Abstract

AbstractBackgroundPhysical activity is a modifiable behavioral factor that could delay the development of Alzheimer’s disease. Although metabolites detected in the brain correspond to neuronal integrity and neurodegenerative pathologies, we do not clearly understand the effect of physical activity interventions on brain metabolites. The purpose of this systematic review and meta‐analysis was to assess the effect of physical activity on brain metabolites measured by magnetic resonance spectroscopy (MRS).MethodsA systematic search was performed in PubMed, Embase, Web of Science and CINAHL from database inception to November 2022. Eight studies were integrated into the final systematic review and meta‐analysis.ResultsAmong included studies, 5 of the studies were randomized control designs, 1 study was an observational longitudinal study, 1 study was an observational cross‐sectional design, and 1 study was a case‐control design study. These studies involved 312 participants with mean age from 23 to 72. Physical activity interventions included cycling, running, and yoga. We found multiple metabolites are associated with physical activity including Myo‐inositol, choline (Cho), N‐acetyl aspartate (NAA), creatine, glutamate, and glutamine. The brain areas studied in reviewed articles included the hippocampus, frontal, occipital, or thalamus. From the quantitative synthesis, NAA/ Cho was higher in the physical activity group (effect size (ES) = ‐0.30, p = 0.03) than in the control group. However, for NAA (ES = ‐0.22, p = 0.08) and NNA/Cr (ES = 0.03, p = 0.07), the difference between the physical activity group and the control group was not statistically significant.ConclusionEvidence shows that there have been attempts to understand the relationship between physical activity and metabolites. The meta‐analysis demonstrates physical activity may affect changes in NAA/Cho. However, caution needs to be accompanied when interpreting the direct association between physical activity and different brain metabolites due to insufficient data, publication bias, and heterogeneity.

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