Journal
ARCHIVES OF NEUROLOGY
Volume 65, Issue 11, Pages 1518-1526Publisher
AMER MEDICAL ASSOC
DOI: 10.1001/archneur.65.11.1518
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Funding
- NIA-LOAD Family Study [U24AG026395]
- National Cell Repository for Alzheimer's Disease [U24AG021886]
- Boston University [P50AG08702]
- Columbia University [P50AG08702]
- Duke University [P30AG028377]
- Indiana University [P30AG010133]
- Massachusetts General Hospital [PO1 AG05138]
- Mayo Clinic, Rochester [PO1 AG05138]
- Mayo Clinic, Jacksonville [PO1 AG05138]
- Mount Sinai School of Medicine [PO1 AG05138]
- Northwestern University Medical School [P30AG010124]
- Oregon Health and Science University [P30AG010124]
- Rush University Medical Center [P30AG010124]
- University of Alabama at Birmingham [P30AG010124]
- David Geffen School of Medicine, University of California, Los Angeles [P30AG010124]
- University of Kentucky, Lexington [P30AG010124]
- University of Pennsylvania [P30AG010124]
- University of Pittsburgh [P30AG010124]
- University of Southern California [P30AG010124]
- The University of Texas Southwestern Medical Center [P30AG010124]
- University of Washington [P30AG010124]
- Washington University School of Medicine [P30AG010124]
- National Institutes of Health (The Johns Hopkins University) [N01-HG65403]
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Objective: To identify putative genetic loci related to the risk of late-onset Alzheimer disease (LOAD). Design: Linkage analysis and family-based and case-control association analyses from a genomewide scan using approximately 6000 single-nucleotide polymorphic markers at an average intermarker distance of 0.65 cM. Setting: The National Institute on Aging Genetics Initiative for Late-Onset Alzheimer's Disease (NIA-LOAD) was created to expand the resources for studies to identify additional genes contributing to the risk for LOAD. Participants: We investigated 1902 individuals from 328 families with LOAD and 236 unrelated control subjects. Main Outcome Measures: Clinical diagnosis of LOAD. Results: The strongest overall finding was at chromosome 19q13.32, confirming the effect of the apolipoprotein E gene on LOAD risk in the family-based and case-control analyses. However, single-nucleotide polymorphisms at the following loci were also statistically significant in 1 or more of the analyses performed: 7p22.2, 7p21.3, and 16q21 in the linkage analyses; 17q21.31 and 22q11.21 in the family-based association analysis; and 7q31.1 and 22q12.3 in the case-control analysis. Positive associations at 7q31.1 and 20q13.33 were also significant in the meta-analysis results in a publicly available database. Conclusions: Several additional loci may harbor genetic variants associated with LOAD. This data set provides a wealth of phenotypic and genotypic information for use as a resource in discovery and confirmatory research.
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