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Biomarker-based clustering of patients with chronic obstructive pulmonary disease

Lowie E.G.W. Vanfleteren, Julie Weidner, Frits M.E. Franssen, Swetlana Gaffron, Niki L. Reynaert, Emiel F.M. Wouters, Martijn A. Spruit
ERJ Open Research 2023 9: 00301-2022; DOI: 10.1183/23120541.00301-2022
Lowie E.G.W. Vanfleteren
1COPD Center, Department of Respiratory Medicine and Allergology, Sahlgrenska University Hospital, Gothenburg, Sweden
2Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
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  • For correspondence: Lowie.vanfleteren@gu.se
Julie Weidner
3Krefting Research Centre, Department of Internal Medicine and Clinical Nutrition, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
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Frits M.E. Franssen
4Department of Research and Development, CIRO+, Horn, The Netherlands
5Department of Respiratory Medicine, Maastricht University Medical Center (MUMC+), Maastricht, The Netherlands
6NUTRIM School of Nutrition and Translational Research in Metabolism, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
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Swetlana Gaffron
7Viscovery Software GmbH, Vienna, Austria
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Niki L. Reynaert
5Department of Respiratory Medicine, Maastricht University Medical Center (MUMC+), Maastricht, The Netherlands
6NUTRIM School of Nutrition and Translational Research in Metabolism, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
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Emiel F.M. Wouters
4Department of Research and Development, CIRO+, Horn, The Netherlands
5Department of Respiratory Medicine, Maastricht University Medical Center (MUMC+), Maastricht, The Netherlands
6NUTRIM School of Nutrition and Translational Research in Metabolism, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
8Ludwig Boltzmann Institute for Lung Health, Vienna, Austria
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Martijn A. Spruit
4Department of Research and Development, CIRO+, Horn, The Netherlands
5Department of Respiratory Medicine, Maastricht University Medical Center (MUMC+), Maastricht, The Netherlands
6NUTRIM School of Nutrition and Translational Research in Metabolism, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
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  • FIGURE 1
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    FIGURE 1

    Network interactions of predicted upregulated or downregulated proteins by cluster. Proteins that were similarly and significantly upregulated (clusters 3 and 4) or downregulated (clusters 1 and 2) were entered into String [35], all possible interaction sources were allowed and subjected to a minimum required high-confidence interaction score (0.7). Disconnected nodes are not shown. All clusters had a p-value of ≥3.53×10−11. The mode of interaction is depicted as an arrow (positive interaction), inhibition (negative interaction) or ball (unspecified interaction). Gene names, with corresponding biomarker names in parenthesis, used in this figure: ADIPOQ (adiponectin), BDNF (brain-derived neurotrophic factor), B2M (β2-microglobulin), C3 (complement C3), CCL2 (monocyte chemotactic protein-1), CCL5 (RANTES), CRP (C-reactive protein), CXCL10 (interferon (IFN)-γ-induced protein-10), CXCL11 (IFN-γ-inducible T-cell α chemoattractant), EPO (erythropoietin), HP (haptoglobin), ICAM1 (intercellular adhesion molecule-1), IFNG (IFN-γ), IL1RN (interleukin (IL)-1ra), IL2RA (IL-2 receptor-α), IL6 (IL-6), IL12RB1 (IL12p40), BGLAP (osteocalcin), KITLG (stem cell factor), LEP (leptin), MMP3 (matrix metalloproteinase-3), SAA1 (serum amyloid A), SERPINA1 (α1-antitrypsin), SERPINE1 (plasminogen activator inhibitor-1), SPARC (osteonectin), TGFB1 (latency-associated peptide of transforming growth factor-β1), TIMP1 (tissue inhibitor of metalloproteinases-1), TNFRSF11B (osteoprotegerin), TNFRSF1A (tumour necrosis factor receptor (TNFR)I), TNFRSF1B (TNFR2), VEGFA (vascular endothelial growth factor), VCAM1 (vascular cell adhesion molecule-1).

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  • TABLE 1

    Systemic levels of biomarkers of inflammation, chemoattraction, cell activation, tissue destruction and tissue repair per cluster

    Cluster 1:Cluster 2:Cluster 3:Cluster 4:
    lower-level cluster Ilower-level cluster IIhigher-level cluster Ihigher-level cluster II
    Patients, n64644639
    Acute phase proteins and complement system
     Complement C3, mg·mL−11.2±0.21.1±0.21.3±0.21.5±1.0
     CRP, ng·mL−13011±27951773±18598214±81539725±8480
     Fibrinogen, μg·mL−16417±28266870±45336465±23748879±7911
     Serum amyloid A, ng·mL−13059±27051889±14036239±731110 745±7810
    Cytokines and chemokines and their receptors
     Eotaxin-2, pg·mL−11022±6321398±9401371±9541337±965
     IL-1β, pg·mL−14.8±1.24.3±1.34.2±1.15.0±1.6
     IL-12 subunit p40, ng·mL−10.6±0.20.5±0.10.5±0.10.6±0.1
     IL-23, ng·mL−11.4±0.41.2±0.31.2±0.31.4±0.3
     IL-6, pg·mL−12.9±1.61.9±1.73.4±1.76.3±8.2
     IL-8, pg·mL−112±513±514±614±5
     IFN-γ-inducible T-cell α-chemoattractant, pg·mL−143±2244±2455±2564±47
     IFN-γ-inducible protein-10, pg·mL−193±4173±3990±30142±98
     IFN-γ, pg·mL−10.5±0.30.4±0.40.5±0.21.3±2.6
     Macrophage migration inhibitory factor, ng·mL−10.1±0.10.1±0.10.1±0.10.1±0.1
     MCP-1, pg·mL−1511±190469±130606±159513±200
     MCP-4, pg·mL−1688±235678±207762±210778±455
     T-cell-specific protein RANTES, ng·mL−119±823±1031±1025±14
     Thymus and activation-regulated chemokine, pg·mL−1524±414636±384784±620770±828
     IL-2 receptor-α, pg·mL−12427±6942020±5352695±9273429±1240
     TNF-R2, ng·mL−16.0±1.64.9±1.26.0±1.89.8±5.0
     TNF-R1, pg·mL−11850±4761531±4361905±5882603±919
     Osteoprotegerin, pM7.0±1.96.7±1.17.2±1.38.9±2.0
    Inhibitors of cytokine signalling
     IL-1 receptor antagonist, pg·mL−1423±132336±74372±99388±118
    Adhesion molecules
     sICAM-1, ng·mL−1282±76292±76321±102389±113
     sVCAM-1, ng·mL−1520±116493±106517±142719±396
    Immunoglobulins
     IgA, mg·mL−12.9±1.62.4±1.23.1±1.43.6±2.9
     IgM, mg·mL−12.1±1.41.8±1.91.7±1.12.5±4.2
    Growth factors
     Angiopoietin-2, ng·mL−13.7±1.83.8±1.34.4±1.45.1±1.3
     BDNF, ng·mL−118.1±4.922±523±718±7
     Stem cell factor, pg·mL−1397±93330±83354±88473±163
     Vascular endothelial growth factor, pg·mL−1242±111258±122354±159290±170
    Tissue remodelling
     α1-Antitrypsim, mg·mL−11.9±0.32.0±0.41.9±0.42.3±0.6
     LAP TGF-β1, ng·mL−19.4±2.812±313±310±3
     MMP-3, ng·mL−119±1413±714±723±16
     MMP-9, ng·mL−1147±72130±62153±69159±83
     Tissue inhibitor of metalloproteinases-1, ng·mL−1150±23163±27195±30199±65
    Hormones and adipokines
     Adiponectin, μg·mL−14.4±2.17.0±3.35.1±2.77.4±4.7
     Leptin, ng·mL−114.8±12.38.2±8.816.8±14.613.7±14.8
     Erythropoietin, IU·mL−111.3±5.28.4±2.611±713±4
     Osteocalcin (OCN/BGLAP), ng·mL−1117±20127±18116±17135±25
    Coagulation
     α2-Macroglobulin (A2Macro), mg·mL−11.7±0.41.7±0.41.7±0.61.9±0.7
     Factor VII, ng·mL−1447±140406±99403±127422±119
     PAI-1, ng·mL−1195±45228±53290±56220±112
    Plasma carrier proteins
     Fetuin A, μg·mL−1574±292706±364603±303652±420
     Haptoglobin, mg·mL−11.7±0.91.6±1.12.9±1.43.5±3.1
     IGFBP-1, ng·mL−12978±24324368±27713204±21784504±2870
     IGFBP-2, ng·mL−179±34110±5380±35132±45
     Vitamin D-binding protein, μg·mL−1288±108300±91291±122396±727
    Other
     Ferritin, ng·mL−1180±142151±128190±160183±203
     β2-Microglobulin, μg·mL−12.1±0.51.8±0.32.1±0.42.9±1.0
     Myoglobin, ng·mL−169±3774±11154±2896±62
     Osteonectin, ng·mL−11145±3441394±2301720±3221318±394
     Osteopontin, ng·mL−122±722±822±736±14
     Bilirubin, mmol·L−111.6±4.914±610±512±3
     Leukocytes, ×109 cells·L−16.7±1.46.9±1.98.1±1.48.5±2.4
     LDL, mmol·L−12.7±0.93.1±0.93.2±1.22.9±1.0
     HDL, mmol·L−11.7±0.41.7±0.51.7±0.51.5±0.5

    Data are presented as mean±sd. Eight biomarkers were measured, but excluded from the statistical analysis, because of >30% missing values (B-lymphocyte chemoattractant, eotaxin-1, eotaxin-3, interleukin (IL)-1α, IL-12 subunit p70, IL-15, IL-17 and major histocompatibility complex (MHC) class I chain-related protein-A). ▪ A significantly higher level compared to the remaining three clusters (p-value <0.01); ▪ a tendency for a significantly higher level compared to the remaining three clusters (p-value between 0.05 and 0.01); ▪ a significantly lower level compared to the remaining three clusters (p<0.01); ▪ a tendency for a significantly lower level compared to the remaining three clusters (p-value between 0.05 and 0.01). CRP: C-reactive protein; IFN: interferon; MCP: monocyte chemotactic protein; TNF-R: tumour necrosis factor receptor; BDNF: brain-derived neurotrophic factor; sICAM: soluble intercellular adhesion molecule; sVCAM: soluble vascular adhesion molecule; LAP TGF-β1: latency-associated peptide of transforming growth factor-β1; MMP: matrix metalloproteinase; PAI: plasminogen activator inhibitor; IGFBP: insulin-like growth factor-binding protein; LDL: low-density lipoprotein; HDL: high-density lipoprotein.

    • TABLE 2

      General characteristics of study subjects

      Subjects, n213
      Age, years63.6±7.0
      Male59
      BMI, kg·m−226.2±5.1
      FFMI, kg·m−217.0±2.4
      mMRC dyspnoea grade2.1±1.1
      Current smoker28
      Smoking pack-years46±26
      Long-term oxygen therapy17
      FEV1, L1.40±0.54
      FEV1, % predicted51.2±16.9
      FEV1/FVC0.40±0.11
      ITGV, % predicted148±33
      DLCO, % predicted56±17
      6MWD, m470±106
      SGRQ, total score51.3±17.5
      Updated BODE score2.9±2.5
      Framingham 10-year risk, %9.4±6.7

      Data are presented as mean±sd or %, unless otherwise stated. BMI: body mass index; FFMI: fat-free mass index; mMRC: modified Medical Research Council; FEV1: forced expiratory volume in 1 s; FVC: forced vital capacity; ITGV: intrathoracic gas volume; DLCO: diffusion capacity of the lung for carbon monoxide; 6MWD: 6-min walk distance; SGRQ: St George's Respiratory Questionnaire; BODE: body mass index, obstruction, dyspnoea, exercise capacity index.

      • TABLE 3

        The clinical characteristics of each cluster

        Cluster 1:
        lower-level cluster I
        Cluster 2:
        lower-level cluster II
        Cluster 3:
        higher-level cluster I
        Cluster 4:
        higher-level cluster II
        Female34474833
        Age, years65±761±662±669±6
        Lung function
         FEV1, L1.5±0.51.4±0.51.4±0.51.3±0.6
         FEV1, % predicted54±1651±1950±1548±16
         FEV1/FVC, %41±1240±1140±1138±9
         DLCO, % predicted60±1754±1658±1748±14
         ITGV, % predicted139±32156±35147±34152±29
         RV, % predicted153±45175±54162±44165±39
         TLC, % predicted116±17123±16119±17116±16
         PaCO2, kPa5.3±0.65.2±0.55.5±0.75.4±0.6
         PaO2, kPa9.6±1.19.6±1.29.3±0.99.2±0.9
         SaO2, %95.1±1.995.2±1.794.7±2.094.4±1.8
         PImax, % predicted85±2477±2578±2275±18
         PEmax, % predicted64±2062±2260±1756±17
        COPD-specific characteristics
         mMRC dyspnoea grade2.0±1.12.0±1.12.1±0.92.4±1.3
         Long-term oxygen therapy11141731
         Smoking pack-years44±2147±2848±3047±23
         Current smoker14313736
         Hospital admissions for COPD in past 12 months, n0.51±1.170.42±1.170.49±0.840.69±1.28
         Steroid/antibiotic courses for COPD in past 12 months, n1.53±1.951.42±1.611.01±1.321.92±1.92
         Exacerbations in past 12 months, n2.05±2.601.85±2.411.54±1.812.55±2.18
         GOLD group A/B/C/D19/30/20/3018/26/15/4011/40/7/4015/18/15/51
        Physical fitness
         6MWD, m493±91497±101461±91402±126
         Peak work rate, W86±3076±2375±2758±26
         Peak work rate, % predicted63±2562±2561±2947±22
         Constant work-rate test, s409±264408±329296±191234±187
        Health status
         SGRQ symptoms domain54±1953±2157±1857±25
         SGRQ activity domain65±2268±2273±1769±27
         SGRQ impact domain35±1938±1847±1643±26
         SGRQ total score48±1950±1757±1253±23
        Prognostic indices
         Updated BODE index2.2±1.82.7±2.32.6±2.04.6±3.7
         Framingham risk score9.7±6.17.5±5.99.3±7.212.3±7.2

        Data are presented as mean±sd or %, unless otherwise stated. ▪ A significantly higher level compared to the remaining three clusters (p<0.01); ▪ a tendency for a significantly higher level compared to the remaining three clusters (p-value between 0.05 and 0.01); ▪ a significantly lower level compared to the remaining three clusters (p<0.01); ▪ a tendency for a significantly lower level compared to the remaining three clusters (p-value between 0.05 and 0.01). FEV1: forced expiratory volume in 1 s; FVC: forced vital capacity; DLCO: diffusion capacity of the lung for carbon monoxide; ITGV: intrathoracic gas volume; RV: residual volume; TLC: total lung capacity; PaCO2: arterial carbon dioxide partial pressure; PaO2: arterial oxygen partial pressure; SaO2: arterial haemoglobin oxygen saturation; PImax: maximal inspiratory mouth pressure; PEmax: maximal expiratory mouth pressure; mMRC: modified Medical Research Council; GOLD: Global Initiative for Chronic Obstructive Lung Disease; 6MWD: 6-min walk distance; SGRQ: St George's Respiratory Questionnaire; BODE: body mass index, obstruction, dyspnoea, exercise capacity index.

        • TABLE 4

          Comorbidities per biomarker-based cluster

          Cluster 1: lower-level cluster ICluster 2: lower-level cluster IICluster 3: higher-level cluster ICluster 4: higher-level cluster II
          Comorbidities, n3.5±1.53.4±1.53.7±1.74.3±1.8
          Charlson Comorbidity Index1.6±0.71.5±0.91.6±0.81.8±1.1
          eGFR, mL·min−178±2183±2387±2566±20
          Creatinine, μmol·L−193±2078±1584±1499±32
          Renal impairment23141541
          Haemoglobin, mmol·L−19.0±0.69.1±0.79.1±0.98.7±0.7
          Haematocrit44±444±444±542±4
          Anaemia221110
          Systolic blood pressure, mmHg140±17136±25138±15145±28
          Diastolic blood pressure, mmHg83±882±1183±983±12
          Hypertension45444862
          BMI, kg·m−227.4±4.824.2±4.928.1±5.425.2±4.2
          Obese28163318
          Underweight925415
          FFMI, kg·m−217.6±2.016.1±2.517.5±2.816.9±2.0
          Muscle wasting14502026
          Glucose, mmol·L−15.8±1.05.7±0.85.9±1.05.6±0.9
          Hyperglycaemia56556144
          Triglycerides, mmol·L−11.6±0.71.3±0.52.0±1.31.4±0.7
          Cholesterol, mmol·L−15.0±1.05.4±1.05.8±1.55.1±1.1
          Cholesterol/HDL ratio3.2±1.03.3±0.93.8±1.33.6±1.1
          Dyslipidaemia41225233
          Thrombocytes, ×109 cells·L−1235±57253±65334±138260±72
          HADS Anxiety5.5±3.6.7±4.37.0±3.86.0±3.7
          Anxiety16232522
          HADS Depression5.1±3.55.5±3.96.7±3.35.7±3.2
          Depression16152014
          c-IMT, mm1.0±0.20.9±0.21.0±0.21.0±0.2
          Atherosclerosis61355762
          Cardiac Infarction Injury Score10.4±7.211.2±5.411.3±5.713.3±7.0
          T-score total body−0.6±1.1−1.4±1.3−0.8±1.2−1.4±1.5
          Osteoporosis22412241

          Data are presented as mean±sd or %, unless otherwise stated. ▪ A significantly higher level compared to the remaining three clusters (p<0.01); ▪ a tendency for a significantly higher level compared to the remaining three clusters (p-value between 0.05 and 0.01); ▪ a significantly lower level compared to the remaining three clusters (p<0.01); ▪ a tendency for a significantly lower level compared to the remaining three clusters (p-value between 0.05 and 0.01). eGFR: estimated glomerular filtration rate; BMI: body mass index; FFMI: fat-free mass index; HDL: high-density lipoprotein; HADS: Hospital Anxiety and Depression Score; c-IMT: carotid intima-media thickness.

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          Biomarker-based clustering of patients with chronic obstructive pulmonary disease
          Lowie E.G.W. Vanfleteren, Julie Weidner, Frits M.E. Franssen, Swetlana Gaffron, Niki L. Reynaert, Emiel F.M. Wouters, Martijn A. Spruit
          ERJ Open Research Jan 2023, 9 (1) 00301-2022; DOI: 10.1183/23120541.00301-2022

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          Biomarker-based clustering of patients with chronic obstructive pulmonary disease
          Lowie E.G.W. Vanfleteren, Julie Weidner, Frits M.E. Franssen, Swetlana Gaffron, Niki L. Reynaert, Emiel F.M. Wouters, Martijn A. Spruit
          ERJ Open Research Jan 2023, 9 (1) 00301-2022; DOI: 10.1183/23120541.00301-2022
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