1. ppmi genetics Andy Singleton Laboratory of Neurogenetics, NIA, NIH

2. 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)

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

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

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

6. 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 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

7. 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

8. 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; 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)

9. 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

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

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

12. Age at onset – implicates alpha-synuclein biology

13. 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

14. FOUNDIN-PD

15. 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

16. 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.