The Identification of Phenotypes in Patients With Severe Chronic Obstructive Pulmonary Disease (Groningen Severe COPD Cohort)
Conditions: Severe COPD
Sponsor: University Medical Center Groningen

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COVER PAGE 
 
COHORT PROFILE: The Groningen severe COPD Cohort – phenotyping and 
endotyping severe COPD 
NCT number: NCT04023409 
Date of document 11-6-2024 
 
 
 

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COHORT PROFILE: The Groningen severe COPD Cohort – phenotyping and 
endotyping severe COPD 
Short title: The Groningen severe COPD Cohort 
 
Jorine E. Hartman, PhD1,2, Pauline J.M. Kuks, MD1,2, Maarten van den Berge. MD PhD1,2, Nick 
H.T. ten Hacken, MD PhD1,2, Jorrit B.A. Welling, MD PhD1,2, Karin Klooster, PhD1,2, Marieke C. 
van der Molen, MD1,2, Simon D. Pouwels, PhD1,2,3, Dirk-Jan Slebos, MD PhD1,2 
 
1. Department of Pulmonary Diseases, University of Groningen, University Medical Center 
Groningen, Groningen, The Netherlands.  
2. Groningen Research Institute for Asthma and COPD, University of Groningen, University 
Medical Center Groningen, Groningen, The Netherlands. 
3. Department of Pathology and Medical Biology, University of Groningen, University Medical 
Center Groningen, Groningen, The Netherlands 
 
Corresponding author 
J.E. Hartman, PhD 
Department of Pulmonary diseases AA11 
University Medical Centre Groningen 
PO Box 30001, 9700 RB Groningen 
The Netherlands 
Tel : +31 503612357, E-mail: j.hartman@umcg.nl 
 
Word count manuscript: 1445 
Number of tables and figures: tables: 2, figures: 0. 
Keywords: COPD, emphysema, cohort, phenotyping 
 

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ABSTRACT 
 
The projection is that the prevalence and burden of chronic obstructive pulmonary disease 
(COPD) will increase in the coming decades. Consequently, the group of patients with severe, 
often end-stage, COPD will also increase. In the last decade, multiple new treatment 
modalities became available. However, due to the heterogeneity and complexity of end-stage 
COPD, these treatments can be best provided by identifying the phenotype or endotype of 
the patient and consequently selecting the right treatment for the right patient. Our hospital 
is an expertise center for severe COPD. We have been active in developing bronchoscopic lung 
volume reduction techniques and other experimental bronchoscopic treatments. This has led 
to a constant large flow of nationwide referrals of patients with severe COPD, which gave us 
the unique opportunity to set up “the Groningen Severe COPD Cohort (GSCC)”. The main aim 
of the GSCC cohort is to identify clinical phenotypes and endotypes in patients with severe 
COPD and to investigate the contribution of (epi)genomics. In total, the cohort included 1030 
patients of whom 121 also underwent a bronchoscopy with collection of lung biopsies, lung 
brushes and nosh brush samples. In the future, the findings of this cohort may lead to earlier 
identification of subjects at risk for severe COPD, better clinical characterisation of established 
COPD, and a more tailored treatment of this subgroup. This manuscript describes the 
Groningen Severe COPD cohort, providing an overview of the cohort design, the collected 
data, a description of the cohort characteristics, future plans and possibilities for 
collaboration. 
 

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INTRODUCTION 
Chronic obstructive pulmonary disease (COPD) is highly prevalent with an estimated global 
prevalence of 11.7% and was the third leading cause of death in 2019 according to the World 
Health Organization (WHO) [1,2]. The projection is that the prevalence and burden of COPD 
will increase even further in the coming decades due to aging of the world’s population and 
continued exposure to COPD risk factors [3].  
Consequently, the group of patients with severe, often end-stage, COPD will increase. In the 
last decade, multiple new treatment modalities became available for these patients [4]. 
However, due to the heterogeneity and complexity of end-stage COPD, these treatments can 
be best provided by identifying the phenotype or endotype of the patient and consequently 
selecting the right treatment for the right patient [4]. As the phenotype or endotype is 
important for treatment selection and success, more insight and identification of the different 
subgroups of patients with severe COPD would be useful. Even more, because there still is a 
large group of severe COPD patients who could benefit from new therapies aimed at reducing 
symptoms despite the increase in treatment modalities. 
The classical clinical phenotypes of COPD are small airway disease, emphysema and chronic 
bronchitis but this distinction seems not sufficient to optimally characterize COPD patients to 
target their treatment. Furthermore, there is significant overlap between these phenotypes 
and there is a lot of heterogeneity even between patients within one of these phenotypes [5]. 
A proposed definition of a phenotype is ‘a single or combination of disease attributes that 
describe differences between individuals with COPD as they relate to clinically meaningful 
outcomes (symptoms, exacerbations, response to therapy, rate of disease progression or 
death)’ [6]. The observable structural and functional characteristics that constitute a 
phenotype are determined by the combined influence of environmental and genetic factors. 

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Subgroups of patients can also be defined based on an endotype. The advantage of 
endotyping is that it defines subtypes of a given disease based on distinct functional or 
pathobiological mechanisms. Next to improved selection of specific subgroups, e.g. who 
benefit the most from a given therapy, endotyping also leads to novel insights on the biological 
mechanisms driving these subgroups thus providing new targets for improved personalized 
treatment [7]. Gaining more insight in new phenotypes and endotypes based on e.g. lung 
function, clinical, radiologic, systemic, pathological, immunological and even genetic 
parameters in patients with severe COPD could lead to a more personalized approach in the 
management of severe COPD, and contribute to the understanding of the multifactorial 
pathophysiology of COPD. 
The University Medical Center Groningen in the Netherlands is an expertise center for severe 
COPD. Next to other treatment options such as lung transplantation, non-invasive ventilation 
and pulmonary rehabilitation, we have been active in developing bronchoscopic lung volume 
reduction (BLVR) techniques and other experimental bronchoscopic treatments. This has led 
to a constant large flow of nationwide referrals of patients with severe COPD [8], which gave 
us the unique opportunity to set up “the Groningen Severe COPD Cohort- GSCC”. 
The main aim of the GSCC cohort is to identify clinical phenotypes and endotypes in patients 
with severe COPD and to investigate the contribution of (epi)genomics to these pheno- and 
endotypes. In the future, the findings of this cohort may lead to earlier identification of 
subjects at risk for severe COPD, better clinical characterisation of established COPD, and a 
more tailored treatment of this subgroup. 
This manuscript describes the Groningen Severe COPD cohort, providing an overview of the 
cohort design, the collected data, a description of the cohort characteristics, future plans and 
possibilities for collaboration. 

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COHORT DESCRIPTION 
This cohort had an observational cross-sectional study design with 2 phases. The aim was to 
include 1000 patients with severe COPD who were referred to our hospital for bronchoscopic 
lung volume reduction (BLVR) treatment evaluation. During the physical consultation in our 
hospital an extensive panel of study measurements were performed (Phase A). A subgroup of 
patients who were eligible for a BLVR treatment and underwent a bronchoscopy were asked 
for phase B, in which, during the therapeutic bronchoscopy procedure nose brushes, bronchial 
brushes and bronchial biopsies were collected. Patients were included between 18-8-2014 
and 10-7-2019. 
 
DATA COLLECTION 
The included study measures and outcomes are shown in table 1. 
Samples: Blood samples have been collected from 924 subjects of the Groningen Severe COPD 
cohort. From all these subjects serum, plasma and peripheral blood DNA has been isolated 
and stored at -80 °C until further use. Serum and plasma can be used to assess a wide range 
of inflammatory markers, cytokines and other biomarkers, while peripheral blood DNA can be 
used for whole-genome sequencing.  
From a subset of 121 subjects additional samples have been collected, including bronchial 
brushes, nose brushes and lung tissue biopsies (Phase B). RNA has been isolated from 
bronchial and nose brushes and whole genome sequencing has been performed to analyse 
gene expression levels. 
 
FOLLOW-UP 

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This is an observational cross-sectional cohort. We did verify the vital status of the patients 
with the Dutch government personal record database at 3-4-2021 and whether patients 
underwent a bronchoscopic treatment or not. This verification could be repeated in the 
future. 
 
PARTICIPANT CHARACTERISTICS 
In total 1030 patients were included of whom 677 were female (66%). Patient characteristics 
are shown in table 2. In 121 patients who also underwent a bronchoscopy, lung biopsies, lung 
brush and nose brush samples were collected. At the verification date of vital status on 3-4-
2021, 274 of the patients (27%) had died with a median of 857 days (range 2-2245) after their 
physical consultation in our hospital. 
 
ETHICS 
This cohort was approved by the ethics committee of the UMCG, Groningen, The Netherlands 
and all patients provided written informed consent (ECnumber:2014/102). Furthermore, the 
trial is registered at clinicaltrials.gov: NCT04023409. 
 
FINDINGS TO DATE 
So far, one paper was published including data from this cohort. In this paper, we combined 
this cohort with a previous dataset of patients who visited us for a consultation visit. We 
investigated the survival rate in patients who were evaluated for BLVR treatment and whether 
the survival rate differed between patients who underwent BLVR treatment and patients who 
did not [9]. In total 1471 patients were included of whom the median survival was 
approximately 7.4 years. The median survival time of patients who were treated with BLVR 

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was significantly longer than in patients who were not and furthermore undergoing BLVR was 
found to be an independent predictor of survival. Our results suggest that bronchoscopically 
reducing lung volume in patients with severe hyperinflation may lead to a survival benefit in 
a population with a severely reduced life expectancy. 
 
STRENGHTS AND LIMITATIONS 
A strength of this cohort is the large sample size of severe COPD patients and the fact that all 
measurements were performed in one hospital with the same equipment and protocols. A 
limitation of this cohort is that it only includes patients who were referred for a bronchoscopic 
lung volume reduction treatment and therefore is a specific subset of patients which might 
not be representative of the complete severe COPD population. On the other hand it is a 
rather homogeneous group of patients. Another limitation of the cohort is that it is cross-
sectional and does not include follow up.  
 
COLLABORATION / ONGOING ACTIVITIES AND FUTURE PLANS 
Currently, multiple analyses are being performed to investigate specific subgroups in an effort 
to identify potential new phenotypes of severe COPD. One example is a comparison between 
patients with severe early onset COPD versus ‘normal’ onset COPD. And another analysis aims 
to identify the frequency of genetic variants in genes known to cause COPD in this patient 
group with severe COPD.  
Currently, the SHERLOCK/P4O2 project [NCT04263961] is being executed in our hospital. In 
this study also severe COPD patients are included who undergo a bronchoscopy in which 
samples are collected. In addition, both ex- and current smokers with mild-to-moderate COPD 
and those without airflow obstruction are included. The combination of both cohorts in the 

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future enables us to identify which phenotypes and endotypes are present in COPD in general 
and which are specific to those who develop severe end-stage disease with extensive 
emphysema. To this end, amongst others RNA-sequencing and proteomics analyses will be 
performed in bronchial biopsies. In addition, extensive clinical characterization and sample 
collection (blood, urine, stool, sputum, bronchial and nasal brushes and bronchial wash) will 
be performed for future analyses yet to be defined. Next to the 121 severe COPD of whom 
already airway samples were collected in the GSCC cohort, this cohort aims to include before 
the end of 2024 a total of 433 patients: 100 patients with severe COPD and 333 participants 
with either mild-to-moderate COPD or without airflow obstruction.  
We are open to collaborations and proposals for new research questions by contacting the 
corresponding author. 
 
Contributorship statement 
JEH and DJS: substantial contributions to the conception and design of the cohort, the 
acquisition, analysis and interpretation of data for the work; AND drafting the manuscript AND 
final approval of the version to be published; AND agreement to be accountable for all aspects 
of the work in ensuring that questions related to the accuracy or integrity of any part of the 
work are appropriately investigated and resolved 
NHTtH and MvdB: substantial contributions to the conception and design of the cohort, the 
acquisition, and interpretation of data for the work; AND revising the manuscript critically for 
important intellectual content; AND final approval of the version to be published; AND 
agreement to be accountable for all aspects of the work in ensuring that questions related to 
the accuracy or integrity of any part of the work are appropriately investigated and resolved. 

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PJMK, JBAW, KK, MCvdM and SDP: substantial contributions to data acquisition AND revising 
the manuscript critically for important intellectual content; AND Final approval of the version 
to be published; AND Agreement to be accountable for all aspects of the work in ensuring that 
questions related to the accuracy or integrity of any part of the work are appropriately 
investigated and resolved. 
 
Funding declaration 
The authors received no specific funding for this work. 
 
Competing interest statement 
The authors have declared that no competing interests exist. 
 
Data sharing statement 
The data obtained from the cohort described in this manuscript can be shared for 
collaborations or proposals. Data are available on reasonable request. 
We have provided the following statement in the manuscript: "We are open to collaborations 
and proposals for new research questions by contacting the corresponding author.”  

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REFERENCES 
[1]  
Adeloye D, Chua S, Lee C, et al. Global and regional estimates of COPD prevalence: Systematic 
review and meta-analysis. J Glob Health. 2015;5(2): 020415.  
[2]  
WHO. Global Health estimates: Life expectancy and leading causes of death and disability 
[Internet]. 2019. Available from: https://www.who.int/data/gho/data/themes/mortality-and-
global-health-estimates 
[3]  
GOLD. Global strategy for the diagnosis, management, and prevention of Chronic Obstructive 
pulmonary disease: 2022 report [Internet]. 2022. Available from: https://goldcopd.org/2022-
gold-reports-2 
[4]  
van Dijk M, Gan CT, Koster TD, et al. Treatment of severe stable COPD: the multidimensional 
approach of treatable traits. ERJ Open Res. 2020;21(6):00322–2019.  
[5]  
Friedlander A, Lynch D, Dyar L, et al. Phenotypes of chronic obstructive pulmonary disease. 
COPD J Chronic Obstr Pulm Dis. 2007;4(4):355–84.  
[6]  
Han MLK, Agusti A, Calverley PM, et al. Chronic obstructive pulmonary disease phenotypes: 
The future of COPD. Am J Respir Crit Care Med. 2010 Sep 1;182(5):598-604.  
[7]  
Lötvall J, Akdis CA, Bacharier LB, et al. Asthma endotypes: A new approach to classification of 
disease entities within the asthma syndrome. J Allergy Clin Immunol. 2011;127(2): :355-60.  
[8]  
Welling JBA, Hartman JE, Augustijn SWS, et al. Patient selection for bronchoscopic lung 
volume reduction. Int J COPD. 2020;15:871–81.  
[9]  
Hartman J, Welling J, Klooster K, et al. Survival in COPD patients treated with bronchoscopic 
lung volume reduction. Respir Med. 2022;ePub.  
 
 

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TABLES 
Table 1: Overview of study measures 
Variable 
Measures 
Demographics 
Gender, age, birthweight, gestational age, smoking 
status, packyears. Physical therapy status, pulmonary 
rehabilitation status, use of pulmonary medications 
and long term oxygen therapy (LTOT) 
Exacerbation status 
Number in past year, hospital admissions in past year 
Body composition 
BMI, hip-waist ratio, bio-impedance 
Pulmonary function measures 
Spirometry 
Body plethysmography 
Diffusion capacity 
 
Annual lung function decline before visit (spirometry) 
Lab regular 
Arterial blood gas, complete blood count, basic 
chemistry, fibrinogen, alpha-1-anitrypsine  
Additional blood samples 
Serum, plasma, peripheral blood DNA 
CT-scan 
Quantification LungQ software (Thirona, Nijmegen, The 
Netherlands): Per lung and lobes: volumes and 
emphysema scores. Air trapping score, fissure integrity 
and Pi10. 
Questionnaires 
mMRC:             Dyspnea 
 
CAT:                  Quality of life 
 
SGRQ:               Quality of life 
 
CCQ:                  COPD control  
 
EQ5D:               Quality of life 
 
BHQ:                 Bronchial hyperresponsiveness 
 
SQUASH:          Physical activity 
 
Comorbidities: Self-reported 
 
Family history of pulmonary diseases: Self-reported 
Subset (patients who underwent a bronchoscopy) 
Nose brushes 
RNA from nose brushes 
Bronchial brushes 
RNA from bronchial brushes 
Bronchial biopsies 
Paraffin-embedded 
Follow-up 
Vital status  
Verified with Dutch government personal records 
database on 3-4-2021 
BLVR treatment status 
Treated with a bronchoscopic lung volume reduction 
treatment 
 
 

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Table 2: Patient characteristics 
Gender, female (%) 
 
677 (65.7%) 
Age, years 
 
61 ± 7.5 
mMRC, score 
 
3 (0-4) 
Current smokers, number (%) 
 
20 (2%) 
Packyears, years 
 
40 ± 19 
Use of 
Maintenance Antibiotics 
212 (21%) 
 
Maintenance Prednisolon 
169 (16%) 
 
Any ICS 
896 (87%) 
 
LTOT in rest 
183 (18%) 
 
LTOT during exercise 
266 (26%) 
FEV1, liter 
 
0.82 ± 0.32 
FEV1, % of predicted 
 
30.9 ± 10.6 
Annual FEV1, decline before participation, liter /year 
 
-0.07 ± 0.05 
FVC, liter 
 
2.99 ± 10.2 
RV, liter 
 
4.62 ± 1.11 
RV, % of predicted 
 
219 ± 47 
TLC, liter 
 
7.62 ± 1.49 
DLCO, mmol/min*kPa 
 
2.59 ± 1.00 
RV/TLC, ratio 
 
0.61 ± 0.09 
PaCO2, kPa 
 
5.33 ± 0.73 
PaO2, kPa 
 
9.02 ± 1.24 
Exacerbation in past year, number 
 
2 (0-15) 
Hospitalizations for exacerbation in past year, number 
 
0 (0-11) 
EBV treatment, yes (%) 
 
220 (21%) 
Coil treatment, yes (%) 
 
46 (5%) 
CAT, total score 
 
22.4 ± 6.3 
SGRQ, total score 
 
58.8 ± 13.4 
CCQ, total score 
 
3.17 ± 0.98 
EQ-5D, VAS 0-100 
 
49 ± 17 
BHQ, mean score 
 
2.63 ± 0.99 
Emphysema score, %voxels <-950 HU 
 
36.7 ± 8.5 
Total lung capacity inspiratory on CT, liter 
 
6.97 ± 1.44 
Pi10, mm 
 
2.65 ± 0.31 
 
Data are presented as n(%), mean ± standard deviation or median (range).  
mMRC: modified Medical Research Council scale, ICS: inhaled corticosteroids, LTOT: long term oxygen 
therapy, FEV1: forced expiratory volume in 1 second, FVC: forced vital capacity, RV: residual volume, 
TLC: total lung capacity, DLCO: diffusing capacity for carbon monoxide, PaCO2: Partial pressure of 
carbon dioxide, PaO2: Partial pressure of oxygen, EBV: endobronchial valve, CAT: COPD assessment 
test, SGRQ: St. George’s Respiratory Questionnaire, CCQ: COPD control questionnaire, EQ-5D: 
EuroQol-5 dimensions, VAS: visual analogue scale (0-100), BHQ: bronchial hyperresponsiveness 
questionnaire, Pi10:the square root of wall area at airways with a perimeter of 10mm, CT: computed 
tomography, HU: Hounsfield units, mm: millimetre.