Journal of Exercise & Organ Cross Talk
Journal of Eexercise & Organ Cross Talk

Physical fitness and frailty index in developing biological age prediction model

Document Type : Original Article

Authors

Masoud Golpayegany 1
Saba Amiri 2
Abbas Haghparast 2
Maryam Nourshahi 1

1 Department of Biological Sciences in Sport, Faculty of Sports Sciences and Health, Shahid Beheshti University, Daneshjoo Blvd., Daneshjoo Sq., Velenjak, Tehran, Iran.

2 Neuroscience Research Center, Shahid Beheshti University of Medical Sciences, School of Medicine, Daneshjoo Blvd., Daneshjoo Sq., Velenjak, Tehran, Iran.

https://doi.org/10.22122/jeoct.2024.478382.1124
Abstract
The global increase in the older population has resulted in escalating healthcare costs and burdens on governments and families. Understanding biological age (BA) as distinct from chronological age (CA) holds significant potential in accurately assessing individuals' health status and susceptibility to diseases. During exercise, myokines like irisin and lactate are released from skeletal muscles, facilitating cross-talk with organs such as the brain and heart. This may improve physical fitness, reducing frailty and BA. This research aimed to develop a comprehensive BA prediction model integrating genetic and epigenetic factors. The study involved 59 healthy adults, comprising 31 males and 28 females, with average ages of 58.2 ± 7 years and 50.1 ± 8.5 years, respectively. Assessments of physical fitness and completion of the Frailty Index (FI34) questionnaire were conducted to capture genetic and epigenetic influences. Feature selection, principal component analysis (PCA), and multiple linear regression (MLR) were employed to tailor BA prediction models for each gender. We identified seven significant biomarkers for males, including FI34, percent of skeletal muscle mass (SM), handgrip strength (GS), flexibility via sit-and-reach test (SR), peak torque of quadriceps muscles (PTQ), cardiopulmonary fitness (VO2max), and basal metabolic rate (BMR). Conversely, females exhibited six key biomarkers: FI34, SM, GS, waist-to-hip ratio (WHR), peak torque of hamstring muscles (PTH), and percentage of body fat (PBF). We have successfully developed a comprehensive model for estimating BA by integrating key biomarkers representing epigenetic and genetic impacts. Estimating BA is crucial for precise health evaluations and disease risk assessments.

What is already known on this subject?

Several methods including epigenetic clock, measuring telomere length, frailty index and using physical fitness biomarkers have been proposed for estimating BA. Physical fitness biomarkers can measure epigenetic conditions and the ability and functionality of different parts of the body. Conversely, FI34's substantial genetic basis makes it suitable for analyzing healthy aging and longevity, but this index alone may not accurately estimate BA.

 

What this study adds?

This study incorporates both genetic and epigenetic factors, which could enhance BA model's comprehensiveness and applications.

Keywords

Healthy aging
Biological age
Lifestyle
Exercise physiology
Epigenetic factors

Subjects

Acknowledgements

None.

Funding

None of the researchers received financial support.

Compliance with ethical standards

Conflict of interest The authors declare that they have no conflict of interest.

Ethical approval All the research was approved by the ethical committee of the Iran University of Medical Sciences (Ethical code: IR.IUMS.REC.1400.197).

Informed consent Not applicable

Author contributions

Conceptualization: M.G., M.N.; Methodology: M.G., S.A.; Software: S.A.; Validation: M.N; Formal analysis: M.N; Investigation: M.N., A.H.; Resources: M.G., A.H.; Data curation: M.N., S.A.; Writing - original draft: M.G.; Writing - review & editing: M.N., S.A.; Visualization: M.N; Supervision: M.N; Project administration: M.N; Funding acquisition: M.N.

Ahlund, K., Ekerstad, N., Back, M., Karlson, B. W., & Oberg, B. (2019). Preserved physical fitness is associated with lower 1-year mortality in frail elderly patients with a severe comorbidity burden. Clin Interv Aging, 14, 577-586. doi: https://doi.org/10.2147/CIA.S198591
Bae, C. Y., Kang, Y. G., Piao, M. H., Cho, B., Cho, K. H., Park, Y. K., Yu, B. Y., Lee, S. W., Kim, M. J., Lee, S. H., Kim, Y. J., Kim, D. H., Kim, J. S., & Oh, J. E. (2013). Models for estimating the biological age of five organs using clinical biomarkers that are commonly measured in clinical practice settings. Maturitas, 75(3), 253-260. doi: https://doi.org/10.1016/j.maturitas.2013.04.008  
Brooks, G. A. (2021). Role of the Heart in Lactate Shuttling. Front Nutr, 8, 663560. doi:  https://doi.org/10.3389/fnut.2021.663560  
Calverley, T. A., Ogoh, S., Marley, C. J., Steggall, M., Marchi, N., Brassard, P., Lucas, S. J. E., Cotter, J. D., Roig, M., Ainslie, P. N., Wisløff, U., & Bailey, D. M. (2020). HIITing the brain with exercise: mechanisms, consequences and practical recommendations. J Physiol, 598(13), 2513-2530. doi: https://doi.org/10.1113/jp275021  
Carson, R. G. (2020). What accounts for the association between grip strength and mental functioning in aging people? Maturitas, 138, 80-81. doi: https://doi.org/10.1016/j.maturitas.2020.01.010
Chen, J., Zhao, M., Zhou, R., Ou, W., & Yao, P. (2023). How heavy is the medical expense burden among the older adults and what are the contributing factors? A literature review and problem-based analysis. Front Public Health, 11, 1165381. doi: https://doi.org/10.3389/fpubh.2023.1165381
Delezie, J., & Handschin, C. (2018). Endocrine Crosstalk Between Skeletal Muscle and the Brain. Front Neurol, 9, 698. doi: https://doi.org/10.3389/fneur.2018.00698
Fathi, I., Nourshahi, M., Haghparast, A., & Fallahhosseini, H. (2015). Effect of eight-week aerobic continuous and high intensity interval training on levels of SIRT3 in skeletal muscle tissue of Wistar rats Exercise Physiology & Physical Activity, 8(2), 1277-1289. doi:  https://joeppa.sbu.ac.ir/article_98771_36ed96396210890e86e3404f62a5b1be.pdf
Ferguson, B. (2014). ACSM’s Guidelines for Exercise Testing and Prescription. J Can Chiropr Assoc., 58(3), 328. (9th Ed. )
Forny-Germano, L., De Felice, F. G., & Vieira, M. (2018). The Role of Leptin and Adiponectin in Obesity-Associated Cognitive Decline and Alzheimer's Disease. Front Neurosci, 12, 1027. doi: https://doi.org/10.3389/fnins.2018.01027
Freitas, S. R., Cruz-Montecinos, C., Ratel, S., & Pinto, R. S. (2024). Powerpenia Should be Considered a Biomarker of Healthy Aging. Sports Med Open, 10(1), 27. doi: https://doi.org/10.1186/s40798-024-00689-6
Hashimoto, T., Tsukamoto, H., Ando, S., & Ogoh, S. (2021). Effect of Exercise on Brain Health: The Potential Role of Lactate as a Myokine. Metabolites, 11(12). doi: https://doi.org/10.3390/metabo11120813  
He, W., Goodkind, D., Kowal, P., Almasarweh, I., Islam, M. M., Giang, L., Lee, S., Teerawichitchainan, B., & Tey, N. (2022). Asia Aging: Demographic, Economic, and Health Transitions.
Höög, S., & Andersson, E. P. (2021). Sex and Age-Group Differences in Strength, Jump, Speed, Flexibility, and Endurance Performances of Swedish Elite Gymnasts Competing in TeamGym. Front Sports Act Living, 3, 653503. doi: https://doi.org/10.3389/fspor.2021.653503
Husted, K. L. S., Brink-Kjær, A., Fogelstrøm, M., Hulst, P., Bleibach, A., Henneberg, K., Sørensen, H. B. D., Dela, F., Jacobsen, J. C. B., & Helge, J. W. (2022). A Model for Estimating Biological Age From Physiological Biomarkers of Healthy Aging: Cross-sectional Study. JMIR Aging, 5(2), e35696. doi: https://doi.org/10.2196/35696
Inyushkin, A. N., Poletaev, V. S., Inyushkina, E. M., Kalberdin, I. S., & Inyushkin, A. A. (2023). Irisin/BDNF signaling in the muscle-brain axis and circadian system: A review. J Biomed Res, 38(1), 1-16. doi: https://doi.org/10.7555/jbr.37.20230133
Jee, H., Jeon, B. H., Kim, Y. H., Kim, H. K., Choe, J., Park, J., & Jin, Y. (2012). Development and application of biological age prediction models with physical fitness and physiological components in Korean adults. Gerontology, 58(4), 344-353. doi: https://doi.org/10.1159/000335738
 
Jia, L., Zhang, W., & Chen, X. (2017). Common methods of biological age estimation. Clin Interv Aging, 12, 759-772. doi: https://doi.org/10.2147/cia.S134921
Jylhävä, J., Pedersen, N. L., & Hägg, S. (2017). Biological Age Predictors. EBioMedicine, 21, 29-36. doi: https://doi.org/10.1016/j.ebiom.2017.03.046
Khavinson, V., Kuznik, B. I., Tarnovskaya, S. I., & Lin'kova, N. S. (2016). Short Peptides and Telomere Length Regulator Hormone Irisin. Bull Exp Biol Med, 160(3), 347-349. doi: https://doi.org/10.1007/s10517-016-3167-y
Kim, S., & Jazwinski, S. M. (2015). Quantitative measures of healthy aging and biological age. Healthy Aging Res, 4. doi: https://doi.org/10.12715/har.2015.4.26
Kim, S., Welsh, D. A., Cherry, K. E., Myers, L., & Jazwinski, S. M. (2013). Association of healthy aging with parental longevity. Age (Dordr), 35(5), 1975-1982. doi: https://doi.org/10.1007/s11357-012-9472-0
Kimura, M., Mizuta, C., Yamada, Y., Okayama, Y., & Nakamura, E. (2012). Constructing an index of physical fitness age for Japanese elderly based on 7-year longitudinal data: sex differences in estimated physical fitness age. Age (Dordr), 34(1), 203-214. doi: https://doi.org/10.1007/s11357-011-9225-5
Kitazoe, Y., Kishino, H., Tanisawa, K., Udaka, K., & Tanaka, M. (2019). Renormalized basal metabolic rate describes the human aging process and longevity. Aging Cell, 18(4), e12968. doi: https://doi.org/10.1111/acel.12968
Kleiven, S. (2020). Hip fracture risk functions for elderly men and women in sideways falls. J Biomech, 105, 109771. doi: https://doi.org/10.1016/j.jbiomech.2020.109771
Kokkinos, P., Faselis, C., Samuel, I. B. H., Pittaras, A., Doumas, M., Murphy, R., Heimall, M. S., Sui, X., Zhang, J., & Myers, J. (2022). Cardiorespiratory Fitness and Mortality Risk Across the Spectra of Age, Race, and Sex. J Am Coll Cardiol, 80(6), 598-609. doi: https://doi.org/10.1016/j.jacc.2022.05.031
Loh, J., Amanullah, M. R., See, C. K., Tang, H. C., Gunasegaran, K., Hamid, N., Lau, J., Lee, C. Y., Ewe, S. H., Ding, Z. P., & Sahlén, A. (2021). Predicting premature termination of exercise during Bruce protocol stress echocardiography. Echocardiography, 38(9), 1612-1617. doi:  https://doi.org/10.1111/echo.15186
Maffei, V. J., Kim, S., Blanchard, E. t., Luo, M., Jazwinski, S. M., Taylor, C. M., & Welsh, D. A. (2017). Biological Aging and the Human Gut Microbiota. J Gerontol A Biol Sci Med Sci, 72(11), 1474-1482. doi: doi: https://doi.org/10.1093/gerona/glx042
McLester, C. N., Nickerson, B. S., Kliszczewicz, B. M., & McLester, J. R. (2020). Reliability and Agreement of Various InBody Body Composition Analyzers as Compared to Dual-Energy X-Ray Absorptiometry in Healthy Men and Women. J Clin Densitom, 23(3), 443-450. doi: https://doi.org/10.1016/j.jocd.2018.10.008
Meysami, S., Raji, C. A., Glatt, R. M., Popa, E. S., Ganapathi, A. S., Bookheimer, T., Slyapich, C. B., Pierce, K. P., Richards, C. J., Lampa, G., Gill, J. M., Rapozo, M. K., Hodes, J. F., Tongson, Y. M., Wong, C. L., Kim, M., Porter, V. R., Kaiser, S. A., Panos, S. E., . . . Merrill, D. A. (2023). Handgrip Strength Is Related to Hippocampal and Lobar Brain Volumes in a Cohort of Cognitively Impaired Older Adults with Confirmed Amyloid Burden. J Alzheimers Dis, 91(3), 999-1006. doi: https://doi.org/10.3233/jad-220886
Mitnitski, A. B., Mogilner, A. J., & Rockwood, K. (2001). Accumulation of deficits as a proxy measure of aging. ScientificWorldJournal, 1, 323-336. doi: https://doi.org/10.1100/tsw.2001.58
Nascimento, C. M., Ingles, M., Salvador-Pascual, A., Cominetti, M. R., Gomez-Cabrera, M. C., & Viña, J. (2019). Sarcopenia, frailty and their prevention by exercise. Free Radic Biol Med, 132, 42-49. doi: https://doi.org/10.1016/j.freeradbiomed.2018.08.035
Nikooyeh, B., Shariatzadeh, N., Kalayi, A., Zahedirad, M., & Neyestani, T. R. (2022). Development of new predictive equations for basal metabolic rate in Iranian healthy adults: negligible effect of sex. Int J Vitam Nutr Res, 92(5-6), 311-320. doi: https://doi.org/10.1024/0300-9831/a000669
Nokariya, S., Kotani, T., Sakuma, T., Iijima, Y., Okumura, T., Katogi, T., Okuwaki, S., Miyagi, M., Inoue, G., Akazawa, T., Shiga, Y., Minami, S., Ohtori, S., & Takaso, M. (2023). Trunk flexibility using a sit-and-reach test after surgery for adolescent idiopathic scoliosis. Spine Deform, 11(2), 297-303. doi: https://doi.org/10.1007/s43390-022-00608-3
Park, J., Kim, J., & Mikami, T. (2021). Exercise-Induced Lactate Release Mediates Mitochondrial Biogenesis in the Hippocampus of Mice via Monocarboxylate Transporters. Front Physiol, 12, 736905. doi: https://doi.org/10.3389/fphys.2021.736905
Qu, Q., Guo, Q., Sun, J., Lu, X., Cheang, I., Zhu, X., Yao, W., Li, X., Zhang, H., Zhou, Y., Liao, S., & Gao, R. (2023). Low lean mass with obesity in older adults with hypertension: prevalence and association with mortality rate. BMC Geriatr, 23(1), 619. doi: https://doi.org/10.1186/s12877-023-04326-x
Rana, K. S., Arif, M., Hill, E. J., Aldred, S., Nagel, D. A., Nevill, A., Randeva, H. S., Bailey, C. J., Bellary, S., & Brown, J. E. (2014). Plasma irisin levels predict telomere length in healthy adults. Age (Dordr), 36(2), 995-1001. doi: https://doi.org/10.1007/s11357-014-9620-9
Rogers, R., Sánchez-Querubín, N., & Kil, A. (2015). Issue Mapping for an Ageing Europe. doi:  https://doi.org/10.1515/9789048524457
Rudnicka, E., Napierała, P., Podfigurna, A., Męczekalski, B., Smolarczyk, R., & Grymowicz, M. (2020). The World Health Organization (WHO) approach to healthy ageing. Maturitas, 139, 6-11. doi: https://doi.org/10.1016/j.maturitas.2020.05.018
Siddiqi, F. A., & Masood, T. (2018). Training on Biodex balance system improves balance and mobility in the elderly. J Pak Med Assoc, 68(11), 1655-1659.
Søgaard, D., Lund, M. T., Scheuer, C. M., Dehlbaek, M. S., Dideriksen, S. G., Abildskov, C. V., Christensen, K. K., Dohlmann, T. L., Larsen, S., Vigelsø, A. H., Dela, F., & Helge, J. W. (2018). High-intensity interval training improves insulin sensitivity in older individuals. Acta Physiol (Oxf), 222(4), e13009. doi: https://doi.org/10.1111/apha.13009
Tuominen, J., Leppänen, M., Jarske, H., Pasanen, K., Vasankari, T., & Parkkari, J. (2023). Test-Retest Reliability of Isokinetic Ankle, Knee and Hip Strength in Physically Active Adults Using Biodex System 4 Pro. Methods Protoc, 6(2). doi: https://doi.org/10.3390/mps6020026
U.S.CensusBureau. (2023). National Population Projections Tables: Main Series.
Wilke, J., Macchi, V., De Caro, R., & Stecco, C. (2019). Fascia thickness, aging and flexibility: is there an association? J Anat, 234(1), 43-49. doi:  https://doi.org/10.1111/joa.12902
Wu, J., Boström, P., Sparks, L. M., Ye, L., Choi, J. H., Giang, A. H., Khandekar, M., Virtanen, K. A., Nuutila, P., Schaart, G., Huang, K., Tu, H., van Marken Lichtenbelt, W. D., Hoeks, J., Enerbäck, S., Schrauwen, P., & Spiegelman, B. M. (2012). Beige adipocytes are a distinct type of thermogenic fat cell in mouse and human. Cell, 150(2), 366-376. doi: https://doi.org/10.1016/j.cell.2012.05.016
Zammit, A. R., Robitaille, A., Piccinin, A. M., Muniz-Terrera, G., & Hofer, S. M. (2019). Associations Between Aging-Related Changes in Grip Strength and Cognitive Function in Older Adults: A Systematic Review. J Gerontol A Biol Sci Med Sci, 74(4), 519-527. doi: https://doi.org/10.1093/gerona/gly046
Zhang, W., Li, Z., Niu, Y., Zhe, F., Liu, W., Fu, S., Wang, B., Jin, X., Zhang, J., Sun, D., Li, H., Luo, Q., Zhao, Y., Chen, X., & Chen, Y. (2024). The biological age model for evaluating the degree of aging in centenarians. Arch Gerontol Geriatr, 117, 105175. doi: https://doi.org/10.1016/j.archger.2023.105175
Zhou, L., Chen, S. Y., Han, H. J., & Sun, J. Q. (2021). Lactate augments intramuscular triglyceride accumulation and mitochondrial biogenesis in rats. J Biol Regul Homeost Agents, 35(1), 105-115. doi: https://doi.org/10.23812/20-624-a
Journal of Exercise & Organ Cross Talk
Volume 4, Issue 2
Spring 2024
Pages 74-85

  • Receive Date 29 March 2024
  • Revise Date 03 June 2024
  • Accept Date 05 June 2024

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