1. health and fitness
2. disease

LETTERS
© 2009 Nature America, Inc. All rights reserved.
Sequence variants affecting eosinophil numbers associate
with asthma and myocardial infarction
Daniel F Gudbjartsson*1, Unnur S Bjornsdottir1,2, Eva Halapi1, Anna Helgadottir1, Patrick Sulem1,
Gudrun M Jonsdottir1, Gudmar Thorleifsson1, Hafdis Helgadottir1, Valgerdur Steinthorsdottir1,
Hreinn Stefansson1, Carolyn Williams3–5, Jennie Hui6,7, John Beilby6,8, Nicole M Warrington9,
Alan James10,11, Lyle J Palmer9, Gerard H Koppelman12, Andrea Heinzmann13, Marcus Krueger13,
H Marike Boezen14, Amanda Wheatley15, Janine Altmuller16, Hyoung Doo Shin17,18, Soo-Taek Uh19,
Hyun Sub Cheong19, Brynja Jonsdottir20, David Gislason20, Choon-Sik Park21, Linda M Rasmussen22,
Celeste Porsbjerg22, Jakob W Hansen22, Vibeke Backer22, Thomas Werge23, Christer Janson24,
Ulla-Britt Jönsson24, Maggie C Y Ng25, Juliana Chan25, Wing Yee So25, Ronald Ma25, Svati H Shah26,
Christopher B Granger26, Arshed A Quyyumi27, Allan I Levey27, Viola Vaccarino27, Muredach P Reilly28,
Daniel J Rader28, Michael J A Williams29, Andre M van Rij29, Gregory T Jones29, Elisabetta Trabetti30,
Giovanni Malerba30, Pier Franco Pignatti30, Attilio Boner31, Lydia Pescollderungg32, Domenico Girelli33,
Oliviero Olivieri33, Nicola Martinelli33, Bjorn R Ludviksson2,20, Dora Ludviksdottir20,
Gudmundur I Eyjolfsson34, David Arnar2,20, Gudmundur Thorgeirsson2,20, Klaus Deichmann13,
Philip J Thompson3–5, Matthias Wjst35,36, Ian P Hall16, Dirkje S Postma37, Thorarinn Gislason2,20,
Jeffrey Gulcher1, Augustine Kong1, Ingileif Jonsdottir1,2,20, Unnur Thorsteinsdottir1,2 & Kari Stefansson1,2
Eosinophils are pleiotropic multifunctional leukocytes involved
in initiation and propagation of inflammatory responses and
thus have important roles in the pathogenesis of inflammatory
diseases. Here we describe a genome-wide association scan for
sequence variants affecting eosinophil counts in blood of 9,392
Icelanders. The most significant SNPs were studied further
in 12,118 Europeans and 5,212 East Asians. SNPs at 2q12
(rs1420101), 2q13 (rs12619285), 3q21 (rs4857855), 5q31
(rs4143832) and 12q24 (rs3184504) reached genome-wide
significance (P ¼ 5.3 1014, 5.4 1010, 8.6 1017,
1.2 1010 and 6.5 1019, respectively). A SNP at IL1RL1
associated with asthma (P ¼ 5.5 1012) in a collection of ten
different populations (7,996 cases and 44,890 controls). SNPs
at WDR36, IL33 and MYB that showed suggestive association
with eosinophil counts were also associated with atopic asthma
(P ¼ 4.2 106, 2.2 105 and 2.4 104, respectively).
We also found that a nonsynonymous SNP at 12q24, in SH2B3,
associated significantly (P ¼ 8.6 108) with myocardial
infarction in six different populations (6,650 cases and
40,621 controls).
Eosinophils are pleiotropic multifunctional leukocytes that release
from their granules compounds including many potent inducers of
inflammatory and immune responses observed in asthma, eczema,
rhinitis and other inflammatory diseases1. Eosinophils are often the
dominant inflammatory cell type present in the bronchi of asthmatics2. As such, we carried out a genome-wide association (GWA)
scan for sequence variants associating with the number of blood
eosinophils and then assessed the association of these variants with
asthma and other inflammation-related diseases (Fig. 1).
We analyzed genome-wide SNP data from 9,392 Icelanders with
blood eosinophil counts and typed with the Illumina 317K SNP set.
The analysis was done by regression of mean standardized eosinophil
counts on SNP allele counts (Supplementary Methods online; effect
sizes are given in percentages of s.d. units in this paper). After quality
control, 312,179 SNPs remained (see quantile-quantile plot in Supplementary Fig. 1 online), and we selected 32 SNPs, capturing the
signals from the top 55 SNPs of the GWA scan, for follow-up in an
additional 4,458 Icelanders with blood eosinophil counts enriched for
extreme values (Supplementary Tables 1 and 2 and Supplementary
Fig. 2 online). Fifteen of the tested SNPs at ten distinct loci were
chosen for further study in 1,411 individuals from the United States,
387 from Germany, 419 from Sweden, 484 from Italy, 2,619 from The
Netherlands and 2,297 from Australia (Table 1, Supplementary
Tables 1 and 3 and Supplementary Fig. 3 online). Combining the
results from the discovery and follow-up sets, we found variants at five
*A full list of author affiliations appears at the end of the paper.
Received 28 July 2008; accepted 5 January 2009; published online 8 February 2009; doi:10.1038/ng.323
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individuals, 1,958 from Korea and 3,254 from
Hong Kong (Table 1). SNPs at four of the ten
loci replicated nominally in the East Asians.
SNPs at five loci reached threshold
SNPs at three of the remaining six loci had
for genome-wide signifcance
minor allele frequency less than 5% and hence
there was little power to replicate signals for
Assessment of association with ten
other blood parameters (n = 9,392)
these markers.
Icelandic
Icelandic
To determine whether the eosinophileosinophil
genome-wide
Assessment in nine asthma samples
follow-up study
associated
loci were specific to eosinophils,
eosinophil scan
(7,996 cases, 44,890 controls)
(n = 4,458)
(n = 9,392)
we analyzed data on white blood cell differThree SNPs significant, accounting
Select 15 SNPs at
Select 32 SNPs
ential counts, platelet counts and several red
for multiple testing (30 tests)
10 loci with smallest
tagging top 55 SNPs
blood cell parameters for the Icelanders
follow-up P values
Assessment of association
with data on blood eosinophil counts. IgE
with COPD in Iceland
measurements were available for a smaller
(765 cases, 39,376 controls)
subset of individuals. Figure 2 shows an overNo significant association
view of the association of the SNPs identified
through the blood eosinophil count GWA
Assessment of association
Association with MI
with MI in Iceland
validated in six
scan with the blood measurements (see
(2,625 cases,
samples
33,625 controls)
also Supplementary Table 4 online). The
(3,925 cases,
6,996 controls)
sequence variants associating with eosinophil
One SNP suggestive
counts clustered into two groups; those having a broad effect on the majority of the blood
Figure 1 Overview of the study design, implementation and results.
cell types, and those with effect limited to one
or two blood parameters (Fig. 2).
Given the role of eosinophils in the pathogenesis of asthma, we
of ten loci that satisfied our criteria for genome-wide significance
(P o 1.6 107 E 0.05/312,179) and had a consistent direction of tested the 15 SNPs from the ten initial loci identified through the
correlation in the different sample sets. We also examined the effects of blood eosinophil count scan for association with asthma, and
the SNPs correlating with blood eosinophil counts in 5,212 East Asian atopic and nonatopic asthma subphenotypes, in nine sample sets of
© 2009 Nature America, Inc. All rights reserved.
Follow-up of eosinophil association
in Europeans (n = 7,660) and
East Asians (n = 5,212)
Table 1 Results of genome-wide search for SNPs associating with blood eosinophil count and replication effort
SNP
Chr.
Position
Freq.a Gene
Icelandic discovery
Icelandic follow-up
Other European
Combined European
East Asian
(n ¼ 9,392)
(n ¼ 4,458)
(n ¼ 7,660)
(n ¼ 21,510)
(n ¼ 5,212)
Effect
SNPs satisfying the criteria for genome-wide significance
rs1420101[A]c 2
102,324,148 0.41 IL1RL1 6.4
rs12619285[G] 2
rs4857855[T]
3
213,532,290 0.74 IKZF2
6.8
129,743,240 0.82 GATA2
8.3
P
Effectb
2.2 106 10.6
5.1 106 4.1
1.5 106 9.6
P
Effect
8.5 1011 4.4
P
Effect (95% CI)
P
Freq Effect
P
6.4
5.3 1014 0.37 4.8
0.046
7.6 105
(4.7, 8.1)
6.3
5.4 1010 0.36 5.9
0.017
3.6 106 11.0 1.3 107
(4.3, 8.3)
9.4
8.6 1017 0.70 8.4
0.00057
0.024
7.0
0.0064
(7.2, 11.6)
rs4143832[C]
5
131,890,876 0.16 IL5
rs3184504[T]
12 110,368,991 0.38 SH2B3
10.0 4.6 108 12.3
1.0 108 2.0
0.34
7.1
(4.9, 9.2)
1.2 1010 0.17 10.2 0.0039
1.3 108 10.6
8.5 1011 6.6
3.2 105
7.6
(5.9, 9.3)
6.5 1019 0.00d
7.7
SNPs that did not satisfy the criteria for genome-wide significance
rs2416257[G]
5
110,463,389 0.85 WDR36
7.9
2.5 105 6.1
0.0070
4.4
0.062
6.1
(3.7, 8.6)
1.0 106 0.95 –4.4 0.27
rs2269426[T]
6
32,184,477
0.76 MHC
6.0
1.9 105 5.1
0.0023
1.5
0.48
4.6
(2.7, 6.6)
2.9 106 0.30 –0.4 0.89
rs9494145[T]
6
135,474,245 0.33 MYB
7.4
1.5 106 6.6
0.00037
–0.9 0.66
4.3
(2.4, 6.2)
1.2 105 0.70 2.5
rs748065[A]
8
21,734,049
0.69 GFRA2
6.0
2.9 105 2.7
0.11
1.6
0.36
3.8
(1.8, 5.7)
0.00012
rs3939286[A]
9
6,200,099
0.25 IL33
6.8
8.2 106 2.8
0.13
2.7
0.14
4.4
(2.4, 6.5)
1.8 105 0.03 –1.9 0.72
0.38
0.43 –0.5 0.84
Effects are given in percentage of standard units.
aFrequency in Iceland. bBecause of the extreme value selection in the Icelandic replication, the corresponding estimates have been deflated by a factor of 1.40. cBecause of assay quality issues,
the reported results for the non-Icelandic samples are based on the T allele of rs950880 (r2 ¼ 0.96 in the European HapMap data3). dThe frequency of the rs3184504 too low in the East Asians
for our SNP assay to yield reliable genotypes.
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rs3184504
SH2B3
12q24
rs9494145
HBS1L−MYB
6q23
Broad
effect
rs2269426
HLA
6p21
rs1420101
IL1RL1
2q11
rs4857855
GATA2
3q21
© 2009 Nature America, Inc. All rights reserved.
rs12619285
IKZF2
2q34
rs4143832
IL5
5q23
Specific
effect
rs2416257
WDR36
5q22
rs748065
GFRA2, DOK2
8p21
rs3939286
IL33
9p24
EOS
n = 13,850
NEU
n = 13,850
LYM
n = 13,850
MON
n = 13,850
BAS
n = 13,850
WBC
n = 13,896
PLT
n = 13,896
RBC
n = 13,896
Ht
n = 13,896
Hb
n = 13,896
IgE
n = 1,812
Figure 2 Association of SNPs identified through the blood eosinophil count genome-wide scan with differential white blood cell counts, platelet counts and
red blood. Results shown are EOS, eosinophil counts; NEU, neutrophil counts; LYM, lymphocyte counts; MON, monocyte counts; BAS, basophil counts;
WBC, white blood cell counts; PLT, platelet counts; RBC, red blood cell counts; Ht, hematocrit; Hb, Hemoglobin; and IgE, Immunoglobulin E. The SNPs are
classified into having broad or specific effect depending on the number of blood parameters with P o 0.01. The middle tick shows the estimated effect and
the end ticks mark its 95% confidence interval. The values behind this figure are given in Supplementary Table 4. Association results with P o 107,
P o 104, P o 0.01 and P 4 0.01 are indicated by gradually thinning lines.
European origin and one of East Asian origin (Table 2 and Supplementary Table 5 online). We assessed the association of all 15 SNPs
with asthma, even though the association of SNPs at only five of the
ten loci reached our threshold for genome-wide significance for
association with eosinophil counts, as the associations with some of
the five remaining loci may be true positives. SNPs belonging to four
loci (rs1420101 on 2q12, rs3939286 on 9p24, rs2416257 on 5q22 and
rs9494145 on 6q23) satisfied our criteria for significance after we
accounted for the testing of 15 SNPs in three asthma phenotypes:
asthma, atopic asthma and nonatopic asthma (P o 0.05/15/3 ¼
0.0011). Of those four loci, only the 2q12 locus was genome-wide
significant for blood eosinophil counts. The asthma risk alleles for all
four SNPs were the alleles correlating with increased blood eosinophil
counts (Tables 1 and 2). For rs3939286 on 9p24, rs2416257 on 5q22
and rs9494145 on 6q23, the observed association was stronger with
atopic asthma than nonatopic asthma (Table 2). The A allele of
rs1420101 on 2q12 also correlated positively with serum IgE (P ¼ 2.1
105), but with none of the other measured blood parameters
discussed above (Fig. 2). The SNPs at 9p24 and 5q22 did not associate
with any of the other blood parameters measured, whereas rs9494145
on 6q23 showed suggestive association with most of the blood
parameters measured (Fig. 2). The genotyping assay for rs1420101
yielded data that were difficult to call consistently for some of our
sample sets; we therefore used rs950880 as a surrogate for most of the
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non-Icelandic samples (r2 between rs1420101 and rs950880 is 0.96 in
the European HapMap data3).
rs1420101 on 2q12 is located in IL1RL1, and rs3939286, on 9p24, is
located 32 kb proximal to the start codon of IL33. IL33 encodes a
cytokine belonging to the IL1 superfamily, and is the natural ligand
for the IL1RL1 receptor4. IL33 can also function as a chromatinassociated nuclear factor with transcriptional regulatory properties5.
Signaling through the IL1RL1–ST2–IL33 complex has an important
role in eosinophil maturation, survival and activation, both by direct
effects on eosinophils and indirectly through recruitment and regulation of Th2 cell effector functions, which are consistent with a major
contribution of IL1RL1–IL33 signaling in eosinophil-mediated
inflammation6, such as that encountered in asthma. Although the
2q12 variant is located within IL1RL1, it is within a linkage disequilibrium (LD) block that contains three additional genes (IL18R1,
IL18RAP and SLC9A4) that can not be excluded as candidates for
driving the observed association.
SNPs in the IL1RL1, IL18R1, IL18RAP and SLC9A4 block have
previously been associated with Crohn’s disease (rs917997)7, celiac
disease (rs917997 and rs13015714)8, atopic dermatitis (rs6543116)9
and asthma (rs1974675)10. The Crohn’s- and celiac disease–associated
variants are not correlated with rs1420101, and these variants did not
associate with eosinophil counts or asthma in our samples (data not
shown). The atopic dermatitis–associated variant is in weak LD with
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Table 2 Association with asthma in nine European sample sets and one East Asian sample set
Asthma
SNP
Atopic asthma
Nonatopic asthma
Control
Closest gene
Chr.
Freq.a (n)
Freq.a (n)
OR (95% CI)
P
Freq.a (n)
OR (95% CI)
P
Freq.a (n)
OR (95% CI)
P
rs1420101[A]b
IL1RL1
2q12
0.367
(44,890)
0.405
(7,996)
1.16
(1.11, 1.21)
5.5 1012
0.417
(4,531)
1.18
(1.12, 1.24)
5.9 1010
0.375
(2,284)
1.11
(1.04, 1.19)
0.0017
rs3939286[A]
IL33
9q24
0.252
(44,997)
0.278
(8,167)
1.12
(1.07, 1.17)
5.3 106
0.288
(4,629)
1.14
(1.07, 1.21)
2.2 105
0.250
(2,381)
1.04
(0.96, 1.12)
0.33
rs2416257[G]
WDR36
5q22
0.847
(44,872)
0.861
(8,249)
1.13
(1.06, 1.20)
0.00012
0.878
(4,677)
1.20
(1.11, 1.29)
4.2 106
0.835
(2,390)
1.01
(0.92, 1.12)
0.78
rs9494145[T]
6q23
0.0037
0.778
1.06
0.10
(2,341)
(0.99, 1.15)
MYB
0.762
0.777
1.07
(45,018)
(8,150)
(1.02, 1.13)
0.779
1.12
(4,626)
(1.05, 1.19)
0.00024
© 2009 Nature America, Inc. All rights reserved.
For complete results, see Supplementary Table 5. aThe reported frequencies are the average frequencies in the Europeans sample sets. bBecause of assay quality issues, the results
for some populations are based on the T allele of rs950880 (r2 ¼ 0.96 in the European HapMap data3).
rs1420101, and rs1420101 did not associate with atopic dermatitis in with myocardial infarction (2,625 cases, 33,625 controls, P o 0.002;
the previous study9. rs1974675 was recently shown to associate with Supplementary Table 6 online). The association of both SNPs with
asthma in candidate gene studies10,11. This SNP is in LD with myocardial infarction was subsequently replicated in six sample sets
rs1420101 (D¢ ¼ 1, r2 ¼ 0.27, in the European HapMap data3) but of European ancestry (Table 3 and Supplementary Table 7 online).
has not been typed in our asthma or eosinophil sample sets. However, The association with myocardial infarction was slightly stronger
another SNP (rs10206753) on the Illumina chip and in much stronger for rs3184504 (combined OR ¼ 1.13, 95% CI ¼ 1.08–1.18, P ¼
LD with rs1974675 than rs1420101 (D¢ ¼ 1, r2 ¼ 0.96, in the 8.6 108). The Wellcome Trust Case Control Consortium has
European HapMap data3) shows weaker association than rs1420101 published imputed genotype counts for rs3184504[T] on 1,477
with eosinophil counts (P ¼ 0.00031 versus P ¼ 6.8 106) and coronary artery disease cases and 2,932 controls, which yield an OR
asthma (P ¼ 0.00057 versus P ¼ 0.00013) in the Icelandic discovery of 1.10 and a P value of 0.025 (ref. 19).
sample set. Furthermore, its association with asthma and eosinophil
rs3184504 is a nonsynonymous SNP (R262W) in exon 3 of SH2B3
counts could be accounted for by rs1420101 (P 4 0.18 for both (also known as LNK). It has previously been shown to associate with
eosinophil counts and asthma), whereas the association of rs1420101 type 1 diabetes20 and celiac disease8. In addition to associating with
could not be accounted for by rs1974675 (P ¼ 0.0022 for eosinophil eosinophil counts and increased risk of myocardial infarction, the
counts and P ¼ 0.025 for asthma).
T allele of rs3184504 associates with an increase in several blood
rs2416257, the most strongly associated SNP at the 5q22 locus, is parameters (Fig. 2). A trend toward risk for hypertension was
located in an LD block that contains WDR36 and TSLP. WDR36 observed for rs3184504 (see Supplementary Methods), but no
encodes a T-cell activation protein with a minimum of eight WD40 association was observed between rs3184504 and other traditional
repeats that is highly co-regulated with the T-cell growth factor IL-2 risk factors for myocardial infarction such as high-density lipoprotein
(ref. 12). TSLP encodes an IL-7–like cytokine that is expressed (P ¼ 0.63, n ¼ 8,269), low-density lipoprotein (P ¼ 0.70, n ¼ 5,615),
within the thymus and peripheral tissues and that regulates dendritic type 2 diabetes (P ¼ 0.85, 1,521 cases and 34,754 controls) and
cell–mediated central tolerance, peripheral T-cell homeostasis and smoking initiation (P ¼ 0.46, 10,521 smokers and 5,954 never
inflammatory Th2 response. TSLP is an initiator of allergic airway smokers)18. SH2B3 is a member of the APS family of adaptor proteins
inflammation in mice13 and, in asthmatic individuals, it shows and acts as a broad inhibitor of growth factor and cytokine signaling
increased expression in airways and correlates with expression of pathways. Lnk-deficient mice show profound perturbation of hemaTh2-attracting chemokines and disease severity14. rs9494145 on 6q23 topoiesis with increased numbers of megakaryocytes, B lymphoid,
is located between the HBS1L and MYB genes. Variants at this locus erythroid progenitor cells and hematopoietic stem cells21. The associahighly correlated with rs9494145 have previously been shown to tion of rs3184504[T] with increased counts for all major human blood
associate with fetal hemoglobin levels in
adults15, and subsequently platelet, monocyte
Table 3 Association of rs3184504[T], a coding SNP in SH2B3 on 12q24, with myocardial
and white blood cell counts16. MYB encodes a
infarction in the Icelandic discovery sample set in six replication sets of European ancestry
nuclear transcription factor implicated in proliferation, survival and differentiation of Sample set
n (control/case)
Freq (control/case)
OR (95% CI)
P value
hematopoietic stem and progenitor cells17.
33,625/2,625
0.380/0.404
1.11 (1.04, 1.18)
0.0012
Eosinophils have a role in diseases other Iceland discovery
3,700/343
0.382/0.420
1.17 (1.00, 1.37)
0.053
than asthma. Therefore, we examined the Iceland replication
730/1,209
0.439/0.497
1.26 (1.11, 1.44)
0.00045
association of the 15 SNPs identified through US, Durham
1,216/588
0.467/0.497
1.13 (0.98, 1.29)
0.096
the blood-eosinophil-counts scan in chronic US, Atlanta
462/681
0.541/0.537
0.99 (0.83, 1.17)
0.86
obstructive pulmonary disease (COPD) and US, Philadelphia
New
Zealand
501/558
0.452/0.492
1.17
(0.99,
1.39)
0.067
myocardial infarction using Icelandic GWA
387/646
0.495/0.531
1.16 (0.97, 1.38)
0.11
scan data18. None of the SNPs associated Italy
significantly with COPD (765 cases, 39,376
Combined replication
6,996/4,025
1.15 (1.08, 1.23)
1.1 105
controls), but the T allele of rs3184504 and the
G allele of rs653178, both located in SH2B3
Combined
40,621/6,650
1.13 (1.08, 1.18)
8.6 108
on chromosome 12, associated significantly
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LETTERS
cell types further supports an important role for SH2B3 in regulating
human hematopoietic progenitor and stem cell numbers. SH2B3 is
expressed in human vascular endothelial cells, where it promotes
inflamation. rs3184504[T] could contribute to the progression of
plaques in coronary arteries leading to myocardial infarction through
reduced anti-inflammatory activity of SH2B3.
The sequence variants at the remaining loci did not associate
significantly with risk of the three diseases tested. Briefly, a SNP
(rs4857855) located near GATA2 on 3q21 associates significantly with
blood eosinophil counts (Table 1), but even more significantly with
blood basophil counts (effect ¼ 14.5, 95% CI ¼ 11.8–17.2, P ¼ 1.8 1025). GATA2 is a transcription factor acting as an important
regulator of hematopoiesis22, affecting mainly the differentiation of
cells of the eosinophil, basophil and mast cell lineages23. A SNP
(rs4143832) located near IL5 on 5q31 showed association that was
restricted to blood eosinophil counts. IL5 encodes a growth and
differentiation factor for B cells and controls the production, activation and localization of eosinophils17. A SNP (rs12619285) located
near IKZF2 on 2q13 showed association specific to blood eosinophil
counts. IKZF2 has not been linked to eosinophil biology but is a
known regulator of lymphocyte development and differentiation
through transcriptional regulation24.
The results in Table 1 suggest some population heterogeneity with
respect to association with eosinophil counts. The association of the
SNP at IL5 in non-Icelandic Europeans is weaker than expected
from the Icelandic data (P ¼ 0.00055), and the relationship with
the SNP at MYB is in the inverse direction of what would be expected
(P ¼ 0.00053). This heterogeneity is either due to the different criteria
for sample inclusion (Supplementary Methods) or inherent differences in environmental factors between the different populations.
In summary, we have discovered several sequence variants that
associate with blood eosinophil counts by carrying out a GWA scan
on a large number of individuals. Following our previous approach to
studying smoking and lung cancer and peripheral artery disease18 and
pigmentation and skin cancers25 and that of others with uric acid and
gout26, we then assessed the association of the variants showing the
strongest suggestive association with eosinophil counts with disease,
and identified three asthma and one myocardial infarction susceptibility loci. The sequence variants discovered also provide candidates
for association with other diseases for which we do not have sufficient
data, such as autoimmune diseases and leukemia.
METHODS
Quantitative association testing. All blood measurements were standardized
using quantile-quantile standardization and then corrected for year of birth (or
age), sex and age at measurement, where available, for each study population
separately. In Iceland, year of birth was rounded to five years and used as a
factor variable in the correction, but in the other populations, a linear term in
year of birth was used to correct the measurements. For each SNP, a classical
linear regression, using the genotype as an additive covariate and the standardized blood measurement as a response, was fit to test for association. We
scaled the test statistics from the Icelandic genome-wide scan by the method of
genomic control27 using an estimate of 1.12 for blood eosinophil counts
obtained by comparing the observed median of all w2 test statistics to the
value predicted by theory (0.6752). The inflation factor in the combined
Icelandic dataset was estimated by simulating genotypes through the known
Icelandic genealogy as 1.15 for blood eosinophil counts. The inflation factors
for the other blood measurements were of similar magnitude. We combined
data from different sources by estimating effective sample size from the
observed effect sizes and P values using standard meta-analysis techniques.
Case-control association testing. We calculated the OR for each SNP allele or
haplotype assuming the multiplicative model; that is, assuming that the risk of
346
a homozyogous carrier relative to a noncarrier is the square of the risk of a
heterozygous carrier relative to a noncarrier. Allelic frequencies and OR are
presented for the markers. The associated P values were calculated with the
standard likelihood ratio w2 statistic as implemented in the NEMO software
package28. Confidence intervals were calculated assuming that the estimate of
OR has a log-normal distribution. The trios from the Netherlands II sample set
were analyzed assuming mendelian inheritance under the null hypothesis, using
the untransmitted parental alleles as controls. We carried out joint analyses of
multiple case-control replication groups using a Mantel-Haenszel model in
which the groups were allowed to have different population frequencies for
alleles or genotypes but were assumed to have common relative risks. The tests
of heterogeneity were done by assuming that the allele frequencies were the
same in all groups under the null hypothesis, but that each group had a
different allele frequency under the alternative hypothesis. We carried out joint
analyses of multiple groups of cases using an extended Mantel-Haenszel model
that corresponds to a polytomous logistic regression using the group indicator
as a covariate.
Accession codes. IL1RL1, 9173; WDR36, 134430; IL33, 90865; MYB, 4602;
IL18R1, 8809; IL18RAP, 8807; SLC9A4, 389015; TSLP, 85480; HBS1L, 10767;
SH2B3, 10019; GATA2, 2624; IL5, 3567; IKZF2, 22807.
Note: Supplementary information is available on the Nature Genetics website.
ACKNOWLEDGMENTS
The genotyping of some of the myocardial infarction sample sets was funded in
part through a grant from the US National Heart, Lung, and Blood Institute
(SR01HL089650-01). The New Zealand cohort study was supported by a
programme grant from the Health Research Council of New Zealand. The Korean
study was supported by a grant from the Korean Health 21 R&D project,
Ministry of Health & Welfare, Republic of Korea (A010249).
AUTHOR CONTRIBUTIONS
D.F.G., U.S.B., M.W., I.P.H., D.S.P., I.J., U.T. and K.S. wrote the first draft of
the paper. U.S.B., E.H., A. Helgadottir, B.J., D. Gislason, B.R.L., D.L., G.I.E.,
D.A. and G. Thorgeirsson participated in the collection of the Icelandic data.
C.W., J.H., J.B., N.M.W., A.J., L.J.P. and P.J.T. collected the Australian data.
G.H.K., H.M.B. and D.S.P. collected the Dutch data. A. Heinzmann, M.K., J.A.,
K.D. and M.W. collected the German data. A.W. and I.P.H. collected the
UK data. H.D.S., S.-T.U., H.S.C. and C.-S.P. collected the Korean data. L.M.R.,
C.P., J.W.H., V.B. and T.W. collected the Danish data. C.J. and U.-B.J. collected
the Swedish data. M.C.Y.N., J.C., W.Y.S. and R.M. collected the Hong Kong
data. S.H.S., C.B.G, A.A.Q., A.I.L., V.V., M.P.R. and D.J.R. collected the US
data. M.J.A.W., A.M.V.R. and G.T.J. collected the New Zealand data. E.T.,
G.M., P.F.P., A.B., L.P., D. Girelli, O.O. and N.M. collected the Italian data.
E.H., A. Helgadottir, H.H., V.S. and U.T. carried out the genotyping. D.F.G.,
P.S., G.M.J., G. Thorleifsson, H.S. and A.K. analyzed the data. D.F.G., U.S.B.,
K.D., P.J.T., M.W., I.P.H., D.S.P., T.G., J.G., I.J., U.T. and K.S. planned
and supervised the work. All authors contributed to the final version of
the paper.
COMPETING INTERESTS STATEMENT
The authors declare competing financial interests: details accompany the full-text
HTML version of the paper at http://www.nature.com/naturegenetics/.
Published online at http://www.nature.com/naturegenetics/
Reprints and permissions information is available online at http://npg.nature.com/
reprintsandpermissions/
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1deCODE
Genetics, Sturlugata 8, 101 Reykjavik, Iceland. 2Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland. 3The Lung Institute of Western Australia,
Nedlands WA 6006, Australia. 4The Western Australian Institute of Medical Research, Perth WA 6000, Australia. 5The Centre for Asthma, Allergy and Respiratory
Research, University of Western Australia, Perth WA 6009, Australia. 6Department of Molecular Genetics, PathWest Laboratory Medicine of Western Australia, QEII
Medical Centre, Nedlands WA 6009, Australia. 7Western Australian Institute for Medical Research, B Block, QEII Medical Centre, The University of Western Australia,
Nedlands WA 6009, Australia. 8School of Surgery and Pathology, and 9Centre for Genetic Epidemiology and Biostatistics, University of Western Australia, Perth WA
6009, Australia. 10West Australian Sleep Disorders Research Institute, Department of Pulmonary Physiology, Sir Charles Gairdner Hospital, Nedlands WA 6009,
Australia. 11School of Medicine and Pharmacology, The University of Western Australia, Nedlands WA 6009, Australia. 12Department of Pediatric Pulmonology and
Pediatric Allergology, Beatrix Children’s Hospital, University Medical Center Groningen, University of Groningen, 9700 RB Groningen, The Netherlands. 13Centre of
Pediatrics and Adolescent Medicine, University of Freiburg, 79085 Freiburg, Germany. 14Department of Epidemiology, University Medical Center, University of
Groningen, 9700 RB Groningen, The Netherlands. 15Division of Therapeutics, University Hospital of Nottingham, Queen’s Medical Centre, Nottingham NG7 2UH, UK.
16Cologne Center for Genomics, University of Cologne, 50923 Cologne, Germany. 17Laboratory of Genomic Diversity, Department of Life Science, Sogang University,
Seoul121-742, Republic of Korea. 18Department of Genetic Epidemiology, SNP Genetics, Inc., Seoul 153-803, Republic of Korea. 19Division of Allergy and
Respiratory Medicine, Soonchunhyang University Seoul Hospital, 140-210 Seoul, Republic of Korea. 20Landspitali University Hospital, 101 Reykjavik, Iceland.
21Division of Allergy and Respiratory Medicine, Soonchunhyang University, Bucheon Hospital, 420-031 Puchon, Republic of Korea. 22Department of Respitory
Medicine, Bispebjerg Hospital, Copenhagen University Hospital, DK-2400 Copenhagen, Denmark. 23Research Institute of Biological Psychiatry, Sct. Hans Hospital,
Boserupvej 2, DK-4000 Roskilde, Denmark. 24Department of Medical Sciences: Inflammation, Uppsala University, 75105 Uppsala, Sweden. 25Department of
Medicine and Therapeutics, Prince of Wales Hospital, Chinese University of Hong Kong, Shatin, Hong Kong. 26Duke University School of Medicine, Durham, North
Carolina 27710, USA. 27Emory University School of Medicine, Atlanta, Georgia 30322, USA. 28University of Pennsylvania School of Medicine, Philadelphia,
Pennsylvania 19104, USA. 29Vascular Research Group, Otago Medical School, PO Box 913, Dunedin 9054, New Zealand. 30Section of Biology and Genetics,
Department of Mother and Child, Biology and Genetics, University of Verona, 37129 Verona, Italy. 31Section of Pediatrics, Department of Mother and Child, University
of Verona, 37129 Verona, Italy. 32Department of Pediatrics, Bolzano Hospital, 39100 Bolzano, Italy. 33Department of Clinical and Experimental Medicine, Section of
Internal Medicine, University of Verona, 37129 Verona, Italy. 34The Laboratory in Mjodd, RAM, 109 Reykjavik, Iceland. 35Helmholtz Zentrum München, German
Research Center for Environmental Health, 85764 Neuherberg, Germany. 36Institute of Genetic Medicine, EURAC Research, 39100 Bozen, Germany. 37Department of
Pulmonology, University Medical Center, University of Groningen, 9700 RB Groningen, The Netherlands. Correspondence should be addressed to D.F.G.
([email protected]) or K.S. ([email protected]).
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