"Genetics, diabetes and obesity

–

where

are

we?"

Torben Hansen Professor, MD, PhD

Hagedorn

Research Institute

Gentofte, Denmark

Winter School

2010‐2011 

Individual

Health

& Nutrition

9 november 2010

Homo stupidus

Homo sapiens

1.

Genetics of increased  BMI/obesity and 

common forms of  diabetes 

2.

Missing heritability

3.

Our other genome

Features of obesity

Hypertension

High TG Low HDL

Insulin resistance

InflammationPro-coagulation

Type 2 diabetesand

vasculardisease

Triggers: OvereatingPhysical inactivity

What

about

genetics

of

obesity?What

about

genetics

of

obesity?

Photograph by Karen Kasmauski

©

National Geographic

2007

Studies Studies ofof

thethe

geneticsgenetics

ofof

complexcomplex

disordersdisorders: : thethe

developmentdevelopment ofof

technologytechnology

drives drives thethe

progressprogress

single variant 

(100 SNPs; 103

genotypes)

detailed study of individual genes(102 SNPs; 105+

genotypes)

regional studies (104 SNPs; 108

genotypes )

genome‐wide association 

(106

SNPs; 1010 genotypes)20052005

GenomeGenome‐‐widewide

association in 2007association in 2007

Studies Studies ofof

thethe

geneticsgenetics

ofof

complexcomplex

disordersdisorders: : thethe

developmentdevelopment ofof

technologytechnology

drives drives thethe

progressprogress

single variant 

(100 SNPs; 103

genotypes)

detailed study of individual genes(102 SNPs; 105+

genotypes)

regional studies (104 SNPs; 108

genotypes )

genome‐wide association 

(106

SNPs; 1010 genotypes)20052005

Whole exome

and whole

genome sequencing 2010

GenomeGenome‐‐widewide

association (GWA) in association (GWA) in shortshort

Type for ~/>500,000 SNPs

Obtain information about strength of associationgenome wide 

(within limits of sample size, allele frequency, LD etc)

Validation in independent samples of what looks  interesting

followed by combined analyses

By courtesy of http://www.broad.mit.edu/diabetes/

ExampleExample

ofof

a GWA a GWA withwith

389,000 389,000 SNPsSNPs

successfullysuccessfully genotypedgenotyped

Eighteen risk loci associate with obesity/increased BMI with genome-wide significance

Each of them are common but only increase risk of obesity with 8-33%

Odds ratio

1.05

1.10

1.15

1.20

1.25

1.30

1.35

1.40

1.00

Positional cloningHypothesis-free approach

1.05

1.10

1.15

1.20

1.25

1.30

1.35

1.40

1.00

Odds ratio

2007

MC4RPCSK1

2008

FTO

2009

TMEM18 SEC16BGNPDA2 KCTD15PTERNGR1

BAT2

BDNFFAIM2MAF ETV5

SH2B1NCP1

PRLMTCH2

Most of

obesity

risk

loci

are

related

to genes in the

hypothalamus

-> disturbed appetite regulation

MC4R

PTER NCR3/AIF1/ BAT2

PRLPCSK1

TMEM18

NEGR1SH2B1

MAF

FAIM2/BCDIN3D MTCH2

BDNF KCTD15

NPC1

FTO

Explain collectively about 1 % of the genetic component of obesity

Speliotes-EK et al. Nature Genetics. Online Oct. 10, 2010

Combined association analyses of 249,796 individuals show additional eighteen new loci associated with body mass index

Meta-analysis

of

GWAS identifies

13 new loci

associated

with

waist-hip

ratio

Nature GeneticsOnline

October

10, 2010

The clinician’s view!

Cumulative effect and predictive value of 32 loci

•

ARIC study, 8,120 individuals, population-based, whites

250

2627

2829

Mean

BM

I (k

g/

m2)

500

1000

1500

Nu

mb

er

of

ind

ivid

uals

(N

)

≤2122-23

24-2526-27

28-2930-31

32-3334-35

36-37≥38

Number of weighted risk alleles

0.17 k

g/m2 per

alle

le

435-551g p

er a

llele

2.71 kg/m2

6.9 - 8.8 kg

0

0

0.25

0.50

0.75

1.00

Sen

siti

vity

0.25 0.50 0.75 1.00

1-Specificity

AUC32 SNPs = 0.574

By By courtesycourtesy ofof Dr. Ruth Dr. Ruth LoosLoos

Speliotes et al., Nature Genetics. Online 10 October, 2010

GeneticsGenetics

ofof

obesityobesity

Allele frequency

(%)

Effect size

(OR)

0.1%

High

Low

1.1

1.5

3.0

>50

Modest

Inter-

mediate

Very rare

Rare Low frequency

Common0.5% 5%

Monogenic mutation

LEPLEPRMC4RPOMCPCSK1SIM1BDNFNTRK2

Deletion16p11.2, SH2B1

ABCB5EDIL3FOXP2NEGR1S1PR5ZPLD1Duplication

ARL15KIF2B

FANCL

LRRN6C

BDNF

MAP2K5

GNPDA2FLJ35779

GPRC5B

FTO

LRP1B

MTCH2

NEGR1 NPC1MTIF3

CTNNBL1

ETV5/SFRS10

MAFKCTD15

FAIM2

MC4RCADM2

PCSK1

TMEM160

PTBP2

PRL

PFKPPRKD1

NUDT3

NRXN3RPL27A

QPCTL

SH2B1

SEC16B

PTER RBJ

TMEM18

SLC39A8

TNNI3K

ZNF608

Biologic candidate approachPositional cloningHypothesis-free approach

1.05

1.10

1.15

1.20

1.25

1.30

1.35

1.40

1.00

SLC30A8CDKAL1

IGF2BP2

CDKN2AFTO

HHEX

WFS1TCF2

1.05

1.10

1.15

1.20

1.25

1.30

1.35

1.40

1.00

Risk of diabetes (Odds ratio)

37 risk loci associate with T2D with genome-wide significance

Each of them are common but only increase risk of type 2 diabetes with 5-35%Risk of diabetes (Odds ratio)

1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

TCF7L2 KCNJ11PPARG

MTNR1B

THADANOTCH2

CAMK1DADAM30

JAZF1ADAMTS9

TSPAN8

KCNQ1

2010

DUSP9CENTD2

TP53INP1CHCHD9HNF1A

HMGA2ZFAND6

PRC1KLF14

PROX1

ZBED3

DGKBGCK

GCKR

ADCY5

BCL11A

KCNQ1IRS1

FTO

PPARGIRS1

ADAMTS9GCKRKLF14 CDKAL1

C2CD4A

Estimated

functions

of

variants at type 2 diabetes risk

loci

TCF7L2WFS1

KCNQ1

Undetermined:

Fasting

glucose

meta- analysis

discovers

G6PC2

GCK

MTNR1B

GCKR DGKBPROX1

ADCY5SLC2A2 GLIS3

ADRA2AMADD

FADS1

CRY2

FAM148BSLC30A8 TCF7L2

Five known FGP loci

Dupuis et al, Nat Genet online Jan 17th 2010

Two established T2D lociNine novel loci

slide 19 The Steno Advanced Update Course

TheThe

combinedcombined

impactimpact

ofof

16 16 riskrisk

variants variants onon

fastingfasting glucoseglucose

in a in a nonnon‐‐diabeticdiabetic

populationpopulation

number

of

risk

alleles

Fast

ing

gluc

ose

(mm

ol/l)

<12 12 13 14 15 16 17 18 19 20 21 22 >22

5.0

6.0

Num

bero

find

ivid

uals

020

060

080

0 Increase per allele: 0.04 mmol/l (p=10-17)

5.5400

slide 20

CommonCommon

variants variants explainexplain

a a minorminor

fractionfraction

ofof

thethe

variancevariance

in in  metabolicmetabolic

phenotypesphenotypes

in in thethe

general populationgeneral population

Of total:     4‐6%

Of genetic:  8‐12%

Fasting

plasma glucoseHeritability

30‐40%

slide 21

GeneticsGenetics

ofof

nonnon‐‐autoimmuneautoimmune

diabetesdiabetes

PPARG

KCNJ11

PNDM genesKCNJ11ABCC8

INS

Other rare syndromes

MODY genesHNF1AHNF4A

GCKIPF1

HNF1BNEUROD1

CEL

TCF7L2

WFS1

IGF2BP2 CDKAL1

CDKN2A

FTO

SLC30A8

HHEX

HNF1B CDC123 JAZF1

TSPAN8

ADAMTS9

NOTCH2

THADA

KCNQ1

MTNR1B

IRS1

GCK

GCKR DGKB

PROX1 ADCY5

Allele frequency

(%)

Effect size

(OR)

0.1%

High

Low

1.1

1.5

3.0

>50

Modest

Inter-

mediate

Very rare

Rare Low frequency

Common0.5% 5%

and many more

Rare, penetrant

mutationsGood for individual prediction in rare cases

Too rare for population effect

Common SNPs

with low penetranceEffects too small for individual prediction

ExplosionExplosion

in in thethe

numbernumber

ofof

validatedvalidated

commoncommon variants for all variants for all diabetesdiabetes‐‐relatedrelated

metabolicmetabolic

traitstraits

Fasting

plasma glucose ~16 loci

Circulatinglipid

levels ~36 loci

Cardiovasculardisease ~18 loci

BMI orobesity ~18+ loci

Hypertensionor

BP ~14 loci

Unknown

causal

mutation and gene

Type 2 diabetes 37+ loci

Common

variants with

low

individual

impact

Identified

variants explain

5‐10 %

of

the

genetic

contribution

Collectively

the

variants have no

clinical

utility

for disease

discrimination

or

prediction

More More thanthan

90% 90% ofof

thethe

heritabilityheritability

ofof thesethese

disordersdisorders

is not is not explainedexplained

Additional common risk alleles?Additional common risk alleles?

GeneGene--environment interactions?environment interactions?

GeneGene--gene interactions?gene interactions?

Copy number variations?Copy number variations?

EpigeneticsEpigenetics??

TheThe ‘‘missing missing heritabilityheritability’’ ofof type 2 diabetes and type 2 diabetes and obesityobesity

More More thanthan

90% 90% ofof

thethe

heritabilityheritability

ofof thesethese

disordersdisorders

is not is not explainedexplained

Additional common risk alleles?Additional common risk alleles?

GeneGene--environment interactions?environment interactions?

GeneGene--gene interactions?gene interactions?

Copy number variations?Copy number variations?

EpigeneticsEpigenetics??

TheThe ‘‘missing missing heritabilityheritability’’ ofof type 2 diabetes and type 2 diabetes and obesityobesity

By By courtesycourtesy

ofof

Dr. Mark Dr. Mark McCarthyMcCarthy

TheThe

association association ofof

FTO FTO withwith

obesityobesity‐‐relatedrelated quantitativequantitative

traitstraits

in Inter99in Inter99

•

FTO associates

with

increased

BMI, body

weight

and waist circumference

•

No

association with

serum lipids

Andreasen CH, Diabetes 2008;57:95-101

The impact of the FTO rs9939609 genotype on BMI- levels is highly influenced by habitual physicial activity: Physical inactivity was associated with an increase of

1.95 BMI units in AA-allele carriers A population-based study of 5,722 middle-aged Danes

Physical

activity

was

self-reported

by questionnaire

Number

of

subjects

(TT/TA/AA)

Pint = 0.007

Andreasen CH, Diabetes 2008;57:95-101

APOLIPOPROTEIN A-V; APOA5

-1131T>C

• Carrier frequency

11 % among Caucasians

Association with fasting serum triglycerides in the general population

of 5,873 middle-aged Danes

T/T T/C C/C p

n(men/women) 5,152(2,563/2,589) 698(356/342) 23(10/13)

Age (years) 46 ± 8 46 ± 8 44 ± 7

BMI (kg/m2) 26.2 ± 4.5 26.4 ± 4.8 24.3 ± 4.6 0.7

Waist-to-hip ratio 0.86 ± 0.09 0.86 ± 0.09 0.84 ± 0.08 0.9

Fasting serum lipids (mmol/l)

Triglyceride 1.3 ± 1.1 1.7 ± 2.7 1.8 ± 0.9 110-15

Mean ± SD. Adjustment for age, sex, and BMI (where appropriate). Calculated by GLM assuming additivity.

The effect of APOA5 -1131T>C on fasting serum triglycerides is modulated by the level of hyperglycaemia

in studies of 5,873 middle-aged Danes

Fasting serum triglyceride (mmol/l)

Wild type TC + CC

p = 510-9

0

1

2

3

4 NGTIFGIGTScreen-detected T2DM

3880 438 609 221 561 57 73 28

The impact of APOA5 -1131T>C on fasting serum triglycerides is modulated by the degree of insulin resistance (Homa-IR)

in studies of 5,873 middle-aged Danes

Fasting serum triglyceride (mmol/l)

Wild type TC + CC

p = 510-9

0

1

2 < 44-55-66-77-88-9.59.5-11.511.5-14.514.5-20> 20

HOMA IR:equally sized subgroups

The impact of APOA5 -1131T>C on fasting serum triglyceride is modulated by smoking

Fasting serum triglyceride (mmol/l)

Wild type TC + CC

p = 0.0003

0

1

2

2.5

Daily and occasional smokersNon-smokers and previous smokers

0.5

1.5

The impact of APOA5 -1131T>C on fasting serum triglyceride is modulated by alcohol intake

Wild type TC + CC

Fasting serum triglyceride (mmol/l)

p = 0.005

0

4

6

None or moderate alcohol intakeHigh alcohol intake

2

Public health implications: Gene-Lifestyle and Gene-Metabolism

Interactions

Specific health behaviour recommendations seem appropriate based upon knowledge of the

FTO, LIPC and APOA5 genotypes

More More thanthan

90% 90% ofof

thethe

heritabilityheritability

ofof thesethese

disordersdisorders

is not is not explainedexplained

Additional common risk alleles?Additional common risk alleles?

GeneGene--environment interactions?environment interactions?

GeneGene--gene interactions?gene interactions?

Copy number variations?Copy number variations?

EpigeneticsEpigenetics??

TheThe ‘‘missing missing heritabilityheritability’’ ofof type 2 diabetes and type 2 diabetes and obesityobesity

TheThe

‘‘rare variant rare variant hypothesishypothesis’’

A A significantsignificant

proportion proportion ofof

thethe inheritanceinheritance

ofof

complexcomplex

disordersdisorders

is is

due to due to thethe

cumulativecumulative

load load ofof

rare rare variantsvariants

Rare Rare riskrisk allelesalleles ––nextnext frontierfrontier

Rare risk Rare risk allesalles??

Allele frequency

(%)

Effect size

(OR)

0.1%

High

Low

1.1

1.5

3.0

>50

Modest

Inter-

mediate

Very rare

Rare Low frequency

Common0.5% 5%

Monogenic mutation

LEPLEPRMC4RPOMCPCSK1SIM1BDNFNTRK2

Deletion16p11.2, SH2B1

ABCB5EDIL3FOXP2NEGR1S1PR5ZPLD1Duplication

ARL15KIF2B

FANCL

LRRN6C

BDNF

MAP2K5

GNPDA2FLJ35779

GPRC5B

FTO

LRP1B

MTCH2

NEGR1 NPC1MTIF3

CTNNBL1

ETV5/SFRS10

MAFKCTD15

FAIM2

MC4RCADM2

PCSK1

TMEM160

PTBP2

PRL

PFKPPRKD1

NUDT3

NRXN3RPL27A

QPCTL

SH2B1

SEC16B

PTER RBJ

TMEM18

SLC39A8

TNNI3K

ZNF608

??

WhereWhere

is is thethe

missing missing heretabilityheretability??

The Lundbeck

Foundation Initiative in genomics of type 2 diabetes and obesity

www.lucamp.org

•

Sequencing of the coding part of the human genome in 2,000 Danes

•

Gene-wise comparisons of ~

20,000

likely deleterious gene variants in 17,000 Danes

Exome

capturingGenome elements # Of elements Total length

Promoter 1,917 490,995

5-UTR 17,046 672,142

CDS-exons 209,095 32,584,741

3-UTR 6,524 401,002

Intron 55,372 4,349,839

•The “exome”

is defined to be the designed target region which would be hybridized with the NimbleGen

2.1M-

probe sequence- capturing array.

•

18,654 genes, ~34Mbp length in total

ProductionProduction

ofof

hugehuge

amountsamounts

ofof

data data throughthrough highhigh‐‐throughputthroughput

DNA DNA sequencingsequencing

in in ChinaChina

IndividualIndividual

sequencingsequencing

ofof

thethe

codingcoding

region region ofof

200 initial Danish 200 initial Danish  human human genomesgenomes

coveringcovering

~20,000 genes ~20,000 genes discovereddiscovered

~53,000 ~53,000 

novelnovel

variants (= not in variants (= not in availableavailable

databases)databases)

Li et al., Nat Genet, online 3 October 2010

b

The

bacteria

in our

distal

intestines

function

as

a metabolic organ

Nature 444, 21 December 2006

Is an imbalance in gut bacteria in part to blamefor metaboliccomplications

Is an imbalance in gut bacteria in part to blamefor metaboliccomplications

Dethlefsen L. et al. Nature 449: 811-818,2007

Human colon

bacteria≈

1.5 kg microbes

Bacteriodetes and Firmicutes account

for > 90%

Functions:

TrophicControl of epithelial cell proliferation

and differentiation

ProtectiveProtection against pathogens

MetabolicFermentation of non-digestible

polysaccharides and storage of the extracted energy in host fat depots. Contributes with about 10% of total daily energy infusion

Who

is who? The

microflora

of

human body

cavities

FirmicutesBacteriodetes

Obese mice have more Firmicutes

Obese mice have 50 % higher representation of gut Firmicutes division and proportionally less of the Bacteroidetes division than lean mice

This

trait

was

transmissible: When

germ-free

mice

were

given an 'obese

gut microflora' it

resulted

in an increase

in total body

fat compared

with

colonization with

a 'lean

gut microflora’

The Firmicutes have a higher capacity for fermentation of

non-digestible polysaccharides than

Bacteriodetes

Ley RE et al. PNAS 102:11070-5,2005 Turnbaugh

PJ et al., Nature 444:1027-31,2006

Features of obesity

Hypertension

High TG Low HDL

Insulin resistance

InflammationPro-coagulation

Type 2 diabetes,vasculardisease, cancer

Triggers: Genetic risk factorsOvereatingPhysical inactivityThe gut microbiome?

Massively parallel shotgun sequencing of genes from distal

gut bacteria of 86 Danes

and

38 from Spain

a culture-independent approachto identify the gut bacterial genes

Identification

of

3.3 million genes from distal

gut of 86 Danes

and 38 from Spain

•

Human gut gene set is at least

150 times larger

than

the

gene set of

the

human genome

•

> 99% of

gut genes are

bacterial

•

Each

individual

harbors

~ 160 gut bacterial

species with

~

530,000 bacterial

genes

•

64 out of

160 gut bacterial

species are

shared

by >90% of

individuals

•

Bacteriodetes and Firmicutes are

the

most abundant

Nature 464:59-65, 2010

Which

molecular

mediators are

involved

in the

metabolic

dysfunctions?

……bacterial

lipopolysaccharides?……bacterial

short

chain

fatty

acids?

…....bacterial

amino

acids? ……other

mediators

What

are

the

primary drivers?

….host genomics?

…..unhealthy

dietary

habits with preference

of

fat food?

Gut microbiome

based

interventions: perspectives

•

Coloscopic

replacement

with

a mixture of

cultured

or

fresh

’healthy’ bacteria

species?

•

Oral prebiotics?

•

Oral probiotics?

•

Irradications?

Individualizing

the

gut treatmentdependent on

host genotype profiles?

Gut Gut microbiomemicrobiome (genetic

diversity)Human Human genomegenome(genetic

variations)

Bacterial components and metabolites

Bacterial components and metabolites

DietDiet HealthHealth DiseaseDisease

InteractionInteraction

Is the presence of the Firmicutes imbalance determined by the individual make-up of the host nuclear genome?

Is the presence of the Firmicutes imbalance determined by the individual make-up of the host nuclear genome?

Next

steps

Oluf

Pedersen

Niels

Grarup

Thomas Sparsø

Michel Kristensen

Grete Lademann

Arne Lykke Nielsen Toby

Brunt

Thomas Sparsø

Anders Albrechtsen

Camilla Andreasen

Anette

Prior Gjesing

Trine Welløv

Boesgaard

Trine Nielsen Ehm

Anderson Kristoffer

Burgdorf

Karina Banasik

Annemette

Forman

Marianne Stendahl

Lise

Wantzin

Debbie Nadelman

Tina Lorentzen

Marie Vestmar

Malene Hornbak

Marie Harder

Nicolaj Krarup

Frida Emanuelsson

Lise Højsgaard Olsen Lise

Wegner

Signe Torekov

Lise

Wegner

Christian Rose

Dorit

Zobel

Kirstine

Stender-Petersen Johan Holmkvist

Lesli

Larsen

Meena

Hussain

Stine Anthonsen

Mette

Andersen Rahul

Kapur

Metagenomics of the Human Intestinal Tract

Institut National de la Recherche Agronomique, France

Hagedorn Research Institute, Denmark

University of Copenhagen, Denmark

Technical University of Denmark

Beijing Genomics Institute, China

Wellcome Trust Sanger Institute, UK

Danone Research, France

European Molecular Biology Laboratory, Germany

Genoscope – Centre national de séquençage, France

INRA Transfert S.A, France

Hospital Universitari Vall d´Hebron, Spain

Instituto Europeo di Oncologia, Italy

Pharma S.A, Spain

Wageningen Universitit, Netherlands

Thorkild I A SørensenThue SchwartzJens Juul Holst,Torben Jørgensen,Kim Overvad,Anne Tjønneland,Torsten LauritzenAnelli SandbaekSten Madsbad,Bernard ThorensSøren Brunak

Ulf Smith,C.Ronald Kahn,Marku Laakso,Hans Härring,Henrik Mortensen,Valgerdur Steinthorsdottir,Unnur Thorsteinsdottir,Kári Stefánsson

Hans-Henrik Parving,Peter Rossing,Lise Tarnow,V Mohan,Jan Lebl,Danniel Witte,Ole Schmitz,Ivan Brandslund,Cramer K Christensen

Hennning Beck-Nielsen,Kurt Højlund,Søren Urhammer,Flemming Pociot,Jørn Nerup,Thomas Mandrup-Poulsen,Toni Maasen,Leen M’T Hart,Fabrizio Barbetti,Giorgio Sesti,Matha Hribal

Juleen Zierath,Peter Damm,Lars Hansen,Sten Lund,Søren Lund,Katrine Almind,Henrik Vestergaard,Jesper Clausen,Shiro Maeda,Yusuke Nakamura,Hans Eiberg,Søren Brunak,Aage Vølund,Niels Møller,Hui Liwen

Jun Wang,Li Yuingrui,Tian Saturn,Jian Wang,Huanming Yang,Rasmus Nielsen,Robert Sladek,Johan Rung,David Meyre,Nabila Bouatia-Naji,Michael Benzinou,Unoki HiroyukiClifton BogardusLeslie Baier,M. Alan Permutt

Philippe Froguel,Mark McCarthy,Andrew Hattersley,Tim Frayling,Leif Groop,José Florez,Pål Njølstad,Arne Astrup,Johan Auwerx

Allan Vaag,Pernille Poulsen,Jørgen Wojtaszewski,Rasmus Riebel-Madsen,Kirstine Færch,Kasper Pilgaard