Jaakko Kaprio
Odense
Twin Methods
Course
27 May 2013

Outline

Causality and observational epidemiological studies

Value of heritability estimates

Accounting for missing heritability?

Early consequences of weight gain and mechanisms in obesity

Finnish Twin Cohort study
 established 37 years ago
 a unique longitudinal study resource with a richness of phenotypic data collected in repeated surveys, interviews, and by register linkage

Cancer registry, hospitalizations, medications, disability pensions and causes of death

The older cohort of twins (c. 16500 pairs known zygosity) born before 1958 and studied since 1975 has contributed to longitudinal genetic epidemiological studies.

Cancer data contributes to NorTwinCan, a collaboration of all Nordic Twin Cohorts and Cancer Registries

Suicide among smokers
– evaluation of epidemiological associations observed in unrelated individuals

Smoking status available for 26020 subjects with followup data

226 suicides

Causal relationship or confounded by psychiatric illness and/or family factors?

Men smokstat = never smokstat = Former smokstat = Current
20 40
Age (years)
60 80

The discordant pair design
Non-smoker
Cotwin (alive or death from other causes)
Smoker
A
C
Non-smoker Smoker
B
D
Pairs from cells A and D are non-informative
The ratio B/C is an estimate of the risk associated with smoking controlling for family/genes. Statistical significance tested by
McNemar’s test, and conditional logistic regression

Suicides and smoking in twin pairs

In the discordant pairs, there were 23 pairs in which the suicide case was a current smoker in 1975 and the cotwin
(non-suicide) was a never smoker, vs. 2 pairs in which the suicide case was a never smoker and the cotwin was a current smoker. The OR is 11.5, 95% CI 2.84 – 100). Chisq(1)=17.4, p<0.0001

The numbers for MZ pairs were 5 vs. 0, exact McNemar p=0.06

The association between current smoking and suicide is independent of family factors, probably causal.

Outline

Causality and observational epidemiological studies

Value of heritability estimates

Accounting for missing heritability?

Early consequences of weight gain and mechanisms in obesity

Linkage to hospital discharge registry and
National Insurance Institute medication registry to identify diabetes cases to end of 2004
16430 twin pairs baseline cohort (MZ,
DZ, XZ)
Total of 2336 diabetes cases, of which
2077 type 2 diabetes
(rest are T1DM, gestational DM and secondary cases)
Lehtovirta et al, Diabetologia
2010
Photo: Elina Ketola, Helsinki

(Lehtovirta et al, Diabetologia 2010)
Risk for T2D in the twins with an affected cotwin

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Heritability >70% using a frailty model,
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Strong phenotypic association with BMI, but less than
20% was due to shared genetic effects
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Development of novel methods to correctly take into account censorship in survival analyses (Hjelmborg et al)

Competing causes of death/co-morbidity

A Genome Wide Association Study Identifies 31 Genetic Loci
Associated with Human Serum Metabolites
• Aim was to estimate the heritabilities and catalogue genetic variants modifying circulating levels of 216 metabolic traits identified using thorough techniques
1 H NMR metabonomic screening
• We test for associations between 7.7 million genetic markers derived from 1000 genomes European imputation reference and metabonomic measurements in 8322 randomly ascertained Finnish individuals
• Gwas reveals thirty-three independent genomic markers associated with one or more metabolites
• Ft12 and FT16 data used to estimate heritability and as a independent replication data set
• Together, these loci explain up to 40% of the genetic variance in an individual metabolic measure.
• Fifteen of the loci are novel

Heatmap of associations with the novel loci across all metabolites. LIPO,
LIPID and LMWM refer to the spectral windows utilized in the quantification.
Significant associations
(p<2.31*10 -10 ) are presented with black outline in the figure.

The heritabilities (blue) and proportion of variance explained by significant SNPs in metabonomic traits

Outline

Causality and observational epidemiological studies

Value of heritability estimates

Accounting for missing heritability?

Early consequences of weight gain and mechanisms in obesity

Heritability of BMI is considerable
Twin Research 2003; 6(5): 409-421
Based on comparison of MZ to DZ twin similarity, using standard twin modelling approaches to estimate heritability

0,4
0,3
0,2
0,1
0
0,9
0,8
0,7
0,6
0,5
Men Women
Australia Denmark Italy Finland Netherlands Sweden UK
Notable lack of shared environmental effects – i.e. non-genetic factors common to family members

Coming together of many events
Slide based on Mark McCarthy, 2009

Mark McCarthy, modified from Nat Reviews Genetics 2008

Peter M. Visscher, Matthew A. Brown, Mark I. McCarthy, and Jian Yang. Five Years of GWAS Discovery. Am J Hum Genet 2012 (online)

Published Genome-Wide Associations through 03/2011,
1,319 published GWA at p≤5x10 -8 for 221 traits
NHGRI GWA Catalog www.genome.gov/GWAStudies

Genome-wide Case-Control Analyses

Three large lung cancer GWAs in 2008 identified chr 15q25 region with nicotinic receptors alpha5, alpha3, beta 4 as linked to smoking/nicotinic dependence

Pooled GWAs increase sample size and power to detect contributing genes (CGASP,
TAG, OX-GSK, ENGAGE)
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Three coordinated papers published in May
2010 issue of Nature Genetics on 143 000 subjects

Over past few years hundreds of new genes in tens of common diseases and traits have been identified
 http://www.genome.gov/gwastudies

Figure 2

The CHRNA5 SNP

Accounts for 1% of the variance in cigarettes per day but 4.3% of the variance in serum cotinine levels
(Keskitalo et al, 2009,
Munafo et al, 2012)

Results in an amino acid change in α5 , D398N
 The high risk α5 Asn 398 is associated with reduced permeability of Ca 2+ et desensitises faster than the wildtype variant Asp
398(α4β2)
2 of α5 (Kuryatov
2011)
Cigarettes per day
N
Genotype of rs1051730
GG
10.1
5956
GT
11.2
TT
12.2
6287 1702
Fowler et al,
Nature 2011
Kuryatov, A., Berrettini, W. & Lindstrom, J. Acetylcholine receptor (AChR) a5 subunit variant associated with risk for nicotine dependence and lung cancer reduces (a4b2)2a5 AChR function. Mol. Pharmacol. 79, 119–125 (2011).

GIANT study

Gwas meta-analysis associations between body mass index (BMI) and ~2.8 million SNPs in 123,865 individuals

Targeted follow-up of 42 SNPs in 125,931 additional individuals. Confirmed 14 known obesitysusceptibility loci and identified 18 new loci associated with BMI (P<5x10-8)

Speliotes EK et al. Association analyses of 249,796 individuals reveal eighteen new loci associated with body mass index. Nature Genetics, 2010

Accounts less than 5% of the variance

Very few persons have very many risk alleles
Obesity is a multifactorial disorder influenced by multiple genes
Each gene has a small impact on disease risk
Universally acting genes appear to play a minor role

Lusis et al, Nat Rev Genetics 2008; 9: 819-30
Manolio TA et al, Nature, 461: 747-733 (October) 2009

Peter M. Visscher, Matthew A. Brown, Mark I. McCarthy, and Jian Yang. Five Years of GWAS Discovery. Am J Hum Genet 2012 (online)

90
80
70
60
50
40
30
20
10
0
11 y
(Ft12)
14 y
(FT12)
16 y
(FT16)
17 y
(FT12)
17 y
(FT16)
Genetic Common environment
25 y
(FT16)
Pietiläinen et al. 1999, Mustelin et al. Int J Obes 2009, Lajunen et al. Int J Obes 2009
> 4000 pairs from Finnish FT12 and FT16 cohorts

Conceptual model of individual’s phenotype:
Y = μ + G + C + E, and where Environment = C+E
I.e. we assume independent effects
Hence, variance can be decomposed:
σ 2 = σ 2 G + σ 2 C + σ 2 E
Is the assumption of no gene-environment interaction realistic?

M
G-E interaction model
(Purcell S, Twin Research 2002)
T is phenotype in classic twin model, A additive genetic effect, C common environmental and E uniquE environmental; M is moderator variable
A a+ β
X
M
C c+ β
Y
M e+ β
Z
M
E
μ+β
M
M
T

Low Medium
Leisure time physical activity
High
Mustelin L et al, Int J Obes 2009 (based on Finntwin16 adults)
Now replicated in three other twin data sets (Vietnam Era vets , FinnTwin12,
Geminakar – both papers in Am J Clin Nutr 2009)

Heritability of different obesity indicators by physical activity in the pooled data of Danish and Finnish men and women
Low Medium
Physical activity
High
BMI
Waist circumference
Proportion of fat body mass
Silventoinen et al, Am J Clin Nutr, 2009

Multiple genes and g by e interaction
Willer et al, Nat Genet 2009:41:25-
34

Significant interactions of physical activity and genetic BMI risk score on BMI (crosssectionally) and weight change
(prospectively)

SNPs representing the obesity susceptibility loci near or in
NEGR1, SEC16B, TMEM18, ETV5, GNPDA2, BDNF,
MTCH2, FAIM2, SH2B1, FTO, MC4R, and KCTD15 genes summed to form a genetic risk score

Work and leisure physical activity index

Covariates and comorbidies did not affect interactions

Li S et al. Physical activity attenuates the genetic predisposition to obesity in 20,000 men and women of
European descent. PLoS Med, 2010

Cross-sectional analysis

1 1
0
0
4
Low
Dick et al, J Abn Psychol, 2007
6 7 8 9
Monitoring
10
High
11 12 a2
Additive genetics c2
Shared envirome nt
Specific e2
Envirome nt

Odds ratio for heavy versus light smoking and rs16969968 allele
A across studies where subjects are stratified by age of onset of regular smoking (AOS) at or before age 16 versus after age 16..
Hartz S et al.
Increased genetic vulnerability to smoking at CHRNA5 in early-onset smokers (Arch Gen
Psychiatry, 2012)

Meta-analysis of association between rs16969968 genotype and heavy (CPD > 20) vs. light (CPD ≤ 10) smoking, stratified by earlyonset (onset ≤ 16) and late onset (onset > 16) smoking. Odds ratios are given relative to late-onset smokers with GG genotype (Hartz et al, Arch Gen Psychiatry in press)
Interaction between rs16969968 A allele and early-onset smoking on risk of heavy smoking, OR= 1.16, n=36,936, P=0.01

Chen et al, Addiction 2009

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FinnTwin16, 90% of all twins born in Finland 1975-79 n=2453 pairs at 25 y kg/m 2
45
40
35
30
25
20
15
MZ twins r=0.79
p<0.001
15 20 25 30 35 40 45
Twin A, BMI kg/m 2 kg/m 2
45
40
35
30
25
20
15
DZ twins r=0.37
p=0.03
15 20 25 30 35 40 45
Twin A, BMI kg/m 2
Kaprio J, FinnTwin16

FinnTwin16
Birth cohorts 1975-1979
N=2500 twin pairs at 25 y
N=658 MZ-pairs
14 obesity-discordant
MZ-pairs, > 10 kg diff
BMI
Obese co-twins
15 kg, 20% heavier
70% more sc fat
100% more ia fat
280% more liver fat
0 5 10 15 20 y

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Fasting blood samples for DNA, routine hematology, chemistry and lipids, cytokines, neuropeptides, lipidomics etc body composition and anthropometrics by DXA, bioelectrical impedance, skinfolds, and circumferences body fat accumulation (subcutaneous and visceral fat content by
MRI, intrahepatic and intramyocellular fat content by proton spectroscopy) adipocyte gene expression from subcutaneous fat biopsies, candidate genes and genome-wide microarray analyses in MZ discordant twins, mitochondrial DNA sequencing & telomere length assays, epigenetics

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intra-arterial endothelic function whole body insulin sensitivity under normoglycemic hyperinsulinemic conditions
(the clamp technique)
Faeces samples and microbiome analyses test meal with ghrelin and leptin assays
PROP- and fat-tasting procedures resting energy expenditure (indirect calorimetry) and a 14 day-total energy expenditure in free living conditions (the doubly labeled water technique)
Accelerometers & physical fitness by bicycle spiroergometer questionnaires and interviews on past and current food intake, food preferences, physical activity, use of alcohol and smoking, health-related attitudes, weight history, family history and quality of life structural and functional brain MRI, SPET autonomic nervous system assays structured psychiatric interview questionnaires and interviews of the parents

%
100
75
50
25
0
%
100
75
50
25
0
Non-obese Obese
Pietiläinen et al. Am J Phys Endo Met 2005
Pietiläinen et al. Obesity 2006

2-3 –fold upregulation of inflammatory pathways
%
Non-obese Obese
Pietiläinen et al. PLoS Med 2008

Proinflammatory
LysoPCs
Antioxidant
Plasmalogens
Pietiläinen et al. PLoS One 2007

Fatty acid composition of adipose tissue in acquired obesity
Fatty acid profile was measured in adipose tissue biopsies in each of the 44 subjects.
Selected fatty acid relative amounts in 13 twin pairs discordant for BMI. Lines connect the cotwins.
Pietiläinen et al. Association of Lipidome Remodeling in the Adipocyte
Membrane with Acquired Obesity in Humans. Plos Biol 2011

Schematic representation of fatty acid compositional changes when comparing heavy and lean obesity-discordant co-twins. Significant changes (p < 0.05; pairwise t-test) are marked with colors. The activities of specific fatty acid elongation or desaturation steps are estimated by appropriate fatty acid concentration ratios.
Plos Biol 2011

Regulation of lipid remodeling in adipose tissue.
A dependency network was constructed from the selected gene expression, clinical, and lipidomic data from twin pairs discordant for
BMI. Node shapes represent different types of variables and platforms (L,
UPLC-MS lipidomics; FA, GC fatty acids; GE, gene expression), node color corresponds to significance and direction of regulation , and line width is proportional to strength of dependency.

Model of physiological regulation of lipid membrane composition in obesity
PL, phospholipid; PUFA, polyunsaturated fatty acid; SFA, saturated fatty acid; MUFA, monounsaturated fatty acid.
Pietiläinen et al, Plos Biol 2011

Outline

Causality and observational epidemiological studies

Value of heritability estimates

Accounting for missing heritability?

Early consequences of weight gain and mechanisms in obesity

Same designs can be used to address questions about the epigenome

The microbiome

Rare variants

Need to master many methods and approaches/need to collaborations

A tour of possibilities made possible by twin studies

A jack of all trades,
 master of none,

Though oftentimes better master of one


Due to prenatal exposure to testosterone from opposite-sex twin (organizational effects of testosterone). Phenotype with known sex difference and correlation with (prenatal) testosterone

Due to postnatal socialization as a result of growing up with same age brother (exposure to male typical toys and activities). Phenotype with known sex difference and effect of practice.

• Males score on average even 1 SD higher than females. Range of effect size
(depending on task) d = .75 – 1.00 (Voyer et al., 1995)
• Internet study: data from 53 countries (Lippa et al., 2010)
 MRT: males scored higher than females in all countries d = .47 (150 second time limit, six trials of Vandenberg and Kuse MRT)
• Females with CAH perform better than non-CAH females in male favoring spatial tests, males with CAH perform worse than non-CAH males (possible organizational effects of testosterone on spatial abilities, meta-analysis: Puts et al., 2008)
• Sex difference in MRT evident in 5 month olds
Vandenberg and Kuse MRT (based on the stimuli by Shepard and Metzler, 1971)

Fig. 1. Mean mental rotation test scores (with 95% confidence intervals) for females and males from same-sex and opposite-sex twin pairs.
Vuoksimaa E et al. Psychological Science 2010;21:1069-
1071
Copyright © by Association for Psychological Science

Females from opposite-sex pairs (n=100, black fraternal twin bar) performed better than females from same-sex dizygotic pairs (n=100, white fraternal twin bar), non-twin females with slightly older sister (n=100, white sibling bar) or non-twin females with slightly older brother (n=100, black sibling bar)
Masculinization of mental rotation ability
(V-K MRT) replicated in Heil et al. (2011)
Biol Psychol.
Mental rotation performance (MRT score) as a function of “relation” (fraternal twin vs. regular sibling) and “sibling's sex” (same vs. opposite). Error bars indicate standard errors.

No difference in fluctuating levels of testosterone and estradiol at age 14
Mean testosterone levels (with 95% confidence intervals) of two saliva samples for same-sex female (SSF), opposite-sex female
(OSF), same-sex male (SSM), and opposite-sex male (OSM) twins from FinnTwin12.
Vuoksimaa et al. (2010) Psychoneuroendocrinology, 35, 1462-1472.