Affiliations: [a] Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA | [b] Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA | [c] Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA | [d] Alzheimer's Disease Research Center, University of Pittsburgh, Pittsburgh, PA, USA | [e] Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA | [f] Department of Neurology, University of Virginia School of Medicine, Charlottesville, VA, USA | [g] VISN 4 Mental Illness Research, Education and Clinical Center (MIRECC), VA Pittsburgh Healthcare System, Pittsburgh, PA, USA
Correspondence:
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Correspondence to: Professor M. Ilyas Kamboh, Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, PA 15261, USA. Tel.: +1 412 624 3066; Fax: +1 412 624 3020; E-mail: [email protected].
Abstract: There is a strong genetic basis for late-onset of Alzheimer's disease (LOAD), and thus far >20 genes/loci have been identified that affect the risk of LOAD. In addition to disease risk, genetic variation at these loci may also affect components of the natural history of AD, such as survival in AD. In this study, we first examined the role of known LOAD genes with survival time in 983 AD patients. We then performed genome-wide single-nucleotide polymorphism (SNP) and gene-based association analyses to identify novel loci that may influence survival of AD. Survival analysis was conducted using Cox proportional hazards regression under an additive genetics model. We found multiple nominally significant associations (p < 0.01) either within or adjacent to known LOAD genes. Genome-wide SNP analysis identified multiple suggestive novel loci and two of them were also significant in gene-based analysis (CCDC85C and NARS2) that survived after controlling for false-discovery rate at 0.05. In summary, we have identified two novel genes for survival in AD that need to be replicated in independent samples. Our findings highlight the importance of focusing on AD-related phenotypes that may help to identify additional genes relevant to AD.
Keywords: Gene-based analysis, genome-wide association studies, late-onset Alzheimer's disease, survival
