Candidate gene discovery procedure after follow-up confirmatory
analyses of candidate regions of interests for Alzheimer's disease in the NIMH
sibling dataset
Affiliations: Section on Statistical Genetics, Department of
Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294,
USA | Department of Epidemiology and International Health,
University of Alabama at Birmingham, Birmingham, AL 35294, USA | Department of Neurology, University of Alabama at
Birmingham, Birmingham, AL 35294, USA
Note: [] Corresponding author: Tesfaye M. Baye, Section on Statistical
Genetics, Department of Biostatistics, RPHB 327, University of Alabama at
Birmingham, Birmingham, AL 35294-0022, USA. Tel.: +1 205 975 9273; Fax: +1 205
975 2540; E-mail: [email protected]
Abstract: The objective of this research was to develop a procedure to
identify candidate genes under linkage peaks confirmed in a follow-up of
candidate regions of interests (CRIs) identified in our original genome scan in
the NIMH Alzheimer's diseases (AD) Initiative families (Blacker et al. [1]).
There were six CRIs identified that met the threshold of multipoint lod score
(MLS) of ⩾ 2.0 from the original scan. The most significant peak (MLS =
7.7) was at 19q13, which was attributed to APOE. The remaining CRIs with
'suggestive' evidence for linkage were identified at 9q22, 6q27, 14q22, 11q25,
and 3p26. We have followed up and narrowed the 9q22 CRI signal using simple
tandem repeat (STR) markers (Perry et al. [2]). In this confirmatory project,
we have followed up the 6q27, 14q22, 11q25, and 3p26 CRIs with a total of 24
additional flanking STRs, reducing the mean interval marker distance (MID) in
each CRI, and substantially increase in the information content (IC). The
linkage signals at 6q27, 14q22 and 11q25 remain 'suggestive', indicating that
these CRIs are promising and worthy of detailed fine mapping and assessment of
candidate genes associated with AD. We have developed a bioinformatics approach for identifying
candidate genes in these confirmed regions based on the Gene Ontology terms
that are annotated and enriched among the systematic meta-analyzed genes,
confirmed by at least three case-control samples, and cataloged in the "AlzGene
database" as potential Alzheimer disease susceptibility genes
(http://www.alzgene.org).
