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Susceptibility Gene Identification in Obesity and Type 2 Diabetes
Inês Barroso
Is the glass half-empty or half-full?
Wellcome Trust | MRC
Genes and Environment in Disease
Monogenic
Type 2 Diabetes
Obesity
Infectious Disease Environment
Genes
Environmental Component
Modern Diet
Physical (In)Activity
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
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”
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 GeneMutation
Candidate Gene
500K-1M variants
1K- 500K individualsPopulations or affected (cases) – unaffected (controls)
Variant association with disease
GWAS
Changing Genetic Approaches IIGWAS 1
GWAS 2
GWAS 3
GWAS…
Large Scale Meta-AnalysisInternational GWASConsortia + Denser/
Custom Arrays
GWAS+ Imputation Dense Reference Panel
Whole-Exome and Whole-Genome Sequencing
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
First Obesity Locus
Science, 2007
PLOS Genetics, 2007
Nature Genetics, 2007
No additional variants robustly associated with BMI identified
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
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
GWAS Catalogue Filtered ObesityData 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
What have we learned?
Architecture: "the complex or carefully designed structure of something”
Genetic Architecture
Biological Insights
Clinical Applications
Genetic ArchitectureBlue – previously knownRed – 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
Phenotypic Variance Explained
Locke et al., 2015
Risk Alleles and BMI
Locke et al., 2015
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
From BMI to Severe Childhood Obesity…
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?
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
Severe Childhood Obesity
GWAS on ~1,500 obese children and ~5,400 controls
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
BMI loci in SCOOP
• BMI results from Speliotes et al. 2010 (Nature Genetics)
G ANTG ANTC 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
UK10K
4,000 Cohort SamplesWhole Genome Sequenced
~6x depth
3,000 Autism and Schizophrenia
2,000 Obesity 1,000 Rare Disease
6,000 Diseased Case SamplesWhole Exome Sequenced
~80x depth
1,000 Severe Childhood Obesity
Aim: Investigate the role of additional low- and rare-frequency variants in severe obesity
LEP, LEPR: <1%2 new homozygousLEPR mutations
8 different heterozygouscoding NSN variants
POMC: <1%none
MC4R : 5%none, but werepre-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%nonebut 2 very rareheterozygousmutations
Mutations in the leptin-melanocortin pathway: UK10K
SH2B1: 1%6 mutation carriers (1%)(3 new mutations)
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
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
Prop
ortio
n Pa
tient
s who
ach
ieve
targ
et H
bA1c
<7%
Pearson et al., 2007
TT
Knowledge of genotype at the TCF7L2 risk variant may influence treatment
choice
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
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
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.
Glass Half-empty or Half-full?
?
Barroso LabJennifer AsimitBill BottomleyAllan DalyJi ChenGaëlle MarenneRachel MooreFelicity PayneFernando Riveros Mckay AguileraNeneh SallahRachel WatsonEleanor Wheeler
..and all patients and study participants!!
All Sanger support groups and pipelines
Wellcome Trust | MRC
Sadaf Farooqi Steve O’Rahilly
G ANTG ANTC O N S O R T I U M
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