Skip to main content

Advertisement

Log in

Longitudinal course of GDF15 levels before acute hospitalization and death in the general population

  • Original Article
  • Published:
GeroScience Aims and scope Submit manuscript

Abstract

Growth differentiation 15 (GDF15) is a potential novel biomarker of biological aging. To separate the effects of chronological age and birth cohort from biological age, longitudinal studies investigating the associations of GDF15 levels with adverse health outcomes are needed. We investigated changes in GDF15 levels over 10 years in an age-stratified sample of the general population and their relation to the risk of acute hospitalization and death. Serum levels of GDF15 were measured three times in 5-year intervals in 2176 participants aged 30, 40, 50, or 60 years from the Danish population-based DAN-MONICA cohort. We assessed the association of single and repeated GDF15 measurements with the risk of non-traumatic acute hospitalizations. We tested whether changes in GDF15 levels over 10 years differed according to the frequency of hospitalizations within 2 years or survival within 20 years, after the last GDF15 measurement. The change in GDF15 levels over time was dependent on age and sex. Higher GDF15 levels and a greater increase in GDF15 levels were associated with an increased risk of acute hospitalization in adjusted Cox regression analyses. Participants with more frequent admissions within 2 years, and those who died within 20 years, after the last GDF15 measurement already had elevated GDF15 levels at baseline and experienced greater increases in GDF15 levels during the study. The change in GDF15 levels was associated with changes in C-reactive protein and biomarkers of kidney, liver, and cardiac function. Monitoring of GDF15 starting in middle-aged could be valuable for the prediction of adverse health outcomes.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Data availability

The datasets are not publicly available due to regulations set out by the Danish Data Protection Agency but are available from the corresponding author on reasonable request.

References

  1. Brown CJ, Roth DL, Allman RM, Sawyer P, Ritchie CS, Roseman JM. Trajectories of life-space mobility after hospitalization. Ann Intern Med. 2009;150:372–8.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Brown CJ, Foley KT, Lowman JD, MacLennan PA, Razjouyan J, Najafi B, et al. Comparison of posthospitalization function and community mobility in hospital mobility program and usual care patients: a randomized clinical trial. JAMA Intern Med. 2016;176:921–7.

    Article  PubMed  Google Scholar 

  3. Volpato S, Onder G, Cavalieri M, Guerra G, Sioulis F, Maraldi C, et al. Characteristics of nondisabled older patients developing new disability associated with medical illnesses and hospitalization. J Gen Intern Med. 2007;22:668–74.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Boyd CM, Ricks M, Fried LP, Guralnik JM, Xue Q-L, Xia J, et al. Functional decline and recovery of activities of daily living in hospitalized, disabled older women: the Women’s Health and Aging Study I. J Am Geriatr Soc. 2009;57:1757–66.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Bodilsen AC, Klausen HH, Petersen J, Beyer N, Andersen O, Jørgensen LM, et al. Prediction of mobility lmitations after hospitalization in older medical patients by simple measures of physical performance obtained at admission to the emergency department. PLoS One. 2016;11:e0154350.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  6. Brown CJ, Friedkin RJ, Inouye SK. Prevalence and outcomes of low mobility in hospitalized older patients. J Am Geriatr Soc. 2004;52:1263–70.

    Article  PubMed  Google Scholar 

  7. Søvsø MB, Hermansen SB, Færk E, Lindskou TA, Ludwig M, Møller JM, et al. Diagnosis and mortality of emergency department patients in the North Denmark region. BMC Health Serv Res. 2018;18:548.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Vest-Hansen B, Riis AH, Sørensen HT, Christiansen CF. Acute admissions to medical departments in Denmark: diagnoses and patient characteristics. Eur J Intern Med. 2014;25:639–45.

    Article  PubMed  Google Scholar 

  9. Nieminen MS, Brutsaert D, Dickstein K, Drexler H, Follath F, Harjola V-P, et al. EuroHeart Failure Survey II (EHFS II): a survey on hospitalized acute heart failure patients: description of population. Eur Heart J Oxford Academic. 2006;27:2725–36.

    Article  Google Scholar 

  10. Ranasinghe I, Wang Y, Dharmarajan K, Hsieh AF, Bernheim SM, Krumholz HM. Readmissions after hospitalization for heart failure, acute myocardial infarction, or pneumonia among young and middle-aged adults: a retrospective observational cohort study. PLoS Med [Internet]. 2014 [cited 2020 Sep 20];11. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4181962/

  11. Jain S, Khera R, Mortensen EM, Weissler JC. Readmissions of adults within three age groups following hospitalization for pneumonia: analysis from the Nationwide Readmissions Database. PLoS One. 2018;13:e0203375.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  12. Juul-Larsen HG, Petersen J, Sivertsen DM, Andersen O. Prevalence and overlap of disease management program diseases in older hospitalized patients. Eur J Ageing. 2017;14:283–93.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Juul-Larsen HG, Christensen LD, Bandholm T, Andersen O, Kallemose T, Jørgensen LM, et al. Patterns of multimorbidity and differences in healthcare utilization and complexity among acutely hospitalized medical patients (≥65 years) - a latent class approach. Clin Epidemiol. 2020;12:245–59.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci. 2001;56:M146–56.

    Article  CAS  PubMed  Google Scholar 

  15. Gordon SJ, Baker N, Kidd M, Maeder A, Grimmer KA. Pre-frailty factors in community-dwelling 40–75 year olds: opportunities for successful ageing. BMC Geriatr. 2020;20:96.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Hanlon P, Nicholl BI, Jani BD, Lee D, McQueenie R, Mair FS. Frailty and pre-frailty in middle-aged and older adults and its association with multimorbidity and mortality: a prospective analysis of 493 737 UK Biobank participants. Lancet Public Health. 2018;3:e323–32.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Salanitro AH, Ritchie CS, Hovater M, Roth DL, Sawyer P, Locher JL, et al. Inflammatory biomarkers as predictors of hospitalization and death in community-dwelling older adults. Arch Gerontol Geriatr. 2012;54:e387–91.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Salanitro AH, Hovater M, Hearld KR, Roth DL, Sawyer P, Locher JL, et al. Symptom burden predicts hospitalization independent of comorbidity in community-dwelling older adults. J Am Geriatr Soc. 2012;60:1632–7.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Byles JE, D’Este C, Parkinson L, O’Connell R, Treloar C. Single index of multimorbidity did not predict multiple outcomes. J Clin Epidemiol. 2005;58:997–1005.

    Article  PubMed  Google Scholar 

  20. Boeckxstaens P, Vaes B, Van Pottelbergh G, De Sutter A, Legrand D, Adriaensen W, et al. Multimorbidity measures were poor predictors of adverse events in patients aged ≥80 years: a prospective cohort study. J Clin Epidemiol. 2015;68:220–7.

    Article  PubMed  Google Scholar 

  21. Adriaensen W, Matheï C, Vaes B, van Pottelbergh G, Wallemacq P, Degryse J-M. Interleukin-6 as a first-rated serum inflammatory marker to predict mortality and hospitalization in the oldest old: a regression and CART approach in the BELFRAIL study. Exp Gerontol. 2015;69:53–61.

    Article  CAS  PubMed  Google Scholar 

  22. Lehallier B, Gate D, Schaum N, Nanasi T, Lee SE, Yousef H, et al. Undulating changes in human plasma proteome profiles across the lifespan. Nat Med. 2019;25:1843–50.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Conte M, Ostan R, Fabbri C, Santoro A, Guidarelli G, Vitale G, et al. Human aging and longevity are characterized by high levels of mitokines. J Gerontol A Biol Sci Med Sci. 2019;74:600–7.

    Article  CAS  PubMed  Google Scholar 

  24. Brown DA, Ward RL, Buckhaults P, Liu T, Romans KE, Hawkins NJ, et al. MIC-1 Serum level and genotype: associations with progress and prognosis of colorectal carcinoma. Clin Cancer Res. 2003;9:2642–50.

    CAS  PubMed  Google Scholar 

  25. Fairlie WD, Moore AG, Bauskin AR, Russell PK, Zhang H-P, Breit SN. MIC-1 is a novel TGF-β superfamily cytokine associated with macrophage activation. J Leukoc Biol. 1999;65:2–5.

    Article  CAS  PubMed  Google Scholar 

  26. 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.

    Article  CAS  PubMed  Google Scholar 

  27. Buendgens L, Yagmur E, Bruensing J, Herbers U, Baeck C, Trautwein C, et al. Growth differentiation factor-15 is a predictor of mortality in critically ill patients with sepsis. Dis Markers. 2017;2017:5271203.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  28. Lerner L, Hayes TG, Tao N, Krieger B, Feng B, Wu Z, et al. Plasma growth differentiation factor 15 is associated with weight loss and mortality in cancer patients. J Cachexia Sarcopenia Muscle. 2015;6:317–24.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Clark BJ, Bull TM, Benson AB, Stream AR, Macht M, Gaydos J, et al. Growth differentiation factor-15 and prognosis in acute respiratory distress syndrome: a retrospective cohort study. Crit Care. 2013;17:R92.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Kim JS, Kim S, Won CW, Jeong KH. Association between plasma levels of growth differentiation factor-15 and renal function in the elderly: Korean frailty and aging cohort study. Kidney Blood Press Res. 2019;44:405–14.

    Article  CAS  PubMed  Google Scholar 

  31. Kempf T, Björklund E, Olofsson S, Lindahl B, Allhoff T, Peter T, et al. Growth-differentiation factor-15 improves risk stratification in ST-segment elevation myocardial infarction. Eur Heart J. 2007;28:2858–65.

    Article  CAS  PubMed  Google Scholar 

  32. 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.

    Article  CAS  PubMed  Google Scholar 

  33. Kempf T, von Haehling S, Peter T, Allhoff T, Cicoira M, Doehner W, et al. Prognostic utility of growth differentiation factor-15 in patients with chronic heart failure. J Am Coll Cardiol. 2007;50:1054–60.

    Article  CAS  PubMed  Google Scholar 

  34. Brown DA, Breit SN, Buring J, Fairlie WD, Bauskin AR, Liu T, et al. Concentration in plasma of macrophage inhibitory cytokine-1 and risk of cardiovascular events in women: a nested case-control study. Lancet. 2002;359:2159–63.

    Article  CAS  PubMed  Google Scholar 

  35. Wollert KC, Kempf T, Lagerqvist B, Lindahl B, Olofsson S, Allhoff T, et al. Growth differentiation factor 15 for risk stratification and selection of an invasive treatment strategy in non ST-elevation acute coronary syndrome. Circulation. 2007;116:1540–8.

    Article  PubMed  Google Scholar 

  36. Wollert KC, Kempf T, Peter T, Olofsson S, James S, Johnston N, et al. Prognostic value of growth-differentiation factor-15 in patients with non-ST-elevation acute coronary syndrome. Circulation. 2007;115:962–71.

    Article  CAS  PubMed  Google Scholar 

  37. Carlsson AC, Ingelsson E, Sundström J, Jesus Carrero J, Gustafsson S, Feldreich T, et al. Use of proteomics to investigate kidney function decline over 5 years. Clin J Am Soc Nephrol. 2017;12:1226–35.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Ho JE, Hwang S-J, Wollert KC, Larson MG, Cheng S, Kempf T, et al. Biomarkers of cardiovascular stress and incident chronic kidney disease. Clin Chem. 2013;59:1613–20.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Husebø GR, Grønseth R, Lerner L, Gyuris J, Hardie JA, Bakke PS, et al. Growth differentiation factor-15 is a predictor of important disease outcomes in patients with COPD. Eur Respir J. 2017;49:1601298.

    Article  PubMed  CAS  Google Scholar 

  40. Lee ES, Kim SH, Kim HJ, Kim KH, Lee BS, Ku BJ. Growth differentiation factor 15 predicts chronic liver disease severity. Gut Liver. 2017;11:276–82.

    Article  CAS  PubMed  Google Scholar 

  41. Krintus M, Braga F, Kozinski M, Borille S, Kubica J, Sypniewska G, et al. A study of biological and lifestyle factors, including within-subject variation, affecting concentrations of growth differentiation factor 15 in serum. Clin Chem Lab Med. 2019;57:1035–43.

    Article  CAS  PubMed  Google Scholar 

  42. Bao X, Borné Y, Muhammad IF, Nilsson J, Lind L, Melander O, et al. Growth differentiation factor 15 is positively associated with incidence of diabetes mellitus: the Malmö Diet and Cancer-Cardiovascular Cohort. Diabetologia. 2019;62:78–86.

    Article  CAS  PubMed  Google Scholar 

  43. Fluschnik N, Ojeda F, Zeller T, Jørgensen T, Kuulasmaa K, Becher PM, et al. Predictive value of long-term changes of growth differentiation factor-15 over a 27-year-period for heart failure and death due to coronary heart disease. PLoS One. 2018;13:e0197497.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  44. Eggers KM, Kempf T, Wallentin L, Wollert KC, Lind L. Change in growth differentiation factor 15 concentrations over time independently predicts mortality in community-dwelling elderly individuals. Clin Chem. 2013;59:1091–8.

    Article  CAS  PubMed  Google Scholar 

  45. Kempf T, Guba-Quint A, Torgerson J, Magnone MC, Haefliger C, Bobadilla M, et al. Growth differentiation factor 15 predicts future insulin resistance and impaired glucose control in obese nondiabetic individuals: results from the XENDOS trial. Eur J Endocrinol. 2012;167:671–8.

    Article  CAS  PubMed  Google Scholar 

  46. Anand IS, Kempf T, Rector TS, Tapken H, Allhoff T, Jantzen F, et al. Serial measurement of growth-differentiation factor-15 in heart failure: relation to disease severity and prognosis in the Valsartan Heart Failure Trial. Circulation. 2010;122:1387–95.

    Article  CAS  PubMed  Google Scholar 

  47. Dallmeier D, Brenner H, Mons U, Rottbauer W, Koenig W, Rothenbacher D. Growth differentiation factor 15, its 12-month relative change, and risk of cardiovascular events and total mortality in patients with stable coronary heart disease: 10-year follow-up of the KAROLA study. Clin Chem. 2016;62:982–92.

    Article  CAS  PubMed  Google Scholar 

  48. Zeller T, Hughes M, Tuovinen T, Schillert A, Conrads-Frank A, den Ruijter H, et al. BiomarCaRE: rationale and design of the European BiomarCaRE project including 300,000 participants from 13 European countries. Eur J Epidemiol. 2014;29:777–90.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Osler M, Linneberg A, Glümer C, Jørgensen T. The cohorts at the Research Centre for Prevention and Health, formerly ‘The Glostrup Population Studies’. Int J Epidemiol Oxford Academic. 2011;40:602–10.

    Article  Google Scholar 

  50. Moore AG, Brown DA, Fairlie WD, Bauskin AR, Brown PK, Munier ML, et al. The transforming growth factor-ss superfamily cytokine macrophage inhibitory cytokine-1 is present in high concentrations in the serum of pregnant women. J Clin Endocrinol Metab. 2000;85:4781–8.

    CAS  PubMed  Google Scholar 

  51. Blankenberg S, Salomaa V, Makarova N, Ojeda F, Wild P, Lackner KJ, et al. Troponin I and cardiovascular risk prediction in the general population: the BiomarCaRE consortium. Eur Heart J. 2016;37:2428–37.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Skaaby T, Husemoen LLN, Borglykke A, Jørgensen T, Thuesen BH, Pisinger C, et al. Vitamin D status, liver enzymes, and incident liver disease and mortality: a general population study. Endocrine. 2014;47:213–20.

    Article  CAS  PubMed  Google Scholar 

  53. Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF, Feldman HI, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med. 2009;150:604–12.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Ambye L, Rasmussen S, Fenger M, Jørgensen T, Borch-Johnsen K, Madsbad S, et al. Studies of the Gly482Ser polymorphism of the peroxisome proliferator-activated receptor γ coactivator 1α (PGC-1α) gene in Danish subjects with the metabolic syndrome. Diabetes Res Clin Pract. 2005;67:175–9.

    Article  CAS  PubMed  Google Scholar 

  55. Tanaka T, Biancotto A, Moaddel R, Moore AZ, Gonzalez-Freire M, Aon MA, et al. Plasma proteomic signature of age in healthy humans. Aging Cell. 2018;17:e12799.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  56. Ho JE, Mahajan A, Chen M-H, 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Herpich C, Franz K, Ost M, Otten L, Coleman V, Klaus S, et al. Associations between serum GDF15 concentrations, muscle mass and strength show sex-specific differences in older hospital patients. Rejuvenation Res. 2020.

  58. Tavenier J, Rasmussen LJH, Andersen AL, Houlind MB, Langkilde A, Andersen O, et al. Association of GDF15 with inflammation and physical function during aging and recovery after acute hospitalization: a longitudinal study of older patients and age-matched controls. The Journals of Gerontology: Series A. 2021;glab010.

  59. Rothenbacher D, Dallmeier D, Christow H, Koenig W, Denkinger M, Klenk J. Association of growth differentiation factor 15 with other key biomarkers, functional parameters and mortality in community-dwelling older adults. Age Ageing. 2019;48:541–6.

    Article  PubMed  Google Scholar 

  60. Daniels LB. Clopton Paul, Laughlin Gail A., Maisel Alan S., Barrett-Connor Elizabeth. Growth-differentiation factor-15 is a robust, independent predictor of 11-year mortality risk in community-dwelling older adults. Circulation. 2011;123:2101–10.

    Article  PubMed  PubMed Central  Google Scholar 

  61. Wiklund FE, Bennet AM, Magnusson PKE, Eriksson UK, Lindmark F, Wu L, et al. Macrophage inhibitory cytokine-1 (MIC-1/GDF15): a new marker of all-cause mortality. Aging Cell. 2010;9:1057–64.

    Article  CAS  PubMed  Google Scholar 

  62. Breit SN, Carrero JJ, Tsai VW-W, Yagoutifam N, Luo W, Kuffner T, et al. Macrophage inhibitory cytokine-1 (MIC-1/GDF15) and mortality in end-stage renal disease. Nephrol Dial Transplant. 2012;27:70–5.

    Article  CAS  PubMed  Google Scholar 

  63. Emmerson PJ, Duffin KL, Chintharlapalli S, Wu X. GDF15 and growth control. Front Physiol. 2018;9:1712.

    Article  PubMed  PubMed Central  Google Scholar 

  64. Tsai VWW, Husaini Y, Sainsbury A, Brown DA, Breit SN. The MIC-1/GDF15-GFRAL pathway in energy homeostasis: implications for obesity, cachexia, and other associated diseases. Cell Metab. 2018;28:353–68.

    Article  CAS  PubMed  Google Scholar 

  65. Basisty N, Kale A, Jeon OH, Kuehnemann C, Payne T, Rao C, et al. A proteomic atlas of senescence-associated secretomes for aging biomarker development. PLoS Biol. 2020;18:e3000599.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  66. Schafer MJ, Zhang X, Kumar A, Atkinson EJ, Zhu Y, Jachim S, et al. The senescence-associated secretome as an indicator of age and medical risk. JCI Insight. 2020;5.

Download references

Code availability

Not applicable.

Author information

Authors and Affiliations

Authors

Contributions

JT: Conceptualization, data analysis, interpretation of the results, writing of the original draft, figure preparation, review, and editing; OA: Conceptualization, interpretation of the results, review, and editing. JON: Conceptualization, interpretation of the results, review, and editing. JP: Conceptualization, data analysis, interpretation of the results, figure preparation, review, and editing. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Juliette Tavenier.

Ethics declarations

Ethics approval

The study was approved by the Research Ethics Committee for Copenhagen County.

Consent to participate

All participants provided informed consent.

Consent for publication

All the authors have read and approved the manuscript.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

ESM 1

(PDF 75 kb)

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tavenier, J., Andersen, O., Nehlin, J.O. et al. Longitudinal course of GDF15 levels before acute hospitalization and death in the general population. GeroScience 43, 1835–1849 (2021). https://doi.org/10.1007/s11357-021-00359-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11357-021-00359-5

Keywords

Navigation