Assessing the Reproducibility of Asthma Candidate Gene Associations, Using Genome-wide Data

Rogers et al.

Assessing the reproducibility of asthma candidate gene associations using genome-

wide data

Angela J. Rogers1,2,3, Benjamin A. Raby1,2,3, Jessica A. Lasky-Su1,3, Amy Murphy1,3,

Ross Lazarus1,3, Barbara J. Klanderman1, Jody S. Sylvia1, John P. Ziniti1, Christoph

Lange5, Juan C. Celedón1,2,3, Edwin K. Silverman1,2,3, Scott T. Weiss1,2,3,4

1).Channing Laboratory, Department of Medicine, Brigham and Women’s Hospital,

Boston, Massachusetts

2). Division of Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital,

Boston, Massachusetts

3) Harvard Medical School, Boston, Massachusetts

4) Center for Genomic Medicine, Brigham and Women’s Hospital, Boston,

Massachusetts

5). Harvard School of Public Health, Boston, Massachusetts

Correspondence:

Angela J. Rogers MD, MPH

Research Fellow

Channing Laboratory

Brigham and Women’s Hospital

Harvard Medical School

181 Longwood Avenue

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Copyright (C) 2009 by the American Thoracic Society.

Rogers et al.

Boston, MA 02115

Fax: 617-525-0958

Tel: 617-525-2045

Email: [email protected]

Declaration of Funding Sources: The CAMP Genetics Ancillary Study was supported

by the National Institutes of Health and the National Heart, Lung, and Blood Institute,

NO1 HR16049. Additional support for this research came from grants U01 HL065899,

U01 HL075419, P01 HL083069 and T32 HL07427 also from the National Heart, Lung

and Blood Institute. B.A.R. is a recipient of a Mentored Clinical Scientist Development

Award from NIH/NHLBI (K08 HL074193).

Running header: Asthma candidate genes in GWAS

Descriptor number: 58 (asthma: genetics)

Body word count: 3272

At a glance commentary

Scientific Knowledge on this Subject: Dozens of genes have been implicated in

asthma pathogenesis, yet most prior studies assessed only a few loci within a gene.

What this Study Adds to the Field: Using genome-wide data in a well-

characterized cohort of asthmatic children, we performed a comprehensive replication

study 39 candidate genes previously associated with asthma. We found evidence for

variant- and gene-level replication for 17 genes.

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mailto:[email protected]

Rogers et al.

Online Supplement: This article has an online data supplement, which is accessible from

this issue's table of content online at www.atsjournals.org

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Rogers et al. 1

ABSTRACT

Rationale: Association studies have implicated many genes in asthma pathogenesis, with

replicated associations between single nucleotide polymorphisms (SNPs) and asthma

reported for more than 30 genes. Genome-wide genotyping enables simultaneous

evaluation of most of this variation, and facilitates more comprehensive analysis of other

common genetic variation around these candidate genes for association with asthma.

Objective: To use available genome-wide genotypic data to assess the reproducibility of

previously reported associations with asthma and evaluate the contribution of additional

common genetic variation surrounding these loci to asthma susceptibility.

Methods: Illumina 550Kv3 SNP arrays were genotyped in 422 nuclear families

participating in the Childhood Asthma Management Program (CAMP). Genes with at

least one SNP demonstrating prior association with asthma in two or more populations

were tested for evidence of association with asthma using family-based association

testing.

Measurements and Main Results: We identified 39 candidate genes from the literature

using prespecified criteria. Of the 160 SNPs previously genotyped in these 39 genes, 10

SNPs in six genes were significantly associated with asthma (including the first

independent replication for asthma-associated integrin beta-3 [ITGB3]). Evaluation of

619 additional common variants included in the Illumina 550K array revealed additional

evidence of asthma association for 15 genes, though none were significant after

adjustment for multiple comparisons.

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Conclusions: We replicated asthma associations for a minority of candidate genes.

Pooling GWAS results from multiple studies will increase power to appreciate marginal

effects of genes and further clarify which candidates are true “asthma genes.”

Abstract word count: 243

Key words: asthma, replication, SNP, Integrin beta3, association

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INTRODUCTION

Asthma is a disease with a strong genetic component, with estimates of

heritability as high as 36-75%.(1) A thorough review of the literature in 2006 highlighted

more than 100 susceptibility genes for atopy and asthma identified through candidate

gene studies, positional cloning, or linkage studies.(2) Yet for nearly every gene

putatively associated with asthma, multiple publications have failed to replicate the

original findings. Differentiating false positives (related to factors such as multiple

comparisons, random chance, and population stratification) from false negatives

(resulting from underpowered replication studies, random chance, or population

stratification) is difficult.

Until recently, candidate gene studies were constrained largely by limitations of

genotyping: technical and monetary considerations limited the number of SNPs that

could reasonably be evaluated per study. For example, in 2001, deCODE published the

finding that 42 SNPs within 24 “asthma genes” did not differ between cases and

controls.(3) Because only 94 cases and controls were studied, they could only conclude

that those mutations were unlikely to incur odds ratios (ORs) greater than 2. After 8

more years of studying asthma genetics, additional candidate loci have been identified,

and we recognize that contributions of individual asthma genes are almost certainly more

modest, yet no additional systematic assessments of previously identified asthma genes

have been performed.

The cost of SNP genotyping has fallen dramatically, enabling more thorough

assessment of candidate loci, both by testing a sufficient number of SNPs to cover

common variation within the gene, and by genotyping cohorts sufficiently large to detect

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modest genetic associations. In this work, we used data from a genome-wide association

study (GWAS) to evaluate previously replicated asthma genes. The primary analysis of

these data to identify novel genetic variants in asthma is ongoing. However, this

genotyping array also provides coverage of ~75% of common genetic variation in

Caucasian individuals,(4) thus enabling assessment all known asthma genes in a single

large, well-phenotyped population—in this case children with mild to moderate asthma

who participated in the Childhood Asthma Management Program (CAMP). This dataset

also enables us to comprehensively assess the common genetic variation surrounding

putative asthma-susceptibility genes. Herein we describe the results of our analysis of

more than 600 SNPs in 39 replicated asthma candidate genes using GWAS. Some of the

results of this analysis have been previously reported in the form of an abstract.(5)

METHODS

Study Population and Human Subjects

CAMP is a multicenter North American clinical trial designed to investigate the

long-term effects of inhaled anti-inflammatory medications in children with mild to

moderate asthma.(6, 7) Inclusion criteria and protocols for collection of baseline

phenotypic data have been described in detail elsewhere.(6)

Of the 1,041 children enrolled in the original clinical trial, 968 children and 1,518

of their parents contributed DNA samples to the CAMP Genetics Ancillary Study. Our

only selection criteria for GWAS genotyping were (1) self-described non-Hispanic white

ethnicity and (2) availability of sufficient DNA for microarray hybridization. 422

subjects and their parents met these criteria. The Institutional Review Boards of the

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Brigham and Women’s Hospital and of the other CAMP study centers approved this

study. Informed assent and consent were obtained from the study participants and their

parents to collect DNA for genetic studies.

Candidate gene selection

We developed a list of candidate asthma genes based on a literature review of

asthma genetic association studies published through 2005 (2), supplemented with a

PubMed (www.ncbi.nlm.nih.gov/pubmed/) search limited to articles published between

9/1/2005 and 7/1/2008 and using the terms “genetic association AND asthma” and “case

control AND asthma.” Candidate genes were included if the following criteria were met:

(1) significant association with asthma affection status in at least two populations; (2) at

least one significant association study with no fewer than 150 cases and 150 controls or

150 trios; (3) asthma association with SNP (as opposed to haplotypes, microsatellite

markers, or with structural genetic variants) in at least one population.(8, 9) Genes were

excluded if the associations were with asthma-associated phenotypes rather than asthma

or if inclusion criteria were met only through association studies in the CAMP

cohort.(10-12)

SNP Genotyping

The Illumina 550Kv3 SNP array was used for SNP genotyping. Please see the online

supplement for detailed genotyping and QC methods (S1). 97.5% of SNPs passed our

quality control checks, leaving 534,290 SNPs for analysis. Genotype completion rates for

these SNPs averaged 99.75%.

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Statistical analysis

Association testing was performed with PBAT v.5.3.0 (Golden Helix, Inc.

Bozeman, MT). The primary association analysis assumed an additive genetic model,

with additional testing under dominant or recessive models performed for those SNPs

with prior association under those models.

We performed two sets of association analyses. First, we assessed SNP-level

replication, testing SNPs previously associated with asthma that were either themselves

represented on the Illumina array or were tagged with an r2 ≥ 0.80 (as calculated from the

CEU HapMap genotype data).(13, 14) SNP-level analysis tests were 1-tailed, because

significance was only declared if exact replication was observed (i.e. same risk allele).

Second, we assessed gene-level replication, by testing whether other common genetic

variants in these candidate genes were associated with asthma. We considered all

additional SNPs on the Illumina 550K array with minor allele frequency ≥.05 mapping

within 50kb up- or downstream of the RefSeq mRNA sequence of candidate genes (based

on the extent of CEU linkage disequilibrium and haplotype block patterns (15)).

Association tests in this second analysis were two-tailed. Power was calculated with

Quanto, assuming 400 trios and 15% disease prevalence.(16)

RESULTS

Review of the medical literature through July 2008 identified 39 genes with SNP-

association with asthma in at least two populations. A complete list of genes and prior

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publications is in the online supplement (S2). All of these genes harbor SNPs within

50kb of transcript that were represented on the Illumina 550K array. We note that

because lymphotaxin alpha (LTA) and tumor necrosis factor alpha (TNFα) lie within a

7kb region of Chromosome 6, they were considered jointly (LTA/TNF) for all analyses.

Genotyping was performed for 422 CAMP participants and their parents using the

Illumina 550Kv3 array. Following quality control analysis and removal of 43 individuals

with inadequate genotype data, 1,169 members of 403 nuclear families were available for

analysis (see online supplement (S1) for details). Of the 403 probands, 63% were male,

with a mean age of 8.8 (+/- 2) years and baseline FEV1 of 93 (+/-14) percent predicted.

The 403 probands analyzed were more frequently male and had slightly more severe

asthma than the remaining white probands in the CAMP cohort (see online supplement

S1 for full comparison).

SNP-level replication

We first evaluated variants previously associated with asthma that were testable

using the Illumina 550K array (see online supplement S3). 160 SNPs within 39 genes

were previously associated with asthma. Of these 160 SNPs, 93 (58%) were amenable to

testing with the Illumina array: 39 SNPs were present on the array (directly tested) and 54

were in high LD (r2 > 0.8 based on HapMap CEU data) with a SNP on the array

(indirectly tested). The remaining SNPs previously associated with asthma were not

amenable to testing, because they were either not taggable (18 SNPs) or unknown (49

SNPs with no rs number, or not in HapMap).

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Of the 93 SNPs tested, 10 SNPs in 6 candidate genes were nominally associated

with asthma in our population with directionality consistent with prior association studies

(one-sided p<.05, see Table 1). While multiple SNP associations were replicated in both

IRAK-3 and ORMDL3, these likely reflect a single disease susceptibility locus in each

gene. In ORMDL3, for example, the r2 between all tagged SNP is >.9, thus all SNPs

could have been tagged had we tested only a single marker in CAMP. Direct replication

(meaning the SNP reported in the literature was genotyped) was observed for three genes

(IRAK-3, ORMDL3, and IL4R), whereas only indirect evidence of replication (using

LD-tagging SNPs) was observed for three genes (PHF11, IL10 and ITGB3). To our

knowledge, this is the first independent replication of association with asthma and ITGB3

following the two populations analyzed in the initial publication.(17) We note that we

required consistent directionality to call replication (i.e. minor allele is risk allele in both

studies). We did see evidence of a so-called “flip-flop” association for two SNPs,

rs946263 within CHI3L1 (tags rs4950928, minor allele is risk allele in our cohort, p=.04)

and rs5065 in NPPA (directly tested, minor allele is protective in our cohort, p = .03).

The significance of such associations, both biologically and clinically, is unclear.(18)

Gene-level replication

SNP-level replication was observed for 6 of 34 genes. Among possible reasons

for failing to replicate the remaining SNP associations is allelic heterogeneity, where

more than one variant per gene contributes independently to disease risk. To evaluate this

possibility, we next assessed whether the 39 genes harbor other common asthma-

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associated variants. The Illumina 550Kv3 array includes 619 additional SNPs with MAF

≥.05 mapping within or near these loci (see online supplement S4).

We found additional association in 15 genes, each with at least one SNP

associated with asthma in an additive model (54 SNPs with uncorrected p<.05, see Table

2). The complex nature of the associations is evident, for example, in the gene ITGB3, as

shown in Figure 1 (see online supplement S5 for images of all genes with association).

The minor allele of rs11869835 (“A” in Figure 4) is associated with asthma and tags a

previously identified SNP with an r2 of 1.0. Four previously identified SNPs were

directly tested in CAMP and showed no association in CAMP (“B”). Finally, a SNP

upstream of ITGB3 has not been previously tested, yet was associated with asthma here

(“C”); this locus demonstrates the capacity of GWAS surveys to identify novel

susceptibility SNP within the candidate genes. Only one SNP, located in NPPA, met

significance after gene-level Bonferroni correction (p <.013 for the 4 SNPs tested); none

met the more stringent Bonferroni correction for all SNPs tested in this analysis (pBonferroni

<8 x 10-5 for 619 SNPs).

Factors associated with replication

We performed several analyses to investigate potential contributors to our

replication of only a minority of previous asthma associations (in 10/93 SNPs and 15/39

genes) using GWAS. LD coverage of common variation was adequate for most genes

using the Illumina 550k array (89% of HapMap SNPs with MAF ≥.05 were directly

tested or tagged), though coverage within genes varied widely, ranging from 21% in

CCL24 to 98% in IL4.

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We assessed whether using the Affymetrix Genome-Wide Human SNP Array 6.0

(Affymetrix 6.0, with >900k SNPs represented) would have increased SNP coverage and

thus increased our ability to replicate SNP associations. Coverage was not improved with

the Affymetrix 6.0 array, with only 83% of HapMap SNPs tagged; this is a best-case

estimate of Affymetrix SNP 6.0 array coverage, as genotype completion rates of 100%

were assumed for this analysis. As shown in Figure 2, of the 160 SNPs previously

associated with asthma, fewer would be directly tested, and more would be untaggable

with Affymetrix 6.0 rather than the Illumina 550K array.

The 403 trios included here represent a substantially larger population than the

vast majority (>90%) of prior publications (supplement S2). We had 80% power to

identify ORs ranging from 1.4-1.7 for genes and 1.35-1.8 for SNPs. Despite our larger

population, these odds ratios are high for complex trait genetics; thus low power may

have contributed to our failure to replicate the majority of SNPs and genes tested.

We assessed whether genes that successfully replicated differed from those that did not in

any important ways. We found that genes that were larger or contained more SNPs were

more likely to be significant: genes with at least 1 significant SNP were a median 73kb

long and contained 11 SNPs, while those without significant associations were 42 kb and

contained 7 SNPs (Wilcoxon p = .07 and .11 respectively). In contrast, the number of

published replications did not vary between the 2 groups of genes (median 3 populations

in each, p = .43). A higher effect estimate in previous publications likewise was not

associated with replication in this study (median OR 2.82 in replicated genes vs. 2.78 in

non-replicated genes, Wilcoxon p=.87). Among the 619 Illumina 550k SNPs tested for

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gene-level replication, minor allele frequency was higher in the 54 significant SNPs

(MAF .29 vs. MAF .25 in non-significant SNPs, p=.03).

DISCUSSION

The focus of most previous GWAS publications has been on discovery of novel

biology, tested in large association studies in a “hypothesis-free” manner. Yet by virtue

of their broad genomic coverage, GWASs also include loci that have been previously

associated with phenotypes in candidate gene or fine-mapping association studies. We

thus have the opportunity to evaluate many previously reported asthma associations in a

well-characterized asthma cohort using GWAS data, assess the reproducibility of these

associations, test additional common variants in these loci, and ask the question: “Are

these genes truly associated with asthma?” In this work, we used GWAS data to

systematically test the most promising asthma candidate genes (i.e. those previously

associated in 2 or more cohorts). We were able to replicate findings at the SNP and gene

level for multiple genes, but failed to replicate many others—both points merit

discussion.

We found evidence for SNP-level replication for 6 genes in this cohort. All 6

associations are modest, with TDT ratios of 1.18-1.43, leading to p values in the .01-.05

range (see Table 1). They were appreciated here only because of a focus on candidate

genes—none would have been detected in the context of typical GWAS analysis where

very stringent multiple comparisons correction is required (i.e., α <10-6). This is the first

independent replication for integrin beta-3 (ITGB3). Two previous case-control analyses

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in Caucasian children showed association with ITGB3, but directionality of the minor

allele differed between the two studies.(17) Our study adds support to the finding that the

minor allele is actually the risk allele at this locus. Additionally, the family-based nature

of our cohort makes population stratification an unlikely false-positive cause of these

asthma associations, thus increasing the likelihood that these associations are real.

Another convincing replication is in ORMDL3, a candidate gene discovered via a

GWAS.(19) All associated SNPs identified in CAMP are in strong LD with SNPs from

the initial report of association (Fig. 1); while a precise causative locus for asthma risk is

uncertain, our results are certainly consistent with the findings of others that this region

harbors an asthma-susceptibility locus.(19-22)

We focused not only on SNP-level replication, but also more broadly assessed

each gene and its LD-flanking region for evidence of association with asthma. We found

an additional 54 SNPs in 15 genes that were significantly associated with p <.05. As

shown in Figure 1, the SNPs associated with asthma in our study were frequently distant

from those noted in original publications. Given that none of these SNPs met correction

for multiple comparisons testing (p< 8 x 10-5), it is certainly possible that some of these

findings represent false positives. Alternatively, these new associations may represent

differences between populations in LD structure or may be due to allelic heterogeneity,

with two or more causative variants resulting in similar phenotype.

Our results may be most striking for our failure to find more evidence of

replication, at both the SNP and the gene level. Only a small minority of previously

identified SNPs (10/93 SNPs either tested directly or LD-tagged) could be replicated.

Only 17 of the 39 genes showed any evidence of association with asthma (11 with

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association at the gene level only, 2 with only SNP-level replication, and 4 with both).

Thus, even using the liberal standard of “any p <.05” to suggest replication, we failed to

find any association with asthma in the majority of previously identified genes. Why did

we not find more evidence of replication? One potential answer is inadequate coverage

of common variation using a GWAS genotyping platform. The Illumina 550k array

tagged ≥70% of HapMap SNPs with r2 of >.8 for 29 of the 39 genes, and SNP-level

coverage would not have improved using an alternate GWAS platform (the Affymetrix

Genome-Wide Human SNP Array 6.0). However, these estimates are derived using

HapMap data (from which LD data was used to inform SNP content on SNP arrays) and

may thus overestimate genetic coverage on current GWAS microarray platforms. More

recent estimates suggest substantially lower coverage, approaching 50%.(23) This

sparseness would diminish power (and thus sensitivity) to detect true associations.

Poor coverage is clearly not the answer for the 93 SNPs that were directly tagged

or tested—even in those SNPs, we found an association for only 10 SNPs. Lack of

statistical power could further explain our negative associations. We studied 403 trios, a

substantially larger population than the vast majority of previous publications. Thus, we

had 80% power to detect an OR of 1.4-1.7 in these genes. It is certainly possible that we

missed smaller effects, however—genetic studies suffer a well-described “Winner’s

Curse” phenomenon, with initial publications tending to over-estimate effect estimates.(9,

24) Genes were more likely to replicate if they were larger and more SNPs were tested;

in both analyses, SNPs with higher MAF were more likely to be positive. These findings

suggest that higher power would have increased our significant findings. Thus, for the 24

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genes without evidence of replication, it may be that their true effect size is ≤1.3, and

thus even larger sample sizes are needed to identify a true association.

Another potential cause of failure to replicate is heterogeneity between studies.

Definitions of “asthma” vary widely. While we used an extraordinarily well-phenotyped

cohort of children with documented doctor-diagnosed asthma and a positive

methacholine challenge test who were participating in a clinical trial, many studies rely

on self-reported asthma or wheezing. Heterogeneity in the age and race of subjects could

reduce power as well. We note that while we ran our analyses in an additive model, we

also assessed for association in a recessive or dominant model if these were supported in

the literature. In no case did we find additional significant SNPs—thus, model

misspecification does not contribute to our negative results. Finally, we note that

evidence for replication at either the SNP or gene level was observed for five of six genes

identified using position-based genetic mapping approaches (i.e. linkage analysis or

GWAS, including GPR154, ORMDL3, CHI3L1, PHF11, and DPP10, but not ADAM33).

This compares to replication for less than 50% of primarily biological candidates. It is

interesting to speculate that susceptibility variants identified by hypothesis-free gene

mapping more consistently contribute to disease liability across populations.

So what does GWAS add to our understanding of candidate genes? It is most

obviously useful when previously identified SNP are directly represented (the 93 SNPs

testable here, for example). As the number of available asthma GWAS studies increases,

we may soon be able to pool results from multiple cohorts and thus have sufficient power

to more definitively answer whether those SNPs are truly asthma susceptibility loci.

GWAS also facilitates broader surveys of common variation within these candidate genes

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and can reveal novel candidate susceptibility SNP, as illustrated in 15 genes in this study.

However, where genetic coverage is sparse, GWAS is less well suited for “ruling out”

candidate genes. In these instances, negative studies not only require larger samples, but

also direct genotyping of candidate variants not represented (either directly or indirectly)

on the arrays.

In summary, we have performed the first systematic assessment of asthma genes

using GWAS technology. We found evidence of SNP-level replication in 6 genes, and

gene-level replication for 15. We anticipate that GWAS data will continue to be used to

evaluate candidate genes. As results from additional asthma GWASs become available

and investigators pool their results, we will be able to more definitively resolve which of

these candidates are truly asthma genes.

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ACKNOWLEDGEMENTS

We thank all subjects for their ongoing participation in this study. We acknowledge the

CAMP investigators and research team, supported by the National Heart, Lung, and

Blood Institute (NHLBI), for collection of CAMP Genetic Ancillary Study data. All

work on data from the CAMP Genetic Ancillary Study was conducted at the Channing

Laboratory and the Brigham and Women’s Hospital under appropriate CAMP policies

and human subjects protections.

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FIGURE LEGENDS

Figure 1: Results for ITGB3

Legend: SNPs in the literature are coded black, SNPs positive in CAMP are blue,

negative in CAMP are green. “A” denotes the significant association between RS

11869835 in CAMP and rs2317676, which is tagged with LD of 1.0. “B’s” denote 4

SNP that have been previously associated with asthma and were directly tested in CAMP

but showed no association. “C” is a SNP in the promoter region of ITGB3 that has not

been previously evaluated, but was significantly associated in CAMP with a p of .04. LD

map is for HapMap (CEU). Negative literature SNPs includes only those SNPs reported

in studies that published at least 1 positive association (to ensure adequate power). Image

created using the UCSC genome browser (http://genome.ucsc.edu/) and Haploview

(http://www.broad.mit.edu/mpg/haploview/).

Figure 2: Affymetrix 6.0 vs. Illumina 550K coverage of the 160 SNP previously

associated with asthma

No legend

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http://genome.ucsc.edu/




Table 1. Replication of previously identified SNPs using GWAS

CAMP tested

MAF in CAMP Risk Allele SNP Associated in

Previous Reports P value Over(+) or Under (-) transmission of minor allele

Transmitted: Untransmitted ratio

IRAK-3 rs1821777 .295 (C:T) T rs1821777, rs1882200 0.03 + 167:134

PHF11 rs1046028 .488 (C:T) C rs1046295 0.01 - 211:166

IL10 rs3024490 .236 (C:A) A rs1800872 (r2,948) 0.02 + 151:116

ITGB31 rs11869835 .072 (G:T) T rs2317676 0.04 + 60:42

rs8067378 .444 (A:G) A rs8067378 0.05 - 205:173

rs2872507 .406 (G:A) G rs8076131 (r2,935) 0.04 - 199:164 ORMDL3

rs4795405 .389 (C:T) C rs4795405, 4378650 (r2,845) 0.04 - 198:163

IL4R1 rs1805015 .163 (T:C) T rs1805015 0.03 - 122:95

P values are 1-sided given that only minor alleles with directionality consistent with previous reports are considered significant. Bold

indicates direct replication. R2 for tagged SNPs was 1.0 unless noted otherwise. Underlining denotes asthma genes identified via

positional cloning approaches. 1The minor allele has been shown to be the risk allele(17, 25) and protective allele(17, 26) in differing

populations.

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Table 2. 15 genes show additional evidence of association with asthma

Gene UCSC Location (build Mar. 2006)

Additional SNP tested SNP <.05 % SNP

significant pmin rs of pmin

IL10 chr1:205000986-205018827 7 1 14 0.01 rs3021094

CHI3L1

chr1:201408561-201435504 11 1 9 0.04 rs946263

NPPA chr1:11819241-11835780 4 2 50 0.002 rs198372

CTLA4 chr2:204430997-204452775 2 1 50 0.04 rs733618

DPP10

chr2:114909360-116350519 248 25 10 0.001 rs1914973

INPP4A chr2:98383407-98603871 14 1 7 0.02 rs11676357

MYLK chr3:124774156-125135166 31 1 3 0.04 rs11718105

PAFAH chr6:46731657-46824038 16 3 19 0.02 rs974670

GPR1541 chr7:34658901-34893456 60 3 5 0.01 rs17789834

FCER1B chr 11:59607673-59673270 3 1 33 0.05 rs12361312

GSTP1 chr11:67060003-67116179 7 3 43 0.03 rs614080

IRAK-3 chr12:64861524-64934595 5 1 20 0.05 rs1152912

PHF111 chr13:48920090-49007585 20 9 45 0.01 rs2981

PTGDR chr14:51797382-51828230 5 1 20 0.04 rs1953367

ITGB3 chr17:42672021-42751086 17 1 6 0.04 rs16969966

SNPs in the Illumina 550K array that were within the 39 genes and their neighboring LD-flanking region

were tested for association with asthma in an additive model. All p values here are 2-sided. The SNP that

were tested for association with previous asthma SNP are not re-represented here. Underlining denotes

asthma genes identified via positional cloning approaches. 1SNP associations with asthma in CAMP have

been previously published for these genes. (27)

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Figure 1: Results for ITGB3

IITTGGBB33

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Figure 2. Affymetrix 6.0 vs. Illumina 550K coverage of the 160 SNP previously

associated with asthma

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Assessing the reproducibility of asthma candidate gene associations using genome-

wide data

Angela J. Rogers, Benjamin A. Raby, Jessica A. Lasky-Su, Amy Murphy, Ross Lazarus,

Barbara J. Klanderman, Jody S. Sylvia, John P. Ziniti, Christoph Lange, Juan C. Celedón,

Edwin K. Silverman, Scott T. Weiss

Online Data Supplement

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S1: Phenotypic and genotyping QC Due to the small sample size of non-white ethnic groups and concerns regarding potential genetic heterogeneity, we restricted genotyping to 422 self-described white subjects and their available parents in whom sufficient DNA was available for all family members for genome-wide genotyping. Genome-wide SNP genotyping was performed by Illumina, Inc. (San Diego, CA) on the HumanHap550v3 BeadChip. Genotype reproducibility was assessed by analyzing 4 subjects that were repeated once on each of the 14 genotyping plates; all replicates had at least 99.8% concordance. The data were cleaned in several steps (see table below). 6,257 markers were removed due to low Illumina clustering scores. An additional 1,329 markers were removed because their flanking sequences did not map to a unique position on the hg17 reference genome sequence. We used PLINK (http://pngu.mgh.harvard.edu/purcell/plink/)(1) to further QC the remaining markers. All markers had greater than 90% genotyping completion rate, while the average completion rate for each marker was over 99%. 3,790 markers were removed because they were monomorphic in our sample. 2,445 markers were removed due to five or more parent-child genotype inconsistencies. No filtering was done based on Hardy-Weinberg equilibrium due to ascertainment of the cohort through affected probands. From 561,466 markers present on the BeadChip, 547,645 markers (97.54%) passed quality control metrics. 1169 CAMP subjects were successfully genotyped, including 403 probands and their parents. The average genotyping completion rate for each subject was 99.75%. S1. Table 1: Data QC

Attribute Count

(% of 561, 466 Markers on array) Low Illumina QC score 6,257 (1.1 %) Flank sequences do not map to hg17 1,329 (0.2 %) Monomorphic 3,790 (0.7 %) Parent-offspring genotype inconsistencies >4 2,445 (0.4 %) Total number of failed markers 13,821 (2.5 %) Total number of passed markers 547,645 (97.5 %) Autosomes 534,290 (95.1 %) Sex-linked 13,229 (2.4 %) Mitochondrial genome 126 (0.02 %)

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The 403 probands analyzed were more frequently male and had slightly more severe asthma than the remaining 308 white probands in the CAMP cohort, as shown in Table 2 below. S1. Table 2: Phenotypic characteristics

403 analyzed 308 non-analyzed P value1 Gender 63% 53% .006

Age 8.8 9 .21 FEV1 93% 96% .004

FEV1/FVC 79% 80% .16 LnPC20 .02 .27 .005

Log10IgE 2.6 2.5 .005 1Analyzed using Fisher’s exact test for gender, t-test for age, and linear regression for lung function, IgE, and methacholine hyper-responsiveness, after adjusting for age, gender, and height as appropriate. All values are at baseline, off controller therapy. E1. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, Maller J, Sklar P, de Bakker PI, Daly MJ, et al. Plink: A tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 2007;81:559-575.

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S2: Replicated SNP associations with asthma Gene Name (Official symbol, alias) N* Race/Ethnicity Age Pub Year Max OR

(if noted) Reference

130/217 Caucasian UK & US . 2002 . van Erdwegh(1)

220/230 European Am . 2003 . Howard(2) 160/265 Af Am . . 113/127 Hispanic . . 200/200 Dutch Adult . 171 F German . 2004 . Werner(3) 48/499 German Adult .

504/651 Japanese Adult 2006 .63 Hirota(4)

ADAM metallopeptidase domain 33 (ADAM33)

155 T Japanese Pediatric (mean 10) 2006 . Noguchi(5)

410 pop British Childhood 1998 2.18 Hopes(6) 38/155 US Children 2003 . Binaei(7)

907 Mexican Adults 2003 .5 Santillin(8) 71/400 Hutterites . 2003 . Bourgain(9)

Beta-2 adrenergic receptor (ADRB2)

125/96 N. Chinese . 2004 2.9 Gao(10) 65/362 Hutterites . 2003 . Bourgain(9)

235/239 N. India Adult 2007 1.96 Batra(11) Chemokine (C-C motif) ligand 11 (CCL11, eotaxin)

230 F N. India Mixed . 550/171 Korean Mixed 2003 . Shin(12) Chemokine (C-C motif)

ligand 24 (CCL24, eotaxin-2) 225/294 Korean Adult 2004 .4 Chae(13)

105/42 Brit/Caucasian Mean 35 2000 2.7 Fryer(14) 154 F, 83/67,

212/96 Brit/White Caucasian Mixed 2005 9.75 Al-Abdulhadi

(15)

Chemokine (C-C motif) ligand 5 (CCL5, Rantes)

210/224 African W Caucasian

Children (5-16) 2007 1.76 Lachheb(16)

187/227 India Adults 2004 1.96 Sharma(17) 106 Trios (mixed

atopy/asthma) India Mixed 2004 .

CD14 molecule (CD14)

327 F Barbados Mixed 2005 .25 Zambelli-Weiner (18)

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210/224 African White Caucasian Children (5-16) 2008 1.61 Lachheb (19)

546 (pop) Hutterites Mixed 2008 . Ober (20) 344/294 German Children .54

Chitinase 3-like 1 (CHI3L1)

99/197 Chicago/European descent Mixed .56

200/201 Dutch Adult 2002 . Howard (21) Cytotoxic T-lymphocyte-associated protein 4 (CTLA4) 364 F European Mixed 2004 . Munthe-Kass

(22) 223 F Quebec Mixed 2006 . Tremblay (23) Chemokine (C-X3-C

motif) receptor 1 (CX3CR1) . (≥ 178/268) Vancouver/Winn

ipeg Adult 2.75

359T Danish/US . 2004 . Pillai (24) 384T Mixed . .

Cysteinyl leukotriene receptor 2 (CYSLTR2) 137T Japanese . 2004 . Fukai (25)

244 F Australia & UK Mixed 2003 . Allen (26) Dipeptidyl peptidase 10 (DPP10) 1047 pop (incl

118 asthma) Germany 9-11 .

Unspec Caucasian . 2001 . Immervoll (27) 342 F UK Mean 14 2008 . Zhu (28)

Endothelin 1 (EDN1)

100 F Norway Mean 14 . 351/1769 German Children 9-11 2005 1.4/.77 Kormann (29) G-protein coupled receptor

154 (GPR154, also neuropeptidase receptor- NPSR)

439 F Costa Rica Children (mean 9.1) 2007 . Hersh (30)

44/127 British Adult 2000 .16 Fryer (31) 210/265 Turkey Adults 2003 .29 Aynacioglu (32) 101/103 Turkish Adult 2004 3.68 Tamer (33)

61/95 Taiwan Children 2004 . Lee (34)

82/184 Taiwan Children 2005 1.94 Lee (35)

391/639 Japanese Childhood (ctrls = adult) 2007 1.33 Kamada (36)

115/184 Japanese Children (ctrls = adult) 1.87

Glutathione-S transferase p1 (GSTP1)

105/112 Tunisia Children 2007 2.33 Hanene (37)

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Hepatitis A virus cellular receptor 1 (HAVCR1) 89/85 Bermuda, Af Am Adult 2005 2.8 Gao (38)

189/270 Indian Adult 2008 .5 Kumar (39) Interferon gamma (IFNG)

137 F Indian Mixed (proband mean age 15) .

76/434 Hutterites . 2003 . Bourgain (9) 117/47 Taiwan Mixed 2003 3.599 Hang (40)

272/307 N Indian Mixed 2005 1.318 Chaterjee (41)

Interleukin 10 (IL10)

164 F N. Indian . 2005 . 101/107 Dutch . 1999 7.8 Pouw Kran (42) 150/150 British Young adult 2000 2.14 Heinzmann (43) 200/100 Japanese adult 1.81 290 pop Japanese 6-12 . 184/184 Dutch Adults 2001 . Howard (44)

228/270 German Children 5-18 (ctrl = 19-40) 2003 . Heinzmann (45)

61/157 Af American Mixed 2005 2.9 Moissidis (46)

Interleukin 13 (IL13)

30/50 Iranian . 2007 . Hosseini-Farahabadi (47)

97 probands/ 121 par (TDT) Japanese Childhood

(3-29) 1998 . Noguchi (48)

11/269 Canadian W Infants to 1 2000 4.1 Zhu(49) 157 fatal/90 mod/143 ctrl

Canada & Australia W Adults 2000 1.8 Sandford(50)

1120 pop Germany 9-11 2003 . Kabesch(51) 337 T Caucasian Childhood 2003 . Beghe(52)

233/245 US W Mixed 2004 . Basehore(53) 116/130 US Hispanic Mixed . 231/270 German Age 5-18 2006 . Schubert(54) 109/68 Russian 17-65 2006 . Gervaziev(55) 30/50 N- Iranian Adult 2007 . Hosseini(47)

Interleukin 4 (IL4)

167/111 N-Taiwan(Chinese) Adult 2007 3.76 Chiang(56)

120/120 Japanese Childhood 1998 6.3 Mitsuyasu (57) Izayura (58)

Interleukin 4 Receptor(IL4R)

149/57 US Adult 1999 8.2 Rosa-Rosa(59)

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100/100 Japan . 2000 . Takabayashi(60) 200/201 Dutch Adult 2002 . Howard(61)

. Chinese Adult 2003 3.8 Cui(62) 423/114 China Mixed 2007 4.48 Zhang H(63) 73/98 Malay Adult 2007 .32 Zhang W(64) 277 T Indian Mixed 2008 . Sharma(65) Inosytol polyphosphate-4-

phosphatase, type 1 (INPP4A) 288/293 Indian Mixed .13

139/460 Sardinia Adult 2007 2.964 Balaci(66) Interleukin-1 receptor associated kinase 3 (IRAK-3, IRAK-M) 67/278 Italy . 2.67

108/186 Eur American Mixed (mean 19) 2005 . Weiss(67)

184/175 Af American Mixed (mean 13) .

Integrin, β-3 (ITGB3)

114/89 White Adult . 92/318 Australian Mixed 1997 . Moffatt(68) 74/50 Australian Children 1998 4.89 Albuquerque(69)

Lymphotaxin alpha (LTA)

137 F Japanese Children (subj & sibs age 3-29) 2005 . Migita(70)

200/100 Japanese Mixed 1996 3.43 Shirakawa(71) 45/51 S. African W 6-45 1998 . Green(72) 96/125 Kuwaiti Arab Children 1998 . Hijazi(73)

. Mixed British (90% Caucasian) Mixed 1998 . Cox(74)

26 F (134 subj) Cauc Australian Child 6-15 1999 . Palmer(75) 216/198 Chinese 3-65 2003 . Cui(76) 141/157 Chinese Adult 2004 1.97 Zhang X(77) 281/169 N India Mean age 27 2004 2.24 Sharma(78)

Membrane-spanning 4 domains, sub-family A, member 2 (MS4A2, also Fc fragment of IgE, high affinity I, receptor for, β polypeptide, FCER1β)

230/160 W India Mean age 29 2.15 125 F (848

indiv) African

Caribbean . 2007 . Gao(79) Myosin light chain kinase (MYLK)

125/89 European American . 2007 1.76 Flores(80)

96/94 Russian Children 2000 3.79 Makarova(81) N-acetyltransferase 2 (NAT2) 219/210 India Mixed 2006 .606 Batra(82)

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97/104 Russian White Adult 2006 5.27 Tamer(83)

189 T German Probands mean age 12 2005 . Weidinger(84)

. Australia . 2005 . Hysi(85)

. UK . .

Nucleotide-binding oligomerization domain containing 1 (NOD1)

600/1194 German 9-11 6.3 Nitric oxide synthase 3 (NOS3) 76/434 Hutterites . 2003 . Bourgain(9)

336/154 White Mixed 2008 .5 Lima(86) Natriuretic peptide precursor A (NPPA) 172/116 White Mixed .24

994/1243 UK & German Children 2007 1.84 Moffatt(87) 200/2120 German Children 1.52 3301 pop UK . 1.68

253 F Fr-Canad Mixed 2008 . Madore(88) 399 T Puerto Rican 10-15 2008 1.35 Galanter(89) 301T Mexican 11-19 1.38

261/176 Af Am 8-40 .32

ORM1-like protein 3 (ORMDL3)

1054/1465 N European 3-22 2008 2.11 Tavendale(90) 264/263 Japanese Adult 1999 . Stafforini(91) 181/119 British . 2000 2.2 Kruse(92)

Phospholipase A2, group 7 (PLA2G7, also platelet activating factor acetylhydrolase, PAFAH) 118/142 Japanese childhood 2002 3.3 Ito(93)

230 F (pop) Australian Mixed 2003 . Zhang(94)

130/28 British Adult 4 PHD finger protein 11 (PHF11)

49/28 (same ctrl as above) British Children 3

518/175 Europ Am Adult 2004 3.3 Oguma(95) 80/45 Af Am Adult 2004 6.47 118/79 Caucasian Adult 2006 3.06 Sanz(96)

342 F UK Caucasian Children (mean 14) 2007 . Zhu(97)

Prostaglandin D2 receptor (PTGDR)

294 F Denmark Adult (mean 28) .

585/343 Japanese Mixed 2000 . Unoki(98) Thromboxane A2 receptor (TBXA2R) 533/164 Korean . 2003 . Shin(99) Toll-like receptor 4 (TLR4) 115 pop Finnish Children 2004 4.5 Bottcher(100)

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(8 & 14) 316/1110 German/white Children 2008 1.32 Kormann (101)

70/140 European American Adult 2003 1.85 Lazarus(102)

329/1086 German/white Children 2008 1.33 Kormann (101)

Toll-like receptor 9 (TLR9)

210/224 African White Children (5-16) 2008 1.53 Lachheb(19)

122 severe, 91 mild/122 ctrl UK White Adult 2001 . Pulleyn(103) Transforming growth

factor, β1 (TGFB1) 527/170 US White Adult 2004 2.98 Silverman(104) 92/318 Australian Mixed 1997 . Moffatt(68) 74/50 Australian Children 1998 5.23 Albuquerque(69) 251/43 Caucasian . 1999 3.07 Chagani(105)

20/416 Irish/UK Childhood asthma 2000 2.6 Winchester(106)

236/275 Mixed Mean 43 2002 1.86 Witte(107) 188 T Japanese Mean 10 2002 . Noguchi(108)

550/171 Korean . 2004 .37 Shin(109) 191/138 Chinese 5-18 2004 2.17 Wang(110)

107/118 Chinese Mean 10 (5th grade) 2004 2.6 Sandford(111)

155/211 Indian Mixed 2005 . Gupta (112) 3699 pop Mixed 8-18 2006 .8 Li (113)

246/252 Indian Adult 2006 .66 Sharma (114) 238/224 Indian Adult .69

959 pop Norway 8-13 2007 1.7 Munthe-Kas(115)

596 T Mexico 4-17 2007 1.54 Wu (116)

5065 pop Caucasian 20-44 2008 1.84 Castro-Giner(117)

Tumor necrosis factor alpha (TNFα)

719/243 Korea Children (mean 10) 2008 1.72 Kim(118)

67/47 White Australian Child 6-12 1998 6.9 Laing(119) (120) 41/34 Netherlands . 2000 . Choi(121)

Uteroglobin (UGB, also Clara-cell specific 10kd protein, CC10) 85/85 Iran Adults 2004 1.91 Saadat(122)

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464 pop Denmark Adults 2005 3.2 Candelaria(123) Only those populations that show positive association are noted here. Studies limited to English language publications available on PubMed reporting primary SNP associations with asthma. Odds ratio = highest calculated by authors for asthma (in any model), when only OR for subgroups were calculated, average is noted. LTA and TNFα are listed separately here, as prior publications have focused on SNP within 1 gene or the other; given the overlap in gene regions, they are grouped together for analyses in this work. * N/N= Case/Ctrl, F=families, T=trios, pop=population-based sample (# of asthmatics indicated in parentheses where available)

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S3: Tested/Tagged status of 160 SNP

previously associated with asthma

Tested in CAMP

SNP in literature (r2 with tagging

SNP) Alias UCSC Location Untaggable

at r2 0.80

Unknown LD relationship

(not in HapMap)

rs3918395 rs3918395 M+1 chr20:3601149 . rs511898 F+1 chr20:3603085 1 . rs2271511 I1 chr20:3602433 1 . rs517155 L-1 chr20:3596877 1 . rs612709 Q-1 chr20:3600207 1 . rs3918396 S1 chr20:3599765 1 . rs528557 S2 chr20:3599742 1 . rs44707 ST+4 chr20:3599226 1 . rs597980 ST+5 chr20:3599165 1 . rs574174 ST+7 chr20:3598694 1 . rs2280091 T1 chr20:3598234 1 . rs2280090 T2 chr20:3598205 1 . rs2280089 T+1 chr20:3598127 1 . rs543749 V-1 chr20:3597679 1 . rs2787094 V4 chr20:3597161 1 . rs2853209 S+1 chr20:3599472 1 . rs628977 V-3 chr20:3597721 1

rs1042713 rs1042713 Arg16Gly chr5:148186633 rs2400707 rs1042714 (0.967) Gln27Glu chr5:148186666

rs4795895 rs4795895 -1328 G/A chr17:29635559

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rs17735961 rs3744508 (1.0) +67G/A chr17:29637007 . rs4732416 1265 A/G chr7:75279698 1 . rs2302004 179 T/C chr7:75280791 1 . rs2302005 275 C/T chr7:75280695 1

rs2291299 rs2107538 (1.0) -403A/G chr17:31231893 . rs2280788 -28C/G chr17:31231518 1

rs2569188 rs2569190 (1.0) -159C/T chr5:139993100

rs946263 rs946263 chr1:201432004 rs4950929 (1.0) chr1:201426749 rs2153101 (1.0) chr1:201435097 rs4950928 (1.0) -131C->G chr1:201422505

rs926169 rs231775 (1.0) +49 G>A chr2:204440959 . rs16840252 -1147C/T chr2:204439764 1 . rs11571302 JO31/T chr2:204451179 1 . rs7565213 JO30/A chr2:204451654 1 . rs11571297 JO27_1/C chr2:204453248 1

rs3732378 rs3732378 T280M chr3:39282166 rs3732379 rs3732379 V249I chr3:39282260

rs1050592 (1.0) chr3:39281788 . rs938203 chr3:39297669 1 . rs2669849 chr3:39303878 1 . Met201Val (601 A/G) chr13:48179555 1 . -1220 A/C ? . rs9595969 IVS2-37A/G chr13:48168626 1

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rs1430090 rs1430090 543WTC122P chr2:114927112 rs17712682 rs17712682 543WTC110P chr2:114935998

rs17763180 (0.90) 543WTC124P chr2:114930979 rs7559909 rs7559909 16WTC106P chr2:114969758

rs12151526

(0.896) 16WTC104P chr2:114973765 rs13011555 (0.90) 543WTC42P chr2:114945010

rs1820924 rs1820924 317WTC59P chr2:114986677 . 543WTC41P chr2:114913641 1 . rs17764091 543WTC43P chr2:114945592 1

rs5370 rs5370 chr6:12404241 rs1476046 (0.956) chr6:12401207 rs1800543 (0.955) chr6:12402123

rs4714351 rs5369 (1.0) chr6:12402244 . rs2071942 4124C/T chr6:12402979 1 . rs1800541 chr6:12397205 1

rs324396 rs324396 SNP563704 chr7:34756648 rs11773493 rs740347 (1.0) SNP585883 chr7:34778827

. SNP546333 chr7:34739277 1

rs1695 rs1695 Ile105Val chr11:67109265

rs2277025 rs2277025 chr5:156392673

rs10878779 rs1861494 (1.0) chr12:66837676

rs3024490 rs1800872 (0.948) -571C/A, -591 G/A chr1:205013030 rs1800896 rs1800896 -1082 A/G chr1:205013520

rs20541 rs20541 Gln130Arg chr5:132023863

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. -1112C/T chr5:132020708 1

rs3798130 rs2243250 (1.0) -589C/T chr5:132037053 rs2070874 (1.0) -33C/T chr5:132037609

rs2074529 rs2227284 (0.882) 3017G/T chr5:132040624

rs1805015 rs1805015 Ser478Pro, c1507T>C chr16:27281681

rs1801275 rs1801275 Gln551Arg chr16:27281901

rs1805011 rs1805011 c. 1199A>C, Glu375Ala chr16:27281373

rs1805012 rs1805012 c.1291 T>C, Cys406Arg chr16:27281465

rs2234898 (1.0) c.1242G>T chr16:27281416 rs2234900 (1.0) c.1299T>C chr16:27281473 . rs1805010 Ile50Val chr16:27263704 1 . c.899 -2 C>A chr16:27281072 1

rs2278206 rs2278206 A+110832G chr2:98538676 rs3769712 (1.0) A+92031T chr2:98519875 . rs3769710 C+92344T chr2:98520188 1

rs1821777 rs1821777 chr12:64892495 rs1882200 (1.0) chr12:64883968

rs1732877 rs1624395 (0.965) chr12:64904483 . rs11465955 chr12:64889666 1 . rs2293657 chr12:64891273 1

rs1623665 rs1370128 (1.0) chr12:64904905

rs7223003 rs2317385 (1.0) chr17:42684681 rs7209700 rs2015729 (0.853) chr17:42709492

rs1000232 (0.955) chr17:42711560 rs2292867 rs2292867 chr17:42712488

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rs999323 rs999323 chr17:42726602 rs15908 (0.838) chr17:42723336

rs3760372 rs3760372 chr17:42735001 rs3809863 rs3809863 chr17:42740011 rs11869835 rs2317676 (1.0) chr17:42743282

. rs1009312 chr17:42687139 1

. rs4634 chr17:42724788 1

. rs2317677 chr17:42748406 1

rs1041981 rs909253 (1.0) NcoI (intron1) chr6:31648292 rs2844484 rs2071590 (0.863) -753G/A chr6:31647747 rs2844482 rs1800630 (1.0) -863 chr6:31650455

. rs1800629 -308 G/A chr6:31651010 1

. rs1799724 -857 C/T chr6:31650461 1

rs2847666 rs2847655 (1.0) RsaIex7 chr11:59622247 . Ile181Leu chr11:59618016 1 . Val183Leu chr11:59618022 1 . RsaIin2 ? . rs569108 Gly237Glu chr11:59619680 1 . rs4678047 Thr335Thr chr3:124935528 1 . rs936170 chr3:124905507 1

rs7832071 rs1801280 (0.843) 341 C/T chr8:18302134 rs1390359 rs1799930 (1.0) G590A chr8:18302383

rs1041983 (0.921) 282 C/T chr8:18302075 rs1208 rs1208 803 A/G chr8:18302596

. 481 C/T chr8:18302274 1

rs2907749 rs2907749 chr7:30452266 rs2907748 (0.849) chr7:30439548

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. chr7:30465976 1

. chr7:30457285 1

. nd1+21658 chr7:30463233 1 . rs1799983 Glu298Asp chr7:150327044 1

rs5063 rs5063 G/A Exon 1 chr1:11830235 rs5065 rs5065 T/C Exon 3 chr1:11828655

rs5067 (1.0) T/C in 3'UT chr1:11828568

rs11557467 rs11557467 chr17:35282160 rs8067378 rs8067378 chr17:35304874 rs2290400 rs2290400 chr17:35319766 rs7216389 rs7216389 chr17:35323475

rs2305479 (1.0) chr17:35315743 rs9303281 (1.0) chr17:35327572 rs7219923 (1.0) chr17:35328044

rs12603332

(0.844) chr17:35336333 rs4795405 rs4795405 chr17:35341943

rs4378650 (0.845) chr17:35334391 rs2872507 rs8076131 (0.935) chr17:35334438 rs3744246 rs3744246 chr17:35337876

. rs9303277 chr17:35229995 1

. rs8079416 chr17:35346239 1

. rs4795408 chr17:35361153 1

. rs3894194 chr17:35375519 1

. rs3859192 chr17:35382174 1

rs1051931 rs1051931 Ala379Val chr6:46780902 . rs16874954 Val279Phe chr6:46785057 1 . rs1805018 Ile198Thr chr6:46787262 1

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rs1046028 rs1046295 (1.0) b5_3 chr13:49000811

. b4_2 chr13:48993128 1

rs7161576 rs8004654 (0.932) T-549C chr14:51803734 rs810633 rs803010 (0.855) C-441T chr14:51803842 rs803012 rs708487 (1.0) +6651 C/T chr14:51810721 rs708486 rs708486 +6541C/T chr14:51810831

. rs11157907 T-197C chr14:51804086 1

. rs803011 -731 A/G chr14:51803449 1

rs8105780 rs4523 (0.827) 924T/C chr19:3546794 . rs11085026 795 T/C chr19:3546923 1

rs2241714 rs1800469 (1.0) -509C/T chr19:46552136

rs1927914 rs2737190 (1.0) chr9:119504002 . rs5743836 -1237 chr3:52235822 1 . rs187084 chr3:52236071 1

rs3741240 rs3741240 38A/G chr11:61943118

Gene names in bold had representative SNP content on Illumina HumanHap550v3 BeadChip and were thus ammenable to testing in this study. SNP highlighted in yellow represent those directly tested (genotyped) in CAMP. SNPs highlighted in blue represent those indirectly tested in CAMP (r2 with tagging SNP, based on CEU HapMap data, in parenthesis).

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S4. SNPs assayed in 39 Genes with Illumina Infinium II array

Number of SNP tested

Most significant SNP association with asthma in CAMP

Gene UCSC Region

(hg 17)

Phase I: SNP-level

replication study

Phase II: Gene-level

replication study Total MAF>.05

% Hapmap coverage

with r2 > 0.8 FBAT

p-value dbSNP

rs number

ADAM33 chr20:3591348-3615825 1 7 8 8 0.43 0.200 rs2853210

ADRB2 chr5:148180746-148194515 2 5 7 7 0.89 0.208 rs2053044

CCL11 chr17:29621985-29650620 2 5 8 7 0.62 0.166 rs3815341

CCL24 chr7:75273759-75290520 0 3 3 3 0.21 0.281 rs2302006

CCL5 chr17:31172715-31281163 1 4 5 5 0.96 0.106 rs2306630

CD14 chr5:139941967-139998929 1 8 9 9 0.92 0.086 rs7721577

CHI3L1 chr1:201408561-201435504 1 11 12 12 0.85 0.036 rs946263

CTLA4 chr2:204430997-204452775 1 2 3 3 0.57 0.041 rs733618

CX3CR1 chr3:39274673-39302453 2 8 11 10 0.60 0.055 rs13088991

CYSLTR2 chr13:48150826-48187410 0 5 5 5 0.71 0.232 rs9595973

DPP10 chr2:114909360-116350519 4 248 294 252 0.93 0.001 rs1914973

EDN1 chr6:12382974-12410409 2 7 9 9 0.70 0.272 rs2859338

FCER1B chr 11:59607673-59673270 1 3 6 4 0.81 0.050 rs12361312

GPR154 chr7:34658901-34893456 2 60 62 62 0.93 0.015 rs17789834

GSTP1 chr11:67060003-67116179 1 7 9 8 0.86 0.030 rs614080

HAVCR1 chr5:156339186-156436363 1 16 18 17 0.98 0.060 rs4704843

IFNG chr12:66796544-66879212 1 15 19 16 0.97 0.175 rs12321565

IL10 chr1:205000986-205018827 2 7 10 9 0.88 0.015 rs3021094

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IL13 chr5:131980965-132029923 1 6 8 7 0.84 0.317 rs7719175

IL4 chr 5:132031985-132095375 2 9 11 11 0.98 0.426 rs3798130

IL4R chr16:27226879-27289213 4 13 19 17 0.71 0.058 rs1805011

INPP4A chr2:98383407-98603871 1 14 15 15 0.95 0.022 rs11676357

IRAK-M chr12:64861524-64934595 3 5 10 8 0.70 0.045 rs1152912

ITGB3 chr17:42672021-42751086 7 17 26 24 0.96 0.037 rs16969966

LTA/TNFA chr6:31633891-31659326 3 7 10 10 0.79 0.272 rs1041981

MYLK chr3:124774156-125135166 0 31 46 31 0.94 0.037 rs11718105

NAT2 chr8:18287748-18308094 3 5 9 8 0.76 0.649 rs7832071

NOD1 chr7:30419443-30497397 1 11 14 12 0.95 0.286 rs11763119

NOS3 chr7:150304247-150356655 0 7 7 7 0.68 0.163 rs2373929

NPPA chr1:11819241-11835780 2 4 6 6 0.69 0.002 rs198372

ORMDL3 chr17:35282160-35342870 7 2 9 9 0.92 0.073 rs4795405

PAFAH chr6:46731657-46824038 1 16 18 17 0.92 0.019 rs974670

PHF11 chr13:48920090-49007585 1 20 26 21 0.97 0.006 rs2981

PTGDR chr14:51797382-51828230 4 5 10 9 0.87 0.039 rs1953367

TBXA2R chr19:3540074-3562972 1 5 7 6 0.67 0.103 rs1476707

TGFB1 chr19:46521149-46575038 1 7 8 8 0.58 0.160 rs2241715

TLR4 chr9:119501043-119525036 1 6 8 7 0.52 0.135 rs1927906

TLR9 chr3:52192744-52240255 0 4 4 4 0.89 0.151 rs352143

UGB (CC10)

chr11:61937318-61954003 1 4 5 5 0.70 0.087 rs2509963

Totals 69 619 774 688

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S5: Physical and genetic (linkage disequilibrium) relationships for asthma-associated polymorphisms Legends: For each gene, the relative physical position of SNPs and gene transcript (coordinates in parenthesis) are presented as mapped to UCSC Human Genome (hg17). SNPs reported from the literature in the literature are denoted in black (Lit + = SNPs associated with asthma; Lit - = SNPs tested in at least one population and not associated with asthma); asthma-associated SNPs in CAMP are denoted in blue; SNPs not associated with asthma in CAMP are in green; SNPs typed in CAMP that evaluate previously associated SNP are denoted in red. Pair-wise SNP linkage disequilibrium maps were generated using the HapMap CEU genotype data. Haplotype blocks (solid black triangles) are based on the Gabriel definition.(1) Negative literature SNP includes only those SNPs in studies that published at least 1 positive association (to ensure adequate power). Images were created using the UCSC genome browser (genome.ucsc.edu/) and Haploview (www.broad.mit.edu/haploview/ haploview). NPPA (Natriuretic peptide precursor A, chr1:11819241-11835780)

1. Gabriel SB, Schaffner SF, Nguyen H, Moore JM, Roy J, Blumenstiel B, Higgins J, DeFelice M, Lochner A, Faggart M, et al. The structure of haplotype blocks in the human genome. Science 2002;296:2225-2229.

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http://www.broad.mit.edu/haploview/

CHI3L1 (Chitinase 3-like 1, chr1:201408561-201435504)

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IL10 (Interleukin 10, chr1:205000986-205018827)

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INPP4A (Inosytol polyphosphate-4-phosphatase, type 1, chr2:98383407-98603871)

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DPP10 (Dipeptidyl peptidase 10, chr2:114909360-116350519)

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CTLA4 (Cytotoxic T-lymphocyte-associated protein 4, chr2:204430997-204452775)

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MYLK (Myosin light chain kinase, chr3:124774156-125135166)

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PLA2G7 (Phospholipase A2, group 7 chr6:46731657-46824038)

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GPR154 (G-protein coupled receptor 154, chr7:34658901-34893456)

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MS4A2 (Membrane-spanning 4 domains, sub-family A, member 2 chr11:59607673-59673270)

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GSTP1 (Glutathione-S transferase P1, chr11:67060003-67116179)

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IRAK-3 (Interleukin-1 receptor associated kinase 3, chr12:64861524-64934595)

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PHF11 (PHD finger protein 11, chr13:48920090-49007585)

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PTGDR (Prostaglandin D2 receptor, chr14:51797382-51828230)

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IL4R (Interleukin 4 Receptor, chr16:27226879-27289213)

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ORMDL3 (ORM1-like protein 3, chr17:35282160-35342870)

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ITGB3 (Integrin, β-3, chr17:42672021-42751086)

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Assessing the Reproducibility of Asthma Candidate Gene Associations, Using Genome-wide Data

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