What´s next after the genes?

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In this presentation, some pitfalls and challenges of the genetics of autoimmune diseases are reviewed, and an approximation to the future of research in this field is presented (Further information at http://www.biomedcentral.com/1741-7015/11/197)

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What´s next after the genes?

  1. 1. Juan-Manuel Anaya Center for Autoimmune Diseases Research Universidad del Rosario Bogota, Colombia
  2. 2. What’s Next After the Genes for Autoimmunity? • How important is genetics in autoimmune diseases? • What have we learned about genetics of autoimmune diseases? • Pitfalls and challenges of complex trait analysis
  3. 3. Pathophysiology of Autoimmune Diseases Anaya JM. Autoimmun Rev 2012, 11:781-784.
  4. 4. 5-100.5-12-412-15Rheumatoid Arthritis 20-400.22-524-57SLE 200.13-525Multiple Sclerosis 150.4630-50Type 1 DM Non-twins Siblings Monozygotic Twins s ** Population Prevalence (%) Concordance (%)* Disease Wandstrat & Wakeland. Nat Immunol 2001;2:802-9. How Important is the Genetic Predisposition on Susceptibility to Autoimmune Diseases? Concordance and Familial Aggregation () * Concordance: the presence of the same trait in both members of a pair of twins, or in sets of individuals. **Aggregation (s): relative risk to siblings. Disease prevalence in siblings of affected / Disease prevalence in general population.
  5. 5. Function Gene FUNCTIONAL Phenotype Mapping POSITIONAL Gene Phenotype Mapping Function Genome-wide screen or candidate gene? Genome-wide screen • Hypothesis-free • High-cost: large genotyping requirements • Multiple-testing issues Possible many false positives, fewer misses Candidate gene • Hypothesis-driven • Low-cost: small genotyping requirements • Multiple-testing less important Possible many misses, fewer false positives
  6. 6. Autoimmune Diseases with Significant Genetic Variants http://www.genome.gov/gwastudies http://www.ncbi.nlm.nih.gov/gap
  7. 7. Why limited success after all? • ~ 9000 papers on SLE AND Genetics • ~ 50 genes involved and replicated • Only around 20-30% of the inherited risk for SLE can be explained at present. • Most of the common variants individually or in combination confer relatively small increments in risk (1.1- to 1.5-fold) and explain only a small proportion of heritability. 2012:522
  8. 8. HLA discloses the strongest association with autoimmune diseases Lessard CJ et al. Nat Genetics 2013 (in press) MS: International Multiple Sclerosis Genetics Consortium. NEJM 2007 30;357:851-62. Hom G et al. NEJM 2008;358:900 Wellcome Trust Case Control Consortium Nature 2007; 447: 661. Nature 2010; 464: 713. Sjögren's Syndrome Multiple Sclerosis Systemic Lupus Erythematosus Rheumatoid Arthritis
  9. 9. What’s Next After the Genes for Autoimmunity? • How important is genetics in autoimmune diseases? • What have we learned about genetics of autoimmune diseases? • Pitfalls and challenges of complex trait analysis
  10. 10. Limitations of Complex Trait Analysis • Epistasis and gene interactions • Genetic heterogeneity • Pleiotropy • History of mutations/polymorphisms • Population stratification • Sample size • Refined phenotype (and genotype)
  11. 11. Epistasis is a form of gene interaction in which one gene masks the phenotypic expression of another. Interactions between genes at different loci that affect the same phenotype. Mani et al. Proc Natl Acad Sci U S A. 2008;105:3461-6. Gene Interactions
  12. 12. IRF5 Interaction Network
  13. 13. Limitations of Complex Trait Analysis • Epistasis and gene interactions • Genetic heterogeneity • Pleiotropy • History of mutations/polymorphisms • Population stratification • Sample size • Refined phenotype (and genotype)
  14. 14. Limitations of Complex Trait Analysis • Epistasis and gene interactions • Genetic heterogeneity • Allelic heterogeneity Different mutations within the same locus result in the same phenotype • Locus heterogeneity Different genes cause the same clinical syndrome
  15. 15. Wandstrat & Wakeland. Nat Immunol 2001;2:802-9. How many genes are needed for autoimmunity to occur?
  16. 16. Limitations of Complex Trait Analysis • Epistasis and gene interactions • Genetic heterogeneity • Pleiotropy • History of mutations/polymorphisms • Population stratification • Sample size • Refined phenotype (and genotype)
  17. 17. Genetic Pleiotropy single causal variant Solovieff et al. Nat Rev Genet. 2013;14:483-95. Different causal variants colocalizing in same gene and tagged by the same genetic variant Different causal variants colocalizing the same gene
  18. 18. DR4 OR: 3.9 (2.89-5.27) DRB1*0405 OR:7.2 (3.36-15.27) DQ2 OR:1.93 (1.09-3.41) DQB1*0201 OR:2.32 (1.12-4.8) DRB1*0301 OR:3.63 (1.25-10.47) Common Autoimmune HLA Alleles in Latin America Cruz-Tapias et al. Autoimmune Dis. 2012
  19. 19. Rheumatoid Arthritis Colombians Ramírez et al. Clin Exp Rheumatol 2012 Systemic Lupus Erithematosus Colombians Anaya et al. Genes Immun. 2005;6:628. Ramírez et al. Clin Exp Rheumatol 2012 Argentinians Orrú et al. Hum Mol Genet 2009;18:569. PTPN22 (1858 T) is a Pleiotropic Autoimmune Allele in Latin Americans Sjögren´s Syndrome Colombians Anaya et al. Genes Immun. 2005;6:628. Type 1 Diabetes Colombians Anaya et al. Genes Immun. 2005;6:628-31. Brazilians Chagastelles et al .Tissue Antigens 2010;76:144. Rassi et al. Ann N Y Acad Sci. 2008;1150:282.
  20. 20. Courtesy of Leah C. Kottyan IRF5 is a Pleiotropic Autoimmune Gene Reported IRF5-TNPO3 associations
  21. 21. Limitations of Complex Trait Analysis • Epistasis and gene interactions • Genetic heterogeneity • Pleiotropy • History of mutations/polymorphisms • Population stratification • Sample size • Refined phenotype (and genotype)
  22. 22. PTPN22 1858C>T Distribution in Europe and Association with Rheumatoid Arthritis Totaro et al. PLoS One. 2011;6:e24292.
  23. 23. Ancestry in Latin America Sans M. Hum Biol 2000;72:155. 503711Cuba 80<10<10Peru 80<10<10Ecuador >80<10>10Bolivia <4010>50Venezuela 25.96.567.5Argentina 43~057Chile 201565Brazil 1-207-15>80Uruguay 56341Mexico >15>15<60Colombia Amerindian (%) African (%) European (%) Country
  24. 24. Limitations of Complex Trait Analysis • Epistasis and gene interactions • Genetic heterogeneity • Pleiotropy • History of mutations/polymorphisms • Population stratification • Sample size • Refined phenotype (and genotype)
  25. 25. Stratification The presence of a systematic difference in allele frequencies between subpopulations in a population due to different ancestry, especially in the context of association studies.
  26. 26. Limitations of Complex Trait Analysis • Epistasis and gene interactions • Genetic heterogeneity • Pleiotropy • History of mutations/polymorphisms • Population stratification • Sample size • Refined phenotype (and genotype)
  27. 27. Statistical Power and Sample Size MAF Prevalence Association (NA) 0.05 0.01 2,278 0.05 0.20 2,448 0.20 0.01 659 0.20 0.20 700 MAF = Minor allele frequency NA = Number of case-control pairs Odds Ratio = 1.5 Roeder et al. Am J Hum Genet. 2006;78:243-52.
  28. 28. Limitations of Complex Trait Analysis • Epistasis and gene interactions • Genetic heterogeneity • Pleiotropy • History of mutations/polymorphisms • Population stratification • Sample size • Refined phenotype (and genotype)
  29. 29. Refining the Phenotype-Genes • Make the effect of certain genes in the sample more easily detectable • Genetic effects may be stronger for extremes of the risk factor distribution – restrict sample to people with onset at a very young or very old age • Genetic effects may be stronger for particular presentations – restricting sample to patients with rheumatoid arthritis and anti-CCP – restricting sample to SLE with nephropathy
  30. 30. Refining the Phenotype-Environment • Minimize effect of known environmental confounders – restrict sample to RA and nonsmokers – restrict sample to EBV negative patients • Collect data in a genetically homogenous population such as a particular ethnic group or genetically isolated population – Reduce the number of genes contributing to the phenotype (i.e. the Paisa community, Colombia)
  31. 31. Post-Genomics and P4 Medicine What’s Next After the Genes for Autoimmunity?
  32. 32. Post-Gen“omics” Post-genomics evaluate patterns in how genes are transcribed into RNA (transcriptomics), in the way genes are expressed as proteins (proteomics), in how they influence the chemicals that control the cellular biochemistry and metabolism (metabolomics).
  33. 33. Hood L. Annu Rev Anal Chem (Palo Alto Calif). 2008;1:1-43.
  34. 34. Overt RAGenotype Prediction of Autoimmune Diseases The case of Rheumatoid Arthritis Pre-clinical RA Severity? HLA-DRB1*0404 TNF2 PTPN22 Tobacco Anti-CCP Familial Autoimmunity T’
  35. 35. Tebbutt et al. Chest 2007;131:1216 ©2007 by American College of Chest Physicians Personalized Medicine 1. Informed consent 2. Blood (or even hair) sample 3. DNA extraction 4. Genotyping 5. Analysis of SNPs 6. Bioinformatic tools. 7. Structural and functional correlation of the genotype 8. Plan of action. Predict the biological and treatment implications
  36. 36. • Deciphering the genetics of complex diseases remains challenging. • Drastic technologic advances are leading research to organize clinical genomic multidisciplinary approaches to understand the nature of human biological systems. • Making accurate predictions for autoimmune diseases is an ambitious goal. • Personalized medicine is committed to survey, monitor and diagnose risks to provide patients with a specific treatment, taking into account their particular genetic profile. What’s Next After the Genes for Autoimmunity? Castiblanco J, Arcos-Burgos M, Anaya JM BMC Medicine 2013

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