α1-Antitrypsin Gene Variation Associates with Asthma Exacerbations and Related Health Care Utilization

Victor E Ortega; Vickram Tejwani; Abhishek Kumar Shrivastav; Sara Pasha; Joe G Zein; Meher Boorgula; Mario Castro; Loren Denlinger; Serpil C Erzurum; John V Fahy; Elliot Israel; Nizar N Jarjour; Bruce Levy; David Mauger; Wendy C Moore; Sally E Wenzel; Prescott Woodruff; Gregory A Hawkins; Eugene R Bleecker; Deborah A Meyers

doi:10.1016/j.jaip.2025.01.039

. Author manuscript; available in PMC: 2026 Jun 23.

Published in final edited form as: J Allergy Clin Immunol Pract. 2025 Feb 13;13(7):1634–1646.e7. doi: 10.1016/j.jaip.2025.01.039

α₁-Antitrypsin Gene Variation Associates with Asthma Exacerbations and Related Health Care Utilization

Victor E Ortega ¹, Vickram Tejwani ^2,³, Abhishek Kumar Shrivastav ¹, Sara Pasha ⁴, Joe G Zein ¹, Meher Boorgula ⁵, Mario Castro ⁶, Loren Denlinger ⁷, Serpil C Erzurum ⁸, John V Fahy ⁹, Elliot Israel ¹⁰, Nizar N Jarjour ⁷, Bruce Levy ¹⁰, David Mauger ¹¹, Wendy C Moore ¹², Sally E Wenzel ¹³, Prescott Woodruff ¹⁴, Gregory A Hawkins ¹⁵, Eugene R Bleecker ¹, Deborah A Meyers ¹, for the NHLBI Severe Asthma Research Program (SARP)

¹Department of Internal Medicine, Division of Respiratory Medicine, Mayo Clinic, Scottsdale, AZ

²Department of Pulmonary Medicine, Integrated Hospital Care Institute, Cleveland Clinic, Cleveland, OH

³Department of Systems Biology and Genome Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH

⁴Division of Pulmonary, Critical Care, and Sleep Medicine, University of Kentucky, Lexington, KY

⁵University of Colorado Anschutz Medical Campus, Denver, CO

⁶Department of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, University of Kansas Medical Center, Kansas City, KS

⁷Department of Medicine, Division of Allergy, Pulmonary and Critical Care Medicine, University of Wisconsin-Madison, Madison WI

⁸Department of Inflammation and Immunity, Lerner Research Institute, Cleveland Clinic, Cleveland, OH

⁹Department of Medicine, University of California San Francisco, San Francisco, CA

¹⁰Department of Pulmonary and Critical Care Medicine and Allergy and Immunology, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA

¹¹Pennsylvania State University, University Park, PA

¹²Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC

¹³Department of Environmental and Occupational Health, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA

¹⁴Division of Pulmonary and Critical Care Medicine, Department of Medicine, Cardiovascular Research Institute, University of California, San Francisco, CA

¹⁵Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC.

Author Contributions:

Victor E. Ortega, MD, PhD: study design, data quality control and harmonization, data analysis, manuscript preparation.

Vickram Tejwani, MD: data quality control and harmonization, data analysis, manuscript preparation.

Abhishek Shrivastav: data quality control and harmonization, data analysis, manuscript preparation.

Sara Pasha, MD: study design, data quality control and harmonization, data analysis.

Joe G. Zein, MD, PhD: study design, data quality control and harmonization, data analysis, manuscript preparation.

Meher Boorgula, MS: data quality control and harmonization, data analysis, manuscript preparation.

Mario Castro, MD, MPH: study design, data collection, critical review of manuscript.

Loren Denlinger, MD, PhD: study design, data collection, critical review of manuscript.

Serpil C. Erzurum, MD: study design, data collection, critical review of manuscript.

John Fahy, MD: study design, data collection, critical review of manuscript.

Elliot Israel, MD: study design, data collection, critical review of manuscript.

Nizar N. Jarjour, MD: study design, data collection, critical review of manuscript.

Bruce Levy, MD: study design, data collection, critical review of manuscript.

David Mauger, PhD: study design, data collection, critical review of manuscript.

Sally E. Wenzel, MD: study design, data collection, critical review of manuscript.

Prescott Woodruff, MD, MPH: study design, data collection, critical review of manuscript.

Gregory A. Hawkins, PhD: study design, data collection, critical review of manuscript.

Eugene R. Bleecker, MD: data quality control and harmonization, data analysis, critical review of manuscript.

Deborah A. Meyers, PhD: data quality control and harmonization, data analysis, critical review of manuscript.

^✉

Corresponding Author: Victor E. Ortega, MD, PhD, ATSF, Professor of Medicine, Department of Internal Medicine, Division of Respiratory Medicine, Associate Director, Center for Individualized Medicine in Arizona, Mayo Clinic, 13400 E. Shea Boulevard, Scottsdale, Arizona, 85259, Ortega.Victor@mayo.edu

PMCID: PMC13285010 NIHMSID: NIHMS2058758 PMID: 39954727

Abstract

Background:

α₁-antitrypsin deficiency is caused by rare pathogenic variants in SERPINA1, the strongest genetic risk factor for COPD. Few studies have evaluated the effects of SERPINA1 variation on asthma severity accounting for critical gene-by-environment interactions with smoking.

Objective:

To characterize the influence of SERPINA1 variation on asthma severity.

Methods:

DNA samples from 847 non-Hispanic whites and 446 African Americans from the Severe Asthma Research Program underwent SERPINA1 resequencing to identify rare variants. An independent population of 1,955 individuals with asthma and α₁-antitrypsin concentrations from a Cleveland Clinic Health System (CCHS) database were evaluated for severity measures.

Measurements and Main Results:

In whites, a history of minimum smoking significantly interacted with SERPINA1 low-to-rare frequency variation to determine risk for asthma-related healthcare utilization. This was attributed to PI type Z heterozygotes (MZ, N=11) who had a higher frequency of ED visits (6 [54.5%] MZ heterozygotes, OR=7.60, 95%CI=1.71–39.7, p=0.010), hospitalization (5 [45.5%], OR=16.1, 95%CI=2.64–150.4, p=0.0050) in the past year, and lifetime ICU admissions (6 [54.5%], OR=12.5, 95%CI=2.44–75.6, p=0.0032) compared to 146 individuals without SERPINA1 variants (30 [20.5%] reporting ED visits, 17 [11.6%] hospitalization, 15 [10.3%] ICU admission). SERPINA1 variant-ever smoking interactions in African Americans for ED visits (p=0.069) related to four of six compound heterozygotes reporting an ED visit. In CCHS, α₁-antitrypsin concentrations were inversely associated with moderate-to-severe asthma risk (OR=0.97 per 10 mg/dL increase in α₁-antitrypsin, 95%CI=0.94–0.99, p=0.010) and exacerbations (OR=0.84 per 10 mg/dL, 95%CI=0.76–0.94, p=0.002).

Conclusions:

SERPINA1 variation and α₁-antitrypsin concentrations impact asthma severity through gene-environment interactions with minimum smoking.

Keywords: asthma, alpha1-antitrypsin, SERPINA1, genetics, rare variant, exacerbations, lung function

Introduction:

Asthma is an inflammatory airways disease characterized by variable airflow obstruction which reverses with inhaled bronchodilators; however, a subgroup of individuals with severe asthma show fixed airflow obstruction which does not reverse to normal (1). Genome-wide association studies (GWAS) in asthma cohorts enriched for severe disease and general populations have provided insight into the heritable factors underlying severe asthma and its key features of baseline airflow obstruction and exacerbations, but GWAS loci to date cumulatively account for a small proportion of the observed heritability.(2–5) This missing heritability could be related to rare genetic variants with strong biologic effects such as the locus coding for α₁-antitrypsin, serpin peptidase inhibitor, clade A, member 1 or SERPINA1 on chromosome 14q31. α₁-antitrypsin deficiency is the strongest genetic risk factor for chronic obstructive pulmonary disease (COPD). Low frequency SERPINA1 variants result in α₁-antitrypsin deficiency and anti-protease dysfunction leading to uninhibited neutrophil elastase activity in the lung and an early-onset obstructive lung disease, primarily in individuals with a significant history of cigarette smoking.(6, 7)

Based on protein isoelectric focusing (PIEF) protease inhibitor or PI typing, the most frequent PI types associated with α₁-antitrypsin deficiency are PI type Z due to a low frequency coding variant at amino acid position 366 (Glu³⁶⁶Lys, rs28929474) and PI type S (Glu²⁸⁸Val, rs17580) as homozygotes or compound heterozygote (SZ) genotypes.(7, 8) The MZ heterozygote genotype also increases the risk for COPD suggesting that a single PI type Z allele is sufficient.(9–13) With advances in DNA sequencing, more than 100 additional rare SERPINA1 variants have been identified of which a subgroup have effects on α₁-antitrypsin concentrations and COPD risk.(6, 10, 14–18)

α₁-antitrypsin deficiency has been associated with asthma-related phenotypes, but the relationship between SERPINA1 variation and asthma severity remains largely unknown with a small number of negative studies.(19–26) A study of a Spanish cohort with a physician’s diagnosis of asthma showed a significant association of PI Z and S with exacerbations, but consisted of a high proportion of tobacco exposed individuals and did not account for exposure history or intensity.(26) The potential relationship between α₁-antitrypsin deficiency and asthma severity is reflected by ATS/ERS guidelines recommending that α₁-antitrypsin plasma concentrations be obtained for all asthmatics with irreversible airflow obstruction.(27) To date, there have been no studies evaluating the association of SERPINA1 variation with exacerbations in objectively diagnosed asthma patients with a minimal smoking history with gene sequencing to completely evaluate background variation beyond PI Z and PI S.

We hypothesize that PI type Z and additional rare SERPINA1 variation causes reduced α₁-antitrypsin concentrations drives asthma severity and that this risk is modulated by a prior history of smoking, even if minimal. To test our hypothesis, we performed a deep sequencing candidate gene study of SERPINA1 in the National Heart, Lung, and Blood Institute (NHLBI)-sponsored Severe Asthma Research Program (SARP1–3), a comprehensively characterized, multi-ethnic asthma cohort enriched for severe disease.(28) These genetic studies of SERPINA1 variation in SARP have been previously reported in abstract form and expanded with DNA sequencing by two NHLBI-sponsored programs.(29, 30) Since SARP studies did not have data on plasma α₁-antitrypsin concentrations, we evaluated α₁-antitrypsin concentrations in independent cohort asthma patients from the Cleveland Clinic Health System (CCHS) with electronic health record (EHR) data.

Methods:

Study Populations

This candidate gene study analyzed phenotype and DNA sequencing data of the SERPINA1 gene region from 847 non-Hispanic Whites and 446 African Americans who met criteria of ≤5 pack-years of smoking from the NHLBI SARP1–2 and ≤10 pack-years of smoking from the NHLBI SARP3. Participants were non-smokers at the time of exam with a diagnosis of asthma confirmed by either methacholine bronchial hyperresponsiveness or bronchodilator reversibility with documented asthma symptoms.(1, 28) Comprehensive questionnaires including asthma-related health care utilization, cigarette smoking history, and medication use were standardized across all study sites and administered by centrally trained clinical staff. SARP studies were approved by the institutional review boards at each institution and written consent was obtained for all study participants. The CCHS EHR cohort database included 1,955 individuals with an asthma diagnosis based on ICD-9 codes and α₁-antitrypsin concentrations collected between 2010 and 2021. Of these, 531 reported a history of smoking and 1,424 did not report a smoking history. Current smokers were excluded. Asthma severity (mild, moderate, severe), and exacerbations were defined based on ICD-9 codes(31) given the study preceded ICD-10 code implementation.

Resequencing of SERPINA1 for the Identification of Low-frequency and Rare Variants

DNA samples from 563 non-Hispanic White and 286 African American SARP participants with asthma underwent SERPINA1 resequencing from the NHLBI Resequencing and Genotyping Service (RS&G) providing an average depth of 62X (median=60X). DNA samples from an additional 294 non-Hispanic White and 172 African American SARP participants underwent whole-genome sequencing through the NHLBI-sponsored Trans-Omics for Precision Medicine (TOPMed) program and an additional six African Americans had resequencing data from whole-exome sequencing through the NHLBI-sponsored GO Exome Sequencing Program (ESP). With the exception of ESP, these data were examined for the identification of low frequency and rare polymorphisms with minor allele frequency (MAF) ≤0.05 within a 16.9 kilobase (kB) region of chromosome 14 (nucleotide position 94841102–94857987 based on human genome assembly GRCh37 [hg19]) consisting of the 5’ and 3’ untranslated regions (UTR), five coding exons, and four introns of SERPINA1.(32) Resequencing and analyses are illustrated in Figure 1 and were stratified by race and ethnicity due to relatively higher frequency or PI type Z in non-Hispanic white compared to African Americans and the presence of multiple ancestry-specific variants with potential effects not detectable in combined analyses.

Figure 1: — This diagram summarizes the sequential analytical steps for characterizing rare *SERPINA1* variants in the Severe Asthma Research Program (SARP) and α1-antitrypsin concentrations in the electronic health record (EHR)-based, Cleveland Clinic Health System (CCHS). ^aDNA samples from 847 white and 446 African American SARP participants with asthma were sequenced the identification of low frequency and rare polymorphisms with minor allele frequency (MAF) less than 0.05 in a 16.9kB region of *SERPINA1* through the NHLBI Resequencing and Genotyping Service (RS&G) and TOPMed whole-genome sequencing program. ^bSix additional African Americans had whole-exome DNA sequencing data through the NHLBI-sponsored GO Exome Sequencing Program (ESP). First, gene-level tests assessed the cumulative effects of PI types Z, S, and additional, rare exonic and splice site variants on lung function and asthma exacerbation outcomes by gene-by-smoking status interactions (iSKAT) by race/ethnic group. Cumulative variant effects were then evaluated in ever and never smoking subgroups (SKAT). Next, we performed PI Z genotype-by-smoking status interaction models in whites (not in African Americans because of PI Z MAF being much lower) and mediation analysis in white ever smokers to evaluate the contributions of PI Z heterozygote genotype (MZ), smoking status, and medication use on asthma exacerbations requiring hospitalization. In all groups, we performed rare variant genotype association testing conditional on the low frequency PI Z and S variants and additional rare SERPINA1 variants (V_R). These conditional analyses compared the lung function and frequency of exacerbation outcomes in individuals without PI S, Z or V_R (MM), PI S heterozygotes (MS), PI Z heterozygotes (MZ), compound heterozygotes with non-PI Z rare variation (SV_R/V_RV_R), PI Z homozygotes, and PI Z-containing compound heterozygotes with PI S or additional, rare variants (ZZ/ZS/ZV_R).

Statistical Methods

SERPINA1 polymorphisms with a call rate ≤0.98 and common variants that did not meet Hardy-Weinberg expectations (HWE p<0.05) or showed non-random missingness by genotype were excluded. Low frequency and rare variants identified with resequencing and genotyping were annotated based on GRCh37 using the Online Mendelian Inheritance in Man, NHLBI GO ESP, NCBI ClinVar, International Genome Sample Resource based on the 1,000 Genomes Project, and Exome Aggregation Consortium databases to determine PI type and novelty.(33–37)

In SARP, we applied iSKAT to low frequency (MAF≤0.05: PI types Z and S) and rare (MAF<0.01, Figure 1) coding and intronic splice site variants to test for interactions with ever smoking history at a gene-level that determine cumulative effects on lung function and health care-related outcomes similar to what was previously performed in a pharmacogenetic study of rare ADRB2 and SERPINA1 in a heavy smoking COPD cohort.(38–41) We then characterized significant gene-level interaction associations with health care-related outcome through stratified gene-level analyses by ever (N=173) and never-smoking (N=674) status in non-Hispanic whites and African American cohorts (N=446, 69 ever smokers) with SKAT. SKAT, iSKAT, and regression-based models for individual low-to-rare frequency variant-by-smoking history interactions and SERPINA1 genotypes using PLINK v1.07 were adjusted for age, sex, BMI, pack-years smoking history, high-dose inhaled corticosteroids (ICS), and long-acting beta agonists (LABA) treatment using PLINK v1.07. (38, 42)

In SARP, regression-based mediation models assessed the contribution of smoking status, ICS, and LABA use on asthma-related hospitalizations with PI type Z heterozygote genotype (MZ) as a mediator using the “psych::mediate” function of “psych” R package.(43) These mediation models estimated the direct effect from smoking status, high-dose ICS, and LABA use on the likelihood of an asthma-related hospitalization via the influence of MZ genotype as the mediator. The significance of direct effects was calculated using bootstrapping procedures and computed for 1000 bootstrapped samples.

In the CCHS cohort, we tested for the association of α₁-antitrypsin concentrations with asthma severity and exacerbations with logistic regression models with a restricted cubic spline. α₁-antitrypsin concentrations were also analyzed as quartiles. Models for severity were adjusted for age, sex, race, BMI, and pack-years. For exacerbations, ICS use was included in models for all participants and a subgroup analysis of ICS-treated patients based on use of any ICS-containing regimen. Combined and stratified analyses were performed based on a prior smoking history.

Results:

SARP Multi-Ethnic Study Cohort and the Identification of Rare SERPINA1 Variants

The baseline characteristics of the SARP1–3 study cohort is shown by ethnic group and smoking status on Table 1. The MAF for all identified, functional low frequency and rare SERPINA1 variants (Figure 2) are shown by ethnic group in Table 2. Non-Hispanic whites had 16 low-frequency-to-rare coding rare variants, including PI type Z, PI type S, Ser⁶Leu (PI type Z_Wrexham, rs140814100), Thr³⁵Ala (rs1374116152), Arg⁶³Cys (PI type I, rs28931570), Ala⁸⁴Thr (PI type M6_Passau, rs111850950), Leu¹⁰⁸Arg (rs137888162), Gly¹⁷²Arg and Gly¹⁷²Trp (PI types V and M2_Obernburg, respectively, rs112030253), Val²⁴⁰Glu (rs1401368743), Arg²⁴⁷Cys (PI type F, rs28929470), Asp²⁸⁰Val (P_Lowell/Q0_Cardiff, rs121912714), His²⁹⁴Asn (rs772436715), Ala³⁰⁸Ser (rs141620200), Pro³⁸⁶Thr (rs12233), Glu³⁸⁷Lys (PI type X_{Christ Church}, rs121912712), and Pro³⁹³Ser (PI type M_Wurzburg, rs61761869, Table 2). African Americans had 14 functional low-frequency-to-rare SERPINA1 variants, including PI type Z, PI type S, Ser⁶Leu (rs140814100), Arg⁶³Cys (PI type I), Glu¹⁵⁶Lys (rs78640395), Pro²²¹His (rs368117781), Val²⁴⁰Glu, His²⁸⁶Tyr (rs149537225), His²⁹³Gln (rs141095970), two splice site variants (rs375378877 and rs367822021), Ala³⁰⁸Ser, Val³²⁶Ile (rs139964603), and Asp³⁶⁵Asn (PI type P_{St. Albans}, rs143370956, Table 2). African Americans had seven rare nonsynomyous and two splice site variants not found in whites while whites had 11 rare variants not found in African Americans (Table 2) (44). Among whites with two low-frequency-to-rare functional variants, there were two ZZ homozygote never smokers, two PI type Z/S never smokers and one prior smoker, and one compound heterozygote each for PI type S/M_Wurzberg, PI type Z/I, and Z/Val²⁴⁰Glu who were all never smokers. There were six African American compound heterozygotes identified: two PI type I/P_{St Albans}, one PI type S/His²⁹³Gln, one PI type Z_Wrexham/Val²⁴⁰Glu, one Pro²²¹His/Val²⁴⁰Glu, and one Val³²⁶Ile/Glu¹⁵⁶Lys.

Table 1:

Baseline Characteristics

NHLBI Severe Asthma Research Program (SARP 1–3)	Asthma Cases by Ethnic Group
Subject Characteristics	Non-Hispanic Whites Pooled	Whites with Smoking History	Whites Never Smoking	African Americans

Patients (N)	847	173	674	446
Age in Years (SD)^a,b	40.2 (16.7)	46.8 (14.3)	38.5 (16.9)	30.8 (16.6)
Females N (%)	541 (63.9%)	110 (63.6%)	431 (63.9%)	268 (60.1%)
BMI (SD)^c	29.3 (7.89)	30.2 (7.93)	29.1 (7.87)	30.8 (10.3)
Ever smoker N (%)^d	173 (20.4%)	NA	NA	69 (15.5%)
Smoking Pack-Years (SD)^b	0.54 (1.91)	2.86 (3.58)	0 (0)	0.38 (1.33)
Pulmonary Function
% Predicted Baseline FEV1 (SD)^e,f	75.5 (21.6)	72.0 (20.2)	76.3 (21.8)	77.6 (20.5)
% Predicted Baseline FVC (SD)^f	86.3 (18.9)	83.3 (17.7)	87.1 (19.1)	90.3 (18.6)
FEV1/FVC Ratio (SD)^g	70.4 (11.7)	68.3 (11.0)	71.0 (11.9)	71.8 (11.5)
% Obstruction (FEV1/FVC < 70%)^h	309 (36.5%)	76 (45.0%)	233 (35.4%)	148 (33.2%)
Asthma-Related Health Care
Utilization
≥3 Steroid Bursts Last 12 Months	228 (26.7%)	51 (29.5%)	177 (26.3%)	107 (24.0%)
Unscheduled Visit Last 12 Months (%)	504 (59.5%)	100 (57.8%)	404 (60.0%)	282 (63.2%)
ED Visit Last 12 Months (%)^a	189 (22.3%)	39 (22.5%)	150 (22.3%)	203 (45.5%)
Hospitalization Last 12 Months (%)^a	97 (11.5%)	25 (14.5%)	72 (10.7%)	93 (20.9%)
ICU Admission Lifetime (%)^a	136 (16.1%)	24 (13.9%)	112 (16.8%)	130 (29.1%)

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p<0.001 for the trend between ethnic groups.

p<0.001 for the trend between smoking status groups.

p=0.0037 between ethnic groups.

p=0.03 between ethnic groups.

p=0.018 between ethnic groups.

p=0.018 between smoking status groups.

p=0.0074 between smoking status groups.

p=0.022 between smoking status groups.

Figure 2: — Rare and low frequency variants showed by amino acid coding change (or rs number for splice site variants) with known PI types, including the common PI types M2/M4 and M3. Variants highlighted in red were only in African Americans and those in blue only found in non-Hispanic whites.

Table 2:

SERPINA1 Missense and Intronic Splice Site Polymorphisms Identified by Ethnic Group in SARP.

SERPINA1 Variants^a			Minor Allele Frequencies by Ethnic Group
rs number	Coding Change	PI Type	Non-Hispanic Whites (N=847)	African Americans (N=446)

rs140814100	Ser⁶Leu	Z_Wrexham	0	0.0011
rs1374116152	Thr³⁵Ala		0.00059	0
rs28931570	Arg⁶³Cys	I	0.0065	0.0022
rs111850950	Ala⁸⁴Thr	M6_Passau	0.00059	0
rs137888162	Leu¹⁰⁸Arg		0.00059	0
rs709932	Arg¹²⁵His	M2/M4	0.16	0.030
rs78640395	Glu¹⁵⁶Lys		0	0.0011
rs112030253	Gly¹⁷²Trp	M2_Obernburg	0.0018	0
rs112030253	Gly¹⁷²Arg	V	0.00060	0
rs368117781	Pro²²¹His		0	0.0011
rs6647	Val²³⁷Ala	M1Ala/M1Val	0.22	0.54
rs1401368743	Val²⁴⁰Glu		0.0018	0.034
rs28929470	Arg²⁴⁷Cys	F	0.0024	0
rs121912714	Asp²⁸⁰Val	P_Lowell, Q0_Cardiff	0.00059	0
rs149537225	His²⁸⁶Tyr		0	0.0011
rs17580	Glu²⁸⁸Val	S	0.041	0.0090
rs141095970	His²⁹³Gln		0	0.0067
rs772436715	His²⁹⁴Asn		0.00059	0
rs375378877	Splice Site		0	0.0011
rs367822021	Splice Site		0	0.0011
rs141620200	Ala³⁰⁸Ser		0.0018	0.0011
rs139964603	Val³²⁶Ile		0	0.012
rs143370956	Asp³⁶⁵Asn	P_{St Albans}	0	0.0022
rs28929474	Glu³⁶⁶Lys	Z	0.030	0.0067
rs12233	Pro³⁸⁶Thr		0.0012	0
rs121912712	Glu³⁸⁷Lys	X_{christ Church}	0.00059	0
rs61761869	Pro³⁹³Ser	M_Wurzburg	0.00059	0
rs1303	Glu⁴⁰⁰Asp	M3	0.24	0.099

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Minor allele frequencies of functional polymorphisms identified though resequencing of a 16.9kB region of SERPINA1 shown by ethnic group.

Variants are described by rs number, protease inhibitor (PI) type based on protein isoelectric focusing, and amino acid coding change when indicated.

Gene-Level Testing of Low Frequency and Rare Functional SERPINA1 Variants

iSKAT analyses (Table 3) showed that non-Hispanic whites had significant interactions between ever smoking status and low frequency-to-rare SERPINA1 variant for history of an asthma-related ER visit (p_interaction=0.049) or hospitalization, (p_interaction=0.019) in the past year and lifetime history of an ICU admission based on self-report (p_interaction=0.010). In stratified SKAT analyses of ever smoking whites (Table E1), low-to-rare frequency variants were associated with pre-bronchodilator FEV1/FVC ratio (p=0.017), history of ER visits (p=0.022), hospitalizations (p=0.0024), and lifetime ICU admission (p=0.00018). These gene-level SKAT associations in white ever smokers translated into a higher frequency of asthma-related hospitalization in the past year (N=7 [29.2%], OR=4.60, 95%CI=1.19–18.73, p=0.027) and lifetime ICU admission (N=8 [33.3%], OR=6.61, 95%CI=1.87–24.9, p=0.0036) in those with at least 1 variant (N=24) compared to those without variants (148 white ever smokers of which 18 [12.2%] reported hospitalizations, and 8 [33.3%] lifetime ICU admissions, Table E1). Among white never smokers and in African American ever and never smokers, SERPINA1 variants were not associated with lung function or asthma healthcare utilization outcomes (Tables E1 and E2).

Table 3:

Interaction Effect Between Rare SERPINA1 Variants and Ever Smoking History on Lung Function and Asthma-Related Healthcare Utilization in Patients with Asthma from SARP.

	Number of Rare Variants (RV)			Interaction	0 RV vs 1 RV		0 RV vs 2 RV
	0 RV	1 RV	2 RV	iSKAT p-value	Beta/OR(95%CI)	p-value	Beta/OR(95%CI)	p-value

Non-Hispanic Whites (N)	703	137	7
Pre-BD FEV1 percentage predicted (SD)	75.4 (21.5)	75.6 (21.6)	82.8 (24.9)	0.71	−0.44	0.80	0.90	0.79
Pre-BD FVC percentage predicted (SD)	86.3 (19.0)	86.2 (18.1)	89.9 (19.2)	0.59	−0.93	0.52	−0.91	0.75
Pre-BD FEV1/FVC Ratio (SD)	70.3 (11.6)	71.1 (12.6)	76.0 (14.7)	0.10	0.52	0.59	1.75	0.37
Number with FEV1/FVC <0.7 (%)	256 (37.2%)	51 (38.6%)	2 (28.6%)	0.23	0.99(0.65–1.51)	0.97	0.82(0.29–1.95)	0.67
3 or More Steroid Bursts past 12 mo (%)	192 (27.3%)	34 (25.0%)	2 (28.6%)	0.31	1.02 (0.63–1.64)	0.93	1.27 (0.45–3.07)	0.61
Urgent Visit past 12 mo (%)	417 (59.4%)	82 (59.4%)	5 (71.4%)	0.42	1.13(0.76–1.68)	0.56	1.42(0.65–3.82)	0.41
ED Visit past 12 mo (%)	156 (22.3%)	33 (24.1%)	0 (0%)	0.049	1.20(0.75–1.90)	0.43	NA	0.98
Hospitalization past 12 mo (%)	76 (10.8%)	21 (15.3%)	0 (0%)	0.019	1.78(0.99–3.13)	0.049	NA	0.99
ICU Over Lifetime (%)	110 (15.8%)	25 (18.2%)	1 (14.3%)	0.010	1.27(0.75–2.08)	0.35	NA	0.99
African Americans (N)	397	43	6
Pre-BD FEV1 percentage predicted (SD)	77.7 (20.8)	76.4 (18.2)	78.2 (20.4)	0.62	−2.72	0.38	0.59	0.88
Pre-BD FVC percentage predicted (SD)	90.3 (18.9)	90.2 (15.8)	90.0 (17.9)	0.32	−2.92	0.30	0.20	0.96
Pre-BD FEV1/FVC Ratio (SD)	71.8 (11.5)	71.4 (12.1)	74.3 (8.96)	0.41	−0.68	0.70	1.16	0.59
Number with FEV1/FVC <0.7 (%)	130 (33.2%)	15 (34.9%)	3 (50%)	0.31	1.11(0.55–2.22)	0.76	0.89(0.31–2.14)	0.80
3 or More Steroid Bursts past 12 mo (%)	91 (22.9%)	12 (27.9%)	4 (66.7%)	0.20	1.13(0.52–2.36)	0.74	2.48(1.05–6.85)	0.044
Urgent Visit past 12 mo (%)	250 (63.5%)	27 (62.8%)	5 (83.3%)	0.53	0.88(0.44–1.80)	0.71	1.47(0.58–6.49)	0.49
ED Visit past 12 mo (%)	179 (45.2%)	20 (46.5%)	4 (66.7%)	0.069	0.85(0.43–1.68)	0.64	1.47(0.63–4.04)	0.39
Hospitalization past 12 mo (%)	80 (20.3%)	11 (25.6%)	2 (33.3%)	0.25	1.00(0.44–2.16)	0.99	1.43(0.52–3.39)	0.43
ICU Over Lifetime (%)	110 (27.8%)	17 (39.5%)	3 (50.0%)	0.17	1.45(0.71–2.88)	0.30	1.52(0.64–3.61)	0.32

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Patients with no rare variants (0 RV), one rare variant (1 RV), and two rare variants (2 RV), including PI types Z and S were compared. Data shown as number of patients with percentages in parentheses or means with standard deviation (SD) in parentheses. iSKAT and variant number genotype association regression-based models included age, sex, BMI, pack-year smoking history, and inhaled high-dose glucocorticoid and long-acting beta agonist treatment.

In African Americans, the iSKAT interaction between ever smoking and low-to-rare SERPINA1 variants showed a trend towards significance for ER visits in the past year (p_interaction=0.069, Table 3). Four of six (66.7%) African American compound heterozygotes with two SERPINA1 variants, all of which were never smokers, had an asthma-associated ER visit in the past year compared to those without rare variants (N=179 of 397 [45.2%], Table 3).

Smoking Interactions and Effects of the PI type Z Genotype on Lung Function and Asthma-Related Healthcare Utilization in SARP

PI type Z is the strongest genetic factor for COPD risk and lung function impairment in the setting of cigarette smoking exposure and has an allele frequency 4.5 times higher is whites (MAF=0.03) compared to African Americans (MAF=0.0067, Table 2), as shown in previous studies.(12, 13) Interaction analyses of individual low-to-rare frequency SERPINA1 variants showed significant interactions between ever smoking status and PI type Z (Glu³⁶⁶Lys, C and T alleles, summarized in Table E3) for history of an asthma-related ER visit (p_interaction=0.029) or hospitalization in the past year (p_interaction=0.031) and lifetime history of an ICU admission (p_interaction=0.023). In stratified analyses of ever smoking whites, six (50%) of 12 white PI type Z heterozygotes (CT genotype) reported exacerbations requiring an ED visit in the past year (OR=5.51, 95%CI=1.37–24.5, p=0.018), five (41.7%) an asthma-related hospitalization (OR=9.92, 95%CI=1.97–61.4, p=0.0071, and six (50%) a lifetime history of ICU admission (OR=8.70, 95%CI=1.87–43.8, p=0.0060) compared to 33 (20.5%) of 161 common allele homozygotes (CC genotype) reporting ED visits, 20 (12.4%) hospitalizations, and 18 (11.2%) ICU admissions (Table E4). These health care utilization outcome associations were not identified in whites without a history of cigarette smoking (Table E4).

Effects of PI Type Z (Glu³⁶⁶Lys), S (Glu²⁸⁸Val), and non-PI Z/S (V_R) Genotypes on Lung Function and Asthma-Related Healthcare Utilization in SARP

Due to the significant healthcare utilization outcome associations in whites with at least one SERPINA1 variant (Table 3) and PI type Z SNP heterozygotes (Table E2), we grouped the SARP cohort into six genotype groups by collapsing genotypes containing PI type Z, PI type S, or non-PI Z or S variation (V_R) to enable the analysis MZ and MS heterozygotes in the absence of background SERPINA1 variation based on sequencing and the impact of PI type Z-containing homozygote (ZZ) and compound heterozygote genotypes (ZS/ZV_R) (Table 4).

Table 4:

Effects of PI Type Z (Glu³⁶⁶Lys), S (Glu²⁸⁸Val), and non-PI Z/S (V_R) Genotypes on Lung Function and Exacerbations and Asthma-Related Healthcare Utilization in Non-Hispanic Whites with Asthma by Smoking Status.

	PI Z/S/VR-Based Genotypes						MM vs MS		MM vs MV_R		MM vs MZ		MM vs V_RV_R/V_RS		MM vs ZZ/ZS/SV_R
	MM	MS	MV_R	MZ	VRVR/VRS	ZZ/ZS/ZVR	Beta/OR(95%CI)	p-value	Beta/OR(95%CI)	p-value	Beta/OR(95%CI)	p-value	Beta/OR(95%CI)	p-value	Beta/OR(95%CI)	p-value

Whites with history smoking (N)	146	8	7	11	0	1
Pre-BD FEV1% predicted (SD)	71.7 (19.9)	80.1 (22.8)	74.8 (29.5)	70.6 (17.1)	NA	47	6.83	0.29	6.66	0.36	2.52	0.66	NA	NA	−15.28	0.38
Pre-BD FVC% predicted (SD)	83.3 (17.8)	83.5 (17.4)	79.7 (21.8)	87.4 (15.1)	NA	59	0.66	0.91	−2.34	0.72	8.09	0.12	NA	NA	−13.54	0.39
Pre-BD FEV1/FVC Ratio (SD)	67.9 (10.5)	78.4 (6.83)	72.46 (17.2)	63.7 (11.3)	NA	61	8.89	0.016	5.77	0.17	−3.97	0.24	NA	NA	−3.41	0.74
Number with FEV1/FVC <0.7 (%)	65 (45.8%)	1 (12.5%)	2 (28.6%)	7 (63.6%)	NA	1 (100%)	0.13(0.01–0.93)	0.080	0.19 (0.01–1.40)	0.16	1.81(0.40–9.81)	0.45	NA	NA	NA	0.99
3 or More Steroid Bursts past 12 mo (%)	41 (28.1%)	2 (25.0%)	3 (42.9%)	4 (36.4%)	NA	1 (100%)	1.21(0.15–6.93)	0.84	1.17(0.13–8.93)	0.88	1.96(0.41–9.20)	0.39	NA	NA	NA	0.99
Urgent Visit past 12 mo (%)	83 (56.8%)	4 (50.0%)	4 (57.1%)	8 (72.7%)	NA	1 (100%)	0.72 (0.15–3.37)	0.66	0.67(0.11–4.21)	0.66	2.95(0.66–16.82)	0.18	NA	NA	NA	0.99
ED Visit past 12 mo (%)	30 (20.5%)	1 (12.5%)	2 (28.6%)	6 (54.5%)	NA	0 (0%)	0.57 (0.03–3.86)	0.62	0.60 (0.03–4.59)	0.67	7.60(1.71–39.75)	0.010	NA	NA	NA	0.99
Hospitalization past 12 mo (%)	17 (11.6%)	1 (12.5%)	2 (28.6%)	5 (45.5%)	NA	0 (0%)	6.84 (0.22–215.93)	0.22	1.03(0.04–12.01)	0.98	16.06(2.64–150.41)	0.0050	NA	NA	NA	1.00
ICU Over Lifetime (%)	15 (10.3%)	1 (12.5%)	2 (28.6%)	6 (54.5%)	NA	0 (0%)	2.12(0.10–19.03)	0.54	7.00 (0.71–72.09)	0.082	12.53(2.44–75.58)	0.0032	NA	NA	NA	0.99
Whites with no history smoking (N)	554	58	24	32	1	5							NA	NA
Pre-BD FEV1% predicted (SD)	76.4 (21.8)	75.5 (22.6)	75.0 (21.4)	75.3 (22.2)	56	95.3 (15.2)	−1.32	0.60	−2.41	0.53	−3.60	0.28	NA	0.68	3.99	0.59
Pre-BD FVC% predicted (SD)	87.2 (19.2)	86.7 (20.3)	86.8 (15.9)	85.1 (17.7)	79.5	98.1 (14.2)	−0.94	0.66	−3.01	0.36	−3.88	0.16	NA	0.72	−0.02	1.00
Pre-BD FEV1/FVC Ratio (SD)	70.9 (11.7)	70.2 (12.4)	71.2 (14.1)	72.0 (12.7)	53.6	83.5 (8.4)	−0.38	0.79	−0.04	0.99	−0.54	0.78	NA	0.27	4.26	0.32
Number with FEV1/FVC <0.7 (%)	189 (34.8%)	28 (48.3%)	8 (36.4%)	7 (24.1%)	1 (100%)	0 (0%)	1.37(0.74–2.51)	0.31	1.05 (0.39–2.78)	0.92	1.08(0.47–2.41)	0.85	NA	0.98	0.41 (0.02–3.06)	0.45
3 or More Steroid Bursts past 12 mo (%)	149 (26.9%)	14 (24.1%)	8 (33.3%)	5 (16.1%)	1 (100%)	0 (0%)	1.31 (0.61–2.70)	0.48	1.19 (0.43–3.10)	0.73	0.51(0.16–1.36)	0.21	NA	0.99	0.97 (0.04–7.88)	0.98
Urgent Visit past 12 mo (%)	332 (60.0%)	32 (55.2%)	13 (54.2%)	23 (71.9%)	1 (100%)	3 (60.0%)	1.08 (0.60–1.93)	0.80	0.67 (0.28–1.62)	0.37	1.89(0.86–4.48)	0.13	NA	0.99	1.85 (0.34–13.88)	0.49
ED Visit past 12 mo (%)	124 (22.5%)	12 (20.7%)	7 (29.2%)	7 (21.9%)	0 (0%)	0 (0%)	1.11(0.53–2.21)	0.77	1.29 (0.46–3.32)	0.61	0.99(0.37–2.35)	0.98	NA	0.99	NA	0.99
Hospitalization past 12 mo (%)	57 (10.3%)	9 (15.5%)	3 (12.5%)	3 (9.40%)	0 (0%)	0 (0%)	2.45 (1.01–5.53)	0.037	0.89(0.19–3.04)	0.87	1.03(0.23–3.28)	0.97	NA	0.99	NA	0.99
ICU Over Lifetime (%)	93 (17.0%)	6 (10.3%)	4 (16.7%)	8 (25.0%)	1 (100%)	0 (0%)	0.64 (0.24–1.47)	0.33	0.80 (0.22–2.27)	0.70	1.92(0.77–4.39)	0.14	NA	0.99	1.33 (0.07–9.51)	0.81

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Regression-based association testing compared individuals without without PI Z or S (No Z,S), PI Z and S heterozygotes without another rare variant (MZ and MS), PI Z-containing compound heterozygotes with PI S or additional rare variants (V_R), and PI Z homozygotes or compound heterozygotes (ZZ/ZS/SV_R). Lung function measures shown in percentage (%) of predicted and nominal outcomes shown as number of patients with percentages in parentheses or means with standard deviation (SD) in parentheses. Regression-based models included age, sex, BMI, pack-year smoking history, and inhaled high-dose glucocorticoid and long-acting beta agonist treatment.

White MZ heterozygotes with a prior smoking history reported a higher frequency of an asthma-related ED visit (OR_{MM vs MZ}=7.60, 95%CI=1.71–39.75, p=0.010), hospitalization in the past year (OR_{MM vs MZ}=16.1, 95%CI=2.64–150.4, p=0.0050), and lifetime ICU admission (OR_{MM vs MZ}=12.5, 95%CI=2.44–75.6, p=0.0032, Table 4, Figure 3a) compared to whites without PI Z or S. There was one ZS compound heterozygote with a prior history of smoking who had an FEV1 of 47% of predicted, FEV1/FVC of 0.61, and a history of ≥3 glucocorticoid bursts and an ED visit in the past year. African American non-PI type Z compound heterozygotes (V_RV_R/SV_R, N=6), reported a higher frequency of exacerbations requiring three or more glucocorticoid bursts that reached nominal statistical significance (OR_{MM vs VRVR/SVR}=6.07, 95%CI=1.09–46.5, p=0.047, Table E5, Figure 3b). The small number of African Americans with a prior history of smoking who had an MZ (N=2) or compound heterozygote (V_RV_R/SV_R, N=0) genotype did not allow for subgroup analyses. In the pooled cohort of ever and never-smoking white patients, MZ heterozygotes reported a higher frequency of an asthma-related hospitalization (N=8 [18.6%], OR_{MM vs MZ}=2.47, 95%CI=0.96–5.84, p=0.047) and lifetime ICU admission (N=14 [32.6%], OR_{MM vs MZ}=2.78, 95%CI=1.32–5.62, p=0.0054) compared to whites without variants (N=74 [10.6%] and 108 [15.6%] of 700 with MM genotype, respectively, Table E6).

Figures 3a, b: — PI Type Z (Glu³⁶⁶Lys), PI Type S (Glu²⁸⁸Val), and non-Z/S variant (V_R) genotypes shown with proportions for each outcome. Individuals without these variant genotypes are designated as MM while heterozygotes are labelled MS, MV_R, and MZ. African American compound heterozygotes (SV_R or V_RV_R) included one PI S/Gln²⁹³, two PI I/P_{St Albans}, one Leu⁶/Val²⁴⁰, one Ile³²⁶/Lys¹⁵⁶, one Pro²²¹/Va²⁴⁰.

Mediating Role of MZ genotype on Asthma-Related Hospitalization in non-Hispanic Whites

MZ genotype significantly mediated the relationship between high dose ICS use and hospitalization as shown on Figure E1a with the direct effect estimate “c’” (Beta=0.11, SE=0.02, t=4.57, p=5.66×10⁻⁶) while the “b’” independent effect estimate of MZ genotype on hospitalization was marginally significant (Beta=0.09, SE=0.05, t=1.89, p=0.058). In ever smokers as shown on Figure E1b, high-dose ICS use was significantly associated with hospitalization when mediated by a direct MZ genotype effects “c” (Beta = 0.16, SE = 0.06, t = 2.87, p = 0.0046) and the independent effect “b” (Beta = 0.34, SE = 0.10, t = 3.54, p = 0.00052).

Effects of α₁-antitrypsin concentrations on asthma severity and exacerbations in CCHS

In the CCHS cohort, 1,955 individuals with asthma and α1-antitrypsin concentrations were identified with baseline characteristics in Table E7. Compared to SARP, CCHS patients were older with a higher proportion of males, lower proportion of ICS use, and a higher proportion of ever smokers, despite similar pack-years. There were no differences in α1-antitrypsin concentrations by self-reported race or smoking status (Figures E2a and E2b). Higher α₁-antitrypsin concentration was associated with a lower risk of moderate-to-severe asthma (OR=0.97 per 10mg/dL increase in α₁-antitrypsin, 95%CI=0.94–0.99, p=0.010, Figure 4a). Subgroup analysis demonstrated a significant association in those with a prior smoking history (OR=0.94 per 10mg/dL increase, 95%CI=0.89–0.99, p=0.021) not found in never smokers (OR=0.96 per 10mg/dL increase, 95%CI=0.89–1.03, p=0.27) without a significant interaction (p=0.24). The association of α₁-antitrypsin concentration with exacerbations demonstrated a J-shaped curve (Figure 4b). Prior to the inflection point of 139mg/dL, each 10mg/dL increase in α₁-antitrypsin was associated with a significantly lower odds of reporting an asthma exacerbation (OR=0.84 per 10 mg/dL increase, 95%CI=0.76–0.94, p=0.002). Subgroup analysis demonstrated similar results in asthma patients with a prior smoking history (OR=0.83 per 10mg/dL increase in α₁-antitrypsin, 95%CI=0.68–0.99, p=0.046) and never smokers (OR=0.85 per 10 mg/dL increase in α₁-antitrypsin, 95%CI=0.75–0.97, p=0.015) with the same inflection point of 139mg/dL and there was no interaction by smoking status at any point on the spline curve (p>0.2). Comparison of α₁-antitrypsin quartile levels showed the most pronounced association with exacerbations in the lowest quartile of 11–123 mg/dL (Table E8). The association of α₁-antitrypsin concentrations with exacerbations was significant in the subgroup of 480 ICS-users (OR=0.79 per 10mg/dL increase in α₁-antitrypsin, 95%CI=0.66–0.94, p=0.03).

Figures 4a, b: — Logistic regression models with a restricted cubic spline tested for the association of α₁-antitrypsin concentrations with asthma exacerbations based on relevant ICD-9 codes adjusted for age, sex, race, BMI, smoking pack-years, and inhaled corticosteroid use. Both models adjusted for age, sex, race, BMI, and pack-years, with the exacerbation model additionally adjusting for inhaled corticosteroid use. A higher α1-antitrypsin concentration was associated with a lower risk of moderate-to-severe asthma (OR=0.97 per 10 mg/dL increase in α1-antitrypsin, 95%CI=0.94–0.99, p=0.010) and prior to the inflection point of 139mg/dL, lower odds of reporting an asthma exacerbation (OR=0.84 per 10 mg/dL increase, 95%CI=0.76–0.94, p=0.002).

Discussion:

This biologic candidate gene study of SERPINA1 represents the largest cohort of comprehensively characterized, objectively diagnosed asthma patients from different ethnic groups, mostly non-Hispanic whites, evaluated for multiple rare SERPINA1 variants using next-generation DNA sequencing. This study evaluated the largest number of functional rare SERPINA1 coding variants studied in a multi-ethnic asthma cohort enriched for severe disease to best characterize variation at this locus as it relates to asthma severity outcomes. Our studies in the CCHS general population confirm the strong biologic effect of pathogenic SERPINA1 variation on reducing α₁-antitrypsin concentrations and increasing risk for more severe asthma and exacerbations.(10)

This study addresses important questions specific to the role of the rare PI type Z variant in determining asthma severity and the potential role of different, much less frequently studied rare SERPINA1 variants. First, we demonstrated that non-Hispanic white heterozygotes for the PI type Z variant with a minimal cigarette smoking history (<10 pack-years) are at a greater risk for severe exacerbations. These associations reflect the strong effects of this rare variant on asthma severity in whites where the MZ genotype has been associated with risk for COPD in the setting of significant cigarette smoking.(9, 10)

In a Spanish cohort with a physician’s diagnosis of asthma, PI Z and S heterozygote genotypes were associated with respiratory disease exacerbations. Nearly one-third of the participants in the discovery and replication cohorts reported a history of tobacco smoking for which the intensity was not reported. In addition, asthma was not objectively confirmed with albuterol bronchodilator reversibility or methacholine bronchial hyperresponsiveness nor was COPD adequately excluded by considering smoking history or CT scan evidence of emphysema.(26) These issues implicate a bias for tobacco-associated respiratory disease (ie chronic bronchitis, emphysema, early or pre-COPD) as a potential cause of the symptoms leading to the exacerbations reported, unrelated to asthma.(45–48) The Spanish study reported significant associations in those without airflow obstruction in an effort to address the potential contribution of COPD. This is inconsistent with reports showing that a significant proportion of MZ heterozygotes with a heavy smoking history also do not show airflow obstruction and that tobacco exposed persons with preserved FEV1/FVC ratios (i.e. without spirometric COPD) experience significant airway mucus abnormalities, respiratory symptoms, and exacerbations. (40, 45–49)

Several studies have confirmed the importance of considering the presence or absence of a history of cigarette smoking as a critical environmental exposure underlying the pathogenicity of the MZ genotype as it relates to the risk for COPD, emphysema, and bronchiectasis.(9, 10, 12, 13, 50, 51) No studies to date have identified associations between SERPINA1 variation or α1-antitrypsin deficiency on asthma specific severity phenotypes, including exacerbations, while accounting for the critical interaction with tobacco smoke exposure.(23–26) Our study is the first to demonstrate the importance of rare SERPINA1 variant interactions with minimal smoking history to determine the association between MZ genotype and asthma severity in whites.

Since SARP1–3 consisted primarily of European white descent patients where PI type Z is most frequent compared to other ethnic groups, it was this subgroup where we were able to detect the strongest effects on asthma severity. The observation of the direct effect of MZ on asthma severity persisted when performing mediation analysis with ICS use supporting that this effect was not a reflection of underlying asthma severity. By performing DNA sequencing, we confirmed MZ genotype in the absence of background variation while adequately characterizing the diverse SERPINA1 locus which contains many ancestry-specific rare variants.(23–25)

Second, we found additional rare SERPINA1 variants unique to minorities of African descent, including African American compound heterozygotes who each had one of four rare variants (His²⁹³Gln, PI type P_{St Albicans}, Ser⁶Leu, Pro²²¹His) not found in whites (44). It is highly plausible that variation outside of the PI Type Z locus, including rare variants specific to African ancestry could influence asthma severity in African Americans, especially in compound heterozygotes as our data suggests (Table 4, Figure 3b). Unfortunately, we were limited in sample size to identify statistically significant associations or to characterize genotype-smoking interactions.

The rationale for the detrimental effects of rare SERPINA1 variants on asthma severity could be due to effects on α₁-antitrypsin expression and function in the setting of minimal cigarette smoking contributing to increased neutrophilic airways inflammation and bronchial hyperresponsiveness.(52–54) Patients with neutrophilic asthma have increased neutrophil elastase activity in sputum samples which correlated with reduced lung function.(55, 56) Therefore, inadequate inhibition of neutrophil elastase in a susceptible genetic subgroup exposed to the additional risk factor of cigarette smoking, even if a remote past history, might lead to more severe asthma.

Finally, our study confirmed that SERPINA1 variants likely impact asthma severity by lowering α₁-antitrypsin concentrations and that smoking history is a contributing risk factor in an independent general population cohort with ICD-based asthma diagnoses. The J-shaped association between α₁-antitrypsin concentrations and exacerbations (Figure 4b) suggests an asthma-specific “protective threshold” that seems to be higher (139mg/dl) from what is used for the treatment of emphysema. This threshold could reflect that MZ heterozygotes variably increase the expression of functional α1-antitrypsin in response to inflammatory stress to provide adequately inhibit neutrophilic inflammation resulting in the protease-anti-protease imbalance hypothesized to underlie COPD risk.(57) Hence, clinically relevant α₁-antitrypsin thresholds for deficiency might differ in severe asthma compared to the traditional thresholds used for emphysema and COPD.(58)

There have been a small number of studies demonstrating the overlap between α₁-antitrypsin deficiency and asthma-related phenotypes.(19–22) In an Italian registry, α₁-antitrypsin concentrations were positively correlated with greater bronchial hyperresponsiveness.(20) In an NHLBI registry, a physician’s diagnosis of asthma, reversible airflow obstruction, and a history of wheezing was present in 21 percent and associated with risk for baseline airflow obstruction and lung function decline.(22)

This biologic candidate gene study was stratified to understand genetic impact within important groups resulting in analyses increasingly limited in sample size, especially in the subgroup of whites and African American individuals with a past smoking history. This limitation in inherent to the study of rare variants across diverse groups and should not minimize the novel evidence we present that provides the first, clear rationale for testing severe asthmatics with baseline airflow obstruction or frequent health care utilization for α₁-antitrypsin deficiency as recommended by current ATS/ERS guidelines.(27) The SARP cohort was ascertained to be enriched for severe asthma and was not a general population cohort which could contribute to selection biases, a rationale for additionally evaluating CCHS. Furthermore, although we assessed the effect of α₁-antitrypsin concentrations among asthma in a EHR cohort using ICD codes for disease definition and exacerbations which could lead to additional biases. Prior general population and COPD-focused genetic studies of SERPINA1 demonstrate that the most frequent pathogenic variants determining α₁-antitrypsin concentrations include PI types S and Z, of which the latter variant has the strongest effects likely captured with α₁-antitrypsin concentrations measured in CCHS.(10, 61) There are inherent limitations to this with moderate congruency between ICD codes and disease with the potential for misclassification biases that we addressed in subgroup analyses of individuals with active ICS prescriptions to enrich for true asthma.(59)

Findings from prior molecular, epidemiologic, and physiologic studies we have highlighted support the hypothesis that genetically dysfunctional α₁-antitrypsin results in uninhibited neutrophilic inflammation and greater bronchial hyper responsiveness in response to intermittent, external exposure challenges leading to detrimental effects on asthma exacerbations without significantly impacting lung function.(20–22) This candidate gene study of SERPINA1 is the first to definitively demonstrate the effects of the MZ heterozygote genotype and lower α₁-antitrypsin concentrations on asthma severity and exacerbation risk via interactions with minimal smoking history. Hence, this genetic study is the first to demonstrate that rare SERPINA1 variation, such as PI type Z, and α₁-antitrypsin concentrations could identify a susceptible, subgroup of severe asthmatics that might benefit from targeted strategies for cigarette smoking cessation and the management of α₁-antitrypsin deficiency or dysfunction or its associated impact on airways neutrophilic inflammation.(27, 60)

Supplementary Material

NIHMS2058758-supplement-1.pdf^{(418.3KB, pdf)}

Highlights Box:

What is already known about this topic?

α1-antitrypsin deficiency is caused by pathogenic SERPINA1 variants resulting in COPD and emphysema in at-risk smokers. α1-antitrypsin deficiency has been associated with asthma phenotypes, but the relationship between SERPINA1 variation and asthma severity is unknown.

What does this article add to our knowledge?

This is the first genetic study of SERPINA1 in a multi-ethnic asthma cohort enriched for severe asthma to demonstrate the effects of MZ genotype and α₁-antitrypsin concentrations on asthma severity while accounting for smoking history.

How does this study impact current management guidelines?

This study provides a rationale for testing severe asthmatics for α₁-antitrypsin deficiency as recommended by current guidelines and as a biomarker for a genotype subgroup that might benefit from strategies targeting smoking cessation and neutrophilic inflammation even at α₁-antitrypsin concentration thresholds higher than traditionally cited for COPD and emphysema.

Sources of funding:

NIH grants R01 HL142992, K08 HL118128, K23 HL173570, R01 HL111527, HL69116, HL69167, HL69170, HL69174, U10 HL109164, U10 HL109257, U10 HL109146, U10 HL109172, U10 HL109250, U10 HL109168, U10 HL109152, U10 HL109086. Sequencing services were provided through the RS&G Service by the Northwest Genomics Center at the University of Washington, Department of Genome Sciences, under U.S. Federal Government contract number HHSN268201100037C, the Trans-Omics for Precision Medicine (TOPMed) program, and the NHLBI-sponsored GO Exome Sequencing Program (ESP) all of which were sponsored by the National Heart, Lung, and Blood Institute.

Role of the funding source:

The sponsors of the study, including the NHLBI, had no role in study design; data collection, data analysis, and data interpretation; or writing of the report or in the decision to submit for publication.

Declarations of interest:

The authors, many of whom receive funding from the NIH or the Foundation of the NIH, report no financial or personal relationships that could inappropriately influence (bias) this work, with the following exceptions:

Victor E. Ortega, MD, PhD: Dr. Ortega reported receiving funding from the National Institutes of Health (NIH) National Heart, Lung, and Blood Institute (NHLBI) in the form of a K08 training award (Mentored Clinical Scientist Research Career Development Award, NIH HL118128, and R01HL142992. Principle Investigator: Victor E. Ortega, MD, PhD). Dr. Ortega also reported consultancy fees from CSL Behring.

Vickram Tejwani, MD: Dr. Tejwani reports receiving funding from the NIH NHLBI.

Abhishek Shrivastav: No potential conflicts of interest to disclose.

Sara Pasha, MD: No potential conflicts of interest to disclose.

Joe G. Zein, MD, PhD: No potential conflicts of interest to disclose.

Meher Boorgula, MS: No potential conflicts of interest to disclose.

Mario Castro, MD, MPH: Dr. Castro reports University Grant Funding from NIH, American Lung Association, PCORI, Pharmaceutical Grant Funding from AstraZeneca, Chiesi, Novartis, GSK, Sanofi-Aventis; consultant fees for Genentech, Theravance, VIDA, Teva, Sanofi-Aventis; speaker fees from AstraZeneca, Genentech, GSK, Regeneron, Sanofi, & Teva; and royalties from Elsevier.

Loren Denlinger, MD, PhD: Dr. Denlinger reports grants from NIH/NHLBI, consultancy fees from AstraZeneca and Sanofi-Regeneron during the conduct of the study, and funding to support the extension of the longitudinal phase of the SARP cohort from AstraZeneca, Boehringer-Ingelheim, Genentech, GSK, Sanofi-Genzyme-Regeneron, and TEVA.

Serpil C. Erzurum, MD: Dr. Erzurum reports grants from National Institutes of Health NIH during the conduct of the study and serves as Chair of the ABIM Pulmonary Disease Board.

John Fahy, MD: Dr. Fahy reports grants from NIH/NHLBI, grants from Boehringer Ingelheim during the conduct of the study; personal fees from Boehringer Ingelheim, Pieris, Arrowhead Pharmaceuticals, and Gossamer outside the submitted work, in addition, Dr. Fahy has a patent US20110123530A1 - “Compositions and methods for treating and diagnosing asthma” issued, a patent WO2014153009A2 -Thiosaccharide mucolytic agents. issued, and a patent WO2017197360 - “CT Mucus Score” - A new scoring system that quantifies airway mucus impaction using CT lung scans.

Elliot Israel, MD: Dr. Israel reports personal fees from AstraZeneca, Biometry, Entrinsic Health Solutions, Equillium, Genentech, GlaxoSmithKline, Merck, Novartis, 4D Pharma, Pneuma Respiratory, Regeneron Pharmaceuticals, Sanofi Genzyme, Sienna Biopharmaceutical, TEVA Specialty Pharmaceuticals, and Vitaeris, Inc; grants from AstraZeneca, Boehringer Ingelheim, Genentech, GlaxoSmithKline, Merck, Novartis, Sanofi, TEVA and Vifor-Pharma; non-financial support from Circassia, Boehringer Ingelheim, Genentech, GlaxoSmithKline, Merck, TEVA Specialty Pharmaceuticals and Vifor-Pharma; other from Vorso Corp.

Nizar N. Jarjour, MD: Dr. Jarjour reports grants from NIH/NHLBI, consultancy fees from AstraZeneca and Boehringer Ingelheim, and funding support for the extension of the longitudinal phase of the SARP cohort from AstraZeneca, Boehringer-Ingelheim, Genentech, GSK, Sanofi-Genzyme-Regeneron, and TEVA.

Bruce Levy, MD: Dr. Levy reports grants from NIH during the conduct of the study; other from Nocion Therapeutics, from Entrinsic Health, grants and personal fees from Sanofi, personal fees from Pieris Pharmaceuticals, Novartis, AstraZeneca, Corbus Pharmaceuticals, Gossamer Bio, Metera Pharmaceuticals, and Teva, and grants from Samsung Research America.

David Mauger, PhD: Dr. Mauger reports grant support from the NIH, AstraZeneca, Boehringer Ingelheim, Genentech, GSK, Sanofi-Genzyme-Regeneron, and Teva.

Wendy C. Moore, MD: Dr. Moore reports grants from NIH, grants from AstraZeneca, Boehringer-Ingelheim, Genentech, GlaxoSmithKline, Sanofi-Genzyme-Regeneron, and Teva during the conduct of the study; grants and personal fees from AstraZeneca, and Sanofi Regeneron, grants from Boehringer Ingelheim, GlaxoSmithKline, Novartis, Gossamer, and Cumberland Pharmaceuticals.

Sally E. Wenzel, MD: Dr. Wenzel reports grants from NIH and personal fees from AstraZeneca, grants and personal fees from GSK during the conduct of the study; grants and personal fees from Sanofi-Regeneron, grants from Boehringer Ingelheim, Novartis, and TEVA, and personal fees from Pieris.

Prescott Woodruff, MD, MPH: Dr. Woodruff reports consultancy fees from Astra Zeneca, Theravance, Glenmark pharmaceuticals, Sanofi and Regeneron and funding from Genetech and the COPD Foundation.

Gregory A. Hawkins, PhD: No potential conflicts of interest to disclose.

Eugene R. Bleecker, MD: Dr. Bleecker reports grants from NIH, funding for clinical trials through his employer, Wake Forest School of Medicine and University of Arizona for AstraZeneca, MedImmune, Boehringer Ingelheim, Genentech, Johnson and Johnson (Janssen), Novartis, Regeneron, and Sanofi Genzyme, personal fees as a consultant for AstraZeneca, MedImmune, Boehringer Ingelheim, Glaxo Smith Kline, Novartis, Regeneron, and Sanofi Genzyme.

Deborah A. Meyers, PhD: No potential conflicts of interest to disclose.

Footnotes

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References:

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Supplementary Materials

NIHMS2058758-supplement-1.pdf^{(418.3KB, pdf)}

[R1] 1.Moore WC, Bleecker ER, Curran-Everett D, Erzurum SC, Ameredes BT, Bacharier L, et al. Characterization of the severe asthma phenotype by the National Heart, Lung, and Blood Institute’s Severe Asthma Research Program. The Journal of allergy and clinical immunology. 2007;119(2):405–13. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R2] 2.Herrera-Luis E, Ortega VE, Ampleford EJ, Sio YY, Granell R, de Roos E, et al. Multi-ancestry genome-wide association study of asthma exacerbations. Pediatr Allergy Immunol. 2022;33(6):e13802. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R3] 3.Proceedings of the ATS workshop on refractory asthma: current understanding, recommendations, and unanswered questions. American Thoracic Society. American journal of respiratory and critical care medicine. 2000;162(6):2341–51. [DOI] [PubMed] [Google Scholar]

[R4] 4.Shrine N, Guyatt AL, Erzurumluoglu AM, Jackson VE, Hobbs BD, Melbourne CA, et al. New genetic signals for lung function highlight pathways and chronic obstructive pulmonary disease associations across multiple ancestries. Nat Genet. 2019;51(3):481–93. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R5] 5.Li X, Howard TD, Zheng SL, Haselkorn T, Peters SP, Meyers DA, et al. Genome-wide association study of asthma identifies RAD50-IL13 and HLA-DR/DQ regions. The Journal of allergy and clinical immunology. 2010;125(2):328–35 e11. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R6] 6.Zaimidou S, van Baal S, Smith TD, Mitropoulos K, Ljujic M, Radojkovic D, et al. A1ATVar: a relational database of human SERPINA1 gene variants leading to alpha1-antitrypsin deficiency and application of the VariVis software. Human mutation. 2009;30(3):308–13. [DOI] [PubMed] [Google Scholar]

[R7] 7.Silverman EK, Sandhaus RA. Clinical practice. Alpha1-antitrypsin deficiency. The New England journal of medicine. 2009;360(26):2749–57. [DOI] [PubMed] [Google Scholar]

[R8] 8.Turino GM, Barker AF, Brantly ML, Cohen AB, Connelly RP, Crystal RG, et al. Clinical features of individuals with PI*SZ phenotype of alpha 1-antitrypsin deficiency. alpha 1-Antitrypsin Deficiency Registry Study Group. American journal of respiratory and critical care medicine. 1996;154(6 Pt 1):1718–25. [DOI] [PubMed] [Google Scholar]

[R9] 9.Foreman MG, Wilson C, DeMeo DL, Hersh CP, Beaty TH, Cho MH, et al. Alpha-1 Antitrypsin PiMZ Genotype Is Associated with Chronic Obstructive Pulmonary Disease in Two Racial Groups. Ann Am Thorac Soc. 2017;14(8):1280–7. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R10] 10.Ortega VE, Li X, O’Neal WK, Lackey L, Ampleford E, Hawkins GA, et al. The Effects of Rare SERPINA1 Variants on Lung Function and Emphysema in SPIROMICS. Am J Respir Crit Care Med. 2020;201(5):540–54. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R11] 11.Hersh CP, Dahl M, Ly NP, Berkey CS, Nordestgaard BG, Silverman EK. Chronic obstructive pulmonary disease in alpha1-antitrypsin PI MZ heterozygotes: a meta-analysis. Thorax. 2004;59(10):843–9. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R12] 12.Molloy K, Hersh CP, Morris VB, Carroll TP, O’Connor CA, Lasky-Su JA, et al. Clarification of the risk of chronic obstructive pulmonary disease in alpha1-antitrypsin deficiency PiMZ heterozygotes. American journal of respiratory and critical care medicine. 2014;189(4):419–27. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R13] 13.Sorheim IC, Bakke P, Gulsvik A, Pillai SG, Johannessen A, Gaarder PI, et al. alpha(1)-Antitrypsin protease inhibitor MZ heterozygosity is associated with airflow obstruction in two large cohorts. Chest. 2010;138(5):1125–32. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R14] 14.Seixas S, Mendonca C, Costa F, Rocha J. alpha1-Antitrypsin null alleles: evidence for the recurrence of the L353fsX376 mutation and a novel G-->A transition in position +1 of intron IC affecting normal mRNA splicing. Clinical genetics. 2002;62(2):175–80. [DOI] [PubMed] [Google Scholar]

[R15] 15.Curiel DT, Vogelmeier C, Hubbard RC, Stier LE, Crystal RG. Molecular basis of alpha 1-antitrypsin deficiency and emphysema associated with the alpha 1-antitrypsin Mmineral springs allele. Molecular and cellular biology. 1990;10(1):47–56. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R16] 16.Thun GA, Imboden M, Ferrarotti I, Kumar A, Obeidat M, Zorzetto M, et al. Causal and synthetic associations of variants in the SERPINA gene cluster with alpha1-antitrypsin serum levels. PLoS genetics. 2013;9(8):e1003585. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R17] 17.Lara B, Martinez MT, Blanco I, Hernandez-Moro C, Velasco EA, Ferrarotti I, et al. Severe alpha-1 antitrypsin deficiency in composite heterozygotes inheriting a new splicing mutation QOMadrid. Respiratory research. 2014;15:125. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R18] 18.Fregonese L, Stolk J, Frants RR, Veldhuisen B. Alpha-1 antitrypsin Null mutations and severity of emphysema. Respiratory medicine. 2008;102(6):876–84. [DOI] [PubMed] [Google Scholar]

[R19] 19.von Ehrenstein OS, Maier EM, Weiland SK, Carr D, Hirsch T, Nicolai T, et al. Alpha1 antitrypsin and the prevalence and severity of asthma. Archives of disease in childhood. 2004;89(3):230–1. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R20] 20.Malerba M, Radaeli A, Ceriani L, Tantucci C, Grassi V. Airway hyperresponsiveness in a large group of subjects with alpha1-antitrypsin deficiency: a cross-sectional controlled study. Journal of internal medicine. 2003;253(3):351–8. [DOI] [PubMed] [Google Scholar]

[R21] 21.Eden E, Strange C, Holladay B, Xie L. Asthma and allergy in alpha-1 antitrypsin deficiency. Respiratory medicine. 2006;100(8):1384–91. [DOI] [PubMed] [Google Scholar]

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PERMALINK

α1-Antitrypsin Gene Variation Associates with Asthma Exacerbations and Related Health Care Utilization

Victor E Ortega, MD, PhD

Vickram Tejwani, MD

Abhishek Kumar Shrivastav

Sara Pasha, MD

Joe G Zein, MD, PhD

Meher Boorgula, MS

Mario Castro, MD, MPH

Loren Denlinger, MD, PhD

Serpil C Erzurum, MD

John V Fahy, MD

Elliot Israel, MD

Nizar N Jarjour, MD

Bruce Levy, MD

David Mauger, PhD

Wendy C Moore, MD

Sally E Wenzel, MD

Prescott Woodruff, MD, MPH

Gregory A Hawkins, PhD

Eugene R Bleecker, MD

Deborah A Meyers, PhD

Abstract

Background:

Objective:

Methods:

Measurements and Main Results:

Conclusions:

Introduction:

Methods:

Study Populations

Resequencing of SERPINA1 for the Identification of Low-frequency and Rare Variants

Figure 1: SERPINA1 SARP1–3 Genetic Study and CCHS α1-antitrypsin Study Flow Diagram.

Statistical Methods

Results:

SARP Multi-Ethnic Study Cohort and the Identification of Rare SERPINA1 Variants

Table 1:

Figure 2: SERPINA1 Missense and Splice Site Intronic Variants Identified in 847 Whites and 446 African Americans from the Severe Asthma Research Program.

Table 2:

Gene-Level Testing of Low Frequency and Rare Functional SERPINA1 Variants

Table 3:

Smoking Interactions and Effects of the PI type Z Genotype on Lung Function and Asthma-Related Healthcare Utilization in SARP

Effects of PI Type Z (Glu366Lys), S (Glu288Val), and non-PI Z/S (VR) Genotypes on Lung Function and Asthma-Related Healthcare Utilization in SARP

Table 4:

Mediating Role of MZ genotype on Asthma-Related Hospitalization in non-Hispanic Whites

Effects of α1-antitrypsin concentrations on asthma severity and exacerbations in CCHS

Figures 4a, b: Relationship Between α1-antitrypsin Concentrations and (a) Probability of Moderate-to-Severe Asthma and (b) Asthma Exacerbations in Asthma Patients from the Cleveland Clinic Health System.

Discussion:

Supplementary Material

Highlights Box:

What is already known about this topic?

What does this article add to our knowledge?

How does this study impact current management guidelines?

Sources of funding:

Role of the funding source:

Declarations of interest:

Footnotes

References:

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

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Links to NCBI Databases

α₁-Antitrypsin Gene Variation Associates with Asthma Exacerbations and Related Health Care Utilization

Effects of PI Type Z (Glu³⁶⁶Lys), S (Glu²⁸⁸Val), and non-PI Z/S (V_R) Genotypes on Lung Function and Asthma-Related Healthcare Utilization in SARP

Effects of α₁-antitrypsin concentrations on asthma severity and exacerbations in CCHS