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Expression array analysis and interpretation

Expression array analysis and interpretation. The Cleveland Heart Study. John F Pearson, Anna P Pilbrow, Les McNoe, Wendy E Sweet, WH Wilson Tang, Richard W Troughton, A Mark Richards, Christine S Moravec and Vicky A Cameron. Mortality from heart attacks. IRELAND. UK. NZ.

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Expression array analysis and interpretation

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  1. Expression array analysis and interpretation The Cleveland Heart Study John F Pearson, Anna P Pilbrow, Les McNoe, Wendy E Sweet, WH Wilson Tang, Richard W Troughton, A Mark Richards, Christine S Moravec and Vicky A Cameron

  2. Mortality from heart attacks IRELAND UK NZ h2 = 0.49 +/-0.12; P=0.01 Left Main Fischer et al 2011 USA AUSTRALIA • Modifiable factors • Environment • Genetic • E x G FRANCE JAPAN (Levi et al Heart 2002 88:119-124)

  3. Cardiovascular Risk Locus: 9p21.3 Multiple GWAS identified 9p21.3 as the strongest risk factor for heart disease. Themechanismunderlying the association between9p21.3and heart disease isunknown. 9p21.3 “…the most highly replicated locus for heart disease identified to date…” McPherson et al Science 2007; Helgadottir et al Science 2007; WTCCC Nature 2007; Samani et al 2007 NEJM.

  4. Chromosome 9p21.3 58 kb risk locus 9p21.3 ANRIL Chr 9 CDKN2A CDKN2B rs1333049 • SNP rs1333049 associated with CAD • Uniformly associated in 7 GWAS (P < 0.05) • Pooled OR per C allele, 1.29 (1.22 -1.37; P = 0.0001) • Not homogeneous by haplotype (interaction, P = 0.0079) • Additive mode of inheritance (Hothorn, unpublished ) • Meta-analysis P = 6 ×10−10(OR 1.24, 1.20 - 1.29) • Shunkert et al, Circulation. 2008 April 1; 117(13): 1675–1684

  5. Cleveland Heart Study

  6. Cleveland Heart Study

  7. Cleveland Heart Study Multiple samples, multiple analyses Expression arrays: Christchurch CardioendocrineResearch Group

  8. Additive model Sample size to achieve 80% power at α = 5% Adapted from Freidlin et al, Hum Heredity 2002

  9. Additive model Sample size to achieve 80% power at α = 5% Adapted from Freidlin et al, Hum Heredity 2002

  10. Additive model • Using an additive model in array analysis • Limma(G. Smyth 2004) • Differential expression of probe(sets) or genes • GSEA(www.broadinstitute.org/gsea) • Concordant differences between sets of genes Adapted from Freidlin et al, Hum Heredity 2002

  11. Batch Effects “ComBat, an Empirical Bayes method, outperformed the other five programs by most metrics.” Chen et al, PLoS ONE 2011 ad break Combat: Johnson et al, Biostatistics (2007). Variance components Graph: adapted from: pvca.r Boedigheimer MJ et al 2008

  12. Additive model • Using an additive model in array analysis • Limma dmx= cbind(mean = 1, x = CHS$rs133049) > dmx mean x [1,] 1 1 [2,] 1 0 [3,] 1 1 [4,] 1 2 [5,] 1 1 [6,] 1 1 [7,] 1 1

  13. Additive model • Using an additive model in array analysis • Limma > tophits( …

  14. Additive model • Using an additive model in array analysis • GSEA • numerical .cls file • select “Pearson correlation” metric #numeric #rs1333049 1 0 1 2 1 1 1 … This takes a bit more work if you want to use GSEA.r

  15. GSEA KEGG • positive correlation with profile • 949 / 1848 upregulated • 0 FDR < 25% • 7 pvalue < 1% • 33 pvalue < 5% • negative correlation with profile • 899 / 1848 upregulated • 84 FDR < 25% • 31 pvalue < 1% • 106 pvalue < 5%

  16. GSEA KEGG • positive correlation with profile • 949 / 1848 upregulated • 0 FDR < 25% • 7 pvalue < 1% • 33 pvalue < 5% • negative correlation with profile • 899 / 1848 upregulated • 84 FDR < 25% • 31 pvalue < 1% • 106 pvalue < 5%

  17. GSEA KEGG Down with additional risk allele

  18. Heart Failure vs Donor > tophits( …

  19. Heart Failure vs Donor • positive correlation with Donors • 1712 / 2458 upregulated • 542  FDR < 25% • 114 pvalue < 1% • 347 pvalue < 5% • negative correlation with Heart Failure • 746 / 2458 upregulated • 0 FDR < 25% • 6 pvalue < 1% • 46 pvalue < 5%

  20. Heart Failure vs Donor Up in Donors/Down in HF

  21. Variability CV: sd/mean HF Donor

  22. Variability CV: sd/mean HF - D (HF + D)/2

  23. Variability CV: sd/mean HF - D (HF + D)/2

  24. Variability CV: sd/mean HF - D (HF+D)/2 decile

  25. High variability in HF KEGG Pathways identified with DAVID* Nature Protocols 2009; 4(1):44 & Nucleic Acids Res. 2009;37(1):1

  26. Low variability in HF KEGG Pathways identified with DAVID* Nature Protocols 2009; 4(1):44 & Nucleic Acids Res. 2009;37(1):1

  27. Low variability in HF KEGG Pathways identified with DAVID* http://www.genome.jp/kegg/

  28. Cardioendocrine Research Group Anna Pilbrow Vicky Cameron Richard Troughton Mark Richards Molecular Endocrinology Lab Foundation of Research, Science and Technology National Heart Foundation of New Zealand Cleveland Clinic Christine Moravec Wendy Sweet Wilson Tang Acknowledgements Otago Genomics Facility Les McNoe Department of Biochemistry Mik Black Chris Brown Molecular Pathology Lab Howard Potter

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