Transcript (Title of Presentation) - Virginia Commonwealth University

Broa
d
Bulim
ia
Alco
hol D
epen
denc
e
Alco
hol A
b /De
p
Nico
tine A
b/De
p
Ca ffe
ine H
eavy
Use
Any
Drug
Ab/D
ep
Ca nn
abis
Ab /D
ep
Sed a
tive A
b/De
p
Stim
ulant
Ab/D
ep
Co ca
ine A
b/De
p
Opia
te Ab
/Dep
Ha llu
cinog
en A
b/De
p
ial Pe
rs
Antis
oc
Co nd
uct D
isord
er
proportion affected
Lifetime Prevalences of Externalizing and Substance
Use Disorders
Among Twins from Same-Sex Pairs
0.5
0.4
0.3
0.2
females
males
0.1
0
3-Stage Conditional Model
Contingent Causal Common Pathway
AI
CI
EI
AR
CR
ER
Regular
Tobacco Use
Tobacco
Initiation
AD
CD
ED
Persistence /
Nicotine
Dependence
Proportions of Variance
Best Fitting CCC Model
TI
RU
ND
.89
.69
TI
RU
FTND
.87 -.29
.93
TI
RU
P
0%
.87
.70
20%
40%
60%
80%
100%
Ai
Ar
Ad
Ei
Er
Ed
No significant sex differences in proportions of variance or causal paths, but sex
differences allowed in thresholds,
No significant shared environmental effects for TI, RU and ND
Genetic Epidemiology of
Alcoholism
• Family Studies
• Adoption Studies
– Denmark
– Sweden
• Twin Studies
– Virginia, Sweden, Australia, WW-II and
Vietnam Era Veteran twin registries
Estimated Genetic Proportions of Variance in Risk
for Substance Abuse/Dependence
0.8
0.7
0.6
females
males
combined
0.5
0.4
0.3
0.2
0.1
ens
Hal lu
cinog
Coca
i ne
ulant
s
Stim
Seda
t ives
Cann
abis
Subs
t ance
Any
Opi a
tes
0
0
Genetic Epidemiology of Substance
Abuse
• How do genetic risk factors for drug abuse
relate to risk for psychiatric disorders?
Genetic Factors
AC2
.54
Major
Depression
.00
.53 .13
.24
ASP
.33 .06
GAD
.00
AC1
Phobia
.22
ASP
.10 .58
Drug
Abuse
or Dep
Alcohol
Dep
.38
ASP
.18 .65
.46
ASP
.21 .56
.11
Adult
Antisocial
Behavior
.00
ASP
.37
Conduct
Disorder
.17
ASP
ASP
Genetic Epidemiology of Substance
Abuse
• How well does personality capture the
genetic risk factors for substance initiation?
Results from Bivariate Twin Model for Overlap of
Novelty Seeking and Cannabis Use among Males
Shared
Environ
Genetic
17%
0%
Individual
Environ
83%
Shared
Environ
Genetic
3%
7%
5%
42%
Individual
Environ
25%
18%
Novelty Seeking
Cannabis Use
Adapted from Table 1, Agrawal et al (2004), Twin Research, 7, 72-81
Are the Genetic Risk Factors for Drug
Abuse in Part Genes for Personality?
• Genetic correlation between Novelty
seeking (NS) and
– Cannabis use – Males +0.96,
Females +0.19
– Cocaine use – Males +0.62, Female
+0.30
Are the Genetic Risk Factors for Drug
Use in Part Genes for Personality?
• Genetic correlation between
Extraversion and
– Cannabis use +0.42
– Cocaine use +0.36
• Genetic correlation between
Neuroticism and
– Cannabis use +0.18
– Cocaine use +0.18
Genetic Epidemiology of Substance
Abuse
• How do the genetic risk for different forms of
substance abuse relate to each other?
Genetic Epidemiology of Substance
Abuse
• Begin to consider mediational models
• Genes → Intermediate phenotype → Drug
Use
• Or, how do genes contribute to well
understood risk factors for drug use and
abuse?
Study the Availability of Drugs
Life history data collection
8-11yrs
12-14yrs
15-17yrs
18-21yrs
22-25yrs
Measures of drug availability
- Alcohol
- Marijuana
- Cigarettes - Cocaine
- Stimulants
“When you were…how
easy would it have been
to get [substance] if you
wanted to use (it /
them)?”
0. Very easy
1. Somewhat easy
2. Somewhat
difficult
3. Very difficult
Item endorsement
Alcohol
Age
0
1
2
3
8-11
21%
17%
22%
41%
12-14
29%
27%
23%
21%
15-17
52%
31%
11%
6%
18-21
89%
9%
2%
<1%
Item endorsement
Marijuana
Age
0
1
2
3
8-11
2%
4%
6%
88%
12-14
8%
11%
16%
65%
15-17
24%
21%
19%
36%
18-21
45%
25%
14%
17%
22-25
46%
26%
14%
13%
Item endorsement
Cocaine
Age
0
1
2
3
8-11
<1%
1%
2%
96%
12-14
2%
2%
9%
88%
15-17
6%
8%
18%
68%
18-21
17%
17%
21%
46%
22-25
21%
18%
23%
39%
3
Alcohol
2
2
E
C
A
1
1
0
8-11yrs
1
12-14yrs
2
3
15-17yrs
4
18-21yrs
0.60
0.50
0.40
A
0.30
C
E
0.20
0.10
0.00
1
8-11yrs
2
12-14yrs
3
15-17yrs
4
18-21yrs
7
Marijuana
6
5
4
E
3
C
A
2
1
0
1
8-11yrs
2
12-14yrs
3
15-17yrs
4
18-21yrs
5
22-25yrs
1.00
0.80
A
0.60
C
E
0.40
0.20
0.00
8-11yrs
1
12-14yrs
2
15-17yrs
3
18-21yrs
4
22-25yrs
5
9
8
Cocaine
7
6
5
E
C
4
A
3
2
1
0
1
8-11yrs
2
12-14yrs
3
15-17yrs
4
18-21yrs
5
22-25yrs
1.00
0.90
0.80
0.70
0.60
A
0.50
C
E
0.40
0.30
0.20
0.10
0.00
1
8-11yrs
2
12-14yrs
3
15-17yrs
4
18-21yrs
5
22-25yrs
N
1. 8-11 Cigarettes (b42)
1790
2. 12-14 Cigarettes (c42)
1795
3. 15-17 Cigarettes (d42)
1792
0
1
43.5
20.4
56.8
24.3
78.4
15.6
2
3
15.1
20.9
12.0
6.8
4.1
2.0
• Unstandardized and standardized
proportions of variance in CIGARETTE
availability. Variance components include
latent genetic and environmental effects
attributable to intercept and slope factors in
the full biometrical DCS model.
3.50
3.00
2.50
2.00
1.50
1.00
0.50
0.00
1
2
3
1.00
0.90
0.80
0.70
0.60
0.50
0.40
0.30
0.20
0.10
0.00
1
2
3
Other Key Intermediate Phenotype –
Peer Group Deviance
• Genes can act to increase liability to drug use
disorders through influencing selection into
high risk environments.
– Example here – deviance of peer group
– Many studies show peer group deviance to
be a powerful predictor of subsequent drug
use.
Modeling Time and Development
and “Outside the Skin” Pathways
• Measures of peer group deviance
retrospectively reported by a life history
method.
• ~750 male-male twin pairs from Virginia Twin
Registry.
• Evaluate 4 ages.
• Use a latent biometrical growth curve model
– Can look separately at “genetics” of mean levels
at different ages and
– “Genetics” of slope (or trajectory).
Peer Group Deviance
35
30
25
20
15
10
5
0
A
C
E
8-11
12-14
15-18
Ages
19-22
Peer Group Deviance
100%
80%
E
C
A
60%
40%
20%
0%
8-11
12-14
15-18
Ages
19-22
Genetics of the Trajectory of Change
in Peer Group Deviance
From Ages 8-22
• a2 = 0.43
• c2 = 0.22
• e2 = 0.35
• So, not only is the mean levels of peer group
deviance influenced by genetic factors, but so
is the rate of change over time.
Prevalence And Heritability Of
Regular Tobacco Use
Three Birth Cohorts Of Men And Women In Sweden
0.8
0.6
Prevalence
Of
Heritability
0.4
0.2
0
1910-1924
1925-1939
1940-1958
Birth Cohort
Female Presence
Male Presence
Female Heritability
Male Heritability
Linkage And Association
• Linkage – in families. Sweeps entire genome.
Good for genes of moderate to large effect.
• Association – in populations. Examines only
small distances. Can detect genes of
relatively small effect.
• If a base pair equals 1 cm, the human
genome equals 33,000 km – around 80% of
the way around the world. A linkage peak for
a complex trait is ~ 200 km and association is
detectable over distances from 50-200
meters.
Irish Affected Sib-Pair Study of Alcohol Dependence
Samples & Measures
Probands ascertained
Interview & DNA
N=591
Affected siblings referred
Interview & DNA
N=610
(M=364, F=227)
(M=413, F=197)
Parents contacted
Brief Interview & DNA
N=213
(M=82, F=131)
Prescott et al., Alc Clin Exp Res, 2005
733 sib pairs
(sibship size: 2-8)
Control Groups
Screened n = 72
Semi-screened ~ 600
Sample & Measures
IASPSAD families with DNA and informative
for linkage (N=511 sib pairs, 485 families)
4 cM genome scan - deCODE genetics (Iceland)
1081 markers x 1500 individuals (1,621,500)
Outcomes used for linkage analysis
AD: DSM-IV Alcohol dependence
SX: DSM-IV AD symptom count (range 3-7)
Genome-wide LOD Scores for
DSM-IV Alcohol Dependence
Ch22
5
4
3
Ch13
2
LOD 1
0
-1
-2
-3
Ch1
chromosome position
22
21
20
19
18
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
Genome-wide LOD Scores for DSM-IV
Alcohol Dependence Symptoms
5
22
21
20
19
18
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
4
3
2
LOD 1
0
-1
-2
-3
Ch4
cM
Chromosome 4 Linkage Results
5
Peak LOD = 4.59
(p<.000002)
4.5
4
3.5
Symptom Count
Alcohol Dependence
3
2.5
LOD 2
1.5
1
0.5
0
-0.5
0
50
100
150
-1
chromosome 4 position (cM)
200
Chromosome 4 linkage in other studies
Southwest Indians:
5
AD – Long et al. 1998
4.5
U.S. Collaborative (COGA):
4
3.5
# symptoms – Reich et al 1998;
max drinks - Saccone et al., 2000;
alc response - Schuckit et al., 2001;
severity – Corbett et al, 2005
Symptom Count
Alcohol Dependence
3
2.5
Mission Indians:
LOD 2
severity - Ehlers et al., 2004
1.5
1
0.5
0
-0.5
0
50
100
150
-1
chromosome 4 position (cM)
200
Chromosome 4 NPL LOD Scores for
Symptom Dropping Analyses
5
ADSX
medical consequences
lack of control
restricted activities
withdrawal
failed to quit
binging
tolerance
4
Lod
3
2
1
0
0
50
100
-1
cM
150
200
5
4.5
4
3.5
Symptom Count
Alcohol Dependence
ADH cluster
3
(1a,1b,1c,4,5,6,7)
2.5
LOD 2
1.5
1
0.5
0
0
50
100
150
-0.5
-1
chromosome 4 position (cM)
200
ADH Follow-Up Association Studies
• 27 SNP markers identified in 7 genes
• Unrelated Case-Control design
Stage 1:
• 328 cases randomly selected from probands & affected sibs
• 328 screened population controls
• Single-marker analyses
• Haplotype analyses
– Haploview, WHAP
ADH Marker information
• 24 markers genotyped in ADH gene
– ADH5 (including 3 SNPs: RS896992 RS1154405 RS1154400)
– ADH4 (including 4 SNPs: RS1042364 RS1984360 RS1126671
RS4699712)
– ADH6 (including 3 SNPs: RS3857224 RS2187483 RS4699733)
– ADH1A (including 2 SNPs: RS1229976 RS1229967)
– ADH1B (including 3 SNPs: RS1042026 RS1789882
RS1353621)
– ADH1C (including 3 SNPs: RS1614972 RS1662060 RS3133158)
– ADH7 (including 6 SNPs: RS894369 RS284786 RS1154454
RS1154458 RS1154460 RS971074)
Block structures of ADH gene from Haploview
Standard Color Scheme
D' < 1
D' = 1
LOD < 2
white
blue
LOD
>=2
shades of
pink/red
bright
red
Association results for single marker analyses
(All data, filter out genotype missing over
25%, n=644)
p<.05
p<.10
(No missing data, n=383)
Haplotype association results for each block
All Subjects (n=644)
Excluding cases with
missing data (n=383)
Carol: Block 3 here is the Block 4 in
above table. Notice that in the
sample including only non-missing
data, LD map from Haploview
doesn’t have the block of marker 19
& 20
The role of GABAA in alcohol dependence
Most of the genes encoding for GABAA receptor subunits
are organized in clusters located on different
chromosomes. Thus, GABRA2, GABRA4, GABRB1, and
GABRG1, encoding α2, α4, β1 and γ1 are on chromosome
4p13-12 whereas GABRA5, GABRB3, and GABRG3
encoding for α5, β3 and γ3 are located on 15q11-13. The
clustering may have functional significance as studies
suggest that variations in GABAA receptor genes
contribute to differences in risk for alcoholism.
Alcoholism and GABAA receptor genes on 4p13-12
Several studies have reported the potential association of GABAA
receptors and alcohol dependence.
Song et al (2003) performed a family based association study using the
large COGA (Collaborative Study on the Genetics of Alcoholism) sample.
A modest association (P<0.03) was observed with GABRB1 and AD using
microsatellite markers.
Variations in GABRA2 were shown to be highly associated with AD as
well as the beta frequency of the electroencephalogram (Edenberg et al,
2004). A comparision of the high-risk and low-risk haplotype coding
sequences showed no differences hence the effect was postulated to be
mediated through gene regulation. Further work has revealed a complex
pattern of alternative splicing and promoter use (Tian et al, 2005).
Other studies include Covault et al (2004) who reported an allelic and
haplotypic association with GABRA2 and AD. Lappalainen et al (2005)
showed that GABRA2 may play a role in risk for AD in a Russian
population.
LD Pattern - D’ Plot
Single marker results using Whap
SNP rs #
HapMap location
GABAA gene
P-value
1497570
45962576
GABRG1
0.836
1948609
45978314
GABRG1
0.683
2221020
46019107
GABRG1
0.947
1391168
46030701
GABRG1
0.541
490434
46108821
GABRA2
0.0075
497068
46166219
GABRA2
0.0165
279871
46221275
GABRA2
0.0167
279858
46230135
GABRA2
0.0678
279845
46245265
GABRA2
0.0685
279826
46249751
GABRA2
0.226
279827
46250244
GABRA2
0.138
279828
46250352
GABRA2
0.255
279836
46254612
GABRA2
0.0304
2055943
46882821
GABRA4
0.767
1512135
46889430
GABRA4
0.724
2280072
46910712
GABRA4
0.193
2055940
46913455
GABRA4
0.413
989808
47082323
GABRB1
0.219
1372496
47123350
GABRB1
0.000004
6284
47237761
GABRB1
0.987
2070922
47321590
GABRB1
0.375
Results of haplotype analysis using Whap
GABRA2
HAPLOTYPE
FREQUENCY
P-VALUE
122212221
0.485
0.0205
211121112
0.470
0.0556
222212221
0.019
0.142
121121112
0.015
0.411
122221111
0.011
0.184
HAPLOTYPE
FREQUENCY
P-VALUE
1222122211
0.389
0.817
2111211121
0.368
0.00352
2111211122
0.109
0.0322
1222122212
0.102
0.0000697
2222122211
0.017
0.25
1211211121
0.015
0.427
GABRA2 & GABRB1
This study provides further evidence that GABRA2
receptor gene is associated with AD. Previous studies
have shown that SNPs in the 3’ region of the α2 subunit
are significantly associated with AD (Covault et al, 2004;
Edenberg et al, 2004). This study replicates the earlier
findings; SNP rs490434 which is localized to the 3’
region produced a P-value of 0.0075. However the most
significantly associated SNP in the current study is
localized to GABRB1. SNP rs1372496 gave a single
marker significance (P-value = 0.000004) when analyzed
for AD.
Association Studies of Smoking
Initiation and Nicotine Dependence
• Unrelated subjects from two twin studies
• Subjects were classified into 3 groups based
on the score of the Fagerstrom Tolerance
Questionnaire
– 244 NonSmokers
– 215 Low-ND smokers (FTQ score 0-2)
– 229 High-ND smokers (FTQ score 7-11)
A Summary of Genes Studied
Gene
chr function
SI
ND
Epac
12
cAMP signal transduction pathway
±
+
PTEN
10
regulate AKT/PKB pathway
++
+
Rhoa
3
Ras gene family, signal pathway
+++ ±
Ywhag
7
signal transduction (mitosis and cellular
proliferation)
-
-
MAP3K2
2
MAPK signaling pathway
-
-
MAP3K4
6
MAPK signaling pathway
-
-
MAP12
22
MAPK signaling pathway
±
±
ARHGAP
15
2
a potential regulator of Rac1
-
+
GABAB2
9
GABA B2 receptor
-
-
OPRM1
6
opioid mu receptor
+
+
Sam CHEN
July 20, 2015
PTEN: Single Marker
Association
Genotype
Marker name
Allele
SI
ND
SI
ND
P-value
P-value
P-value
P-value
rs1234221
0.0898
0.2437
0.0311
0.7252
rs2299939
0.7165
0.8929
0.5279
0.7720
rs1234213
0.0007
0.0821
0.0002
0.0278
rs2735343
0.0036
0.3908
0.0028
0.2105
rs701848
0.4749
0.0856
0.1503
0.1161
Sam CHEN
July 20, 2015
PTEN: Haplotype Association
Marker
Global
p value
Haplotype
Frequency
(case:ctrl)
Odds
ratio
Haplotype
p value
Smoking Initiation
1-3
0.0053
1-2
0.36:0.27
1.33
0.0017
3-5
0.0078
2-1
0.35:0.26
1.38
0.0006
1-3-5
0.0431
1-2-1
0.32:0.24
1.34
0.0037
1-2-3-4
0.0308
1-1-2-2
0.34:0.27
1.25
0.0167
2-3-4-5
0.0647
1-2-2-1
0.34:0.26
1.28
0.0105
1.3
0.0058
Nicotine Dependence
3-5
Sam CHEN
0.0504
2-1
0.40:0.31
July 20, 2015
Rhoa: Single Marker Association
Allelic association
Marker
Genotype association
SI
ND
SI
ND
rs6784820
0.04319
0.47528
0.10830
0.74069
rs2177268
0.10068
0.28590
0.23371
0.51899
rs2878298
0.00349
0.70204
0.00005
0.00070
rs974495
0.26305
0.75573
0.11984
0.92688
rs3448
0.10857
0.55643
0.27922
0.80291
Sam CHEN
July 20, 2015
Rhoa: Haplotype Association (SI)
Marker
Haplotype
Case
Freq
Control
Freq
OR
Chisq
P value
1-3-4
1-1-2
180.5
0.292
68.8
0.189
1.8
8.16
0.0043
2-1-1
69.4
0.112
74.6
0.205
0.7
13.38
0.0003
2-2-1
83.7
0.136
16.2
0.045
4
7.52
0.0061
Global:
LRS
28.89
DF
6
P
6.38E-05
Marker
Haplotype
Case
Freq
Control
Freq
OR
Chisq
P value
1-3-4-5
1-1-2-2
100.0
0.171
29.7
0.086
2.0
7.39
0.00657
2-1-1-1
62.5
0.107
70.8
0.205
0.5
12.76
0.00035
2-2-1-1
82.1
0.140
14.6
0.042
3.3
9.57
0.00198
Global:
LRS
DF
P
Sam CHEN
33.08
8
5.96E-05
July 20, 2015