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GRIP STRENGTH, GAIT SPEED AND PLASMA MARKERS OF NEURODEGENERATION IN ASYMPTOMATIC MIDDLE-AGED AND OLDER ADULTS

 

M.E. Jacob1, A. O’Donnell3, J. Samra3, M.M. Gonzales2, C. Satizabal2, M.P. Pase4,5, J.M. Murabito6, A. Beiser3, S. Seshadri2,6

 

1. University of Washington School of Medicine, Seattle, WA, USA; 2. Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, TX, USA; 3. Boston University School of Public Health, Boston, MA, USA; 4. The Turner Institute for Brain and Mental Health at Monash University, Melbourne, Australia, USA; 5. Harvard T.H. Chan School of Public Health, Boston, MA, USA; 6. Boston University School of Medicine, Boston, MA, USA.

Corresponding Author: Mini E. Jacob, Box 356560,1959 NE Pacific Street, Seattle WA 98195, Phone: 412-996-8778, mejacob@uw.edu

J Frailty Aging 2022;in press
Published online February 28, 2022, http://dx.doi.org/10.14283/jfa.2022.17

 


Abstract

Background: Pragmatic biomarkers of preclinical dementia would allow for easy and large-scale screening of risk in populations. Physical function measures like grip strength and gait speed are potential predictive biomarkers but their relationship with plasma markers of Alzheimer’s Disease and neurodegeneration have not been elucidated.
Objectives: To examine association between physical function measures and plasma markers of Alzheimer’s Disease (AD) and neurodegeneration.
Design: Cross-sectional and longitudinal analyses.
Setting: Community-based cohort in the city of Framingham, Massachusetts.
Participants: 2336 participants of the Framingham Heart Study Offspring cohort with an average age of 61.
Measurements: Plasma Aβ40 and Aβ42 were measured in 1998-2001 (Exam-7) and plasma total tau measured 5 years later (Exam-8). Grip strength, fast walk speed and chair stand speed were measured at both exams. Quantification of Aβ isoforms in plasma was performed using INNO-BIA assays and plasma total-tau was measured using Quanterix Simoa HD-1 assay. Confounder-adjusted linear regression models examined associations between physical function and plasma markers,
Results: Grip strength at Exam-7 was associated with plasma Aβ40 (β -0.006, p-value 0.032) at Exam-7 and plasma total-tau (β -0.010, p-value 0.001) at Exam-8. Grip strength and fast walk speed at Exam-8 were associated with plasma total-tau at Exam-8 (GS: β -0.009, p 0.0005; FWS: β -0.226, p-value <0.0001). Chair stand speed was not associated with plasma markers; Aβ42 was not associated with function.
Conclusion: Grip strength and fast walk speed are associated with plasma markers of neurodegeneration in dementia-free middle aged and older individuals. Both these measures could be used as potential screening tools for identifying individuals at a higher risk for AD and related dementias alongside other validated markers.

Key words: Gait speed, grip strength, physical function, dementia, biomarkers.


 

Introduction

In recent years, there has been much investigative effort to identify biomarkers of preclinical/prodromal Alzheimer’s Disease (AD). These biomarkers would help stage individuals in terms of risk of developing dementia and would enable the inclusion of individuals with early pathology in secondary prevention trials. Currently available biomarkers include brain amyloid burden using PET imaging (1), brain tau burden using PET (2), CSF levels of amyloid beta and phosphorylated tau and measures of neurodegeneration (FDG PET, structural MRI and CSF total-tau) (3). However, none of these measures are suitable for large scale screening of populations as they are invasive or costly, and unavailable in primary care settings. In this context, there has been great interest in validating biomarkers measured from the peripheral circulation, as well as novel markers like sensory-motor function that can be quantified during clinical encounters (4).
Motor function has been studied as a biomarker of dementia due to its frequent coexistence with cognitive impairment. For instance, motor and cognitive impairments are the two most common phenotypes of physiological aging and often co-exist in older individuals even without clinical disease. More extensive motor and cognitive deficits that affect function co-exist in movement disorders where the primary deficit is motor and in neurodegenerative dementias where the primary deficit is cognitive. These associations have led to greater interest in the study of measures of physical function as potential predictive biomarkers of dementia (5). Slow gait speed has been found to be a predictive factor for incident dementia (6). Motor decline, specifically steep gait speed decline over time, is also predictive of dementia independent of baseline gait speed (7) and could be present as early as 12 years before a diagnosis of mild cognitive impairment (8). In the Framingham Heart Study (FHS), both slow gait speed and weak grip strength were predictors of incident dementia (9). Despite these findings, the precise mechanisms explaining the association between motor dysfunction and risk for dementia have not been elucidated. It is possible that early dementia-related pathology is disrupting motor circuits resulting in a slowing of gait speed among apparently normal subjects (10). If this is true, and gait speed and grip strength can reflect dementia related pathology in the brain, they should also correlate with blood markers. To test this, we examined the cross-sectional association between physical function measures (grip strength, gait speed and chair stand speed) and plasma markers of AD and neurodegeneration (Aβ40, Aβ42, Aβ42/Aβ40 ratio, total tau) in a population-based cohort. Additionally, we tested whether a longitudinal decline in physical function measures were predictive of total tau measures in a subsequent exam. Associations would provide evidence for the validity of physical function measures as pre-clinical markers for dementia risk; longitudinal relationships would provide information on temporal relationships with other markers and possible causal pathways.

 

Methods

Study sample

The FHS is an ongoing longitudinal study of cardiovascular risk factors, initiated in 1948 by enrolling the Original Cohort of 5209 participants. In 1971, the offspring of this cohort and their spouses were recruited to the Offspring Cohort (n=5124) and have been examined every 4-8 years, completing their ninth examination in 2014. During their 7th exam from 1998-2001, 3263 participants of the offspring cohort (out of 3539 who attended Exam 7) had their plasma Aβ40 and Aβ42 levels measured. These participants were also invited to attend a call back visit during which physical function was assessed. Call back visits were performed between 1999 and 2005 and 2543 participants aged 34-88 years completed this visit. For evaluating the relationship between physical function and plasma amyloid, we included data from 2026 participants who had plasma amyloid measures and had complete data on physical functioning –grip strength, chair stand speed and fast walk speed measured at the Exam 7 call back visit. During Exam 8, which was conducted between 2005 and 2008, plasma total-tau was measured on 2885 participants and physical function measures (grip strength and fast walk speed) were repeated. For testing the relationship between physical function and plasma total-tau, we included data from 2794 participants who had attended Exam 8 and had complete data on physical function and plasma total-tau at Exam 8. Figure 1 illustrates study measurements collected at different Exams and number of FHS Offspring participants for whom the measurements are available. All subjects provided informed consent, and the research was approved by the institutional review board at Boston University Medical Campus/ Boston Medical Center.

Figure 1. Measures collected at different Exams of the Framingham Offspring Cohort that are used in this study

 

Plasma Aβ assessment

During Exam 7, blood samples were collected in the morning in a supine fasting state, into K3-EDTA specimen tubes. Specimen tubes were centrifuged for 30 minutes at 1850g at 4°C. Plasma was then separated from cells after centrifugation and placed at –80°C, within 90 minutes of venipuncture. The original aliquots consisted 700 μL of plasma in 1mL cryogenic storage vials and were stored at –80°C until they were aliquoted in March 2012 to be frozen and shipped for the assay. Therefore, specimens were thawed once prior to Aβ measurement. New aliquots consisted of 150 μL of plasma in 0.5 mL cryogenic storage vials. All samples were analyzed at the Department of molecular pharmacology and experimental therapeutics of the Mayo Clinic, Jacksonville, FL, from June to August 2012. INNO-BIA plasma Aβ forms assays (Innogenetics, Ghent, Belgium), a multiplex microsphere-based Luminex xMAP technique that allows simultaneous analysis of Aβ40 and Aβ42 was used to quantify amyloid beta isoforms in plasma. Measurements were done in duplicate in a randomly selected sample (9% of all samples). Intra-assay coefficients of variations (CV) for Aβ40 and Aβ42 were 3.2% and 2.6% and inter-assay CVs were 10.5% and 7.6%, respectively. Analysis of 146 phantom samples showed intraclass correlation coefficients of 0.916 and 0.943 and CV of 4.8% and 3.5%, respectively.

Plasma total-tau assessment

After fasting overnight, participants provided morning blood samples during Exam 8. Samples were immediately centrifuged, aliquoted, and stored at –80°C and never thawed until analysis. Plasma samples were analyzed from February to March 2017 using a Simoa Tau 2.0 Kit and a Simoa HD-1 analyzer (Quanterix). This single-molecule ELISA (digital ELISA) uses monoclonal antibodies that react to all isoforms of tau, both normal and phosphorylated tau, is validated as fit-for-purpose research use only. The limit of detection is 0.019 pg/mL. The analytical range was between 0.06 and 360 pg/mL. The intra-assay coefficient of variation was 4.1%, and the inter-assay coefficient of variation was 7.5%.

Physical function

Motor testing including fast walking speed, chair stand speed and hand grip strength, was conducted by trained examiners who instructed participants regarding the tasks before testing. We chose fast walk speed rather than usual walk speed because of previously demonstrated associations with dementia in the FHS.(9) Participants were asked to walk on a 4-meter course wearing comfortable shoes or socks. They were instructed to walk as fast as possible but were not allowed to jog or run. The measured time to walk the 4 meters course was recorded and walking speed was calculated in meters/second. Gait speed was measured to the nearest second during Exam 7 and to the nearest 100th of a second during Exam 8. Handgrip strength was tested using a Jamar Hydraulic Hand Dynamometer (Lafayette Instrument, Lafayette, IN), and measured in kilograms of force exerted. Participants were seated comfortably with the forearm resting on the chair arms and bent 90 degrees at the elbow. They were then instructed to exert their maximum hand force and grip the dynamometer for 5 seconds. This was repeated three times for each hand. The highest measurement was chosen as the final handgrip strength measure, irrespective of manual dominance. Chair stand speed was measured by recording the time taken by the participant to stand up from a chair 5 times, as fast as possible. Chair stand speed was calculated as number of stands performed per second. Physical function measures were obtained both at Exam 7 call-back visit and at Exam 8 (except for chair stand speed which was obtained only at the Exam 7 call-back visit).

Covariates

Covariates for the analyses were determined apriori based on their association between both predictors (physical function measures) and outcomes (plasma amyloid and total-tau levels). Covariates included age, sex, diabetes, cardiovascular disease, atrial fibrillation, smoking, APOE genotype (e4 carrier status), systolic blood pressure, waist-to-hip ratio, total cholesterol level, physical activity index and plasma homocysteine levels. Homocysteine levels were determined with the use of high-performance liquid chromatography with fluorometric detection. The coefficient of variation for this assay was 9 percent. Covariates were assessed at Exam 7 as well as Exam 8 and used for corresponding analyses. Waist-to-hip ratio and total homocysteine levels were not assessed at Exam 8; these were not included in cross-sectional analyses of total-tau and physical function at Exam 8.

Statistical Analysis

Baseline characteristics of the population at Exam 7 and Exam 8 were examined using means and proportions. Plasma total-tau and the Aβ42/Aβ40 ratio was log transformed due to their skewed distribution and all plasma amyloid and tau measures were standardized. The associations between physical function measures and plasma amyloid measures (Aβ40, Aβ42 and Aβ42/Aβ40 ratio) as well as plasma total-tau were examined using linear regression models that adjusted for pre-specified confounders. Models examined (a)physical function measures at Exam 7 and plasma amyloid measures at Exam 7 (b) physical function measures at Exam 8 and plasma total-tau at Exam 8 and (c) physical function measures at Exam 7 and plasma total-tau at Exam 8 (d) change in physical function measures between Exam 7 and 8 and plasma total-tau at Exam 8. Models adjusted for covariates in stages to examine attenuation of effects by confounders – Model 1 adjusted for age at exam when physical function was measured and sex, Model 2 additionally adjusted for vascular risk factors (diabetes, cardiovascular disease, atrial fibrillation, smoking, systolic blood pressure, waist-to-hip ratio, total cholesterol level, and physical activity index) and APOE e4 allele status. Lastly, model 3 additionally adjusted for plasma homocysteine. Interactions of physical function with sex were tested in all models.
Waist-to-hip ratio and homocysteine were not available at Exam 8, hence were not used in models considering physical function at Exam 8. Also, chair stand speed was not assessed at Exam 8, hence its association with plasma tau at Exam 8 or the association between change in chair stand time (between Exam 7 and 8) and tau at Exam 8 could not be examined.
As the different regression analyses included a slightly different sample, for evaluating baseline characteristics (Table 1), we included all study participants who had been included in any analyses, i.e., those who had at least one plasma measure (amyloid or tau) and at least one physical function measure (n=2366 for Exam 7, n=2860 for Exam 8). As gait speed was measured to different levels of precision at the two Exams, we conducted a sensitivity analysis rounding the Exam 8 gait speed to integer seconds as in Exam 7, and repeating the regression analyses.

Table 1. Descriptive Statistics* of FHS Offspring Cohort at Exams 7 and 8

*Mean (SD) or Median [Q1, Q3], unless otherwise specified; †Offspring sample who attended Exam 7 and has non-missing Exam 7 physical functioning and amyloid; ‡Offspring sample who attended Exam 8 and has non-missing Exam 8 physical functioning and tau; Abbreviations: N/A: Not available. CVD: cardiovascular disease. AF: atrial fibrillation

 

Results

Descriptive characteristics of the participants included in analyses are displayed in Table 1. The average age of the 2366 FHS Offspring participants in this study was 61 years at Exam 7; 46% of the sample was male. The mean plasma Aβ40 was 158.2 pg/mL (SD= 35.3) and Aβ42 was 43.5pg/mL (SD= 10.0). At Exam 8, the 2860 participants whose data were analyzed for this study had an average age of 66 years and 46% of the sample was male. The median (inter-quartile range) for total-tau in this sample was 3.85 (3.16-4.71) pg/mL.
As displayed in Table 2, cross-sectional analysis of Exam 7 measurements demonstrated that higher grip strength was independently associated with lower plasma Aβ40. In the fully adjusted model, a one-kilogram higher grip strength was associated with 0.006 standard deviation units lower plasma Aβ40 level (p=0.032). Grip strength was not associated with plasma Aβ42 or the Aβ42/Aβ40 ratio. Walk speed was associated with Aβ40 in the basic model that adjusted only for age and sex, but the association was attenuated and no longer significant when adjusted for vascular risk factors and APOE e4 status. Chair stand speed was not associated with Aβ40, and neither walk speed nor chair stand speed was associated with Aβ42 or the Aβ42/Aβ40 ratio.

Table 2. Associations between Physical function and Plasma Amyloid among FHS Offspring at Exam 7

 

Higher grip strength at Exam 8 was associated cross-sectionally with lower plasma total tau at Exam 8, after adjusting for all confounders (see Table 3). A 1 kg higher hand grip strength among participants was associated with 0.009 standard deviation units lower log total-tau (p=0.0005). Grip strength at Exam 7 was predictive of plasma total tau at Exam 8 in the final model. A 1 kg higher grip strength was associated with 0.010 standard deviation units lower log total-tau measured 5 years later (p=0.001).

Table 3. Associations between physical function measures at Exam 7 and plasma total-tau at Exam 8 among FHS Offspring

*log transformed for normality. N/A: Not available; †Model 1 adjusted for age at Exam (7 or 8) and Sex; ‡Model 2 additionally adjusted for diabetes, cardiovascular disease, atrial fibrillation, smoking, APOE4, systolic blood pressure, waist-to-hip ratio, total cholesterol level, and physical activity index, measured at Exam 7 when the predictor was physical function at Exam 7 or change in physical function measures (from Exam 7 to Exam 8), and at Exam 8 when the predictor was physical function at Exam 8. (except for waist-to-hip ratio which was not available at Exam 8); §Model 3 additionally adjusted for log of homocysteine, in analyses in which physical function at Exam 7 or change in physical function was the predictor.

 

Higher fast walk speed at Exam 8 was independently associated with lower plasma total-tau at Exam 8 after adjusting for available confounders. A 1 m/s higher walk speed was associated with a 0.226 standard deviation units lower log plasma total-tau among participants (p<0.0001). Fast walk speed at Exam 7 was associated with plasma total-tau at Exam 8 in models 1 and 2, but the association was attenuated after further adjustments for plasma homocysteine in model 3. Associations between chair stand speed at Exam 7 and plasma total-tau at Exam 8 were attenuated when adjusted for vascular risk factors and APOE e4 in model 2. Change in physical function measures between Exam 7 and 8 was not associated with plasma total-tau at Exam 8. Results of sensitivity analysis wherein gait speed at Exam 8 was rounded, were similar to those presented.

 

Discussion

In our study of the relationship between plasma markers of AD/neurodegeneration and physical function measures in a large population-based cohort that included middle aged and older individuals, we found that higher grip strength was associated with lower plasma Aβ40 and lower total-tau measured at the same time point, as well as lower plasma total-tau measured 5 years later. Additionally, faster fast walk speeds were cross-sectionally associated with lower plasma total-tau. These associations persisted after adjusting for multiple vascular risk factors indicating that physical function deficits in dementia-free middle-aged and older individuals, may be associated with neurodegenerative processes. Our findings have important implications in the search for early biomarkers of pre-clinical dementia. Although our results do not suggest large effects, they do suggest that certain physical function measures correlate with and may reflect neurodegeneration. However, it is likely that a combination of peripheral markers, including sensory-motor and fluid markers would need to be considered in for evaluating risk for dementia in middle aged and older individuals.
Amyloid deposition in the brain has been linked previously to motor deficits. In APP-PS1 mouse models, amyloid plaques were associated with poor motor coordination, myoclonus and pathological reflexes like limb flexion and paw clasping when suspended in air by the tail;(11) these deficits have correlated well with the extent of neuropathology.(12) Among cognitively normal women aged 50-69 years, higher PiB PET standardized uptake value ratios (SUVR) was cross-sectionally associated with poor performance in gait parameters(13) and longitudinally associated with declining performance in gait over time.(14) In a study of older adults, gait speed was significantly slower among the PiB positive, compared to PiB negative individuals; this relationship was attenuated by cognition and APOE e4.(15) The best validated fluid biomarker, CSF amyloid beta, lower levels of which signify greater amyloid accumulation in the brain, has demonstrated associations with physical function measures. Our study used plasma amyloid rather than PET or CSF levels and found associations between plasma Aβ40 and physical function measures. This was unexpected because Plasma Aβ40, unlike Aβ42, has not demonstrated a consistent relationship with AD in previous studies. Levels of Plasma Aβ40 and Aβ42 typically increase with age(16); studies have found Aβ40 levels reduced in AD(17) and lower levels associated with greater amyloid deposition.(18) On the other hand, there are also several studies that have demonstrated a lack of association between plasma Aβ40 and AD pathology elsewhere, unlike plasma Aβ42 or the Aβ42/Aβ40 ratio, which are more frequently associated.(19) Among Framingham Heart Study Offspring, from whom our data is derived, plasma Aβ40 was not associated with incident dementia, although plasma Aβ42 and Aβ42/Aβ40 were predictive.(20) In the context of mixed results regarding plasma Aβ40, further evaluation of the relationship with function, with more sensitive and reliable assays in larger and novel cohorts, with consideration of cardiovascular and cerebrovascular risk factors(21) is warranted. It is notable that higher plasma levels of Aβ40 have been found to be associated with increased risk of mortality(22) and diffuse cerebral small vessel disease.(23) Hence it is possible that plasma Aβ40 levels may be reflecting other pathophysiological processes that influence physical function in older adults, and not just amyloid deposition per se.
Tau is a microtubule associated protein that is released during neuronal degeneration. In conditions like AD or other tauopathies, Tau is also truncated and/or phosphorylated and accumulates as neurofibrillary tangles. Although amyloid accumulation is considered the initial insult in AD, there is evidence that tau can also accumulate independently of amyloid in AD.(24) PET assessment of tau in the brain, as well as elevated CSF phosphorylated tau are sensitive and specific biomarkers of AD.(25) Levels of CSF phosphorylated tau correlates with the magnitude of neurofibrillary tangle pathology in the neocortex,(26) whereas total-tau has been shown to reflect the amount of neuronal damage. Our findings, however pertain to total tau in plasma where full-length tau is the predominant isoform. This may come mostly from peripheral sources rather than the brain(27) and has only weak correlations with CSF total-tau. However, there is evidence that plasma tau is indeed higher in AD(28) and can complement CSF Tau for an accurate diagnosis.(29). Higher plasma total-tau has also been associated with poorer cognitive function, lower hippocampal volume and higher risk for incident dementia.(30) Therefore, our finding that both grip strength and fast walk speed are cross-sectionally associated with plasma total-tau, and that grip strength may predict plasma total-tau several years later has important connotations. If physical function measures can be used to estimate neurodegenerative processes, this could serve as an important clinical screening measure, along with other biomarkers, to identify individuals at risk.
The co-existence of motor and cognitive dysfunction is a well-recognized phenomenon in physiological as well as pathological aging. A decline in muscle strength as well as cognitive functioning which does not impair function is common in physiological aging. For instance, among older adults without dementia, a “motoric cognitive risk syndrome” characterized by a combination of self-reported cognitive complaints and slow gait has been recognized as a pre- dementia syndrome (31). In “pathological aging,” specifically in neurodegenerative and movement disorders, cognitive and motor symptoms often co-exist. Patients with Primary Movement disorders like Parkinson’s disease, Multiple System Atrophy, Progressive Supranuclear Palsy and Corticobasal Degeneration have been found to have deficiencies in cognitive function, while motor signs are a common feature in Dementia with Lewy Bodies, Alzheimer’s Dementia, and Frontotemporal Dementia (32). In these later stages of dementia, disruption of cholinergic transmission likely mediated by amyloid deposition may explain the presence of motor symptoms, as observed in a study by Schirinzi et. al, using Transcranial Magnetic Stimulation (TMS) of the motor cortex and a protocol of Short Latency Afferent Inhibition (SAI) to demonstrate reduced afferent inhibition among those with dementia (33). However, the mechanism of early subtle motor signs in preclinical dementia require further elucidation. Our findings suggest that motor signs in preclinical dementia may have stronger correlation with neurodegeneration (Total Tau) rather than amyloid deposition (Aβ42). In neurodegenerative processes, synaptic dysfunction (“synaptopathy”) may be present even before evidence of abnormal protein deposition, and may be driving motor and cognitive phenomena in pre-clinical dementia (32). In fact, it has been shown that the severity of cognitive loss in AD correlates with synaptic dysfunction rather than abnormal protein deposition (34, 35). Synaptopathy leads to loss of synaptic plasticity (activity dependent modifications of synaptic strength) which is the neurobiological substrate of learning and memory. Study of plasticity of M1 area in human brains by non-invasive brain stimulation techniques would therefore likely provide more information about the underlying mechanisms of motor dysfunction in preclinical neurodegenerative disease (36).
Our findings highlight the potential role of grip strength as a marker of preclinical dementia. Poor grip strength is a well-known component of the frailty syndrome alongside slow gait speed and is associated with several poor health outcomes including mortality among older adults. More recently, there has been increasing evidence regarding the association between grip strength and cognitive function (37). However, just as in the case of gait speed, the neurophysiological underpinnings of this relationship are not very clear. While a weak grip strength may reflect poor muscle strength to a large extent, other factors like diminished neural capacity may also factor in, by reducing neuromuscular activation and recruitment of motor units (38). Additionally, cognitive deficits limit hand dexterity which is an important part of hand grip strength. Our study has identified significant association between grip strength and total tau levels among individuals without dementia indicating that grip strength may be affected by subclinical neurodegenerative processes. Grip strength assessment is non-invasive and brief and could be a potential screening tool in geriatric care settings for identifying individuals at high risk for dementia.
Our study has several strengths. We had a large community living sample of middle and older aged individuals to test associations. We also had multiple functional measures and data on covariates for adjustment of multiple confounders. However, our study does have limitations. Firstly, this study is observational, and we cannot attribute causal associations. Secondly, we have used “fast walk speed” rather than “usual walk speed” as the gait measure although “usual gait speed” is more commonly used and has been more extensively studied for its association with dementia outcomes. We chose to do this as fast walk speed has been shown to be associated with incident dementia in the Framingham cohort (20). Fast walk speed has been shown to have discriminative power, alongside other gait measures like usual gait speed, steps per meter and dual task gait speed, in distinguishing dementia (39). Thirdly, we have not normalized gait speed for leg length, which may be responsible for gender differences, as this was not measured in our study. Lastly, plasma assays for amyloid and tau are being competitively improved, with enhanced sensitivity and specificity, as in the case of P tau 217 (40); future studies with these more valid assays may need to be done for more comprehensive assessment of AD biomarkers.

 

Conclusion

In a sample of cognitively normal middle aged and older adults, higher grip strength and fast walk speed were associated with lower plasma total-tau and higher grip strength was associated with lower plasma amyloid β40. These results provide additional evidence for studying grip strength and gait speed as potential markers of pre-clinical neurodegeneration and evaluating them as potential screening tools for identifying individuals at a higher risk for dementia alongside other validated markers. Future research should examine the correlation between functional measures and PET as well as how brain plasticity measured using brain stimulation techniques may explain motor signs in preclinical dementia.

 

Funding: The Framingham Heart Study is supported by the National Heart, Lung, and Blood Institute (contract no. N01-HC-25195, no. HHSN268201500001I and 75N92019D00031) and by grants from the National Institute on Aging (R01 AG0059421, R01 AG054076, R01 AG049607, R01 AG058589, R01 AG059421, U01 AG049505, U01 AG052409, R01 AG063507 and R01 AG066524) and the National Institute of Neurological Disorders and Stroke (NS017950 and UH2 NS100605). The sponsors had no role in the design and conduct of the study; in the collection, analysis, and interpretation of data; in the preparation of the manuscript; or in the review or approval of the manuscript.

Acknowledgements: We thank the Framingham Heart Study participants for donating their time to our research.

Conflicts of Interest: None of the authors report a conflict of interest.

 

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