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Sex-specific muscle and metabolic biomarkers associated with gait speed and cognitive transitions in older adults: a 9-year follow-up

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Abstract

Physical frailty and cognitive frailty share biological mechanisms, but sex-specific biomarkers associated with transitions in gait speed and cognition during ageing are poorly understood.Gait speed, cognition (3MSE), body composition (DXA) and serological biomarkers were assessed annually over 9 years in 216 males (72.7 + 8.07 years) and 384 females (71.1 + 8.44 years). In females, maintaining normal gait speed was associated with lower percent body fat (IRR 0.793, p = 0.001, 95%CI 0.691–0.910) and lower lactate dehydrogenase (LDH) (IRR 0.623, p = 0.00, 95%CI 0.514–0.752), and in males, the association was with higher cholesterol (IRR 1.394, p = 0.001, 95%CI 1.154–1.684). Abnormal to normal gait speed transitions were associated with higher insulin in females (IRR 1.325, p = 0.022, 95%CI 1.041–1.685) and lower creatinine in males (IRR 0.520, p = 0.01, 95%CI 0.310–0.870). Normal to slow gait speed transitions in males were associated with IGF-1 (IRR 1.74, p = 0.022, 95%CI 1.08–2.79) and leptin in females (IRR 1.39, p = 0.043, 95%CI 1.01–1.91.) Maintaining normal cognition was associated with lower LDH in females (IRR 0.276, p = 0.013, 95%CI 0.099–0.765) and higher appendicular skeletal muscle mass in males (IRR 1.52, p = 0.02, 95%CI 1.076–2.135). Improved cognition was associated with higher leptin (IRR 7.5, p = 0.03, 95%CI 1.282–44.34) and lower triglyceride (IRR 0.299, p = 0.017, 95%CI 0.110–0.809) in males. Education was protective against cognitive decline in females (IRR 0.84, p = 0.037, 0.732–0.982). Sex-specific biomarkers of muscle (LDH, Creatinine, IGF-1, APSM) and metabolism (%fat, insulin,cholesterol, leptin, tryglycerides) were associated with gait speed and cognitive transitions. These data suggest that modifiable biomarkers of muscle and metabolism could be targeted for interventions.

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References

  • Barzilai N, Ferrucci L (2012) Insulin resistance and aging: a cause or a protective response? J Gerontol A Biol Sci Med Sci 67:1329–1331

    Article  Google Scholar 

  • Cardoso AL, Fernandes A, Aguilar-Pimentel JA, de Angelis MH, Guedes JR, Brito MA, Ortolano S, Pani G, Athanasopoulou S, Gonos ES, Schosserer M, Grillari J, Peterson P, Tuna BG, Dogan S, Meyer A, van Os R, Trendelenburg AU (2018) Towards frailty biomarkers: candidates from genes and pathways regulated in aging and age-related diseases. Ageing Res Rev 47:214–277

    Article  CAS  Google Scholar 

  • Diehr PH, Thielke SM, Newman AB, Hirsch C, Tracy R (2013) Decline in health for older adults: five-year change in 13 key measures of standardized health. J Gerontol A Biol Sci Med Sci 68:1059–1067

    Article  Google Scholar 

  • Doi T, Shimada H, Makizako H, Tsutsumimoto K, Hotta R, Nakakubo S et al (2015) Association of insulin-like growth factor-1 with mild cognitive impairment and slow gait speed. Neurobiol Aging:942–947

  • Doi T, Shimada H, Makizako H, Tsutsumimoto K, Hotta R, Nakakubo S et al (2016) Insulin-like growth factor-1 related to disability among older adults. J Gerontol A Biol Sci Med Sci:797–802

  • Farr SA, Banks WA, Morley JE (2006) Effects of leptin on memory processing. Peptides. 27:1420–1425

    Article  CAS  Google Scholar 

  • Farr SA, Yamada KA, Butterfield DA, Abdul HM, Xu L, Miller NE et al (2008) Obesity and hypertriglyceridemia produce cognitive impairment. Endocrinology. 149:2628–2636

    Article  CAS  Google Scholar 

  • García-Esquinas E, José García-García F, León-Muñoz LM, Carnicero JA, Guallar-Castillón P, Gonzalez-Colaço HM et al (2015) Obesity, fat distribution, and risk of frailty in two population-based cohorts of older adults in Spain

  • Garry PJ, Wayne SJ, Vellas B (2007) The New Mexico aging process study (1979-2003) a longitudinal study of nutrition, health and aging. J Nutr Health Aging 11:125–130

    CAS  PubMed  Google Scholar 

  • Harris RB (2014) Direct and indirect effects of leptin on adipocyte metabolism

    Book  Google Scholar 

  • Heiland EG et al (2017) Cardiovascular risk burden and future risk of walking speed limitation in older adult. J Am Geriatr Soc:2418–2424

  • Holden KF, Lindquist K, Tylavsky FA, ., Rosano C, Harris TB, Yaffe K. Serum leptin level and cognition in the elderly: findings from the health ABC study. Neurobiol Aging 2009;30:1483–1489

    Article  CAS  Google Scholar 

  • Jequier E (2002) Leptin signaling, adiposity, and energy balance

    Book  Google Scholar 

  • Kane AE, Sinclair DA (2019) Frailty biomarkers in humans and rodents: current approaches and future advances. Mech Ageing Dev:117–128

  • Kojimaa G, Taniguchi Y, Iliffe S, Jivraj S, Walters K (2019) Transitions between frailty states among comminuty-dwelling older people: a systematic review and meta-analysis. Ageing Res Rev:81–88

  • Kontari P, Smith KJ (2019) Risk of dementia associated with cardiometabolic abnormalities and depressive symptoms: a longitudinal cohort study using the English longitudinal study of ageing. Int J Geriatr Psychiatry 34:289–298

    Article  Google Scholar 

  • Lana A, Struijk E, Guallar-Castillón P, Martín-Moreno JM, Rodríguez Artalejo F, Lopez-Garcia E (2016) Leptin concentration and risk of impaired physical function in older adults: the Seniors-ENRICA cohort. Age Ageing 45(6):819–826

    Article  Google Scholar 

  • Lana A, Valdés-Bécares A, Buño A, Rodríguez-Artalejo F, Lopez-Garcia E (2017) Serum leptin concentration is associated with incident frailty in older adults. Aging Dis 8(2):240–249

    Article  Google Scholar 

  • Meng Y, Wu H, Yang Y, Du H, Xia Y, Guo X et al (2015) Relationship of anabolic and catabolic biomarkers with muscle strength and physical performance in older adults: a population-based cross-sectional study

    Google Scholar 

  • Morley JE, Banks WA (2010) Lipids and cognition. J Alzheimers Dis 20:737–747

    Article  Google Scholar 

  • Newman AB, Sanders JL, Kizer JR, Boudreau RM, Odden MC, Al Hazzouri AZ et al (2016) Trajectories of function and biomarkers with age: the CHS all stars study. Int J Epidemiol:1135–1145

  • Paschalis V, Giakas G, Baltzopoulos V, Jamurtas AZ, Theoharis V, Kotzamanidis C, Koutedakis Y (2007) The effects of muscle damage following eccentric exercise on gait biomechanics. Gait Posture 25:236–242

    Article  Google Scholar 

  • Perice L, Barzilai N, Verghese J, Weiss EF, Holtzer R, Cohen P et al (2016) Lower circulating insulin-like growth factor-I is associated with better cognition in females with exceptional longevity without compromise to muscle mass and function

  • Pujos-Guillot E, Pétéra M, Jacquemin J, Centeno D, Lyan B, Montoliu I et al (2019) Identification of Pre-frailty Sub-Phenotypes in Elderly Using Metabolomics. Front Physiol

  • Qualls C, Waters DL, Vellas B, Villareal DT, Garry PJ, Gallini A et al (2017) Reversible states of physical and/or cognitive dysfunction: a 9-year longitudinal study. J Nutr Health Aging 21:271–275

    Article  CAS  Google Scholar 

  • Rikkert MGMO, Melis RJF (2019) Rerouting geriatric medicine by complementing static frailty measures with dynamic resilience indicators of recovery potential. Front Physiol 723

  • Rodriguez-Manas L, Araujo De Carvalho I, Bhasin S, Bischoff-Ferrari HA, Cesari M, Evans WJ et al (2019) ICFSR Task Force Perspective on Biomarkers For Sarcopenia and Frailty. J Frailty Aging

  • Salive ME, Jones CA, Guralnik JM, Agodoa LY, Pahor M, Wallace RB (1995) Serum creatinine levels in older adults: relationship with health status and medications. Age Ageing 24:142–150

    Article  CAS  Google Scholar 

  • Sanders JLDV, Arnold AM, Kaplan RC, Cappola AR, Kizer JR, Boudreau RM, Cushman M, Newman AB (2014) Do changes in circulating biomarkers track with each other and with functional changes in older adults? J Gerontol Ser A 69A:174–181

    Article  Google Scholar 

  • Spauwen PJJ et al (2017) Associations of fat and muscle tissue with cognitive status in older adults: the AGES-Reykjavik Study. Age Ageing 46:250

    Article  Google Scholar 

  • Stefano FD, Zambon S, Giacometti L (2015) al. e. Obesity, muscular strength, muscle composition and physical performance in an elderly population. J Nutr Health Aging 19:785

    Article  Google Scholar 

  • Teng EL, Chui HC (1987) The modified mini-mental state (MMS) examination. J Clin Psychiatry 48:314–318

    CAS  PubMed  Google Scholar 

  • Thielke SM, Whitson H, Diehr P, O'Hare A, Kearney PM, Chaudhry SI et al (2012) Persistence and remission of musculoskeletal pain in community-dwelling older adults: results from the cardiovascular health study. J Am Geriatr Soc:1393–1400

  • Wang J, Maxwell CA, Yu F (2019) Biological processes and biomarkers related to frailty in older adults: a state-of-the-science literature review. Biol Res Nurs:80–106

  • Wennberg AMV et al (2018) The association between peripheral total IGF-1, IGFBP-3, and their molar ratio levels and functional and cognitive outcomes in the Mayo Clinic study of aging Neurobiol aging. Neurobiol Aging:68–74

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Authors and Affiliations

  1. Department of Medicine and School of Physiotherapy, University of Otago, Dunedin, 9054, New Zealand

    D. L. Waters & L. Vlietstra

  2. Department of Internal Medicine, University of New Mexico School of Medicine, Albuquerque, NM, 87131, USA

    D. L. Waters

  3. Department of Mathematics & Statistics and School of Medicine, University of New Mexico, Albuquerque, NM, 87131, USA

    C. Qualls

  4. Division of Geriatric Medicine, Saint Louis University, 1402 South Grand Blvd, Room M238, St. Louis, MO, 63110-0250, USA

    J. E. Morley

  5. Department of Internal and Geriatrics Medicine, Gerontopole, CHU de Toulouse, UMR 1027 INSERM, University Toulouse III, Toulouse, France

    B. Vellas

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  1. D. L. Waters
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  2. L. Vlietstra
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  3. C. Qualls
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  4. J. E. Morley
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  5. B. Vellas
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Correspondence to D. L. Waters.

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Waters, D.L., Vlietstra, L., Qualls, C. et al. Sex-specific muscle and metabolic biomarkers associated with gait speed and cognitive transitions in older adults: a 9-year follow-up. GeroScience 42, 585–593 (2020). https://doi.org/10.1007/s11357-020-00163-7

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  • DOI: https://doi.org/10.1007/s11357-020-00163-7

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