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Clinical Chemistry and Laboratory Medicine (CCLM)

Published in Association with the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM)

Editor-in-Chief: Plebani, Mario

Ed. by Gillery, Philippe / Greaves, Ronda / Lackner, Karl J. / Lippi, Giuseppe / Melichar, Bohuslav / Payne, Deborah A. / Schlattmann, Peter


IMPACT FACTOR 2018: 3.638

CiteScore 2018: 2.44

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1437-4331
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Volume 57, Issue 7

Issues

A study of biological and lifestyle factors, including within-subject variation, affecting concentrations of growth differentiation factor 15 in serum

Magdalena Krintus
  • Corresponding author
  • Department of Laboratory Medicine, Nicolaus Copernicus University, Collegium Medicum, 9 Sklodowskiej-Curie Street, 85-094 Bydgoszcz, Poland, Phone: +48 52 585 40 23, Fax: +48 52 585 40 24
  • Email
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Federica Braga
  • Department of Biomedical and Clinical Sciences “Luigi Sacco”, University of Milan, Milan, Italy
  • Clinical Pathology Unit, ASST Fatebenefratelli-Sacco, Milan, Italy
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Marek Kozinski
  • Department of Principles of Clinical Medicine, Nicolaus Copernicus University, Collegium Medicum, Bydgoszcz, Poland
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Simona Borille / Jacek Kubica
  • Department of Cardiology and Internal Medicine, Nicolaus Copernicus University, Collegium Medicum, Bydgoszcz, Poland
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Grazyna Sypniewska
  • Department of Laboratory Medicine, Nicolaus Copernicus University, Collegium Medicum, Bydgoszcz, Poland
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Mauro Panteghini
  • Department of Biomedical and Clinical Sciences “Luigi Sacco”, University of Milan, Milan, Italy
  • Clinical Pathology Unit, ASST Fatebenefratelli-Sacco, Milan, Italy
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2018-11-24 | DOI: https://doi.org/10.1515/cclm-2018-0908

Abstract

Background

Growth differentiation factor 15 (GDF-15) is an emerging cardiovascular biomarker, and a fully automated immunoassay has recently become available. The objectives of the study were to identify biological and lifestyle factors affecting serum GDF-15 concentrations and derive robust reference intervals, and to estimate GDF-15 within-subject biological variation and derived indices.

Methods

A presumably healthy population of 533 questionnaire-screened adults was used to identify the biological and lifestyle determinants of serum GDF-15. Following stringent exclusion criteria, a final group of 173 individuals was selected to establish GDF-15 reference interval. Twenty-six healthy volunteers were enrolled in the biological variation substudy.

Results

Using a multiple regression model, age, B-type natriuretic peptide and C-reactive protein as well as smoking status were significantly related to serum GDF-15 concentrations. The upper reference limit (URL) for serum GDF-15 concentrations (90% confidence interval [CI]) was 866 ng/L (733–999 ng/L), with no sex-related difference. Although GDF-15 tended to increase with age, the weak dependence of marker from age does not justify age-related URL. The within-subject CV was 6.3% (95% CI, 4.5%–8.5%), with no sex difference in intraindividual variances. The reference change value (RCV) for GDF-15 was 23%, and two are the specimens required to ensure that the mean GDF-15 result is within ±10% of the individual’s homeostatic set point.

Conclusions

By identifying the main factors influencing serum GDF-15 concentrations, we robustly established the URL to be applied in adult population. As intraindividual variation of GDF-15 is relatively low, monitoring longitudinal changes in its concentrations over time using RCV can be a good alternative for interpreting GDF-15 in clinical setting.

Keywords: biological variation; growth differentiation factor 15; reference limits

References

  • 1.

    Wollert KC, Kempf T, Giannitsis E, Bertsch T, Braun SL, Maier H, et al. An automated assay for growth differentiation factor 15. JALM 2017;1:510–21.Google Scholar

  • 2.

    Hijazi Z, Oldgren J, Lindbäck J, Alexander JH, Connolly SJ, Eikelboom JW, et al. A biomarker-based risk score to predict death in patients with atrial fibrillation: the ABC (age, biomarkers, clinical history) death risk score. Eur Heart J 2018;39:477–85.CrossrefWeb of SciencePubMedGoogle Scholar

  • 3.

    Wollert KC, Kempf T, Wallentin L. Growth differentiation factor 15 as a biomarker in cardiovascular disease. Clin Chem 2017;63:140–51.CrossrefWeb of SciencePubMedGoogle Scholar

  • 4.

    Lind L, Wallentin L, Kempf T, Tapken H, Quint A, Lindahl B, et al. Growth-differentiation factor-15 is an independent marker of cardiovascular dysfunction and disease in the elderly: results from the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) study. Eur Heart J 2009;30:2346–53.Web of ScienceCrossrefPubMedGoogle Scholar

  • 5.

    Daniels LB, Clopton P, Laughlin GA, Maisel AS, Barrett-Connor E. Growth-differentiation factor-15 is a robust, independent predictor of 11-year mortality risk in community-dwelling older adults: the Rancho Bernardo Study. Circulation 2011;123:2101–10.CrossrefWeb of ScienceGoogle Scholar

  • 6.

    Wang TJ, Wollert KC, Larson MG, Coglianese E, McCabe EL, Cheng S, et al. Prognostic utility of novel biomarkers of cardiovascular stress: the Framingham Heart Study. Circulation 2012;126:1596–604.PubMedCrossrefWeb of ScienceGoogle Scholar

  • 7.

    Andersson C, Enserro D, Sullivan L, Wang TJ, Januzzi JL Jr, Benjamin EJ, et al. Relations of circulating GDF-15, soluble ST2, and troponin-I concentrations with vascular function in the community: the Framingham Heart Study. Atherosclerosis 2016;248:245–51.CrossrefWeb of SciencePubMedGoogle Scholar

  • 8.

    Rohatgi A, Patel P, Das SR, Ayers CR, Khera A, Martinez-Rumayor A, et al. Association of growth differentiation factor-15 with coronary atherosclerosis and mortality in a young, multiethnic population: observations from the Dallas Heart Study. Clin Chem 2012;58:172–82.CrossrefWeb of ScienceGoogle Scholar

  • 9.

    Hagström E, Held C, Stewart RA, Aylward PE, Budaj A, Cannon CP, et al. Growth differentiation factor 15 predicts all-cause morbidity and mortality in stable coronary heart disease. Clin Chem 2017;63:325–33.PubMedCrossrefGoogle Scholar

  • 10.

    Hagström E, James SK, Bertilsson M, Becker RC, Himmelmann A, Husted S, et al. Growth differentiation factor-15 level predicts major bleeding and cardiovascular events in patients with acute coronary syndromes: results from the PLATO study. Eur Heart J 2016;37:1325–33.CrossrefWeb of SciencePubMedGoogle Scholar

  • 11.

    Chan MM, Santhanakrishnan R, Chong JP, Chen Z, Tai BC, Liew OW, et al. Growth differentiation factor 15 in heart failure with preserved vs. reduced ejection fraction. Eur J Heart Fail 2016;18:81–8.Web of SciencePubMedCrossrefGoogle Scholar

  • 12.

    Cotter G, Voors AA, Prescott MF, Felker GM, Filippatos G, Greenberg BH, et al. Growth differentiation factor 15 (GDF-15) in patients admitted for acute heart failure: results from the RELAX-AHF study. Eur J Heart Fail 2015;17:1133–43.CrossrefWeb of SciencePubMedGoogle Scholar

  • 13.

    Wallentin L, Hijazi Z, Andersson U, Alexander JH, De Caterina R, Hanna M, et al. Growth differentiation factor 15, a marker of oxidative stress and inflammation, for risk assessment in patients with atrial fibrillation: insights from the Apixaban for Reduction in Stroke and Other Thromboembolic Events in Atrial Fibrillation (ARISTOTLE) trial. Circulation 2014;130:1847–58.Web of SciencePubMedGoogle Scholar

  • 14.

    Ho JE, Mahajan A, Chen MH, Larson MG, McCabe EL, Ghorbani A, et al. Clinical and genetic correlates of growth differentiation factor 15 in the community. Clin Chem 2012;58:1582–91.Web of ScienceCrossrefPubMedGoogle Scholar

  • 15.

    Mueller T, Leitner I, Egger M, Haltmayer M, Dieplinger B. Association of the biomarkers soluble ST2, galectin-3 and growth-differentiation factor-15 with heart failure and other non-cardiac diseases. Clin Chim Acta 2015;445:155–60.Web of ScienceCrossrefPubMedGoogle Scholar

  • 16.

    Doerstling S, Hedberg P, Öhrvik J, Leppert J, Henriksen E. Growth differentiation factor 15 in a community-based sample: age-dependent reference limits and prognostic impact. Ups J Med Sci 2018;123:86–93.CrossrefWeb of ScienceGoogle Scholar

  • 17.

    Meijers WC, van der Velde AR, Muller Kobold AC, Dijck-Brouwer J, Wu AH, Jaffe A, et al. Variability of biomarkers in patients with chronic heart failure and healthy controls. Eur J Heart Fail 2017;19:357–65.Web of ScienceCrossrefPubMedGoogle Scholar

  • 18.

    Braga F, Panteghini M. Generation of data on within-subject biological variation in laboratory medicine: an update. Crit Rev Clin Lab Sci 2016;53:313–25.CrossrefPubMedWeb of ScienceGoogle Scholar

  • 19.

    Krintus M, Kozinski M, Boudry P, Lackner K, Lefèvre G, Lennartz L, et al. Defining normality in a European multinational cohort: critical factors influencing the 99th percentile upper reference limit for high sensitivity cardiac troponin I. Int J Cardiol 2015;187:256–63.Web of ScienceCrossrefGoogle Scholar

  • 20.

    Krintus M, Kozinski M, Fabiszak T, Kubica J, Panteghini M, Sypniewska G. Establishing reference intervals for galectin-3 concentrations in serum requires careful consideration of its biological determinants. Clin Biochem 2017;50:599–604.Web of ScienceCrossrefPubMedGoogle Scholar

  • 21.

    Krintus M, Kozinski M, Braga F, Kubica J, Sypniewska G, Panteghini M. Plasma midregional proadrenomedullin (MR-proADM) concentrations and their biological determinants in a reference population. Clin Chem Lab Med 2018;56:1161–8.Web of ScienceCrossrefGoogle Scholar

  • 22.

    Krintus M, Kozinski M, Boudry P, Capell NE, Köller U, Lackner K, et al. European multicenter analytical evaluation of the Abbott ARCHITECT STAT high sensitive troponin I immunoassay. Clin Chem Lab Med 2014;52:1657–65.PubMedWeb of ScienceGoogle Scholar

  • 23.

    Ponikowski P, Voors AA, Anker SD, Bueno H, Cleland JG, Coats AJ, et al. 2016 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: the task force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC) developed with the special contribution of the Heart Failure Association (HFA) of the ESC. Eur Heart J 2016;37:2129–200.Web of ScienceGoogle Scholar

  • 24.

    Pearson TA, Mensah GA, Alexander RW, Anderson JL, Cannon RO 3rd, et al. Centers for Disease Control and Prevention; American Heart Association. Markers of inflammation and cardiovascular disease: application to clinical and public health practice: a statement for healthcare professionals from the Centers for Disease Control and Prevention and the American Heart Association. Circulation 2003;107:499–511.PubMedGoogle Scholar

  • 25.

    Panteghini M, John WG. Implementation of haemoglobin A1c results traceable to the IFCC reference system: the way forward. Clin Chem Lab Med 2007;45:942–4.Web of SciencePubMedGoogle Scholar

  • 26.

    Stevens PE, Levin A. Evaluation and management of chronic kidney disease: synopsis of the Kidney Disease: Improving Global Outcomes 2012 clinical practice guideline. Ann Intern Med 2013;158:825–30.Web of SciencePubMedCrossrefGoogle Scholar

  • 27.

    Roche Cobas Elecsys GDF-15 package insert, 03.2018, V.2.0.Google Scholar

  • 28.

    CLSI. Defining, establishing and verifying reference intervals in the clinical laboratory; Approved guideline. CLSI document EP28A3c. Wayne PA. Clinical and Laboratory Standards Institute, 2010.Google Scholar

  • 29.

    Reed AH, Henry RJ, Mason WB. Influence of statistical method used on the resulting estimate of normal range. Clin Chem 1971;17:275–84.PubMedGoogle Scholar

  • 30.

    Røraas T, Støve B, Petersen PH, Sandberg S. Biological variation: evaluation of methods for constructing confidence intervals for estimates of within-person biological variation for different distributions of the within-person effect. Clin Chim Acta 2017;468:166–73.PubMedWeb of ScienceCrossrefGoogle Scholar

  • 31.

    Røraas T, Støve B, Petersen PH, Sandberg S. Biological variation: the effect of different distributions on estimated within-person variation and reference change values. Clin Chem 2016;62: 725–36.CrossrefWeb of SciencePubMedGoogle Scholar

  • 32.

    Braga F, Ferraro S, Mozzi R, Panteghini M. The importance of individual biology in the clinical use of serum biomarkers for ovarian cancer. Clin Chem Lab Med 2014;52:1625–31.PubMedWeb of ScienceGoogle Scholar

  • 33.

    Pasqualetti S, Infusino I, Carnevale A, Szoke D, Panteghini M. The calibrator value assignment protocol of the Abbott enzymatic creatinine assay is inadequate for ensuring suitable quality of serum measurements. Clin Chim Acta 2015;450:125–6.CrossrefWeb of SciencePubMedGoogle Scholar

  • 34.

    Røraas T, Petersen PH, Sandberg S. Confidence intervals and power calculations for within-person biological variation: effect of analytical imprecision, number of replicates, number of samples, and number of individuals. Clin Chem 2012;58:1306–13.CrossrefPubMedWeb of ScienceGoogle Scholar

  • 35.

    Fraser CG, Petersen PH. The importance of imprecision. Ann Clin Biochem 1991;28:207–11.PubMedCrossrefGoogle Scholar

  • 36.

    Fraser CG, Hyltoft Peterson P, Libeer JC, Ricos C. Proposal for setting generally applicable quality goals solely based on biology. Ann Clin Biochem 1997;34:8–12.CrossrefGoogle Scholar

  • 37.

    Sandberg S, Fraser CG, Horvath AR, Jansen R, Jones G, Oosterhuis W, et al. Defining analytical performance specifications: consensus statement from the 1st Strategic Conference of the European Federation of Clinical Chemistry and Laboratory Medicine. Clin Chem Lab Med 2015;53:833–5.Web of SciencePubMedGoogle Scholar

  • 38.

    Ceriotti F, Hinzmann R, Panteghini M. Reference intervals: the way forward. Ann Clin Biochem 2009;46:8–17.Web of ScienceCrossrefPubMedGoogle Scholar

  • 39.

    Panteghini M, Adeli K, Ceriotti F, Sandberg S, Horvath AR. American liver guidelines and cutoffs for “normal” ALT: a potential for overdiagnosis. Clin Chem 2017;63:1196–8.CrossrefWeb of ScienceGoogle Scholar

  • 40.

    Kempf T, Horn-Wichmann R, Brabant G, Peter T, Allhoff T, Klein G, et al. Circulating concentrations of growth differentiation factor 15 in apparently healthy elderly individuals and patients with chronic heart failure as assessed by a new immunoradiometric sandwich assay. Clin Chem 2007;53:284–91.Web of SciencePubMedGoogle Scholar

  • 41.

    Ceriotti F. Quality specifications for the extra-analytical phase of laboratory testing: reference intervals and decision limits. Clin Biochem 2017;50:595–8.Web of ScienceCrossrefPubMedGoogle Scholar

  • 42.

    Aarsand AK, Røraas T, Fernandez-Calle P, Ricos C, Díaz-Garzón J, Jonker N, et al. The Biological Variation Data Critical Appraisal Checklist: a standard for evaluating studies on biological variation. Clin Chem 2018;64:501–14.Web of SciencePubMedCrossrefGoogle Scholar

About the article

aMagdalena Krintus and Federica Braga contributed equally to this work.


Received: 2018-08-22

Accepted: 2018-10-18

Published Online: 2018-11-24

Published in Print: 2019-06-26


Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

Research funding: None declared.

Employment or leadership: None declared.

Honorarium: None declared.

Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.


Citation Information: Clinical Chemistry and Laboratory Medicine (CCLM), Volume 57, Issue 7, Pages 1035–1043, ISSN (Online) 1437-4331, ISSN (Print) 1434-6621, DOI: https://doi.org/10.1515/cclm-2018-0908.

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