Serum dysregulation of serine and glycine metabolism as predictive biomarker for cognitive decline in frail elderly subjects
Bibliographic record
Abstract
Frailty is a common age-related clinical syndrome characterized by a decline in the function of multiple organ systems, increased vulnerability to stressors, and a huge socio-economic burden. Despite recent research efforts, the physiopathological mechanisms underlying frailty remain elusive and biomarkers able to predate its occurrence in the early stages are still lacking. Beyond its physical component, cognitive decline represents a critical domain of frailty associated with higher risk of adverse health outcomes. We measured by High-Performance Liquid Chromatography (HPLC) a pool of serum amino acids including L-glutamate, L-aspartate, glycine, and D-serine, as well as their precursors L-glutamine, L-asparagine, and L-serine in a cohort of elderly subjects encompassing the entire continuum from fitness to frailty. These amino acids are known to orchestrate excitatory and inhibitory neurotransmission, and in turn, to play a key role as intermediates of energy homeostasis and in liver, kidney, muscle, and immune system metabolism. To comprehensively assess frailty, we employed both the Edmonton Frail Scale (EFS), as a practical tool to capture the multidimensionality of frailty, and the frailty phenotype, as a measure of physical function. We found that D-serine and D-/Total serine ratio were independent predictors of EFS but not of physical frailty. Furthermore, higher levels of glycine, glycine/L-serine and D-/Total serine were associated with worse cognition and depressive symptoms in the frail group. These findings suggest that changes in peripheral glycine and serine enantiomers homeostasis may represent a novel biochemical correlate of frailty.
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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 | 0.000 | 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".