Temporal Muscle Thickness as a New Biomarker: Its Association With Alzheimer Pathology and Cognitive Impairment in Chinese Adults
Bibliographic record
Abstract
ABSTRACT Background The association between skeletal muscle mass loss and cognitive decline remains unclear. Temporal muscle thickness (TMT) has been validated as an easily obtainable surrogate marker for muscle mass loss in neurological patients. This study was aimed at exploring whether a decline in TMT correlates with Alzheimer's disease ( AD )–related cognitive impairment and its underlying mechanisms. Methods This study was a cross‐sectional substudy of the Chinese preclinical AD study, which included data from 801 participants. TMT was measured using cranial magnetic resonance imaging. Appendicular skeletal muscle index (ASMI) was estimated using an anthropometric equation as a control. Cognitive function was assessed using a battery of standardised neuropsychological tests, and participants were categorised into three groups based on clinical diagnosis: normal cognition (NC), mild cognitive impairment (MCI) and AD . Functional performance was evaluated using the Functional Activities Questionnaire. Of the 801 participants, 733 underwent 18 F‐florbetapir PET scans to assess cerebral amyloid‐beta (Aβ) deposition. Additionally, 165 Aβ‐PET‐positive participants were randomly selected for further evaluation of cerebral tau burden using 18 F‐MK6240 PET. Results Significant differences in TMT measurements were observed by age and sex, with thinner TMT found in females and older adults. TMT was significantly associated with ASMI, handgrip strength and mobility. Regarding cognition, TMT, but not ASMI, was thinner in MCI and AD participants than those with NC. TMT was positively correlated with Montreal Cognitive Assessment‐Basic (MoCA‐B) scores ( r = 0.124, p = 0.001), independent of confounders such as age, sex, education level, nutritional risk, history of hypertension and apolipoprotein E ε4 genotype. Among cognitive domains, TMT was most closely associated with performance on the Auditory Verbal Learning Test recognition ( p < 0.05). Stratified analyses revealed that the correlation between TMT and MoCA‐B remained significant in MCI participants but not in AD participants. Multivariable logistic regression analysis showed that higher TMT was significantly associated with a lower risk of MCI (OR: 0.494, 95% CI: 0.287–0.849, p < 0.05) and a reduced likelihood of functional dependence (OR: 0.791, 95% CI: 0.670–0.935, p < 0.01). Furthermore, TMT was lower in participants with higher brain tau deposition and was negatively associated with tau PET Braak stages (both p < 0.01). Conclusions A decline in TMT was associated with worse cognitive function, increased cerebral tau deposition and impaired functional performance. TMT may serve as a simple, noninvasive and cost‐effective marker for MCI due to AD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".