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