Cardiovascular risk in patients with alpha-1-antitrypsin deficiency
Fähndrich et al. Respiratory Research
Cardiovascular risk in patients with alpha-1- antitrypsin deficiency
Sebastian Fähndrich 1
Frank Biertz 3
Annika Karch 3
Björn Kleibrink 2
Armin Koch 3
Helmut Teschler 2
Tobias Welte 8
Hans-Ulrich Kauczor 6 7
Sabina Janciauskiene 8
Rudolf A. Jörres 5
Timm Greulich 9 10
Claus F. Vogelmeier 9 10
Robert Bals 0 1 4
on behalf of the COSYCONET investigators
0 Department of Internal Medicine V - Pulmonology, Allergology, Intensive Care Medicine , 66421 Homburg, Saar , Germany
1 Department of Internal Medicine V, Pulmonology, Allergology, Intensive Care Medicine, Saarland University Hospital , 66424 Homburg , Germany
2 Department of Pneumology, Ruhrlandklinik, West German Lung Center, and University Hospital Essen, University Duisburg-Essen , Essen , Germany
3 Institute for Biostatistics, Hannover Medical School , 30625 Hannover , Germany
4 Department of Internal Medicine V - Pulmonology, Allergology, Intensive Care Medicine , 66421 Homburg, Saar , Germany
5 Institute and Outpatient Clinic for Occupational, Social and Environmental Medicine, Ludwig-Maximilians-Universität München , 80336 Munich , Germany
6 Translational Lung Research Center (TLRC), Member of the German Center for Lung Research , Heidelberg , Germany
7 Department of Diagnostic and Interventional Radiology, University of Heidelberg , 69120 Heidelberg , Germany
8 Clinic for Pneumology, Hannover Medical School, Member of the German Center for Lung Research , 30625 Hannover , Germany
9 Member of the German Center for Lung Research (DZL) , Marburg , Germany
10 Department of Medicine, Pulmonary and Critical Care Medicine, University Medical Center Giessen and Marburg, Philipps-Universität Marburg , Marburg , Germany
Background: Alpha-1-antitrypsin deficiency (AATD) is a rare inherited condition caused by mutations of the SERPINA1 gene that is associated with the development of a COPD like lung disease. The comorbidities in patients with AATDrelated lung diseases are not well defined. The aim of this study was to analyze the clinical phenotype of AATD patients within the German COPD cohort study COSYCONET (“COPD and SYstemic consequences-COmorbidities NETwork”) cohort focusing on the distribution of comorbidities. Method and results: The data from 2645 COSYCONET patients, including 139 AATD patients (110 with and 29 without augmentation therapy), were analyzed by descriptive statistics and regression analyses. We found significantly lower prevalence of cardiovascular comorbidities in AATD patients as compared to non-AATD COPD patients. After correction for age, pack years, body mass index, and sex, the differences were still significant for coronary artery disease (p = 0.002) and the prevalence of peripheral artery disease as determined by an ankle-brachial-index <= 0.9 (p = 0.035). Also the distribution of other comorbidities such as bronchiectasis differed between AATD and non-deficient COPD. Conclusion: AATD is associated with a lower prevalence of cardiovascular disease, the underlying mechanisms need further investigation.
Alpha-1-antitrypsin deficiency; Phenotype; Cardiovascular disease; Emphysema; Personalized medicine
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
]. 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 . Comorbidities often complicate the
clinical presentation of patients with COPD and comprise
cardiovascular and cerebrovascular diseases,
osteoporosis, depression, lung cancer, and diabetes [
in lung function is an independent risk factor for the
presence of cardiovascular diseases [
] and the presence
of cardiac disease impacts on the natural history of
COPD and vice versa [
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 [
] as well as a higher prevalence
of bronchiectasis as compared to historical data [
studies reported that AATD patients without COPD have
a lower risk for developing cardiovascular diseases as
compared to PiMM individuals [
], however this issue
remains controversial [
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
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 [
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 FEV1/FVC < 70% were
allocated according their FEV1%pred and patients having
a ratio of FEV1/FVC > 70% were classified as “at risk”
for COPD or GOLD stage 0 [
] 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.
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 [
]. The BODE index was computed
using the algorithm developed by Celli and colleagues
]. 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
]. Pulmonary function testing by spirometry
and body plethysmography was performed according to
the ATS/ERS guidelines [
] and reference equations
were used as described by the Global Lung Function
Initiative (GLI) [
]. The diffusing capacity for carbon
monoxide (TLCO) was determined by the single-breath
technique following the ERS/ATS guidelines [
ankle-brachial Index, ABI) was measures as described [
and an ABI of <0.9 was considered abnormal according to
the American College of Cardiology Foundation/American
Heart Association Task Force Practice Guidelines [
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 [
]. 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.
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
A total of 139 patients with AATD were identified (5.2%
of total cohort). Of these, 110 patients (79.1%) received
AAT augmentation therapy, whereas 29 patients (20.9%)
reported no augmentation therapy or information on
this therapy was missing. The AATD group comprised
106 Pi ZZ patients (78.5%), 2 with PiSZ genotype, 20
with unknown genotype but augmentation therapy and
11 patients with unknown genotype and no or unknown
augmentation treatment. These 11 patients were
classified as AATD patients because of the low serum levels
of AAT (< 50 mg/dl). The group of COPD subjects
without AATD included 8 patients with self-reported AATD
of genotype Pi MZ, 16 patients with self-reported AATD
of unknown genotype but normal AAT serum level and
no replacement treatment, and 2482 patients without
AATD according to self-report and medication.
The characteristics of the individuals with AATD with
(“AATD + T”) or without augmentation therapy (“AATD-T”)
and individuals with COPD only (“COPD”) are shown in
Table 1. As expected, there were significant differences
between COPD and AATD patients. AATD patients were
younger, had a lower BMI, and had smoked considerably less.
AATD-T as compared to AAT + T patients were younger,
showed less severe lung disease and better performance in the
We next focused on the lung disease phenotype (Table 2).
As compared to non-deficient COPD, AATD + T patients
showed more severe airflow limitation as indicated by
significantly lower FEV1%pred, lower FEV1/FVC and
increased effective specific airway resistance sRaweff %pred.
In contrast, AATD-T individuals had less airflow limitation
as compared to the COPD or AATD + T groups. Some
patients provided CT scans obtained for the clinical
purposes up to 4 years prior to inclusion into our study. In
total, 356 CT scans from 2506 COPD patients (14.2%) and
23 CT scans from 139 AATD patients (16.5%) were
available, which did not allow to perform AATD patients
grouping according to augmentation therapy. Hence, AATD
patients showed more emphysema, with 16% having an
involvement of more than 75% of lung as compared to only
3% within COPD group (Additional file 1: Table S1). At the
same time, wall thickening of the airways was less
frequently observed in the AATD group, while bronchiectasis
was more frequent as compared to the COPD group.
Next we performed a multivariate regression analysis
with TLCO %pred as dependent variable, which is related
to emphysema and linked to other parameters that differ
between AATD and COPD groups [
]. The presence of
AATD was associated with a significant reduction of
TLCO %pred after adjustment for airway obstruction in
terms of FEV1% pred, lung hyperinflation in terms of
ITGV %pred and for COPD risk factors, such as smoking
(pack-years) and BM (Fig. 1 and Additional file 1: Table
S2). This difference is illustrated for ITGV%pred in
Additional file 1: Figure S1A, B and for BMI in Additional
file 1: Figure S1C, D. The reduction of TLCO in AATD is
greater than expected from other parameters known to be
associated with COPD and emphysema.
Sensitivity analysis in a dataset matched for age, sex
and pack years was performed. In the matched dataset,
AATD-COPD patients (n = 138) had a similar 6-min
walk distance and a comparable time-up-and-go test as
patients of the COPD group (n = 414) (6-MWT:
437 ± 111 vs. 440 ± 11 m, time-up-and-go: 6.0 vs. 6.2 s
as median time). Differences in pulmonary assessments
remained highly significant in the matched dataset.
sRaweff showed a (nearly significant) trend towards
increased airflow resistance in the AATD-COPD
patients with a median of 133%pred. as compared to
115%pred. in patients without AATD (p = 0.053).
Cardiovascular diseases are less frequent in AATD + T patients after adjustment for potential confounders
In a first step, we analyzed lung-specific comorbid
entities, for which AATD individuals reported increased
prevalence of bronchiectasis as compared to the COPD
patients (Fig. 2).
Next, we analyzed the distribution of extra-pulmonary
comorbidities and found significant differences between
AATD and COPD patients, with particularly lower
frequencies of cardiovascular and related diseases
(hypertension, chronic heart failure, diabetes, cardiac infarction, and
cardiac arterial disease) in AATD (Fig. 3). These changes
were concordant for patients with and without
augmentation therapy and remained significant when AATD + T
and AATD-T were combined (prevalence in COPD vs.
AATD: hypertension 57 vs. 41%, chronic heart failure 11
vs. 2%, diabetes without insulin 9 vs. 3%, cardiac infarction
9 vs. 1%, and cardiac arterial disease 3 vs. 17%). Logistic
regression models with adjustment for sex, age, pack
years, FEV1%pred, BMI and hypertension revealed
significant differences between CODP and AATD + T patients
for selected comorbidities (Fig. 4 and Additional file 1:
Table S3). The number of AATD-T patients was too low
to perform this type of analysis. These data indicate that
in AATD + T patients cardiovascular diseases were less
frequent after adjustment for potential confounders. Based
on the small number of patients without augmentation,
no conclusion can be drawn about the effect of therapy.
AATD is associated with lower triglyceride and lower
To reveal whether AATD patients have altered levels of
biochemical risk markers for cardiovascular disease in
the blood, we analyzed laboratory data (Table 3). Levels
of triglycerides were lower in the AATD + T group,
while cholesterol was higher in the AATD-T group.
HDL-cholesterol was higher in AATD patients
independent of augmentation therapy. HbA1c was lower in
sRaw eff %
AATD patients. As compared to the COPD group,
HDL-cholesterol was higher and HbA1c was lower in
AATD patients independent of augmentation therapy.
Multivariate linear analyses adjusting for sex, age,
packyears, FEV1%pred and BMI supported these findings
(parameter estimates, p-values): triglycerides as well as
HBa1c were lower in AATD patients as compared to
COPD (triglycerides −39.5 mg/dl, p < 0.001; HBa1c
−2.5 mmol/mol, p = 0.002). HDL-cholesterol was not
significantly different between AATD + T and AATD-T
(+2.4, p = 0.223), but cholesterol was significantly higher
in AATD-T group (+22.9, p = 0.038).
The main finding of the present study is that
AATDrelated 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
]. A recent study based on health
insurance data found a decreased prevalence of
ischemic heart disease in AATD individuals as compared
to COPD patients . 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
AATDCOPD 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
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 [
]. This finding was replicated
in another study [
]. Earlier studies also observed a
reduced blood pressure in AATD [
], however others
authors did not find such differences [
]. 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 [
]. 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 [
]. 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 [
] 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
] These activities might include i) loss of
vascular elastic recoil and decreased resistance due to excess
activity of elastase; ii) upregulation and release of
angiopoietinlike protein 4 (Angptl4) by AAT in complex with fatty acids
].; iii) decreased production of inflammatory
cytokines, such as TNF-α and IL-1β by AAT . In addition, a
protective role for AAT was demonstrated in the Lipid
Coronary Angiography Trial that evaluated male participants
after coronary bypass surgery [
]. 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 [
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 [
study analyzed the distribution of AATD alleles among
patients with bronchiectasis and found an even
distribution between patients and controls [
]. 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
]. CT studies have shown heterogeneity of
the distribution of emphysema [
]. Indeed, AATD
was associated with a significant reduction of TLCO
%pred after adjustment for ITGV%pred as well as
FEV1%pred, packyears and BMI as other potentially
relevant confounders. A defect of diffusion capacity is
known to associate with worse quality of life [
] and a
decrease of KCO was associated with apical loss of lung
parenchyma in CT [
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
In conclusion, within the German COPD cohort
COSYCONET we found that AATD is associated with a lower
number of cardiovascular comorbidities even after adjustment for
confounders. The underlying mechanisms are currently
unclear. These data add to the understanding of the complex
biology of AATD and indicated that AATD likely impacts on
processes involved in cardiovascular disease.
Additional file 1: Table S1. Analysis of lung density by CT (available for
379 patients). (f) n = 3 missings, (g) n = 89 missings, *panlobular
emphysema, PLE; centrilobular emphysema, CLE. Table E2. Multivariate
linear regression model with TLCO %pred. as dependent variable. AATD
refers to the presence of AATD versus COPD. Figure S1. Patients with
AATD revealed a reduced TLCO %pred at similar levels of ITGV %pred. (A,
B) or BMI (B, D) for both female and male patients after adjustment for
FEV1, sex, BMI, packyears, and age (AATD - dotted line, COPD - straight
line). Table S3. Results (Odds Ratio [95% confidence interval] and
p-value) of multivariable logistic regression analyses for different
comorbidities as dependent variable. (DOCX 265 kb)
6-MWT: 6-min walk test; ABI: Ankle-brachial-index; alpha-1: Antitrypsin
deficiency; BMI: Body mass index; CAT: COPD assessment test; COPD: Chronic
obstructive lung disease; COSYCONET: COPD and SYstemic
consequencesCOmorbidities NETwork; FEV1: Forced expiratory volume in 1 s; FVC: Forced
vital capacity; OR: Odd ratio; sRaw: Specific airway resistance; TLCO: Transfer
factor for CO
The authors thank Sandra Söhler and Inge Kokot from the COSYCONET office.
COSYCONET was financially supported by Competence Network Asthma/
COPD, funded by the German Federal Ministry of Education and Research,
FKZ 01GI1001, as well as by unrestricted grants from a consortium of
pharmaceutical companies including 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.
Availability of data and materials
The COSYCONET data are available to researchers and a respective data
management policy applies (http://www.asconet.net/html/cosyconet).
Conception and design, RB, SF, CV. Drafting of the manuscript, RB, SF, FB,
RAJ, AK. Acquisition and analysis of data, FB, AK, RAJ. Analysis and
interpretation of data, RB, SF, FB, AK, CV, TW, BK, HUK, RAJ. Drafting the
manuscript for important intellectual content, all authors. All coauthors
critically revised the article and gave final approval of this version to be
Ethics approval and consent to participate
The COSYCONET study was approved by the Ethics Committees of the local
study centers. The leading ethics committee was at the Philipps University
Marburg. All cohort participants gave their written informed consent. The
paper does not contain individual person’s data.
Consent for publication
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.
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