Conceived and designed the experiments: GKKH. Performed the experiments: MBK JMBM TP JG AMT. Analyzed the data: TMB MBK JMBM LJM AL ML. Contributed reagents/materials/analysis tools: MWK MER NTE LB GKKH. Wrote the paper: TBM LM GKKH. Performed data analyses and helped prepare table and figures: HH. Executed subject recruitment efforts: MBE.
The authors have declared that no competing interests exist.
Candidate gene case-control studies have identified several single nucleotide polymorphisms (SNPs) that are associated with asthma susceptibility. Most of these studies have been restricted to evaluations of specific SNPs within a single gene and within populations from European ancestry. Recently, there is increasing interest in understanding racial differences in genetic risk associated with childhood asthma. Our aim was to compare association patterns of asthma candidate genes between children of European and African ancestry.
Using a custom-designed Illumina SNP array, we genotyped 1,485 children within the Greater Cincinnati Pediatric Clinic Repository and Cincinnati Genomic Control Cohort for 259 SNPs in 28 genes and evaluated their associations with asthma. We identified 14 SNPs located in 6 genes that were significantly associated (p-values <0.05) with childhood asthma in African Americans. Among Caucasians, 13 SNPs in 5 genes were associated with childhood asthma. Two SNPs in IL4 were associated with asthma in both races (p-values <0.05). Gene-gene interaction studies identified race specific sets of genes that best discriminate between asthmatic children and non-allergic controls.
We identified IL4 as having a role in asthma susceptibility in both African American and Caucasian children. However, while IL4 SNPs were associated with asthma in asthmatic children with European and African ancestry, the relative contributions of the most replicated asthma-associated SNPs varied by ancestry. These data provides valuable insights into the pathways that may predispose to asthma in individuals with European vs. African ancestry.
Asthma (MIM 600807) is a disease of chronic airway inflammation characterized by recurrent episodes of wheezing, dyspnea, chest tightness, and cough. It affects nearly 300 million individuals worldwide including 20 million adults and children in the United States
While many studies have evaluated the importance of genetics on asthma susceptibility, most studies employ samples from populations of European descent. Few have focused on asthma risk in African Americans, despite the fact that asthma morbidity and mortality are more prevalent in this subgroup. In the PubMed database, European populations are mentioned 5 times more often in various asthma related literature than African Americans (
Therefore, the objective of this study was to identify the similarities and differences in association patterns of asthma and known candidate genes between European ancestry and African American children. To accomplish this objective, we used a carefully collected cohort of children from the greater Cincinnati area as the discovery cohort and an independent replication cohort of Caucasians and publicly available dataset of African Americans.
The analysis included Caucasian and African American asthmatic, allergic and non-allergic children enrolled in the Greater Cincinnati Pediatric Clinic Repository (GCPCR) and Cincinnati Genomic Control Cohort (GCC) and who met the case and control definitions (outlined below). Recruitment for GCPCR began in November, 2003 and is ongoing. Children with asthma and other allergic conditions visiting the allergy/immunology, pulmonary, and dermatology outpatient specialty clinics and from the Emergency Department at CCHMC were invited to participate in the GCPCR. Non-allergic control children were recruited into GCPCR from headache, dental and orthopedic clinics as well as from the community at large using paper and online advertising media. Following written informed consent, participants were asked to provide a buccal (using a cytobrush) or saliva sample (Oragene DNA Self-Collection Kit, DNA Genotek Inc., Ottawa, ON Canada) for DNA isolation and to complete repository specific questionnaires. The GCC is an ongoing community-based cohort of over 1,020 healthy children ages 3–18 years old. In terms of race, ethnicity, gender, and socioeconomic status, participants are representative of the 7 counties that cover the Greater Cincinnati region. Participating GCC children provided a blood sample for DNA isolation at their baseline visit. For these genetic association studies, GCPCR participants aged 4 to 17 years with physician diagnosed asthma based on the ATS criteria
The Caucasian replication population includes asthmatic children from the GCC compared to non-asthmatic adults with no family history of asthma from the Cincinnati Control Cohort (CCC). Like the GCC, the CCC is a population-based sample of 298 Caucasians (age 24–90 years) from the Greater Cincinnati/Northern Kentucky area. The African American replication populations were 42 African American trios (126 individual samples) from the Childhood Asthma Management Program (CAMP) data available from the NIH-based database of Genotypes and Phenotypes (dbGaP) (
We conducted a large-scale evaluation of candidate genes to identify common variants that influence asthma risk. A total of 28 candidate genes were selected for inclusion in a custom Illumina GoldenGate™ assay. To investigate asthma liability genes systematically, we selected 28 candidate genes. These candidates were chosen based on a high number of replications in the literature (>10)
Gene symbol | Gene name | Chr location | SNPs genotyped |
Gene Ontology Terms ( |
|
Process | Function | ||||
ATPAF1 | Apoptotic protease activating factor 1 | 1p33 | 3 (1) | protein complex assembly | |
CHI3L2 | chitinase3like 2 | 1p13 | 13 (9) | carbohydrate metabolic process, chitin catabolic process | cation binding, hydrolase activity |
CHIA | chitinase | 1p13.2 | 31(23) | cell wall chitin metabolic process, immune response, polysaccharide catabolic process, response to fungus, response to acid | cation binding, chitin binding, lysozyme activity, sugar binding |
CLCA1 | chloride channel accessory 1 | 1p22.3 | 29 (24) | ||
FLG | filaggrin | 1q21.3 | 12 (6) | keratinocyte differentiation, multicellular development | calcium ion binding, structural molecule activity |
IL10 | interleukin 10 | 1q32.1 | 10 (9) | B cell differentiation, T-helper 2 type immune response, defense response to bacterium, immune response, inflammatory response, receptor biosynthetic process, negative regulation of interleukin12 | cytokine activity, interleukin10 receptor binding, protein binding |
INSIG2 | insulin induced gene 2 | 2q14.1 | 9 (9) | cholesterol metabolic process, lipid metabolic process, response to sterol depletion, steroid metabolic process | protein binding |
NFE2L2 | nuclear factor erythroidderived 2like 2 | 2q31.2 | 8 (5) | regulation of transcription, DNA dependent transcription from RNA polymerase II promoter | sequencespecific DNA binding, transcription factor activity |
ADIPOQ | adiponectin, C1Q and collagen domain containing | 3q27.3 | 13 (10) | fatty acid betaoxidation, generation of precursor metabolites and energy, protein/glucose homeostasis, lowdensity lipoprotein particle clearance, negative regulation of inflammatory response | cytokine activity, eukaryotic cell surface binding, protein homodimerization activity |
ADRB2 | adrenergic, beta2, receptor, surface | 5q33.1 | 9 (6) | Gprotein coupled receptor protein signaling pathway, receptormediated endocytosis, negative regulation of inflammatory response | beta2adrenergic receptor activity, potassium channel regulator activity, receptor activity |
IL13 | interleukin 13 | 5q31.1 | 7 (6) | cell motion, cellcell signaling, immune response, inflammatory response, signal transduction | cytokine activity, interleukin13 receptor binding, |
IL4 | interleukin 4 | 5q3135 | 10 (7) | B cell differentiation, Thelper 2 type immune response, cellular defense response, cholesterol metabolic process, regulation of immune response, positive regulation of isotype switching to IgE isotypes | cytokine activity interleukin4 receptor, binding |
IL9 | interleukin 9 | 5q31.1 | 5 (5) | immune response, inflammatory response positive regulation of cell proliferation positive regulation of interleukin5 biosynthetic process | cytokine activity growth factor activity cytokine receptor binding |
SPINK5 | serine protease inhibitor Kazal type 5 | 5q33.1 | 19 (13) | negative regulation of immune response, regulation of T cell differentiation, epithelial cell differentiation | serinetype endopeptidase inhibitor activity |
TSLP | thymic stromal lymphopoietin | 5q22.1 | 9 (9) | cytokine activity | |
CCL26 | eotaxin3 | 7q11.23 | 10 (5) | Chemotaxis, immune response inflammatory response, signal transduction | chemokine activity |
SERPINE1 | serpin peptidase inhibitor, clade E, member 1 | 7q22.1 | 20 (9) | chronological cell aging fibrinolysis, regulation of angiogenesis | protease binding, protein binding, serinetype endopeptidase activity |
ALOX5 | arachidonate 5lipoxygenase | 10q11.21 | 14 (13) | inflammatory response, leukotriene biosynthetic process, oxidation reduction | arachidonate 5lipoxygenase activity, calcium ion binding |
SPI1 | spleen focus forming virus proviral integration spi1 | 11p11.2 | 8 (7) | negative regulation of transcription from RNA polymerase II promoter, positive regulation of genespecific, transcription | protein binding, sequencespecific DNA binding |
SERPINA1 | serpin peptidase inhibitor, clade A (alpha1 antiproteinase, antitrypsin), member 1 | 14q32.1 | 15 (15) | acutephase response, blood coagulation | peptidase activity, peptidase inhibitor activity, protease binding, protein binding, serinetype endopeptidase inhibitor activity |
CIITA | class II, major histocompatibility complex | 16p13.13 | 13 (8) | immune response, regulation of transcription, DNAdependent, response to antibiotic | protein binding, transcription coactivator activity |
IL4Rα | interleukin 4Rα | 16p11 | 31 (16) | immune response, signal transduction | interleukin4 receptor activity protein binding, receptor activity |
STUB1 | STIP1 homology and Ubox protein 1 | 16p13.3 | 4 (1) | protein polyubiquitination, regulation of glucocorticoid metabolic process, ubiquitindependent SMAD protein catabolic process | Hsp70 protein binding, |
HRH4 | histamine receptor H4 | 18q11.2 | 14 (11) | Gprotein coupled receptor protein signaling pathway, signal transduction | histamine receptor activity, |
TGFB1 | transforming growth factor, beta 1 | 19q13.2 | 5 (4) | positive regulation of interleukin17 production, induction of apoptosis, inflammatory response, lymph node development | protein Nterminus binding type II transforming growth factor |
CDH26 | cadherinlike 26 | 20q13.33 | 12 (8) | integral to membrane, plasma membrane | homophilic cell adhesion |
IL13RA1 | interleukin 13R1 | Xq24 | 17 (14) | receptor activity | |
IL13RA2 | interleukin 13R2 | Xq13 | 5 (4) | extracellular space, integral to membrane | cytokine receptor activity |
*numbers in parentheses indicates number of SNPs that passed quality control and enter to statistical analysis.
SNPs for this chip were selected in one of two ways. First, non-synonymous SNPs or SNPs in regulatory or coding regions were selected. Second, tagging SNPs that efficiently capture all the common genetic variation in a gene were selected using Haploview and Tagger (
All analyses were performed separately in Caucasian and African American datasets. Prior to analysis, SNPs which failed Hardy Weinberg Equilibrium (HWE) in the control dataset (p<0.0001) or had poor genotype calling (missing rate greater than 10%) or minor allele frequencies below 10% were excluded from the analysis. In addition, individuals with more than 20% of their total SNPs missing were also removed from the analysis. To account for potential population stratification/confounding or admixture in these samples, principal component analyses (PCA) was performed using 30 unlinked Ancestry Informative Markers (AIMs) and the EIGENSTRAT software
Statistical comparisons in both Caucasians and African Americans were made between asthmatic children and non-allergic controls and also between the allergic children and the non-allergic controls. As a general association screen, we tested for the additive models of single SNP analysis, which assume that each copy of the risk allele will increase disease prevalence. Unconditional logistic regression was used to calculate p-values and odds ratios for each SNP using the software PLINK (V1.05) and Bonferroni adjustment that scales the original threshold by the number of tests performed was used to correct for multiple testing and determine the statistical significance of each SNP
To compare the allele frequencies between Caucasian and African Americans asthmatic and non-allergic controls, we used the absolute allele frequency difference also called delta (δ). It is defined as the absolute value of the difference of the frequency of a particular allele observed between the two populations. If we let P11 represent the frequency of allele in the first population and P21 the frequency of the same allele in the second population, then δ = |P11−P21|. A marker with δ = 1 provides perfect information regarding ancestry whereas a marker with δ = 0 carries no information
Recursive partitioning (RP) was used to evaluate gene-gene interactions using the R package PARTY (v0.9-995;
We used Ingenuity Pathways Analysis (IPA) 8.6 (Ingenuity Systems, Mountain View, CA, USA), to demonstrate whether the RP interacting genes are part of an integrated and interconnected biological networks that involved in genes that have functional commonalities in both races. A data set containing RP gene identifiers was uploaded into IPA to map and generate putative networks based on the manually curated knowledge database of pathway interactions extracted from the literature. The gene network was generated using both direct and indirect relationships/connectivity. These networks were ranked by scores that measured the probability that the genes were included in the network by chance alone.
For the replication Caucasian (GCC cases and CCC controls) and African American dbGaP (CAMP trio dataset) populations, we utilized the available genotyping data from the Affymetrix 6.0 SNP chip (
For the Caucasian population, both imputed and genotyped SNPs were tested for association with asthma status using additive logistic regression models in PLINK. For the dbGaP CAMP dataset, association analysis was performed using the transmission disequilibrium test (TDT) described by Spielman and Ewens
Basic descriptive statistics of the study populations by race is provided in
Variable | Asthmatic Group | Allergic Group | Non-Allergic Controls | |||
Caucasian | African Am. | Caucasian | African. Am. | Caucasian | African Am. | |
Total children (n) | 420 | 330 | 269 | 150 | 298 | 51 |
Children after exclusions (n) |
413 | 315 | 261 | 147 | 298 | 51 |
Mean age (years) | 10.1 |
10.3 | 10.3 |
10.8 | 12.0 | 11.4 |
Percent male | 55.2% | 63.2% |
56.3% | 48.3% | 48.0% | 45.1% |
Indicates the number children after children with missing call rates above 20% were removed.
Indicates significant differences (p<0.05) with similar race non-allergic normal control children.
Indicates significant differences (p<0.05) with similar race allergic children. African Am. indicates African American race.
A comparison of allele frequency differences for 111 out of the 259 SNPs in Caucasian versus African Americans asthmatics (red) and Caucasian versus African American non-allergic control groups (blue) were statistically significant (
Among children with European ancestry, significant single SNP associations between asthmatics and non-allergic controls were detected in 13 of the 230 SNPs in 5 of the 28 genes (p-value = 0.05). These include SNPs in IL4, SPINK5, SERPINA1, IL9 and IL13 (
Associations between the 230 total SNPs within the 28 candidate genes were tested using the additive model after adjusting for age, gender and population stratification. The upper line corresponds to the conservative Bonferroni adjusted p value 0.00022. The middle line corresponds to the Bonferroni adjusted p value 0.00085 considering a LD correlation of 0.25. SNPs significant at this level (all in IL4) include rs2243250, rs243268, rs2243274 and rs43282. The lower line is a nominal significance p value = 0.05. SNPs are plotted on the x-axis according to their position on each candidate gene across the chromosome against association with asthma on the y axis (shown as log10 p value).
IL4 | Asthmatics vs. Non-Allergic Controls | ||||||||
Caucasian | African American | ||||||||
Frequency cases/controls = | 413/298 | 315/51 | |||||||
SNP (major/minor) | Function | MAF | MAF | ||||||
Asthmatics | controls | OR | P-value | Asthmatics | controls | OR | P-value | ||
rs2243250 (C/T) |
Promoter | 0.195 | 0.116 | 2.00 (1.45,2.75) | 0.00002 | 0.332 | 0.471 | 0.56 (0.37,0.86) | 0.008 |
rs2243282 (C/A) | Intronic | 0.180 | 0.117 | 1.81 (1.31,2.50) | 0.0003 | 0.336 | 0.294 | 1.26 (0.79,2.02) | 0.34 |
rs2243274 (G/A) |
Intronic | 0.188 | 0.126 | 1.74 (1.27,2.38) | 0.0006 | 0.389 | 0.500 | 0.64 (0.42, 0.96) | 0.03 |
rs2243268 (A/C) | Intronic | 0.178 | 0.116 | 1.81 (1.32,2.50) | 0.0003 | 0.250 | 0.220 | 1.22 (0.73,2.06) | 0.45 |
rs2243263 (G/C) | Intronic | 0.113 | 0.135 | 0.77 (0.55,1.08) | 0.13 | 0.167 | 0.265 | 0.54 (0.32,0.89) | 0.016 |
rs2243248 (T/G) | Promoter | 0.146 | 0.245 | 0.47 (0.27,0.82) | 0.008 | ||||
rs2243283 (C/G) | Intronic | 0.152 | 0.039 | 4.4 (1.34,14.44) | 0.015 |
Associations between asthmatic and non-allergic controls, and between allergic and non-allergic controls were tested independently and odds ratios (OR) were determined using logistic regression based on the minor allele after adjusting for age, gender and population stratification.
Indicates major and minor alleles are reversed in African American children. Confidence intervals are indicated in parenthesis, MAF stands for minor allele frequency.
In the African American children, 14 SNPs in 6 genes were significantly associated with asthma (p-value = 0.05,
To investigate if the strong single SNP association of IL4 gene is independent of IL13, linkage disequilibrium (LD) analyses were performed. IL13 is an adjacent cytokine gene, which lies 200 kb away from IL4 on chromosome 5q31 and has many structural and functional similarities with IL4 including a shared receptor (IL4Rα). All the genotyped IL4 SNPs in Caucasians and African Americans were studied for LD patterns. In both populations, LD within the IL4 gene was strong. However, LD was not observed between IL13 and IL4 in the African American population, while weak LD was observed between IL13 and IL4 genes in Caucasians (
Pairs of common SNPs in genomic regions containing IL4 and IL13 in the Caucasian (A) and African American (B) population. The positions of SNPs within the IL4 and IL13 genes are shown above the plot. Values in boxes are r2 measures on a decimal scale (i.e. 97 represent r2 = 0.97), indicating extent of LD between two SNPs. Box without numbers have r2 = 1. The shade of each square indicates the strength of the LD relationship between pairs of SNPs.
Analysis of SNPs imputed from Affymetrix data revealed similar significant associations with asthma. In fact, for Caucasians, the effect sizes for the replication studies were greater than those observed in the discovery analyses. For example, the odds ratio of asthma for
IL4 | Asthmatic (GCC) Vs. non-asthmatic controls (CCC)Caucasian | Childhood Asthma Management Program, CAMP (dbGaP)African American | ||||
Frequency cases/controls = | 74/211 | 42 trios | ||||
SNP ID | Function | OR* | P-value | OR** | P-value | |
Replication association | rs2243250 | Promoter | 3.86 | 0.003 | 2.15 | 0.019 |
rs2243282 | Intronic | 3.86 | 0.003 | 1.3 | 0.53 | |
rs2243274 | Intronic | 2.97 | 0.0076 | 1.73 | 0.086 | |
rs2243268 | Intronic | 3.86 | 0.003 | 1.08 | 0.84 | |
rs2243263 | Intronic | 2.22 | 0.04 | |||
rs2243248 | Promoter | 1.38 | 0.49 | |||
rs2243283 | Intronic | 1 | 1 | |||
Discovery of untyped SNP association | rs2070874 | Promoter | 3.86 | 0.003 | ||
rs734244 | Intron | 3.86 | 0.003 | |||
rs2227284 | Intron | 5.17 | 1.04E-06 | |||
rs2227282 | Intron | 5.17 | 1.04E-06 | |||
rs2243266 | Intron | 3.86 | 0.003 | |||
rs2243267 | Intron | 3.86 | 0.003 | |||
rs2243288 | Intron | 2.97 | 0.0076 | |||
rs2243289 | Intron | 3.86 | 0.003 | |||
rs2243290 | Intron | 3.86 | 0.003 | |||
rs2243240 | Promoter | 0 | 0.0455 | |||
rs2243246 | Promoter | 0.3571 | 0.03895 | |||
rs2243252 | Intron | 0 | 0.0455 |
Similarly, in the African American population, the odds of asthma for IL4 SNP rs2243250 increased from 1.75 (95% CI 1.16–2.70) in the discovery analysis to 2.15 in the replication analysis (
To identify the SNP combination that best discriminates between asthma cases and non-allergic controls, we explored the gene-gene interactions (epistasis) among all 259 SNPs across the 28 candidate genes using RP.
For the Caucasian population, a total of 6 SNPs from the total of 259 SNPs (in genes IL4, STUB1, ADRβ2, IL4Rα, IL13Rα2 and CHIA) remained in the final tree from the RP process (see
Using the program PARTY (implemented in R), non-parametric recursive partitioning was performed to identify combination of SNPs that together had the greatest ability to discriminate between asthmatic and non-allergic controls. All the 257 SNPs within the 28 candidate genes were evaluated in the process. For the stopping criterion we use the nominal level of the conditional independence test of α = 0.05. The final trees were enough to achieve 62% discrimination accuracy between the asthmatic and non-allergic control individuals for Caucasian population and 77% for African American population. The number of subgroup is indicated below each terminal node.
In the African American children, 5 SNPs in 5 genes together significantly discriminate between asthmatic and non-allergic children. INSIG2 rs4848492 was the most predictive gene following by IL4, CHIA, ADIPOQ and ALOX5 (see
Ingenuity Pathways Analysis (IPA) demonstrated that RP based interacting genes are part of an interconnected gene network that involved in related biological activities and functional commonalities. In Caucasian, the most enriched IPA canonical pathways in the 6 genes (p<3.21*10−4) were IL4 signaling and T helper cell differentiation. In African Americans, airway inflammation in asthma and role of cytokines in mediating communication between immune cells were the most enriched pathways among the 5 genes (p<1.89*10−2). Gene ontology analysis of the African American network showed enrichment for specific biological functions, including arachidonate 5-lipoxygenase activity (p = 2.2×10−6), mevalonate kinase activity (p = 1.5×10−3) and interleukin-4 receptor binding (p = 1.5×10−3). Gene ontology analysis of the Caucasian based Network showed cytokine binding (p = 1.9×10−12), cytokine receptor activity (p = 1.4×10−10). And transmembrane receptor activity (p = 3.7×10−6). Enriched biological process includes production of molecular mediator involved in inflammatory response (p = 9.7×10−9) for AA and immune response (p = 1.0×10−20) for CEU.
To our knowledge, this is the largest candidate genes association study that has examined racial differences in childhood asthma. Through this systematic study, we have simultaneously studied both Caucasian and African American asthmatic children and demonstrated that these populations predominantly exhibit different patterns of association between genetic variants and asthma. To accomplish this goal we used well characterized European ancestry and African American children who live in the same geographic region of the greater Cincinnati area. Using both cohorts we have shown that only 1 of 28 genes had associations in both populations, as well as only 2 genes were common across the two races in the recursive partitioning analysis. Indeed, different gene networks were associated with asthma in children with European ancestry versus African Americans suggesting that there may be distinct mechanisms underlying the pathogenesis and expression of asthma in these 2 subgroups. Simultaneous investigation of risk variants across European and African American populations enabled the identification of population specific risk alleles and disease pathways, which may contribute to health disparity. The results from this study may also assist in fine-mapping of genetic associations by exploiting the differences in linkage disequilibrium between populations to narrow the range of marker alleles demarking regions that contain a true biologically relevant variant.
These analyses revealed two major findings. First, we confirmed the importance of IL4 genetic variation in the risk of pediatric asthma, and present evidence of replication among the African-American population. While IL4 has been consistently reported to be associated with asthma in Caucasian, Asian, and Hispanic populations, two of the four SNPs, which reached Bonferroni corrected significance in the Caucasian children (rs2243250 and rs2243274) replicated (p<0.05) in the African American children (
Secondly, Using RP, we report for the first time an interaction of six genes affecting European ancestry pediatric asthma: rs2243250 (IL4), rs6597 (STUB1) rs11168070 (ADRβ2), rs3024676 (IL4Rα), rs638376 (IL13Rα2) and rs3806446 (CHIA). These SNPs resulted in 62% accuracy of asthmatic and non-allergic classification. Similarly seven SNPs in five genes rs4848492 (INSIG2), rs2243283 (IL4), rs4423003 (CHIA), rs2243283 (IL4), rs12495941 (ADIPOQ), rs2243268 (IL4), and rs2291427 (ALOX5) in African American children had 77% discriminate power between asthmatic and non-allergic individuals. The combination of genotypes in these interactive SNPs can help to pin-point individuals with greater asthma risk (
Further analysis using Ingenuity Pathways Analysis (IPA) revealed that these RP based interactive genes belong to an interconnected and interactive gene network, indicating that they are involved in related biological activities and have functional commonalities (
IPA network for recursive partitioning prioritized genes. Genes with red node are focused genes in our analysis, others are generated through the network analysis from the Ingenuity Pathways Knowledge Base (
In critically evaluating our results, it is important to note that our analyses, and hence interpretations, are subject to several limitations. First, SNP allele frequencies and association were determined by using relatively small sample sizes (see Methods). However, it should be noted that large sample sizes may not help powering genetic studies and improve our understanding of the genetic underpinnings of allergy phenotypes as much as precise phenotyping
In summary, through our systematic and comprehensive screen of variants in asthmatic children who live in the same geographic region, we have demonstrated the importance of IL4 genetic variation in both Caucasians and African American. Variants found in populations of both African and European ancestry may represent more universally important genes to the disorder
Allele frequency differences (delta) between Caucasian and African American for asthma and non-allergic controls, respectively.
(TIF)
Significant SNPs by gene in Caucasian population
(DOC)
Significant SNPs by gene in African American population
(DOC)
The authors thank the physicians, nurses and staff of Cincinnati Children's Hospital Medical Center Allergy and Immunology clinics, Pulmonary clinics, Dermatology clinics, Headache Center clinics, Dental clinics, Orthopedic clinics and Emergency Department as well as the investigators and staff of the Genomic Control Cohort. We thank all the patients and their families who participated in this study. The datasets used for the replication analyses described in this manuscript were obtained from dbGaP through dbGaP accession number phs000166.v2.p1.