Susceptibility loci for intracranial aneurysm in European and Japanese populations.
ABSTRACT Stroke is the world's third leading cause of death. One cause of stroke, intracranial aneurysm, affects approximately 2% of the population and accounts for 500,000 hemorrhagic strokes annually in mid-life (median age 50), most often resulting in death or severe neurological impairment. The pathogenesis of intracranial aneurysm is unknown, and because catastrophic hemorrhage is commonly the first sign of disease, early identification is essential. We carried out a multistage genome-wide association study (GWAS) of Finnish, Dutch and Japanese cohorts including over 2,100 intracranial aneurysm cases and 8,000 controls. Genome-wide genotyping of the European cohorts and replication studies in the Japanese cohort identified common SNPs on chromosomes 2q, 8q and 9p that show significant association with intracranial aneurysm with odds ratios 1.24-1.36. The loci on 2q and 8q are new, whereas the 9p locus was previously found to be associated with arterial diseases, including intracranial aneurysm. Associated SNPs on 8q likely act via SOX17, which is required for formation and maintenance of endothelial cells, suggesting a role in development and repair of the vasculature; CDKN2A at 9p may have a similar role. These findings have implications for the pathophysiology, diagnosis and therapy of intracranial aneurysm.
- SourceAvailable from: ncbi.nlm.nih.gov[show abstract] [hide abstract]
ABSTRACT: Evidence supports a substantial genetic contribution to the risk of intracranial aneurysm (IA). The purpose of this study was to identify chromosomal regions likely to harbor genes that contribute to the risk of IA. Multiplex families having at least 2 individuals with "definite" or "probable" IA were ascertained through an international consortium. First-degree relatives of individuals with IA who were at increased risk of an IA because of a history of hypertension or present smoking were offered cerebral magnetic resonance angiography. A genome screen was completed using the Illumina 6K SNP system, and the resulting data from 192 families, containing 1155 genotyped individuals, were analyzed. Narrow and broad disease definitions were used when testing for linkage using multipoint model-independent methods. Ordered subset analysis was performed to test for a gene x smoking (pack-years) interaction. The greatest evidence of linkage was found on chromosomes 4 (LOD=2.5; 156 cM), 7 (LOD=1.7; 183 cM), 8 (LOD=1.9; 70 cM), and 12 (LOD=1.6; 102 cM) using the broad disease definition. Using the average pack-years for the affected individuals in each family, the genes on chromosomes 4 (LOD=3.5; P=0.03), 7 (LOD=4.1; P=0.01) and 12 (LOD=3.6; P=0.02) all appear to be modulated by the degree of smoking in the affected members of the family. On chromosome 8, inclusion of smoking as a covariate did not significantly strengthen the linkage evidence, suggesting no interaction between the loci in this region and smoking. We have detected possible evidence of linkage to 4 chromosomal regions. There is potential evidence for a gene x smoking interaction with 3 of the loci.Stroke 06/2008; 39(5):1434-40. · 6.16 Impact Factor
- [show abstract] [hide abstract]
ABSTRACT: The mechanisms by which bone marrow (BM)-derived stem cells might contribute to angiogenesis and the origin of neovascular endothelial cells (ECs) are controversial. Neovascular ECs have been proposed to originate from VEGF receptor 2-expressing (VEGFR-2+) stem cells mobilized from the BM by VEGF or tumors, and it is thought that angiogenesis and tumor growth may depend on such endothelial precursors or progenitors. We studied the mobilization of BM cells to circulation by inoculating mice with VEGF polypeptides, adenoviral vectors expressing VEGF, or tumors. We induced angiogenesis by syngeneic melanomas, APCmin adenomas, adenoviral VEGF delivery, or matrigel plugs in four different genetically tagged universal or endothelial cell-specific chimeric mouse models, and subsequently analyzed the contribution of BM-derived cells to endothelium in a wide range of time points. To study the existence of circulating ECs in a nonmyeloablative setting, pairs of genetically marked parabiotic mice with a shared anastomosed circulatory system were created. We did not observe specific mobilization of VEGFR-2+ cells to circulation by VEGF or tumors. During angiogenesis, abundant BM-derived perivascular cells were recruited close to blood vessel wall ECs but did not form part of the endothelium. No circulation-derived vascular ECs were observed in the parabiosis experiments. Our results show that no BM-derived VEGFR-2+ or other EC precursors contribute to vascular endothelium and that cancer growth does not require BM-derived endothelial progenitors. Endothelial differentiation is not a typical in vivo function of normal BM-derived stem cells in adults, and it has to be an extremely rare event if it occurs at all.Proceedings of the National Academy of Sciences 06/2008; 105(18):6620-5. · 9.74 Impact Factor
- [show abstract] [hide abstract]
ABSTRACT: Genome-wide association (GWA) studies have identified multiple loci at which common variants modestly but reproducibly influence risk of type 2 diabetes (T2D). Established associations to common and rare variants explain only a small proportion of the heritability of T2D. As previously published analyses had limited power to identify variants with modest effects, we carried out meta-analysis of three T2D GWA scans comprising 10,128 individuals of European descent and approximately 2.2 million SNPs (directly genotyped and imputed), followed by replication testing in an independent sample with an effective sample size of up to 53,975. We detected at least six previously unknown loci with robust evidence for association, including the JAZF1 (P = 5.0 x 10(-14)), CDC123-CAMK1D (P = 1.2 x 10(-10)), TSPAN8-LGR5 (P = 1.1 x 10(-9)), THADA (P = 1.1 x 10(-9)), ADAMTS9 (P = 1.2 x 10(-8)) and NOTCH2 (P = 4.1 x 10(-8)) gene regions. Our results illustrate the value of large discovery and follow-up samples for gaining further insights into the inherited basis of T2D.Nature Genetics 06/2008; 40(5):638-45. · 35.21 Impact Factor
Susceptibility loci for intracranial aneurysm in European
and Japanese populations
Kaya Bilguvar1,2, Katsuhito Yasuno3, Mika Niemela ¨4, Ynte M Ruigrok5, Mikael von und zu Fraunberg6,
Cornelia M van Duijn7, Leonard H van den Berg5, Shrikant Mane8, Christopher E Mason2,9, Murim Choi2,
Emı ´lia Gaa ´l1,2,4, Yasar Bayri1,2, Luis Kolb1,2, Zulfikar Arlier1,2, Sudhakar Ravuri8, Antti Ronkainen6,
Atsushi Tajima3, Aki Laakso4, Akira Hata10, Hidetoshi Kasuya11, Timo Koivisto6, Jaakko Rinne6,
Juha O¨hman12, Monique M B Breteler7, Cisca Wijmenga13,14, Matthew W State2,9, Gabriel J E Rinkel5,
Juha Hernesniemi4, Juha E Ja ¨a ¨skela ¨inen6, Aarno Palotie15,16, Ituro Inoue3, Richard P Lifton2,17&
Murat Gu ¨nel1,2
Stroke is the world’s third leading cause of death. One cause of
stroke, intracranial aneurysm, affects B2% of the population
and accounts for 500,000 hemorrhagic strokes annually in mid-
life (median age 50), most often resulting in death or severe
neurological impairment1. The pathogenesis of intracranial
aneurysm is unknown, and because catastrophic hemorrhage
is commonly the first sign of disease, early identification is
essential. We carried out a multistage genome-wide
association study (GWAS) of Finnish, Dutch and Japanese
cohorts including over 2,100 intracranial aneurysm cases
and 8,000 controls. Genome-wide genotyping of the European
cohorts and replication studies in the Japanese cohort
identified common SNPs on chromosomes 2q, 8q and 9p that
show significant association with intracranial aneurysm with
odds ratios 1.24–1.36. The loci on 2q and 8q are new, whereas
the 9p locus was previously found to be associated with
arterial diseases, including intracranial aneurysm2–5.
Associated SNPs on 8q likely act via SOX17, which is
required for formation and maintenance of endothelial cells6–8,
suggesting a role in development and repair of the vasculature;
CDKN2A at 9p may have a similar role9. These findings have
implications for the pathophysiology, diagnosis and therapy
of intracranial aneurysm.
Siblings of intracranial aneurysm probands are at Bfourfold increased
risk of hemorrhage from intracranial aneurysm, suggesting a genetic
component to risk10. Genome-wide linkage studies of familial cases11
and rare apparently mendelian kindreds have not thus far identified
robustly replicable loci, and no underlying mutations have been
identified12–14. Similarly, examination of candidate genes in small
case-control studies has failed to produce replicable results12.
These considerations motivate the use of GWAS to identify com-
mon variants that contribute to intracranial aneurysm. We carried out
a multistage intracranial aneurysm GWAS in three cohorts: a Finnish
cohort of 920 cases and 985 controls, a Dutch cohort of 781 cases and
6,424 controls and a Japanese cohort of 495 cases and 676 controls (see
Supplementary Methods online).
The study design consisted of a first stage of genome-wide geno-
typing of the European cohorts on the Illumina platform, careful
matching of cases and controls, and identification of intervals
harboring SNPs that surpassed a significance threshold of 5 ? 10?7
for association with intracranial aneurysm2. This discovery phase had
80% power to detect common alleles that confer a genotype relative
risk (GRR) of 1.31 and 50% power to detect a GRR of 1.25 (assuming
an additive model in log-odds scale). Replication of association
of SNPs in these intervals was tested in the Japanese cohort, setting
P o 0.05 for significant replication. The replication study had
Received 7 July; accepted 18 August; published online 9 November 2008; doi:10.1038/ng.240
1Departments of Neurosurgery, Neurobiology and2Genetics, Yale Program on Neurogenetics, Yale Center for Human Genetics and Genomics, Yale University School of
Medicine, New Haven, Connecticut 06510, USA.3Division of Molecular Life Science, School of Medicine, Tokai University, Shimokasuya 143, Isehara, Kanagawa
259-1193, Japan.4Department of Neurosurgery, Helsinki University Central Hospital, Helsinki, P.O. Box 266, FI-00029 HUS, Finland.5Department of Neurology,
Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands.6Department of Neurosurgery, Kuopio University
Hospital, Kuopio FI-70211, Finland.7Genetic Epidemiology Unit, Department of Epidemiology and Biostatistics and Department of Clinical Genetics, Erasmus
Medical Center, 2040, 3000 CA Rotterdam, The Netherlands.8Keck Foundation Biotechnology Resource Laboratory, Yale University, 300 George Street, New Haven,
Connecticut 06510, USA.9Child Study Center, Yale University School of Medicine, New Haven, Connecticut 06510, USA.10Department of Public Health, School of
Medicine, Chiba University, Chiba 260-8670, Japan.11Department of Neurosurgery, Medical Center East, Tokyo Women’s University, Tokyo 116-8567 , Japan.
12Department of Neurosurgery, Tampere University Hospital, 33521 Tampere, Finland.13Complex Genetics Section, Department of Biomedical Genetics, University
Medical Center Utrecht, 3508 AB Utrecht, The Netherlands.14Department of Genetics, University Medical Center Groningen and University of Groningen, 9700 RR
Groningen, The Netherlands.15Biomedicum Helsinki, Research Program in Molecular Medicine, University of Helsinki, 00290 Helsinki, Finland.16Wellcome Trust
Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1HH, UK.17Howard Hughes Medical Institute and Department of Internal Medicine, Yale
University School of Medicine, New Haven, Connecticut 06510, USA. Correspondence should be addressed to R.P.L. (email@example.com) or M.G.
1472VOLUME 40 [ NUMBER 12 [ DECEMBER 2008 NATURE GENETICS
© 2008 Nature Publishing Group http://www.nature.com/naturegenetics
80% and 66% power to replicate SNPs with GRRs of 1.31 and 1.25,
respectively. The utility of using a genetically diverse population for
replication has been demonstrated by recent studies15, thereby extend-
ing association results to a broad segment of the world’s population.
Discovery phase genotypes were processed using rigorous quality
controls; because Dutch controls and some Finnish controls were
genotyped separately on Illumina chips of varying SNP density,
particular attention was paid to ensuring consistent genotyping
performance and excluding nonrandom genotyping error within
and across cohorts (Supplementary Methods and Supplementary
Tables 1 and 2 online). To control for population stratification, we
genetically matched cases and controls from each cohort16, resulting in
a dataset in which cases and controls are similarly distributed along
axes of significant principal components (Supplementary Table 1).
We tested for association between each SNP and intracranial
aneurysm by using the Cochran-Armitage trend test in each cohort
and combined the results using the Mantel extension test. The
distribution of test statistics for association of SNPs with intracranial
aneurysm in the combined cohort is shown in Figure 1a. The genomic
inflation factor (l) was 1.043 and 1.136 for the Finnish and Dutch,
respectively, and 1.114 combined, indicating well-matched popula-
tions17(Fig. 1a); further logistic regression including principal com-
ponents as covariates2did not significantly change l (Supplementary
Fig. 1 online), nor did exclusion of SNPs with call rates o99% in any
case or control cohort (Supplementary Methods); in contrast,
because genomic inflation factor increases with sample size18, the
large Dutch control sample was a major contributor to l (Supple-
mentary Methods). The association results reveal a number of SNPs
whose P values exceed those expected under the null hypothesis; these
persist after correction for l (Fig. 1b). The P values across each
chromosome are shown in Figure 1c. Four intervals (on 1q, 2q, 8q
and 9p) harbored SNPs that surpassed the threshold for genome-wide
significance; these include multiple SNPs with correlated P values and
comprise 15 of the 16 SNPs with P o 10?6(Fig. 1c). Associated SNPs
in each interval have very high call rates in every cohort and none
violate HWE in any cohort (Supplementary Table 2). The first three
loci have not previously shown association with intracranial aneurysm
or other diseases, whereas SNPs on 9p are in the block of linkage
disequilibrium (LD) that has previously been shown to be associated
with myocardial infarction2–4, abdominal aortic aneurysm and intra-
cranial aneurysm5. Both Finnish and Dutch cohorts contributed to the
significance of each locus, the risk alleles were identical and their odds
ratios were not significantly different between cohorts (Table 1).
To attempt to replicate these four loci, we genotyped 15 SNPs from
these intervals in the Japanese cohort (Supplementary Tables 2 and 3
online). Eight of the 15 SNPs showed significant association with
intracranial aneurysm; these included SNPs on 2q, 8q and 9p (Table 1).
At each locus, SNPs in strong LD in the Japanese sample showed highly
correlated P values (Fig. 2). For associated SNPs, risk alleles in Japan
were identical to and showed similar odds ratios to those found in
Europe (Table 1 and Supplementary Table 3). Using the Mantel
extension test to combine data from all three cohorts, we found the
following P values and odds ratios for the SNPs showing the strongest
evidence for association at each locus: 2q, P ¼ 4.4 ? 10?8(odds ratio
(OR) ¼ 1.24); 8q, P ¼ 1.4 ? 10?10(OR ¼ 1.36); 9p, P ¼ 1.4 ? 10?10
(OR ¼ 1.29) (Table 1). No locus showed significant deviation from an
additive model (log-odds scale) (Supplementary Table 3).
We examined the distributions of P values in each significant
interval. At 2q, association in Europe lies within a large block of LD
(197.8–198.6 Mb; Fig. 2 and Supplementary Table 4 online). In Asian
subjects, this segment is divided into two smaller blocks of LD
and the association seen in Japan is confined to SNPs in the more
telomeric block (198.2–198.5 Mb). This interval contains four known
genes; the two most strongly associated SNPs, rs700651 and rs700675,
lie in introns of adjacent genes, BOLL and PLCL1. PLCL1 is of
interest because it has significant homology to phospholipase C,
which lies downstream of VEGFR2 signaling19. VEGFR2 is a
marker of endothelial progenitor cells and has a role in central nervous
The LD structure at 8q is also of interest (Fig. 2 and Supplementary
Table 4). SNP rs10958409 shows the most significant association;
SNPs in high LD with rs10958409 show correlated P values. In
addition, however, rs9298506, which lies 110 kb distally and shows
virtually no LD with rs10958409 (r2¼ 0.004 in European HapMap
subjects21, 0.004 in Finnish cases and 0.0005 in Dutch cases) none-
theless also revealed significant association in Europeans; adjacent
SNPs in LD showed correlated P values. This observation suggests the
presence of two independent risk alleles. A conditional test of
association demonstrated that after accounting for the association
with rs9298506, rs10958409 still showed significant association with
intracranial aneurysm (and vice versa), consistent with two risk loci
(Supplementary Table 4). The Japanese cohort replicated association
at rs10958409, but not rs9298506, despite having had 88% power to
detect association of this latter SNP (Supplementary Table 3). Further
work will be required to determine whether the European association
with rs9298506 is a true positive result. This 8q interval contains a
051015 2005 1015 20
Figure 1 Genome-wide association of SNPs with intracranial aneurysm in
the combined European cohort. (a) Quantile-quantile plot of the observed
w2values derived from the Mantel-extension test statistics versus the
expected w2distribution. The solid line represents concordance of observed
and expected values. The slope of the dashed line represents the genomic
inflation factor (l ¼ 1.11). (b) The plot of expected and observed w2values
for association of SNPs with intracranial aneurysm after correction for the
genomic inflation factor (l ¼ 1.0). Significant deviation from the expected
values suggests association of these SNPs with intracranial aneurysm
phenotype. (c) The –log10of uncorrected P values for association of each
SNP and intracranial aneurysm is plotted according to its physical position
on successive chromosomes. Green dots indicate SNPs yielding P values
o1 ? 10?5, and red dots denote SNPs that surpass a significance level
of 5 ? 10?7.
NATURE GENETICS VOLUME 40 [ NUMBER 12 [ DECEMBER 20081473
© 2008 Nature Publishing Group http://www.nature.com/naturegenetics
Table 1 Summary of results for five SNPs that characterize the association with intracranial aneurysm on chromosomes 2, 8 and 9
Odds ratio (95% CI)
4.4 ? 10?4
1.6 ? 10?4
2.5 ? 10?7
5.8 ? 10?7
5.6 ? 10?3
5.0 ? 10?4
8.9 ? 10?6
4.4 ? 10?8
1.4 ? 10?3
1.4 ? 10?7
1.6 ? 10?9
1.4 ? 10?10
4.6 ? 10?7
2.3 ? 10?4
8.6 ? 10?10
1.8 ? 10?9
2.8 ? 10?3
9.5 ? 10?7
1.5 ? 10?8
1.4 ? 10?10
SNPs that replicate with P o 0.05 in the Japanese cohort are italicized. Position shown is from NCBI build 36 coordinates. Risk allele is indexed to the forward strand of NCBI build 36.
aThe Cochran-Armitage trend test P value for cohorts from Finland, Netherlands and Japan, respectively, and the Mantel extension test (uncorrected for l) P value for combined cohorts.bP value of the test of heterogeneity in effect size
among populations.cP value of the test of deviation from an additive model. PAF, population attributable fraction. RRF, recurrence risk fraction attributable to each SNP, assuming the overall sibling recurrence risk of 4 (ref. 10).
1474VOLUME 40 [ NUMBER 12 [ DECEMBER 2008 NATURE GENETICS
© 2008 Nature Publishing Group http://www.nature.com/naturegenetics
single gene, SOX17, which lies between these two association peaks,
43 kb from rs10958409 and 64 kb from rs9298506. The next closest
genes lie 201 kb distal and 266 kb proximal to rs10958409. Sox17 has
an important role in formation and maintenance of the endothelium
Finally, SNPs on 9p that showed association with intracranial
aneurysm (22.07–22.10 Mb) (Fig. 2 and Supplementary Table 4)
were in LD with SNPs that have previously shown association with
multiple arterial diseases2–4. Adjacent SNPs that are associated with
type 2 diabetes mellitus22–24showed no significant association with
intracranial aneurysm. The strongest association was with rs1333040,
which lies 74 kb from the 5¢ end of CDKN2B and 88 kb from
CDKN2A. These genes encode the cyclin-dependent kinase inhibitors
p15INK4band p16INK4a, as well as ARF, a regulator of p53 activity. In
addition, a non-protein-coding transcript (ANRIL) lies within this
interval25. Among these, p16INK4ais of particular interest (see below).
To determine whether the effects of these loci are influenced by
known risk factors, we examined the odds ratios of the most
significant allele at each locus after partitioning cases by gender, family
history of intracranial aneurysm, age (older half versus younger) and
ruptured versus unruptured aneurysm. The results showed no signi-
ficant difference in odds ratios after any of these partitions, suggesting
independent contributions to risk (Supplementary Table 5 online).
Finally, to assess the combined effects of the three loci, we defined
each subject’s risk score by summing the logarithm of the odds ratio
for each risk allele they harbor as determined in each cohort. The
observed intracranial aneurysm risk showed a significant linear
relationship with risk score in each cohort, with a more than threefold
increase from lowest to highest strata (Table 2 and Supplementary
Table 6 online).
This study provides the first results of a large GWAS of intracranial
aneurysm or stroke. Three significant loci have been identified. These
results cannot be explained by nonrandom genotyping error or
population stratification and are robust to alternative analyses (Sup-
plementary Fig. 1). We calculate that these loci collectively account for
38–46% of the population-attributable fraction of intracranial aneur-
ysm and 2.3–3.8% of the sibling recurrence risk (Table 1). Additional
common variants are likely to have a role in intracranial aneurysm, as
the study was not well powered to find loci with GRR o1.25. In
addition, population-specific effects were not considered in this study
design. Given the risk allele frequencies and odds ratios of the
identified loci, future replication cohorts will require B900 to 1,600
cases and controls to have 80% power for replication (a ¼ 0.05).
After genomic control correction and exclusion of SNPs at the four
top loci, 37 SNPs remained with P values less than 10?4(28 are
expected by chance). Some of these may prove to be true risk alleles as
additional cohorts are evaluated, as has occurred with type 2 dia-
betes26. In addition, rare variants with larger effects at these same loci
may also contribute to the occurrence of intracranial aneurysm27,28.
Intracranial aneurysms predominate at arterial branch points and
sites of shear stress, locations that incur endothelial damage. Vascular
injury mobilizes bone marrow–derived cells that localize to these sites
and contribute to repair29,30. SOX17, a member of the Sry-related
HMG box transcription factor family, is of particular interest because
it is required for both endothelial formation and maintenance6–8.
Sox17 plays a key role in the generation and maintenance of fetal and
neonatal stem cells of both hematopoietic and endothelial lineages8
and is expressed in adult endothelium6. Sox17?/?mice show multiple
vascular abnormalities7; moreover, whereas Sox18?/?mice are normal,
Sox18?/?;Sox17+/?mice show defective endothelial sprouting and
CHB + JPT
CHB + JPT
CHB + JPT
Chromosome 2q33.1 Chromosome 8q11.12–12.1Chromosome 9p21.3
Position (Mb)Position (Mb)
199199.5 55.255.4 55.6 55.856 21.922.1 22.2 22
Figure 2 Regional association plots and linkage disequilibrium structure. (a–c) The –log10of the P value for association of each SNP and intracranial
aneurysm in discovery phase across segments of 2q (a), 8q (b) and 9q (c) are shown as small diamonds (using NCBI build 36 for map locations). Fifteen
SNPs that were genotyped in the Japanese replication cohort are shown as triangles that show the combined (discovery + replication) P values: blue triangles
represent SNPs that demonstrate replication in the Japanese cohort with P o 0.05, and gray triangles denote SNPs with P 4 0.05 in the replication study.
SNPs with the most significant P values in each interval in the combined analysis are marked with their SNP IDs. Known transcripts (RefSeq database) are
represented as horizontal bars at the bottom of each panel. Population-specific LD structures based on D¢ are shown for the HapMap European (CEU) and
Asian (CHB + JPT) cohorts21. The results demonstrate that on chromosome 2, SNPs spanning an B800-kb interval are in strong LD in the CEU population
and show evidence of association with intracranial aneurysm in the Finnish and Dutch cohorts. In Asia, this segment is broken into two smaller blocks of LD
that are not strongly correlated with one another, and significant association with intracranial aneurysm in Japanese cohort is seen only for the telomeric
segment. For chromosome 8, SNPs in two blocks that are not in significant LD with one another both show significant association with intracranial aneurysm
in the European cohort; only SNPs located within the proximal block replicate in Japan. Cohort-specific r2values among all SNPs genotyped in the
replication studies are shown in Supplementary Table 4.
NATURE GENETICS VOLUME 40 [ NUMBER 12 [ DECEMBER 2008 1475
© 2008 Nature Publishing Group http://www.nature.com/naturegenetics
vascular remodeling6. Similarly, p16INK4ahas a role in regulation of
stem (progenitor) cell populations, including bone marrow–derived
cells of the vasculature9. These considerations suggest that intracranial
aneurysm may result from defective stem (progenitor) cell–mediated
vascular development and/or repair.
Finally, these findings have implications for identification of indi-
viduals with intracranial aneurysm before morbid events. The odds
ratio of intracranial aneurysm increases greater than threefold in
subjects with the highest versus the lowest risk (Table 2 and Supple-
mentary Table 6). Although we caution that further work is required,
these findings advance the potential for preclinical diagnosis by
combined assessment of inherited susceptibility with previously estab-
lished risk factors.
Cohorts. The study protocol was approved by the Yale Human Investigation
Committee (HIC protocol 7680). In all cases, the diagnosis of intracranial
aneurysm was made with computerized tomography angiogram, magnetic
resonance angiogram or cerebral digital subtraction angiogram and confirmed
at surgery, when applicable. Rupture of aneurysm was defined by identification
of acute subarachnoid hemorrhage (via computerized tomography or magnetic
resonance imaging) from a proven aneurysm. Cases with a first-degree relative
with intracranial aneurysm were considered familial, and other cases were
Three cohorts from independent studies in Finland, The Netherlands and
Japan were collected and all participants provided informed consent. There
were 960 Finnish cases and 1,017 controls; 786 Dutch cases and 6,424 controls;
and 495 Japanese cases and 676 controls. Japanese controls were screened for
not harboring intracranial aneurysm.
Genotyping and SNP quality control. Genome-wide genotyping in European
cohorts was done on the Illumina platform according to the manufacturer’s
protocol (Illumina). We genotyped subjects on either the CNV370-Duo,
HumanHap300 or HumanHap550 chips. SNPs shared across all platforms
(n ¼ 314,125) were extracted. We applied prespecified criteria to exclude
samples and SNPs that performed poorly as well as samples that could not be
genetically well matched (Supplementary Table 1 and Supplementary Meth-
ods). The overall median genotype call rate was 99.7% and the mean
heterozygosity of all SNPs was 35%. Seventy-two duplicate pairs of samples
were genotyped and showed 99.91% genotype identity. We carried out detailed
Table 2 Increased intracranial aneurysm risk with increased risk score based on genotypes for rs700651, rs10958409 and rs133040
Japan Netherlands Finland
No. of risk
Average risk score
0 or 1 0.14/0.080.2310.3/0.21 0.221 0.32/0.21 0.171
2 0.28/0.211.290.36/0.29 1.130.34/0.34 1.47
5 or 60.06/0.100.02/0.030.03/0.02
OR (95% CI)b
3.3 ? 10?7
8.4 ? 10?16
7.8 ? 10?8
Individuals with non-missing genotypes for all six alleles were included in the analysis.
aP value for linear relationship of risk score and logarithm of ORs (complete data set is listed in Supplementary Table 6).bIncrease in odds ratio per one unit change in risk score.
analysis of the performance of SNPs across cohorts and platforms to ensure
that significant associations observed were not due to differences in SNP
performance (Supplementary Table 2).
Cryptic relatedness. We determined the identity by state (IBS) similarity and
estimated the degree of relatedness for each pair of samples in the GWAS
(Supplementary Methods) and excluded inferred first- and second-degree
relatives (Supplementary Table 1).
Analysis of population structure. In order to identify population outliers and
cases whose genetic ancestry cannot be properly matched to controls (and vice
versa), we used the Genetic Matching (GEM) method described previously16
based on principal component analysis (PCA). After this matching process,
three significant principal components remained in the Finnish cohort and
none in the Dutch cohort, as previously observed (Supplementary Methods).
After quality control and analysis of population structure, there remained 874
cases and 944 controls in the Finnish cohort and 706 cases and 5,332 controls in
the Dutch cohort. Among the Finnish cases, 57% were female; 73% had suffered
ruptured aneurysm and 43% had positive family history; the median age at
diagnosis was 50 years (those with rupture 49 years versus those without rupture
52 years). In the Dutch cohort, 69% were female, 92% had ruptured aneurysm,
15% had a positive family history and the median age was 49 years.
SNP association analysis. To test for association of each SNP with intracranial
aneurysm, we assumed an additive (in log-odds scale) model. We used the
Cochran-Armitage trend test for each cohort. For the combined sample of
European descent or of European and Japanese cohorts, we used the Mantel
extension test (Supplementary Methods).
We calculated the per-allele and genotype-specific ORs and their 95%
confidence intervals by fitting 1-d.f. and 2-d.f. logistic models, respectively.
We assessed heterogeneity of ORs among populations by considering the
likelihood ratios of a logistic model with population by genotype interaction
term(s) versus a linear model without the interaction term(s) and used a
P value o0.05 as evidence of significant heterogeneity (Supplementary
Table 3). To evaluate the degree of overdispersion of test statistics, we calculated
the genomic inflation factor (l) for each statistical test by the ratio of the mean
of the lower 90% of observed test statistics to that of the expected w2values17.
We applied the genomic control method to correct for l (Fig. 1b) and then
compared a pairwise plot of P values for each SNP in the trend and corrected
tests to determine the potential effect of any residual population stratification
(Supplementary Fig. 1a,b and Supplementary Methods).
We also examined the validity of the assumption of additivity (in log-odds
scale) in the association tests by comparing likelihood ratios assuming
1476VOLUME 40 [ NUMBER 12 [ DECEMBER 2008 NATURE GENETICS
© 2008 Nature Publishing Group http://www.nature.com/naturegenetics
alternative models of dominance and rejected additivity for P o 0.05 (ref. 2
and Supplementary Table 3).
For each chromosome segment showing significant association with intra-
cranial aneurysm, we investigated whether more than one SNP had an
independent marginal effect on intracranial aneurysm by the Mantel extension
test conditioned on genotypes for SNPs within each interval (Supplementary
To assess the robustness of our GWAS results, we also performed a weighted
Z-score test and found that the results of this alternative analysis were highly
correlated with the results of the Mantel extension test (Supplementary Fig. 1c).
Replication study in Japanese cohort. For the Japanese replication study,
allelic discrimination assays were done with 15 SNPs on the Sequenom iPLEX
genotyping platform according to the manufacturer’s protocol. For SNPs that
showed significant P values, genotypes were repeated and P values confirmed
on the TaqMan platform (Applied Biosystems). Association tests were done as
described above, using P ¼ 0.05 (in the Cochran-Armitage trend test with the
same allele found associated in Europe) as the threshold for significance
(Supplementary Table 3).
Subset analysis. For SNPs with the most significant P values we investigated
whether the association results were affected by potential confounding variables
such as rupture status, family history or gender. We compared genotype
distributions of cases stratified by these variables using the trend test (Supple-
mentary Table 5).
Population-attributable fraction and proportion of genetic variance attri-
butable to SNPs. We investigated two risk measures based on replicated SNPs:
the population attributable fraction (PAF) and the proportion of the sibling
recurrence risk attributable to a SNP (‘recurrence risk fraction’) as previously
described (Table 1 and Supplementary Methods). For these calculations we
assumed intracranial aneurysm population prevalence of 2% and lsibof 4
(ref. 10). The combined contribution of SNPs was obtained by assuming the
multiplicative model (Supplementary Methods).
Cumulative effects of risk alleles. We analyzed the cumulative effects of the
risk alleles at the most significant SNP at 2q, 8q and 9p (rs700651, rs10958409
and rs1333040) by calculating the risk score for each individual by the weighted
sum of the number of risk alleles as defined by
Risk score ¼
where c[i] is the logarithm of the calculated per-allele odds ratio at each locus
and n[i] is the number of risk alleles at the same locus. We then assessed the
risk score for each of the 27 possible three-locus genotypes in each cohort
(Supplementary Table 6). We fitted a simple linear logistic model with an
additive effect (on log-odds scale) for each cohort and performed a likelihood-
ratio test. For display purposes, the 27 strata of Supplementary Table 6 are
compressed into 5 strata shown in Table 2 according to the absolute number of
risk alleles, which closely parallels the risk score.
Note: Supplementary information is available on the Nature Genetics website.
We are grateful to the participants who made this study possible. We thank
A. Chamberlain, O. To ¨rnwall, M. Alalahti, K. Helin, S. Malin and J. Budzinack
for their technical help. This study was supported by the Yale Center for Human
Genetics and Genomics and the Yale Program on Neurogenetics, the US National
Institutes of Health grants R01NS057756 (M.G.) and U24 NS051869 (S.M.) and
the Howard Hughes Medical Institute (R.P.L.). C.E.M. and M.W.S. are supported
by a gift from the Lawrence Family and Y.M.R. by the Dr E. Dekker program of
The Netherlands Heart Foundation (2005T014). K.Y. and I.I. were supported by
the Core Research for Evolutional Science and Technology, Japan Science and
Cohort ascertainment, characterization and DNA preparation: M.N., E.G., A.L.,
A.P., J.O¨. and J.H. (Helsinki); M.v.u.z.F., A.R., T.K., J.R., A.P. and J.E.J. (Kuopio);
Y.M.R., L.H.v.d.B., C.W. and G.J.E.R. (Utrecht); C.M.v.D. and M.M.B.B.
(Rotterdam) and A.T., A.H., H.K. and I.I. (Japan). Genotyping: K.B., Y.B., L.K.,
Z.A., S.R., R.P.L., M.G. and S.M. Study design and analysis plan: R.P.L. and
M.G. Data management and informatics: C.E.M., K.B., M.W.S. and M.G.
Statistical analysis: K.Y., K.B., I.I., M.C., R.P.L. and M.G. Writing team: K.B., K.Y.,
M.W.S., M.G. and R.P.L.
Published online at http://www.nature.com/naturegenetics/
Reprints and permissions information is available online at http://npg.nature.com/
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