Advertisement

Genetic ancestry and its association with asthma exacerbations among African American subjects with asthma

Published:October 15, 2012DOI:https://doi.org/10.1016/j.jaci.2012.09.001

      Background

      There are large and persisting disparities in severe asthma exacerbations by race-ethnicity, and African American subjects are among those at greatest risk. It is unclear whether this increased risk solely represents differences in environmental exposures and health care or whether there is a predisposing genetic component.

      Objective

      We sought to assess the relationship between genetic ancestry and severe exacerbations among African American subjects with asthma.

      Methods

      Participants were part of the Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-ethnicity (SAPPHIRE). These subjects were 12 to 56 years of age, received care from a single large health system, and had a physician's diagnosis of asthma. Genetic ancestry was estimated by using a set of validated ancestry informative markers. Severe exacerbations (ie, asthma-related emergency department visits, hospitalizations, and burst oral steroid use) were prospectively identified from health care claims.

      Results

      We assessed genetic ancestry in 392 African American subjects with asthma. The average proportion of African ancestry was 76.1%. A significant interaction was identified between ancestry and sex on severe exacerbations, such that the risk was significantly higher with increasing African ancestry among male but not female subjects. The association among male subjects persisted after adjusting for potential confounders (relative rate, 4.30 for every 20% increase in African ancestry; P = .029).

      Conclusions

      African ancestry was significantly and positively associated with severe exacerbations among male African American subjects. These findings suggest that a portion of the risk of asthma exacerbations in this high-risk group is attributable to a genetic risk factor that partitions with ancestry.

      Key words

      Abbreviations used:

      AIM (Ancestry informative marker), ED (Emergency department), ICS (Inhaled corticosteroid), RR (Relative rate), SAPPHIRE (Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-ethnicity)
      Asthma accounts for approximately 14 million days of missed school and 100 million days of restricted activity yearly,
      Self-reported asthma prevalence and control among adults—United States, 2001.
      and direct medical expenditures for asthma exceed $37 billion annually.
      • Kamble S.
      • Bharmal M.
      Incremental direct expenditure of treating asthma in the United States.
      As much as 43% of these costs might be attributable to asthma exacerbations.
      • Weiss K.B.
      • Gergen P.J.
      • Hodgson T.A.
      An economic evaluation of asthma in the United States.
      Moreover, the burden of asthma is not shared equally among groups. For example, in 1999, the prevalence of self-reported asthma among African American subjects was 42.7 per 1000 compared with a prevalence of 37.6 per 1000 among white subjects.
      • Mannino D.M.
      • Homa D.M.
      • Akinbami L.J.
      • Moorman J.E.
      • Gwynn C.
      • Redd S.C.
      Surveillance for asthma—United States, 1980-1999.
      However, even more dramatic were the differences in asthma-related emergency department (ED) visits, hospitalizations, and deaths, which showed rates up to 3 to 5 times higher in African American compared with white patients.
      • Mannino D.M.
      • Homa D.M.
      • Akinbami L.J.
      • Moorman J.E.
      • Gwynn C.
      • Redd S.C.
      Surveillance for asthma—United States, 1980-1999.
      • Miller J.E.
      The effects of race/ethnicity and income on early childhood asthma prevalence and health care use.
      Asthma mortality and hospitalization among children and young adults—United States, 1980-1993.
      We have previously shown that response to inhaled corticosteroids (ICSs) does not appear to differ by race-ethnicity or genetic ancestry,
      • Gould W.
      • Peterson E.L.
      • Karungi G.
      • Zoratti A.
      • Gaggin J.
      • Toma G.
      • et al.
      Factors predicting inhaled corticosteroid responsiveness in African American patients with asthma.
      and we have shown that race-ethnicity appears to still be a risk factor for asthma exacerbations, even accounting for asthma controller medication use and the level of adherence.
      • Williams L.K.
      • Peterson E.L.
      • Wells K.
      • Ahmedani B.K.
      • Kumar R.
      • Burchard E.G.
      • et al.
      Quantifying the proportion of severe asthma exacerbations attributable to inhaled corticosteroid nonadherence.
      In addition, recent genome-wide association studies have demonstrated differences in the genetic predictors of asthma by race-ethnicity.
      • Sleiman P.M.
      • Flory J.
      • Imielinski M.
      • Bradfield J.P.
      • Annaiah K.
      • Willis-Owen S.A.
      • et al.
      Variants of DENND1B associated with asthma in children.
      • Torgerson D.G.
      • Ampleford E.J.
      • Chiu G.Y.
      • Gauderman W.J.
      • Gignoux C.R.
      • Graves P.E.
      • et al.
      Meta-analysis of genome-wide association studies of asthma in ethnically diverse North American populations.
      Therefore it is reasonable to speculate that differences in asthma exacerbation rates might also have a genetic underpinning.
      To assess for the possibility of genetic determinants of asthma exacerbations that differ by race-ethnicity, we examine whether genetic African ancestry is an independent predictor of asthma exacerbations among African American participants in the Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-ethnicity (SAPPHIRE). This cohort represents one of the largest and best characterized groups of asthmatic patients in the United States with detailed longitudinal clinical information.

      Methods

       Study population

      This study was approved by the Institutional Review Board of Henry Ford Health System. SAPPHIRE is an ongoing longitudinal cohort study of asthmatic patients that has been described in detail elsewhere.
      • Gould W.
      • Peterson E.L.
      • Karungi G.
      • Zoratti A.
      • Gaggin J.
      • Toma G.
      • et al.
      Factors predicting inhaled corticosteroid responsiveness in African American patients with asthma.
      • Torgerson D.G.
      • Ampleford E.J.
      • Chiu G.Y.
      • Gauderman W.J.
      • Gignoux C.R.
      • Graves P.E.
      • et al.
      Meta-analysis of genome-wide association studies of asthma in ethnically diverse North American populations.
      Patients were eligible for inclusion if they fulfilled the following requirements: age between 12 and 56 years, a physician's diagnosis of asthma, member of the affiliated health plan with both medical and pharmaceutical coverage, and no prior history of congestive heart failure or chronic obstructive pulmonary disease.
      Eligible patients were invited for an initial evaluation that included the completion of a staff-administered questionnaire, pulmonary function testing, assessment of bronchodilator response, and collection of blood samples. Spirometry was performed according to current 2005 American Thoracic Society/European Respiratory Society recommendations.
      • Miller M.R.
      • Hankinson J.
      • Brusasco V.
      • Burgos F.
      • Casaburi R.
      • Coates A.
      • et al.
      Standardisation of spirometry.
      • Miller M.R.
      • Crapo R.
      • Hankinson J.
      • Brusasco V.
      • Burgos F.
      • Casaburi R.
      • et al.
      General considerations for lung function testing.
      Predictive equations from Hankinson et al
      • Hankinson J.L.
      • Odencrantz J.R.
      • Fedan K.B.
      Spirometric reference values from a sample of the general U.S. population.
      were used to estimate expected lung function values according to each participant’s age, sex, and race. We assessed bronchodilator response after administering 360 μg of albuterol sulfate hydrofluoroalkane from a standard metered-dose inhaler using an AeroChamber Plus Z STAT spacer (Monahan Medical, Plattsburgh, NY). Bronchodilator reversibility was measured as the percentage change in FEV1 before and after albuterol administration.
      • Miller M.R.
      • Hankinson J.
      • Brusasco V.
      • Burgos F.
      • Casaburi R.
      • Coates A.
      • et al.
      Standardisation of spirometry.
      We defined reversibility as an improvement in FEV1 of 12% or greater after albuterol treatment. Each patient's smoking status was assessed on the staff-administered questionnaire by using questions from the National Health and Nutrition Examination Survey (www.cdc.gov/nchs/data/nhanes/nhanes_05_06/fi_smq_d.pdf).
      Longitudinal information on asthma medication use (ie, ICSs and oral corticosteroids) and clinical events (ie, asthma-related ED visits and asthma-related hospitalizations) was available on all SAPPHIRE patients included in the analysis through electronic prescriptions, pharmacy claims, and encounter data routinely maintained by the health system. We have previously validated the clinical algorithms for detecting these events.
      • Williams L.K.
      • Peterson E.L.
      • Wells K.
      • Campbell J.
      • Wang M.
      • Chowdhry V.K.
      • et al.
      A cluster-randomized trial to provide clinicians inhaled corticosteroid adherence information for their patients with asthma.

       Assessment of genetic ancestry

      We isolated genomic DNA from whole-blood samples. Genotyping was performed on a Sequenom iPLEX platform (Sequenom, San Diego, Calif) for a set of previously validated ancestry informative markers (AIMs).
      • Yaeger R.
      • Avila-Bront A.
      • Abdul K.
      • Nolan P.C.
      • Grann V.R.
      • Birchette M.G.
      • et al.
      Comparing genetic ancestry and self-described race in African Americans born in the United States and in Africa.
      For the purposes of this study, we used a subset of 59 markers that were informative for estimating West African (henceforth referred to as African) and European ancestry. The contribution of each marker for determining a subject’s ancestry is based primarily on differences in allele frequency for that polymorphism between ancestral populations. As described in detail elsewhere,
      • Pritchard J.K.
      • Stephens M.
      • Donnelly P.
      Inference of population structure using multilocus genotype data.
      we estimated a single overall proportion of African ancestry for each study participant by using the program STRUCTURE, which analyzed the genotype calls at the 59 AIMs collectively. It was this single, individual-level estimate of overall African ancestry that was used in the regression models described below. Of note, because we assumed admixture from 2 ancestral populations (ie, African and European), the estimated proportion of European ancestry was 100% minus the percentage of African ancestry. Earlier studies have shown that 40 biallelic AIMs are sufficient to estimate individual ancestry with an SE of 0.1 or less when the study population consists of 2 admixed ancestral populations.
      • Hoggart C.J.
      • Parra E.J.
      • Shriver M.D.
      • Bonilla C.
      • Kittles R.A.
      • Clayton D.G.
      • et al.
      Control of confounding of genetic associations in stratified populations.

       Statistical analysis

      We first calculated descriptive statistics for the 392 participants. These measures included means and SDs for continuously distributed variables (eg, proportion of African ancestry, age, and duration of asthma) and numbers and percentages for categorical variables (eg, sex and smoking status).
      The primary outcome was a severe exacerbation defined as one of the following: burst use of oral corticosteroids, an asthma-related ED visit, or an asthma-related hospitalization. These have been recognized as the core measures for severe asthma exacerbations by the American Thoracic Society, the European Respiratory Society, and the National Institutes of Health.
      • Reddel H.K.
      • Taylor D.R.
      • Bateman E.D.
      • Boulet L.P.
      • Boushey H.A.
      • Busse W.W.
      • et al.
      An official American Thoracic Society/European Respiratory Society statement: asthma control and exacerbations: standardizing endpoints for clinical asthma trials and clinical practice.
      • Fuhlbrigge A.
      • Peden D.
      • Apter A.J.
      • Boushey H.A.
      • Camargo C.A.
      • Gern J.
      • et al.
      Asthma outcomes: exacerbations.
      Because our primary exploratory variable was African ancestry, we restricted our analysis to subjects whose self-reported race was African American. We used negative binomial regression to regress the number of severe exacerbations on African ancestry. We selected negative binomial regression because this method allows for additional variance within defined groups (rather than assuming a fixed rate, λ); therefore it is robust to the presence of additional unmeasured explanatory variables.
      • Simonoff J.S.
      Analyzing categorical data.
      Our first regression model (model 1) assessed the univariable relationship between African ancestry and exacerbations. Our next model (model 2) adjusted for potential confounders, including the patient's age, sex, percent predicted FEV1, percentage of bronchodilator reversibility, smoking status (ie, indicator variables for current and past smoking compared with never smoking), ICS use at the time of initial evaluation, and age of asthma onset. Our third model (model 3) adjusted for all of the potential confounders previously mentioned but also included an interaction term between sex and ancestry (to assess for potential differences in the relationship between ancestry and exacerbations by sex). Given an apparent interaction by sex, we performed stratified analyses for the relationship between African ancestry and exacerbations among men and women separately. A relative rate (RR) of greater than 1 from the stratified analyses can be interpreted as increased likelihood of a severe exacerbation for the factor assessed; conversely, an RR of less than 1 can be interpreted as lower likelihood of a severe exacerbation. Our models estimated the RR for each percentage increase in African ancestry on the likelihood of severe exacerbation; parameter estimates from these models were rescaled to present the relationship for a 20% change in African ancestry in the tables. The stratified analyses also accounted for all of the potential confounders described above (with the exception of sex), and therefore all of the RRs presented are adjusted for these other variables.
      Power estimations were based on the total available sample. We estimated the power of our negative binomial analysis using calculations for a case-control study estimating RRs. Accordingly, we assumed admixture was a binary variable split at 80% ancestry; this resulted in 79 male and 127 female subjects with less than 80% African ancestry and 66 male and 120 female subjects with 80% or greater African ancestry. We also assumed that the prevalence of the primary outcome was 12% in the group with lower African ancestry. This gave us 80% power to detect an RR of 2.8 for male subjects and an RR of 2.3 for female subjects with a 2-sided α level of .05.
      We used the deviance statistic to measure the fit of the negative binomial model.
      • Simonoff J.S.
      Analyzing categorical data.
      The approximate distribution of this statistic is χ2, and it was 62.3 with 136 df for male subjects and 204.8 with 238 df for female subjects. The associated P value for both male and female subjects was greater than .90, suggesting that model fit was adequate.
      All analyses were performed with SAS version 9.2 software (SAS Institute, Cary, NC).
      SAS Institute Inc
      SAS/STAT users guide. Version 9.2.
      We accepted a type 1 error rate of 5%, and therefore a P value of less than .05 was considered statistically significant.

      Results

      Table I shows the characteristics of 392 self-identified African American subjects with asthma from the SAPPHIRE cohort. The average age of the study population was 31.2 years, but approximately two thirds (69.1%) had asthma since childhood. Nearly one third (32.4%) of patients demonstrated bronchodilator reversibility, and 18.1% had prescription fills suggesting the use of an ICS at the time of their initial visits. The estimated mean proportion of African ancestry among the African American participants was 76.1% (SD, 9.6%; range, 29.4% to 96.5%). This estimate of genetic African ancestry is consistent with other studies of African Americans in the United States.
      • Parra E.J.
      • Marcini A.
      • Akey J.
      • Martinson J.
      • Batzer M.A.
      • Cooper R.
      • et al.
      Estimating African American admixture proportions by use of population-specific alleles.
      • Tsai H.J.
      • Kho J.Y.
      • Shaikh N.
      • Choudhry S.
      • Naqvi M.
      • Navarro D.
      • et al.
      Admixture-matched case-control study: a practical approach for genetic association studies in admixed populations.
      • Tishkoff S.A.
      • Reed F.A.
      • Friedlaender F.R.
      • Ehret C.
      • Ranciaro A.
      • Froment A.
      • et al.
      The genetic structure and history of Africans and African Americans.
      • Bryc K.
      • Auton A.
      • Nelson M.R.
      • Oksenberg J.R.
      • Hauser S.L.
      • Williams S.
      • et al.
      Genome-wide patterns of population structure and admixture in West Africans and African Americans.
      Table ICharacteristics of African American subjects from the SAPPHIRE cohort with longitudinal clinical information (n = 392)
      Each study subject had a single estimate for proportion of African ancestry. This measure of global ancestry was determined by using 59 AIMs, as described in the Methods section. Shown is the average proportion of African ancestry across all study subjects (n = 392). Individual African ancestry ranged from 29.4% to 96.5%.
      Characteristic
      Proportion of African ancestry, mean ± SD (range)
      Each study subject had a single estimate for proportion of African ancestry. This measure of global ancestry was determined by using 59 AIMs, as described in the Methods section. Shown is the average proportion of African ancestry across all study subjects (n = 392). Individual African ancestry ranged from 29.4% to 96.5%.
      76.1 ± 9.6 (29.4-96.5)
      Age (y), mean ± SD31.2 ± 15.2
      Female sex, no. (%)247 (63.0)
      Duration of asthma (y), mean ± SD17.5 ± 12.5
      Age of asthma onset, no. (%)
       Childhood onset (<18 y of age)271 (69.1)
       Adult onset (≥18 y of age)121 (30.9)
      Smoking status, no. (%)
       Never313 (79.8)
       Past40 (10.2)
       Current39 (9.9)
      Percent predicted FEV1, mean ± SD89.6 ± 17.8
      Bronchodilator reversibility (% change), mean ± SD0.10 ± 0.12
      Bronchodilator reversibility (>12%), no. (%)127 (32.4)
      ICS use, no. (%)71 (18.1)
      Each study subject had a single estimate for proportion of African ancestry. This measure of global ancestry was determined by using 59 AIMs, as described in the Methods section. Shown is the average proportion of African ancestry across all study subjects (n = 392). Individual African ancestry ranged from 29.4% to 96.5%.
      We next assessed the relationship between the proportion of African ancestry and the risk of an asthma exacerbation. In the initial unadjusted and adjusted analyses (Table II), we did not see a relationship between ancestry and asthma exacerbations (P = .568 and P = .257, respectively). However, we did observe a significant sex-ancestry interaction (P = .010), and after accounting for this interaction, the relationship between ancestry and asthma exacerbations was also statistically significant (P = .009). Not surprisingly, we observed a significant inverse association between measured percent predicted FEV1 and exacerbations in both multivariable models. We also found a positive association between baseline ICS use and asthma exacerbations, as would be expected if subjects with more serious asthma were prescribed controller therapy.
      Table IIUnadjusted and adjusted relationships between African ancestry and asthma exacerbations among African American participants in the SAPPHIRE cohort
      VariableModel 1
      Model 1 includes just the variable representing the proportion of African ancestry. The parameter estimate represents the effect of a 20% increase in African ancestry.
      Model 2
      Model 2 includes African ancestry as in model 1 but adjusts for all other variables shown. These variables include age (per 10-year increment), female sex (female = 1, male = 0), childhood asthma onset (<18 years = 1, ≥18 years = 0), smoking status (separate indicator variables for current smoking and past smoking = 1, never smoker = 0), percent predicted FEV1 (per 10% increase), bronchodilator reversibility (>12% improvement in FEV1 = 1, ≤12% = 0), and ICS use at the time of study enrollment assessed by pharmacy fill data (yes = 1, no = 0).
      Model 3
      Model 3 includes all covariates included in models 1 and 2 but also includes an interaction term between African ancestry and sex (coded as described above).
      Parameter estimate (β)
      Parameter estimates are of the form y = β1x1 + β2x2 +…+ βixi + βintx1x2, where y represents the number of exacerbations, xi represents the independent variable of interest, βi represents the effect estimate for that independent variable, and βint represents the effect estimate for the interaction of 2 of the covariates. Parameter estimates of greater than 0 indicate a positive association between the factor and the likelihood of an asthma exacerbation, and parameter estimates of less than 0 indicate an inverse association between the factor and the likelihood of an exacerbation.
      P valueParameter estimate (β)
      Parameter estimates are of the form y = β1x1 + β2x2 +…+ βixi + βintx1x2, where y represents the number of exacerbations, xi represents the independent variable of interest, βi represents the effect estimate for that independent variable, and βint represents the effect estimate for the interaction of 2 of the covariates. Parameter estimates of greater than 0 indicate a positive association between the factor and the likelihood of an asthma exacerbation, and parameter estimates of less than 0 indicate an inverse association between the factor and the likelihood of an exacerbation.
      P valueParameter estimate (β)
      Parameter estimates are of the form y = β1x1 + β2x2 +…+ βixi + βintx1x2, where y represents the number of exacerbations, xi represents the independent variable of interest, βi represents the effect estimate for that independent variable, and βint represents the effect estimate for the interaction of 2 of the covariates. Parameter estimates of greater than 0 indicate a positive association between the factor and the likelihood of an asthma exacerbation, and parameter estimates of less than 0 indicate an inverse association between the factor and the likelihood of an exacerbation.
      P value
      African ancestry0.12.5680.24.2571.08.009
      Age0.10.3120.08.399
      Female sex0.29.2394.94.010
      Ancestry-sex interaction term−5.94.014
      Childhood asthma onset0.30.2900.29.306
      Current smoker0.32.3270.43.182
      Past smoker−0.11.763−0.04.899
      Percent predicted FEV1−0.14.041−0.13.052
      Bronchodilator reversibility0.16.5130.16.528
      ICS use0.55.0320.57.024
      Model 1 includes just the variable representing the proportion of African ancestry. The parameter estimate represents the effect of a 20% increase in African ancestry.
      Model 2 includes African ancestry as in model 1 but adjusts for all other variables shown. These variables include age (per 10-year increment), female sex (female = 1, male = 0), childhood asthma onset (<18 years = 1, ≥18 years = 0), smoking status (separate indicator variables for current smoking and past smoking = 1, never smoker = 0), percent predicted FEV1 (per 10% increase), bronchodilator reversibility (>12% improvement in FEV1 = 1, ≤12% = 0), and ICS use at the time of study enrollment assessed by pharmacy fill data (yes = 1, no = 0).
      Model 3 includes all covariates included in models 1 and 2 but also includes an interaction term between African ancestry and sex (coded as described above).
      § Parameter estimates are of the form y = β1x1 + β2x2 +…+ βixi + βintx1x2, where y represents the number of exacerbations, xi represents the independent variable of interest, βi represents the effect estimate for that independent variable, and βint represents the effect estimate for the interaction of 2 of the covariates. Parameter estimates of greater than 0 indicate a positive association between the factor and the likelihood of an asthma exacerbation, and parameter estimates of less than 0 indicate an inverse association between the factor and the likelihood of an exacerbation.
      Given the apparent interaction between ancestry and sex on asthma exacerbations, we repeated the analysis after stratifying by sex (Table III). Among male participants, the relative rate of a severe exacerbation was increased more than 4-fold for every 20% increase in the proportion of African ancestry (RR, 4.30; P = .029). Among female participants, there was not a significant relationship between ancestry and asthma exacerbations (RR, 0.92; P = .678). There was also a significant protective association between increasing FEV1 and risk of exacerbation among women (RR, 0.82 per 10% increase in the measured percent predicted FEV1; P = .004).
      Table IIIAdjusted relationship between African ancestry and asthma exacerbations among African American participants in the SAPPHIRE cohort stratified by sex
      VariableMale subjects (n = 145)Female subjects (n = 247)
      Adjusted RR (95% CI)
      Models are adjusted for all of the following variables: African ancestry (per 20% increase in African ancestry), age (per 10-year increment), childhood asthma onset (<18 years of age = 1, ≥18 years of age = 0), smoking status (separate indicator variables for current smoking and past smoking = 1, never smoker = 0), percent predicted FEV1 (per 10% increase), bronchodilator reversibility (>12% improvement in FEV1 = 1, ≤12% = 0), and ICS use at the time of study enrollment assessed by pharmacy fill data (yes = 1, no = 0).
      P valueAdjusted RR (95% CI)
      Models are adjusted for all of the following variables: African ancestry (per 20% increase in African ancestry), age (per 10-year increment), childhood asthma onset (<18 years of age = 1, ≥18 years of age = 0), smoking status (separate indicator variables for current smoking and past smoking = 1, never smoker = 0), percent predicted FEV1 (per 10% increase), bronchodilator reversibility (>12% improvement in FEV1 = 1, ≤12% = 0), and ICS use at the time of study enrollment assessed by pharmacy fill data (yes = 1, no = 0).
      P value
      African ancestry4.30 (1.16-15.88).0290.92 (0.61-1.39).678
      Age1.42 (0.87-2.33).1661.02 (0.83-1.25).841
      Asthma duration1.02 (0.19-5.51).9841.39 (0.80-2.40).239
      Current smoker2.40 (0.42-13.75).3251.41 (0.74-2.68).297
      Past smoker0.33 (0.04-3.04).3311.16 (0.60-2.27).658
      Percent predicted FEV11.09 (0.74-1.62).6600.82 (0.71-0.94).004
      Bronchodilator reversibility2.08 (0.61-7.06).2391.02 (0.62-1.71).925
      ICS use1.92 (0.60-6.18).2751.61 (0.93-2.78).087
      Models are adjusted for all of the following variables: African ancestry (per 20% increase in African ancestry), age (per 10-year increment), childhood asthma onset (<18 years of age = 1, ≥18 years of age = 0), smoking status (separate indicator variables for current smoking and past smoking = 1, never smoker = 0), percent predicted FEV1 (per 10% increase), bronchodilator reversibility (>12% improvement in FEV1 = 1, ≤12% = 0), and ICS use at the time of study enrollment assessed by pharmacy fill data (yes = 1, no = 0).
      As an additional post hoc analysis, we included patient-reported passive smoke exposure as a separate covariate in our regression models. Inclusion of this variable did not significantly change any of the aforementioned associations (data not shown).

      Discussion

      For the first time, we note a significant relationship between genetic ancestry and asthma exacerbations among African American men, such that the risk of a severe exacerbation appeared to be 4 times greater for every 20% increase in African ancestry. In African American female subjects we did not observe a significant relationship between African ancestry and severe asthma exacerbations.
      It is important to interpret our findings in the context of the epidemiology of asthma. First, based on national surveillance data from the United States, African American subjects have rates of asthma-related ED visits, hospitalizations, and death that are 2 to 3 times higher when compared with those of white subjects.
      • Moorman J.E.
      • Rudd R.A.
      • Johnson C.A.
      • King M.
      • Minor P.
      • Bailey C.
      • et al.
      National surveillance for asthma—United States, 1980-2004.
      Second, the prevalence of asthma and wheezing differs by age and sex. Specifically, wheezing and asthma are more common in prepubescent boys when compared with girls; however, this pattern reverses by young adulthood.
      • Venn A.
      • Lewis S.
      • Cooper M.
      • Hill J.
      • Britton J.
      Questionnaire study of effect of sex and age on the prevalence of wheeze and asthma in adolescence.
      • Anderson H.R.
      • Pottier A.C.
      • Strachan D.P.
      Asthma from birth to age 23: incidence and relation to prior and concurrent atopic disease.
      This pattern might be attributable to differences in lung growth and forced expiratory volume by age and sex
      • Hibbert M.
      • Lannigan A.
      • Raven J.
      • Landau L.
      • Phelan P.
      Gender differences in lung growth.
      or possibly the influence of estrogen (endogenous or exogenous) on asthma risk.
      • Troisi R.J.
      • Speizer F.E.
      • Willett W.C.
      • Trichopoulos D.
      • Rosner B.
      Menopause, postmenopausal estrogen preparations, and the risk of adult-onset asthma. A prospective cohort study.
      These epidemiologic observations suggest that differences in asthma presentation by race-ethnicity and sex might be due to genetics or epistasis (ie, gene-gene interactions).
      There are well-described differences in lung function
      • Hankinson J.L.
      • Odencrantz J.R.
      • Fedan K.B.
      Spirometric reference values from a sample of the general U.S. population.
      • Zhang Y.
      • McConnell R.
      • Gilliland F.
      • Berhane K.
      Ethnic differences in the effect of asthma on pulmonary function in children.
      and ICS use
      • Apter A.J.
      • Boston R.C.
      • George M.
      • Norfleet A.L.
      • Tenhave T.
      • Coyne J.C.
      • et al.
      Modifiable barriers to adherence to inhaled steroids among adults with asthma: it's not just black and white.
      • Williams L.K.
      • Joseph C.L.
      • Peterson E.L.
      • Moon C.
      • Xi H.
      • Krajenta R.
      • et al.
      Race-ethnicity, crime, and other factors associated with adherence to inhaled corticosteroids.
      • Wells K.
      • Pladevall M.
      • Peterson E.L.
      • Campbell J.
      • Wang M.
      • Lanfear D.E.
      • et al.
      Race-ethnic differences in factors associated with inhaled steroid adherence among adults with asthma.
      by race-ethnicity, and both of these factors are strongly associated with asthma exacerbations.
      • Fuhlbrigge A.L.
      • Kitch B.T.
      • Paltiel A.D.
      • Kuntz K.M.
      • Neumann P.J.
      • Dockery D.W.
      • et al.
      FEV(1) is associated with risk of asthma attacks in a pediatric population.
      • Williams L.K.
      • Pladevall M.
      • Xi H.
      • Peterson E.L.
      • Joseph C.
      • Lafata J.E.
      • et al.
      Relationship between adherence to inhaled corticosteroids and poor outcomes among adults with asthma.
      Recently, we have shown African ancestry to be inversely associated with lung function in both men and women
      • Kumar R.
      • Seibold M.A.
      • Aldrich M.C.
      • Williams L.K.
      • Reiner A.P.
      • Colangelo L.
      • et al.
      Genetic ancestry in lung-function predictions.
      but not associated with response to ICS medication.
      • Gould W.
      • Peterson E.L.
      • Karungi G.
      • Zoratti A.
      • Gaggin J.
      • Toma G.
      • et al.
      Factors predicting inhaled corticosteroid responsiveness in African American patients with asthma.
      However, in the current study the relationship between genetic ancestry and asthma exacerbation was still present after accounting for differences in lung function and ICS use, suggesting that ancestry is an independent predictor of exacerbations. Flores et al
      • Flores C.
      • Ma S.F.
      • Pino-Yanes M.
      • Wade M.S.
      • Perez-Mendez L.
      • Kittles R.A.
      • et al.
      African ancestry is associated with asthma risk in African Americans.
      examined the relationship between ancestry and asthma diagnosis and found that African ancestry was significantly higher in African American subjects with asthma when compared with unaffected subjects. These investigators also examined the relationship between African ancestry and exacerbations but did not observe a significant association; however, exacerbations were ascertained based on patient self-report, and the study did not examine for differences in risk by sex.
      Women and men might differ in their immune responses. For example, one group demonstrated that PBMCs isolated from women had greater IL-13 and IFN-γ production when exposed to rhinovirus compared with cells from age-matched men.
      • Carroll M.L.
      • Yerkovich S.T.
      • Pritchard A.L.
      • Davies J.M.
      • Upham J.W.
      Adaptive immunity to rhinoviruses: sex and age matter.
      This might have implications for asthma exacerbations because many of these events are triggered by rhinovirus upper respiratory tract infections.
      • Johnston S.L.
      • Pattemore P.K.
      • Sanderson G.
      • Smith S.
      • Campbell M.J.
      • Josephs L.K.
      • et al.
      The relationship between upper respiratory infections and hospital admissions for asthma: a time-trend analysis.
      In addition, a number of other immunologic conditions, such as multiple sclerosis
      • Wallin M.T.
      • Page W.F.
      • Kurtzke J.F.
      Multiple sclerosis in US veterans of the Vietnam era and later military service: race, sex, and geography.
      and systemic lupus erythematosus,
      • Bae S.C.
      • Fraser P.
      • Liang M.H.
      The epidemiology of systemic lupus erythematosus in populations of African ancestry: a critical review of the “prevalence gradient hypothesis.”.
      differ by both sex and race-ethnicity. Research has demonstrated that these conditions also vary by genetic ancestry,
      • Molokhia M.
      • Hoggart C.
      • Patrick A.L.
      • Shriver M.
      • Parra E.
      • Ye J.
      • et al.
      Relation of risk of systemic lupus erythematosus to west African admixture in a Caribbean population.
      and investigators have begun to use this relationship to map for disease-related genes.
      • Reich D.
      • Patterson N.
      • De Jager P.L.
      • McDonald G.J.
      • Waliszewska A.
      • Tandon A.
      • et al.
      A whole-genome admixture scan finds a candidate locus for multiple sclerosis susceptibility.
      Our study had important limitations. First, the study was carried out at one site, and as a result, we might not be able to generalize our findings to other groups of African American subjects. Nevertheless, our study population had a similar admixture, as has been described for other African American groups throughout the United States.
      • Parra E.J.
      • Marcini A.
      • Akey J.
      • Martinson J.
      • Batzer M.A.
      • Cooper R.
      • et al.
      Estimating African American admixture proportions by use of population-specific alleles.
      In addition, by studying one geographic area, our study might have been less susceptible to confounding by differences in ambient exposures. This is not to say subjects in our study could not have experienced different environmental exposures as a result of differences in ancestry. For example, African ancestry is associated with darker skin color,
      • Parra E.J.
      • Kittles R.A.
      • Shriver M.D.
      Implications of correlations between skin color and genetic ancestry for biomedical research.
      • Shriver M.D.
      • Parra E.J.
      • Dios S.
      • Bonilla C.
      • Norton H.
      • Jovel C.
      • et al.
      Skin pigmentation, biogeographical ancestry and admixture mapping.
      which might have resulted in discrimination and other untoward events that varied proportionally to the latter.
      • Krieger N.
      • Sidney S.
      • Coakley E.
      Racial discrimination and skin color in the CARDIA study: implications for public health research. Coronary Artery Risk Development in Young Adults.
      However, if our findings were confounded by a relationship between these external exposures (eg, discrimination) and ancestry, we would have expected to see an association in both men and women.
      Second, we used only 59 AIMs to estimate ancestry. Although earlier studies have indicated that as few as 40 AIMs are sufficient for estimating ancestry in groups with primarily 2 admixed ancestral populations,
      • Hoggart C.J.
      • Parra E.J.
      • Shriver M.D.
      • Bonilla C.
      • Kittles R.A.
      • Clayton D.G.
      • et al.
      Control of confounding of genetic associations in stratified populations.
      greater numbers of AIMs might improve the precision of the estimate and current methods can use data derived from genome-wide arrays.
      • Price A.L.
      • Tandon A.
      • Patterson N.
      • Barnes K.C.
      • Rafaels N.
      • Ruczinski I.
      • et al.
      Sensitive detection of chromosomal segments of distinct ancestry in admixed populations.
      Yet this imprecision or misclassification would have likely resulted in our underestimating the true effect of ancestry. Unfortunately, these individual-level estimates of global ancestry do not allow us to localize specific chromosomal regions where ancestry is associated with exacerbations.
      A final limitation is that we did not reassess our findings in a replication population of African American subjects. This was due, in part, to the somewhat unique combination of data available for our study population, a well-characterized, diverse cohort with near-complete capture of longitudinal clinical outcomes. For example, in an earlier study of asthma medication use, we showed that we could capture greater than 99% of prescriptions filled by our covered patient population.
      • Williams L.K.
      • Joseph C.L.
      • Peterson E.L.
      • Wells K.
      • Wang M.
      • Chowdhry V.K.
      • et al.
      Patients with asthma who do not fill their inhaled corticosteroids: a study of primary nonadherence.
      In summary, we found a significant and independent association between genetic ancestry and severe exacerbations among male African American subjects with asthma. To our knowledge, this is the first report of such an association, and it suggests that at least part of the risk of asthma exacerbations is genetic and partitions with ancestry. Our findings also suggest that analytic approaches, such as admixture mapping, might help uncover and localize these genetic determinants.
      • McKeigue P.M.
      Prospects for admixture mapping of complex traits.
      The importance of identifying and understanding the predictors of these potentially life-threatening complications cannot be understated, especially given their frequency and the large and persisting disparities by race-ethnicity.
      Clinical implications
      This study suggests that there is a genetic contribution to asthma exacerbations, which might be identifiable by using approaches that measure and account for individual admixture.

      References

      1. Self-reported asthma prevalence and control among adults—United States, 2001.
        MMWR Morb Mortal Wkly Rep. 2003; 52: 381-384
        • Kamble S.
        • Bharmal M.
        Incremental direct expenditure of treating asthma in the United States.
        J Asthma. 2009; 46: 73-80
        • Weiss K.B.
        • Gergen P.J.
        • Hodgson T.A.
        An economic evaluation of asthma in the United States.
        N Engl J Med. 1992; 326: 862-866
        • Mannino D.M.
        • Homa D.M.
        • Akinbami L.J.
        • Moorman J.E.
        • Gwynn C.
        • Redd S.C.
        Surveillance for asthma—United States, 1980-1999.
        MMWR Surveill Summ. 2002; 51: 1-13
        • Miller J.E.
        The effects of race/ethnicity and income on early childhood asthma prevalence and health care use.
        Am J Public Health. 2000; 90: 428-430
      2. Asthma mortality and hospitalization among children and young adults—United States, 1980-1993.
        MMWR Morb Mortal Wkly Rep. 1996; 45: 350-353
        • Gould W.
        • Peterson E.L.
        • Karungi G.
        • Zoratti A.
        • Gaggin J.
        • Toma G.
        • et al.
        Factors predicting inhaled corticosteroid responsiveness in African American patients with asthma.
        J Allergy Clin Immunol. 2010; 126: 1131-1138
        • Williams L.K.
        • Peterson E.L.
        • Wells K.
        • Ahmedani B.K.
        • Kumar R.
        • Burchard E.G.
        • et al.
        Quantifying the proportion of severe asthma exacerbations attributable to inhaled corticosteroid nonadherence.
        J Allergy Clin Immunol. 2011; 128: 1185-1191
        • Sleiman P.M.
        • Flory J.
        • Imielinski M.
        • Bradfield J.P.
        • Annaiah K.
        • Willis-Owen S.A.
        • et al.
        Variants of DENND1B associated with asthma in children.
        N Engl J Med. 2010; 362: 36-44
        • Torgerson D.G.
        • Ampleford E.J.
        • Chiu G.Y.
        • Gauderman W.J.
        • Gignoux C.R.
        • Graves P.E.
        • et al.
        Meta-analysis of genome-wide association studies of asthma in ethnically diverse North American populations.
        Nat Genet. 2011; 43: 887-892
        • Miller M.R.
        • Hankinson J.
        • Brusasco V.
        • Burgos F.
        • Casaburi R.
        • Coates A.
        • et al.
        Standardisation of spirometry.
        Eur Respir J. 2005; 26: 319-338
        • Miller M.R.
        • Crapo R.
        • Hankinson J.
        • Brusasco V.
        • Burgos F.
        • Casaburi R.
        • et al.
        General considerations for lung function testing.
        Eur Respir J. 2005; 26: 153-161
        • Hankinson J.L.
        • Odencrantz J.R.
        • Fedan K.B.
        Spirometric reference values from a sample of the general U.S. population.
        Am J Respir Crit Care Med. 1999; 159: 179-187
        • Williams L.K.
        • Peterson E.L.
        • Wells K.
        • Campbell J.
        • Wang M.
        • Chowdhry V.K.
        • et al.
        A cluster-randomized trial to provide clinicians inhaled corticosteroid adherence information for their patients with asthma.
        J Allergy Clin Immunol. 2010; 126: 225-231
        • Yaeger R.
        • Avila-Bront A.
        • Abdul K.
        • Nolan P.C.
        • Grann V.R.
        • Birchette M.G.
        • et al.
        Comparing genetic ancestry and self-described race in African Americans born in the United States and in Africa.
        Cancer Epidemiol Biomarkers Prev. 2008; 17: 1329-1338
        • Pritchard J.K.
        • Stephens M.
        • Donnelly P.
        Inference of population structure using multilocus genotype data.
        Genetics. 2000; 155: 945-959
        • Hoggart C.J.
        • Parra E.J.
        • Shriver M.D.
        • Bonilla C.
        • Kittles R.A.
        • Clayton D.G.
        • et al.
        Control of confounding of genetic associations in stratified populations.
        Am J Hum Genet. 2003; 72: 1492-1504
        • Reddel H.K.
        • Taylor D.R.
        • Bateman E.D.
        • Boulet L.P.
        • Boushey H.A.
        • Busse W.W.
        • et al.
        An official American Thoracic Society/European Respiratory Society statement: asthma control and exacerbations: standardizing endpoints for clinical asthma trials and clinical practice.
        Am J Respir Crit Care Med. 2009; 180: 59-99
        • Fuhlbrigge A.
        • Peden D.
        • Apter A.J.
        • Boushey H.A.
        • Camargo C.A.
        • Gern J.
        • et al.
        Asthma outcomes: exacerbations.
        J Allergy Clin Immunol. 2012; 129: S34-S48
        • Simonoff J.S.
        Analyzing categorical data.
        Springer, New York2003
        • SAS Institute Inc
        SAS/STAT users guide. Version 9.2.
        SAS Institute, Cary (NC)2008
        • Parra E.J.
        • Marcini A.
        • Akey J.
        • Martinson J.
        • Batzer M.A.
        • Cooper R.
        • et al.
        Estimating African American admixture proportions by use of population-specific alleles.
        Am J Hum Genet. 1998; 63: 1839-1851
        • Tsai H.J.
        • Kho J.Y.
        • Shaikh N.
        • Choudhry S.
        • Naqvi M.
        • Navarro D.
        • et al.
        Admixture-matched case-control study: a practical approach for genetic association studies in admixed populations.
        Hum Genet. 2006; 118: 626-639
        • Tishkoff S.A.
        • Reed F.A.
        • Friedlaender F.R.
        • Ehret C.
        • Ranciaro A.
        • Froment A.
        • et al.
        The genetic structure and history of Africans and African Americans.
        Science. 2009; 324: 1035-1044
        • Bryc K.
        • Auton A.
        • Nelson M.R.
        • Oksenberg J.R.
        • Hauser S.L.
        • Williams S.
        • et al.
        Genome-wide patterns of population structure and admixture in West Africans and African Americans.
        Proc Natl Acad Sci U S A. 2010; 107: 786-791
        • Moorman J.E.
        • Rudd R.A.
        • Johnson C.A.
        • King M.
        • Minor P.
        • Bailey C.
        • et al.
        National surveillance for asthma—United States, 1980-2004.
        MMWR Surveill Summ. 2007; 56: 1-54
        • Venn A.
        • Lewis S.
        • Cooper M.
        • Hill J.
        • Britton J.
        Questionnaire study of effect of sex and age on the prevalence of wheeze and asthma in adolescence.
        BMJ. 1998; 316: 1945-1946
        • Anderson H.R.
        • Pottier A.C.
        • Strachan D.P.
        Asthma from birth to age 23: incidence and relation to prior and concurrent atopic disease.
        Thorax. 1992; 47: 537-542
        • Hibbert M.
        • Lannigan A.
        • Raven J.
        • Landau L.
        • Phelan P.
        Gender differences in lung growth.
        Pediatr Pulmonol. 1995; 19: 129-134
        • Troisi R.J.
        • Speizer F.E.
        • Willett W.C.
        • Trichopoulos D.
        • Rosner B.
        Menopause, postmenopausal estrogen preparations, and the risk of adult-onset asthma. A prospective cohort study.
        Am J Respir Crit Care Med. 1995; 152: 1183-1188
        • Zhang Y.
        • McConnell R.
        • Gilliland F.
        • Berhane K.
        Ethnic differences in the effect of asthma on pulmonary function in children.
        Am J Respir Crit Care Med. 2011; 183: 596-603
        • Apter A.J.
        • Boston R.C.
        • George M.
        • Norfleet A.L.
        • Tenhave T.
        • Coyne J.C.
        • et al.
        Modifiable barriers to adherence to inhaled steroids among adults with asthma: it's not just black and white.
        J Allergy Clin Immunol. 2003; 111: 1219-1226
        • Williams L.K.
        • Joseph C.L.
        • Peterson E.L.
        • Moon C.
        • Xi H.
        • Krajenta R.
        • et al.
        Race-ethnicity, crime, and other factors associated with adherence to inhaled corticosteroids.
        J Allergy Clin Immunol. 2007; 119: 168-175
        • Wells K.
        • Pladevall M.
        • Peterson E.L.
        • Campbell J.
        • Wang M.
        • Lanfear D.E.
        • et al.
        Race-ethnic differences in factors associated with inhaled steroid adherence among adults with asthma.
        Am J Respir Crit Care Med. 2008; 178: 1194-1201
        • Fuhlbrigge A.L.
        • Kitch B.T.
        • Paltiel A.D.
        • Kuntz K.M.
        • Neumann P.J.
        • Dockery D.W.
        • et al.
        FEV(1) is associated with risk of asthma attacks in a pediatric population.
        J Allergy Clin Immunol. 2001; 107: 61-67
        • Williams L.K.
        • Pladevall M.
        • Xi H.
        • Peterson E.L.
        • Joseph C.
        • Lafata J.E.
        • et al.
        Relationship between adherence to inhaled corticosteroids and poor outcomes among adults with asthma.
        J Allergy Clin Immunol. 2004; 114: 1288-1293
        • Kumar R.
        • Seibold M.A.
        • Aldrich M.C.
        • Williams L.K.
        • Reiner A.P.
        • Colangelo L.
        • et al.
        Genetic ancestry in lung-function predictions.
        N Engl J Med. 2010; 363: 321-330
        • Flores C.
        • Ma S.F.
        • Pino-Yanes M.
        • Wade M.S.
        • Perez-Mendez L.
        • Kittles R.A.
        • et al.
        African ancestry is associated with asthma risk in African Americans.
        PLoS One. 2012; 7: e26807
        • Carroll M.L.
        • Yerkovich S.T.
        • Pritchard A.L.
        • Davies J.M.
        • Upham J.W.
        Adaptive immunity to rhinoviruses: sex and age matter.
        Respir Res. 2010; 11: 184
        • Johnston S.L.
        • Pattemore P.K.
        • Sanderson G.
        • Smith S.
        • Campbell M.J.
        • Josephs L.K.
        • et al.
        The relationship between upper respiratory infections and hospital admissions for asthma: a time-trend analysis.
        Am J Respir Crit Care Med. 1996; 154: 654-660
        • Wallin M.T.
        • Page W.F.
        • Kurtzke J.F.
        Multiple sclerosis in US veterans of the Vietnam era and later military service: race, sex, and geography.
        Ann Neurol. 2004; 55: 65-71
        • Bae S.C.
        • Fraser P.
        • Liang M.H.
        The epidemiology of systemic lupus erythematosus in populations of African ancestry: a critical review of the “prevalence gradient hypothesis.”.
        Arthritis Rheum. 1998; 41: 2091-2099
        • Molokhia M.
        • Hoggart C.
        • Patrick A.L.
        • Shriver M.
        • Parra E.
        • Ye J.
        • et al.
        Relation of risk of systemic lupus erythematosus to west African admixture in a Caribbean population.
        Hum Genet. 2003; 112: 310-318
        • Reich D.
        • Patterson N.
        • De Jager P.L.
        • McDonald G.J.
        • Waliszewska A.
        • Tandon A.
        • et al.
        A whole-genome admixture scan finds a candidate locus for multiple sclerosis susceptibility.
        Nat Genet. 2005; 37: 1113-1118
        • Parra E.J.
        • Kittles R.A.
        • Shriver M.D.
        Implications of correlations between skin color and genetic ancestry for biomedical research.
        Nat Genet. 2004; 36: S54-S60
        • Shriver M.D.
        • Parra E.J.
        • Dios S.
        • Bonilla C.
        • Norton H.
        • Jovel C.
        • et al.
        Skin pigmentation, biogeographical ancestry and admixture mapping.
        Hum Genet. 2003; 112: 387-399
        • Krieger N.
        • Sidney S.
        • Coakley E.
        Racial discrimination and skin color in the CARDIA study: implications for public health research. Coronary Artery Risk Development in Young Adults.
        Am J Public Health. 1998; 88: 1308-1313
        • Price A.L.
        • Tandon A.
        • Patterson N.
        • Barnes K.C.
        • Rafaels N.
        • Ruczinski I.
        • et al.
        Sensitive detection of chromosomal segments of distinct ancestry in admixed populations.
        PLoS Genet. 2009; 5: e1000519
        • Williams L.K.
        • Joseph C.L.
        • Peterson E.L.
        • Wells K.
        • Wang M.
        • Chowdhry V.K.
        • et al.
        Patients with asthma who do not fill their inhaled corticosteroids: a study of primary nonadherence.
        J Allergy Clin Immunol. 2007; 120: 1153-1159
        • McKeigue P.M.
        Prospects for admixture mapping of complex traits.
        Am J Hum Genet. 2005; 76: 1-7