Inés Barroso-Lo último en obesidad
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'Lo último en obesidad'. Este es el título del Simposio Internacional que organizamos en la Fundación Ramón Areces los días 1 y 2 de diciembre de 2015. En colaboración con la Fundación General CSIC, reunió a algunos de los mayores expertos en la materia para analizar cómo reducir este grave problema de salud pública.
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Inés Barroso-Lo último en obesidad
- 1. Susceptibility Gene Identification in Obesity and Type 2 Diabetes Inês Barroso Is the glass half-empty or half-full? Wellcome Trust | MRC
- 2. Genes and Environment in Disease Monogenic Type 2 Diabetes Obesity Infectious Disease Environment Genes
- 3. Environmental Component Modern Diet Physical (In)Activity
- 4. Genetic Component • In humans heritability of fat mass = 40-70% • Percentage heritability of fat mass is very conserved across species • Different forms of obesity: • Common “garden” variety obesity – complex trait; • Extreme forms of obesity – Mendelian-like inheritance (<1% of prevalence of obesity) – Very early onset – Degree of obesity much greater – Likely to be more “genetically loaded” , i.e., rarer mutations of higher penetrance
- 5. Disease Gene Identification • Loci for Mendelian forms of obesity found – Severe early onset forms of obesity (leptin, leptin receptor, MC4R, POMC, PCSK1, SIM1), syndromic forms of obesity (Bardet-Biedl, Alstrom, etc.) However… • Complex Diseases (T2D, common obesity) > 10 years of little progress – Linkage and candidate gene studies did not yield many robustly associated loci – Studies were usually small and underpowered – Statistically lenient – Lots of “false positives”
- 6. Changing Genetic Approaches I Family Linkage ob/ob– leptin deficient mouse Zhang et al. Nature, 1994 Human LEP orthologue Re-sequence in affected individuals Disease Gene Mutation Candidate Gene 500K-1M variants 1K- 500K individuals Populations or affected (cases) – unaffected (controls) Variant association with disease GWAS
- 7. Changing Genetic Approaches II GWAS 1 GWAS 2 GWAS 3 GWAS… Large Scale Meta-Analysis International GWAS Consortia + Denser/ Custom Arrays GWAS+ Imputation Dense Reference Panel Whole-Exome and Whole- Genome Sequencing
- 8. 2000 2002 2003 2004 2005 2006 2007 2008 20092001 Genetic Landscape of Common Obesity pre- GWAS GWAS era begins GWAS Meta- Analysis era begins Large-scale custom arrays available- metabochip 2010
- 9. First Obesity Locus Science, 2007 PLOS Genetics, 2007 Nature Genetics, 2007 No additional variants robustly associated with BMI identified
- 10. Second Common Obesity Locus Nature Genetics, 2008 Required: >16K samples in initial analysis; replication in additional ~90K samples; association study in population of different ancestry
- 11. Obesity Genetic Loci Post-GWAS Susceptibility loci for BMI/ obesity increased from 0 to ~100 GWAS era begins GWAS Meta- Analysis era begins Large-scale custom arrays - metabochip
- 12. GWAS Catalogue Filtered Obesity Data up to May 2014 https://www.ebi.ac.uk/gwas/home • 39 Loci in the catalogue; • Since then total number of BMI/ obesity associated loci ~97
- 13. What have we learned? Architecture: "the complex or carefully designed structure of something” Genetic Architecture Biological Insights Clinical Applications
- 14. Genetic Architecture Blue – previously known Red – new loci • >90 loci to date • Most are common alleles (MAF>5%) with small effect sizes • As sample sizes increase can detect rarer alleles or those with even more modest effects • Most risk alleles map to non-coding region of the genome • FTO still largest effect size - ~16% European population AA homozygous ~3kg heavier and 1.67- fold increased odds obesity (BMI>30)Locke et al., 2015
- 15. Phenotypic Variance Explained Locke et al., 2015
- 16. Risk Alleles and BMI Locke et al., 2015
- 17. Biological Insights • Genes within BMI-associated loci are enriched for expression in brain and central nervous system • Suggests genes are important in central control of appetite and energy expenditure • We see overlapping signals in loci mapping close to established genes involved in monogenic/ severe obesity: MC4R, POMC, SH2B1 , BDNF, BBS4 Locke et al., 2015
- 18. From BMI to Severe Childhood Obesity…
- 19. Severe Early Onset Obesity • More heritable – More Mendelian-like – Less time for environmental effects – Identify genes with more penetrant alleles with larger effects on phenotype • Questions – Is the genetic architecture of extreme obesity the same as common obesity? – Can it teach us something about genes/ pathways involved in energy homeostasis more generally?
- 20. Severe Childhood Onset Obesity Project (SCOOP) • Clinical extremes • BMI > 3 standard deviations above the mean • Age of onset < 10 years old • UK white patients • MC4R pre-screened in all patients • Additional known causes of obesity excluded in some patients Collaborator: Sadaf Farooqi
- 21. Severe Childhood Obesity GWAS on ~1,500 obese children and ~5,400 controls
- 22. Leptin Receptor Gene (LEPR) • Known monogenic obesity locus • Intermediate frequency allele (6% MAF in CEU HapMap) • Supports the idea that both common and rare variants can be involved in the pathogenesis of obesity at some loci Wheeler et al., 2013
- 23. BMI loci in SCOOP • BMI results from Speliotes et al. 2010 (Nature Genetics) G ANTG ANT C O N S O R T I U M p < 5x10-8 5x10-8 ≤ p < 1x10-4 1x10-4 ≤ p < 0.01 0.01 ≤ p < 0.05 0.05 ≤ p < 1 Wheeler et al., 2013
- 24. UK10K 4,000 Cohort Samples Whole Genome Sequenced ~6x depth 3,000 Autism and Schizophrenia 2,000 Obesity 1,000 Rare Disease 6,000 Diseased Case Samples Whole Exome Sequenced ~80x depth 1,000 Severe Childhood Obesity Aim: Investigate the role of additional low- and rare-frequency variants in severe obesity
- 25. LEP, LEPR: <1% 2 new homozygous LEPR mutations 8 different heterozygous coding NSN variants POMC: <1% none MC4R : 5% none, but were pre-screened BDNF, TRKB : <1% 2 new de novo mutations SIM1 : 1.8% 8 mutation carriers (1.4%) (3 new mutations including frameshift) PC1/3: <1% none but 2 very rare heterozygous mutations Mutations in the leptin-melanocortin pathway: UK10K SH2B1: 1% 6 mutation carriers (1%) (3 new mutations)
- 26. Clinical Applications • For rare forms of obesity/ syndromic forms – Diagnosis – In very rare instances treatment (e.g. leptin) • Common forms of obesity – translational impacts yet to be fulfilled • But…. • There are a couple of examples for proof-of-concept from diabetes studies
- 27. Clinical Application I • 12% of diabetes patients are homozygous for TCF7L2 rs1225372 risk allele (TT); • TT homozygous patients have a ~2-fold greater chance of not achieving HbA1c <7% (i.e. fail treatment) on sulfonylureas than the 48% of GG patients • Sulfonylurea first line of treatment for T2D patients first diagnosed Sulfonylurea Metformin rs1225372 rs1225372 ProportionPatientswhoachievetargetHbA1c<7% Pearson et al., 2007 TT Knowledge of genotype at the TCF7L2 risk variant may influence treatment choice
- 28. Clinical Applications II • Loss-of-function mutations that protect against disease risk (without other adverse effects) => validation for that gene as a target for possible therapeutic inhibition Flannick et al., 2014 Loss-of-function mutations in SLC30A8 protect against T2D risk => New Possible Target for Inhibition
- 29. What have we learned? • Obesity Genetic Architecture – Most risk alleles are common, have small effect sizes, and map outside coding regions – Some loci overlap with monogenic forms of disease – Though there is overlap, there are also some differences between loci influencing BMI and risk of severe obesity – Role of rare variants still largely untested in sufficiently powered studies • Important biological pathways – Brain and central nervous system over represented in genes mapping within BMI-associated loci • Clinical application potential – Some loci may influence response to treatment – Some loci may become drug targets – Genetic risk scores can be used to test disease aetiology and establish causality between statistically associated traits
- 30. BUT…. • Majority of GWAS loci have limited predictive value for clinical testing – But this is changing… • Even including loci that haven’t reached genome- wide significance, much of the heritability still not accounted for.
- 31. Glass Half-empty or Half-full?
- 32. Barroso Lab Jennifer Asimit Bill Bottomley Allan Daly Ji Chen Gaëlle Marenne Rachel Moore Felicity Payne Fernando Riveros Mckay Aguilera Neneh Sallah Rachel Watson Eleanor Wheeler ..and all patients and study participants!! All Sanger support groups and pipelines Wellcome Trust | MRC Sadaf Farooqi Steve O’Rahilly G ANTG ANT C O N S O R T I U M