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Ulrike Peters, Fred Hutchinson Cancer Research Center, University of Washington

Fine-mapping of obesity GWAS loci using the Metabochip in PAGE (Population Architecture using Genetics and Epidemiology). Ulrike Peters, Fred Hutchinson Cancer Research Center, University of Washington. Design of Metabochip for anthropometric related traits.

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Ulrike Peters, Fred Hutchinson Cancer Research Center, University of Washington

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  1. Fine-mapping of obesity GWAS loci using the Metabochip in PAGE (Population Architecture using Genetics and Epidemiology) Ulrike Peters, Fred Hutchinson Cancer Research Center, University of Washington

  2. Design of Metabochip for anthropometric related traits • Anthropometric related MetaboChip content • Replication • 13k SNPs for BMI, WHR, WC, height, % fat mass • Fine-mapping • 41 regions, 26k SNPs

  3. Current Study Population in PAGE and Collaborative Studies

  4. 16q12.2/FTOStrongest GWAS finding for obesity-related traits Submitted to PLoS Genetics 2012

  5. 16q12.2/FTO Association with BMI 1,529 SNPs across 650kb r2 based on AA r2 based on EA

  6. Bioinformatic Characterization by Praveen Sethupathy, UNC • Candidate intronic regulatory elements: • rs11642015, rs17817497, rs3751812, rs17817964, rs62033408, and rs1421085 • Highly sequence-conserved elements among vertebrates: rs3751812 and rs1421085 • Predicted to have allele-specific binding affinities for different transcription factors: • rs11642015 ->Paired box protein 5 (PAX5) • rs1421085 ->Cut-like homeobox 1 (CUX1), previously implicated in the transcriptional regulation of FTO (Stratigopoulos, J BiolChem 2011)

  7. Definition of Significance Levels • Different alpha-levels for different aims: • Fine-mapping regions: • Fine-mapping of GWAS index SNPs • Adjust only for SNPs that are correlated with GWAS index SNP at r2>0.2, >0.5, >0.8 in population that identified GWAS index SNP (mostly EA or Asian) • Accounting for correlation among SNPs, e.g. by permutation or estimate # of bins • Search for second independent signals • Adjust for all other SNPs in the fine-mapping region (excluding those included in #1) while accounting for correlation • Replication/generalization • Pleiotropy– or analysis across the Metabochip

  8. FTO region with correlation in EA In total 88 SNPs are correlated at r2>0.2 with 9 GWAS index SNPs in EA (all dotes that are red, yellow, green or light blue) GWAS hit 1 GWAS hit 2 GWAS hit 3

  9. Example FTO Region

  10. Based on ~21,000 subjects (ARIC, HyperGEN, GenNet, MEC, WHI)

  11. Summary for primary signals

  12. 11p14.1/BDNF,LIN7C,LGR4 Correlation based on EA with 2 different GWAS index SNPs

  13. 11p14.1/BDNF,LIN7C,LGR4 Correlation based on AA with one GWAS index SNP and most significant SNP in the region

  14. Summary for secondary signals

  15. Decisions for Next Paper(s) • Study populations • Focus on AA, AA and Asian or multiethnic panel? • Data freeze • Outcome • Two separate papers for BMI and WHR/WC • Metabochip content • Focus on fine-mapping regions or entire Metabochip content • Note, some of the most significant findings are outside of the BMI regions, but require more complex follow up • Overall timing • We need to be fast to avoid being scooped by other groups

  16. Study population for next papers

  17. Within HDL region # 3 rs6712203 is most significant SNP 1.7 x 10-10 Correlation between BMI and HDL ~ 0.2

  18. GWAS hit in HDL region #3 is rs10195252 BMI HDL lnBMI ~ SNP + HDL + age*sex + PC1 + PC2 HDL ~ SNP + BMI + age*sex + PC1 + PC2 Note results based on 11,792 subjects with HDL and BMI data (~55% of all with BMI in Manhattan plot)!

  19. Extra slides

  20. Example FTO region: Fine-mapping of GWAS index SNPs • 1,529 SNP genotyped across 640kb region • Correlation with 9 index SNPs in CEU (EA) 1000 Genome Project pilot: • r2>0.2 = 88 SNPs on Metabochip(r2>0.5 = 72; r2>0.8 = 59 SNPs) • Permute random normal distributed phenotype and run analysis of all 97 (88+9) SNPs 10,000 times to compute the # of independent tests =>30 • Nominal p-value * number of independent test = multi-comparison adjusted p-value (e.g. 2.4E-04*30=7.2E-03) OR • Alpha of 0.05 /# of independent test = multi-comparison adjusted alpha level (e.g. 0.05/30 = 0.002)

  21. Example FTO region: Search for second independent signals • 1,529 SNP genotyped across 640kb • Exclude 97 SNPs included in fine-mapping of GWAS index SNPs (1,529-97 = 1,432) • Repeat permutation for all SNPs in entire region => 1109 independent tests There are 1,432 SNPs that are not correlated with GWAS index SNPs in EA (r2<0.2, dark blue dots) These result in 1,109 independent tests

  22. Exploration if most significant BMI locus is independent from HDL BMI HDL lnBMI ~ SNP + HDL + age*sex + PC1 + PC2 HDL ~ SNP + BMI + age*sex + PC1 + PC2 Note results based on 11,792 subjects with HDL and BMI data (~55% of all with BMI in Manhattan plot)!

  23. Same as slide before but not mutually adjusted for HDL and BMI BMI HDL lnBMI ~ SNP + age*sex + PC1 + PC2 HDL ~ SNP + age*sex + PC1 + PC2 Note results based on 11,792 subjects with HDL and BMI data (~55% of all with BMI in Manhattan plot)!

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