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Diabetic Phenotypes and Late-Life Dementia Risk

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Background:

Mendelian Randomization (MR) studies have reported that type 2 diabetes (T2D) was not associated with Alzheimer disease (AD). We adopted a modified, mechanism-specific MR design to explore this surprising result.

Methods:

Using inverse-variance weighted MR analysis, we evaluated the association between T2D and AD using data from 39 single nucleotide polymorphisms (SNPs) significantly associated with T2D in DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) and the corresponding associations of each SNP with AD risk obtained from the International Genomics of Alzheimer’s Project (IGAP, n=17,008 AD cases and n=37,154 controls). We evaluated mechanism-specific genetic subscores, including β-cell function, insulin sensitivity, and adiposity, and repeated analyses in 8501 Health and Retirement Study participants for replication and model validation.

Results:

In IGAP, the overall T2D polygenic score did not predict AD [odds ratio (OR) for the T2D polygenic score=1.01; 95% confidence interval (CI), 0.96, 1.06] but the insulin sensitivity polygenic score predicted higher AD risk (OR=1.17; 95% CI, 1.02, 1.34). In the Health and Retirement Study, polygenic scores were associated with T2D risk; the associations between insulin sensitivity genetic polygenic score and cognitive phenotypes were not statistically significant.

Conclusions:

Evidence from polygenic scores suggests that insulin sensitivity specifically may affect AD risk, more than T2D overall.
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Keywords: Alzheimer disease; Mendelian Randomization study; dementia; insulin sensitivity; type 2 diabetes mellitus

Document Type: Research Article

Affiliations: 1: Department of Epidemiology & Biostatistics, University of California, San Francisco, San Francisco, Departments of Social and Behavioral Sciences 2: Departments of Social and Behavioral Sciences 3: Department of Epidemiology & Biostatistics, University of California, San Francisco, San Francisco 4: Department of Medicine, Division of General Internal Medicine, University of Washington, Seattle, WA 5: Nutrition, Harvard School of Public Health, Boston, MA 6: Department of Medicine, Division of General Medical Disciplines, Stanford University, Stanford, CA

Publication date: January 1, 2016

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