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O5‐05‐01: DETECTION AND DIFFERENTIATION OF MILD COGNITIVE IMPAIRMENT, ALZHEIMER'S AND PARKINSON's DISEASES BY ANALYSIS OF BRAIN‐ENRICHED MICRORNAS IN PLASMA
Author(s) -
Sheinerman Kira,
Umansky Samuil,
Tsivinsky Vladimir,
Keegan Andrew,
Abdullah Laila,
Crawford Fiona
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.2014.04.500
Subject(s) - cognitive impairment , microrna , parkinson's disease , neuroscience , psychology , medicine , cognition , disease , biology , genetics , gene
Background: Recent genome-wide association studies (GWAS) have identified around 20 variants as late-onset Alzheimer’s disease (LOAD) susceptibility loci in whites. In addition to these single loci tests, it is important to detect and understand combined effects of multiple associated genes on LOAD. We performed a preliminary network analysis incorporating human protein-protein interaction database mined from 12 different sites including BIND, BioGRID, IntAct etc. to the HapMap2-imputed combined ADGC data set. Post-GWAS, this helps researchers to prioritize functionally related genes and networks that are of the highest biological relevance underlying the pathogenesis of LOAD. Methods: We combined HapMap2-imputed data sets from 15 studies after performing strict quality control. We performed a case-control association for LOAD adjusting for population sub-structure and study sites on a set of 19,692 unrelated individuals using PLINK and those results were used to perform a gene-wide analysis using VEGAS. The gene-wide association results were then integrated into the human protein-protein interaction network using a dense module searching (DMS) method to identify candidate genes or sub-networks for LOAD. We then attempted to functionally validate candidate genes from this network in vivo using a transgenic C. elegans model of Ab 1-42 toxicity. Results: The network analysis identified several of the known LOAD risk loci as well as other genes such as ALB, BAG1 and UBC to be strongly associated with LOAD. RNAi knockdown of the C. elegans orthologs of UBC (ubq-1 or ubq-2) significantly accelerated the age-associated onset of Ab 1-42 toxicity. Conclusions:We were able to identify a set of significant modules and candidate genes, including some well-studied genes not detected in the single-marker analysis of GWA studies for LOAD, and to demonstrate a role for two of these genes as modifiers of Ab toxicity in C. elegans. This approach provides complementary data to a GWAS of a complex disease phenotype by incorporating biological knowledge derived from protein-protein interactions and allows for initial functional validation in vivo. Further functional enrichment analysis is needed to determine whether these novel loci may provide targets for interventions to ameliorate LOAD. THURSDAY, JULY 17, 2014 ORAL SESSIONS O5-05 BIOMARKERS: NOVEL MOLECULAR FLUID MARKERS