Premium
F1‐02‐03: MULTISCALE COMPUTATIONAL APPROACH ILLUMINATING NOVEL COMMON PATHWAYS BETWEEN DIABETES AND AD
Author(s) -
Hao Ke
Publication year - 2014
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1016/j.jalz.2014.04.049
Subject(s) - genome wide association study , genetic architecture , genetic association , genetics , biology , type 2 diabetes , disease , kegg , expression quantitative trait loci , computational biology , phenotype , gene , bioinformatics , diabetes mellitus , genotype , medicine , single nucleotide polymorphism , transcriptome , gene expression , endocrinology
Background: Diabetes may increase the risk of Alzheimer’s disease (AD). Many epidemiology studies indicate that people with diabetes are at higher risk of eventually developing AD or other dementias. It is estimated that hyperinsulinemia in elderly people could account for 39% of cases of AD. However, how these two diseases are connected remains unknown. Possible mechanisms include shared genetic or microbial risk factors, which will be systematically investigated in this study. Methods: We accessed large genetic association studies (e.g., genome wide association studies, GWAS) in dbGap (The database of Genotypes and Phenotypes) databases with endpoints of diabetes type 2 (D2T), AD and related phenotypes. We applied various p value thresholds and examined the overlap between diabetes and AD GWAS hits. A significant overlap indicates shared genetic components underlying the two diseases. Further, by leveraging ENCODE (Encyclopedia of DNA Elements) and gene co-expression networks of relevant tissues, the studies were designed to inform the functionality of the shared genetic signals. We are currently focusing on 75 subjects meeting AD and T2D criteria and 75 T2D but AD-free subjects. We are currently resequencing genetic loci found in shared pathways/gene-networks identified in GWAS and search for polymorphisms showing different frequencies in the two groups. Gut microbiome of the two groups and search for fecal bacteria responsible to AD pathogenesis among T2D subjects will reveal additional associations. Results: We surveyed GWAS reports, and found 195 genetics loci for AD traits and 364 genetic loci for T2D traits which reached genome-wide significance. We identified several inflammatory genes, e.g., CLU, CR1, CD33, EPHA1, and MS4A4A/MS4A/6A, among others. This evidence strongly support the hypothesis inflammation is one of the genetic risk factors shared byAD and diabetes.Conclusions:By leveraging GWAS, ENCODE, gene co-expression networks, genomeand fecal bacteriasequencing data, using multiscale biology approaches, data will be presented to reveal common genetic and microbiome pathways between diabetes and AD. The study will clarify a potential common etiology of the two diseases, information that will help identify T2D cases that are likely to develop AD. The study will also inform about mechanisms for novel therapeutic approaches. F1-02-04 THERAPEUTIC EFFECTS OF INTRANASAL INSULIN AND INSULIN ANALOGUES ON COGNITION AND MRI MEASURES IN MILD COGNITIVE IMPAIRMENTAND ALZHEIMER’S DISEASE Suzanne Craft, Amy Claxton, Angela Hanson, Brenna Cholerton, Bryan Neth, Emily Trittschuh, Laura Baker, Wake Forest University School of Medicine, Winston Salem, North Carolina, United States; University of Washington, Seattle, Washington, United States; Wake Forest School of Medicine, Winston Salem, North Carolina, United States. Contact e-mail: suzcraft@wakehealth.edu