Low blood S-methyl-5-thioadenosine is associated with postoperative delayed neurocognitive recovery
Bibliographic record
Abstract
Abstract Background Elderly individuals display metabolite alterations that may contribute to development of cognitive impairment following surgery and exposure to anesthesia. However, these relationships remain largely unexplored. We assessed altered metabolites following anesthesia/surgery in both mouse models and human patients to identify blood biomarkers of delayed neurocognitive recovery (dNCR). Methods We used metabolomics to evaluate metabolite levels in the brains of mice following exposure to anesthesia. We also clinically evaluated 67 elderly patients who had neck and maxillofacial tumor resection under general anesthesia. Presence of dNCR was assessed with the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). Preoperative and postoperative plasma metabolites were determined by widely targeted metabolomics. Results The brains of mice with anesthesia/surgery-induced cognitive dysfunction showed decreased S-methyl-5-thioadenosine (MTA) levels and activated MTA phosphorylase (MTAP). Mouse models also showed that preoperative administration of MTA could prevent inflammation and cognitive decline. In clinical patients, we detected lower preoperative serum MTA levels (adjusted OR: 0.094; 95% CI: 0.014–0.477; P = 0.008, per ng/mL) in those who developed dNCR following anesthesia/surgery. Further, anesthesia/surgery decreased serum MTA levels compared to preoperative levels (adjusted OR: 0.057; 95% CI: 0.005–0.376; P = 0.008, per ng/mL). Both low preoperative and postoperative blood MTA levels were associated with increased risk of postoperative dNCR. Conclusions These results suggest that anesthesia/surgery induces cognitive decline through pathways involving inflammation and methionine synthesis and that MTA could be a perioperative predictor of dNCR as well as a potential therapeutic target. Trial registration: This prospective observational cohort study was registered with clinicaltrials.gov (No. NCT05105451; May 28, 2021; Hong Jiang). The study was performed in 2021 to 2022 at the Shanghai Ninth People’s Hospital at Shanghai Jiao Tong University School of Medicine in Shanghai, China. Ethics approval was obtained from the Ethics Committee of Shanghai Ninth People’s Hospital (SH9H-2021-T120).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".