Leveraging the Exome Sequencing Project: Creating a WHI Resource Through Exome Imputation in SHARe. Chris Carlson on behalf of WHISP May 5, 2011

Transcription

1 Leveraging the Exome Sequencing Project: Creating a WHI Resource Through Exome Imputation in SHARe Chris Carlson on behalf of WHISP May 5, 2011

2 Exome Sequencing Project (ESP) Three cohort-based groups Heart disease (HeartGO, S Rich) Lung disease (LungGO, M Bamshad) Women s Health Initiative (WHISP, R Jackson) Two sequencing centers Broad Institute (BroadGO, S Gabriel/D Altshuler) University of Washington (SeattleGO, D Nickerson) Two additional GO components CHARGE-S (E Boerwinkle, targeted sequencing) WashUGO (T Graubert, cancer focus, whole genome seq) 2

3 ESP Major Goals: 1) To discover novel genes and mechanisms contributing to heart, lung, and blood disorders by pioneering the application of nextgeneration sequencing of the human protein coding regions across racially and ethnically diverse, richly phenotyped populations; 2) To establish robust methods to discover novel disease susceptibility genes by next generation sequencing and analysis of identified rare mutations; 3) To share these datasets, methods, and findings with the scientific community to enhance the diagnosis, management and treatment of heart, lung, and blood disorders.

4 ESP Specific Aims: To select samples for study from phenotypic extremes and/or subjects with highly familial phenotypes of clinically important heart, lung, and blood diseases; selection of samples to optimize power and to discover novel disease mechanisms; To establish robust and high quality exome sequencing for phenotype integration; To develop new analytical strategies (statistical and population genetic).

5 ESP Specific Aims: (Continued): To perform follow up evaluation of newly discovered genes/pathways/variants and to translate these findings into large populations, thereby assessing their public health impact; To share summary and individual data promptly through dbgap; To provide access to novel analytic methods; To develop approaches for personalized medical applications though genotype phenotype evaluation of rare variation; To develop guidelines for returning results to study participants. 5

6 WHISP GO Structure Ohio State University Contact PI: Becky Jackson FHCRC Co-PI: Riki Peters Co-PI: Chris Carlson Charles Kooperberg Li Hsu Alex Reiner Paul Auer UNC PI: Kari North Leslie Lange Ethan Lange Yun Li Chris Bizon Keri Monda Kira Taylor The WHI Sequencing Project (WHISP GO) coordinates the selection of samples from WHI for participation in the larger ESP project, and provides expertise in target phenotypes, statistical genetics, and genetic association analysis.

7 ESP Analytic Approach Extremes of cardiovascular and lung phenotypes to be analyzed to enrich for genetic effects Mendelianize Traits Compare extremes of trait distribution Example: Extreme BMI in AA Women BMI (N=178) BMI >40 (N=267)

8 BMI Statistical Analyses 277,108 called variants in 445 exomes Ongoing Statistical Analyses: Single variant (all SNPs with maf > 1%) Burden tests within gene (missense SNPs) T1 (N variants <1% MAF per gene per ind) Madsen-Browning (All variants but MAF weighted) SKAT (Allows for risk and protective in same gene) Functionally weighted analyses (nonsense, splice site, frameshift, predicted damaging missense)

9 Example T1 top hit (CPNE7) chr:pos function polyphen2 Obese Normal chr16: Missense Possibly damaging 7 5 chr16: Missense Benign 1 0 chr16: Missense Benign 7 0 chr16: Nonsense NA chr16: Missense Benign 4 0 chr16: Missense Benign 2 0 chr16: Missense Benign 1 0 Chr16: Missense Benign 1 0 Chr16: Missense Possibly damaging 0 1 Chr16: Missense Benign 1 0 Chr16: Missense benign 1 0 Chr16: Nonsense NA 0 1 Chr16: Missense Probably damaging 2 0 Chr16: Missense Benign 1 0 Chr16: Missense Possibly damaging 1 0 Chr16: Missense Probably damaging 1 0 Chr16: Missense Probably damaging 1 0 Chr16: Missense Probably damaging 6 1 Chr16: Missense Probably damaging 1 0 Chr16: Missense Possibly damaging 1 0 Chr16: Missense Benign Chr16: Missense Probably damaging /267 3/178

10 Imputation into WHI SHARe AA samples BMI findings in 267:178 real exomes are intriguing, but not conclusive (yet) 8,000 WHI AAs from SHARe have Affy 6.0 data available Can we impute exomes to SHARe? Enhanced N should improve power quite cost-effectively 10

11 Imputation Resources Reference panel (current) ~350 WHI AA with SHARe GWAS and exome ~350 Heart GO AA with CARe GWAS and exome ~700 AA altogether with Affy 6 GWAS and exome AA exome reference panel from ESP will exceed 1500 next year Target populations for imputation ~8000 WHI AA SHARe participants with GWAS ~8000AA CARe participants with GWAS 11

12 Merge Data for Reference Panel GWAS Exome Merged Genotypes

13 Imputing from Reference Panel Into GWAS Merged Genotypes Serve as templates Genotypes of remaining samples only on GWAS snps Impute the exome SNP values in the remaining samples

14 Merged Genotypes Imputation Steps Genotypes of remaining samples only on GWAS snps Phasing serve as templates Imputation Phased haplotypes

15 Limitations Idiosyncratic variants cannot be imputed Rare variant burden tests are not recommended Average imputation accuracy deteriorates when the rare allele has been seen less than 40 times Pilot reference panel of 1400 chromosomes: should allow accurate imputation to ~2.5% MAF Anticipated reference panel of 3000 chromosomes should allow accurate imputation to ~1.3% MAF

16 Opportunities Imputation accuracy is SNP-specific Some SNPs observed less than 40 times are still imputed with reasonable accuracy Poorly imputed SNPs will trend to null in analysis Single-SNP analyses are feasible Low MAF requires larger effect size to be adequately powered in SHARe

17 Virtual WHI Exome Resource Pilot (under way) Reference panel ~800 AA exomes Impute AA exomes in all 8000 WHI AA SHARe samples Analyze for BMI and Plans (within 12 months) Develop and QC larger ESP AA reference panel in concert with CARe Impute WHI SHARe genotypes and deposit to dbgap and WHI Encourage investigators to leverage data for additional analyses

18 ESP BMI Project Team Acknowledgements Co-chairs Chris Carlson Rebecca Jackson WHISP Riki Peters Alex Reiner Charles Kooperberg Kari North Leslie Lange Danyu Lin Paul Auer Keri Monda Kira Taylor Eric Whitsel Jonna Grimsby Judy Zhong Chris Bizon SeattleGO Suzanne Leal Jay Shendure NHLBI Deborah Applebaum- Bowden Phyllis Schalinsky Jacques Roussow NCBI Mike Feolo Coordinator Jenny Schoenberg HeartGO Larry Atwood Don Bowden Ida Chen Adrienne Cupples Josee Dupuis Caroline Fox Myron Gross Nancy Heard-Costa Jiankang Liu James Meigs Kari North Jim Pankow Jerry Rotter David Siscovick Nancy Swords Jim Wilson BroadGO David Altshuler Guillaume Lettre Laura Scott Shamil Sunyaev Ben Voight Cristen Willer Imputation Yun Li Yi Liu Leslie Lange Kari North