pinter = 1.83 × 10-7), in which the minor allele of rs1944572 confers increased risk for AD in females and protection in males. ZBTB7C encodes the Zinc Finger and BTB Domain Containing 7C, a transcriptional repressor of membrane metalloproteases (MMP). Members of this MMP family were implicated in AD neuropathology.

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