Translational genomics research space

1. ™ ClinSeq: Piloting Large-Scale Medical Sequencing for Translational Genomics ResearchLeslie Biesecker, M.D.National Human Genome Research Institute, NIH

2. Translational genomics research space

3. Genetic architecture of disease Rare variants Common variants

4. Genetic architecture of disease Rare variants Common variants The only way to assess both is by sequencing

5. Building a clinical genomics research program • Develop a robust infrastructure for the generation and use of genomic data in clinical research • Genomically dissect a phenotype with complex genetic architecture • To understand how to interact with subjects re genomic data

6. Initial approach • 1,000 subjects recruited from general population • Initial phenotype for atherosclerosis • Consented for follow-up sequencing • Consented for re-contact for phenotyping • Sequence ~400 candidate genes • Selected for many reasons • Consented for WGS • Associate variants with phenotypes • Return results • A goal of the study is to learn from the subjects which results we should return

8. Progress – the numbers • Enrollment began January, 2007 • 590 patients enrolled Feb. 1 • 354 DNAs sequenced – PCR/3730 • 326 ClinSeq subject samples • 28 HapMap samples • 219 genes • 3,500 genomic target sequences • > 1.7 M sequence reads to date ~825,000,000 bp of bidirectional genomic sequence

9. Quality measures • Sample ID spike • Non-human genomic clone spike • HapMap control DNAs • 1/30 ClinSeq DNAs • Manual review of traces • CLIA sample confirmation

10. Visual quality % coverage Q20

11. Yield snapshot • Coverage • Sample 140 genes • Targeted 402,907 bp ROI • Yielded 357,912 bp – 88.8% design coverage • Variants • Total 3,353 • Adjust sample coverage to exactly 500 chromosomes • Variants 2,271 • Extrapolate false positive rate • 1,984 variants

12. Uncommon alleles common

13. Data flow

14. Sub-projects underway Positive controls Validating recent assoc. of rare variants & phenotypes Sequencing genes under GWAS peaks for rare, high penetrance variants Testing associations of candidate genes with phenotype Control cohort for other sample sets Search for miRNA variants cDNA sequencing pilot to measure expression & isoforms Capture method refinement Patient motivations and preferences for results of medical sequencing Testing automated vs. manual pedigree acquisition

15. Positive result example • 65 yo female • High cholesterol diagnosed at 25 years • RX: atorvastatin, ezetimibe, hctz, lisinopril, niacin • Coro Ca++ 1,726 • Chol 172, Trig 50, HDL 75, LDLd 88 • LDLR p.Y188X • Family members diagnosed & treatment started

16. Replications • ANGPTL4 – (decr trigs) • 30 NS variants, one novel, p.E40K x 3 • Not quite significant, await full sample • SLC12A3, SLC12A1, & KCNJ1 (decr BP) • 15 NS variants • Not assoc with decr BP

17. Penetrance & frequency Penetrance Frequency

18. Penetrance & frequency We understand this work Penetrance Frequency

19. Penetrance & frequency We understand this work Explore this Penetrance Frequency

20. Penetrance & frequency We understand this work Explore this Penetrance This is probably not clinical genetics! Frequency

21. Classic translational paradigm Generate Hypothesis Sort Phenotype Apply Assay Correlate

22. Generate Hypothesis Sort Genotype Correlate Apply Assay Novel translational paradigm Generate Hypothesis Sort Phenotype Apply Assay Correlate (Sort) Phenotype

23. Implications • Large numbers of patients are interested • Possible to consent subjects to WGS • Clinically relevant results can be sifted • Subjects can receive and act upon results • Going forward: • Next-Gen: Exome -> WGS • More diverse population • Discovering associations of variants and phenotype • Learning subject’s view in real setting

24. ™ Collaborators • NISC • Jim Mullikin, Bob Blakesly, Gerry Bouffard, Praveen Cherukuri, Pedro Cruz, Nancy Hanson, Morgan Park, Alice Young • NHGRI • Eric Green, Flavia Facio, Stephanie Brooks, Amy Linn, Paul Gobourne, Jennifer Johnston, Teri Manolio, Jamie Teer, Clesson Turner, Alec Wilson • NHLBI • Richard Cannon, Andrew Arai, Paul Hwang, Toren Finkel, Vandana Sachdev, Bob Shamburek • NIDDK • Monical Skarulis, Kristina Rother • NIHCC • Alan Remaley