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Lack of replication of the GRIN2A-by-coee interaction
in Parkinson disease.
Ismaïl Ahmed, Pei-Chen Lee, Christina M Lill, Susan Searles Nielsen, Fanny
Artaud, Lisa G Gallagher, Marie-Anne Loriot, Claire Mulot, Magali Nacfer,
Tian Liu, et al.
To cite this version:
Ismaïl Ahmed, Pei-Chen Lee, Christina M Lill, Susan Searles Nielsen, Fanny Artaud, et al.. Lack of
replication of the GRIN2A-by-coee interaction in Parkinson disease.. PLoS Genetics, Public Library
of Science, 2014, 10 (11), pp.e1004788. �10.1371/journal.pgen.1004788�. �inserm-01160040�
Formal Comment
Lack of Replication of the
GRIN2A
-by-Coffee Interaction
in Parkinson Disease
Ismaı
¨
l Ahmed
1,2.
, Pei-Chen Lee
3.
, Christina M. Lill
4,5.
, Susan Searles Nielsen
6.
, Fanny Artaud
7,8
,
Lisa G. Gallagher
6
, Marie-Anne Loriot
9,10
, Claire Mulot
10,11
, Magali Nacfer
10,11
, Tian Liu
12
,
Joanna M. Biernacka
13
, Sebastian Armasu
13
, Kari Anderson
13
, Federico M. Farin
6
,
Christina Funch Lassen
14
, Johnni Hansen
14
, Jørgen H. Olsen
14
, Lars Bertram
4,15
,
Demetrius M. Maraganore
16
, Harvey Checkoway
17
, Beate Ritz
18"
, Alexis Elbaz
7,8"
*
1 INSERM, Centre for research in Epidemiology and Population Health, U1018, Biostatistics team, Villejuif, France, 2 Univ P aris-Sud, UMRS 1018, Paris, Villejuif, France,
3 Department of Health Care Management, College of Healthcare Administration and Management, National Taipei University of Nursing Health Sciences, Taipei, Taiwan,
4 Department of Vertebrate Genomics, Neuropsychiatric Genetics Group, Max Planck Institute for Molecular Genetics, Berlin, Germany, 5 Department of Neurology, Focus
Program Translational Neuroscience, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany, 6 Department of Environmental and
Occupational Health Sciences, University of Washington, Seattle, Washington, United States of America, 7 INSERM, Centre for research in Epidemiology and Population
Health, U1018, Social and occupational determinants of health, Villejuif, France, 8 Univ de Versailles St-Quentin, UMRS 1018, Versailles, France, 9 Assistance Publique
Ho
ˆ
pitaux de Paris, Ho
ˆ
pital Europe
´
en Georges Pompidou, Service de Biochimie, Paris, France, 10 Universite
´
Paris Descartes, Inserm, UMR-S1147, Me
´
decine personnalise
´
e,
Pharmacoge
´
nomique et optimisation the
´
rapeutique, Paris , France, 11 Centre de ressources biologiques (CRB) Epigenetec, Paris, France, 12 Max Planck Institute for
Human Development, Berlin, Germany, 13 Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America, 14 Danish Cancer
Society Research Center, Danish Cancer Society, Copenhagen, Denmark, 15 Department of Medicine, School of Public Health, Imperial College London, London, United
Kingdom, 16 Department of Neurology, NorthShore University HealthSystem , Evanston, Illinois, United States of America, 17 Department of Family and Preventive
Medicine, University of California, San Diego, La Jolla, California, United States of America, 18 Department of Epidemiology, Fielding School of Public Health, University of
California Los Angeles, Los Angeles, California, United States of America
Overview
The etiology of Parkinson disease (PD) involves both genetic
susceptibility and environmental exposures. In particular, coffee
consumption is inversely associated with PD but the mechanisms
underlying this intriguing association are unknown. According to a
recent genome-wide gene–environment interaction study, the
inverse coffee–PD association was two times stronger among
carriers of the T allele of SNP rs4998386 in gene GRIN2A than in
homozygotes for the C allele. We attempted to replicate this result
in a similarly sized pooled analysis of 2,289 cases and 2,809
controls from four independent studies (Denmark, France, Seattle-
United States (US), and Rochester-US) with detailed caffeinated
coffee consumption data and rs4998386 genotypes. Using a variety
of definitions of coffee drinking and statistical modeling tech-
niques, we failed to replicate this interaction. Notably, whereas in
the original study there was an association between rs4998386 and
coffee consumption among controls, but not among cases, none of
the datasets analyzed here indicated an association between
rs4998386 and coffee consumption among controls. Based on
large, well-characterized datasets independent from the original
study, our results are not in favor of an interaction between
caffeinated coffee consumption and rs4998386 for PD risk and
suggest that the original finding may have been driven by an
association of coffee consumption with rs4998386 in controls. The
next years will likely see an increasing number of papers
examining gene–environment interactions at the genome-wide
level, which poses important methodological challenges. Our
findings underline the need for a careful assessment of the findings
of such studies.
Introduction
Genome-wide association studies (GWAS) have identified
thousands of genetic risk variants for common diseases, which
typically explain only a small proportion of the underlying
heritability [1]. Unexplained or missing heritability could be
partly due to gene–environment interactions. PD is a good
example of a disease for which numerous susceptibility loci [2] and
putative risk or protective environmental factors [3] have been
identified and may interact. Among environmental factors, there is
robust epidemiological evidence that coffee consumption is
inversely associated with PD independently of smoking [4].
Caffeine is hypothesized to account for this association because
it is an adenosine A
2A
-receptor antagonist, and this family of
agents has been shown to be neuroprotective and attenuate loss of
Citation: Ahmed I, Lee P-C, Lill CM, Searles Nielsen S, Artaud F, et al. (2014) Lack
of Replication of the GRIN2A-by-Coffee Interaction in Parkinson Disease. PLoS
Genet 10(11): e1004788. doi:10.1371/journal.pgen.1004788
Editor: Jonathan Flint, The Wellcome Trust Centre for Human Genetics,
University of Oxford, United Kingdom
Published November 20, 2014
Copyright: ß 2014 Ahmed et al. This is an open-access article distributed under
the ter ms of the Creative Commons Attributi on License, which pe rmi ts
unrestricted use, distribution, and reproduction in any medium, provided the
original author and source are credited.
Funding: The French study was funded by Agence Nationale de la Recherche
(MNP 2009, IGE-MP). The Danish study was funded by NIEHS of the National
Institutes of Health under award number R01ES013717. Additional funding for
genotyping of the Danish samples was provided by the German Ministry for
Education and Research (BMBF, grant 16SV5538; to LB). The GWAS re-analysis of
the LEAPS dataset was partly funded by the Michael J. Fox Foundation (to LB). The
Seattle-US study was sponsored in part by University of Washington Superfund
Research Program, Grant # NIEHS P42ES004696; NIEHS R01ES010544 and NIEHS
P30ES007033 provided additional funding. The Rochester-US study was funded
by the National Institutes of Health grant R01ES10751. The funders had no role in
study design, data collection and analysis, decision to publish, or preparation of
the manuscript.
Competing Interests: The authors have declared that no competing interests
exist.
* Email: alexis.elbaz@inserm.fr
" BR and AE jointly directed the work.
. These authors contributed equally to this work.
PLOS Genetics | www.plosgenetics.org 1 November 2014 | Volume 10 | Issue 11 | e1004788
dopaminergic neurons in animal models of PD [5]; however, other
explanations for this association, including reverse causation or
confounding, cannot be discarded.
A recent genome-wide gene–environment interaction study in
PD (testing 811,597 single nucleotide polymorphisms [SNPs] across
1,458 cases and 931 controls) used a joint test of marginal
association and gene–environment interaction [6], followed by
analyses stratified by coffee consumption, to identify modifiers of the
coffee-PD association [7]. The inverse association between coffee
and PD was about two times stronger among carriers of the rare T
allele of rs4998386 in GRIN2A than in homozygotes for the major
C allele (odds ratio (OR) for interaction, OR
interaction
= 0.52,
p=4610
23
). This finding was replicated in a pooled analysis of
three independent US datasets (1014 cases, 1917 controls;
OR
interaction
= 0.48, p = 5610
24
). The authors concluded that the
inclusion of coffee consumption in their analyses to test for an
interaction with rs4998386 allowed them to uncover one of the most
important PD susceptibility genes, not previously identified in
GWAS due to its small overall effect. GRIN2A encodes a subunit of
the N-methyl-D-aspartate (NMDA) glutamate receptor and regu-
lates excitatory neurotransmission in the brain. The authors
considered it to be biologically plausible that GRIN2A plays a role
in PD through an interaction with caffeinated coffee and suggested
that GRIN2A genotypes may be a useful biomarker for pharma-
cogenetic studies on prevention and treatment in PD.
The study by Hamza et al. [7] represents one of the first
published attempts to identify gene–environment interactions at a
genome-wide scale, a challenging task given the requirement of
very large sample sizes with exposure data [8]. The results from
this study are of great interest as they may provide insight into the
PD–coffee association and thus the underlying pathophysiology of
PD. Analyses of gene–environment interactions can be performed
through a variety of approaches [8], and, to better understand the
findings presented by Hamza et al. [7], we performed a re-analysis
of their data by examining the association between coffee and
rs4998386 separately in cases and controls (Table S1). We found a
strong positive association in controls between rs4998386-T and
heavy coffee drinking (OR = 1.48, 95% CI = 1.23, 1.78,
p=3610
25
), thus suggesting that GRIN2A-rs4998386-T is
associated with an increased likelihood of drinking coffee among
persons free of PD. On the contrary, among PD cases, heavy
coffee drinking tended to be less frequent in carriers of the
rs4998386-T allele, but this association was not statistically
significant (OR = 0.82, 95% CI = 0.65, 1.03, p = 0.08). Therefore,
it appears that the interaction between rs4998386 and coffee
consumption was in part explained by a positive association
between the rs4998386-T allele and coffee consumption among
controls, but not among PD cases.
Because of the well-described constraints of genome-wide gene–
environment interaction analyses [8] and of this somewhat
unusual pattern of gene–environment interaction, our objective
was to replicate these findings by pooling data from four
independent and well-characterized studies, three of them
population-based, which had collected detailed coffee data.
Results
Our analyses comprised 2,289 cases and 2,809 controls with
complete data on coffee consumption, GRIN2A-rs4998386, and
ever smoking. Rs4998386 genotypes were in Hardy-Weinberg
equilibrium (HWE) in controls from each dataset (p$0.05) and the
frequency of the T allele was similar in controls across all studies
(ranging from 8.7% to 11.8%). Rs4998386 was not associated with
PD in any of the four datasets (Table S2). Danish participants had
the highest level of coffee drinking. Ever coffee drinking was
statistically significantly inversely associated with PD in the French
and Danish datasets; in the Seattle-US dataset, PD cases were less
frequently heavy coffee drinkers than controls, and there was no
statistically significant association of coffee drinking and PD in the
Rochester-US dataset (Table S2). Ever smoking was inversely
associated with PD in all studies (Table S2). In pooled marginal
association analyses of the French, Danish, and Seattle-US studies,
rs4998386 showed no evidence for association with PD risk while
ever coffee drinking was inversely associated with PD, showing a
dose-response relation for all coffee variables (Table S3).
Table S4 shows the cross-tabulation of rs4998386 and coffee
drinking by case-control status and dataset. Regardless of the
definition of coffee drinking, there was no consistent significant
departure from multiplicative effects of rs4998386 and coffee
drinking in any of the individual datasets (Table 1, Table S5). In
pooled analyses of the French, Danish, and Seattle-US datasets
(Table 1), the inverse association with ever coffee drinking was
stronger among CT+TT carriers (OR = 0.73/1.32 = 0.55) com-
pared to CC carriers (OR = 0.77), but the difference was not
statistically significant (OR
interaction
= 0.72, p = 0.18). In analyses
based on quantitative characteristics of coffee drinking, there was
no evidence of statistically significant interactions, except for the
category of 130–200 cupyears of coffee consumption (p = 0.038):
the association with cupyears was stronger among CT+TT
carriers (OR = 0.52/1.33 = 0.39) compared to CC carriers
(OR = 0.70). Analyses based on the Rochester-US dataset and
pooled analyses of all datasets revealed no statistically significant
interactions. Analyses using the same approach to categorize
coffee drinking as Hamza et al. [7] revealed no statistically
significant interactions, except for participants from the Rochester-
US dataset in the second quartile of cupyears; however, this result
was only based on seven cases and 23 controls, this pattern was not
apparent in the other studies, and there was no evidence of
interaction at higher consumption levels (Table S6). In addition,
interaction ORs with heavy coffee drinking tended to be greater
than one, whereas Hamza et al. [7] reported interaction ORs
smaller than one (Table S6). Pooled analyses of the French,
Danish, and Seattle-US data using the empirical Bayes approach
yielded results consistent with those of our main analyses;
compared to the traditional case-control analysis, interaction
ORs were generally closer to one and p-values greater (Table S7).
We found similar results in sensitivity analyses when excluding
TT homozygotes, adjusting for packyears of smoking (2140 cases,
2602 controls) or Mini-Mental State Examination (MMSE) (686
cases, 1,100 controls), or upon stratification by sex, median disease
duration (,5 versus $5 years), and median age (#70 versus .70
years) (data not shown). In addition, in the Seattle-US dataset,
there was no interaction between rs4998386 and total caffeine
intake from seven food and beverage sources.
Case-only analyses of the association between rs4998386 CT-
TT genotypes and coffee consumption showed no evidence of
association regardless of the coffee definition (Table 2). Table 3
shows the same set of analyses in controls. While there was no
statistically significant association between rs4998386 and coffee,
OR estimates tended to be greater than one.
Taken altogether, these findings are not in favor of an
interaction between rs4998386 and coffee drinking for the risk
of PD.
Discussion
In this large data pooling effort across multiple sites in the US
and Europe, we found no evidence of an interaction between
PLOS Genetics | www.plosgenetics.org 2 November 2014 | Volume 10 | Issue 11 | e1004788
Table 1. Independent and joint effects of coffee drinking and GRIN2A-rs4998386 for Parkinson disease.
France, Denmark, Seattle-US Rochester-US Pooled analysis
Interaction Interaction Interaction
rs4998386 Coffee OR (95% CI)
a
p OR (95% CI)
a
p OR (95% CI)
b
p OR (95% CI)
b
p OR (95% CI)
c
p OR (95% CI)
c
p
Ever versus never
CC Never 1.00 (Ref.) - - - 1.00 (Ref.) - - - 1.00 (Ref.) - - -
CC Ever 0.77 (0.62, 0.96) 0.017 - - 1.03 (0.61, 1.73) 0.92 - - 0.79 (0.65, 0.96) 0.016 - -
CT, TT Never 1.32 (0.84, 2.07) 0.23 1.00 (Ref.) - 0.89 (0.31, 2.53) 0.83 1.00 (Ref.) - 1.24 (0.82, 1.87) 0.30 1.00 (Ref.) -
CT, TT Ever 0.73 (0.57, 0.94) 0.014 0.72 (0.45, 1.16) 0.18 0.89 (0.41, 1.92) 0.77 0.97 (0.32, 2.99) 0.96 0.75 (0.60, 0.94) 0.015 0.77 (0.50, 1.19) 0.23
Cups per day
CC Never 1.00 (Ref.) - - - 1.00 (Ref.) - - 1.00 (Ref.) - -
CC 1 cup 0.98 (0.76, 1.26) 0.87 - - 0.97 (0.55, 1.70) 0.91 - - 0.95 (0.75, 1.19) 0.85 - -
CC 2 cups 0.77 (0.61, 0.98) 0.034 - - 1.14 (0.56, 2.32) 0.72 - - 0.79 (0.63, 0.99) 0.094 - -
CC $3 cups 0.64 (0.51, 0.81) ,0.001 - - 1.12 (0.62, 2.04) 0.70 - - 0.67 (0.54, 0.83) 0.38 - -
CT, TT Never 1.33 (0.85, 2.09) 0.22 1.00 (Ref.) - 0.83 (0.29, 2.37) 0.73 1.00 (Ref.) - 1.26 (0.84, 1.91) 0.32 1.00 (Ref.) -
CT, TT 1 cup 0.99 (0.67, 1.47) 0.96 0.76 (0.42, 1.38) 0.37 0.64 (0.26, 1.57) 0.33 0.80 (0.23, 2.77) 0.72 0.85 (0.60, 1.21) 0.66 0.71 (0.42, 1.21) 0.21
CT, TT 2 cups 0.75 (0.53, 1.07) 0.11 0.73 (0.42, 1.28) 0.27 1.35 (0.47, 3.92) 0.58 1.43 (0.34, 6.12) 0.63 0.80 (0.58, 1.12) 0.26 0.81 (0.48, 1.35) 0.41
CT, TT $3 cups 0.59 (0.44, 0.79) ,0.001 0.69 (0.42, 1.14) 0.15 1.14 (0.43, 3.04) 0.79 1.22 (0.34, 4.35) 0.75 0.63 (0.48, 0.82) 0.19 0.74 (0.47, 1.17) 0.20
Global test
d
0.55 Global test
d
0.76 Global test
d
0.58
Cupyears
CC Never 1.00 (Ref.) - - - 1.00 (Ref.) - - 1.00 (Ref.) - -
CC [0–65] 0.88 (0.69, 1.12) 0.30 - - 0.92 (0.51, 1.64) 0.77 - - 0.87 (0.69, 1.09) 0.22 - -
CC [65–130] 0.85 (0.67, 1.09) 0.20 - - 1.19 (0.63, 2.25) 0.60 - - 0.88 (0.70, 1.10) 0.27 - -
CC [130–200] 0.70 (0.55, 0.90) 0.006 - - 1.06 (0.50, 2.22) 0.89 - - 0.72 (0.57, 0.90) 0.005 - -
CC .200 0.61 (0.48, 0.79) ,0.001 - - 1.21 (0.62, 2.37) 0.58 - - 0.64 (0.51, 0.81) 0.0002 - -
CT, TT Never 1.33 (0.85, 2.08) 0.22 1.00 (Ref.) - 0.90 (0.32, 2.58) 0.85 1.00 (Ref.) - 1.26 (0.84, 1.91) 0.26 1.00 (Ref.) -
CT, TT [0–65] 0.98 (0.68, 1.42) 0.93 0.84 (0.48, 1.49) 0.56 0.72 (0.27, 1.90) 0.51 0.87 (0.24, 3.18) 0.83 0.91 (0.65, 1.28) 0.60 0.83 (0.50, 1.40) 0.49
CT, TT [65–130] 0.72 (0.51, 1.03) 0.073 0.64 (0.37, 1.12) 0.12 0.78 (0.29, 2.11) 0.63 0.73 (0.18, 2.91) 0.65 0.72 (0.52, 1.00) 0.048 0.65 (0.39, 1.08) 0.092
CT, TT [130–200] 0.52 (0.36, 0.74) ,0.001 0.55 (0.32, 0.97) 0.038 0.90 (0.30, 2.67) 0.84 0.94 (0.22, 3.98) 0.93 0.56 (0.40, 0.78) 0.0006 0.62 (0.37, 1.03) 0.064
CT, TT .200 0.71 (0.51, 1.00) 0.049 0.88 (0.51, 1.50) 0.63 1.98 (0.62, 6.32) 0.25 1.81 (0.44, 7.47) 0.41 0.78 (0.56, 1.07) 0.12 0.95 (0.58, 1.57) 0.85
Global test
d
0.13 Global test
d
0.75 Global test
d
0.12
Years of coffee
drinking
CC Never 1.00 (Ref.) - - - 1.00 (Ref.) - - 1.00 (Ref.) - -
CC [0–37] 0.84 (0.65, 1.08) 0.17 - - 1.00 (0.52, 1.90) 0.99 - - 0.85 (0.68, 1.08) 0.18 - -
CC [37–45] 0.74 (0.58, 0.95) 0.018 - - 1.27 (0.68, 2.38) 0.45 - - 0.78 (0.62, 0.98) 0.034 - -
CC [45–53] 0.80 (0.63, 1.03) 0.084 - - 0.85 (0.42, 1.73) 0.66 - - 0.79 (0.63, 1.00) 0.051 - -
PLOS Genetics | www.plosgenetics.org 3 November 2014 | Volume 10 | Issue 11 | e1004788
coffee intake and GRIN2A-rs4998386 in PD as previously
reported [7], even though we included a similar number of cases
and controls as the replication phase and more than twice as many
participants as the discovery phase of the original study [7]. We
performed extensive sensitivity analyses, in which we considered
alternative definitions of coffee consumption, applied different
statistical approaches, and performed stratified analyses that
demonstrated the robustness of our lack of replication of the
interaction between coffee intake and GRIN2A-rs4998386 in PD.
There are several possible explanations for our lack of
replication. First, one could argue that the approach of Hamza
et al. [7] is not specifically targeted at identifying gene–
environment interactions: for the genome-wide discovery phase,
they used the 2-df Kraft test, i.e., a test that combines marginal
and interaction effects and was originally presented as a ‘‘tool for
large-scale association scans where the true gene–environment
interaction model is unknown’’ [6]. For their replication, Hamza
et al. [7] specifically focused on the rs4998386-PD association
among heavy coffee drinkers, which was genome-wide significant
in their pooled analyses of discovery and replication data
(OR = 0.51, p = 7610
28
); however, the test for the interaction
between rs4998386 and coffee was not genome-wide significant
(OR = 0.51, p = 3610
25
). Second, the interaction reported by
Hamza et al. [7] resulted in part from a highly significant
association between coffee consumption and rs4998386 among
controls. Interestingly, this is the only situation where the case-only
approach is less efficient than traditional case-control studies to
identify gene–environment interactions [9]. The interpretation of
this pattern of association in the Hamza et al. [7] study is not
straightforward: while controls who carried the rs4998386-T allele
were heavier coffee drinkers than noncarriers, there was a
nonsignificant association between rs4998386-T and coffee in
the opposite direction among PD patients, therefore suggesting
that GRIN2A may play a role in coffee drinking behaviour with
opposite effects in healthy subjects and PD cases. In contrast, we
found no association between coffee drinking and rs4998386
among population controls included in the present study. This is
supported by a meta-analysis of GWAS on coffee intake from eight
Caucasian cohorts (n = 18,176) that found no association between
the number of cups of coffee per day and GRIN2A-rs4998386 in
healthy subjects (beta regression coefficient per one T al-
lele = 0.0105, SE = 0.0165, p = 0.52; I
2
= 18%, p
heterogeneity
= 0.41;
personal communication [10]). Third, PD patients included in the
Hamza et al. [7] study were younger than those included in the
present analysis. However, we found no evidence of interaction in
analyses restricted to younger PD patients and controls. Fourth,
Hamza et al. [7] used dataset-specific cutoffs to define coffee
variables; this approach combines participants from separate
datasets with different exposure levels in the same category and the
resulting ORs do not have a simple interpretation. Our results
were sensitive to the way coffee consumption data were
categorized, as interaction estimates from analyses based on our
main definition and those based on Hamza et al. [7] were not
comparable; it is therefore possible that findings from Hamza et al.
[7] may be sensitive to the way coffee data were categorized for
their analyses.
According to our power calculations, our study was well
powered to identify an interaction of the size estimated by Hamza
et al. [7] or even weaker. The case-only approach, a method with
increased statistical power to detect gene–environment interac-
tions compared to traditional case-control analyses, relies on the
assumption of gene–environment independence among controls
[11]. In our study, rs4998386 was not associated with coffee
consumption among controls and the case-only approach also did
Table 1. Cont.
France, Denmark, Seattle-US Rochester-US Pooled analysis
Interaction Interaction Interaction
rs4998386 Coffee OR (95% CI)
a
p OR (95% CI)
a
p OR (95% CI)
b
p OR (95% CI)
b
p OR (95% CI)
c
p OR (95% CI)
c
p
CC .53 0.71 (0.55, 0.92) 0.011 - - 0.99 (0.46, 2.15) 0.98 - - 0.73 (0.57, 0.92) 0.0089 - -
CT, TT Never 1.32 (0.84, 2.06) 0.23 1.00 (Ref.) - 0.94 (0.33, 2.69) 0.90 1.00 (Ref.) - 1.24 (0.82, 1.87) 0.30 1.00 (Ref.) -
CT, TT [0–37] 0.76 (0.53, 1.08) 0.12 0.69 (0.40, 1.18) 0.18 1.13 (0.35, 3.62) 0.83 1.21 (0.29, 5.00) 0.79 0.80 (0.58, 1.11) 0.19 0.76 (0.46, 1.25) 0.27
CT, TT [37–45] 0.75 (0.53, 1.05) 0.093 0.77 (0.45, 1.32) 0.34 0.60 (0.21, 1.71) 0.34 0.50 (0.13, 2.01) 0.33 0.73 (0.53, 1.00) 0.052 0.75 (0.46, 1.25) 0.27
CT, TT [45–53] 0.66 (0.46, 0.95) 0.025 0.62 (0.36, 1.09) 0.10 0.53 (0.15, 1.90) 0.33 0.67 (0.14, 3.26) 0.62 0.65 (0.46, 0.92) 0.014 0.65 (0.39, 1.11) 0.11
CT, TT .53 0.79 (0.55, 1.14) 0.21 0.84 (0.48, 1.48) 0.54 1.38 (0.48, 3.99) 0.55 1.48 (0.38, 5.76) 0.57 0.84 (0.59, 1.18) 0.31 0.93 (0.55, 1.56) 0.78
Global test
d
0.48 Global test
d
0.42 Global test
d
0.44
a
Odds ratios (OR) and 95% confidence intervals (CI) computed using unconditional logistic regression and adjusted for sex, age in quartiles, ever cigarette smoking, and dataset (1974 cases, 2494 controls).
b
Odds ratios (OR) and 95% confidence intervals (CI) computed using conditional logistic regression and adjusted for sex, age in quartiles, and ever cigarette smoking (315 cases, 315 controls).
c
Odds ratios (OR) and 95% confidence intervals (CI) computed by pooling individual data from the matched and unmatched case-control analyses and adjusted for sex, age in quartiles, ever cigarette smoking, and dataset (2289
cases, 2809 controls).
d
Global test of interaction: p-values were computed using a likelihood ratio test that compared the likelihood of models with and without interaction terms.
doi:10.1371/journal.pgen.1004788.t001
PLOS Genetics | www.plosgenetics.org 4 November 2014 | Volume 10 | Issue 11 | e1004788
