NMR-based serum metabolomics of dementia patients and search for metabolic biomarkers associated with cognitive decline.

Cognitive decline (CD) and dementia are major age-associated neurodegenerative conditions lacking minimally invasive biomarkers that reflect underlying disease biology. Systemic metabolic alterations closely mirror brain bioenergetic dysfunction and may provide accessible indicators of disease progression. This study applied quantitative 1H NMR-based serum metabolomics to identify metabolic signatures associated with cognitive decline and to evaluate their diagnostic relevance. The serum samples from individuals with cognitive decline (CD, n = 40) and cognitively normal controls (NCD, n = 54) were analyzed using high-field 800 MHz 1H NMR spectroscopy. Multivariate (PCA, PLS-DA, OPLS-DA, Random Forest) and univariate statistical analyses were performed to explore their discriminatory performance. Receiver operating characteristic (ROC) analysis evaluated diagnostic performance, and correlations with Mini-Mental State Examination (MMSE) scores assessed clinical relevance. Thirty-three metabolites and key metabolic ratios were quantified. CD subjects showed significantly increased glucose, pyruvate, acetate, creatine, and mannose, while lactate, Leucine, Methanol, Valine, and Histidine were decreased. Metabolic ratios including glutamine-to-glucose (QGR), alanine-to-glucose (AGR), and histidine-to-tyrosine (HTR) were markedly reduced. AGR and QGR further declined with increasing disease severity and AGR positively correlated with MMSE scores. ROC analysis showed promising discriminatory performance within the study cohort for QGR (AUC = 0.876), AGR (AUC = 0.840), and HTR (AUC = 0.822). The observed metabolic pattern is consistent with alterations in systemic energy metabolism, amino-acid homeostasis and metabolic flexibility. These findings support the concept of dementia as a disorder of metabolic network dysregulation and highlight NMR-based serum metabolomics as a promising approach for objective disease assessment and progression monitoring.