genes, physical activity and obesity actions and … physical activity and obesity actions and...

Genes, physical activity and obesity actions and interactions

Ruth Loos

Professor and Program Director

Genetics of Obesity and Related Metabolic Traits Program The Charles Bronfman Institute of Personalized Medicine

The Mindich Child Health and Development Institute Department of Preventive Medicine

Icahn School of Medicine at Mount Sinai New York

[email protected] ISBNPA - 2013 Annual Meeting, Ghent, Belgium, 22-25 May, 2013

Overview

•  Where do genes fit in ?

•  Genetics epidemiology of physical activity

•  Heritability

•  Candidate gene approach

•  Genome-wide scans

•  Gene-physical activity interaction

•  Summary & conclusions

Genes & physical activity

Physical activity as an outcome


Physical activity as an intermediate factor


Physical activity as an interactor


Physical activity as a effector


Physical activity as an outcome

Physical activity as an interactor

Overview


•  Gene1cs epidemiology of physical ac1vity

•  Heritability


•  Genome-‐wide scans

•  Gene-‐physical ac1vity interac1on


Is physical activity heritable ?

Heritability studies

Twin studies Iden,cal / MZ

Fraternal / DZ

Family studies

Mul,-‐genera,onal

Is physical activity heritable ?

Heritability studies

Twin studies Family studies

h2 = 0 -‐ 78% h2 = 0 – 57%

Reasons for the wide range -‐  Difference in assessing physical ac1vity -‐  Age of study popula1on -‐  Methods for es1ma1ng heritability -‐  Sample size, and thus sta1s1cal power for analyses

The classical twin study design to assess heritability

Basic sta,s,c Intra-‐pair correla1ons

1.6 1.6

1.7

1.8

1.9

2

1.7 1.8 1.9 2 Twin 1 – height (m)

Twin 2 – height (m)

r MZ= 1.0

r DZ= 0.50

Basic assump,ons MZ twins: 100% genes in common 100% shared environment in common DZ twins: 50% genes in common 100% shared environment in common

More refined: structural equa1on modeling: V = Va + Vc + Ve

Quick and simple: Falconer’s formula: h2 = 2[rMZ – rDZ]

A large twin study with objectively assessed physical activity

TwinsUK •  419 pairs of MZ twins •  352 pairs of DZ twins Physical ac,vity assessment •  7-‐day monitoring (96% had >4 days) •  Heart rate monitors •  accelerometer

Marcel den Hoed

PA 82% adhere to the physical ac1vity guidelines


Descrip,ves

Residuals PAEE twin 1

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

-‐1.5 -‐1.0 -‐0.5 0.0 0.5 1.0 1.5

Residuals PAEE twin 2

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

-‐1.5 -‐1.0 -‐0.5 0.0 0.5 1.0 1.5

MZICC = 0.47 DZICC = 0.22

A large twin study with objectively assessed physical activity Intra-‐pair correla,ons

Explaine

d varia

nce

0.00

0.20

0.40

0.60

0.80

1.00

1.20

PAEE Sedentary Light MVPA

gene1c factors unique environmental factors


Structural equa,on modeling

Heritability of daily physical ac,vity 43-‐49%

Overview



•  Heritability





Candidate gene approach

= hypothesis-‐driven, based on the current understanding of the biology and pathophysiology of the trait/disease

Epidemiology Physiology/Biology

Animal studies

Butler et al. Nature Neuroscience 2001

High Fat diet

Kelly et al. J. Neurosci 1998

-/-

-/-

+/-

+/-

+/+

+/+


DRD2 (dopamine receptor D2)

MC4R (melanocor@n 4 receptor)

Reward and aversion Craving and need

Animal studies


Home cage ac,vity

Effect on ability, pain

Common genetic variation - SNPs

GGC GCC GGA CGC TCC ATC TCC TGG GCC TGG TGG GCA TGT GTG Gly Ala Gly Arg Ser Ile Ser Trp Ala Trp Trp Ala Cys Val

GGC GCC GGA CGC TCC ATC TCC TGG GCC TGG TGG GCA TGT GTG

GGC GCC GGA CGC ACC ATC TCC TGG GCC TGG TGG GCA TGT GTG GGC GCC GGA CGC TCC ATC TCC TGG GCC TGG TGG GCA TGT GTG

GGC GCC GGA CGC TCC ATC TCC TGG GCC TGG TGG GCA TGT GTG GGC GCC GGA CGC TCC ATC TCC TGG GCC TGG TGG GCA TGT GTG

GGC GCC GGA CGC ACC ATC TCC TGG GCC TGG TGG GCA TGT GTG GGC GCC GGA CGC ACC ATC TCC TGG GCC TGG TGG GCA TGT GTG

GGC GCC GGA CGC TCC ATC TCC TGG GCC TGG TGG GCA TGT GTG GGC GCC GGA CGC ACC ATC TCC TGG GCC TGG TGG GCA TGT GTG

A

A A

A

T

T T

T T

T

Gly Ala Gly Arg Thr Ile Ser Trp Ala Trp Trp Ala Cys Val

T/T

A/T

A/A

T/T

A/T

SNP à Single Nucleo,de Polymorphism

Genetic associations

The ‘addi,ve’ model tests whether the A-‐allele increases PAEE significantly.

25.2

26.6

27.9

24

25

26

27

28

29

T/T A/T A/A Genotype

PAEE(kJ/kg/day)

Human studies


MC4R

•  669 individuals of the Québec Family Study •  Physical activity assessed by 3-day diary, every 15min

Human studies


MC4R

100

200

300

400 500

600 700

800

Total Moderate-to- strenuous Inactivity

Ph

ysic

al A

ctiv

ity

Cou

nts

C/C C/T T/T p = 0.08

p = 0.005

p = 0.01

Human studies


PCK1

*sex, age, age-‐group, standardised height, maturity and country

•  2,101 boys and girls from European Youth Hearth Study

•  1,255 9-‐y olds

•  846 15-‐y olds

•  Denmark and Estonia

•  Physical ac,vity -‐ MTI accelerometer

Human studies


PCK1

•  669 individuals of the Québec Family Study •  Physical activity assessed by 3-day diary, every 15min

0

540

580

620

660

PCK1 SNPs

Physical Ac,vity cou

nts

0 1 2

p = 0.87 p = 0.57 p = 0.68 p = 0.65 p = 0.67 p = 0.33 p = 0.87

p = 0.95 p = 0.63 p = 0.07

*sex, age, age-‐group, standardised height, maturity and country

Candidate gene approach – literature overview

Reward and aversion

Craving and need

Effect on ability, pain

•  Melanocor1n 4 receptor (MC4R) •  Lep1n receptor (LEPR)

•  Dopamine 2 receptor (DRD2)

Genes, exercise, and physiological factors, Eco J.C. de Geus & Marleen H.M. de Moor, in GeneAc and Molecular Aspects of Sport Performance, Claude Bouchard and Eric P. Hoffman (eds), 2011

Human studies

•  Loos et al. (IJO, 2005): Associa1on with moderate-‐to-‐strenuous PA (p=0.005) in the QFS.

•  Stefan et al. (IJO, 2002): Associa1on with total PA in Pima Indians (p=0.007) •  de Moor et al. (MSSE, 2009) Associa1on with leisure 1me PA in Americans (p=0.0005)

•  Simonen et al. (Physiology & Behavior, 2009): Associa1on with physical ac1vity, sports par1cipa1on, and occupa1onal ac1vity (p=0.05) in the QFS and HERITAGE.

•  Calcium sensing receptor (CASR)

•  Angiotensin-‐conver1ng enzyme (ACE)

•  Lorentzon et al. (EJE, 2009): Associa1on with hours spent on physical ac1vity per week in adolescent girls (p=0.01)

•  Winnicki et al. (AJMG, 2004): Associa1on with leisure 1me physical ac1vity per week in hypertensives (p=0.001)

Overview



•  Heritability





Genome-wide scans

= hypothesis-‐genera1ng, to iden1fy new, unan1cipated, genes and thus expand view of biology and physiology of disease/trait

Epidemiology Physiology/Biology

Genome-‐wide analyses

Genome-‐wide linkage analyses aim to iden@fy a crude chromosomal loca@on of the gene or genes associated with a phenotype of interest

Genome-‐wide associa,on analyses aim to iden@fy an exact chromosomal loca@on of the gene@c variant associated with a phenotype of

interest

Genome-wide scans

Genome-wide linkage studies

•  1,030 sibling of 319 Hispanic families

•  Physical ac,vity -‐ accelerometer

Genome-wide linkage studies

MC4R

Genome-wide association studies

STAGE 1 -‐ Discovery stage

•  Determine genotype of up to 2,500,000 gene1c variants (SNPs)

•  Case-‐control or cohort studies

•  Large amount of tests à significance threshold p < 0.000001

STAGE 2 - Replication/follow-up stage •  1-‐100 SNPs that represent top loci

•  Case-‐control or cohort studies – at least equal size of discovery panel

•  Meta-‐analysis of stage 1 & 2 results

Published Genome-‐wide Associa,ons

06/2006 06/2007 06/2008 06/2009 06/2010 06/2011 06/2012

NHGRI GWA Catalog www.genome.gov/GWAStudies

>1,700 published GWA at p<5x10-‐8

Genome-wide association for physical activity

Aim: Large-‐scale genome-‐wide meta-‐analysis on five physical ac,vity traits

Outcomes of interest: 1.  Moderate-‐to-‐vigorous intensity leisure 1me ac1vi1es 2.  Sedentary behavior during commu1ng 3.  Sedentary behavior at work 4.  TV viewing 5.  Other sedentary behavior at home

Genome-‐wide genotypes: 2,5 million gene1c varia1ons across the autosomal genome

Study design Stage 1 (discovery): 33 studies with required data were invited, up to 82,000 individuals Study-‐specific analyses plans sent out (customized by ques1onnaire) Meta-‐analyses of summary sta1s1cs (for each of the 2,5 million variants)

N stage 1 82,231 15,076 61,612 28,695 27,627

Study design Stage 2 (follow-‐up): >40 studies with required data have been invited, expect data from up to 80,000 individuals Follow-‐up of 56 gene1c variants with promising associa1on (p < 10-‐6) in stage 1

Loci with p<10-‐6

6 6 15 17 12

Marcel den Hoed


Sedentary commu,ng to work (vs ac,ve commu,ng to work)


TV viewing

Genes for physical activity

Candidate gene studies Even though animal studies have iden1fied credible proteins that affect physical ac1vity, gene1c variants in the encoding genes are not (yet) convincingly associated with daily physical ac1vity levels in humans .

Genome-‐wide linkage studies Even though one study provided sugges1ve confirma1on for the MC4R locus, results have not been firmly confirmed.

Genome-‐wide associa,on studies Large-‐scale meta-‐analysis is on-‐going;

-‐ stage 1 results are promising

-‐ stage 2 results will soon be available !

à First results are emerging, but much more work is needed !

Overview



•  Heritability






Does physical ac,vity anenuate the associa,on between gene and outcome ? Does genotype anenuate the associa,on between physical ac,vity and outcome ?

Physical activity, FTO and obesity-susceptibility

•  17,619 men and women of the EPIC-‐Norfolk study (40-‐75y), with self-‐reported physical ac1vity levels.

25

25.5

26

26.5

27

27.5

28

All Inac1ve Ac1ve

BMI (kg/m

2 )

CC CT TT CC CT TT CC CT TT

P = 3.1 x 10-‐20

P = 1.5 x 10-‐13

P = 8.5 x 10-‐13

EPIC-‐Norfolk (n=20,374)

Vimaleswaran KS, et al. Am J Clin Nutr 2009;90:425-‐8

Overview of the literature on FTOxPA interaction and BMI

Greek adol. (n=499)

Scon RA, et al. Eur J Hum Genet 2010 Aug 18

Inter 99 (n=5,922)

Interac,on No interac,on

HAPI Heart (n=702)

DPS (n=479)

NHS98 (n=4,210)

Malmö PP (n=15,925)

Botnia PP (n=2,511)

HELENA (n=752)

NFBC86 (n=4,780)

KSNP (n=8,842)

TRAILS (n=1,230)

LACHY & APEX (n=744)

ULSAM (n=1,115)

NFBC66 (n=4,022)

BCAMS (n=3,503)

MDC (n=4,810)

Andreasen CH, et al. Diabetes 2008;57:95-‐101

Rampersaud E, et al. Arch Intern Med 2008;168:1791-‐7

DESIR (n=4,640)

Cauchi S, et al. J Mol Med 2009;87:537-‐46

Cauchi S, et al. J Mol Med 2009;87:537-‐46

Jonsson A, et al. Diabetologia 2009;52:1334-‐8

Jonsson A, et al. Diabetologia 2009;52:1334-‐8

Kaakinen M, et al. Am J Epidemiol 2010;172:653-‐65

Ruiz JR, et al. Arch Pediatr Adolesc Med 2010;164:328-‐33

Tan JT, et al. Diabetes 2008;57:2851-‐7

Sonestedt E, et al. Am J Clin Nutr 2009;90:1418-‐25

Jacobsson JA, et al. BMC Med Genet 2009;10:131

Lee HJ, et al. Clin Chim Acta 2010;11:1716-‐22

Xi B, et al. BMC Med Genet 2010;11:107

Liem ET, et al. Am J Clin Nutr 2010;91:321-‐8

Liu G, et al. BMC Med Genet 2010;11:57

Lappalainen TJ, et al. Obesity 2009;17:832-‐6

Study design

•  Contact all cohorts that have published on the FTO locus (and that are known to have physical

ac1vity data).

•  ‘Harmonise’ physical ac1vity data across cohorts (i.e. ques1onnaire, diary, accelerometry, …).

à Dichotomise: ac1ve vs sedentary – custom defini1on for each cohort

•  Ask cohorts to (re-‐)analyse data according to detailed analysis plan.

Data collec,on & analysis

•  45 studies – 218,166 individuals

•  Meta-‐analyses of the interac1on term

•  Stra1fied meta-‐analyses of ac1ve and sedentary individuals

Kilpeläinen et al (PLoS Medicine 2011)

De novo meta-analysis of all available data

Tuomas Kilpeläinen

Results

FTO influences BMI in inac1ve people only

Results

FTO influences BMI in inac1ve people only

Overall interaction term:

b3 = - 0.14 kg/m2 [95%CI -0.23 to -0.04]

P = 0.005

à The BMI-increasing effect of FTO is less pronounced in active individuals than in sedentary individuals; i.e. for each additional risk allele the increase is 0.14kg/m2 less.

0

1000

2000

3000

4000

≤6 7 8 9 10 11 12 13 14 15 16 ≥17 Genetic predisposition score

N

24.5

25.5

26.5

27.5

28.5

BM

I (k

g/

m2)

0.15 kg/m2/allele or 444 g/allele p = 1.54x10-22

Gene1c predisposi1on score on BMI in 20,000 individuals of the EPIC-‐Norfolk study

Li et al AJCN 2010 & PLoS Medicine 2010

Twelve obesity-susceptibility loci – interaction with physical activity

0

1000

2000

3000

4000

≤6 7 8 9 10 11 12 13 14 15 16 ≥17 Genetic predisposition score

N

24.5

25.5

26.5

27.5

28.5

BM

I (k

g/

m2)



Active

Inactive

Gene1c predisposi1on score on BMI in 20,000 individuals of the EPIC-‐Norfolk study

Li et al AJCN 2010 & PLoS Medicine 2010

Twelve obesity-susceptibility loci – interaction with physical activity

Overview



•  Heritability





Summary

Heritability Based on a large-‐scale twin study with objec1ve PA measurements, 43-‐49% of the inter-‐individual varia1on can be explained by gene1c difference.

Candidate gene approach Animal studies have iden1fied genes that play a role in PA (reward, craving, ability). However, these varia1on in these candidate genes does not (yet) associate with PA in humans. à Study more variants, in larger studies

Genome-‐wide scans On-‐going large scale genome-‐wide associa1on studies have iden1fied loci that show promising associa1on with PA (in par1cular sedentary behavior). These results need to be confirmed.

Gene-‐physical ac@vity interac@on Physical ac1vity atenuates the BMI-‐increasing effects of obesity-‐suscep1bility loci by 30-‐40% à Even those gene1cally predisposed to obesity benefit from physical ac1vity.

Collaborators and acknowledgements

[email protected]

Tuomas Kilpeläinen, PhD Assistant professor Novo Nordisk Founda1on Center for Basic Metabolic Research Copenhagen, Denmark

Marcel den Hoed, PhD Researcher Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory Uppsala University Uppsala, Sweden

Marilyn Cornelis, PhD Research Associate in Nutri1on Harvard School of Public Health Boston, MA, USA

genes, physical activity and obesity actions and … physical activity and obesity actions and...

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