Skip to main content

Main menu

  • Home
  • Current issue
  • Early View
  • Archive
  • Authors/reviewers
    • Instructions for authors
    • Submit a manuscript
    • Institutional open access agreements
    • Peer reviewer login
  • Alerts
  • Subscriptions
  • ERS Publications
    • European Respiratory Journal
    • ERJ Open Research
    • European Respiratory Review
    • Breathe
    • ERS Books
    • ERS publications home

User menu

  • Log in
  • Subscribe
  • Contact Us
  • My Cart

Search

  • Advanced search
  • ERS Publications
    • European Respiratory Journal
    • ERJ Open Research
    • European Respiratory Review
    • Breathe
    • ERS Books
    • ERS publications home

Login

European Respiratory Society

Advanced Search

  • Home
  • Current issue
  • Early View
  • Archive
  • Authors/reviewers
    • Instructions for authors
    • Submit a manuscript
    • Institutional open access agreements
    • Peer reviewer login
  • Alerts
  • Subscriptions

Cardiovascular disease-linked plasma proteins are mainly associated with lung volume

Andreas Rydell, Elisabet Nerpin, XingWu Zhou, Lars Lind, Eva Lindberg, Jenny Theorell Haglöw, Tove Fall, Christer Janson, Karin Lisspers, Sölve Elmståhl, Suneela Zaigham, Olle Melander, Peter M. Nilsson, Johan Ärnlöv, Andrei Malinovschi
ERJ Open Research 2023 9: 00321-2022; DOI: 10.1183/23120541.00321-2022
Andreas Rydell
1Division of Family Medicine and Primary Care, Department of Neurobiology, Care Sciences and Society (NVS), Karolinska Institute, Huddinge, Sweden
2Region Dalarna, Falun, Sweden
8These authors contributed equally
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Elisabet Nerpin
3Department of Medical Sciences, Uppsala University, Uppsala, Sweden
4School of Health and Welfare, Dalarna University, Falun, Sweden
8These authors contributed equally
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Elisabet Nerpin
  • For correspondence: ene@du.se
XingWu Zhou
3Department of Medical Sciences, Uppsala University, Uppsala, Sweden
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Lars Lind
3Department of Medical Sciences, Uppsala University, Uppsala, Sweden
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Eva Lindberg
3Department of Medical Sciences, Uppsala University, Uppsala, Sweden
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jenny Theorell Haglöw
3Department of Medical Sciences, Uppsala University, Uppsala, Sweden
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Jenny Theorell Haglöw
Tove Fall
3Department of Medical Sciences, Uppsala University, Uppsala, Sweden
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Christer Janson
3Department of Medical Sciences, Uppsala University, Uppsala, Sweden
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Karin Lisspers
5Department of Public Health and Caring Sciences, Family Medicine and Preventive Medicine, Uppsala University, Uppsala, Sweden
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Sölve Elmståhl
6Department of Clinical Sciences, Lund University, Malmö, Sweden
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Suneela Zaigham
3Department of Medical Sciences, Uppsala University, Uppsala, Sweden
6Department of Clinical Sciences, Lund University, Malmö, Sweden
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Suneela Zaigham
Olle Melander
6Department of Clinical Sciences, Lund University, Malmö, Sweden
7Skåne University Hospital, Malmö, Sweden
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Peter M. Nilsson
6Department of Clinical Sciences, Lund University, Malmö, Sweden
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Johan Ärnlöv
1Division of Family Medicine and Primary Care, Department of Neurobiology, Care Sciences and Society (NVS), Karolinska Institute, Huddinge, Sweden
2Region Dalarna, Falun, Sweden
4School of Health and Welfare, Dalarna University, Falun, Sweden
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Andrei Malinovschi
3Department of Medical Sciences, Uppsala University, Uppsala, Sweden
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Andrei Malinovschi
  • Article
  • Figures & Data
  • Info & Metrics
  • PDF
Loading

Figures

  • Tables
  • Supplementary Materials
  • FIGURE 1
    • Download figure
    • Open in new tab
    • Download powerpoint
    FIGURE 1

    Flowchart of subjects included in the analyses. MOS: Malmö Offspring Study.

Tables

  • Figures
  • Supplementary Materials
  • TABLE 1

    Baseline characteristics for the EpiHealth and Malmö Offspring Study (MOS) cohorts

    EpiHealthMOS
    Subjects n2229645
    Age years60.7±8.440.2±13.4
    Sex (female)1122 (50.3)335 (51.9)
    Height cm172±9174±9
    Weight kg78.6±14.378.8±16.8
    BMI kg·m−226.5±3.826.1±4.6
    BMI category
     <18.5 (underweight)8 (0.4)6 (0.9)
     ≥18.5 to <25 (normal weight)772 (34.6)296 (45.9)
     ≥25 to <30 (overweight)1083 (48.6)227 (35.2)
     ≥30 (obesity)366 (16.4)116 (18)
    Central obesity cm (male ≥102, female ≥88)879 (39.4)206 (31.9)
    Physical activity
     Sedentary907 (40.7)281 (43.6)
     Moderate934 (41.9)163 (25.3)
     High388 (17.4)201 (31.1)
    Smoking history
     Never1108 (49.7)393 (60.9)
     Previous946 (42.4)173 (26.8)
     Current175 (7.9)79 (12.3)
    Pack-years#14.6±13.111.7±10.8
    Diabetes77 (3.5)21 (3.3)
    Hypertension602 (27.0)107 (16.6)
    Hyperlipidaemia486 (21.8)81 (12.6)
    Cardiovascular disease165 (7.4)80 (12.7)
    FEV1 L3.1±0.83.5±0.8
    FEV1 % pred GLI100±1694±12
    FVC L4.0±1.14.5±1.0
    FVC % pred GLI101±1698±12
    FEV1/FVC0.77±0.070.78±0.07
    FEV1/FVC % pred GLI99±995±8
    Normal spirometry2002 (89.8)506 (78.4)
    Obstructive spirometry124 (5.6)91 (14.1)
    Restrictive spirometry26 (1.2)5 (0.8)
    PRISm77 (3.5)43 (6.7)

    Data are presented as mean±sd for continuous variables and n (%) for dichotomous variables. BMI: body mass index; FEV1: forced expiratory volume in 1 s; GLI: Global Lung Function Initiative; FVC: forced vital capacity; LLN: lower limit of normal. Cardiovascular disease: a history of myocardial infarction, stroke, angina pectoris, heart failure or atrial fibrillation. Normal spirometry: FEV1/FVC ≥ LLN and FEV1 ≥ LLN and FVC ≥ LLN. Obstructive spirometry: FEV1/FVC < LLN. Restrictive spirometry: FEV1/FVC ≥ LLN and FVC < LLN and FEV1 ≥ LLN. Preserved ratio impaired spirometry (PRISm): FEV1/FVC ≥ LLN and FEV1 < LLN. #: calculated only for subjects with a history of smoking.

    • TABLE 2

      Cross-sectional associations between plasma proteins and FEV1 % predicted in EpiHealth (discovery cohort) and MOS (replication cohort)

      ProteinAbbreviationUniProtNoDiscovery cohort (EpiHealth)#Replication cohort (MOS)¶
      FEV1% predictedFEV1% predicted
      β-coefficient (95% CI)Adjusted p-valueβ-coefficient (95% CI)p-value
      LeptinLEPP41159−4.80 (−5.87– −3.74)4.9×10−16−2.17 (−3.52– −0.81)0.002
      Interleukin-6IL-6P05231−1.86 (−2.54– −1.18)5.8×10−6−1.49 (−2.48– −0.51)0.003
      Paraoxonase 3PON3Q151661.87 (1.12–2.61)4.5×10−51.45 (0.47–2.44)0.004
      Interleukin-1 receptor antagonistIL-1RAP18510−1.54 (−2.32– −0.77)0.003−1.50 (−2.57– −0.43)0.006
      Fatty acid-binding protein 4FABP4P15090−2.61 (−3.51– −1.72)1.4×10−6−1.62 (−2.86– −0.38)0.01
      Agouti-related proteinAGRPO002531.01 (0.35–1.67)0.041.01 (−0.04–2.05)0.06
      Growth hormoneGHP012411.15 (0.39–1.92)0.041.12 (−0.08–2.32)0.07
      Plasminogen activator inhibitorKIM1Q96D42−1.30 (−2.00– −0.60)0.007−0.88 (−1.96–0.20)0.11
      C-C motif chemokine 16CCL16O15467−1.23 (−1.91– −0.54)0.01−0.57 (−1.51–0.38)0.24
      Metalloproteinase inhibitor 4TIMP4Q99727−1.20 (−1.89– −0.50)0.01−0.61 (−1.61–0.41)0.24
      Retinoic acid receptor responder 2RARRES2Q99969−1.96 (−2.68– −1.24)5.8×10−6−0.59 (−1.60–0.41)0.25
      Receptor for advanced glycosylation and productsRAGEQ151091.02 (0.36–1.68)0.040.46 (−0.46–1.38)0.33
      Trefoil factor 3TFF3Q07654−1.08 (−1.77– −0.39)0.04−0.43 (−1.38–0.53)0.38
      Matrix metalloproteinase 7MMP7P09237−1.15 (−1.85– −0.45)0.020.34 (−0.60–1.29)0.48
      Plasminogen activator inhibitorPAIP05121−1.00 (−1.66– −0.34)0.04−0.26 (−1.24–0.72)0.60
      AdrenomedullinADMP35318−1.92 (−2.69– −1.15)4.5×10−5−0.22 (−1.20–0.75)0.65
      Growth/differentiation factor 15GDF15Q99988−1.36 (−2.15– −0.57)0.010.11 (−0.84–1.06)0.82
      Tissue-type plasminogen activatortPAP00750−1.56 (−2.28– −0.58)0.00060.09 (−0.95–1.12)0.87
      Adhesion G protein-coupled receptor G2ADGRG2Q8IZP91.64 (0.95–2.32)4.5×10−5−0.006 (−1.02–1.01)0.99

      Multivariable linear regression analysis for each protein. Sorted based on p-value in replication cohort. Data are presented as regression coefficients for proteins increased by at least 1 standard deviation. Adjusted for age, sex, cohort, body mass index, smoking, pack-years and physical activity. MOS: Malmö Offspring Study; FEV1: forced expiratory volume in 1 s; CI: confidence interval. #: n=2229; ¶: n=645.

      • TABLE 3

        Cross-sectional associations between plasma proteins and FVC % predicted in EpiHealth (discovery cohort) and MOS (replication cohort)

        ProteinAbbreviationUniProtNoDiscovery cohort (EpiHealth)#Replication cohort (MOS)¶
        FVC % predictedFVC % predicted
        β-coefficient (95% CI)Adjusted
        p-value
        β-coefficient (95% CI)p-value
        LeptinLEPP41159−5.31 (−6.40– −4.22)6.8×10−19−2.63 (−3.93– −1.32)8.8×10−5
        Paraoxonase 3PON3Q151662.17 (1.41–2.93)3.4×10−61.69 (0.74–2.64)0.0005
        Fatty acid-binding protein 4FABP4P15090−2.35 (−3.27– −1.43)2.6×10−5−2.09 (−3.29– −0.89)0.0006
        Interleukin-6IL-6P05231−1.34 (−2.04– −0.64)0.003−1.77 (−2.72– −0.81)0.0003
        Insulin-like growth factor-binding protein 2IGFBP2P180651.66 (0.91–2.42)0.0011.42 (0.44–2.40)0.004
        Interleukin-1 receptor antagonist proteinIL-1RAP18510−1.55 (−2.35– −0.76)0.003−1.40 (−2.44– −0.36)0.008
        Receptor for advanced glycosylation and productsRAGEQ151090.97 (0.30–1.65)0.051.20 (0.31–2.09)0.008
        Agouti-related proteinAGRPO002531.19 (0.51–1.87)0.0081.13 (0.12–2.14)0.03
        Fibroblast growth factor 21FGF21Q9NSA1−1.02 (−1.71– −0.31)0.05−1.01 (−2.00– −0.03)0.04
        Kidney injury moleculeKIM1Q96D42−1.40 (−2.11– −0.68)0.0028−1.01 (−2.06–0.03)0.06
        Retinoic acid receptor responder 2RARRES2Q99969−1.96 (−2.70– −1.22)1.2×10−5−0.84 (−1.81–0.13)0.09
        Hydroxyacid oxidase 1HAOX1Q9UJM8−1.41 (−2.08– −0.73)0.001−0.71 (−1.65–0.23)0.14
        C-C motif chemokine 16CCL16O15467−1.46 (−2.16– −0.76)0.001−0.68 (−1.60–0.24)0.15
        Insulin-like growth factor-binding protein 1IGFBP1P088331.53 (0.75–2.30)0.00270.76 (−0.32–1.83)0.17
        Plasminogen activator inhibitorPAIP05121−1.28 (−1.95– −0.60)0.0035−0.62 (−1.57–0.33)0.20
        Tissue-type plasminogen activatortPAP00750−1.41 (−2.15– −0.68)0.003−0.58 (−1.59–0.42)0.25
        Growth hormoneGHP012411.24 (0.45–2.02)0.0250.61 (−0.56–1.78)0.31
        C-C motif chemokine 17CCL17Q92583−1.03 (−1.70– −0.36)0.030.44 (−0.46–1.33)0.34
        C-C motif chemokine 3CCL3P10147−1.02 (−1.71– −0.33)0.04−0.34 (−1.27–0.59)0.47
        Matrix metalloproteinase 7MMP7P09237−1.34 (−2.06– −0.62)0.00430.33 (−0.58–1.25)0.48
        Adhesion G protein-coupled receptor G2ADGRG2Q8IZP91.89 (1.19–2.59)1.0×10−50.31 (−0.67–1.30)0.53
        Thrombospondin-2THBS2P35442−1.02 (−1.68– −0.36)0.03−0.27 (−1.19–0.64)0.55
        Spondin-2SPON2Q9BUD6−1.15 (−1.83– −0.46)0.013−0.25 (−1.14–0.63)0.57
        AdrenomedullinADMP35318−1.91 (−2.70– −1.12)9.5×10−5−0.25 (−1.19–0.70)0.61

        Multivariable linear regression analysis for each protein. Data are regression coefficients for proteins increased by at least 1 standard deviation. Adjusted for age, sex, cohort, body mass index, smoking, pack-years and physical activity. MOS: Malmö Offspring Study; FVC: forced vital capacity; CI: confidence interval. #: n=2229; ¶: n=645.

        • TABLE 4

          Sensitivity analysis in EpiHealth

          ProteinAbbreviationUniProtNoEpiHealth#EpiHealth¶
          FEV1 % predictedFEV1 % predicted
          β-coefficient (95% CI)Adjusted p-valueβ-coefficient (95% CI)Adjusted p-value
          LeptinLEPP41159−4.80 (−5.87– −3.74)4.9×10−16−3.44 (−4.46– −2.41)1.6×10−8
          Interleukin-6IL-6P05231−1.86 (−2.54– −1.18)5.8×10−6−1.78 (−2.54– −1.03)0.0003
          Paraoxonase 3PON3Q151661.87 (1.12–2.61)4.5×10−50.91 (0.69–1.75)0.27*
          Interleukin-1 receptor antagonistIL-1RAP18510−1.54 (−2.32– −0.77)0.003−1.16 (−2.07–0.46)0.17*
          Fatty acid-binding protein 4FABP4P15090−2.61 (−3.51– −1.72)1.4×10−6−2.3 (−3.27– −1.33)0.0003
          Agouti-related proteinAGRPO002531.01 (0.35–1.67)0.040.7 (−0.07–1.46)0.36*
          Growth hormoneGHP012411.15 (0.39–1.92)0.041.21 (0.33–2.08)0.11*
          Plasminogen activator inhibitorKIM1Q96D42−1.30 (−2.00– −0.60)0.007−1.37 (−2.20– −0.55)0.025
          C-C motif chemokine 16CCL16O15467−1.23 (−1.91– −0.54)0.01−0.90 (−1.66– −0.14)0.22*
          Metalloproteinase inhibitor 4TIMP4Q99727−1.20 (−1.89– −0.50)0.01−1.36 (−2.15– −0.57)0.023
          Retinoic acid receptor responder 2RARRES2Q99969−1.96 (−2.68– −1.24)5.8×10−6−1.68 (−2.46–0.9)0.001
          Receptor for advanced glycosylation and productsRAGEQ151091.02 (0.36–1.68)0.040.92 (0.17–1.67)0.2*
          Trefoil factor 3TFF3Q07654−1.08 (−1.77– −0.39)0.04−1.30 (−2.08– −0.53)0.025
          Matrix metalloproteinase 7MMP7P09237−1.15 (−1.85– −0.45)0.02−0.81 (−1.65–0.02)0.31*
          Plasminogen activator inhibitorPAIP05121−1.00 (−1.66– −0.34)0.04−0.76 (−1.50– −0.01)0.31*
          AdrenomedullinADMP35318−1.92 (−2.69– −1.15)4.5×10−5−1.65 (−2.54– −0.76)0.01
          Growth/differentiation factor 15GDF15Q99988−1.36 (−2.15– −0.57)0.01−1.58 (−2.54–0.63)0.03
          Tissue-type plasminogen activatortPAP00750−1.56 (−2.28– −0.58)0.0006−1.52 (−2.32– −0.73)0.009
          Adhesion G protein-coupled receptor G2ADGRG2Q8IZP91.64 (0.95–2.32)4.5×10−51.34 (0.56–2.11)0.02

          Cross-sectional associations between plasma proteins and FEV1% predicted in EpiHealth before and after exclusion of individuals with known CVD, diabetes or obesity. Multivariable linear regression analysis for each protein. Data are presented as regression coefficients for proteins increased by at least 1 standard deviation. Adjusted for age, sex, cohort, body mass index, smoking, pack-years and physical activity. For the sensitivity analysis this multivariable linear regression model was adjusted for hypertension, hyperlipidaemia and waist circumference (normal versus high) instead of BMI. FEV1: forced expiratory volume in 1 s; CI: confidence interval; CVD: cardiovascular disease. #: n=2229; ¶: n=1685; *: non-significant.

          • TABLE 5

            Sensitivity analysis in EpiHealth

            ProteinAbbreviationUniProtNoEpiHealth#EpiHealth¶
            FVC % preictedFVC % predicted
            β-coefficient (95% CI)Adjusted
            p-value
            β-coefficient (95% CI)Adjusted p-value
            LeptinLEPP41159−5.31 (−6.40– −4.22)6.8×10−19−4.64 (−5.7– −3.58)5.1×10−15
            Paraoxonase 3PON3Q151662.17 (1.41–2.93)3.4×10−061.52 (0.65–2.39)0.013
            Fatty acid-binding protein 4FAB4P15090−2.35 (−3.27– −1.43)2.6×10−05−2.93 (−3.93– −1.93)1.3×10−6
            Interleukin-6IL-6P05231−1.34 (−2.04– −0.64)0.003−1.35 (−2.14– −0.56)0.015
            Insulin-like growth factor-binding protein 2IGFBP2P180651.66 (0.91–2.42)0.0011.37 (0.51–2.23)0.02
            Interleukin-1 receptor antagonist proteinIL-1RAP18510−1.55 (−2.35– −0.76)0.003−1.78 (−2.73– −0.83)0.007
            Receptor for advanced glycosylation and productsRAGEQ151090.97 (0.30–1.65)0.050.95 (0.17–1.73)0.1+
            Agouti-related proteinAGRPO002531.19 (0.51–1.87)0.0081.07 (0.27–1.86)0.07+
            Fibroblast growth factor 21FGF21Q9NSA1−1.02 (−1.71– −0.31)0.05−1.27 (−2.08– −0.46)0.03
            Kidney injury moleculeKIM1Q96D42−1.40 (−2.11– −0.68)0.0028−1.59 (−2.44– −0.73)0.008
            Retinoic acid receptor responder 2RARRES2Q99969−1.96 (−2.70– −1.22)1.2×10−5−2.07 (−2.88–1.26)4.4×10−5
            Hydroxyacid oxidase 1HAOX1Q9UJM8−1.41 (−2.08– −0.73)0.001−1.33 (−2.11– −0.55)0.015
            C-C motif chemokine 16CCL16O15467−1.46 (−2.16– −0.76)0.001−1.31 (−2.09– −0.53)0.02
            Insulin-like growth factor-binding protein 1IGFBP1P088331.53 (0.75–2.30)0.00271.59 (0.72–2.47)0.008
            Plasminogen activator inhibitorPAIP05121−1.28 (−1.95– −0.60)0.0035−1.16 (−1.93– −0.39)0.04
            Tissue-type plasminogen activatortPAP00750−1.41 (−2.15– −0.68)0.003−1.59 (−2.41– −0.76)0.007
            Growth hormoneGHP012411.24 (0.45–2.02)0.0251.53 (0.62–2.45)0.02
            C-C motif chemokine 17CCL17Q92583−1.03 (−1.70– −0.36)0.03−1.09 (−1.86– −0.33)0.052+
            C-C motif chemokine 3CCL3P10147−1.02 (−1.71– −0.33)0.04−1.22 (−2.08– −0.35)0.06+
            Matrix metalloproteinase 7MMP7P09237−1.34 (−2.06– −0.62)0.0043−1.18 (−2.05– −0.32)0.06+
            Adhesion G protein-coupled receptor G2ADGRG2Q8IZP91.89 (1.19–2.59)1.0×10−51.79 (0.97–2.59)0.0006
            Thrombospondin-2THBS2P35442−1.02 (−1.68– −0.36)0.03−1.0 (−1.8– −0.19)0.1+
            Spondin-2SPON2Q9BUD6−1.15 (−1.83– −0.46)0.013−1.49 (−2.27– −0.7)0.007
            AdrenomedullinADMP35318−1.91 (−2.70– −1.12)9.5×10−5−2.14 (−3.07– −1.21)0.0004
            Angiopoietin Like 1ANGPTL1O958410.74 (0.07–1.4)0.18+31 (0.54–2–08)0.01
            Tumour necrosis factor receptor 2TNFR2P20333−0.87 (−1.59– −0.14)0.13+−1.25 (−2.04–−0.46)0.03
            Versican core proteinVCANP136110.93 (0.26–1.6)0.06+1.21 (0.44–1.97)0.03
            Trefoil factor 3TFF3Q07654−0.92 (−1.63– −0.21)0.095+−1.19 (−1.99– −0.39)0.04
            Low-density lipoprotein receptorLDLreceptorP01130−0.88 (−1.58– −0.19)0.1+−1.19 (−1.99– −0.38)0.04

            Cross-sectional associations between plasma proteins and FVC % predicted in EpiHealth before and after exclusion of individuals with known CVD, diabetes or obesity. Multivariable linear regression analysis for each protein. Data are regression coefficients for proteins increased by at least 1 standard deviation. Adjusted for age, sex, cohort, body mass index, smoking, pack-years and physical activity. For the sensitivity analysis this multivariable linear regression model was adjusted for hypertension, hyperlipidaemia and waist circumference (normal versus high) instead of BMI. FVC: forced vital capacity; CI: confidence interval; CVD: cardiovascular disease. #: n=2229; ¶: n=1685; +: non-significant.

            Supplementary Materials

            • Figures
            • Tables
            • Supplementary Material

              Please note: supplementary material is not edited by the Editorial Office, and is uploaded as it has been supplied by the author.

              Table S1a 00321-2022.tableS1a

              Table S1b 00321-2022.tableS1b

            PreviousNext
            Back to top
            Vol 9 Issue 2 Table of Contents
            ERJ Open Research: 9 (2)
            • Table of Contents
            • Index by author
            Email

            Thank you for your interest in spreading the word on European Respiratory Society .

            NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

            Enter multiple addresses on separate lines or separate them with commas.
            Cardiovascular disease-linked plasma proteins are mainly associated with lung volume
            (Your Name) has sent you a message from European Respiratory Society
            (Your Name) thought you would like to see the European Respiratory Society web site.
            CAPTCHA
            This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
            Print
            Citation Tools
            Cardiovascular disease-linked plasma proteins are mainly associated with lung volume
            Andreas Rydell, Elisabet Nerpin, XingWu Zhou, Lars Lind, Eva Lindberg, Jenny Theorell Haglöw, Tove Fall, Christer Janson, Karin Lisspers, Sölve Elmståhl, Suneela Zaigham, Olle Melander, Peter M. Nilsson, Johan Ärnlöv, Andrei Malinovschi
            ERJ Open Research Mar 2023, 9 (2) 00321-2022; DOI: 10.1183/23120541.00321-2022

            Citation Manager Formats

            • BibTeX
            • Bookends
            • EasyBib
            • EndNote (tagged)
            • EndNote 8 (xml)
            • Medlars
            • Mendeley
            • Papers
            • RefWorks Tagged
            • Ref Manager
            • RIS
            • Zotero
            Share
            Cardiovascular disease-linked plasma proteins are mainly associated with lung volume
            Andreas Rydell, Elisabet Nerpin, XingWu Zhou, Lars Lind, Eva Lindberg, Jenny Theorell Haglöw, Tove Fall, Christer Janson, Karin Lisspers, Sölve Elmståhl, Suneela Zaigham, Olle Melander, Peter M. Nilsson, Johan Ärnlöv, Andrei Malinovschi
            ERJ Open Research Mar 2023, 9 (2) 00321-2022; DOI: 10.1183/23120541.00321-2022
            del.icio.us logo Digg logo Reddit logo Technorati logo Twitter logo CiteULike logo Connotea logo Facebook logo Google logo Mendeley logo
            Full Text (PDF)

            Jump To

            • Article
              • Abstract
              • Abstract
              • Introduction
              • Material and methods
              • Results
              • Discussion
              • Supplementary material
              • Footnotes
              • References
            • Figures & Data
            • Info & Metrics
            • PDF

            Subjects

            • Lung biology and experimental studies
            • Lung structure and function
            • Tweet Widget
            • Facebook Like
            • Google Plus One

            More in this TOC Section

            Original research articles

            • CT reveals hypertrophic remodelling of the diaphragm in CF
            • mBorg/6MWD ratio to assess exertional symptoms
            • Impact of infections and probiotics on nasal microbiota
            Show more Original research articles

            Lung function

            • IOS and respiratory symptoms in SCAPIS
            • Association of vitamin K with lung function and disease
            Show more Lung function

            Related Articles

            Navigate

            • Home
            • Current issue
            • Archive

            About ERJ Open Research

            • Editorial board
            • Journal information
            • Press
            • Permissions and reprints
            • Advertising

            The European Respiratory Society

            • Society home
            • myERS
            • Privacy policy
            • Accessibility

            ERS publications

            • European Respiratory Journal
            • ERJ Open Research
            • European Respiratory Review
            • Breathe
            • ERS books online
            • ERS Bookshop

            Help

            • Feedback

            For authors

            • Instructions for authors
            • Publication ethics and malpractice
            • Submit a manuscript

            For readers

            • Alerts
            • Subjects
            • RSS

            Subscriptions

            • Accessing the ERS publications

            Contact us

            European Respiratory Society
            442 Glossop Road
            Sheffield S10 2PX
            United Kingdom
            Tel: +44 114 2672860
            Email: journals@ersnet.org

            ISSN

            Online ISSN: 2312-0541

            Copyright © 2023 by the European Respiratory Society