© 2013 Nature America, Inc. All rights reserved.
31 4 VOLUME 45 | NUMBER 3 | MARCH 2013 Nature GeNetics
L E T T E R S
Refractive error is the most common eye disorder worldwide
and is a prominent cause of blindness. Myopia affects over
30% of Western populations and up to 80% of Asians.
The CREAM consortium conducted genome-wide meta-analyses,
including 37,382 individuals from 27 studies of European
ancestry and 8,376 from 5 Asian cohorts. We identified 16 new
loci for refractive error in individuals of European ancestry,
of which 8 were shared with Asians. Combined analysis
identified 8 additional associated loci. The new loci include
candidate genes with functions in neurotransmission (GRIA4),
ion transport (KCNQ5), retinoic acid metabolism (RDH5),
extracellular matrix remodeling (LAMA2 and BMP2) and eye
development (SIX6 and PRSS56). We also confirmed previously
reported associations with GJD2 and RASGRF1. Risk score
analysis using associated SNPs showed a tenfold increased risk
of myopia for individuals carrying the highest genetic load.
Our results, based on a large meta-analysis across independent
multiancestry studies, considerably advance understanding of
the mechanisms involved in refractive error and myopia.
Refractive error is the leading cause of visual impairment in the world
1
.
Myopia, or nearsightedness, in particular is associated with structural
changes of the eye, increasing the risk of severe complications, such as
macular degeneration, retinal detachment and glaucoma. The preva-
lence of myopia has been rising considerably
over the past few decades
2
, and it is estimated
that 2.5 billion people will be affected by myo-
pia within a decade
3
. Although several genetic
loci influencing refractive error have been
identified
4–10
, their contribution to pheno-
typic variance is small, and many more loci are
expected to explain its genetic architecture.
Here, the Consortium for Refractive Error
and Myopia (CREAM) presents results from
the largest international genome-wide meta-
analysis on refractive error, with data from
32 studies from Europe, the United States,
Australia and Asia. The meta-analysis was
performed in 3 stages. In the first stage, we
investigated the genome-wide association
study (GWAS) results of 37,382 individuals
from 27 populations of European ancestry (Supplementary Table 1
and Supplementary Note) using spherical equivalent as a continuous
outcome. In the second stage, we aimed to test the cross-ancestry trans-
ferability of the statistically significant associations from the first stage
in 8,376 individuals from 5 Asian cohorts (Supplementary Table 1 and
Supplementary Note). In the third stage, we performed a GWAS meta-
analysis on the combined populations (total n = 45,758). Subsequently,
we examined the influence of associated alleles on the risk of myopia in
a genetic risk score analysis, and, lastly, we evaluated gene expression
in ocular tissues and explored potential mechanisms by which newly
found loci might exert their effects on refractive development.
In stage 1, we analyzed ~2.5 million autosomal SNPs for which
data were obtained through whole-genome imputation of genotypes
to HapMap 2. The inflation factors (
λ
GC
) of the test statistics in indi-
vidual studies contributing to the meta-analysis ranged between 0.992
and 1.050, indicating excellent within-study control of population
substructure (Supplementary Table 2). Overall
λ
was 1.09, consistent
with a polygenic inheritance model for refractive error (quantile-
quantile plot; Supplementary Fig. 1). We did not perform a correc-
tion for
λ
, as it has been shown that, under polygenic inheritance,
substantial genomic inflation can be expected, even in the absence of
population structure and technical artifacts
11
. We identified 309 SNPs
that exceeded the conventional genome-wide significance threshold
of P = 5.0 × 10
−8
in the European ancestry sample. These SNPs were
Genome-wide meta-analyses of multiancestry cohorts
identify multiple new susceptibility loci for refractive
error and myopia
A full list of authors and affiliations appears at the end of the paper.
Received 3 October 2012; accepted 16 January 2013; published online 10 February 2013; corrected after print 9 May 2013; doi:10.1038/ng.2554
CREAM
10
–log
10
(P)
5
20
0
1
2
3
4
5
6
7
Chromosome
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
15
CD55
CACNA1D
TJP2
RORB
PCCA/ZIC2
SHISA6
MYO1D
KCNJ2
BMP2
CNDP2
SIX6
GJD2
RASGRF1
PTPRR
RDH5
GRIA4
BICC1
TOX/CHD7
ZMAT4
LAMA2
KCNQ5
BMP3
LOC100506035
PRSS56/CHRNG
CYP26A1
RBFOX1
Figure 1 Manhattan plot of the GWAS meta-analysis for refractive error in the combined analysis
(n = 45,758). The plot shows −log
10
-transformed P values for all SNPs. The upper horizontal line
represents the genome-wide significance threshold of P < 5.0 × 10
−8
; the lower line indicates P value
of 1 × 10
−5
. Previously reported genes are shown in gray. The RBFOX1 gene is also known as A2BP1.
© 2013 Nature America, Inc. All rights reserved.
Nature GeNetics VOLUME 45 | NUMBER 3 | MARCH 2013 3 15
L E T T E R S
clustered in 18 distinct genomic regions across 14 chromosomes
(Fig. 1 and Table 1). In stage 2, we investigated the 18 best-associated
SNPs in the Asian population: 10 showed evidence of association
(Table 1). The most significant association in both ancestry groups
was at a previously identified locus on chromosome 15q14 in the
proximity of the GJD2 gene (encoding the connexin 36 gap-junction
protein; rs524952; P
combined
= 1.44 × 10
−15
)
4,12
. The locus near the
RASGRF1 gene (encoding Ras protein–specific guanine nucleotide–
releasing factor 1) was also replicated in the meta-analysis (rs4778879;
P
combined
= 4.25 × 10
−11
)
9
. The remaining 16 loci associated at genome-
wide significance had not previously been reported in association
with refractive error. Those loci that did not show significant asso-
ciation in the smaller sized Asian population mostly had a similar
effect size and direction of effect as in the European ancestry sample.
In stage 3, we identified eight additional loci with associations
that exceeded genome-wide significance in the combined analysis
(Table 2). Regional and forest plots of the associated loci are provided
in Supplementary Figures 2 and 3, respectively.
Genotype distributions of the risk alleles were evaluated in
Rotterdam Studies 1–3 (n = 9,307). The clinical usefulness for the
prediction of risk of myopia was evaluated by a weighted genetic risk
score analysis based on the aggregate of effects (
β
regression coeffi-
cients) of individual SNPs derived from the meta-analysis, using the
middle risk category as a reference. Risk scores ranged from a mean
risk score of 1.88 (95% confidence interval (CI) = 1.86–1.89) in the
lowest risk score category to 3.63 (95% CI = 3.61–3.65) in the highest
risk score category. Having the lowest or the highest genetic risk score
was associated with an odds ratio (OR) of 0.38 (95% CI = 0.18–0.77)
and an OR of 10.97 (95% CI = 3.73–31.25) of myopia, respectively
(Fig. 2). The predictive value (area under the receiver operating
characteristic curve, AUC) of myopia versus hyperopia was 0.67
(95% CI = 0.65–0.69), a relatively high value for genetic factors in a
complex trait
13,14
. The genetic variants explained 3.4% of the pheno-
typic variation in refractive error in the Rotterdam Study.
We examined the expression of genes harboring a genetic asso-
ciation signal by measuring the levels of RNA in various eye tissues
and found most of these genes expressed in the eye (Supplementary
Table 3). Expression data for the PRSS56, LOC100506035 and SHISA6
genes were not available; all other genes were expressed in the
retina. Subsequently, we assessed the areas with associated SNPs
for acetylation at histone H3 lysine 27 (H3K27ac) modifications
15
and HaploReg
16
annotations for marks of active regulatory elements
(Supplementary Fig. 4 and Supplementary Table 4). We found that
many associated loci contained these elements, and alteration of regu-
latory function is therefore a potential mechanism.
The widely accepted model for myopia development is that eye
growth is triggered by a visually evoked signaling cascade, which
originates from the sensory retina, traverses the retinal pigment
epithelium (RPE) and choroid and terminates in the sclera, where
active extracellular matrix (ECM) remodeling results in a relative
elongation of the eye
17
. Many of the genes in or near the identified
loci can be linked to biological processes that drive this cascade.
Neurotransmission in the retina is a necessary mechanism for eye
growth regulation; the most significantly associated gene GJD2 has
a role in this process. This gene forms a gap junction between neu-
ronal cells in the retina, enabling the intercellular exchange of small
molecules and ions. The other previously reported gene RASGRF1 is a
nuclear exchange factor that promotes the exchange of GTP for GDP
on Ras family GTPases and is involved in the synaptic transmission
of photoreceptor responses
18,19
. Both GJD2 and RASGRF1 knock-
out mice show retinal photoreception defects
18,20
. One of the newly
Table 1 Genome-wide significant associations with refractive error in the European ancestry population with results in the Asian population and combined analysis
Locus
number SNP Chromosome Position Nearest gene A1/A2
MAF
β
SE P value MAF
β
SE P value
β
SE P value P value
Stage 1 (n = 37,382) Stage 2 (n = 8,376) Combined (n = 45,758) Heterogeneity
1 rs1652333 1 203858855 CD55 G/A 0.32 –0.115 0.018 6.29 × 10
–11
0.42 –0.099 0.035 5.00 × 10
–3
–0.112 0.016 3.05 × 10
–12
0.94
2 rs1656404 2 233205446 PRSS56 A/G 0.21 –0.151 0.025 2.38 × 10
–9
0.11 –0.167 0.069 1.60 × 10
–2
–0.153 0.024 7.86 × 10
–11
0.83
rs1881492 2 233406997 CHRNG T/G 0.22 –0.145 0.022 1.28 × 10
–10
0.15 –0.057 0.110 6.09 × 10
–1
–0.139 0.021 5.15 × 10
–11
0.88
3 rs14165 3 53847407 CACNA1D A/G 0.32 0.095 0.017 4.36 × 10
–8
0.12 0.120 0.100 2.29 × 10
–1
0.096 0.017 2.14 × 10
–8
0.25
4 rs1960445 4 81930813 BMP3 C/T 0.17 –0.147 0.026 1.19 × 10
–8
0.11 0.034 0.055 5.32 × 10
–1
–0.114 0.024 1.25 × 10
–6
0.31
5 rs12205363 6 129834628 LAMA2 C/T 0.10 0.228 0.034 1.13 × 10
–11
0.02 0.553 0.236 1.92 × 10
–2
0.235 0.033 1.79 × 10
–12
0.93
6 rs4237036 8 61701056 CHD7 C/T 0.35 0.097 0.017 1.52 × 10
–8
0.23 0.043 0.040 2.81 × 10
–1
0.089 0.016 1.82 × 10
–8
0.76
rs7837791 8 60179085 TOX T/G 0.49 0.106 0.017 9.22 × 10
–10
0.39 0.103 0.035 4.00 × 10
–3
0.106 0.015 3.99 × 10
–12
0.70
7 rs7829127 8 40726393 ZMAT4 G/A 0.25 0.116 0.020 3.04 × 10
–9
0.11 0.112 0.055 4.23 × 10
–2
0.116 0.018 3.69 × 10
–10
0.66
8 rs7042950 9 77149836 RORB G/A 0.24 –0.113 0.020 1.02 × 10
–8
0.42 –0.040 0.037 2.72 × 10
–1
–0.096 0.018 4.15 × 10
–8
0.83
9 rs10882165 10 94924323 CYP26A1 T/A 0.42 –0.111 0.016 1.25 × 10
–11
0.20 –0.060 0.056 2.84 × 10
–1
–0.107 0.016 1.03 × 10
–11
0.90
10 rs7084402 10 60265403 BICC1 G/A 0.48 –0.111 0.016 7.23 × 10
–12
0.50 –0.094 0.035 7.34 × 10
–3
–0.108 0.015 2.06 × 10
–13
0.71
11 rs11601239 11 105061808 GRIA4 C/G 0.46 –0.092 0.017 3.45 × 10
–8
0.42 –0.129 0.058 2.70 × 10
–2
–0.095 0.016 5.92 × 10
–9
0.83
12 rs3138144 12 56114768 RDH5 C/G 0.48 0.113 0.018 4.28 × 10
–10
0.45 0.157 0.072 3.00 × 10
–2
0.119 0.017 4.44 × 10
–12
0.09
13 rs2184971 13 100818091 PCCA G/A 0.44 0.095 0.016 5.90 × 10
–9
0.22 0.022 0.040 5.84 × 10
–1
0.085 0.015 2.11 × 10
–8
0.96
rs8000973 13 100691366 ZIC2 T/C 0.47 0.089 0.016 4.24 × 10
–8
0.22 0.030 0.041 4.63 × 10
–1
0.081 0.015 5.10 × 10
–8
0.50
14 rs524952 15 35005885 GJD2
a
A/T 0.48 –0.154 0.021 1.11 × 10
–13
0.44 –0.193 0.060 1.00 × 10
–3
–0.158 0.020 1.44 × 10
–15
0.22
15 rs4778879 15 79372874 RASGRF1
a
G/A 0.44 –0.103 0.017 1.27 × 10
–9
0.39 –0.103 0.043 1.50 × 10
–2
–0.102 0.015 4.25 × 10
–11
0.15
16 rs17183295 17 31078271 MYO1D T/C 0.23 –0.132 0.021 3.04 × 10
–10
0.16 –0.166 0.144 2.49 × 10
–1
–0.131 0.020 9.66 × 10
–11
0.34
17 rs4793501 17 68718733 KCNJ2 C/T 0.42 0.096 0.016 3.21 × 10
–9
0.44 0.010 0.034 7.64 × 10
–1
0.080 0.014 2.79 × 10
–8
0.04
18 rs12971120 18 72174022 CNDP2 G/A 0.23 0.108 0.020 4.39 × 10
–8
0.30 0.014 0.063 8.27 × 10
–1
0.099 0.019 1.85 × 10
–7
0.49
Summary of SNPs that showed genome-wide significant (P < 5 × 10
−8
) association with spherical equivalent (SE) in subjects of European ancestry (stage 1), with results of replication in Asians (stage 2) and combined analysis
(stage 3). We tested for heterogeneous effects between the Asian and European ancestry samples, for which P values are shown. Nearest gene, reference NCBI build 37; A1, reference allele; A2, other allele, MAF, average minor allele frequency;
β
, effect size on spherical
equivalent in diopters based on allele A1.
a
Previously reported genes.
© 2013 Nature America, Inc. All rights reserved.
31 6 VOLUME 45 | NUMBER 3 | MARCH 2013 Nature GeNetics
L E T T E R S
identified genes, GRIA4 (encoding glutamate receptor, ionotropic,
AMPA 4; rs11601239; P
combined
= 5.92 × 10
−9
), also has a potential
function in this pathway. This gene encodes a glutamate-gated ion
channel that mediates fast synaptic excitatory neurotransmission
21
, is
present in various retinal cells
22
and has been shown to be critical for
light signaling in the retina
23
and emmetropization
24
. Another gene
involved in synaptic transmission is RBFOX1 (encoding RNA-binding
protein, fox-1 homolog; also known as A2BP1; rs17648524; P
combined
=
5.64 × 10
−10
), encoding an RNA-binding splicing regulator that
modulates membrane excitability
25
.
We identified for the first time a number of candidate genes
involved in ion transport, channel activity and the maintenance of
membrane potential. KCNQ5 (encoding a member of the potassium
voltage-gated channel KQT-like subfamily; rs7744813; P
combined
=
4.18 × 10
−9
), participates in the transport of potassium ions from
the retina to the choroid and may contribute to voltage-gated potas-
sium ion channels in the photoreceptors and retinal neurons associ-
ated with myopia
26,27
. CD55 (encoding a decay-accelerating factor
for complement; rs1652333; P
combined
= 3.05 × 10
−12
) is known to
elevate cytosolic calcium ion concentration. Other ion channel genes
that were associated include CACNA1D (encoding a voltage-sensitive
calcium channel regulator; rs14165; P
combined
= 2.14 × 10
–8
), KCNJ2
(encoding a regulator of potassium ion transport; rs4793501; P
combined
=
2.79 × 10
–8
), CHRNG (encoding a nicotinic cholinergic receptor;
rs1881492; P
combined
= 2.15 × 10
–11
) and MYO1D (encoding a putative
binder of calmodulin; rs17183295; P
combined
= 9.66 × 10
–11
), which
mediates calcium ion sensitivity to KCNQ5 ion channels.
Retinoic acid is synthesized in the retina, is highly expressed in
the choroid and has been implicated in eye growth in experimental
myopia models
28–30
. RDH5 (encoding retinol dehydrogenase 5;
rs3138144; P
combined
= 4.44 × 10
–12
), a new refractive error suscep-
tibility gene is involved in the recycling of 11-cis-retinal in the
visual cycle
31
. Mutations in RDH5 cause congenital stationary
night blindness (MIM 136880), a disease associated with myopia.
Other genes involved in retinoic acid metabolism are RORB
(encoding RAR-related orphan receptor; rs7042950; P
combined
=
4.15 × 10
–8
) and CYP26A1 (encoding a member of the cytochrome
P450 superfamily; rs10882165; P
combined
= 1.03 × 10
–11
), genes that
showed significant associations in the European ancestry studies.
Notably, retinoic acid contributes to ECM remodeling by regulating
cell differentiation.
ECM remodeling of the sclera is the pathological hallmark of
myopia development. LAMA2 (encoding laminin α2; rs12205363;
P
combined
= 1.79 × 10
−12
) is the most prominent gene in this respect.
The LAMA2 protein forms a subunit of the heterotrimer laminins,
which are essential components of basement membranes, stabiliz-
ing cellular structures and facilitating cell migration
32
. Two genes
encoding bone morphogenetic proteins (BMP2: rs235770; P
combined
=
1.57 × 10
−8
and BMP3: rs1960445; P
stage 1
= 1.19 × 10
–8
; P
combined
=
1.25 × 10
–6
) also have a role in the ECM architecture. They are
members of the transforming growth factor (TGF)-β superfamily,
regulate the growth and differentiation of mesenchymal cells and may
orchestrate the organization of other connective tissues than bone,
such as sclera. Notably, BMP2 shows expression in RPE in animal
models of myopia
33
.
Genes involved in eye development appeared as a separate
entity among the gene functions. SIX6 (encoding SIX homeobox 6;
rs1254319; P
combined
= 1.00 × 10
−8
) has been linked to anophthalmia
and glaucoma
34,35
, PRSS56 (encoding protease serine 56, rs1656404;
P
combined
= 7.86 × 10
−11
) has been linked to microphthalmia
36–38
,
CHD7 (encoding chromodomain helicase DNA-binding protein 7;
rs4237036; P
combined
= 1.82 × 10
–8
) has been linked to CHARGE
syndrome, a congenital condition with severe eye structural defects,
and ZIC2 (encoding a member of the ZIC family of C2H2-type zinc-
finger proteins; rs8000973; P
combined
= 5.10 × 10
–8
) has been linked
to brain development, including visual perception. For the remaining
new associated loci, a mechanism in the pathogenesis of myopia is
not immediately clear. Results from Ingenuity and the Protein Link
Evaluator
39
(Supplementary Fig. 5) map the subcellular location of
all associated gene products and show their inter-relationships. Direct
connections between genes were infrequent, suggesting molecular
Table 2 Additional genome-wide significant associations from the combined meta-analysis (n = 45,758)
Locus
number SNP Chromosome Position Nearest gene A1/A2
β
SE P value MAF
β
SE P value MAF
β
SE P value P value
Combined (n = 45,758) Stage 1 (n = 37,382) Stage 2 (n = 8,376) Heterogeneity
1 rs9307551 4 80530670 LOC100506035 A/C –0.099 0.017 1.09 × 10
–8
0.25 –0.097 0.020 1.37 × 10
–6
0.50 –0.105 0.035 3.06 × 10
–3
0.70
2 rs7744813 6 73643288 KCNQ5 C/A 0.112 0.019 4.18 × 10
–9
0.41 0.114 0.021 6.80 × 10
–8
0.33 0.094 0.046 4.30 × 10
–2
0.14
3 rs11145465 9 71766592 TJP2 A/C –0.124 0.021 7.26 × 10
–9
0.25 –0.125 0.023 6.92 × 10
–8
0.07 –0.136 0.091 1.35 × 10
–1
0.14
4 rs12229663 12 71249995 PTPRR G/A 0.099 0.017 5.47 × 10
–9
0.27 0.104 0.019 5.46 × 10
–8
0.36 0.080 0.052 1.23 × 10
–1
0.74
5 rs1254319 14 60903756 SIX6 A/G –0.088 0.015 1.00 × 10
–8
0.32 –0.088 0.017 2.03 × 10
–7
0.34 –0.087 0.036 1.57 × 10
–2
0.59
6 rs17648524 16 7459682 RBFOX1 C/G –0.118 0.019 5.64 × 10
–10
0.36 –0.116 0.022 7.48 × 10
–8
0.14 –0.140 0.058 1.60 × 10
–2
0.24
7 rs2969180 17 11407900 SHISA6 A/G –0.101 0.015 7.29 × 10
–11
0.36 –0.101 0.019 7.51 × 10
–8
0.45 –0.097 0.034 4.00 × 10
–3
0.41
8 rs235770 20 6761764 BMP2 T/C –0.089 0.016 1.57 × 10
–8
0.39 –0.088 0.017 1.34 × 10
–7
0.33 –0.087 0.050 8.20 × 10
–2
0.78
Summary of SNPs that showed genome-wide significant (P < 5 × 10
−8
) association with spherical equivalent in the combined analysis (stage 3), with results in subjects of European ancestry (stage 1) and Asians
(stage 2). We tested for heterogeneous effects between the two ancestry groups, for which P values are shown. Nearest gene, reference NCBI build 37. The RBFOX1 gene is also known as A2BP1.
0
5.00
10.00
15.00
20.00
25.00
30.00
<2.00
2.00–2.25
2.25–2.50
2.50–2.75
2.75–3.00
3.00–3.25
3.25–3.50
>3.50
Geneticrisk score
Subjects (%)
0
2.00
4.00
6.00
8.00
10.00
ORof myopia
OR of myopia
Myopia (%)
Emmetropia (%)
Hyperopia (%)
Figure 2 Genetic risk score for myopia. Distribution of subjects from
Rotterdam Study 1–3 (n = 9,307) with myopia (SE ≤ −3 diopters (D)),
emmetropia (SE ≥ −1.5 D and ≤ 1.5 D) and hyperopia (SE ≥ 3 D) as a function
of the genetic risk score. This score is based on the regression coefficients
and allele dosages of the associated SNPs for all 26 loci identified in the
meta-analysis. Mean OR of myopia was calculated per risk category, using the
middle risk score category (risk score of 2.50–2.75) as a reference.
© 2013 Nature America, Inc. All rights reserved.
Nature GeNetics VOLUME 45 | NUMBER 3 | MARCH 2013 3 17
L E T T E R S
disease heterogeneity or functional redundancy in the pathobiological
events involved in the development of refractive error and myopia.
In summary, we identified 24 new loci associated with refractive
error through a large-scale meta-analysis of GWAS from interna-
tional multiancestry studies. The substantial overlap in genetic loci
for refractive error between individuals of European ancestry and
Asians provides evidence for shared genetic risk factors between the
populations. The tenfold increased risk of myopia for those carrying
the highest number of risk alleles shows the clinical significance of our
findings. Further elucidation of the mechanisms by which these loci
affect eye growth carries the potential to improve the visual outcome
of this common trait.
URLs. R, http://www.r-project.org/; LocusZoom, http://csg.sph.
umich.edu/locuszoom/; Ingenuity, http://www.ingenuity.com/.
METHODS
Methods and any associated references are available in the online
version of the paper.
Accession codes. Data on RPE gene expression have been deposited at
the Gene Expression Omnibus (GEO) under accession GSE20191.
Note: Supplementary information is available in the online version of the paper.
ACKNOWLEDGMENTS
We gratefully thank the invaluable contributions of all study participants, their
relatives and staff at the recruitment centers. Complete funding information and
acknowledgments by study can be found in the Supplementary Note.
AUTHOR CONTRIBUTIONS
V.J.M.V., P.G.H., R.W., C.J.H., C.C.W.K., A.W.H., D.A.M., T.L.Y. and C.M.v.D.
performed analyses and drafted the manuscript. C.C.W.K., D.S., C.J.H., J.E.B.-W.,
S.-M.S., C.M.v.D., A.H., D.A.M., S.M., A.D.P., V.V., C.W., P.N.B., T.-Y.W., J.S.R.,
T.L.Y., K.O., O. Pärssinen, S.P.Y., J.A.G., A. Metspalu, M.P., S.K.I. and N.P. jointly
conceived the project and supervised the work. J.E.B.W., S.-M.S., D.A.M., T.L.Y.,
C.J.H., C.C.W.K., D.S., J.E.B.-W., C.M.v.D., R.W., P.G.H., V.J.M.V., K.O., Y.-Y.T., T.-Y.W.,
P.N.B., V.V., N.A., B.A.O., A.H., J.R.V., F.R., A.G.U., N.P., C.M., A. Mirshahi, T.Z.,
B.F., J.F.W., Z.V., O. Polasek, A.F.W., C.H., I.R., S.K.I., E.C., J.H.L., R.P.I., S.J., M.S.,
J.J.W., P.M., I.C., J.S.R., P.M.C., C.E.P., G.W.M., A. Mishra, W.A., F.M., M.P., L.C.K.,
T.D.S., E.Y.-D., A.N., O.R., C.-C.K., T.M., A.D., R.T.O., Y.Z., J.L., R.L., P.C., V.A.B.,
W.-T.T., E.V., T.A., E.-S.T., A. Metspalu, T.H., R.K., B.E.K.K., J.E.C., K.P.B., L.J.C.,
C.P.P., D.W.H.H., S.P.Y., J.W., O. Pärssinen, J.B.J., L.X., H.S.W., S.M.H., A.D.P., M.K.,
T.L., K.-M.M., C.L.S., C.W., N.J.T., D.M.E., B.S.P., J.P.K., G.M., G.H.S.B., M.K.I.,
X.Z., C.-Y.C., A.W.H., S.M., R.H., J.A.G. and Q.F. were responsible for study-
specific data. G.H.S.B., V.J.M.V., Q.F. and J.A.G. were involved in the genetic risk
score analysis. T.L.Y., A.A.B.B., T.G.M.F.G. and F.H. performed the data expression
experiments. A.A.B.B., T.G.M.F.G., A.M. and S.M. were involved in pathway
analyses. J.E.B.-W., S.-M.S., D.A.M., T.L.Y., K.O., T.-Y.W., P.N.B., T.G.M.F.G., S.K.I.,
E.C., J.J.W., A.J.M.H.V., C.-C.K., B.E.K.K., S.P.Y., C.W., N.J.T., G.H.S.B., M.K.I.,
A.W.H. and J.A.G. critically reviewed the manuscript.
COMPETING FINANCIAL INTERESTS
The authors declare no competing financial interests.
Published online at http://www.nature.com/doifinder/10.1038/ng.2554.
Reprints and permissions information is available online at http://www.nature.com/
reprints/index.html.
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© 2013 Nature America, Inc. All rights reserved.
31 8 VOLUME 45 | NUMBER 3 | MARCH 2013 Nature GeNetics
Virginie J M Verhoeven
1,2,68
, Pirro G Hysi
3,68
, Robert Wojciechowski
4,5,68
, Qiao Fan
6,68
, Jeremy A Guggenheim
7,68
,
René Höhn
8,68
, Stuart MacGregor
9
, Alex W Hewitt
10,11
, Abhishek Nag
3
, Ching-Yu Cheng
6,12,13
,
Ekaterina Yonova-Doing
3
, Xin Zhou
6
, M Kamran Ikram
6,12,13
, Gabriëlle H S Buitendijk
1,2
, George McMahon
14
,
John P Kemp
14
, Beate St Pourcain
15
, Claire L Simpson
4
, Kari-Matti Mäkelä
16
, Terho Lehtimäki
16
, Mika Kähönen
17
,
Andrew D Paterson
18
, S Mohsen Hosseini
18
, Hoi Suen Wong
18
, Liang Xu
19
, Jost B Jonas
20
, Olavi Pärssinen
21,22,23
,
Juho Wedenoja
24
, Shea Ping Yip
25
, Daniel W H Ho
7,25
, Chi Pui Pang
26
, Li Jia Chen
27
, Kathryn P Burdon
28
,
Jamie E Craig
28
, Barbara E K Klein
29
, Ronald Klein
29
, Toomas Haller
30
, Andres Metspalu
30
,
Chiea-Chuen Khor
6,12,31,32
, E-Shyong Tai
6,33,34
, Tin Aung
12,13
, Eranga Vithana
13
, Wan-Ting Tay
13
,
Veluchamy A Barathi
12,13,34
, Consortium for Refractive Error and Myopia (CREAM)
35
, Peng Chen
6
, Ruoying Li
6
,
Jiemin Liao
12
, Yingfeng Zheng
13
, Rick T Ong
6
, Angela Döring
36,37
, The Diabetes Control and Complications
Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) Research Group
35
,
David M Evans
14
, Nicholas J Timpson
14
, Annemieke J M H Verkerk
38
, Thomas Meitinger
39
, Olli Raitakari
40,41
,
Felicia Hawthorne
42
, Tim D Spector
3
, Lennart C Karssen
2
, Mario Pirastu
43
, Federico Murgia
43
, Wei Ang
44
,
Wellcome Trust Case Control Consortium 2 (WTCCC2)
35
, Aniket Mishra
9
, Grant W Montgomery
45
,
Craig E Pennell
44
, Phillippa M Cumberland
46,47
, Ioana Cotlarciuc
48
, Paul Mitchell
49
, Jie Jin Wang
10,49
,
Maria Schache
10
, Sarayut Janmahasatian
50
, Robert P Igo Jr
50
, Jonathan H Lass
50,51
, Emily Chew
52
,
Sudha K Iyengar
50,51,53
, The Fuchs’ Genetics Multi-Center Study Group
35
, Theo G M F Gorgels
54
, Igor Rudan
55
,
Caroline Hayward
56
, Alan F Wright
56
, Ozren Polasek
57
, Zoran Vatavuk
58
, James F Wilson
55
, Brian Fleck
59
,
Tanja Zeller
60
, Alireza Mirshahi
8
, Christian Müller
60
, André G Uitterlinden
2,37,61
, Fernando Rivadeneira
2,38,61
,
Johannes R Vingerling
1,2
, Albert Hofman
2,61
, Ben A Oostra
62
, Najaf Amin
2
, Arthur A B Bergen
54,63,64
, Yik-Ying Teo
6,65
,
Jugnoo S Rahi
45,47,66
, Veronique Vitart
56
, Cathy Williams
15
, Paul N Baird
10
, Tien-Yin Wong
6,12,13
, Konrad Oexle
39
,
Norbert Pfeiffer
8
, David A Mackey
10,11
, Terri L Young
42
, Cornelia M van Duijn
2
, Seang-Mei Saw
6,12,13,34,69
,
Joan E Bailey-Wilson
4,69
, Dwight Stambolian
67,69
, Caroline C Klaver
1,2,69
& Christopher J Hammond
3,69
1
Department of Ophthalmology, Erasmus Medical Center, Rotterdam, The Netherlands.
2
Department of Epidemiology, Erasmus Medical Center, Rotterdam,
The Netherlands.
3
Department of Twin Research and Genetic Epidemiology, King’s College London School of Medicine, London, UK.
4
Inherited Disease Research
Branch, National Human Genome Research Institute, US National Institutes of Health, Baltimore, Maryland, USA.
5
Department of Epidemiology, Johns Hopkins
Bloomberg School of Public Health, Baltimore, Maryland, USA.
6
Saw Swee Hock School of Public Health, National University Health Systems, National University of
Singapore, Singapore.
7
Centre for Myopia Research, School of Optometry, The Hong Kong Polytechnic University, Hong Kong.
8
Department of Ophthalmology, University
Medical Center Mainz, Mainz, Germany.
9
Department of Statistical Genetics, Queensland Institute of Medical Research, Herston, Brisbane, Queensland, Australia.
10
Centre for Eye Research Australia (CERA), University of Melbourne, Royal Victorian Eye and Ear Hospital, Melbourne, Victoria, Australia.
11
Centre for Ophthalmology
and Visual Science, Lions Eye Institute, University of Western Australia, Perth, Western Australia, Australia.
12
Department of Ophthalmology, National University Health
Systems, National University of Singapore, Singapore.
13
Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.
14
Medical Research Council
Centre for Causal Analyses in Translational Epidemiology, School of Social and Community Medicine, University of Bristol, Bristol, UK.
15
School of Social and
Community Medicine, University of Bristol, Bristol, UK.
16
Department of Clinical Chemistry, Fimlab Laboratories and School of Medicine, University of Tampere,
Tampere, Finland.
17
Department of Clinical Physiology, Tampere University Hospital and School of Medicine, University of Tampere, Tampere, Finland.
18
Program in
Genetics and Genome Biology, Hospital for Sick Children and University of Toronto, Toronto, Ontario, Canada.
19
Beijing Institute of Ophthalmology, Beijing Tongren
Hospital, Capital Medical University, Beijing, China.
20
Department of Ophthalmology, Medical Faculty Mannheim, Ruprecht-Karls-University Heidelberg, Mannheim,
Germany.
21
Department of Health Sciences, University of Jyväskylä, Jyväskylä, Finland.
22
Gerontology Research Center, University of Jyväskylä, Jyväskylä, Finland.
23
Department of Ophthalmology, Central Hospital of Central Finland, Jyväskylä, Finland.
24
Department of Public Health, Hjelt Institute, University of Helsinki, Helsinki,
Finland.
25
Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong.
26
Department of Ophthalmology and Visual Sciences,
The Chinese University of Hong Kong, Hong Kong Eye Hospital, Kowloon, Hong Kong.
27
Department of Ophthalmology and Visual Sciences, The Chinese University of
Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong.
28
Department of Ophthalmology, Flinders University, Adelaide, South Australia, Australia.
29
Department of
Ophthalmology and Visual Sciences, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA.
30
Estonian Genome Center, University of
Tartu, Tartu, Estonia.
31
Department of Pediatrics, National University of Singapore, Singapore.
32
Division of Human Genetics, Genome Institute of Singapore, Singapore.
33
Department of Medicine, National University of Singapore, Singapore.
34
Duke–National University of Singapore Graduate Medical School, Singapore.
35
A full list of
members appears in the Supplementary Note.
36
Institute of Epidemiology I, Helmholtz Zentrum München–German Research Center for Environmental Health,
Neuherberg, Germany.
37
Institute of Epidemiology II, Helmholtz Zentrum München–German Research Center for Environmental Health, Neuherberg, Germany.
38
Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands.
39
Institute of Human Genetics, Technical University Munich, Munich,
Germany.
40
Research Centre of Applied and Preventive Medicine, University of Turku, Turku, Finland.
41
Department of Clinical Physiology and Nuclear Medicine, Turku
University Hospital, Turku, Finland.
42
Department of Pediatric Ophthalmology, Duke Eye Center For Human Genetics, Durham, North Carolina, USA.
43
Institute of
Population Genetics, National Research Council, Sassari, Italy.
44
School of Women’s and Infants’ Health, University of Western Australia, Perth, Western Australia,
Australia.
45
Department of Molecular Epidemiology, Queensland Institute of Medical Research, Herston, Brisbane, Queensland, Australia.
46
Medical Research Council
Centre of Epidemiology for Child Health, Institute of Child Health, University College London, London, UK.
47
Ulverscroft Vision Research Group, University College
London, London, UK.
48
Imperial College Cerebrovascular Research Unit (ICCRU), Division of Brain Sciences, Department of Medicine, Imperial College London,
London, UK.
49
Department of Ophthalmology, Centre for Vision Research, Westmead Millennium Institute, University of Sydney, Sydney, New South Wales, Australia.
50
Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, USA.
51
Department of Ophthalmology and Visual Sciences, Case
Western Reserve University and University Hospitals Eye Institute, Cleveland, Ohio, USA.
52
National Eye Institute, US National Institutes of Health, Bethesda, Maryland,
USA.
53
Department of Genetics, Case Western Reserve University, Cleveland, Ohio, USA.
54
Department of Clinical and Molecular Ophthalmogenetics, Netherlands
Institute of Neurosciences (NIN; an Institute of the Royal Netherlands Academy of Arts and Sciences (KNAW), Amsterdam, The Netherlands.
55
Centre for Population
Health Sciences, University of Edinburgh, Edinburgh, UK.
56
Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University
of Edinburgh, Edinburgh, UK.
57
Faculty of Medicine, University of Split, Split, Croatia.
58
Department of Ophthalmology, Sisters of Mercy University Hospital, Zagreb,
Croatia.
59
Princess Alexandra Eye Pavilion, Edinburgh, UK.
60
Clinic for General and Interventional Cardiology, University Heart Center Hamburg, Hamburg, Germany.
61
Netherlands Consortium for Healthy Ageing, Netherlands Genomics Initiative, The Hague, The Netherlands.
62
Department of Clinical Genetics, Erasmus Medical
Center, Rotterdam, The Netherlands.
63
Department of Clinical Genetics, Academic Medical Center, Amsterdam, The Netherlands.
64
Department of Ophthalmology,
Academic Medical Center, Amsterdam, The Netherlands.
65
Department of Statistics and Applied Probability, National University of Singapore, Singapore.
66
Institute of
Ophthalmology, Moorfields Eye Hospital, London, UK.
67
Department of Ophthalmology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
68
These authors
contributed equally to this work.
69
These authors jointly directed this work. Correspondence should be addressed to C.C.W.K. (c.c.w.klaver@erasmusmc.nl).
L E T T E R S