Skip to main content

Advertisement

SpringerLink
Log in

Association between aging-related biomarkers and longitudinal trajectories of intrinsic capacity in older adults

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

Abstract

Intrinsic capacity (IC), the composite of physical and mental capacities, declines with age at different rates and patterns between individuals. We aimed to investigate the association between longitudinal IC trajectories and plasma biomarkers of two hallmarks of aging—chronic inflammation and mitochondrial dysfunction—in older adults. From the Multidomain Alzheimer Preventive Trial (MAPT), we included 1271 community-dwelling older people (mean [SD] age = 76.0 [4.3] years) with IC data over four years. Group-based multi-trajectory modeling was performed to identify clusters of the participants with similar longitudinal patterns across four IC domains: cognition, locomotion, psychology, and vitality. Five IC multi-trajectory groups were determined: low in all domains (8.4%), low locomotion (24.6%), low psychological domain (16.7%), robust (i.e., high in all domains except vitality; 28.3%), and robust with high vitality (22.0%). Compared to the best trajectory group (i.e., robust with high vitality), elevated levels of plasma interleukin-6 (IL-6), tumor necrosis factor receptor-1 (TNFR-1), and growth differentiation factor-15 (GDF-15) were associated with a higher risk of belonging to the “low in all domains” group (IL-6: relative risk ratio (RRR) [95% CI] = 1.42 [1.07 – 1.88]; TNFR-1: RRR = 1.46 [1.09 – 1.96]; GDF-15: RRR = 1.99 [1.45 – 2.73]). Higher IL-6 and GDF-15 also increased the risk of being in the “low locomotion” group. GDF-15 outperformed other biomarkers by showing the strongest associations with IC trajectory groups. Our findings found that plasma biomarkers reflecting inflammation and mitochondrial impairment distinguished older people with multi-impaired IC trajectories from those with high-stable IC.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

  1. Beard JR, Officer A, de Carvalho IA, et al. The world report on ageing and health: a policy framework for healthy ageing. Lancet. 2016;387(10033):2145–54. https://doi.org/10.1016/S0140-6736(15)00516-4.

    Article  PubMed  Google Scholar 

  2. Cesari M, Araujo de Carvalho I, Amuthavalli Thiyagarajan J, et al. Evidence for the domains supporting the construct of intrinsic capacity. J Gerontol Ser A Biol Sci Med Sci. 2018;73(12):1653–60. https://doi.org/10.1093/gerona/gly011.

    Article  Google Scholar 

  3. López-Ortiz S, Lista S, Peñín-Grandes S, et al. Defining and assessing intrinsic capacity in older people: A systematic review and a proposed scoring system. Ageing Res Rev. 2022;79:101640. https://doi.org/10.1016/J.ARR.2022.101640.

    Article  PubMed  Google Scholar 

  4. Tay L, Tay EL, Mah SM, Latib A, Koh C, Ng YS. Association of intrinsic capacity with frailty, physical fitness and adverse health outcomes in community-dwelling older adults. J Frailty Aging. 2022:1–9. https://doi.org/10.14283/jfa.2022.28.

  5. Stolz E, Mayerl H, Freidl W, Roller-Wirnsberger R, Gill TM. Intrinsic capacity predicts negative health outcomes in older adults. Lipsitz LA, ed. J Gerontol - Ser A Biol Sci Med Sci. 2022;77(1):101–5. https://doi.org/10.1093/gerona/glab279.

    Article  Google Scholar 

  6. Campbell CL, Cadar D, McMunn A, Zaninotto P. Operationalization of intrinsic capacity in older people and its association with subsequent disability, hospital admission and mortality: Results from the English longitudinal study of ageing. Magaziner J, ed. J Gerontol Ser A. 2023;78(4):698–703. https://doi.org/10.1093/gerona/glac250.

    Article  Google Scholar 

  7. Belloni G, Cesari M. Frailty and intrinsic capacity: Two distinct but related constructs. Front Med. 2019:6. https://doi.org/10.3389/fmed.2019.00133.

  8. Beard JR, Chen M. Intrinsic capacity as a composite outcome measure: Opportunities and challenges. J Nutr Heal Aging. 2023;27(6):398–400. https://doi.org/10.1007/s12603-023-1923-z.

    Article  CAS  Google Scholar 

  9. World Health Organization. Integrated care for older people (ICOPE). Guidance for person-centred assessment and pathways in primary care. Geneva, Switzerland: World Health Organization. https://www.who.int/publications/i/item/WHO-FWC-ALC-19.1. Published 2019. Accessed August 19, 2022.

  10. Bevilacqua R, Soraci L, Stara V, et al. A systematic review of multidomain and lifestyle interventions to support the intrinsic capacity of the older population. Front Med. 2022;9:2115. https://doi.org/10.3389/fmed.2022.929261.

    Article  Google Scholar 

  11. Meng L-C, Huang S-T, Peng L-N, Chen L-K, Hsiao F-Y. Biological features of the outcome-based intrinsic capacity composite scores from a population-based cohort study: Pas de deux of biological and functional aging. Front Med. 2022;9:452. https://doi.org/10.3389/fmed.2022.851882.

    Article  Google Scholar 

  12. Ma L, Liu P, Zhang Y, Sha G, Zhang L, Li Y. High serum tumor necrosis factor receptor 1 levels are related to risk of low intrinsic capacity in elderly adults. J Nutr Heal Aging. 2021;25(4):416–8. https://doi.org/10.1007/s12603-020-1533-y.

    Article  CAS  Google Scholar 

  13. Ferrucci L, Fabbri E. Inflammageing: Chronic inflammation in ageing, cardiovascular disease, and frailty. Nat Rev Cardiol. 2018;15(9):505–22. https://doi.org/10.1038/s41569-018-0064-2.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Ferrucci L, Zampino M. A mitochondrial root to accelerated ageing and frailty. Nat Rev Endocrinol. 2020;16(3):133–4. https://doi.org/10.1038/s41574-020-0319-y.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Aragoni da Silva J, Rolland Y, Martinez LO, de Souto Barreto P. Mitochondrial dysfunction and intrinsic capacity: Insights from a narrative review. Le Couteur D, The Journals Gerontology Series A. 2023;78(5):735-742. doi:https://doi.org/10.1093/gerona/glac227

    Chapter  Google Scholar 

  16. Andrieu S, Guyonnet S, Coley N, et al. Effect of long-term omega 3 polyunsaturated fatty acid supplementation with or without multidomain intervention on cognitive function in elderly adults with memory complaints (MAPT): A randomised, placebo-controlled trial. Lancet Neurol. 2017;16(5):377–89. https://doi.org/10.1016/S1474-4422(17)30040-6.

    Article  CAS  PubMed  Google Scholar 

  17. López-Otín C, Blasco MA, Partridge L, Serrano M, Kroemer G. Hallmarks of aging: An expanding universe. Cell. 2023;186(2):243–78. https://doi.org/10.1016/j.cell.2022.11.001.

    Article  CAS  PubMed  Google Scholar 

  18. Singh T, Newman AB. Inflammatory markers in population studies of aging. Ageing Res Rev. 2011;10(3):319–29. https://doi.org/10.1016/j.arr.2010.11.002.

    Article  CAS  PubMed  Google Scholar 

  19. Sokolova A, Hill MD, Rahimi F, Warden LA, Halliday GM, Shepherd CE. Monocyte chemoattractant protein-1 plays a dominant role in the chronic inflammation observed in Alzheimer’s disease. Brain Pathol. 2009;19(3):392–8. https://doi.org/10.1111/j.1750-3639.2008.00188.x.

    Article  CAS  PubMed  Google Scholar 

  20. Borodkina AV, Deryabin PI, Giukova AA, Nikolsky NN. “Social life” of senescent cells: What is SASP and why study it? Acta Naturae. 2018;10(1):4–14. https://doi.org/10.32607/20758251-2018-10-1-4-14.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Schafer MJ, Zhang X, Kumar A, et al. The senescence-associated secretome as an indicator of age and medical risk. JCI Insight. 2020;5(12) https://doi.org/10.1172/jci.insight.133668.

  22. Jin HJ, Lee HJ, Heo J, et al. Senescence-associated MCP-1 secretion is dependent on a decline in BMI1 in human mesenchymal stromal cells. Antioxid Redox Signal. 2016;24(9):471–85. https://doi.org/10.1089/ars.2015.6359.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Conte M, Giuliani C, Chiariello A, Iannuzzi V, Franceschi C, Salvioli S. GDF15, an emerging key player in human aging. Ageing Res Rev. 2022;75:101569. https://doi.org/10.1016/j.arr.2022.101569.

    Article  CAS  PubMed  Google Scholar 

  24. Wang D, Day EA, Townsend LK, Djordjevic D, Jørgensen SB, Steinberg GR. GDF15: Emerging biology and therapeutic applications for obesity and cardiometabolic disease. Nat Rev Endocrinol. 2021;17(10):592–607. https://doi.org/10.1038/s41574-021-00529-7.

    Article  CAS  PubMed  Google Scholar 

  25. Gore E, Duparc T, Genoux A, Perret B, Najib S, Martinez LO. The multifaceted ATPase inhibitory factor 1 (IF1) in energy metabolism reprogramming and mitochondrial dysfunction: A new player in age-associated disorders? Antioxid Redox Signal. 2022;37(4-6):370–93. https://doi.org/10.1089/ars.2021.0137.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”: A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12(3):189–98. https://doi.org/10.1016/0022-3956(75)90026-6.

    Article  CAS  PubMed  Google Scholar 

  27. Guralnik JM, Simonsick EM, Ferrucci L, et al. A short physical performance battery assessing lower extremity function: Association with self-reported disability and prediction of mortality and nursing home admission. J Gerontol. 1994;49(2):M85–94. https://doi.org/10.1093/geronj/49.2.M85.

    Article  CAS  PubMed  Google Scholar 

  28. Yesavage JA, Sheikh JI. Geriatric Depression Scale (GDS): Recent evidence and development of a shorter version. Clin Gerontol. 1986;5(1-2):165–73. https://doi.org/10.1300/J018v05n01_09.

    Article  Google Scholar 

  29. Roberts HC, Denison HJ, Martin HJ, et al. A review of the measurement of grip strength in clinical and epidemiological studies: Towards a standardised approach. Age Ageing. 2011;40(4):423–9. https://doi.org/10.1093/ageing/afr051.

    Article  PubMed  Google Scholar 

  30. Nagin DS, Jones BL, Passos VL, Tremblay RE. Group-based multi-trajectory modeling. Stat Methods Med Res. 2018;27(7):2015–23. https://doi.org/10.1177/0962280216673085.

    Article  PubMed  Google Scholar 

  31. Giudici KV, de Souto BP, Beard J, et al. Effect of long-term omega-3 supplementation and a lifestyle multidomain intervention on intrinsic capacity among community-dwelling older adults: Secondary analysis of a randomized, placebo-controlled trial (MAPT study). Maturitas. 2020;141:39–45. https://doi.org/10.1016/j.maturitas.2020.06.012.

    Article  CAS  PubMed  Google Scholar 

  32. Locquet M, Sanchez-Rodriguez D, Bruyère O, et al. Intrinsic capacity defined using four domains and mortality risk: A 5-year follow-up of the SarcoPhAge cohort. J Nutr Heal Aging. 2022;26(1):23–9. https://doi.org/10.1007/s12603-021-1702-7.

    Article  CAS  Google Scholar 

  33. Nagin DS, Odgers CL. Group-based trajectory modeling in clinical research. Annu Rev Clin Psychol. 2010;6:109–38. https://doi.org/10.1146/annurev.clinpsy.121208.131413.

    Article  PubMed  Google Scholar 

  34. Tavenier J, Andersen O, Nehlin JO, Petersen J. Longitudinal course of GDF15 levels before acute hospitalization and death in the general population. GeroScience. 2021;43(4):1835–49. https://doi.org/10.1007/s11357-021-00359-5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Bautmans I, Knoop V, Amuthavalli Thiyagarajan J, et al. WHO working definition of vitality capacity for healthy longevity monitoring. Lancet Heal Longev. 2022;3(11):e789–96. https://doi.org/10.1016/S2666-7568(22)00200-8.

    Article  Google Scholar 

  36. Ferrucci L, Penninx BWJH, Volpato S, et al. Change in muscle strength explains accelerated decline of physical function in older women with high interleukin-6 serum levels. J Am Geriatr Soc. 2002;50(12):1947–54. https://doi.org/10.1046/j.1532-5415.2002.50605.x.

    Article  PubMed  Google Scholar 

  37. Kistner TM, Pedersen BK, Lieberman DE. Interleukin 6 as an energy allocator in muscle tissue. Nat Metab. 2022;4(2):170–9. https://doi.org/10.1038/s42255-022-00538-4.

    Article  CAS  PubMed  Google Scholar 

  38. Gross AL, Walker KA, Moghekar AR, et al. Plasma markers of inflammation linked to clinical progression and decline during preclinical AD. Front Aging Neurosci. 2019:11. https://doi.org/10.3389/fnagi.2019.00229.

  39. Buchhave P, Zetterberg H, Blennow K, Minthon L, Janciauskiene S, Hansson O. Soluble TNF receptors are associated with Aβ metabolism and conversion to dementia in subjects with mild cognitive impairment. Neurobiol Aging. 2010;31(11):1877–84. https://doi.org/10.1016/J.NEUROBIOLAGING.2008.10.012.

    Article  CAS  PubMed  Google Scholar 

  40. Conte M, Ostan R, Fabbri C, et al. Human aging and longevity are characterized by high levels of mitokines. J Gerontol - Ser A Biol Sci Med Sci. 2019;74(5):600–7. https://doi.org/10.1093/gerona/gly153.

    Article  CAS  Google Scholar 

  41. Stowe RP, Peek MK, Cutchin MP, Goodwin JS. Plasma cytokine levels in a population-based study: Relation to age and ethnicity. Journals Gerontol - Ser A Biol Sci. Med Sci. 2010;65A:429. https://doi.org/10.1093/gerona/glp198.

    Article  CAS  Google Scholar 

  42. Maggio M, Guralnik JM, Longo DL, Ferrucci L. Interleukin-6 in aging and chronic disease: A magnificent pathway. J Gerontol - Ser A Biol Sci Med Sci. 2006;61(6):575–84. https://doi.org/10.1093/gerona/61.6.575.

    Article  Google Scholar 

  43. Di R, 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(4):541–6. https://doi.org/10.1093/ageing/afz022.

    Article  Google Scholar 

  44. Peterson MJ, Thompson DK, Pieper CF, et al. A novel analytic technique to measure associations between circulating biomarkers and physical performance across the adult life span. J Gerontol Ser A Biol Sci Med Sci. 2016;71(2):196–202. https://doi.org/10.1093/gerona/glv007.

    Article  CAS  Google Scholar 

  45. Lee WJ, Liao YC, Wang YF, Lin IF, Wang SJ, Fuh JL. Plasma MCP-1 and cognitive decline in patients with Alzheimer’s disease and mild cognitive impairment: A two-year follow-up study. Sci Rep. 2018;8(1) https://doi.org/10.1038/s41598-018-19807-y.

  46. Da Silva JP, Wargny M, Raffin J, et al. Plasma level of ATPase inhibitory factor 1 (IF1) is associated with type 2 diabetes risk in humans: A prospective cohort study. Diabetes Metab. 2022;49(1):101391. https://doi.org/10.1016/j.diabet.2022.101391.

    Article  CAS  Google Scholar 

Download references

Funding

The present work was performed in the context of the Inspire Program, a research platform supported by grants from the Region Occitanie/Pyrénées-Méditerranée (Reference number: 1901175) and the European Regional Development Fund (ERDF) (Project number: MP0022856). This study received funds from Alzheimer Prevention in Occitania and Catalonia (APOC Chair of Excellence - Inspire Program).

WHL has been partially supported through the grant EUR CARe N°ANR-18-EURE-0003 in the framework of the Programme des Investissements d'Avenir.

The MAPT study was supported by grants from the Gérontopôle of Toulouse, the French Ministry of Health (PHRC 2008, 2009), Pierre Fabre Research Institute (manufacturer of the omega-3 supplement), ExonHit Therapeutics SA, and Avid Radiopharmaceuticals Inc. The promotion of this study was supported by the University Hospital Center of Toulouse. The data sharing activity was supported by the Association Monegasque pour la Recherche sur la maladie d’Alzheimer (AMPA) and the INSERM-University of Toulouse III UMR 1295 Unit.

Author information

Authors and Affiliations

  1. Gerontopole of Toulouse, Institute of Ageing, Toulouse University Hospital (CHU Toulouse), 31000, Toulouse, France

    Wan-Hsuan Lu, Sophie Guyonnet, Bruno Vellas & Philipe de Souto Barreto

  2. Maintain Aging Research team, Centre d’Epidémiologie et de Recherche en santé des POPulations (CERPOP), Inserm, Université Paul Sabatier, Toulouse, France

    Wan-Hsuan Lu, Sophie Guyonnet, Bruno Vellas & Philipe de Souto Barreto

  3. Institut National de la Santé et de la Recherche Médicale (INSERM), UMR 1297, Institute of Metabolic and Cardiovascular Diseases, Toulouse, France

    Laurent O. Martinez, Alexandre Lucas & Angelo Parini

Authors
  1. Wan-Hsuan Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sophie Guyonnet
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Laurent O. Martinez
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Alexandre Lucas
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Angelo Parini
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Bruno Vellas
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Philipe de Souto Barreto
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

WHL designed and conceptualized the research, performed the analyses, interpreted the data, and drafted the manuscript. SG interpreted the data and revised the draft critically for important intellectual content. LOM managed data of plasma IF1, interpreted the data, and revised the draft critically for important intellectual content. AL and AP managed data of plasma IL-6, TNFR-1, MCP-1, and GDF-15; interpreted the data; and revised the draft critically for important intellectual content. BV conceived the MAPT study, interpreted the data, and revised the draft critically for important intellectual content. PdSB designed and conceptualized the research, interpreted the data, and revised the draft critically for important intellectual content. All authors have read and agreed with the final version to be submitted.

Corresponding author

Correspondence to Wan-Hsuan Lu.

Ethics declarations

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

(DOCX 375 kb)

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lu, WH., Guyonnet, S., Martinez, L.O. et al. Association between aging-related biomarkers and longitudinal trajectories of intrinsic capacity in older adults. GeroScience 45, 3409–3418 (2023). https://doi.org/10.1007/s11357-023-00906-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11357-023-00906-2

Keywords

Search

Navigation