Background
Alpha-1-antitrypsin deficiency (AATD) is a rare inherited condition caused by mutations of the SERPINA1 gene and is a genetic risk factor for liver and lung disease [
1,
2]. AATD is a model disease to explain the pathogenesis of chronic obstructive pulmonary disease (COPD) based on a dysbalance of proteases and antiproteases. COPD is a heterogeneous disorder with several phenotypes [
3]. Comorbidities often complicate the clinical presentation of patients with COPD and comprise cardiovascular and cerebrovascular diseases, osteoporosis, depression, lung cancer, and diabetes [
4]. Reduction in lung function is an independent risk factor for the presence of cardiovascular diseases [
5] and the presence of cardiac disease impacts on the natural history of COPD and vice versa [
6].
Only a few studies have investigated the comorbidity profile of AATD patients and found increased risk for aortic stiffness and musculoskeletal changes as compared to smokers without COPD [
7] as well as a higher prevalence of bronchiectasis as compared to historical data [
8]. Some studies reported that AATD patients without COPD have a lower risk for developing cardiovascular diseases as compared to PiMM individuals [
9,
10], however this issue remains controversial [
11,
12].
The aim of the present study was to analyze the clinical phenotype of AATD patients within the German COPD cohort “COPD and Systemic Consequences-Comorbidities Network” (COSYCONET). For this purpose, we identified AATD patients in the study cohort and analyzed their basic anthropometric data, pulmonary function parameters, and the presence of comorbidities with a focus on cardiovascular diseases.
Methods
Patient description
We used the baseline dataset of the COSYCONET cohort study (visit 1), which is a prospective, multicentre, observational study. In total, 2741 patients were recruited from September 2010 to December 2013 in 31 study centers throughout Germany. Patients were eligible if they were ≥40 years of age and had a diagnosis of COPD or symptoms of chronic bronchitis. Exclusion criteria were previous lung transplantation, lung volume reduction surgery and lung malignancies, and the presence of moderate or severe exacerbation within the last 4 weeks. Further details of the study have been reported elsewhere [
13].
Patients were classified for COPD severity based on two different methods, GOLD criteria using the 2009 spirometric classification I-IV and the 2011 classification A-D based on the CAT score and spirometry (
www.goldcopd.com). For the spirometric classification (GOLD 2009), patients showing a ratio of FEV
1/FVC < 70% were allocated according their FEV
1%pred and patients having a ratio of FEV
1/FVC > 70% were classified as “at risk” for COPD or GOLD stage 0 [
14] if they: (i) had a doctor’s diagnosis of chronic bronchitis, (ii) reported a severity of cough ≥3 points on the respective COPD Assessment Test (CAT) items and/or (iii) reported a severity of phlegm ≥3 points on the respective CAT item. The current analyses included all patients with GOLD stages 0-IV. Patients with missing severity stage (
n = 19) and unclassified patients according to GOLD and the above definition (
n = 77) were excluded from the analysis resulting in a sample of
n = 2645 patients.
Ethics, consent and permissions
The COSYCONET study was approved by the Ethics Committees of the local study centers. All cohort participants gave their written informed consent.
Definition of alpha-1-antitrypsin deficiency (AATD)
The dataset of visit 1 comprised self-reported information on AATD, medication, and laboratory measurement of the serum AAT concentration. Genotyping data for the SERPINA1 gene were not available for most of the patients. Patients with known AATD were asked to specify this condition and the underlying genotype. Patients were assigned to two major groups: 1) COPD patients without AATD (“COPD”): Patients with no historical information of AATD, no augmentation therapy and normal AAT serum level. Patients with known heterozygous PiMZ status were classified as “COPD without AATD”.
2) Patients with (severe) AATD (“AATD”): Patients with known homozygous PiZZ or other homozygous deficiency mutations, patients with augmentation therapy. For missing genotypes, the medication and AAT serum concentration were evaluated: Subjects with AAT augmentation therapy with an AAT serum concentration value <50 mg/dl were classified as “COPD with AATD”. Based on the presence of augmentation therapy, the “AATD” group was subdivided into AATD with augmentation therapy (“AATD + T”) and without (“AATD-T”). Medication lists were screened for all patients and presence of augmentation therapy led to the classification as AATD patient.
Measurements
Clinical history including information on smoking habits and comorbidities was accessed during visit 1. A 6-min walk test (6MWT) was performed according to the 2002 ATS guidelines [
15]. The BODE index was computed using the algorithm developed by Celli and colleagues [
16]. For the time-up-and-go-test, the duration of the procedure (stand up from the sitting position, walk of 3 m distance and back and sit down again) was measured [
17]. Pulmonary function testing by spirometry and body plethysmography was performed according to the ATS/ERS guidelines [
18] and reference equations were used as described by the Global Lung Function Initiative (GLI) [
19]. The diffusing capacity for carbon monoxide (TLCO) was determined by the single-breath technique following the ERS/ATS guidelines [
20]. The ankle-brachial Index, ABI) was measures as described [
21] and an ABI of <0.9 was considered abnormal according to the American College of Cardiology Foundation/American Heart Association Task Force Practice Guidelines [
22]. Within COSYCONET, patients were asked to make their CT scans available for analysis. These were visually assessed for emphysema and airway changes by a senior radiologist with more than 15 years of experience in chest imaging and COPD. In a lobe-based approach, emphysema was rated semi-quantitatively on a five-point scale for each lobe as follows: <5%, 5–25%, 26–50%, 51–75%, >75%. The emphysema was classified as being centrilobular, including coalescent centrilobular emphysema or panlobular, including advanced destructive emphysema [
23]. Large airways were assessed for the presence of bronchiectasis and wall thickening, small airways for centrilobular nodules and mosaic attenuation pattern. Finally, a decision was made whether the predominant component of the disease was emphysema or abnormalities of the airways.
Statistical analysis
The statistical analysis was performed using SAS software version 9.3 (SAS Institute Inc., Cary, NC, USA). P-values ≤0.05 were considered statistically significant. For quantitative variables, results are shown as lsmean, difference between lsmeans with CI 95% and p-values from GLM (if not stated otherwise). The General Linear Models (GLM) procedure is a method of linear regression that uses the method of least squares and is more robust for variables that do not show a normal distribution. Least squares means (lsmean) refers to as marginal means (or sometimes EMM - estimated marginal means). In an analysis of covariance model, they are equivalent to the group means after having controlled for a covariate. Categorical variables are reported as absolute and relative (%) frequencies and chi-square tests were performed to compare groups. Results are visualized using (grouped) bar charts, histograms or forest plots.
In order to adjust the comparisons for potential confounders, multivariate regression analyses and subgroup analyses were conducted. Comorbidities were compared using logistic regression models adjusted for sex, age groups, pack years, FEV1% pred (GLI), BMI and hypertension (yes/no). Sensitivity analyses omitting hypertension as influencing factor were performed. A Forest plot was used to visualize the adjusted odds ratios (ORs) of selected comorbidities with corresponding 95%-confidence intervals. Differences regarding laboratory parameters were analyzed with linear regression adjusted for sex, age groups, pack years, FEV1% predicted and BMI.
An overall sensitivity analysis was applied in a selected dataset matching 3 non-AATD patients to each AATD patient. Matching criteria were sex, age (± 5 years) and pack years (± 10 years). For all AATD patients but one, 3 controls could be found. Comparisons in this dataset were performed in line with the analysis strategy outlined above.
Discussion
The main finding of the present study is that AATD-related lung disease is associated with fewer manifestations of periphery and coronary artery disease after correction for smoking, age and other potential confounders.
Non-deficient COPD is associated with comorbidities such as cardiovascular disease, lung cancer, or osteoporosis [
25,
26]. A recent study based on health insurance data found a decreased prevalence of ischemic heart disease in AATD individuals as compared to COPD patients [
27]. In the present study, hypertension, diabetes, coronary artery disease, heart failure, and alcoholism were reported significantly less often in AATD as compared to non-AATD COPD. The observed differences in comorbidities between AATD-COPD and COPD patients are associated with biochemical markers, such as significantly lower triglyceride concentrations and lower HbA1c in AATD-COPD than in COPD. After correction for potential cofounders such as age, smoking history and BMI, cardiovascular diseases were still found less frequent among AATD-COPD as compared to COPD patients. The observed differences in the prevalence of hypercholesterolemia between the self-reported data (Fig.
3) and the laboratory measurements (Table
3) could results from the different data sourced or the effect of cholesterol-lowering therapies.
This finding highlights the possibility of specific mechanisms in AATD and/or augmentation therapy that may interfere with the development of cardiovascular disease. There are several contradicting studies that highlight this potential link: AATD patients have increased aortic stiffness compared to control individuals without COPD, as determined by aPWV [
7]. This finding was replicated in another study [
28]. Earlier studies also observed a reduced blood pressure in AATD [
9], however others authors did not find such differences [
29]. A genetic study in the Copenhagen City Heart cohort revealed that the systolic blood pressure is lower in PiZZ and PiMZ individuals compared to PiMM or PiMS individuals. However, PiMZ heterozygosity was associated with increased age as a potential confounder [
10]. A genetic association study examined the frequency of AATD mutations in patients with coronary atherosclerosis and healthy controls and found an association of heterozygosity in the patient group [
11]. As to our knowledge, the present study is the first analysis of a direct comparison of non-deficient and AATD-based COPD patients. It is important to point out that the association of AATD with reduced frequencies of hypertension and ischemic heart disease, or a low ABI (as marker of peripheral artery disease) could only be demonstrated for the combined AATD-T and AATD + T group of patients. The low number of patients within AATD-T subgroup (only 29 patients) did not allow a separate statistical evaluation. Similarly, a previous study based on insurance data [
27] had no information on augmentation therapy. Thus, we are not able to make a firm conclusion whether our finding is associated with AATD per se and/or with augmentation therapy. Based on the small number of patients without augmentation, no conclusion can be drawn about the effect of therapy.
The mechanisms that link AATD or augmentation therapy with decreased frequency of cardiovascular disease are speculative and may be related to the pleiotropic activities of AAT [
30,
31] These activities might include i) loss of vascular elastic recoil and decreased resistance due to excess activity of elastase; ii) upregulation and release of angiopoietin-like protein 4 (Angptl4) by AAT in complex with fatty acids [
32‐
34].; iii) decreased production of inflammatory cytokines, such as TNF-α and IL-1β by AAT [
35]. In addition, a protective role for AAT was demonstrated in the Lipid Coronary Angiography Trial that evaluated male participants after coronary bypass surgery [
12]. Altogether, the data above suggest that the mechanisms that links AATD or augmentation therapy with decreased frequency of cardiovascular disease are likely related to the pleiotropic activities of AAT protein. The effect of AATD on cardiovascular risk might represent an advantageous consequence of the SERPINA1 mutation, in addition to a proposed selective anti-infective advantage by increased inflammation [
36].
The present study revealed additional characteristics of AATD-related lung disease. Patients with AATD significantly more often reported the presence of bronchiectasis, which is in line with previous data [
8]. Another study analyzed the distribution of AATD alleles among patients with bronchiectasis and found an even distribution between patients and controls [
37]. The analysis of the lung phenotype revealed an out-of-proportion loss of diffusion capacity. AATD lung disease is associated with panlobular emphysema, with a predominance in the lower lobe, and with a loss of elastic recoil pressure [
38,
39]. CT studies have shown heterogeneity of the distribution of emphysema [
40,
41]. Indeed, AATD was associated with a significant reduction of TLCO %pred after adjustment for ITGV%pred as well as FEV
1%pred, packyears and BMI as other potentially relevant confounders. A defect of diffusion capacity is known to associate with worse quality of life [
41] and a decrease of KCO was associated with apical loss of lung parenchyma in CT [
40].
Several limitations of the present study have to be taken into account: In the present study the information on comorbidities was based on self-reported statements of a doctor’s diagnosis. Although the COSYCONET cohort study is a multicenter study with a large number of patients, the number of AATD individuals with or without augmentation therapy is limited. The low number of patients without therapy made it difficult to discriminate whether the effect of AATD on cardiovascular risk is associated with the disease or with augmentation therapy. Genotyping data on the SERPINA1 gene were only available for a minority of the patients. Nevertheless, the applied grouping algorithm likely results in a correct separation of individuals with severe AATD. The recruitment strategy of COPD and AATD patients was likely different and could account for a selection and confounding bias. Data on the time course of augmentation therapy were not available.
Acknowledgments
The authors thank Sandra Söhler and Inge Kokot from the COSYCONET office.
Competing interests
Dr. Bals reports grants from BMBF, other from AstraZeneca GmbH, Bayer Schering Pharma AG, Boehringer Ingelheim Pharma GmbH & Co. KG, Chiesi GmbH, GlaxoSmithKline, Grifols Deutschland GmbH, MSD Sharp & Dohme GmbH, Mundipharma GmbH, Novartis Deutschland GmbH, Pfizer Pharma GmbH, Takeda Pharma Vertrieb GmbH & Co. KG., during the conduct of the study; grants from Wilhelm-Sander-Stiftung, grants from Deutsche Krebshilfe, grants from Schwiete-Stiftung, outside the submitted work. Dr. Fähndrich reports other from Grifols, other from CSL Behring, other from AstraZeneca, outside the submitted work. Dr. Janciauskiene has nothing to disclose. Dr. Kleibrinkhas nothing to disclose. Dr. Jörres reports personal fees and grants from GSK, Mundipharma, Bosch, Siemens, custo med and Lufthansa outside the submitted work. Dr. Welte reports personal fees from Grifols, CLS Behring, grants from German MInistry for Research and Education, during the conduct of the study; grants from Bayer, Grifols, Insmed, Novartis, outside the submitted work. Dr. Biertz has nothing to disclose. Dr. Kauczor reports grants, personal fees and non-financial support from Siemens, personal fees from Boehringer Ingelheim, personal fees and non-financial support from Bayer, personal fees from GSK, personal fees from Astra Zeneca, personal fees from Novartis, personal fees from Philips, personal fees from Bracco, outside the submitted work. Dr. Karch reports grants from German Federal Ministry of Education and Research, during the conduct of the study. Dr. Greulich reports personal fees from CSL-Behring, grants and personal fees from Grifols, outside the submitted work. Dr. Vogelmeier reports personal fees from Almirall, personal fees from AstraZeneca, personal fees from Boehringer Ingelheim, personal fees from Chiesi, grants and personal fees from GlaxoSmithKline, grants and personal fees from Grifols, personal fees from Mundipharma, personal fees from Novartis, personal fees from Takeda, personal fees from Cipla, personal fees from Berlin Chemie/Menarini, personal fees from CSL Behring, personal fees from Teva, outside the submitted work. Dr. Koch has nothing to disclose. Dr. Teschler reports personal fees from AstraZeneca, personal fees from Boehringer Ingelheim, personal fees from GlaxoSmithKline, personal fees from Mundipharma, personal fees from Novartis, grants and personal fees from Grifols, grants and personal fees from Behring, personal fees from Berlin Chemie, during the conduct of the study.