Introduction

Alpha-1 antitrypsin (A1AT) is a serine protease inhibitor produced mainly by hepatocytes that protects the lung by neutralizing enzymes, such as neutrophil elastase, that degrade elastin and collagen IV in the alveolar walls. A1AT deficiency (A1ATD) leads to a protease-antiprotease imbalance, predisposes the lungs to tissue damage, and the development of emphysema at a younger age, especially among cigarette smokers.1,2

A1ATD is a serious genetic condition that is inherited in an autosomal codominant manner, with over 150 identified variants affecting A1AT serum levels and functionality. The most common phenotypes associated with A1ATD include PiZZ, PiMZ, and PiSZ, or PiNull, highlighting the disorder’s diverse genetic landscape.3,4 The serum levels of A1AT in the normal PiMM phenotype fall between 80–220 mg/dL (15–53 µmol/L). For patients with A1ATD and serum A1AT levels below 11 µmol/L (80 mg/dL), weekly infusions of purified A1AT derived from healthy human donors are recommended to augment blood and alveolar A1AT levels and reduce the progression of emphysema.5 Because cigarette smoking significantly increases the risk of developing emphysema in patients with A1ATD,6 recognizing the presence of heterozygous alleles in A1AT carriers who smoke tobacco products may provide an additional incentive to quit smoking.7

Among patients with chronic obstructive pulmonary disease (COPD), approximately 2% are diagnosed with A1ATD, yet A1ATD is often unrecognized.8,9 Globally, as many as 1 in 25 individuals are estimated to carry a deficient A1AT gene, and 80,000–100,000 individuals in the US have a severe deficiency. Unfortunately, only about 10% of those affected individuals in the US have been identified.10–12 Underdiagnosis leads to a delay in diagnosis of COPD of several years, with an adverse effect on the patient’s prognosis.13 To address this gap, leading international expert groups, the American Thoracic Society (ATS) and the European Respiratory Society (ERS), jointly recommend screening for A1ATD for all symptomatic adults with emphysema, asthma characterized by incompletely reversible airflow obstruction, bronchiectasis, or unexplained liver disease.1 Notably, while the link between A1ATD and emphysema/COPD is well established, evidence regarding its link to asthma is inconsistent, with some investigators suggesting that patients with both asthma and A1ATD experience worse outcomes.3,4,14 Furthermore, the association of A1ATD with asthma/COPD overlap (ACO) remains unclear.

The Appalachian region, particularly East Tennessee, offers a unique environment for studying the prevalence of A1AT phenotypes. The population in East Tennessee is thought to have a lower racial diversity and a higher risk of genetic diseases compared to the overall US population.15

According to the available data, smoking rates in Tennessee are approximately 4.5% higher than the national average (14%).16 Moreover, Tennessee exceeds national averages in the prevalence of COPD (10.4%) and adult asthma (11.0%).17–19 There are limited data on heterozygous A1AT alleles from this region, consisting of only a brief report from the Appalachian Regional Healthcare and a conference abstract from East Tennessee.17,20 Yet, the prevalence of A1ATD among individuals with COPD, asthma, or ACO in East Tennessee, along with its correlation to serum A1AT levels and pulmonary function, has not been previously documented in the existing literature.

This study aimed to investigate the prevalence of A1AT alleles in a cohort of patients with COPD, asthma, or ACO attending a general pulmonary clinic at a tertiary academic medical center in East Tennessee and to evaluate the associations between A1AT alleles, serum A1AT levels, and pulmonary function.

Materials and Methods

This IRB-approved, single-center, retrospective study was conducted at the University Pulmonary and Critical Care (UPCC) clinic at the University of Tennessee Medical Center (UTMC), a tertiary academic medical center in Knoxville, TN. The local IRB waived the requirement for written consent. The study included patients of all ages, both sexes, all races, and any smoking status who were seen in the clinic between July 2019 and December 2023 with a primary diagnosis of COPD, asthma, or ACO. Patients with ACO had overlapping features of asthma and COPD based on history, physical examination, radiology, and comprehensive pulmonary function tests. Patients with a history of lung cancer or cystic fibrosis were excluded from the study.

Data Collection

Patients’ demographics (age, sex, smoking history), medical records, pulmonary function test results, and laboratory data, including serum A1AT levels and phenotypes, were retrospectively extracted from their electronic medical records (EMR). Smoking history was calculated in pack-years, defined as the number of packs of cigarettes smoked per day multiplied by the duration of smoking in years.21

The A1AT phenotype and serum A1AT levels were measured from blood samples obtained by venipuncture. The specimens were processed using multiplex allele-specific polymerase chain reaction (PCR) amplification, followed by gel electrophoresis (LabCorp; Burlington, NC). Patients were classified into A1AT phenotypic groups based on their PCR results, including PiMM, PiMZ, PiSZ, and PiZZ. Serum A1AT levels were measured in milligrams per deciliter (mg/dL), with a normal reference range of 80–220 mg/dL (15–53 µmol/L) for individuals with the MM genotype.

Pulmonary Function Tests

Pulmonary function tests (PFTs) were conducted in accordance with ATS/ERS standards using calibrated Vyntus and V-Max Vyaire body box (Vyaire, Lake Forest, USA). Spirometry, lung volume measurements, and diffusion capacity of the lung for carbon monoxide (DLCO) tests were performed, with all procedures meeting criteria for acceptability and reproducibility. For spirometry, at least three reproducible efforts were required, and pre-bronchodilator values were used for analysis. Lung volumes were measured using body plethysmography, and DLCO tests were considered reproducible if the results differed by < 10%. Results were analyzed using reference equations from the National Health and Nutrition Examination Survey (NHANES III) adjusted for age, sex, height, and ethnicity.22,23 Trained respiratory technologists performed all the tests and ensured strict quality control throughout the study.

Data Analysis

Descriptive statistics were used to summarize patient demographics, smoking history, and disease characteristics. Continuous variables, such as serum A1AT levels and pulmonary function test results, were summarized using means and standard deviations (SD). For non-normally distributed data, non-parametric statistical tests were employed. Differences in serum A1AT levels and pulmonary function tests across phenotypic groups were analyzed using the Kruskal–Wallis test. Post-hoc comparisons were performed using Dunn’s test with a Bonferroni correction for multiple comparisons. PFT measures were also regressed on A1AT phenotype, age, gender, BMI, total pack years, and diagnosis. This test was performed as a multiple linear regression with HC3 standard errors due to small sample sizes and heteroskedasticity in the sample. Statistical significance for all analyses was assumed at a two-sided alpha value of 0.05. The relationships between serum A1AT levels, pack-years of smoking history, and pulmonary function tests were evaluated using simple linear regression. All statistical analyses were performed using IBM SPSS Statistics (Version 29).

Results Participants Characteristics

Out of the N = 177 patients included in the study, the majority were white (n = 167, 94.4%), females (n = 105, 59.3%), and their average age was 63.2 (SD ± 11.9) years. Among the participants, n = 89 (50.3%) were former tobacco smokers, and n = 51 (28.8%) were current smokers, with a mean smoking history of 33.1 pack-years (SD ± 30.6) (Table 1). Additionally, as shown in Table 2, n = 88 patients (49.7%) had COPD, n = 24 (13.6%) had asthma, and n = 65 (36.7%) had ACO.

Table 1 Demographics of Patients in the Study

Table 2 Clinical Characteristics and A1AT Phenotypes

A1AT Phenotype Distribution and Serum A1AT Levels

The clinical diagnosis, comorbidities, and distribution of various A1AT phenotypes are summarized in Table 2. The PiMM phenotype was observed in n = 139 patients (78.5%), while n = 22 (12.4%) had the PiMS phenotype, n = 14 (7.9%) had the PiMZ/PiSZ/PiXZ phenotypes, and n = 2 (1.1%) had the PiZZ phenotype. Among those with COPD and asthma, 23.9% and 8.3%, respectively, carried heterozygous alleles (PiMS, PiMZ, PiSZ, or PiXZ; Table 3). Among patients with ACO, 20.0% had heterozygous alleles.

Table 3 A1AT Phenotypes in Patients with COPD, Asthma, and Asthma-COPD Overlap (ACO)

A subset of patients (n=90) who had both a documented A1AT phenotype and a measure of A1AT serum levels were used to compare serum levels by group. Analysis using the Kruskal–Wallis test revealed a significant effect of phenotype on serum A1AT levels (Χ2 = 22.50; p = 0.0001). Post hoc tests showed that serum A1AT levels differed significantly between patients with the PiMM phenotype and those with the PiMZ/PiSZ/PiXZ phenotypes (p < 0.001). Additionally, there was a significant difference in serum A1AT levels between patients with the PiMS and those with PiMZ/PiSZ/PiXZ phenotypes (p = 0.003). However, serum A1AT levels in patients with the PiMM and PiMS phenotypes showed no difference (p = 0.36, Table 4). Patients with the PiZZ phenotype were excluded from this analysis due to the small number of patients in this group (n=2).

Table 4 A1AT Serum Levels

Pulmonary Function Tests and Correlation with A1AT Phenotypes and Serum Levels

Patients with PiMM and PiMS phenotypes showed no statistically significant differences in the percent predicted values of forced vital capacity (FVC), forced expiratory volume in 1 second (FEV1), total lung capacity (TLC), and DLCO (p>0.05 for all; Table 5). Patients with PiMZ, PiSZ, and PiXZ phenotypes exhibited a non-significantly lower percent predicted FEV1, FVC, TLC, and DLCO compared to those with PiMM and PiMS phenotypes (p > 0.05 for all; Table 5 and Figure 1). Patients with the PiZZ phenotype were excluded from this analysis due to the small number of patients in this group (n=2). Multiple regression analysis found no statistically significant difference between patients with PiMM, PiMS, PiMZ, PiSZ, and PiXZ phenotypes on various PFT measures controlling for age, gender, BMI, diagnosis, and smoking history (p > 0.05 for all; Table 6). However, controlling for A1AT phenotypes, there were significant differences between PFT measures and some of the covariates, such as gender, BMI, smoking history, and diagnosis (Table 6). On average, patients with asthma had higher FEV1 (p<0.001), FVC (p=0.02), FEV1/FVC (p<0.001), and DLCO (p=0.005), and patients diagnosed with ACO had higher FEV1 (p=0.02), FEV1/FVC (p=0.02), and DLCO (p=0.002) scores compared to those with COPD.

Table 5 Pulmonary Function Tests in Patients*

Figure 1 Mean values of FVC (%predicted), FEV1(%predicted), FEV1/FVC% and DLCO(%predicted) across A1AT phenotype groups. Bars represent standard deviation (SD). No statistically significant differences in pulmonary function were observed between phenotype groups (p>0.05). Data for the ZZ phenotype were excluded due to the small number of patients in that subgroup.

Abbreviations: A1AT, alpha-1 antitrypsin; FVC, forced vital capacity; FEV1, forced expiratory volume in 1 second; DLCO, diffusing capacity of the lung for carbon monoxide.

Table 6 Pulmonary Function Test Measures Regressed on A1AT Phenotype, Demographics, and Medical Characteristics

Figures 2 and 3 show no significant correlation between FEV1 and FEV1/FVC% with serum A1AT levels. There was a weak but statistically significant negative correlation between FVC (r =−0.29; p = 0.01) and DLCO (r = −0.27; p = 0.03) with serum A1AT levels.

Figure 2 Scatterplots of A1AT serum level (mg/dl) versus FVC (%predicted) (A) and FEV1 (%predicted) (B) with best-fit linear regression lines. A weak, but statistically significant inverse correlation was found between A1AT serum levels and FVC (predicted) (r = −0.29, p = 0.01). No significant correlation was found between serum A1AT levels and FEV1 (%predicted) (r = −0.12, p = 0.29).

Abbreviations: A1AT, alpha-1 antitrypsin; FVC, forced vital capacity; FEV1, forced expiratory volume in 1 second.

Figure 3 Scatterplots of A1AT serum level (mg/dl) versus FEV1/FVC% (A) and DLCO (%predicted) (B) with best-fit linear regression lines. A weak, but statistically significant inverse correlation was found between A1AT serum levels and DLCO (%predicted) (r = −0.27, p = 0.03). No significant correlation was found between serum A1AT levels and FEV1/FVC% (%predicted) (r = 0.03, p = 0.78).

Abbreviations: A1AT, alpha-1 antitrypsin; FEV1, forced expiratory volume in 1 second; FVC, forced vital capacity; DLCO, diffusing capacity of the lung for carbon monoxide.

Pulmonary Function Tests and Correlation with Cumulative Tobacco Smoking Exposure

We evaluated the effect of cumulative smoking exposure on lung function in our cohort. Consistent with the known progressive decline in lung function with cumulative tobacco smoking exposure, we found a significant negative correlation between pack-years of smoking and the decline in FEV1, FVC, FEV1/FVC% ratio, and DLCO (Figure 4).

Figure 4 Scatterplots of total pack-years smoked versus FEV1/FVC% (A) and DLCO (percent predicted) (B), with best-fit linear regression lines. Total pack-years smoked was negatively correlated with both FEV1/FVC% (r=−0.31, p < 0.001) and DLCO (%predicted)(r=−0.51, p < 0.001).

Abbreviations: FEV1, forced expiratory volume in 1 second; FVC, forced vital capacity; DLCO, diffusing capacity of the lung for carbon monoxide.

Discussion

In this first detailed report of alpha-1 antitrypsin phenotypes and alleles, we examined serum A1AT levels and their correlation with pulmonary function among a general pulmonary clinic population in East Tennessee. We found an unexpectedly high frequency of heterozygous alpha-1 antitrypsin phenotypes (PiMS/PiMZ/PiSZ/PiXZ) in our patients with COPD or ACO. The frequency of heterozygous alleles was lower in patients with asthma (8%) than in those with COPD (~24%) or ACO (20%). Compared to the PiMM phenotype, serum A1AT levels were lower in the PiMZ/PiSZ/PiXZ phenotypes, but pulmonary function did not correlate with A1AT phenotypes; however, interestingly, serum A1AT levels showed a weak negative correlation with FVC and DLCO but no correlation with indicators of airflow obstruction (FEV1 or FEV1/FVC%).

Approximately 116 million individuals worldwide carry at least one abnormal A1AT allele, with 3.4 million having severe deficiency alleles such as PiZ, PiS, and PiNull. The incidence of the PiZZ phenotype is estimated at 1 in 2500 to 5000 people.1,7 The prevalence of different A1AT phenotypes, especially PiZZ, can vary widely across regions and ethnic groups. In the United States, the estimated number of individuals with the PiZZ phenotype ranges from 70,000 to 100,000 individuals, with about 2–3% of the population carrying at least one deficiency allele.1,12,24 We also found that the PiZZ phenotype was present in 2% of our cohort. However, the regional prevalence of heterozygous alleles within the US is not well documented. To our knowledge, no prior research has specifically investigated the prevalence of A1AT phenotypes in Appalachia, despite the region’s higher COPD prevalence than the national average.18,19,25–27

Historically, populations in the Appalachian region, including East Tennessee, were believed to have lower genetic diversity due to geographic isolation.15 Yet demographic data from the 1970s suggest this pattern may be changing, with increased migration and reduced isolation.15 However, the occurrence of A1ATD and frequency of heterozygous alleles in this population has not been determined, except for a brief report from a rural pulmonary clinic in Eastern Kentucky that described A1AT phenotypes in 56 patients from the Appalachian Regional Healthcare. None of these patients had the PiZZ phenotype, while the PiMS phenotype was present in 34 patients, and the PiMZ phenotype in 22 patients.17 In contrast to our study population, the prevalence of PiSZ and PiZZ phenotypes was less than 2%. Another conference presentation reported A1AT heterozygous alleles in 12.4% of 499 Tennesseans.20 Using the Hardy-Weinberg equilibrium, these authors suggested that allele and genotype frequencies are stable in this population.20

A recent nationwide report of US veterans with COPD found that 4.16% had various A1ATD phenotypes and 1.56% had low serum A1AT levels with PiZZ and PiSZ phenotypes.28 In contrast, we did not find the PiZZ phenotype in any of the 88 patients with COPD or the 24 patients with asthma. In the 65 patients with ACO, 2 patients (3.1%) had the PiZZ phenotype. Compared to veterans, there was a much higher frequency of heterozygous phenotypes in our patients with COPD (~4% vs ~24%, respectively). Our findings raise the question of whether the high carrier rate of heterozygous A1AT alleles among East Tennesseans is clinically significant. Other risk factors for the development of COPD, such as cigarette smoking, working in dusty occupations, and parental history of COPD that influence emphysema development in COPD in individuals with A1ATD, are highly prevalent in East Tennesseans, but it is possible that heterozygous A1AT alleles could also be an unrecognized contributory factor.29 Future population surveys and epidemiologic studies are warranted to determine the clinical impact of this higher prevalence of heterozygous A1AT alleles on the occurrence of asthma and COPD in East Tennessee.

In our study, 76% of patients with COPD had the PiMM phenotype, whereas nearly one-quarter had heterozygous A1AT phenotypes, including PiMS in 13.6% and PiMZ/PiSZ/PiXZ in 10.2%. In comparison, previous investigators reported the frequency of the PiMM phenotype in patients with COPD ranging from 58.2% in Germany to 92.9% in the Spanish Canary Islands and Turkey.3,30,31 Other phenotypes were reported in approximately 20 to 30% of patients. Additionally, the prevalence of the PiZZ phenotype among patients with COPD varies, with reported rates of 1.2% in Spain and as high as 9.1% in Germany.3,30 Likewise, Ozdemir et al reported abnormal A1AT alleles in 4% of 794 patients with radiographic emphysema attending a pulmonary clinic in Turkey.32 Our report of the frequency of heterozygous A1AT is also higher than a 7.4% prevalence of heterozygous alleles in patients with COPD from a clinic in Brazil.33 These reports highlight regional differences in the prevalence of A1AT phenotypes among patients with COPD and underscore the need for targeted studies to assess the extent of the problem in each community.

The link between A1AT heterozygous carriers and asthma or ACO has not been well elucidated in the literature. In our study, A1AT phenotypes PiMS, PiMZ, PiSZ, or PiXZ were observed in 8.3% and 20% of patients with asthma and ACO, respectively. In previous studies, the PiMS phenotype has been reported in 6.5% to 18.6% of asthmatic cohorts, while other phenotypes have been documented in less than 10% to nearly one-third of patients.3,30 Similar to populations with COPD, the PiZZ phenotype appears uncommon in asthma, with reported prevalence ranging from 0% to 2.8%.3 Interestingly, the phenotype distribution in patients with ACO in our study more closely resembled that of patients with COPD than that of patients with asthma. Abnormal A1AT phenotypes were observed in 1 in 5 patients with ACO, and 3.1% had the PiZZ phenotype. An earlier report from Germany reported a higher prevalence of PiZZ (7.2%) in patients with ACO.3 It is conceivable that patients with asthma who smoke cigarettes and have heterozygous A1AT alleles are more susceptible to developing ACO and emphysema/irreversible airflow obstruction.

Across all A1AT phenotypes, there were no statistically significant differences in FEV1, FVC, FEV1/FVC%, TLC, or DLCO. However, there was a statistically insignificant trend indicating lower values in individuals with the PiMZ, PiSZ, and PiXZ phenotypes (Table 5 and Figure 1). These results are consistent with previous studies showing that individuals with the PiMZ phenotype do not show significant differences in lung function compared to those with the PiMM phenotype.34 Similar findings have been reported for individuals with the PiSZ phenotype, suggesting that they may have a pulmonary function profile and risk of obstructive lung disease comparable to those with the PiMZ phenotype.35

We found that a higher cumulative pack-years history of smoking had a direct correlation with declines in FEV1, FVC, FEV1/FVC ratio, and DLCO. The link between tobacco smoking and decline in pulmonary function is well established in the literature; researchers have long identified a dose–response relationship between smoking and decreased lung function.36 We observed a similar pattern of decline in pulmonary function among smokers regardless of the patients’ A1AT phenotypes.

Serum A1AT levels in patients with heterozygous A1AT phenotypes (PiMZ, PiSZ, PiXZ) were significantly lower compared to those in the PiMM/PiMS group. Additionally, we did not find a statistically significant difference between the PiMM and PiMS groups. An observational study of 441 participants by Brantly et al also reported that serum A1AT levels were highest in the PiMM and PiMS groups, and significantly lower in other A1AT heterozygotes, with the lowest levels observed in those with the PiZZ phenotype.37

We had the advantage of performing DLCO measurements in our clinic-based patients, as it would be impractical to perform this test in a field setting. There were significant but weak negative correlations between FVC, DLCO, and serum A1AT levels, but no correlation with indicators of airflow obstruction (FEV1 or FEV1/FVC%). Similar findings have been reported in patients with asthma and COPD.33,38 However, we could not find previous reports describing such a relationship in patients with ACO, particularly regarding DLCO.39,40

Our study has some limitations. We studied patients coming to our clinic for more than 4 years. Despite this extended time interval, we had complete data on only 177 patients. Thus, the lack of differences in serum A1AT levels and PFT measures could be due to a Type II error, and studies with larger samples are needed. Although the sample size is small, this is the first comprehensive evaluation of A1AT phenotypes from this region of the country. Moreover, our study was not population-based, and the clinic population may not be representative of the patients with COPD, asthma, or ACO in the general population. However, certain pulmonary function studies, such as DLCO, are only feasible in the clinic setting. The frequent occurrence of heterozygous A1AT alleles was unexpected, and further population-based studies are warranted to evaluate the association of these heterozygous A1AT phenotypes with declines in pulmonary function and the development of COPD in the East Tennessee region.

Conclusion

In our general pulmonary clinic in East Tennessee, we found an unexpectedly high prevalence of abnormal A1AT phenotypes (~ 20–24%) in patients with COPD and ACO, and to a lesser extent in patients with asthma. A1AT serum levels in heterozygote A1AT phenotypes (PIMZ, PiXZ, PiSZ) were significantly lower than those with the PiMM phenotype. We were unable to establish a significant correlation between A1AT phenotypes and spirometric indicators of airflow obstruction. The frequent occurrence of heterozygous A1AT phenotypes in patients with COPD, ACO, and asthma may be clinically relevant to emphysema development, and the association of A1AT heterozygosity with COPD, asthma, and ACO warrants further exploration in larger, prospective, population-based studies in East Tennessee.

Abbreviations

A1AT, alpha-1 antitrypsin; A1ATD, alpha-1 antitrypsin deficiency; ACO, asthma-COPD overlap; ATS, American Thoracic Society; BMI, body mass index; CAD, coronary artery disease; CHF, congestive heart failure; COPD, chronic obstructive pulmonary disease; DLCO, diffusing capacity of the lung for carbon monoxide; EMR, electronic medical record; ERS, European Respiratory Society; FEV1, forced expiratory volume in 1 second; FVC, forced vital capacity; IRB, Institutional Review Board; NHANES, National Health and Nutrition Examination Survey; PCR, polymerase chain reaction; PFTs, pulmonary function tests; SD, standard deviation; TLC, total lung capacity; UPCC, University Pulmonary and Critical Care; UTMC, University of Tennessee Medical Center.

Data Sharing Statement

The datasets generated and/or analyzed during the current study are not publicly available due to patient privacy and institutional restrictions.

Ethics Approval and Informed Consent

This retrospective study was reviewed and approved by the Institutional Review Board of the Graduate School of Medicine, University of Tennessee Medical Center, Knoxville, Tennessee, USA. The study was approved under IRB# 5032. Administrative approval was granted on November 7, 2023. The study was conducted in accordance with the principles of the Declaration of Helsinki. The requirement for written informed consent was waived by the Institutional Review Board because of the retrospective nature of the study. Patient data were handled confidentially and de-identified prior to analysis.

Acknowledgments

The authors received no financial support for the research/authorship of this article. The abstract of this paper was presented at the American College of Chest Physicians (CHEST) Annual Meeting 2024 as a poster presentation with interim findings. The poster abstract was published in CHEST, Volume 166, Issue 4, Supplement, Pages A4842–A4843. Available at: https://doi.org/10.1016/j.chest.2024.06.2873

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Funding

The authors received no financial support for the research, authorship, or publication of this article.

Disclosure

Rajiv Dhand reports Grants or contracts from Viatris; Royalties or licenses from Taylor and Francis, UptoDate, outside the submitted work. The authors report no other conflicts of interest in this work.

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