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ADWP1 - u sing EMRs and other datasets to identify the neuroimmunological signature of AD

ADWP1 - u sing EMRs and other datasets to identify the neuroimmunological signature of AD. Examples from metabolic disease. Heneka , Fink and Doblhammer (2015) Effect of Pioglitazone on the incidence of dementia Annals of Neurology doi : 10.1002/ana.24439.

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ADWP1 - u sing EMRs and other datasets to identify the neuroimmunological signature of AD

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  1. ADWP1 - using EMRs and other datasets to identify the neuroimmunological signature of AD Examples from metabolic disease

  2. Heneka, Fink and Doblhammer(2015) Effect of Pioglitazone on the incidence of dementia Annals of Neurology doi: 10.1002/ana.24439 • Thiazolidinedione (TZDs) – PPARg activators – used for treatment of T2DM • Mechanisms include gene regulation resulting in amelioration of insulin resistance but also suppress pro-inflammatory signals • Possible role in AD • Diabetes risk factor for AD • Insulin signaling and amyloid cascade • TZDs in animal models reduce Ab42 generation, reduce inflammatory markers, alter tau phos in insulin resistance animal models (APOE dependent) • Pioglitazone and Rosiglitazone widely used in T2DM • NB difference in brain penetrance • Rosiglitazone trials • Early studies suggested benefits on cognition in APOE dependent manner • Phase III failure

  3. Methods • Public health insurance medical records in Germany • 2004-2010 • 250k born before 1954 • Gender, age, ICD diagnosis (all episodes) and medications • Identified: • All cause dementia incidence 2006-2010 • Diabetes (ICD10 code E10/14 or antidiabetic medication) • Pioglitazone usage in numbers of 3-month bins • Variable determination: • 1) No diabetes; 2) Diabetes + no pioglitazone (PIO=0); • 3) Diabetes + PIO<8; 4) Diabetes + PIO=>8 • Controlled/confounds: • Age, sex • Other meds (eg rosiglitazone, metformin, insulin) • Cardiovascular disease • Statistics • Incidence dementia dependent on 1-4 • Kaplan Meir survival and hazard ratios

  4. Results • Public health insurance medical records in Germany • 633,418 person years • 13,177 incident dementia cases • Reduced incidence of dementia in those on Pioglitazone • Non-diabetic incidence = 18 new cases per 1000 patient years • Diabetes + No PIO = 28 • Diabetes low PIO = 20 (ns) • Diabete high PIO = 7 • Risk reduction of 90% • Rosiglitazone – non-significant reduction relative to diabetes, no TZD • Dementia free at end of observation period: • 91.7% Non-diabetics • 86.7% diabetics, no PIO • 90.4% diabetics, low PIO • 95.5% diabetics, high PIO

  5. Modeling – 47% risk reduction

  6. Zhang, Luo, Xi and Rogaeva (2015) Drug repositioning for Diabetes based on ‘omics’data miningPLoS ONE doi: 10.1371/journal.pone.0126082 • Drug repositioning through ‘disease focus’ • Expression pattern comparison (egcMAP) • Text mining • Networks analysis; GWAS, OMIM etc • Objective: • Use proteomics and metabolomics as well as GWAS for disease focus repositioning • Methods • Literature search and data extract; PubMed • GWAS; genes, SNPs, ethnicity, phenotype (diabetes type) • Proteomics; proteins, direction, methods, sample type, phenotype • Metabolomics; metabolites, direction, methods, sample type, phenotype • Human Metabolome Database extract; enzymes / transporters associated with known diabetes metabolites • Metabolite – protein network construction with cytoscape • Therapeutic Target Database to identify diabetes risk proteins with drugs in development • cMAP analysis

  7. Fig 2. Diabetic metabolite-protein network. The Cytoscape tool was used to generate the diabetes associated metabolites and their connections to metabolic enzymes/transporters. Overall 1660 diabetes related metabolite-protein pairs were established and visualized. Green triangles represent metabolites associated with diabetes, and red circles represent proteins associated with metabolites based on HMDB database.

  8. Results • Five proteins are known drug targets • Alpha-2A adrenergic receptor, insulin, lysophatidic acid transferase, glucokinae, PPARg) • 22 drugs in clinic trials or market • Thirty proteins are not known to be drug targets for diabetes • 167drugs in clinic trials or market • Connectivity mapping (58 drugs available) • No cMAP data 38 • cMAP data but not links 11 • cMAP links to anti-diabetic drugs or risk compounds 9 • Phenoxybenzamine, Niflumic acid, Perhexiline – associated with resveratol (ie glucose metabolism) • Idazoxan, d-cycloserine, - associated with gliclazide (anti-diabetic drug) • Diflorasone– negatively associated with Steptozocin (induces diabetes) • Diflunasil – associated with glimepride (anti diabetic drug) • Valdecoxib – assoicated with metformin (anti-diabetic drug) Discussion • Diflunisal, nabumetone, niflumic acid, valdecoxib – common target in prostaglandin G/H synthase 2 (COX2). Suggests novel target for diabetes

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