ppmi genetics Andy Singleton Laboratory of Neurogenetics, NIA, NIH

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Presentation transcript:

ppmi genetics Andy Singleton Laboratory of Neurogenetics, NIA, NIH singleta@mail.nih.gov

ANDREW SINGLETON (NIA) ASHLEY WINSLOW (PFIZER) BRIAN FISKE (MJFF) CLIONA MOLONY (PFIZER) Clotilde mannoury-la-cour (SERVIER) DAVE STONE (MERCK) Giulia Malferrari (BIOREP) HONG WANG (LILLY) HU Xiaolan (BMS) jean-christophe corvol (Hôpital Pitié-Salpêtrière) Jesse cedarbaum (BIOGEN) KALPANA MERCHANT (TRANSTHERA) Leanne munsie (LILLY) Kenneth Vielsted Christensen (LUNDBECK) Khanh-Dung nguyen (BIOGEN) MARCEL VAN DER BRUG (GENENTECH) MIKE NALLS (NIA) Paola Casalin (BIOREP) Pierandrea Muglia (UCB) Stefan mcdonough (PFIZER) STUART FACTOR (EMORY) SUSAN BRESSMAN (BETH ISRAEL) TATIANA FOROUD (INDIANA UNIVERSITY) Vera kiyasova (SERVIER)

Genetic data ImmunoChip (200,000 variants) (complete and @LONI) NeuroX (260,000 variants) (complete and @LONI) APOE, DAT vntr, GBA sequencing (complete and @LONI) Exome sequencing (complete and @LONI) SNCA resequencing (complete and @LONI: Farrer lab) Whole genome sequencing (complete and @LONI) DNA methylation (baseline complete and @LONI) RNA sequencing (ongoing: Jensen lab) NeuroArray genotyping ancillary cohorts - ongoing

Understand the pathobiology Target Identification Identify the locus Find the gene Characterize & Predict Treatment

Current GWA meta-analysis to identify new loci Identify the locus Current GWA meta-analysis to identify new loci

Current GWA meta-analysis to identify new loci Identify the locus Current GWA meta-analysis to identify new loci Fifth stage GWA meta-analysis to identify new loci 2nd draft of manuscript underway and soon sent for submission All available PD GWAS data in discovery series 56,382 cases (or proxy cases) + 1,417,654 controls @ 11,477,548 high quality imputed SNPs (MAF > 0.1%) Meta-analysis of 17 studies 126 independent risk loci at P < 5E-8 49 novel loci

Current GWA meta-analysis to identify new loci Identify the locus Current GWA meta-analysis to identify new loci Fifth stage GWA meta-analysis to identify new loci

WGS DATA 4,763 samples (+502 ongoing), comprised of 421 de novo PD (PPMI) 196 controls (PPMI) 64 SWEDD (PPMI) 65 Prodromal (PPMI) 136 Genetic cohort affected (PPMI; + 112 ongoing) 74 Genetic cohort unaffected (PPMI; +180 ongoing) 26 Genetic registry (PPMI; +210 ongoing) 802 cases (PDBP) 726 cases (HBS) 771 LRRK2 case/control (MJFF) 772 cases (NIH clinic) 323 control brains (LNG-NABEC) 387 path confirmed PD (LNG)

Understand the pathobiology Target Identification Identify the locus WGS data GWA results WES results Understand the pathobiology Target Identification Identify the locus Find the gene Characterize & Predict Treatment

Smell Family History Sex Age Genetic Risk Score (~30 variants)

Smell Family History Sex Age MACHINE LEARNING Genetic Risk Score (~1000 variants)

Age at onset – implicates alpha-synuclein biology

Understand the pathobiology Target Identification Identify the locus WGS data GWA results WES results Understand the pathobiology Target Identification Identify the locus Find the gene Characterize & Predict Treatment genetic data AMP-PD

FOUNDIN-PD

FOUNDIN-PD Treatment AMP-PD WGS data GWA results FOUNDIN-PD WES results Understand the pathobiology Target Identification Identify the locus Find the gene Characterize & Predict Treatment genetic data AMP-PD

THANK YOU PPMI has become the high quality reference group in our laboratory – the extremely high quality and depth of the data means that we can set quite accurate estimates for effect sizes and look beyond simple risk.