Abstract
Background
Alzheimer's disease (AD) is a neurodegenerative disease characterized by brain atrophy and closely correlated with sarcopenia. Mounting studies indicate that parameters related to sarcopenia are associated with AD, but some results show inconsistent. Furthermore, the association between the parameters related to sarcopenia and gray matter volume (GMV) has rarely been explored.
Aim
To investigate the correlation between parameters related to sarcopenia and cerebral GMV in AD.
Methods
Demographics, neuropsychological tests, parameters related to sarcopenia, and magnetic resonance imaging (MRI) scans were collected from 42 patients with AD and 40 normal controls (NC). Parameters related to sarcopenia include appendicular skeletal muscle mass index (ASMI), grip strength, 5-times sit-to-stand (5-STS) time and 6-m gait speed. The GMV of each cerebral region of interest (ROI) and the intracranial volume were calculated by computing the numbers of the voxels in the specific region based on MRI data. Partial correlation and multivariate stepwise linear regression analysis explored the correlation between different inter-group GMV ratios in ROIs and parameters related to sarcopenia, adjusting for covariates.
Results
The 82 participants included 40 NC aged 70.13 ± 5.94 years, 24 mild AD patients aged 73.54 ± 8.27 years and 18 moderate AD patients aged 71.67 ± 9.39 years. Multivariate stepwise linear regression showed that 5-STS time and gait speed were correlated with bilateral hippocampus volume ratios in total AD. Grip strength was associated with the GMV ratio of the left middle frontal gyrus in mild AD and the GMV ratios of the right superior temporal gyrus and right hippocampus in moderate AD. However, ASMI did not have a relationship to any cerebral GMV ratio.
Conclusions
Among parameters related to sarcopenia, 5-STS time and gait speed were associated with bilateral hippocampus volume ratios at different clinical stages of patients with AD. Five-STS time provide an objective basis for early screening and can help diagnose patients with AD.
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References
Beaudart C, Zaaria M, Pasleau F et al (2017) Health outcomes of sarcopenia: a systematic review and meta-analysis. PLoS ONE 12:e0169548. https://doi.org/10.1371/journal.pone.0169548
Moon Y, Choi YJ, Kim JO et al (2018) Muscle profile and cognition in patients with Alzheimer’s disease dementia. Neurol Sci 39:1861–1866. https://doi.org/10.1007/s10072-018-3505-0
Dercon Q, Nicholas JM, James SN et al (2021) Grip strength from midlife as an indicator of later-life brain health and cognition: evidence from a British birth cohort. BMC Geriatr 21:475. https://doi.org/10.1186/s12877-021-02411-7
Cooper R, Kuh D, Cooper C et al (2011) Objective measures of physical capability and subsequent health: a systematic review. Age Ageing 40:14–23. https://doi.org/10.1093/ageing/afq117
Camargo EC, Weinstein G, Beiser AS et al (2016) Association of Physical Function with Clinical and Subclinical Brain Disease: The Framingham Offspring Study. J Alzheimers Dis 53:1597–1608. https://doi.org/10.3233/JAD-160229
Taekema DG, Ling CH, Kurrle SE et al (2012) Temporal relationship between handgrip strength and cognitive performance in oldest old people. Age Ageing 41:506–512. https://doi.org/10.1093/ageing/afs013
Chen WL, Peng TC, Sun YS et al (2015) Examining the association between quadriceps strength and cognitive performance in the elderly. Medicine (Baltimore) 94:e1335. https://doi.org/10.1097/MD.0000000000001335
Sui SX, Holloway-Kew KL, Hyde NK et al (2020) Muscle strength and gait speed rather than lean mass are better indicators for poor cognitive function in older men. Sci Rep 10:10367. https://doi.org/10.1038/s41598-020-67251-8
Kim GM, Kim BK, Kim DR et al (2021) An association between lower extremity function and cognitive frailty: a sample population from the KFACS study. Int J Environ Res Public Health 18:1007. https://doi.org/10.3390/ijerph18031007
Rashid MH, Zahid MF, Zain S et al (2020) The neuroprotective effects of exercise on cognitive decline: a preventive approach to alzheimer disease. Cureus 12:e6958. https://doi.org/10.7759/cureus.6958
Burtscher J, Millet GP, Place N et al (2021) The muscle-brain axis and neurodegenerative diseases: the key role of mitochondria in exercise-induced neuroprotection. Int J Mol Sci. https://doi.org/10.3390/ijms22126479
Osawa Y, Tian Q, An Y et al (2021) Longitudinal associations between brain volume and knee extension peak torque. J Gerontol A Biol Sci Med Sci 76:286–290. https://doi.org/10.1093/gerona/glaa095
Cosentino E, Palmer K, Della Pieta C et al (2020) Association between gait, cognition, and gray matter volumes in mild cognitive impairment and healthy controls. Alzheimer Dis Assoc Disord 34:231–237. https://doi.org/10.1097/WAD.0000000000000371
Allali G, Montembeault M, Saj A et al (2019) Structural brain volume covariance associated with gait speed in patients with amnestic and non-amnestic mild cognitive impairment: a double dissociation. J Alzheimers Dis 71:S29–S39. https://doi.org/10.3233/JAD-190038
Matuskova V, Ismail Z, Nikolai T et al (2021) Mild behavioral impairment is associated with atrophy of entorhinal cortex and hippocampus in a memory clinic cohort. Front Aging Neurosci 13:643271. https://doi.org/10.3389/fnagi.2021.643271
Schnellbacher GJ, Hoffstaedter F, Eickhoff SB et al (2020) Functional characterization of atrophy patterns related to cognitive impairment. Front Neurol 11:18. https://doi.org/10.3389/fneur.2020.00018
Moon Y, Moon WJ, Kim JO et al (2019) Muscle strength is independently related to brain atrophy in patients with alzheimer’s disease. Dement Geriatr Cogn Disord 47:306–314. https://doi.org/10.1159/000500718
Burns JM, Johnson DK, Watts A et al (2010) Reduced lean mass in early Alzheimer disease and its association with brain atrophy. Arch Neurol 67:428–433. https://doi.org/10.1001/archneurol.2010.38
McKhann GM, Knopman DS, Chertkow H et al (2011) The diagnosis of dementia due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement 7:263–269. https://doi.org/10.1016/j.jalz.2011.03.005
Folstein MF, Folstein SE, McHugh PR (1975) “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 12:189–198. https://doi.org/10.1016/0022-3956(75)90026-6
Fazekas F, Chawluk JB, Alavi A et al (1987) MR signal abnormalities at 1.5 T in Alzheimer’s dementia and normal aging. AJR Am J Roentgenol 149:351–356. https://doi.org/10.2214/ajr.149.2.351
Liu H, Jiao J, Zhu M et al (2022) Nutritional Status According to the Short-Form Mini Nutritional Assessment (MNA-SF) and clinical characteristics as predictors of length of stay, mortality, and readmissions among older inpatients in china: a national study. Front Nutr 9:815578. https://doi.org/10.3389/fnut.2022.815578
Chen LK, Woo J, Assantachai P et al (2020) Asian working group for sarcopenia: 2019 consensus update on sarcopenia diagnosis and treatment. J Am Med Dir Assoc 21:e302. https://doi.org/10.1016/j.jamda.2019.12.012
Wang Y, Nie J, Yap PT et al (2014) Knowledge-guided robust MRI brain extraction for diverse large-scale neuroimaging studies on humans and non-human primates. PLoS ONE 9:e77810. https://doi.org/10.1371/journal.pone.0077810
Dumurgier J, Artaud F, Touraine C et al (2017) Gait speed and decline in gait speed as predictors of incident dementia. J Gerontol A Biol Sci Med Sci 72:655–661. https://doi.org/10.1093/gerona/glw110
Rosso AL, Studenski SA, Chen WG et al (2013) Aging, the central nervous system, and mobility. J Gerontol A Biol Sci Med Sci 68:1379–1386. https://doi.org/10.1093/gerona/glt089
Rosso AL, Verghese J, Metti AL et al (2017) Slowing gait and risk for cognitive impairment: the hippocampus as a shared neural substrate. Neurology 89:336–342. https://doi.org/10.1212/WNL.0000000000004153
Piekema C, Kessels RP, Mars RB et al (2006) The right hippocampus participates in short-term memory maintenance of object-location associations. Neuroimage 33:374–382. https://doi.org/10.1016/j.neuroimage.2006.06.035
Bland BH, Oddie SD (2001) Theta band oscillation and synchrony in the hippocampal formation and associated structures: the case for its role in sensorimotor integration. Behav Brain Res 127:119–136. https://doi.org/10.1016/s0166-4328(01)00358-8
Allali G, van der Meulen M, Beauchet O et al (2014) The neural basis of age-related changes in motor imagery of gait: an fMRI study. J Gerontol A Biol Sci Med Sci 69:1389–1398. https://doi.org/10.1093/gerona/glt207
Malouin F, Richards CL, Jackson PL et al (2003) Brain activations during motor imagery of locomotor-related tasks: a PET study. Hum Brain Mapp 19:47–62. https://doi.org/10.1002/hbm.10103
Ide R, Ota M, Hada Y et al (2022) Dynamic balance deficit and the neural network in Alzheimer’s disease and mild cognitive impairment. Gait Posture 93:252–258. https://doi.org/10.1016/j.gaitpost.2022.01.018
Rosso AL, Olson Hunt MJ, Yang M et al (2014) Higher step length variability indicates lower gray matter integrity of selected regions in older adults. Gait Posture 40:225–230. https://doi.org/10.1016/j.gaitpost.2014.03.192
Cesari M, Kritchevsky SB, Newman AB et al (2009) Added value of physical performance measures in predicting adverse health-related events: results from the Health, Aging And Body Composition Study. J Am Geriatr Soc 57:251–259. https://doi.org/10.1111/j.1532-5415.2008.02126.x
Cruz-Jentoft AJ, Bahat G, Bauer J et al (2019) Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing 48:16–31. https://doi.org/10.1093/ageing/afy169
Landi F, Calvani R, Martone AM et al (2020) Normative values of muscle strength across ages in a “real world” population: results from the longevity check-up 7+ project. J Cachexia Sarcopenia Muscle 11:1562–1569. https://doi.org/10.1002/jcsm.12610
Munoz-Bermejo L, Adsuar JC, Mendoza-Munoz M et al (2021) Test-retest reliability of five times sit to stand test (FTSST) in adults: a systematic review and meta-analysis. Biology (Basel). https://doi.org/10.3390/biology10060510
Bohannon RW, Bubela DJ, Magasi SR et al (2010) Sit-to-stand test: performance and determinants across the age-span. Isokinet Exerc Sci 18:235–240. https://doi.org/10.3233/IES-2010-0389
Carson RG (2018) Get a grip: individual variations in grip strength are a marker of brain health. Neurobiol Aging 71:189–222. https://doi.org/10.1016/j.neurobiolaging.2018.07.023
Herold F, Labott BK, Grassler B et al (2022) A link between handgrip strength and executive functioning: a cross-sectional study in older adults with mild cognitive impairment and healthy controls. Healthcare (Basel). https://doi.org/10.3390/healthcare10020230
Kilintari M, Raos V, Savaki HE (2014) Involvement of the superior temporal cortex in action execution and action observation. J Neurosci 34:8999–9011. https://doi.org/10.1523/JNEUROSCI.0736-14.2014
Liu G, Liu C, Qiu A (2021) Alzheimer’s Disease Neuroimaging I. Spatial correlation maps of the hippocampus with cerebrospinal fluid biomarkers and cognition in Alzheimer’s disease: A longitudinal study. Hum Brain Mapp 42:2931–2940. https://doi.org/10.1002/hbm.25414
Lisman J, Buzsaki G, Eichenbaum H et al (2017) Viewpoints: how the hippocampus contributes to memory, navigation and cognition. Nat Neurosci 20:1434–1447. https://doi.org/10.1038/nn.4661
Kilgour AH, Todd OM, Starr JM (2014) A systematic review of the evidence that brain structure is related to muscle structure and their relationship to brain and muscle function in humans over the lifecourse. BMC Geriatr 14:85. https://doi.org/10.1186/1471-2318-14-85
El-Sayes J, Harasym D, Turco CV et al (2019) Exercise-induced neuroplasticity: a mechanistic model and prospects for promoting plasticity. Neuroscientist 25:65–85. https://doi.org/10.1177/1073858418771538
Westwood AJ, Beiser A, Decarli C et al (2014) Insulin-like growth factor-1 and risk of Alzheimer dementia and brain atrophy. Neurology 82:1613–1619. https://doi.org/10.1212/WNL.0000000000000382
Kimoto A, Kasanuki K, Kumagai R et al (2016) Serum insulin-like growth factor-I and amyloid beta protein in Alzheimer’s disease: relationship with cognitive function. Psychogeriatrics 16:247–254. https://doi.org/10.1111/psyg.12149
van Nieuwpoort IC, Vlot MC, Schaap LA et al (2018) The relationship between serum IGF-1, handgrip strength, physical performance and falls in elderly men and women. Eur J Endocrinol 179:73–84. https://doi.org/10.1530/EJE-18-0076
Schaeffer E, Roeben B, Granert O et al (2022) Effects of exergaming on hippocampal volume and brain-derived neurotrophic factor levels in Parkinson’s disease. Eur J Neurol 29:441–449. https://doi.org/10.1111/ene.15165
Ferrari R, Caram LM, Faganello MM et al (2015) Relation between systemic inflammatory markers, peripheral muscle mass, and strength in limb muscles in stable COPD patients. Int J Chron Obstruct Pulmon Dis 10:1553–1558. https://doi.org/10.2147/COPD.S85954
Dupont J, Antonio L, Dedeyne L et al (2021) Inflammatory markers are associated with quality of life, physical activity, and gait speed but not sarcopenia in aged men (40–79 years). J Cachexia Sarcopenia Muscle 12:1818–1831. https://doi.org/10.1002/jcsm.12785
Yu JH, Kim REY, Jung JM et al (2021) Sarcopenia is associated with decreased gray matter volume in the parietal lobe: a longitudinal cohort study. BMC Geriatr 21:622. https://doi.org/10.1186/s12877-021-02581-4
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We would like to thank all the participants of the study and the staff involved.
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This study was funded by Basic Research on the Application of Science and Technology of Minsheng Technology in Suzhou (SYSD2019109); Application of Clinical Technology in Elderly Health Research Project in Jiangsu Province (LD2021031).
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This study was approved by the ethics committee of the Second Affiliated Hospital of Soochow University (JD-LK-2021–049-01).
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Liu, S., Zhang, Y., Peng, B. et al. Correlation between parameters related to sarcopenia and gray matter volume in patients with mild to moderate Alzheimer's disease. Aging Clin Exp Res 34, 3041–3053 (2022). https://doi.org/10.1007/s40520-022-02244-3
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DOI: https://doi.org/10.1007/s40520-022-02244-3