A meta-analysis of genome-wide association studies of asthma in Puerto Ricans

Abstract

Rationale

No genome-wide association study (GWAS) of asthma has been conducted in Puerto Ricans.

Objective

To identify susceptibility genetic variants for asthma in Puerto Ricans.

Methods

We conducted a meta-analysis of GWAS of asthma, including Puerto Rican participants from: GALA I-II, the Hartford-Puerto Rico Study, and the Hispanic Community Health Study. Moreover, we examined whether susceptibility loci identified in previous meta-analyses of GWAS are associated with asthma in Puerto Ricans.

Results

The only locus to achieve a genome-wide significant association with asthma in an analysis of 2,144 cases and 2,893 controls was chromosome 17q21, as evidenced by our top SNP, rs907092 (OR = 0.71, P = 1.2 ×10⁻¹²) on IKZF3. Similar to findings in non-Puerto Ricans, SNPs in genes in the same LD block as IKZF3 (e.g. ZPBP2, ORMDL3 and GSDMB) were also significantly associated with asthma in Puerto Ricans. With regard to results from a meta-analysis in Europeans, we replicated findings for the SNP at GSDMB, but not for SNPs in any other genes. On the other hand, we replicated results from a meta-analysis of North American populations for SNPs in IL1RL1, TSLP and GSDMB but not for IL33.

Conclusions

Common variants on chromosome 17q21 have the greatest effects on asthma in Puerto Ricans, a high-risk ethnic group.

INTRODUCTION

Asthma is a disease with substantial heritability.^{(1, 2)} Genome-wide association studies (GWAS) have identified several susceptibility loci for asthma, including the chromosome 17q21 region.^{(3, 4)} This locus, which contains genes IKZF3, ZPBP2, GSDMB and ORMDL3, has been consistently replicated across diverse ethnic groups.^(3–13)

The burden of asthma varies among racial or ethnic groups. In the United States, current asthma is more common in Puerto Ricans (16.1%) than in non-Hispanic blacks (11.2%), non-Hispanic whites (7.7%) or Mexicans (5.4%).⁽¹⁴⁾ Moreover, Puerto Ricans have greater morbidity from asthma than members of other racial or ethnic groups,⁽¹⁵⁾ and thus studying asthma in this ethnic group is relevant to public health and understanding disease pathogenesis. Although two previous GWAS of asthma included Puerto Ricans who participated in the Genetics of Asthma in Latino Americans Study (GALA I)⁽³⁾ and in the Genes-environments & Admixture in Latino Americans Study (GALA II)⁽¹³⁾, no separate analysis was presented for Puerto Ricans.

We conducted a meta-analysis of GWAS of asthma, including only Puerto Rican participants from: GALA I, GALA II, the Hartford-Puerto Rico Study (Hartford-PR)⁽¹⁶⁾ and the Hispanic Community Health Study/Study of Latinos (HCHS/SOL).^{(17, 18)} Moreover, we examined whether susceptibility loci identified in two previous meta-analyses of GWAS of asthma (conducted by the GABRIEL and EVE consortiums^{(3, 4)}) are associated with asthma in Puerto Ricans.

METHODS

Study Populations

Hartford-PR

Children were recruited in Hartford, CT (n=449) and San Juan, PR (n=678), as reported elsewhere.⁽¹⁶⁾ At both study sites, the main recruitment tool was a screening questionnaire given to parents of children ages 6 to 14 years. All participants had to have four Puerto Rican grandparents. Asthma was defined as physician-diagnosed asthma and at least one episode of wheeze in the prior year. Control subjects had neither physician-diagnosed asthma nor wheeze in the prior year. Genome-wide genotyping was conducted using the HumanOmni2.5 BeadChip platform (Illumina Inc., San Diego, CA), as previously described.⁽¹⁶⁾ Imputation of non-genotyped single nucleotide polymorphisms (SNPs) was performed with IMPUTE2,⁽¹⁹⁾ using data from the Phase I (November 2010 release) of the 1000 Human Genomes Project as the reference panel. After quality control measures, 948 children (523 with asthma) and ~7 million genotyped and imputed SNPs were included in the genome-wide association analysis. This analysis was conducted using logistic regression under an additive genetic model, adjusting for age, gender, study site and principal components (PCs) calculated using smartPCA.⁽²⁰⁾ Written parental consent was obtained for participating children, from whom written assent was also obtained. The study was approved by the Institutional Review Boards of the University of Puerto Rico (San Juan, PR), Brigham and Women’s Hospital (Boston, MA) and the University of Pittsburgh (Pittsburgh, PA).

GALA I

This study comprised subjects with and without asthma, recruited mainly from Puerto Rico, but also from New York City, NY.^{(21, 22)} Subjects were included in the study if they were aged 8 to 40 years and self-identified all four grandparents as Puerto Rican. Cases had physician-diagnosed asthma and had experienced two or more symptoms in the previous two years (wheezing, coughing, and/or shortness of breath). Control subjects had no symptoms of asthma or allergies, had no physician-diagnosis of asthma, and no history of other chronic respiratory illness or allergies (eczema, hives, or hay fever). All subjects were genotyped on the Affymetrix 6.0 GeneChip (Affymetrix, Santa Clara, CA), and quality control was performed as described elsewhere.⁽²³⁾ Genotyped data was phased with SHAPE-IT⁽²⁴⁾ and imputation was performed with IMPUTE2,⁽¹⁹⁾ using all populations from 1000 Genomes Project Phase I v3⁽²⁵⁾ as reference. Association testing was conducted using logistic regression under an additive genetic model, adjusting for age, gender, and African and Native American ancestry estimates (calculated using ADMIXTURE⁽²⁶⁾). A total of 437 unrelated subjects (251 with asthma) with complete data for all covariates were used in the current analysis. Written parental consent was obtained for participating children, from whom written assent was also obtained. The study was approved by the Institutional Review Boards of the University of California at San Francisco (UCSF) and at each participating center.

GALA II

This is a case-control study of asthma in Latino children.⁽²⁷⁾ Cases and control subjects were recruited using a combination of community and clinic-based approaches from centers throughout the U.S. (Chicago [IL], Bronx [NY], Houston [TX], San Francisco Bay Area [CA] and Puerto Rico). Subjects were eligible if they were aged 8 to 21 years, had <10 pack-years of smoking history and were not current smokers, and self-reported having four grandparents of Latino ethnicity. Asthma was defined based on physician diagnosis and report of symptoms and medication use within the last two years. Control subjects had no history of asthma or allergies, and no wheeze or shortness of breath during their lifetime. The current analysis focused on 1,786 participants (892 with asthma) with self-reported Puerto Rican ethnicity. All subjects were genotyped on the Axiom^® LAT1 array (World Array 4, Affymetrix, Santa Clara, CA), and quality control was performed as described elsewhere.⁽²⁸⁾ Imputation and association testing was performed as described above for GALA I. The study was approved by the Institutional Review Boards of UCSF and at each participating center. All subjects and their parents provided written informed assent and written informed consent, respectively.

HCHS/SOL

This is a community-based cohort study of self-identified Hispanic/Latino individuals aged 18–74 years, who were recruited at four centers (Chicago, IL; Miami, FL; Bronx, NY; San Diego, CA). Participants were recruited using a two-stage sampling scheme, in which census block units were sampled first, and then household and individuals from these units.^{(17, 18)} The HCHS/SOL study was approved by institutional review boards at participating institutions, and written informed consent was obtained from all participants.

The HCHS/SOL includes individuals who self-identified as Mexican, Central American, South American, Puerto Rican, Dominican or Cuban. However, genetic analysis groups were constructed based on a combination of these self-identified Hispanic/Latino background and genetic similarity. These genetic analysis groups largely overlap with the self-identified groups, but using the genetic analysis groups in association testing and stratified analyses has advantages, as previously described.⁽²⁹⁾ Individuals from the Puerto Rican genetic analysis group were used in the current analysis. Cases (n=478) had self-reported current physician-diagnosed asthma. Control subjects (n=1,388) had never been diagnosed with asthma. Individuals were genotyped at Illumina on the HCHS/SOL custom 15041502 B3 array, and imputed to 1000 Human Genomes Phase I data. Details about genotyping, imputation, and quality control are provided elsewhere.⁽²⁹⁾

Association analysis was performed using GMMAT,⁽³⁰⁾ a mixed-model logistic regression that accounts for correlations due to relatedness, shared household and block group. The analysis was adjusted for five genetic PCs, study center, sampling weights (to prevent potential selection bias resulting from the sampling scheme), age, gender, smoking status, and pack-years of cigarette smoking.

In our primary meta-analysis, we included three cohorts of children (Hartford-PR, GALA I, and GALA II) and one cohort of adults (HCHS/SOL) for maximum sample size. Since childhood asthma likely has genetic determinants that differ from those for adult-onset asthma, we repeated the meta-analysis after excluding HCHS/SOL.

Statistical Methods

METAL⁽³¹⁾ software was used to perform the meta-analysis of the four GWAS of asthma. METAL takes P-values across independent studies as input, with sample size and effect direction taken into account. First, for each SNP, the coded and alternative alleles are determined, and a Z-score is calculated based on the P-values and direction of effect in each study. Specifically, large positive Z-scores indicate small P-values where the coded allele is the risk allele, and large negative Z-scores indicate small P-values where the coded allele is protective. Formally the Z-score is

$$Z_i={\mathrm{\Phi }}^{-1}(1-\raisebox{1ex}{$P_i$}\!\left/ \!\raisebox{-1ex}{$2$}\right.)\times \text{sign}({\mathrm{\Delta }}_i),$$

where Z_i is the Z-score for study i, P_i is the P-value for study i, Δ_i is the direction of effect for study i, and Φ⁻¹ gives the percentile of a standard normal distribution. Then, the overall Z-score and P-value are calculated from a weighted sum of the individual Z-scores,

$$Z=\frac{{\sum }_i{Z}_i{w}_i}{\sqrt{{\sum }_i{w}_i^2}},$$

$$P=2\mathrm{\Phi }(|-Z|)$$

where Z is the overall Z-score, P is the overall P-value, and w_i is the weight for study i,

$$w_i=\frac{{\mathit{\text{MAF}}}_i(1-{\mathit{\text{MAF}}}_i)N_i^{\mathit{\text{cas}}}{N}_i^{\mathit{\text{con}}}}{(N_i^{\mathit{\text{cas}}}+N_i^{\mathit{\text{con}}})}$$

where MAF is the minor allele frequency for study i, $N_i^{\mathit{\text{cas}}}$ is the number of cases for study i and $N_i^{\mathit{\text{con}}}$ is the number of controls for study i. This weighting is intended to closely approximate the results that would be obtained combining subject-level data across the studies, in an analysis that adjusts for study. Summary odds ratios (ORs) were calculated by averaging the study-specific log-odds ratios, with weights reflecting the standard errors from the study-specific ORs.

We used the varLD^{(32, 33)} software to assess whether there were statistically significant differences in regional linkage disequilibrium (LD) structures between our study populations. VarLD uses a Monte Carlo approach to calculate P-values, which were based on 10,000 permutations. For a comparison of two populations, a P < 0.05 indicates a significant difference in LD structures.

RESULTS

The characteristics of participants in each of the four studies included in the meta-analysis are shown in Table 1. The results reported here are calculated based on 7,485,508 million imputed and genotyped SNPs in 2,144 subjects with asthma and 2,893 control subjects.

Table 1.

Summary of characteristics of participants included in the meta-analysis

	Hartford-PR (n=948)	GALA I (n=437)	GALA II (n=1,786)	HCHS/SOL (n=1,866)
Age in years (mean ± standard deviation)	10.0±2.7	18.2±9.5	12.9±3.4	48.2±14.0
Male gender (n, %)	495(52.2)	187(42.8)	907(50.8)	784(42.0)
Asthma (n, %)	523(55.2)	251(57.4)	892(49.9)	478(25.6)
Study sites	Hartford (CT) and San Juan (PR)	Puerto Rico and New York (NY)	Chicago (IL), Bronx (NY), Houston (TX), San Francisco (CA) and Puerto Rico	Bronx (NY), Chicago (IL), Miami (FL) and San Diego (CA)
Genotyping platform	Illumina 2.5M	Affymetrix 6.0 GeneChip	Axiom® LAT1 array (Affymetrix)	Illumina HCHS/SOL custom 15041502 B3 array

QQ plots for the meta-analysis (Figures S1 and S3) show that neither the results from each of the four component studies nor the combined results are inflated in their test statistics. Moreover, these plots reveal an abundance of small P-values in the combined study. We expected to see SNPs with P-value < 5×10⁻⁸, the standard significance threshold for GWAS. In the combined study, we found that 89 SNPs on chromosome 17q21 are significant at this level (Figure 1 and Table S1). Of these 89 SNPs, rs907092 on IKZF3 showed the most significant association with asthma (P = 1.2×10⁻¹², Figures 2 and 3). This SNP is also associated with asthma at P < 0.023 in all three studies of children and at P = 0.092 in HCHS/SOL, a study of adults (Figures 2 and S6).

Figure 1. Manhattan plot of meta-analysis results.

Manhattan plot showing the summary meta-analysis results of Hartford-PR, GALA I, GALA II, and HCHS/SOL. The chromosomal position of each SNP is displayed along the X-axis and the negative logarithm of the association P-value is displayed on the Y-axis. The blue line represents the suggestive significance line (P < 1×10⁻⁵). The red line represents the genome-wide significance line (P < 5×10⁻⁸).

Figure 2. Forest plots of odds ratio and 95% confidence interval for the association with asthma.

Forest plots for rs907092, the most significant SNP in the meta-analysis.

Figure 3. Results of the meta-analysis (Hartford-PR, GALA I, GALA II and HCHS/SOL) on the chromosome 17 region.

The relative location of genes and the direction of transcription are shown in the lower portion of the figure, and the chromosomal position is shown on the x axis. The light blue line show the recombination rate across the region (right y axis), and the left y axis shows the significance of the associations. The purple diamond shows the P-value for rs907092 that is the most significant SNP in the meta-analysis (Hartford-PR, GALA I, GALA II and HCHS/SOL). The circles show the P-values for all other SNPs and are color coded according to the level of LD with rs907092 in the 1000 Genome Project Admixed American (AMR) population.

Given our results for chromosome 17q21 and asthma, particularly in studies including children, we examined the LD pattern of this region among Puerto Ricans in Hartford-PR, GALA I and GALA II. Figures S8–S10 show that subjects in these studies have similar LD patterns (varLD P-value = 0.08 for Hartford-PR vs. GALA I; P-value = 0.46 for Hartford-PR vs. GALA II [see Table S2]), and that nearly all significant SNPs gather in an LD bin spanning ~200 Kb (see Figures S8–S10). The IKZF3-ZPBP2-GSDMB-ORMDL3 locus is included in this bin. We then compared the LD pattern of chromosome 17q21 in Puerto Ricans to that of other ethnic groups (Figure S11). Puerto Ricans have an LD pattern that differs from that in Mexicans or Europeans (varLD P-value ≤0.0007 for Hartford-PR vs. Mexicans (in GALA I or GALA II) or 1000G Europeans [see Table S2]). For this analysis, Mexican genotypes were extracted from GALA I and GALA II, and European genotypes were extracted from the 1000 Genomes Project.

Next, we examined whether SNPs previously associated with asthma in either a meta-analysis of GWAS of Europeans ⁽⁴⁾ or a meta-analysis of ethnically diverse North American populations ⁽³⁾ were also associated with asthma in Puerto Ricans (Table 2). For the meta-analysis in Europeans, we were able to replicate associations for the SNP at GSDMB at P < 0.005 (Bonferroni correction for 10 tests). For the meta-analysis of ethnically diverse populations, we were able to replicate the association with SNPs at IL1RL1, TSLP and GSDMB at P < 0.01 (Bonferroni correction for 5 tests). The two SNPs (rs2305480 and rs11078927) at GSDMB identified in the two cited studies consistently have small P-values in Hartford-PR, GALA I, GALA II, as well as in the meta-analysis. We did not replicate associations with SNPs in IL33, reported by both previous meta-analyses. Since this may be caused by differences in LD patterns in or near IL33 between Puerto Ricans and ethnic groups included in the prior meta-analyses (e.g., Europeans and Mexicans, Figure S12), we also show the top IL33 SNPs from our meta-analysis in Table S3. In this analysis, no IL33 SNP was significantly associated with asthma (P > 0.00035 in all instances, Bonferroni correction for 142 tests).

Table 2.

Results of the meta-analysis of GWAS of asthma in Puerto Ricans, for SNPs associated with asthma in two previous meta-analysis in Europeans (by the GABRIEL consortium) and ethnically diverse North Americans (by the EVE consortium)

SNP	Chr	Position	Ref	Alt	Gene	In cited paper	Hartford-PR			GALA I			GALA II			HCHS/SOL			Combined
						OR	AAF	OR	P-value	AAF	OR	P-value	AAF	OR	P-value	AAF	OR	P-value	OR	P-value
Loci reported by the GABRIEL consortium in Moffatt M.F. et al. N Engl J Med 2010; 363:1211–21
rs3771166	2	102986222	G	A	IL18R1	0.85*	0.45	0.90	0.500	0.44	0.75	0.114	0.43	0.85	0.018	0.46	1.14	0.110	0.94	0.111
rs9273349	6	32625869	A	G	HLA-DQ	1.14	0.61	0.98	0.860	NA	NA	NA	NA	NA	NA	0.62	1.22	0.016	1.13	0.079
rs1342326	9	6190076	A	C	IL33	1.27	0.21	0.90	0.403	0.26	1.12	0.571	0.22	1.05	0.528	0.20	1.13	0.213	1.05	0.376
rs744910	15	67446785	G	A	SMAD3	0.89	0.43	0.88	0.175	0.42	1.01	0.981	0.45	0.93	0.269	0.45	1.05	0.572	0.95	0.326
rs2305480	17	38062196	G	A	GSDMB	0.76	0.31	0.62	2.0×10−6	0.31	0.54	0.003	0.32	0.71	6.7×10−6	0.34	0.86	0.071	0.72	7.4×10−12
rs3894194	17	38121993	G	A	GSDMA	1.26	0.37	1.23	0.034	0.39	0.92	0.648	0.40	1.23	0.002	0.39	0.94	0.406	1.11	0.023
rs2284033	22	37534034	G	A	IL2RB	0.92	0.41	0.91	0.272	0.39	1.09	0.638	0.40	1.17	0.024	0.42	1.00	0.997	1.04	0.289
rs2073643	5	131723288	T	C	SLC22A5	0.89	0.50	0.96	0.668	0.48	1.18	0.356	0.50	0.93	0.257	0.51	1.01	0.856	0.98	0.551
rs1295686	5	131995843	T	C	IL13	0.85	0.59	1.01	0.943	0.62	0.75	0.136	0.62	0.90	0.159	0.61	1.07	0.398	0.96	0.408
rs11071559	15	61069988	C	T	RORA	0.88	0.26	1.07	0.525	0.25	1.69	0.012	0.24	0.90	0.193	0.24	0.85	0.087	0.96	0.486
Replicated genes reported by the EVE consortium in Torgerson D.G. et al. Nat. Genet. 2011; 43(9):887–92
rs1102000	1	158932907	T	C	PYHIN1	0.76#	0.08	1.09	0.651	0.06	0.50	0.061	NA	NA	NA	0.07	1.21	0.986	0.93	0.611
rs10173081	2	102957348	C	T	IL1RL1	0.83	0.19	0.84	0.132	0.16	0.85	0.519	0.26	0.78	0.010	0.18	0.93	0.506	0.84	0.004
rs1837253	5	110401872	C	T	TSLP	0.84	0.25	0.73	0.004	0.23	0.65	0.041	0.27	0.83	0.014	0.26	0.96	0.701	0.82	2.5×10−4
rs2381416	9	6193455	A	C	IL33	1.18	0.38	0.98	0.847	0.39	1.00	0.980	0.37	1.09	0.249	0.35	1.13	0.157	1.07	0.155
rs11078927	17	38064405	C	T	GSDMB	0.79	0.30	0.61	1.4×10−6	0.31	0.55	0.003	0.31	0.71	7.9×10−6	0.34	0.86	0.079	0.72	8.1×10−12

Ref: reference allele; Alt: alternative allele; AAF: alternative allele frequency; OR: odds ratio.

^*This column is childhood onset odds ratio in Moffatt M.F. et al. N Engl J Med 2010; 363:1211–21;

^#This column is overall odds ratio in Torgerson D.G. et al. Nat. Genet. 2011; 43(9):887–92.

Human Genome version: hg19

Since childhood asthma likely has genetic determinants that differ from those of adult-onset asthma, we repeated the meta-analysis of GWAS of asthma without HCHS/SOL, obtaining similar results (Figures S4, S5 and S7) to those from the meta-analysis including HCHS/SOL: only SNPs on chromosome 17q21 reached a significance level of P < 5×10⁻⁸. Moreover, we were able to replicate the same SNPs from the two previous meta-analyses of GWAS of asthma in the meta-analysis excluding HCHS/SOL (Table S4). In addition, SNPs at IL18R1 and GSDMA were replicated at P < 0.005 (Bonferroni correction for 10 tests).

In order to check if there were independent SNPs associated with asthma, we performed conditional analyses in chromosome 17q21 by adjusting for the top SNP in our analysis (rs907092). Since adults did not show a strong genetic association in this region, we conducted the conditional analyses in a meta-analysis of the three cohorts of children. The results showed that no SNPs in chromosome 17q21 reached the Bonferroni- corrected significance level, α=4.1×10⁻⁵ (1,215 overlapped SNPs with MAF > 0.05 across the three cohorts) and no SNPs in the IKZF3-ZPBP2-GSDMB-ORMDL3 locus reached the Bonferroni-corrected significance level, α=2.5×10⁻⁴ (197 overlapped SNPs with MAF > 0.05 across the three cohorts). Thus, in addition to SNPs in LD with rs907092, there seemed to be no other independent signals in chromosome 17q21.

DISCUSSION

We report findings from the first GWAS of asthma conducted solely in Puerto Ricans. Although two of the cohorts included in the current meta-analysis (GALA I and II) were part of Hispanic/Latino cohorts included in previous studies, those studies did not separately analyze data from Puerto Ricans but instead combined data from Puerto Ricans and Mexicans. Such approach can reduce statistical power, since Puerto Ricans and Mexicans differ markedly with regard to racial ancestry (i.e. Puerto Ricans have, on average, a greater proportion of African ancestry but a lower proportion of Native American ancestry than Mexicans), asthma burden (as Mexicans have a much lower asthma burden than Puerto Ricans), and allelic frequencies.⁽¹⁵⁾

In our meta-analysis of four GWAS, the only locus to achieve a genome-wide significant association with asthma was chromosome 17q21, as evidenced by our top SNP, rs907092 (P = 1.2×10⁻¹²), located on IKZF3. Similar to previous findings in non-Puerto Ricans, SNPs in genes located in the same LD block as IKZF3 on chromosome 17q21 (e.g. ZPBP2, ORMDL3 and GSDMB) were also significantly associated with asthma in our meta-analysis. A previous candidate-gene study conducted in 399 Puerto Ricans and 301 Mexicans in GALA I, as well as 261 African Americans, found significant associations between two SNPs in ORMDL3 (rs4378650 and rs12603332) and asthma in Mexicans and African Americans, but not in Puerto Ricans (P=0.08 for both SNPs).⁽⁶⁾ In our meta-analysis, these two SNPs (P = 4.0×10⁻⁶ for rs4378650 and P = 5.5×10⁻⁶ for rs12603332) were replicated for an association with asthma.

Consistent with prior findings suggesting stronger effects for SNPs in chromosome 17q21 on childhood asthma than in adult asthma among Europeans⁽⁴⁾, we found genome-wide significant results for this locus in a meta-analysis restricted to the three cohorts of children, but not in the GWAS of asthma among adults in HCHS/SOL.

We also attempted to replicate previous findings for potential asthma-susceptibility SNPs from meta-analyses conducted in Europeans (by the GABRIEL consortium)⁽⁴⁾ and ethnically diverse North American populations (by the EVE consortium).⁽³⁾ With regard to results from GABRIEL, we replicated findings for the SNP at GSDMB (on chromosome 17q21), but not for SNPs in any other gene. On the other hand, we report the first replication of results from the multi-ethnic EVE consortium for SNPs in IL1RL1, TSLP and GSDMB in a cohort composed exclusively of Puerto Ricans. Our lack of replication of most findings from GABRIEL in Puerto Ricans mimics negative findings from the EVE consortium, and may be due to ethnic differences in risk variants for asthma. In fact, EVE only replicated findings for chromosome 17q21 and IL33 (albeit for different SNPs) from GABRIEL.

We did not replicate results for PYHIN1 or IL33 from EVE. PYHIN1 was only associated with asthma among African-Americans and Afro-Caribbeans, and ancestry differences may account for our negative results. For SNPs with MAF ≥ 0.37 (the MAF of IL33 SNP rs2381416 in our study cohorts), we had ≥ 70% statistical power to detect an OR ≥ 1.10 at α ≤ 0.01 in our meta-analysis.⁽³⁴⁾ Under the same assumptions, the statistical power to detect an OR ≥ 1.20 at α ≤ 0.01 was > 99% in our meta-analysis. Of the 142 SNPs in IL33 that were tested for association with asthma in the current study, only 6 were associated at P < 0.01, and none remained significantly associated with asthma after a Bonferroni correction.

Expression of the 17q21 gene, ORMDL3, is regulated by asthma-associated SNPs,⁽³⁵⁾ as replicated in our previous eQTL study (rs8067378, P = 2.6×10⁻¹⁰) using the Hartford-PR data.⁽³⁶⁾ Lately, ORMDL3 has been implicated in various cellular processes that could be relevant to asthma.⁽³⁵⁾ In addition to its effects on asthma susceptibility, the study from Tavendale et al. also showed that ORMDL3 is associated with asthma exacerbations⁽¹¹⁾ and that the ORMDL3 SNP-mediated expression is affected by rhinovirus infection, a common trigger of such exacerbations.⁽³⁷⁾ The SNP in the IKZF3-ZPBP2-GSDMB-ORMDL3 region that was associated with asthma in the EVE meta-analysis was rs11078927 in GSDMB, which is replicated in our study (P = 8.1×10⁻¹² [see Table 2]). In EVE, the reported ORs for this SNP and asthma were 0.80 in European Americans and 0.78 in Latinos (non-significant in African Americans). In our study, we estimated ORs of 0.72 in all subjects and 0.66 in children only, suggesting a stronger effect of the IKZF3-ZPBP2-GSDMB-ORMDL3 locus on childhood asthma in Puerto Ricans than in other ethnic groups. Thus, the effects of the major allele for SNP rs11078927 (i.e. OR of 1.51 [1/0.66] in children) may contribute to asthma etiology in Puerto Ricans.

The ZPBP2-GSDMB-ORMDL3 locus was detected to have allelic differences in expression levels in lymphoblastoid cell lines (LCLs) and CD4+ cells.^{(38, 39)} Early studies of gene expression^(40–42) revealed that the asthma-associated SNPs regulate the expression of ORMDL3 and GSDMB, and that these two genes might be coregulated.⁽³⁸⁾ Findings from a prior study suggest that an asthma-associated 17q21 regulatory haplotype affects transcriptional activity of ZPBP2, GSDMB, and ORMDL3, with one non-coding variant in ZPBP2, rs12936231, differentially influencing the binding of the insulator protein CTCF in an allele-specific manner;⁽³⁸⁾ subsequent eQTL studies showed that SNP rs12936231 increases ORMDL3 and GSDMB expression in primary lymphocytes, whole blood, and lung tissue.^{(43, 44)} However, SNP rs12936231 (which has a minor allele frequency=0.44–0.46 in our cohorts) was non-significantly associated with asthma in our meta-analysis (P = 2.0×10⁻⁶) and is only in moderate LD (r² >0.51) with our top SNP (rs907092) in IKZF3. This suggests that other functional polymorphisms on chromosome 17q21 may affect asthma risk in Puerto Ricans, likely through changes in expression of ORMDL3 (shown to cause experimental asthma in a transgenic murine model),⁽⁴⁵⁾ GSDMB, or ZPBP2. Another SNP located within the promoter region of ZPBP2 (rs4795397, P=3.7 × 10⁻¹² in our meta-analysis [Table S1]) is a putative functional polymorphism that shows asthma-associated allele specific nucleosome occupancy.⁽³⁹⁾ However, the SNP’s strong influence on ZPBP2 promoter activity is masked by DNA methylation of exon 1 of this gene. In contrast, the ORMDL3 promoter is fully unmethylated. The ZPBP2 and ORMDL3 genes show allelic differences in expression.^{(38, 39)} It has been shown that the IKZF3-ZPBP2-GSDMB-ORMDL3 haplotype acts differently in regulation of transcripts between Europeans and Africans,⁽³⁸⁾ with a stronger association in Europeans than in Africans. In a study by Verlaan et al.,⁽³⁸⁾ SNP rs8067378 was the most significant cis-eQTL in this four-gene region in both Europeans (P = 1.1×10⁻¹⁸) and Africans (P = 4.3×10⁻⁹). In an eQTL study in Puerto Ricans using our Hartford-PR dataset,⁽³⁶⁾ the same SNP was also the most significant cis-eQTL (P = 2.6×10⁻¹⁰) in the four-gene region. Although the two studies^{(36, 38)} might not be comparable due to different statistical models and different tissues (i.e., LCL used in the Verlaan et al. study⁽³⁸⁾ and globin-cleaned whole blood used in the Chen et al. study⁽³⁶⁾), we speculate that the significance of associated SNPs with expression in Puerto Ricans is between Europeans and Africans, since these are two ancestral populations in Puerto Ricans. We further performed eQTL analyses between our top SNP (rs907092) and expression of the IKZF3-ZPBP2-GSDMB-ORMDL3 locus using whole-blood RNA microarray data (n=121) from the Hartford-PR study. Findings from this secondary analysis, conducted using linear regression and adjusting for age, gender, asthma status, study site and the first two PCs, suggest that our top SNP (rs907092) may regulate expression of the IKZF3-ZPBP2-GSDMB-ORMDL3 locus (P = 0.07 for IKZF3, P = 0.02 for ZPBP2, P = 0.009 for GSDMB and P = 0.0004 for ORMDL3).

We recognize several study limitations. First, we had insufficient statistical power to detect weak genetic effects of common SNPs (e.g., ORs between 0.9 and 1.10 for IL33) or rare susceptibility variants. Second, subjects in our study lived in different sites in the U.S. mainland and Puerto Rico, and thus environmental differences may have confounded our results despite adjustment for study site in the four component studies. However, most minor allelic frequencies and effect estimates were similar across study cohorts. Third, misclassification of COPD as asthma is possible among adults in the HCHS/SOL cohort, given that 980 (52.5%) participants were former or current smokers (mean pack-years=18.6). Such misdiagnosis could account for the less significant associations reported in HCHS/SOL, even after adjustment for cigarette smoking. In summary, our findings suggest that common allelic variants in the chromosome 17q21 locus have the greatest effects on, and are thus particularly important in, the pathogenesis of asthma in Puerto Ricans. We confirmed susceptibility variants in two previously reported genes (IL1RL1 and TLSP). Future studies should aim to characterize functional variants that cause asthma in Puerto Ricans, either through primary genetic effects or through interactions with relevant exposures (e.g., second-hand smoke and air pollution).