A genome-wide association study identiﬁes
a region at chromosome 12 as a potential
susceptibility locus for restenosis after
percutaneous coronary intervention
M. Lourdes Sampietro1,15, Stella Trompet2,3, Jeffrey J.W. Verschuren2, Rudolf P. Talens4,
, Bastiaan T. Heijmans4,
, Robbert J. de Winter5, Rene A. Tio6,
Pieter A.F.M. Doevendans8, Santhi K. Ganesh9, Elizabeth G. Nabel10, Harm-Jan Westra7,
Lude Franke7,11, Erik B. van den Akker4,12, Rudi G.J. Westendorp3,
, Aeilko H. Zwinderman13,
Adnan Kastrati14, Werner Koch14, P.Eline Slagboom4,
, Peter de Knijff1,
and J. Wouter Jukema2,15,16, ∗,
Department of Human Genetics,
Department of Cardiology,
Department of Gerontology and Geriatrics and
Department of Molecular Epidemiology, Leiden University Medical Center, Leiden 2300RC, The Netherlands,
Department of Cardiology, Academic Medical Center-University of Amsterdam, Amsterdam 1105AZ, The
Department of Cardiology and
Department of Genetics, University Medical Center Groningen,
University of Groningen, Groningen 9700RB, The Netherlands,
Department of Cardiology, University Medical Center
Utrecht, Utrecht 3508GA, The Netherlands,
Division of Cardiovascular Medicine, Department of Internal Medicine,
University of Michigan, Ann Arbor, MI 48109, USA,
Brigham and Women’s Hospital, Harvard Medical School,
Boston, MA, USA,
Blizard Institute of Cell and Molecular Science, Barts and The London School of Medicine
and Dentistry, Queen Mary University of London, London E1 2AT, UK,
The Delft Bioinformatics Lab, Delft
University of Technology, Delft 2628 CD, The Netherlands,
Department of Medical Statistics, Academic Medical
Center-University of Amsterdam, Amsterdam 1105AZ, The Netherlands,
Deutsches Herzzentrum Mu
1. Medizinische Klinik, Klinikum rechts der Isar, Technische Universita
¨nchen, Munich D80636, Germany,
Interuniversity Cardiology Institute of the Netherlands (ICIN), Utrecht, The Netherlands and
Durrer Center for
Cardiogenetic Research, Amsterdam, The Netherlands
Received June 15, 2011; Revised and Accepted August 25, 2011
Percutaneous coronary intervention (PCI) has become an effective therapy to treat obstructive
coronary artery diseases (CAD). However, one of the major drawbacks of PCI is the occurrence of restenosis
in 5–25% of all initially treated patients. Restenosis is deﬁned as the re-narrowing of the lumen of the blood
vessel, resulting in renewed symptoms and the need for repeated intervention. To identify genetic variants
that are associated with restenosis, a genome-wide association study (GWAS) was conducted in 295 patients
who developed restenosis (cases) and 571 who did not (controls) from the GENetic Determinants of
Restenosis (GENDER) study. Analysis of ∼550 000 single nucleotide polymorphisms (SNPs) in GENDER
was followed by a replication phase in three independent case– control populations (533 cases and 3067
controls). A potential susceptibility locus for restenosis at chromosome 12, including rs10861032
) and rs9804922 (P
), was identiﬁed in the GWAS and replication
phase. In addition, both SNPs were also associated with coronary events (rs10861032, P
Members of the Netherlands Consortium for Healthy Ageing.
To whom correspondence should be addressed at: Department of Cardiology C5-P, Leiden University Medical Center, PO Box 9600, 2300 RC Leiden,
The Netherlands. Tel: +31 715266695; Fax: +31 715266885; Email: email@example.com
#The Author 2011. Published by Oxford University Press. All rights reserved.
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Human Molecular Genetics, 2011, Vol. 20, No. 23 4748–4757
Advance Access published on August 30, 2011
50.023) in a trial based cohort set of elderly patients with (enhanced risk of) CAD
(PROSPER) and all-cause mortality in PROSPER (rs10861032, P
50.007; rs9804922, P
and GENDER (rs10861032, P
50.005; rs9804922, P
50.023). Further analysis suggests that this
locus could be involved in regulatory functions.
Percutaneous coronary intervention (PCI) for unblocking a
narrowed coronary artery is a widely used technique for treat-
ing patients with angina or an acute coronary event. Initially,
PCI was performed only with balloon catheters, but technical
advances made it possible to improve patient outcome by the
placement of bare metal stents (BMS), or later, drug eluting
stents (DES) at the site of blockage (1–3). Patients undergoing
PCI may suffer from a re-narrowing of the treated lesion,
which is called restenosis, with renewed symptoms and the
need for repeated intervention, typically within 3 to 6
months (4). Restenosis occurs in 5 – 25% of all treated
patients depending on individual characteristics and the tech-
niques used (1–3,5,6), thereby still causing a signiﬁcant clin-
ical and economic burden for patients and society.
So far, the etiological basis of restenosis is only partly
understood. The injury induced by PCI within the vascular
wall causes segmental thrombus formation and subsequent
invasion of macrophages and polymorphonuclear leukocytes
in the blood vessel. This process is followed by release of nu-
merous growth factors from blood cells and stretched smooth
muscle cells that lead to the proliferation of smooth muscle
cells in the treated lesion (4,7,8).
In order to prevent restenosis, numerous systemic drugs
have been studied for their inhibitory effect on smooth
muscle cell proliferation but the results have been inconclu-
sive (9). A new solution has been the development of DES
(10,11). DES are made by applying a drug (such as sirolimus
or paclitaxel) on a coronary stent. The drug is released directly
into the (by PCI) injured area and is thereby preventing the in-
ﬂammatory response and smooth muscle cell proliferation at
the site of the coronary intervention. Although DES have
decreased the incidence of restenosis, restenosis still occurs
in all instances (12,13). Moreover, although several clinical
factors, lesion-related, procedural and biological markers
have been shown to be associated with an elevated risk of
restenosis (4,14–16), these associations have not been consist-
ently replicated in all studies.
There is evidence that systemic factors can explain part of
the risk of restenosis independently of conventional clinical
factors or procedures. For instance, in patients with multile-
sion interventions, the risk that a lesion develops restenosis
is 2.5 times higher when a companion lesion developed resten-
osis, independently of clinical factors (17). The inﬂuence of
genetic polymorphisms in the development of restenosis has
been investigated by means of candidate gene approaches
(18–21), with interesting, although sometimes controversial
or inconsistent results. For instance, an insertion/deletion poly-
morphism in the angiotensin-converting enzyme was asso-
ciated with restenosis within a French population (22), but
not in a German or a Dutch population (23,24).
We conducted the ﬁrst genome-wide association study
(GWAS) to identify new genetic risk factors for restenosis
in a subpopulation of the GENetic DEterminants of Restenosis
(GENDER) study. This was followed by a replication phase in
three independent restenosis case – control populations (repli-
cation I, replication II and replication III). In a secondary
step, we tested if the most associated single nucleotide poly-
morphisms (SNPs) were also associated with other relevant
clinical outcomes such as cardiovascular events and all-cause
mortality in GENDER and in the PROspective Study of Pra-
vastatin in the Elderly at Risk (PROSPER) population. This
additional validation effort may add worthwhile information
with regard to the genetic factors involved in the pathophysi-
ology of restenosis.
The overall GWAS results are summarized in a Manhattan
plot (Fig. 1). We found that 91 SNPs were associated with
restenosis at P-value ,10
assuming the additive model
(Supplementary Material, Table S1). In the replication stage,
these 91 SNPs were genotyped in three restenosis populations,
two BMS cohort (replication I and replication II) and a DES
cohort (replication III) (Table 1). Associations found in the
discovery set were replicated for an intergenic region on
chromosome 12 (Table 2). This was specially found for
replication I (Table 2). In replication I, rs10861032 showed
an association with restenosis [P¼3.99 ×10
; odds ratio
(OR) ¼3.06, 95% conﬁdence interval (CI) (1.64– 5.70)];
nominally signiﬁcant at P-value ,0.05 even after Bonferroni
correction (0.05/91 SNPs ¼5.49 ×10
). Using the Fisher’s
trend combined P-value method, we observed that
rs10861032 C allele was potentially associated with higher
risk of restenosis (P
) in all four popula-
tions combined. We computed I
as a measurement of hetero-
geneity and we obtained a value of 77.04% for rs10861032
which can be interpreted as the percentage of total variation
across studies due to heterogeneity (25). A similar association
for all four combined populations was observed for rs9804922
) for the risk allele (T).
In addition, both SNPs were also associated with all-cause
mortality in GENDER (rs10861032, P
¼0.031) and in the PROSPER study
¼0.007; rs9804922, P
(Tables 3and 4), and also with coronary events (rs10861032,
¼0.005; rs9804922, P
¼0.023) in PROSPER.
Both rs10861032 and rs9804922 are located on an intergenic
region. An open reading frame (C12orf42), a hypothetical
protein of unknown function, is located 22.7 kb upstream of
both SNPs, the gene STAB2 (Stabiline2) is located 68.5 kb
downstream and the gene NT5DC3 253.5 kb downstream
Human Molecular Genetics, 2011, Vol. 20, No. 23 4749
(Fig. 2). Non-genotyped SNPs in the 610-quad array were
imputed from HapMap CEU reference panel (release 22)
within a 500 kb window centered on rs10861032. Analysis on
566 imputed and 140 genotyped SNPs within this region
revealed three more imputed SNPs that were associated with re-
stenosis, rs4147305 [P¼1.72 ×10
,OR¼2.1 95% CI
(3.14– 1.41)], rs17034045 [P¼1.72 ×10
OR ¼2.1 95%
CI (3.14– 1.41)] and rs10861033 (P¼8.91 ×10
1.55 95% CI [2.02– 1.20)]. These SNPs are in LD with
¼0.37 and r
Inspection of the UCSC genome browser (http://genome.
ucsc.edu) database revealed that rs10861032 maps 110 bp
downstream and rs9804922 457 bp upstream to a DNase I
hypersensitivity site (chr12:102436746 – 102437115). In add-
ition, the promoter 2.0 Prediction Server predicts with high
scores that the surrounding region of the restenosis associated
SNP could be a promoter region. Moreover, the is-rSNP algo-
rithm (26) for in silico detection of genetic variation which
affect the ability of a transcription factor (TF) to bind to DNA
predicts that both SNPs alter the binding afﬁnity of TFs to the
DNA (Supplementary Material, Table S2). Alleles of
rs10861032 alter the binding afﬁnity of Htlf (Helicase-like
TF) (P¼4.4 ×10
) and Pax4 (P¼5.7 ×10
of Htlf family have helicase and ATPase activities and are
Figure 1. Manhattan plot of the GWAS performed in the GENDER study. P-values were obtained by the Cochrane –Armitage trend test for 556 099 SNPs and
866 individuals (295 cases and 571 controls) are plotted in – log
scale according to their chromosomal position. A horizontal black line indicates an additive
P-value of 10
Figure 2. Description of the loci on chromosome 12 associated with restenosis in the GWAS. On the y-axis, the –log
(P-value) is depicted. The most sig-
niﬁcant SNP in the meta-analysis (rs10861032) is plotted in purple. LD is based on the HapMap CEU sample and is color-code as red (r
from 0.8 to 1.0),
orange (0.6– 0.4), green (0.6 – 0.4), white blue (0.4 to 0.2) and dark blue (0.2 to 0). Recombination rate is depicted in light blue. Asterisks display TF site.
The plot was generated using LocusZoom (53).
4750 Human Molecular Genetics, 2011, Vol. 20, No. 23
thought to regulate transcription of certain genes by altering the
chromatin structure around those genes (27). Pax4 is a member
of the paired box (PAX) family of TFs. These genes play critical
roles in cancer growth (28).
Alleles of rs9804922 alter the binding afﬁnity of TP53
) and HoxA (3.3 ×10
). TP53 is a tumor sup-
pressor protein that regulates the cell cycle known to be
very important in the process of restenosis (sirolimus and
paclitaxel work by inhibiting the cell cycle) (29,30). HoxA
belongs to the cluster A of the called homeobox genes
which may regulate gene expression, morphogenesis and
We have also checked if both SNPs are expression quanti-
tative loci (eQTLs) and regulate the expression level of
genes at the locus (cis-regulation). This experiment was per-
formed using cis expression-genotype data derived from
1469 human whole blood samples reﬂecting primary leuko-
cyte gene expression (32). However, in a window of 1 Mb sur-
rounding rs10861032 and rs9804922, no signiﬁcant eQTL
effect was detected.
To our knowledge, this is the ﬁrst GWAS that investigates the
association between genetic markers and restenosis. Resten-
osis is a complex phenotype in which the individual contribu-
tion of genes to the development of the disease might probably
be relatively small and therefore difﬁcult to detect (16). Using
the GENDER population as a discovery set, we found several
genomic regions that were associated with restenosis.
However, this study presents some potential caveats. First,
we combined patients that underwent PCI either by balloon
angioplasty alone, BMS or DES as restenosis was and still is
the major drawback of PCI in all these three cohort popula-
tions. The fact that we found similar results in the different
cohorts independently of whether they used BMS or DES indi-
cates that it is unlikely that the involvement of chromosome
12q23.3 region in the pathophysiology of restenosis is based
only on the inhibitory effect on smooth muscle cell prolifer-
ation of the drugs coating the DES surface, which is only
expected in subjects with DES. Secondly, it is also important
to point out that in this study we have combined cohorts with
two clinical endpoints [clinical restenosis (discovery set and
replication I) and target lesion revascularization (TLR, replica-
tion II and replication III)]. Although both endpoints are
highly comparable, it should be noted that clinical restenosis,
although nowadays considered the most clinically relevant
endpoint, is somewhat a broader endpoint for restenosis than
TLR. The fact that the replication is mainly in replication
I could indicate that the top SNPs are mainly associated
with clinical restenosis and not with TLR. Finally, it must
be noticed that none of the detected SNPs shows traditional
GWAS threshold signiﬁcance. Nevertheless, the fact that
similar association trends were observed in some of these
regions when using other data sets suggests that these
regions could be indeed potentially involved in the restenosis
phenotype. From these SNPs, a region on chromosome
12q23.3 comprising rs10861032 and rs9804922 was replicated
in three other restenosis populations, two BMS cohorts and
Table 1. Baseline clinical characteristics of GENDER (discovery population), replication I, replication II and replication III
Age (years) 62 +11 64.5 +11.35 64 +11 66 +11
Sex (male) 636 (73.44%) 0.50 182 (68.68%) 0.001 1110 (76.81%) 0.78 1478 (79.04%) 0.67
584 (67.43%) 0.95 265 (100%) 1 1445 (100%) 1 1890 (100%) 1
Diabetes 117 (20.43%) 0.75 97 (36.60%) ,0.001 301 (20.83%) 0.97 508 (26.88%) 0.58
216 (24.94%) 0.40 147 (55.47%) 0.05 453 (31.34%) 0.41 276 (14.60%) 0.98
Hypercholesterolemia 520 (60.04%) 0.84 198 (74.72%) 0.93 624 (43.18%) 0.21 1341(70.95%) 0.51
Total occlusion 154 (17.78%) 0.45 14 (5.28%) 0.31 232 (16.05%) 0.18 144 (7.62%) 0.045
Residual stenosis (.20%) 112 (12.93%) 0.07 11 (4.15%) 0.53 54 (3.37%) 0.92 48 (2.54%) 0.08
n, number of individuals in each cohort.
Endpoint: clinical restenosis.
P-values computed between cases and controls for each variable.
Endpoint: TLR within 1 year after PCI.
GENDER: replication I and replication II are BMS cohorts. Replication III is a DES cohort.
In replication I, the data represented in this table are ever smoke and not current smoker.
Human Molecular Genetics, 2011, Vol. 20, No. 23 4751
a DES cohort (P
, respectively, when considering all four popula-
tions). Interestingly, both SNPs (rs10861032 and rs9804922)
are also associated with all-cause mortality in GENDER and
in PROSPER and also with coronary events in PROSPER
(no data available for this endpoint in GENDER), which
shows that probably this region on chromosome 12 may
play a more general role in the development of coronary
artery diseases. These ﬁndings require further research to dis-
entangle whether the SNPs associated not only with restenosis
but also with cardiovascular events and all-cause mortality are
for instance the result of a pleiotropic effect of single alleles
affecting multiple phenotypes.
The associated locus on 12q23.3 is an intergenic region
ﬂanked upstream by C12orf42 and downstream by the gene
STAB2 located 68.5 kb and the gene NT5DC3 located
253.5 kb away from rs10861032 (Fig. 2). The STAB2 gene
encodes for a transmembrane receptor protein which may
function in angiogenesis, lymphocyte homing, cell adhesion
and receptor scavenging (33–35). All these processes are
described to be of importance in the development of restenosis
and coronary events (16), thereby making it a very plausible
candidate. NT5DC3 encodes for a protein involved in the pro-
gression of pancreatic cancer (36), therefore it is a gene
involved in cell proliferation, an important biological
process for the development of restenosis.
The top associated SNP in this study, rs10861032, is in low
linkage disequilibrium (LD) (r
,0.2) with SNPs in STAB2,
NT5DC3 and C12orf42 (Fig. 2). Moreover, rs10861032
ﬂanks upstream to a DNaseI hypersensitivity site
(chr12:102436746– 102437115), a universal feature of active
cis-regulatory sequences, including promoters, insulators,
enhancers, boundary elements and locus control regions
(37,38). Furthermore, the region ﬂanked by rs10861032 and
rs9804922 is likely to be a promoter region as predicted by
the promoter 2.0 Prediction Server (39). In addition, the
is-rSNP algorithm (26) predicts that alleles of both SNPs
alter the binding afﬁnity of several TFs to the DNA, making
them likely to be regulatory SNPs. Furthermore, it has recently
been shown that ‘gene desert’ regions found by GWAS can be
involved in cis-regulatory functions (40 –42). This could also
be the case of rs10861032 and rs9804922 in the regulation
of the expression of STAB2 or NT5DC3, indicating that the
region, associated with restenosis on chromosome 12, might
be involved in the regulation of the expression of these two
genes. However, all these bioinformatic predictions would
require wet lab conﬁrmation; in fact, analysis of gene expres-
sion and genetic variation on a 1 Mb region surrounding both
rs10861032 and rs9804922 in 1469 whole blood samples (32)
did not ﬁnd any signiﬁcant eQTL effect. Nevertheless, this
result does not preclude cis-regulating effect in the case of
restenosis, as this analysis was performed in whole blood
and not yet in a restenosis population and eQTL effects are
often cell-type speciﬁc (43). It might be possible that the asso-
ciated SNPs affect gene expression in a more speciﬁc tissue
such as coronary or even carotid tissue. These tissues should
be further investigated in order to disentangle the possible
Table 2. Association results for rs10861032 and rs9804922 in GENDER (discovery set), replication I, replication II and replication III
Population N(case/control) Chr SNP Position Alleles
MAF (case/control) P
OR (CI 95%)
GWAS 295/571 12 rs10861032 102436636 C/T 0.212/0.133 3.29E205 1.75 (1.35 – 2.27)
Replication I 78/187 0.192/0.099 3.98E204 3.06 (1.64 – 5.70)
Replication II 275/1170 0.159/0.147 4.94E201 1.09 (0.85 – 1.41)
Replication III 180/1710 0.219/0.177 4.89E202 1.31 (1.00 – 1.7)
GWAS 295/571 12 rs9804922 102437572 T/C 0.114/0.049 1.03E206 2.48 (1.72– 3.60)
Replication I 78/187 0.077/0.043 0.063 2.26 (0.97– 2.14)
Replication II 275/1170 0.077/0.074 8.83E201 1.03 (0.72 – 1.46)
Replication III 180/1710 0.119/0.092 1.03E201 1.33 (0.95 – 1.87)
Combined P-values are computed by means of Fisher’s trend method. Positions are based on hg18 build.
The ﬁrst allele is the minor allele. MAF, minor allele frequency.
Results of the Cochran – Armitage test.
OR of the minor allele from the two by two allele frequency table.
Table 3. Association results with coronary events and all-cause mortality for
rs10861032 and rs9804922 in PROSPER
HR (95% CI)
rs10861032 (MAF ¼0.14)
Coronary events 0.005 1.25 (107–1.46)
All-cause mortality 0.007 1.25 (1.06– 1.47)
rs9804922 (MAF ¼0.06)
Coronary events 0.023 1.30 (1.04–1.62)
All-cause mortality 0.013 1.33 (1.06– 1.67)
Adjusted for sex, age, country and pravastatin used.
MAF, minor allele frequency; HR, hazard ratio.
Table 4. Association results for all-cause mortality for rs10861032 and
rs9804922 in GENDER
HR (95% CI)
rs10861032 (MAF ¼0.16)
All-cause mortality 0.005 1.39 (1.10 – 1.74)
rs9804922 (MAF ¼0.07)
All-cause mortality 0.031 1.42 (1.03 – 1.94)
Adjusted for sex and age.
MAF, minor allele frequency; HR, hazard ratio.
4752 Human Molecular Genetics, 2011, Vol. 20, No. 23
regulatory functions of rs10861032 and rs9804922 in the de-
velopment of restenosis.
In conclusion, we have performed the ﬁrst GWAS to look
for genetic variants associated with the development of resten-
osis after PCI in the GENDER study followed by three inde-
pendent replication steps and we have identiﬁed association
for rs10861032 at the 12q23.3 region. The SNPs,
rs10861032 and rs9804922, are also associated with all-cause
mortality in GENDER and in PROSPER and also with coron-
ary events in PROSPER which indicates that this region might
play an important role in the broader range of coronary events.
Further research will be needed to disentangle the biological
implication of this region in restenosis.
MATERIALS AND METHODS
We investigated the association between genetic variation and
clinical restenosis in patients from four different cohort
studies, a Dutch population (GENDER), an American popula-
tion (replication I) and two populations from Germany, a BMS
population (replication II) and a DES population (replication
III). The GWAS was performed in the GENDER study (dis-
covery set), whereas the replication was performed in replica-
tion I, replication II and replication III. In addition, the
PROSPER and the GENDER studies were used to check
whether the top associated SNPs found in the discovery set
and validated in the replication cohorts are involved in other
relevant clinical outcomes such as all-cause mortality and car-
All studies were approved by the medical ethical commit-
tees of the participating hospitals, had independent clinical
event committees who adjudicated the endpoints in a
blinded way. Blood samples were collected at the index pro-
cedure for DNA isolation after having obtained written
informed consent from the patient and the trials were con-
ducted in concordance with the Declaration of Helsinki.
Genome-wide association study
The main characteristics of the GENDER population have
been described previously (1). Brieﬂy, 3104 consecutive
symptomatic patients treated successfully by PCI for angina
were included in four referral centers for interventional cardi-
ology in the Netherlands. The follow-up protocol included a
phone contact or a medical visit at the outpatient clinic at 30
days and around 9 months after stent placement. Clinical
restenosis was deﬁned as renewed symptoms requiring target
vessel revascularization either by repeated PCI or coronary
artery bypass graft surgery, by death from cardiac causes or
myocardial infarction not attributable to another coronary
event than the target vessel (1). Within the 9-month follow-up
period, 346 patients developed clinical restenosis. Clinical
restenosis was not angiographically conﬁrmed.
The GWAS was performed in 325 cases of restenosis (all
cases with enough quality DNA to perform the experiment)
and 630 matched controls. Cases and controls were matched
by gender, age and some possible confounding clinical vari-
ables for restenosis in the GENDER study, such as total occlu-
sion, diabetes, current smoking and residual stenosis (Table 1).
All-cause mortality long-term follow-up data were collected
in March 2011 and are deﬁned as death from any cause and the
information was collected from death certiﬁcates. Mean time
follow-up was 9.5 years (SD ¼3 years) and 239 (27.9%)
patients died during the study. From the patients analysed in
the GWAS, only nine subjects (1.0%) were not possible to
Genotyping and quality control. In the discovery stage, we
conducted the genotyping using Illumina Human 610-Quad
Beadchips and the inﬁniumII assay following manufacturer’s
instructions. These beadchips contain 620 901 SNPs and
copy number variants covering 89% of the common genetic
variation in the European population at r
955 samples (325 cases and 630 controls) from the
GENDER study were genotyped. After excluding bad-
performing samples (call rate ,0.98 and manually checked
sample quality by means of B-allele frequency and LogR
ratio), genotype cluster deﬁnitions for each SNP were deter-
mined using the ‘Cluster all SNPs’ option in Illumina Bead-
Studio Genotype module version 3.2. Genotype calls were
made when a genotype yielded a quality metric (Gencall
score) of 0.15 or higher. The ﬁnal raw data set released
from Beadstudio (eliminating intensity probes only) contained
reliable called genotypes for 592 186 SNPs and 941 samples
(321 cases and 620 controls), with 14 samples not released
due to inadequate quality of genotypes. The remaining
samples have a call rate ≥0.99. Additional quality-control
measurements were then performed using PLINK (44).
Seven samples (four cases and three controls) were excluded
due to sex discrepancies between the recorded sex and the
inferred sex by the X-chromosome genotypes. We checked
for the presence of population substructure in the GENDER
study by means of multidimensional scaling (MDS). An iden-
tical by state distance matrix was calculated for each pair of
individuals along with the 940 individuals from the human
genome diversity project-centre d’Etude du polymorphisme
humain (HGDP-CEPH) panel (45). We observed that the
vast majority of the individuals fell in the same cluster
along with the European population, but 67 individuals were
outside this cluster and were considered genetic outliers (see
Supplementary Material, Fig. S1). One sample was eliminated
because it showed a close genetic relationship with another
sample from the GENDER study. Furthermore, we excluded
SNPs for further analyses with a call rate lower than 95%
(n¼1731), with a minor allele frequency lower than 1%
(n¼34250) or with a signiﬁcant deviation from Hardy –
Weinberg equilibrium (HWE) in controls (P,0.00001).
The ﬁnal data set consisted of 866 (295 cases, 571 controls)
individuals and 556 099 SNPs that passed all quality-control
We applied the genomic-control method on the GWAS data
and found that there was only a slight inﬂation of the genomic-
control parameter (l¼1.01581), which implies a high genetic
homogeneity between the cases (n¼295) and the controls
(n¼571). Given that the inﬂation factor was found to be
minimal, all the statistics results are reported without
genomic-control correction. At the tail end of the quantile–
quantile plot (Q – Q plot), the P-values from the Cochrane –
Armitage trend test deviate from the null distribution expected
Human Molecular Genetics, 2011, Vol. 20, No. 23 4753
under the hypothesis of no association (Supplementary Mater-
ial, Fig. S2), which indicates that several modest associations
Replication I. The CardioGene Study was an IRB-approved,
prospective cohort study of 358 patients enrolled at the time
of BMS implantation to treat de novo, previously untreated
native coronary artery lesions at William Beaumont Hospital
(Royal Oak, Michigan, USA) and the Mayo Clinic (Rochester,
Minnesota, USA). Patients were followed for 1 year to deter-
mine in-stent restenosis (ISR) outcomes. Enrolment began in
February 2002 and was closed in September 2003, prior to
the approval and clinical use of DES in the USA. Additionally,
104 individuals were enrolled with historical in-stent resten-
osis in bare metallic stents, with two or more episodes of re-
stenosis in native coronary arteries. The protocol was
approved by the NHLBI IRB as well as the IRB at each of
the clinical enrolment sites. Informed consent was provided
by each patient. Standardized case report forms were used to
collect baseline clinical data and outcome information in
For the clinical phenotype, consecutive patients presenting
to the cardiac catheterization laboratories of the clinical enrol-
ment sites were approached for participation in the study.
Follow-up clinical evaluation was performed via patient inter-
view and review of all available medical records at 6 months
and 12 months post-stent. ISR was deﬁned as clinical resten-
osis (46), which was deﬁned by ischemic symptoms after
stent implantation and evidence of ﬂow limitation in the
treated vessel by either invasive or non-invasive testing.
Follow-up angiography was not speciﬁcally performed for
the CardioGene Study. Any available angiographic data per-
formed as part of each patient’s clinical care was recorded.
Genotyping and quality control. Genotypes were assayed
using the Affymetrix Genome-Wide Human SNP Array 6.0
platform, and genotypes were called using the Birdseed algo-
rithm. For this analysis, the ﬁnal sample with genotype data
consisted of 265 samples, with 78 in-stent restenosis cases
and 187 stented no-restenosis controls, from European ances-
try participants among which call rates and deviations from
HWE for all SNPs were calculated. Genotype call rates were
95% or greater for all samples. Of these, 35 samples were
removed in data cleaning steps for sex mismatch, ﬁrst
degree relative of an included individual and genetic outlier
based upon allele sharing and principal components analysis.
Genetic analyses were conducted using an additive model,
using logistic regression to evaluate the association between
the allele dosage and the trait of interest. We adjusted the ana-
lysis for age and gender. Genomic control was not applied.
Data management and statistical analysis used R, ProbABEL
(47) and PLINK software (44).
Replication II and replication III
Patients of replication II and replication III cohorts presented
ischemic symptoms or evidence of myocardial ischemia in
the presence of ≥50% de novo stenosis located in native
coronary vessels. They were treated with PCI and stent im-
plantation at Deutsches Herzzentrum Mu
¨nchen or 1. Medizi-
nische Klinik rechts der Isar der Technischen Universita¨t
¨nchen. The main characteristics of the cohorts and the
protocols of stent placement and post-stenting therapy have
been described previously (23,48). Brieﬂy, replication II
included 1445 patients treated with implantation of BMS
and replication III consisted of 1890 patients treated with
implantation of DES. TLR within 1 year after PCI was con-
sidered the primary endpoint for both cohorts.
Re-hospitalization for repeat angiography was scheduled
between 6 and 8 months or earlier if non-invasive evaluation
or clinical presentation suggested the presence of ischemia.
The secondary endpoint was deﬁned as a diameter stenosis
50% at follow-up angiography at 6 months.
Genotyping and quality control. Initially, 3657 samples were
genotyped by means of iPLEX assays. All SNPs showing a
in the Cochran– Armitage trend test (additive
model) in the discovery set (n¼91) were selected for replica-
tion. Four assays were designed using MassArray design soft-
ware (Sequenom, San Diego, CA, USA). Genotyping was
performed using iPLEX assays with the use of the MassAR-
RAY methodology (Sequenom), with alleles discriminated
by mass spectrometry, following manufacturer’s instructions.
Four SNP pairs were in complete LD (r
¼1) and thus we
ascertained one tagSNP from each pair and the other was
Two SNPs did not ﬁt the assay and four more SNPs failed in
the experiment. Samples with a call rate ,75% per iPLEX or
with a call rate ,90% when considering all iPLEXes were
removed for further analysis. SNPs with call rate ,90% or
out of HWE (P-value,0.001 in controls) were also
removed. Duplicate samples (2.5%) showed identical geno-
types. Blanks and positive controls were added in each experi-
ment. Finally, 79 SNPs and 3335 samples (2880 controls and
455 cases) passed all quality criteria and were further
In order to know if the most associated SNPs in the discov-
ery set contain information to detect the presence of popula-
tion substructure, we performed a MDS extracting the
genotypes of these SNPs from the HGDP-CEPH panel (45),
which contains samples belonging to 52 populations all over
the world. The MDS did not show any cluster (data not
shown) in the HGDP-CEPH panel, not even between popula-
tions from different continents, thus indicating that population
substructure cannot be considered a confounding factor in the
replication cohorts when considering these SNPs.
The protocol of PROSPER (PROspective Study of Pravasta-
tin in the Elderly at Risk) has been described elsewhere (49).
PROSPER is a prospective multicenter randomized placebo-
controlled trial to assess whether treatment with pravastatin
diminishes the risk of major vascular events in elderly indi-
viduals. Between December 1997 and May 1999, subjects
were screened and enrolled in Scotland (Glasgow), Ireland
(Cork) and the Netherlands (Leiden). Men and women
aged 70– 82 years were recruited if they had pre-existing
4754 Human Molecular Genetics, 2011, Vol. 20, No. 23
vascular disease or increased risk of such disease because of
smoking, hypertension or diabetes. A total number of 5804
subjects were randomly assigned to pravastatin or placebo.
In this study, the predeﬁned endpoints, coronary events, vas-
cular events, vascular mortality and all-cause mortality were
evaluated. In particular, coronary events are a combination
of fatal and non-fatal myocardial infarction. Information on
all-cause mortality was received by post-mortem reports,
death certiﬁcates, hospital records, general practitioners’
records and/or interviews of family members or witnesses.
All endpoints were adjudicated by the study endpoint com-
Mean follow-up was 3.2 years (range 2.8 – 4.0) and 604
(10.4%) patients died during the study (50). The SNPs were
selected from the GWAS performed in 5244 subjects of the
PROSPER study from whom genotype data were available.
Statistical analysis was undertaken using R (v2.8), PLINK
v1.06 (44), GenABEL and ProABEL softwares implemented
in the R package (47,51). Haploview software (52) was used
to infer the LD in the targeted regions. LocusZoom (53) was
used to draw regional plots for associated regions.
Each SNP was tested for association using a Cochran –
Armitage test (additive model). Inﬂation in the test statistics
was assessed using the genomic-control method and a Q – Q
plot was computed (54). The genotype counts of the discovery
and replication stages were combined by means of the Fisher’s
trend combined P-value approach. All P-values are two-sided.
Imputation of genotypes around the top associated SNPs were
performed using MACH software (55,56).
The promoter 2.0 Prediction Server (39) was used to predict
promoter regions and is-rSNP for in silico regulatory detection
(26). The eQTL analysis was done following methodology
described in reference (32).
Supplementary Material is available at HMG online.
The authors would like to thank Nico Lakenberg, Yavuz
Ariyurek, Dennis Kremer and Eka Suchiman for technical
assistance and to Oscar Lao for valuable comments and
Conﬂict of Interest statement. None declared.
This work was supported by grants from the Interuniversity
Cardiology Institute of the Netherlands (ICIN) and the
Durrer Center for Cardiogenetic Research both Institutes of
the Netherlands Royal Academy of Arts and Sciences
(KNAW), the Netherlands Heart Foundation, the Center for
Medical Systems Biology (CMSB), a center of excellence
approved by the Netherlands Genomics Initiative/Netherlands
Organisation for Scientiﬁc Research (NWO), the Netherlands
Consortium for Healthy Ageing (NCHA) and the EU project
HEALTH-F2-2007 223004 PHASE. J.W.J. is an established
clinical investigator of the Netherlands Heart Foundation
(2001D032). Part of this project was funded by a grant from
the Netherlands Genomics Initiative (NGI) and Netherlands
Organization for Scientiﬁc Research (NWO) within the frame-
work of the Forensic Genomics Consortium Netherlands
(FGCN) to P.d.K. CardioGene was funded in part by the Na-
tional Heart, Lung and Blood Institute Division of Intramural
Research. S.K.G. was supported in part by NHLBI
R00HL089413. The funders had no role in study design,
data collection and analysis, decision to publish or the prepar-
ation of the manuscript.
1. Agema, W.R., Monraats, P.S., Zwinderman, A.H., de Winter, R.J., Tio,
R.A., Doevendans, P.A., Waltenberger, J., de Maat, M.P., Frants, R.R.,
Atsma, D.E. et al. (2004) Current PTCA practice and clinical outcomes in
The Netherlands: the real world in the pre-drug-eluting stent era. Eur.
Heart. J.,25, 1163– 1170.
2. Roiron, C., Sanchez, P., Bouzamondo, A., Lechat, P. and Montalescot, G.
(2006) Drug eluting stents: an updated meta-analysis of randomised
controlled trials. Heart,92, 641– 649.
3. Sigwart, U., Puel, J., Mirkovitch, V., Joffre, F. and Kappenberger, L.
(1987) Intravascular stents to prevent occlusion and restenosis after
transluminal angioplasty. N. Engl. J. Med.,316, 701– 706.
4. Lee, M.S., David, E.M., Makkar, R.R. and Wilentz, J.R. (2004) Molecular
and cellular basis of restenosis after percutaneous coronary intervention:
the intertwining roles of platelets, leukocytes, and the
coagulation-ﬁbrinolysis system. J. Pathol.,203, 861– 870.
5. Pache, J., Kastrati, A., Mehilli, J., Schuhlen, H., Dotzer, F., Hausleiter, J.,
Fleckenstein, M., Neumann, F.J., Sattelberger, U., Schmitt, C. et al.
(2003) Intracoronary stenting and angiographic results: strut thickness
effect on restenosis outcome (ISAR-STEREO-2) trial. J. Am. Coll.
Cardiol.,41, 1283– 1288.
6. Serruys, P.W., de Jaegere, P., Kiemeneij, F., Macaya, C., Rutsch, W.,
Heyndrickx, G., Emanuelsson, H., Marco, J., Legrand, V. and Materne, P.
(1994) A comparison of balloon-expandable-stent implantation with
balloon angioplasty in patients with coronary artery disease. Benestent
Study Group. N. Engl. J. Med.,331, 489–495.
7. Ross, R., Masuda, J. and Raines, E.W. (1990) Cellular interactions,
growth factors, and smooth muscle proliferation in atherogenesis.
Ann. N. Y. Acad. Sci.,598, 102–112.
8. Ross, R. (1999) Atherosclerosis—an inﬂammatory disease.
N. Engl. J. Med.,340, 115– 126.
9. Rajagopal, V. and Rockson, S.G. (2003) Coronary restenosis: a review of
mechanisms and management. Am. J. Med.,115, 547– 553.
10. Arjomand, H., Turi, Z.G., McCormick, D. and Goldberg, S. (2003)
Percutaneous coronary intervention: historical perspectives, current status,
and future directions. Am. Heart. J.,146, 787–796.
11. Jenkins, N.P., Prendergast, B.D. and Thomas, M. (2002) Drug eluting
coronary stents. BMJ,325, 1315– 1316.
12. Morice, M.C., Serruys, P.W., Sousa, J.E., Fajadet, J., Ban, H.E., Perin, M.,
Colombo, A., Schuler, G., Barragan, P., Guagliumi, G. et al. (2002) A
randomized comparison of a sirolimus-eluting stent with a standard stent
for coronary revascularization. N. Engl. J. Med.,346, 1773– 1780.
13. Stone, G.W., Ellis, S.G., O’Shaughnessy, C.D., Martin, S.L., Satler, L.,
McGarry, T., Turco, M.A., Kereiakes, D.J., Kelley, L., Popma, J.J. and
Russell, M.E. (2006) Paclitaxel-eluting stents vs vascular brachytherapy
for in-stent restenosis within bare-metal stents: the TAXUS V ISR
randomized trial. JAMA,295, 1253– 1263.
14. Bourassa, M.G., Lesperance, J., Eastwood, C., Schwartz, L., Cote, G.,
Kazim, F. and Hudon, G. (1991) Clinical, physiologic, anatomic and
procedural factors predictive of restenosis after percutaneous transluminal
coronary angioplasty. J. Am. Coll. Cardiol.,18, 368– 376.
15. Stein, B., Weintraub, W.S., Gebhart, S.P., Cohen-Bernstein, C.L.,
Grosswald, R., Liberman, H.A., Douglas, J.S. Jr, Morris, D.C. and King,
Human Molecular Genetics, 2011, Vol. 20, No. 23 4755
S.B. III (1995) Inﬂuence of diabetes mellitus on early and late outcome
after percutaneous transluminal coronary angioplasty. Circulation,91,
16. Agema, W.R., Jukema, J.W., Pimstone, S.N. and Kastelein, J.J. (2001)
Genetic aspects of restenosis after percutaneous coronary interventions:
towards more tailored therapy. Eur. Heart. J.,22, 2058–2074.
17. Kastrati, A., Schomig, A., Elezi, S., Schuhlen, H., Wilhelm, M. and
Dirschinger, J. (1998) Interlesion dependence of the risk for restenosis in
patients with coronary stent placement in in multiple lesions. Circulation,
97, 2396– 2401.
18. de Maat, M.P., Jukema, J.W., Ye, S., Zwinderman, A.H., Moghaddam,
P.H., Beekman, M., Kastelein, J.J., van Boven, A.J., Bruschke, A.V.,
Humphries, S.E. et al. (1999) Effect of the stromelysin-1 promoter on
efﬁcacy of pravastatin in coronary atherosclerosis and restenosis.
Am. J. Cardiol.,83, 852– 856.
19. Kastrati, A., Schomig, A., Seyfarth, M., Koch, W., Elezi, S., Bottiger, C.,
Mehilli, J., Schomig, K. and von Beckerath, N. (1999) PlA polymorphism
of platelet glycoprotein IIIa and risk of restenosis after coronary stent
placement. Circulation,99, 1005– 1010.
20. Monraats, P.S., Pires, N.M., Agema, W.R., Zwinderman, A.H., Schepers,
A., de Maat, M.P., Doevendans, P.A., de Winter, R.J., Tio, R.A.,
Waltenberger, J. et al. (2005) Genetic inﬂammatory factors predict
restenosis after percutaneous coronary interventions. Circulation,112,
21. Monraats, P.S., Pires, N.M., Schepers, A., Agema, W.R., Boesten, L.S.,
De Vries, M.R., Zwinderman, A.H., de Maat, M.P., Doevendans, P.A., de
Winter, R.J. et al. (2005) Tumor necrosis factor-alpha plays an important
role in restenosis development. FASEB J.,19, 1998– 2004.
22. Amant, C., Bauters, C., Bodart, J.C., Lablanche, J.M., Grollier, G.,
Danchin, N., Hamon, M., Richard, F., Helbecque, N., McFadden, E.P.
et al. (1997) D allele of the angiotensin I-converting enzyme is a
major risk factor for restenosis after coronary stenting. Circulation,96,
23. Koch, W., Kastrati, A., Mehilli, J., Bottiger, C., von Beckerath, N. and
Schomig, A. (2000) Insertion/deletion polymorphism of the angiotensin
I-converting enzyme gene is not associated with restenosis after coronary
stent placement. Circulation,102, 197– 202.
24. Agema, W.R., Jukema, J.W., Zwinderman, A.H. and van der Wall, E.E.
(2002) A meta-analysis of the angiotensin-converting enzyme gene
polymorphism and restenosis after percutaneous transluminal
coronary revascularization: evidence for publication bias. Am. Heart J.,
144, 760– 768.
25. Higgins, J.P., Thompson, S.G., Deeks, J.J. and Altman, D.G. (2003)
Measuring inconsistency in meta-analyses. BMJ,327, 557–560.
26. MacIntyre, G., Bailey, J., Haviv, I. and Kowalczyk, A. (2010) is-rSNP: a
novel technique for in silico regulatory SNP detection. Bioinformatics,26,
27. Blastyak, A., Hajdu, I., Unk, I. and Haracska, L. (2010) Role of
double-stranded DNA translocase activity of human HLTF in replication
of damaged DNA. Mol. Cell Biol.,30, 684–693.
28. Hata, S., Hamada, J., Maeda, K., Murai, T., Tada, M., Furukawa, H.,
Tsutsumida, A., Saito, A., Yamamoto, Y. and Moriuchi, T. (2008) PAX4
has the potential to function as a tumor suppressor in human melanoma.
Int. J. Oncol.,33, 1065– 1071.
29. Gallo, R., Padurean, A., Jayaraman, T., Marx, S., Roque, M., Adelman, S.,
Chesebro, J., Fallon, J., Fuster, V., Marks, A. and Badimon, J.J. (1999)
Inhibition of intimal thickening after balloon angioplasty in porcine
coronary arteries by targeting regulators of the cell cycle. Circulation,99,
30. Giannakakou, P., Robey, R., Fojo, T. and Blagosklonny, M.V. (2001) Low
concentrations of paclitaxel induce cell type-dependent p53, p21 and G1/
G2 arrest instead of mitotic arrest: molecular determinants of
paclitaxel-induced cytotoxicity. Oncogene,20, 3806– 3813.
31. Argiropoulos, B. and Humphries, R.K. (2007) Hox genes in hematopoiesis
and leukemogenesis. Oncogene,26, 6766– 6776.
32. Dubois, P.C., Trynka, G., Franke, L., Hunt, K.A., Romanos, J., Curtotti,
A., Zhernakova, A., Heap, G.A., Adany, R., Aromaa, A. et al. (2010)
Multiple common variants for celiac disease inﬂuencing immune gene
expression. Nat. Genet.,42, 295– 302.
33. Lee, S.J., So, I.S., Park, S.Y. and Kim, I.S. (2008) Thymosin beta4 is
involved in stabilin-2-mediated apoptotic cell engulfment. FEBS Lett.,
582, 2161– 2166.
34. Park, S.Y., Kim, S.Y., Jung, M.Y., Bae, D.J. and Kim, I.S. (2008)
Epidermal growth factor-like domain repeat of stabilin-2 recognizes
phosphatidylserine during cell corpse clearance. Mol. Cell Biol.,28,
35. Harris, E.N., Baggenstoss, B.A. and Weigel, P.H. (2009) Rat and human
HARE/stabilin-2 are clearance receptors for high- and
low-molecular-weight heparins. Am. J. Physiol. Gastrointest. Liver
Physiol.,296, G1191– G1199.
36. Yatsuoka, T., Furukawa, T., Sunamura, M., Matsuno, S. and Horii, A.
(2004) TU12B1-TY, a novel gene in the region at 12q22-q23.1 frequently
deleted in pancreatic cancer, shows reduced expression in pancreatic
cancer cells. Oncol. Rep.,12, 1263– 1268.
37. Sabo, P.J., Hawrylycz, M., Wallace, J.C., Humbert, R., Yu, M., Shafer, A.,
Kawamoto, J., Hall, R., Mack, J., Dorschner, M.O. et al. (2004) Discovery
of functional noncoding elements by digital analysis of chromatin
structure. Proc. Natl Acad. Sci. USA,101, 16837– 16842.
38. Sabo, P.J., Humbert, R., Hawrylycz, M., Wallace, J.C., Dorschner, M.O.,
McArthur, M. and Stamatoyannopoulos, J.A. (2004) Genome-wide
identiﬁcation of DNaseI hypersensitive sites using active chromatin
sequence libraries. Proc. Natl Acad. Sci. USA,101, 4537–4542.
39. Knudsen, S. (1999) Promoter2.0: for the recognition of PolII promoter
sequences. Bioinformatics,15, 356– 361.
40. Visel, A., Zhu, Y., May, D., Afzal, V., Gong, E., Attanasio, C., Blow,
M.J., Cohen, J.C., Rubin, E.M. and Pennacchio, L.A. (2010) Targeted
deletion of the 9p21 non-coding coronary artery disease risk interval in
mice. Nature,464, 409– 412.
41. Hardy, J. and Singleton, A. (2009) Genomewide association studies and
human disease. N. Engl. J. Med.,360, 1759–1768.
42. Teslovich, T.M., Musunuru, K., Smith, A.V., Edmondson, A.C.,
Stylianou, I.M., Koseki, M., Pirruccello, J.P., Ripatti, S., Chasman, D.I.,
Willer, C.J. et al. (2010) Biological, clinical and population relevance of
95 loci for blood lipids. Nature,466, 707–713.
43. Gerrits, A., Li, Y., Tesson, B.M., Bystrykh, L.V., Weersing, E., Ausema,
A., Dontje, B., Wang, X., Breitling, R., Jansen, R.C. and de, H.G. (2009)
Expression quantitative trait loci are highly sensitive to cellular
differentiation state. PLoS Genet.,5, e1000692.
44. Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M.A.,
Bender, D., Maller, J., Sklar, P., de Bakker, P.I., Daly, M.J. and Sham,
P.C. (2007) PLINK: a tool set for whole-genome association and
population-based linkage analyses. Am. J. Hum. Genet.,81, 559– 575.
45. Li, J.Z., Absher, D.M., Tang, H., Southwick, A.M., Casto, A.M.,
Ramachandran, S., Cann, H.M., Barsh, G.S., Feldman, M., Cavalli-Sforza,
L.L. and Myers, R.M. (2008) Worldwide human relationships inferred
from genome-wide patterns of variation. Science,319, 1100 –1104.
46. Ganesh, S.K., Skelding, K.A., Mehta, L., O’Neill, K., Joo, J., Zheng, G.,
Goldstein, J., Simari, R., Billings, E., Geller, N.L. et al. (2004) Rationale
and study design of the CardioGene Study: genomics of in-stent
restenosis. Pharmacogenomics,5, 952– 1004.
47. Aulchenko, Y.S., Struchalin, M.V. and van Duijn, C.M. (2010)
ProbABEL package for genome-wide association analysis of imputed
data. BMC Bioinformatics,11, 134.
48. Hoppmann, P., Erl, A., Turk, S., Tiroch, K., Mehilli, J., Schomig, A.,
Kastrati, A. and Koch, W. (2009) No association of chromosome 9p21.3
variation with clinical and angiographic outcomes after placement of
drug-eluting stents. JACC Cardiovasc. Interv.,2, 1149– 1155.
49. Shepherd, J., Blauw, G.J., Murphy, M.B., Cobbe, S.M., Bollen, E.L.,
Buckley, B.M., Ford, I., Jukema, J.W., Hyland, M., Gaw, A. et al. (1999)
The design of a prospective study of Pravastatin in the Elderly at Risk
(PROSPER). PROSPER Study Group. PROspective Study of Pravastatin
in the Elderly at Risk. Am. J. Cardiol.,84, 1192–1197.
50. Shepherd, J., Blauw, G.J., Murphy, M.B., Bollen, E.L., Buckley, B.M.,
Cobbe, S.M., Ford, I., Gaw, A., Hyland, M., Jukema, J.W. et al. (2002)
Pravastatin in elderly individuals at risk of vascular disease (PROSPER):
a randomised controlled trial. Lancet,360, 1623– 1630.
51. Aulchenko, Y.S., Ripke, S., Isaacs, A. and van Duijn, C.M. (2007)
GenABEL: an R library for genome-wide association analysis.
Bioinformatics,23, 1294– 1296.
52. Barrett, J.C., Fry, B., Maller, J. and Daly, M.J. (2005) Haploview:
analysis and visualization of LD and haplotype maps. Bioinformatics,21,
53. Pruim, R.J., Welch, R.P., Sanna, S., Teslovich, T.M., Chines, P.S., Gliedt,
T.P., Boehnke, M., Abecasis, G.R. and Willer, C.J. (2010) LocusZoom:
4756 Human Molecular Genetics, 2011, Vol. 20, No. 23
regional visualization of genome-wide association scan results.
Bioinformatics,26, 2336– 2337.
54. McCarthy, M.I., Abecasis, G.R., Cardon, L.R., Goldstein, D.B., Little, J.,
Ioannidis, J.P. and Hirschhorn, J.N. (2008) Genome-wide association
studies for complex traits: consensus, uncertainty and challenges. Nat.
Rev. Genet.,9, 356– 369.
55. Li, Y., Willer, C., Sanna, S. and Abecasis, G. (2009) Genotype
imputation. Annu. Rev. Genomics Hum. Genet.,10, 387–406.
56. Li, Y., Willer, C.J., Ding, J., Scheet, P. and Abecasis, G.R. (2010) MaCH:
using sequence and genotype data to estimate haplotypes and unobserved
genotypes. Genet. Epidemiol.,34, 816– 834.
Human Molecular Genetics, 2011, Vol. 20, No. 23 4757