Strength gains after 12 weeks of resistance training correlate with neurochemical markers of brain health in older adults: a randomized control 1H-MRS study

Samrat Sheoran, Wouter A J Vints, Kristina Valatkevičienė, Simona Kušleikienė, Rymantė Gleiznienė, Vida J Česnaitienė, Uwe Himmelreich, Oron Levin, Nerijus Masiulis, Samrat Sheoran, Wouter A J Vints, Kristina Valatkevičienė, Simona Kušleikienė, Rymantė Gleiznienė, Vida J Česnaitienė, Uwe Himmelreich, Oron Levin, Nerijus Masiulis

Abstract

Physical exercise is considered a potent countermeasure against various age-associated physiological deterioration processes. We therefore assessed the effect of 12 weeks of resistance training on brain metabolism in older adults (age range: 60-80 years). Participants either underwent two times weekly resistance training program which consisted of four lower body exercises performed for 3 sets of 6-10 repetitions at 70-85% of 1 repetition maximum (n = 20) or served as the passive control group (n = 21). The study used proton magnetic resonance spectroscopy to quantify the ratio of total N-acetyl aspartate, total choline, glutamate-glutamine complex, and myo-inositol relative to total creatine (tNAA/tCr, tCho/tCr, Glx/tCr, and mIns/tCr respectively) in the hippocampus (HPC), sensorimotor (SM1), and prefrontal (dlPFC) cortices. The peak torque (PT at 60°/s) of knee extension and flexion was assessed using an isokinetic dynamometer. We used repeated measures time × group ANOVA to assess time and group differences and correlation coefficient analyses to examine the pre-to-post change (∆) associations between PT and neurometabolite variables. The control group showed significant declines in tNAA/tCr and Glx/tCr of SM1, and tNAA/tCr of dlPFC after 12 weeks, which were not seen in the experimental group. A significant positive correlation was found between ∆PT knee extension and ∆SM1 Glx/tCr, ∆dlPFC Glx/tCr and between ∆PT knee flexion and ∆dlPFC mIns/tCr in the experimental group. Overall, findings suggest that resistance training seems to elicit alterations in various neurometabolites that correspond to exercise-induced "preservation" of brain health, while simultaneously having its beneficial effect on augmenting muscle functional characteristics in older adults.

Keywords: Aging; Brain metabolism; Glutamate; N-acetylaspartate; Neurogenesis; Sarcopenia; Strength training.

Conflict of interest statement

The authors declare no competing interests.

© 2023. The Author(s).

Figures

Fig. 1
Fig. 1
Example of voxel placement along with processed MR spectra in the left hippocampus (HPC), b the left primary sensorimotor cortex (SM1), and c the right dorsolateral prefrontal cortex (dlPFC) in one participant
Fig. 2
Fig. 2
The paired mean difference for PT in EXP and CONT group are shown in the above Cumming estimation plot. The raw data is plotted on the upper axes; each paired set of observations for each participant from PRE to POST is connected by a line. Blue lines indicate POST minus PRE > 0 whereas orange lines indicate POST minus PRE 

Fig. 3

The mean differences between responders…

Fig. 3

The mean differences between responders and non-responders at baseline is shown in the…

Fig. 3
The mean differences between responders and non-responders at baseline is shown in the above Gardner-Altman estimation plots for a MoCA score (n = responders, 8; non-responders, 12) and (b) SM1 tNAA/tCr (n = responders, 7; non-responders, 12). Individual results for both groups are plotted on the left axes; the mean difference is plotted on a floating axes on the right as a bootstrap sampling distribution. The mean difference is depicted as a dot between the Gaussian curve and the 95% confidence interval is indicated by the ends of the vertical error bar. Abbreviations: MoCA, Montreal cognitive assessment; NR-R, mean difference between non-responders and responders; SM1 tNAA/tCr, sensorimotor cortex concentration ratio of total N-acetyl aspartate relative to total creatine

Fig. 4

The linear relationship that survived…

Fig. 4

The linear relationship that survived FDR procedure between changes in strength and neurometabolite…

Fig. 4
The linear relationship that survived FDR procedure between changes in strength and neurometabolite ratios were a ∆PT knee extension and ∆SM1 tNAA/tCr (n = EXP, 16; CONT, 16), b ∆PT knee extension and ∆dlPFC Glx/tCr (n = EXP, 17; CONT, 13), and c ∆PT knee flexion and ∆dlPFC mIns/tCr (n = EXP, 19; CONT, 14), in EXP (blue) and CONT (orange) group participants. See Supplementary Fig. 2 for all relationships. Abbreviations: SM1, sensorimotor cortex; Glx, glutamine-glutamate complex; tCr, total creatine; PT, peak torque; dlPFC, pre-frontal cortex; mIns, myo-inositol; EXP, experimental group; CONT, control group
Fig. 3
Fig. 3
The mean differences between responders and non-responders at baseline is shown in the above Gardner-Altman estimation plots for a MoCA score (n = responders, 8; non-responders, 12) and (b) SM1 tNAA/tCr (n = responders, 7; non-responders, 12). Individual results for both groups are plotted on the left axes; the mean difference is plotted on a floating axes on the right as a bootstrap sampling distribution. The mean difference is depicted as a dot between the Gaussian curve and the 95% confidence interval is indicated by the ends of the vertical error bar. Abbreviations: MoCA, Montreal cognitive assessment; NR-R, mean difference between non-responders and responders; SM1 tNAA/tCr, sensorimotor cortex concentration ratio of total N-acetyl aspartate relative to total creatine
Fig. 4
Fig. 4
The linear relationship that survived FDR procedure between changes in strength and neurometabolite ratios were a ∆PT knee extension and ∆SM1 tNAA/tCr (n = EXP, 16; CONT, 16), b ∆PT knee extension and ∆dlPFC Glx/tCr (n = EXP, 17; CONT, 13), and c ∆PT knee flexion and ∆dlPFC mIns/tCr (n = EXP, 19; CONT, 14), in EXP (blue) and CONT (orange) group participants. See Supplementary Fig. 2 for all relationships. Abbreviations: SM1, sensorimotor cortex; Glx, glutamine-glutamate complex; tCr, total creatine; PT, peak torque; dlPFC, pre-frontal cortex; mIns, myo-inositol; EXP, experimental group; CONT, control group

References

    1. Keller K, Engelhardt M. Strength and muscle mass loss with aging process. Age and strength loss. Muscles Ligaments Tendons J. 2013;3:346–50. doi: 10.11138/mltj/2013.3.4.346.
    1. Damoiseaux JS. Effects of aging on functional and structural brain connectivity. Neuroimage. 2017;160:32–40. doi: 10.1016/J.NEUROIMAGE.2017.01.077.
    1. Yankner BA, Lu T, Loerch P. The aging brain. Annu Rev Pathol Mech Dis. 2008;3:41–66. doi: 10.1146/ANNUREV.PATHMECHDIS.2.010506.092044.
    1. Bektas A, Schurman SH, Sen R, Ferrucci L. Aging, inflammation and the environment. Exp Gerontol. 2018;105:10–18. doi: 10.1016/J.EXGER.2017.12.015.
    1. Grachev ID, Vania AA. Aging alters regional multichemical profile of the human brain: an in vivo1H-MRS study of young versus middle-aged subjects. J Neurochem. 2001;76:582–593. doi: 10.1046/J.1471-4159.2001.00026.X.
    1. Cruz-Jentoft AJ, Baeyens JP, Bauer JM, Boirie Y, Cederholm T, Landi F, et al. Sarcopenia: European consensus on definition and diagnosis. Age Ageing. 2010;39:412–423. doi: 10.1093/ageing/afq034.
    1. Weerasekera A, Levin O, Clauwaert A, Heise K-F, Hermans L, Peeters R, et al. Neurometabolic correlates of reactive and proactive motor inhibition in young and older adults: evidence from multiple regional 1H-MR spectroscopy. Cereb Cortex Commun. 2020;1:1–16. doi: 10.1093/TEXCOM/TGAA028.
    1. Levin O, Weerasekera A, King BR, Heise KF, Sima DM, Chalavi S, et al. Sensorimotor cortex neurometabolite levels as correlate of motor performance in normal aging: evidence from a 1H-MRS study. Neuroimage. 2019;202:116050. doi: 10.1016/J.NEUROIMAGE.2019.116050.
    1. Frontera WR, Rodriguez Zayas A, Rodriguez N. Aging of human muscle: understanding sarcopenia at the single muscle cell level. Phys Med Rehabil Clin N Am. 2012;23:201–207. doi: 10.1016/J.PMR.2011.11.012.
    1. Smith C, Woessner MN, Sim M, Levinger I. Sarcopenia definition: does it really matter? Implications for resistance training. Ageing Res Rev. 2022;78:101617. doi: 10.1016/J.ARR.2022.101617.
    1. Blinkouskaya Y, Weickenmeier J. Brain shape changes associated with cerebral atrophy in healthy aging and Alzheimer’s disease. Front Mech Eng. 2021;7:1–17. doi: 10.3389/fmech.2021.705653.
    1. Sala-Llonch R, Bartrés-Faz D, Junqué C. Reorganization of brain networks in aging: a review of functional connectivity studies. Front Psychol. 2015;6:1–11. doi: 10.3389/fpsyg.2015.00663.
    1. Raz N, Lindenberger U, Rodrigue KM, Kennedy KM, Head D, Williamson A, et al. Regional brain changes in aging healthy adults: general trends, individual differences and modifiers. Cereb Cortex. 2005;15:1676–1689. doi: 10.1093/CERCOR/BHI044.
    1. Hsu YH, Liang CK, Chou MY, Wang YC, Liao MC, Chang WC, et al. Sarcopenia is independently associated with parietal atrophy in older adults. Exp Gerontol. 2021;151:111402. doi: 10.1016/J.EXGER.2021.111402.
    1. Yu JH, Kim REY, Jung JM, Park SY, Lee DY, Cho HJ, et al. Sarcopenia is associated with decreased gray matter volume in the parietal lobe: a longitudinal cohort study. BMC Geriatr. 2021;21:1–10. doi: 10.1186/S12877-021-02581-4/TABLES/3.
    1. Nikolich-Žugich J, Goldman DP, Cohen PR, Cortese D, Fontana L, Kennedy BK, et al. Preparing for an aging world: engaging biogerontologists, geriatricians, and the society. J Gerontol - Ser A Biol Sci Med Sci. 2016;71:435–444. doi: 10.1093/gerona/glv164.
    1. Cabral DF, Rice J, Morris TP, Rundek T, Pascual-Leone A, Gomes-Osman J. Exercise for brain health: an investigation into the underlying mechanisms guided by dose 2019. 10.1007/s13311-019-00749-w.
    1. Erickson KI, Voss MW, Prakash RS, Basak C, Szabo A, Chaddock L, et al. Exercise training increases size of hippocampus and improves memory. Proc Natl Acad Sci U S A. 2011;108:3017–3022. doi: 10.1073/PNAS.1015950108/-/DCSUPPLEMENTAL.
    1. Pinho RA, Aguiar AS, Radák Z. Effects of resistance exercise on cerebral redox regulation and cognition: an interplay between muscle and brain. Antioxidants. 2019;8:529. doi: 10.3390/ANTIOX8110529.
    1. Chen W-L, Peng T-C, Sun Y-S, Yang H-F, Liaw F-Y, Wu L-W, et al. Examining the association between quadriceps strength and cognitive performance in the elderly. Med (Baltimore) 2015;94(32):e13335. doi: 10.1097/MD.0000000000001335.
    1. Herold F, Törpel A, Schega L, Müller NG. Functional and/or structural brain changes in response to resistance exercises and resistance training lead to cognitive improvements - a systematic review. Eur Rev Aging Phys Act 2019;16(1). 10.1186/s11556-019-0217-2.
    1. Mavros Y, Gates N, Wilson GC, Jain N, Meiklejohn J, Brodaty H, et al. Mediation of cognitive function improvements by strength gains after resistance training in older adults with mild cognitive impairment: outcomes of the study of mental and resistance training. J Am Geriatr Soc. 2017;65:550–559. doi: 10.1111/JGS.14542.
    1. Colcombe SJ, Erickson KI, Scalf PE, Kim JS, Prakash R, McAuley E, et al. Aerobic exercise training increases brain volume in aging humans. J Gerontol Ser A. 2006;61:1166–1170. doi: 10.1093/GERONA/61.11.1166.
    1. Haeger A, Costa AS, Schulz JB, Reetz K. Cerebral changes improved by physical activity during cognitive decline: a systematic review on MRI studies. NeuroImage Clin. 2019;23:101933. doi: 10.1016/J.NICL.2019.101933.
    1. Erickson KI, Weinstein AM, Sutton BP, Prakash RS, Voss MW, Chaddock L, et al. Beyond vascularization: aerobic fitness is associated with N-acetylaspartate and working memory. Brain Behav. 2012;2:32–41. doi: 10.1002/brb3.30.
    1. Gonzales MM, Tarumi T, Kaur S, Nualnim N, Fallow BA, Pyron M, et al. Aerobic fitness and the brain: increased N-acetyl-aspartate and choline concentrations in endurance-trained middle-aged adults. Brain Topogr. 2013;26:126–134. doi: 10.1007/s10548-012-0248-8.
    1. Hendrikse J, Chye Y, Thompson S, Rogasch NC, Suo C, Coxon JP, et al. Regular aerobic exercise is positively associated with hippocampal structure and function in young and middle-aged adults. Hippocampus. 2022;32:137–152. doi: 10.1002/HIPO.23397.
    1. Duarte JMN, Lei H, Mlynárik V, Gruetter R. The neurochemical profile quantified by in vivo 1H NMR spectroscopy. Neuroimage. 2012;61:342–362. doi: 10.1016/j.neuroimage.2011.12.038.
    1. Haga KK, Khor YP, Farrall A, Wardlaw JM. A systematic review of brain metabolite changes, measured with 1H magnetic resonance spectroscopy, in healthy aging. Neurobiol Aging. 2009;30:353–363. doi: 10.1016/j.neurobiolaging.2007.07.005.
    1. Duarte JMN, Schuck PF, Wenk GL, Ferreira GC. Metabolic disturbances in diseases with neurological involvement. Aging Dis. 2014;5:238–55. doi: 10.14336/AD.2014.0500238.
    1. Ramadan S, Lin A, Stanwell P. Glutamate and glutamine: a review of in vivo MRS in the human brain. NMR Biomed. 2013;26:1630–1646. doi: 10.1002/NBM.3045.
    1. Huang Z, Henry Hap Davis IV, Yue Q, Wiebking C, Duncan NW, Zhang J, et al. Increase in glutamate/glutamine concentration in the medial prefrontal cortex during mental imagery: a combined functional mrs and fMRI study. Hum Brain Mapp. 2015;36:3204–12. doi: 10.1002/HBM.22841.
    1. Thielen JW, Hong D, Rohani Rankouhi S, Wiltfang J, Fernández G, Norris DG, et al. The increase in medial prefrontal glutamate/glutamine concentration during memory encoding is associated with better memory performance and stronger functional connectivity in the human medial prefrontal–thalamus–hippocampus network. Hum Brain Mapp. 2018;39:2381–2390. doi: 10.1002/HBM.24008.
    1. Ding XQ, Maudsley AA, Sabati M, Sheriff S, Schmitz B, Schütze M, et al. Physiological neuronal decline in healthy aging human brain — An in vivo study with MRI and short echo-time whole-brain 1H MR spectroscopic imaging. Neuroimage. 2016;137:45–51. doi: 10.1016/J.NEUROIMAGE.2016.05.014.
    1. Huang D, Liu D, Yin J, Qian T, Shrestha S, Ni H. Glutamate-glutamine and GABA in brain of normal aged and patients with cognitive impairment. Eur Radiol. 2017;27:2698–2705. doi: 10.1007/s00330-016-4669-8.
    1. Maddock RJ, Casazza GA, Buonocore MH, Tanase C. Vigorous exercise increases brain lactate and Glx (glutamate + glutamine): a dynamic 1H-MRS study. Neuroimage. 2011;57:1324–1330. doi: 10.1016/J.NEUROIMAGE.2011.05.048.
    1. Valkenborghs SR, Hillman CH, Nilsson M, Smith JJ, AngusLeahy A, et al. Effect of high-intensity interval training on hippocampal metabolism in older adolescents. Psychophysiol. 2022;59(11):00–14090. doi: 10.1111/PSYP.14090.
    1. Maddock RJ, Casazza GA, Fernandez DH, Maddock MI. Acute modulation of cortical glutamate and GABA content by physical activity. J Neurosci. 2016;36:2449–2457. doi: 10.1523/JNEUROSCI.3455-15.2016.
    1. Kantarci K, Lowe V, Przybelski SA, Senjem ML, Weigand SD, Ivnik RJ, et al. Magnetic resonance spectroscopy, β-amyloid load, and cognition in a population-based sample of cognitively normal older adults. Neurol. 2011;77:951–958. doi: 10.1212/WNL.0B013E31822DC7E1.
    1. Bitsch A, Bruhn H, Vougioukas V, Stringaris A, Lassmann H, Frahm J, et al. Inflammatory CNS demyelination: histopathologic correlation with in vivo quantitative proton MR spectroscopy. AJNR Am J Neuroradiol. 1999;20:1619–1627.
    1. Lind A, Boraxbekk CJ, Petersen ET, Paulson OB, Andersen O, Siebner HR, et al. Do glia provide the link between low-grade systemic inflammation and normal cognitive ageing? A 1H magnetic resonance spectroscopy study at 7 tesla. J Neurochem. 2021;159:185–196. doi: 10.1111/JNC.15456.
    1. Vints WAJ, Kušleikienė S, Sheoran S, Šarkinaitė M, Valatkevičienė K, Gleiznienė R, et al. Inflammatory blood biomarker kynurenine is linked with elevated neuroinflammation and neurodegeneration in older adults: evidence from two 1H-MRS post-processing analysis methods. Front Psychiatry 2022. 10.3389/FPSYT.2022.859772.
    1. Popadic Gacesa J, Schick F, Machann J, Grujic N. Intramyocellular lipids and their dynamics assessed by 1H magnetic resonance spectroscopy. Clin Physiol Funct Imaging. 2017;37:558–566. doi: 10.1111/CPF.12346.
    1. Gleeson M, Bishop NC, Stensel DJ, Lindley MR, Mastana SS, Nimmo MA. The anti-inflammatory effects of exercise: mechanisms and implications for the prevention and treatment of disease. Nat Rev Immunol. 2011;11:607–15. doi: 10.1038/nri3041.
    1. Carson N, Leach L, Murphy KJ. A re-examination of Montreal Cognitive Assessment (MoCA) cutoff scores. Int J Geriatr Psychiatry. 2018;33:379–388. doi: 10.1002/gps.4756.
    1. Nasreddine ZS, Phillips NA, Bédirian V, Charbonneau S, Whitehead V, Collin I, et al. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. 2005. 10.1111/j.1532-5415.2005.53221.x.
    1. Craig CL, Marshall AL, Sjöström M, Bauman AE, Booth ML, Ainsworth BE, et al. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc. 2003;35:1381–1395. doi: 10.1249/01.MSS.0000078924.61453.FB.
    1. Sjöström M, Ainsworth BE, Bauman AE, Bull F, Hamilton-Craig C, Sallis JF. Guidelines for data processing and analysis of the international physical activity questionnaire (IPAQ) – Short and Long Forms. Medicine (Baltimore) 2005;1–15. .
    1. Den Ouden L, Kandola A, Suo C, Hendrikse J, Costa RJS, Watt MJ, et al. The influence of aerobic exercise on hippocampal integrity and function: preliminary findings of a multi-modal imaging analysis. Brain Plast. 2018;4:211–216. doi: 10.3233/bpl-170053.
    1. Tamura M, Nemoto K, Kawaguchi A, Kato M, Arai T, Kakuma T, et al. Long-term mild-intensity exercise regimen preserves prefrontal cortical volume against aging. Int J Geriatr Psychiatry. 2015;30:686–694. doi: 10.1002/GPS.4205.
    1. Santos Monteiro T, Beets IAM, Boisgontier MP, Gooijers J, Pauwels L, Chalavi S, et al. Relative cortico-subcortical shift in brain activity but preserved training-induced neural modulation in older adults during bimanual motor learning 2017. 10.1016/j.neurobiolaging.2017.06.004.
    1. Zhao M, Marino M, Samogin J, Swinnen SP, Mantini D. Hand, foot and lip representations in primary sensorimotor cortex: a high-density electroencephalography study. Sci Reports. 2019;9:1–12. doi: 10.1038/s41598-019-55369-3.
    1. Provencher SW. Automatic quantitation of localized in vivo 1H spectra with LCModel. NMR Biomed. 2001;14:260–264. doi: 10.1002/NBM.698.
    1. Fragala MS, Cadore EL, Dorgo S, Izquierdo M, Kraemer WJ, Peterson MD, et al. Resistance training for older adults: position statement from the national strength and conditioning association. J Strength Cond Res. 2019;33:2019–2052. doi: 10.1519/jsc.0000000000003230.
    1. Aagaard P, Suetta C, Caserotti P, Magnusson SP, Kjær M. Role of the nervous system in sarcopenia and muscle atrophy with aging: strength training as a countermeasure. Scand J Med Sci Sports. 2010;20:49–64. doi: 10.1111/J.1600-0838.2009.01084.X.
    1. Marsh AP, Miller ME, Rejeski WJ, Hutton SL, Kritchevsky SB. Lower extremity muscle function after strength or power training in older adults. J Aging Phys Act. 2009;17:416–443. doi: 10.1123/JAPA.17.4.416.
    1. Fournier NM, Duman RS. Role of vascular endothelial growth factor in adult hippocampal neurogenesis: implications for the pathophysiology and treatment of depression. Behav Brain Res. 2012;227:440–449. doi: 10.1016/J.BBR.2011.04.022.
    1. Yeo NH, Woo J, Shin KO, Park JY, Kang S. The effects of different exercise intensity on myokine and angiogenesis factors. J Sports Med Phys Fitness. 2012;52:448–454.
    1. Vints WAJ, Levin O, Fujiyama H, Verbunt J, Masiulis N. Exerkines and long-term synaptic potentiation: mechanisms of exercise-induced neuroplasticity. Front Neuroendocrinol. 2022;66:100993. doi: 10.1016/J.YFRNE.2022.100993.
    1. Haff GG, Triplett NT. Essentials of strength training and conditioning - fourth edition. Human Kinetics Publishers Inc.; 2015;1–730. Champaign, Illinois.
    1. Swain DP, Brawner CA. ACSM’s resource manual for guidelines for exercise testing and prescription. Lippincott Williams and Wilkins 7th edition; 2013;1–896. Philadelphia, Pennsylvania.
    1. Morishita S, Tsubaki A, Nakamura M, Nashimoto S, Fu JB, Onishi H. Rating of perceived exertion on resistance training in elderly subjects. Expert Rev Cardiovasc Therapy. 2019;17:135–42. doi: 10.1080/14779072.2019.1561278.
    1. Ho J, Tumkaya T, Aryal S, Choi H, Claridge-Chang A. Moving beyond P values: data analysis with estimation graphics. Nat Methods. 2019;16:565–6. doi: 10.1038/s41592-019-0470-3.
    1. Matura S, Fleckenstein J, Deichmann R, Engeroff T, Füzéki E, Hattingen E, et al. Effects of aerobic exercise on brain metabolism and grey matter volume in older adults: results of the randomised controlled SMART trial. Transl Psychiatry. 2017;7:e1172. doi: 10.1038/tp.2017.135.
    1. Sijens PE, Den Heijer T, Origgi D, Vermeer SE, Breteler MMB, Hofman A, et al. Brain changes with aging: MR spectroscopy at supraventricular plane shows differences between women and men1. Radiol. 2003;226(3):889–96. doi: 10.1148/RADIOL.2263011937.
    1. Kantarci K, Weigand SD, Petersen RC, Boeve BF, Knopman DS, Gunter J, et al. Longitudinal 1H MRS changes in mild cognitive impairment and Alzheimer’s disease. Neurobiol Aging. 2007;28:1330–1339. doi: 10.1016/J.NEUROBIOLAGING.2006.06.018.
    1. Ross AJ, Sachdev PS, Wen W, Brodaty H. Longitudinal changes during aging using proton magnetic resonance spectroscopy. Journals Gerontol Ser A. 2006;61:291–298. doi: 10.1093/GERONA/61.3.291.
    1. Cleeland C, Pipingas A, Scholey A, White D. Neurochemical changes in the aging brain: a systematic review. Neurosci Biobehav Rev. 2019;98:306–319. doi: 10.1016/j.neubiorev.2019.01.003.
    1. Duarte JMN, Do KQ, Gruetter R. Longitudinal neurochemical modifications in the aging mouse brain measured in vivo by 1H magnetic resonance spectroscopy. Neurobiol Aging. 2014;35:1660–1668. doi: 10.1016/J.NEUROBIOLAGING.2014.01.135.
    1. Seidler RD, Bernard JA, Burutolu TB, Fling BW, Gordon MT, Gwin JT, et al. Motor control and aging: links to age-related brain structural, functional, and biochemical effects. Neurosci Biobehav Rev. 2010;34:721–733. doi: 10.1016/j.neubiorev.2009.10.005.
    1. Lockhart SN, DeCarli C. Structural imaging measures of brain aging. Neuropsychol Rev. 2014;24:271–289. doi: 10.1007/s11065-014-9268-3.
    1. Erraji-Benchekroun L, Underwood MD, Arango V, Galfalvy H, Pavlidis P, Smyrniotopoulos P, et al. Molecular aging in human prefrontal cortex is selective and continuous throughout adult life. Biol Psychiatry. 2005;57:549–558. doi: 10.1016/j.biopsych.2004.10.034.
    1. Wilckens KA, Stillman CM, Waiwood AM, Kang C, Leckie RL, Peven JC, et al. Exercise interventions preserve hippocampal volume: a meta-analysis. Hippocampus. 2021;31:335–347. doi: 10.1002/HIPO.23292.
    1. Henry LC, Tremblay S, Leclerc S, Khiat A, Boulanger Y, Ellemberg D, et al. Metabolic changes in concussed American football players during the acute and chronic post-injury phases. BMC Neurol. 2011;11:1–10. doi: 10.1186/1471-2377-11-105/FIGURES/3.
    1. Lefebvre G, Chamard E, Proulx S, Tremblay S, Halko M, Soman S, et al. Increased myo-inositol in primary motor cortex of contact sports athletes without a history of concussion. J Neurotrauma. 2018;35:953–962. doi: 10.1089/NEU.2017.5254.
    1. Pajonk FG, Wobrock T, Gruber O, Scherk H, Berner D, Kaizl I, et al. Hippocampal plasticity in response to exercise in schizophrenia. Arch Gen Psychiatry. 2010;67:133–143. doi: 10.1001/archgenpsychiatry.2009.193.
    1. Kintz N, Petzinger GM, Akopian G, Ptasnik S, Williams C, Jakowec MW, et al. Exercise modifies α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor expression in striatopallidal neurons in the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine-lesioned mouse. J Neurosci Res. 2013;91:1492–1507. doi: 10.1002/JNR.23260.
    1. Moffett JR, Ross B, Arun P, Madhavarao CN, Namboodiri AMA. N-Acetylaspartate in the CNS: from neurodiagnostics to neurobiology. Prog Neurobiol. 2007;81:89–131. doi: 10.1016/J.PNEUROBIO.2006.12.003.
    1. Hattingen E, Raab P, Franz K, Zanella FE, Lanfermann H, Pilatus U. Myo-inositol: a marker of reactive astrogliosis in glial tumors? NMR Biomed. 2008;21:233–241. doi: 10.1002/NBM.1186.
    1. Maugeri G, D’agata V, Magrì B, Roggio F, Castorina A, Ravalli S, et al. Neuroprotective effects of physical activity via the adaptation of astrocytes. Cells. 2021;10:1542. doi: 10.3390/cells10061542.
    1. Brockett AT, Lamarca EA, Gould E. Physical exercise enhances cognitive flexibility as well as astrocytic and synaptic markers in the medial prefrontal cortex 2015. 10.1371/journal.pone.0124859.
    1. Li F, Geng X, Yun HJ, Haddad Y, Chen Y, Ding Y. Neuroplastic effect of exercise through astrocytes activation and cellular crosstalk. Aging Dis. 2021;12:1644. doi: 10.14336/AD.2021.0325.
    1. Ekdahl CT, Kokaia Z, Lindvall O. Brain inflammation and adult neurogenesis: the dual role of microglia. Neurosci. 2009;158:1021–1029. doi: 10.1016/J.NEUROSCIENCE.2008.06.052.
    1. Clarkson PM, Devaney JM, Gordish-Dressman H, Thompson PD, Hubal MJ, Urso M, et al. ACTN3 genotype is associated with increases in muscle strength in response to resistance training in women. J Appl Physiol. 2005;99:154–163. doi: 10.1152/japplphysiol.01139.2004.
    1. Hubal MJ, Gordish-Dressman H, Thompson PD, Price TB, Hoffman EP, Angelopoulos TJ, et al. Variability in muscle size and strength gain after unilateral resistance training. Med Sci Sports Exerc. 2005;37:964–72. doi: 10.1249/01.mss.0000170469.90461.5f.
    1. Timmons JA. Variability in training-induced skeletal muscle adaptation. J Appl Physiol. 2011;110:846–853. doi: 10.1152/japplphysiol.00934.2010.
    1. Davidsen PK, Gallagher IJ, Hartman JW, Tarnopolsky MA, Dela F, Helge JW, et al. High responders to resistance exercise training demonstrate differential regulation of skeletal muscle microRNA expression. J Appl Physiol. 2011;110:309–317. doi: 10.1152/JAPPLPHYSIOL.00901.2010/SUPPL_FILE/JAPDATA.PDF.
    1. Ciesielska N, Sokołowski R, Mazur E, Podhorecka M, Polak-Szabela A, Kędziora-Kornatowska K. Is the Montreal Cognitive Assessment (MoCA) test better suited than the Mini-Mental State Examination (MMSE) in mild cognitive impairment (MCI) detection among people aged over 60? Meta-analysis Psychiatr Pol. 2016;50:1039–1052. doi: 10.12740/PP/45368.
    1. Bezold J, Trautwein S, Barisch-Fritz B, Scharpf A, Krell-Roesch J, Nigg CR, et al. Effects of a 16-week multimodal exercise program on activities of daily living in institutionalized individuals with dementia: a multicenter randomized controlled trial. Ger J Exerc Sport Res. 2021;51:506–517. doi: 10.1007/S12662-021-00760-4/TABLES/5.
    1. Meng N, Shi S, Su Y. Proton magnetic resonance spectroscopy as a diagnostic biomarker in mild cognitive impairment following stroke in acute phase. NeuroReport. 2016;27:559–563. doi: 10.1097/WNR.0000000000000555.
    1. Liu Y, Cai ZL, Xue S, Zhou X, Wu F. Proxies of cognitive reserve and their effects on neuropsychological performance in patients with mild cognitive impairment. J Clin Neurosci. 2013;20:548–553. doi: 10.1016/J.JOCN.2012.04.020.
    1. Pickering C, Kiely J. Do non-responders to exercise exist—and if so, what should we do about them? Sport Med. 2019;49:1–7. doi: 10.1007/s40279-018-01041-1.
    1. Montero D. Refuting the myth of non-response to exercise training : ‘ non-responders ’ do respond to higher dose of training 2017;11:3377–87. 10.1113/JP273480.
    1. Near J, Harris AD, Juchem C, Kreis R, Marjańska M, Öz G, et al. Preprocessing, analysis and quantification in single-voxel magnetic resonance spectroscopy: experts’ consensus recommendations. NMR Biomed. 2021;34:e4257. doi: 10.1002/NBM.4257.

Source: PubMed

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