Richard Sherva1, Yorghos Tripodis2, David A Bennett3, Lori B Chibnik4, Paul K Crane5, Philip L de Jager4, Lindsay A Farrer6, Andrew J Saykin7, Joshua M Shulman8, Adam Naj9, Robert C Green10. 1. Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA. Electronic address: rcgreen@genetics.med.harvard.edu. 2. Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA. 3. Rush Alzheimer's Disease Center, Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA. 4. Program in Translational NeuroPsychiatric Genomics, Institute for the Neurosciences, Departments of Neurology & Psychiatry, Brigham and Women's Hospital Boston, MA, USA; Department of Neurology, Harvard Medical School, Cambridge, MA, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA. 5. School of Medicine, University of Washington, Seattle, WA, USA. 6. Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA; Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA; Departments Ophthalmology, Neurology, and Epidemiology, Boston University Schools of Medicine and Public Health, Boston, MA, USA. 7. Department of Medical and Molecular Genetics, Center for Neuroimaging, Department of Radiology and Imaging Sciences, Melvin and Bren Simon Cancer Center, Indiana University School of Medicine, Indianapolis, IN, USA. 8. Departments of Neurology and Molecular and Human Genetics Baylor College of Medicine Jan and Dan Duncan Neurological Research Institute, Houston, TX, USA. 9. Department of Biostatics and Epidemiology and Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA. 10. Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Abstract
BACKGROUND: Substantial interindividual variability exists in the disease trajectories of Alzheimer's disease (AD) patients. Some decline rapidly whereas others decline slowly, and there are no known explanations for this variability. We describe the first genome-wide association study to examine rate of cognitive decline in a sample of AD patients with longitudinal measures of cognition. METHODS: The discovery sample was 303 AD cases recruited in the Alzheimer's Disease Neuroimaging Initiative and the replication sample was 323 AD cases from the Religious Orders Study and Rush Memory and Aging Project. In the discovery sample, Alzheimer's Disease Assessment Scale-cognitive subscale responses were tested for association with genome-wide single-nucleotide polymorphism (SNP) data using linear regression. We tested the 65 most significant SNPs from the discovery sample for association in the replication sample. RESULTS: We identified SNPs in the spondin 1 gene (SPON1), the minor alleles of which were significantly associated with a slower rate of decline (rs11023139, P = 7.0 × 10(-11)) in the discovery sample. A SPON1 SNP 5.5 kb upstream was associated with decline in the replication sample (rs11606345, P = .002). CONCLUSION: SPON1 has not been previously associated with AD risk, but is plausibly related because the gene product binds to the amyloid precursor protein and inhibits its cleavage by β-secretase. These data suggest that SPON1 may be associated with the differential rate of cognitive decline in AD.
BACKGROUND: Substantial interindividual variability exists in the disease trajectories of Alzheimer's disease (AD) patients. Some decline rapidly whereas others decline slowly, and there are no known explanations for this variability. We describe the first genome-wide association study to examine rate of cognitive decline in a sample of ADpatients with longitudinal measures of cognition. METHODS: The discovery sample was 303 AD cases recruited in the Alzheimer's Disease Neuroimaging Initiative and the replication sample was 323 AD cases from the Religious Orders Study and Rush Memory and Aging Project. In the discovery sample, Alzheimer's Disease Assessment Scale-cognitive subscale responses were tested for association with genome-wide single-nucleotide polymorphism (SNP) data using linear regression. We tested the 65 most significant SNPs from the discovery sample for association in the replication sample. RESULTS: We identified SNPs in the spondin 1 gene (SPON1), the minor alleles of which were significantly associated with a slower rate of decline (rs11023139, P = 7.0 × 10(-11)) in the discovery sample. A SPON1 SNP 5.5 kb upstream was associated with decline in the replication sample (rs11606345, P = .002). CONCLUSION:SPON1 has not been previously associated with AD risk, but is plausibly related because the gene product binds to the amyloid precursor protein and inhibits its cleavage by β-secretase. These data suggest that SPON1 may be associated with the differential rate of cognitive decline in AD.
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