Association between growth differentiation factor‐15 (GDF‐15) with neurofilament light chain (NfL) and lower cognitive function with mediation from pulse pressure
Bibliographic record
Abstract
BACKGROUND: Growth differentiation factor-15 (GDF-15) is an emerging biomarker of mitochondrial dysfunction which increases oxidative stress and inflammation. Pulse pressure (PP) is a potential putative factor in cognitive impairment due to pulsatile strain that disrupts cerebral blood flow. We investigate the association between GDF-15 with neurofilament light chain (NfL), a biomarker of neuroaxonal injury and cognitive function, with possible mediation by PP. METHOD: This was a cross-sectional study of 100 participants recruited from health screening and specialist outpatient clinics in a tertiary hospital. Plasma GDF-15 and NfL were measured with enzyme-linked immunosorbent assay. Montreal Cognitive Assessment (MoCA) was used to assess cognitive function. The mediator was peripheral PP which was calculated from difference between systolic blood pressure and diastolic blood pressure. RESULT: The mean age was 55.6±12.9 years. The median GDF-15 level was 692.4 (IQR 465.3-911.6) pg/mL. GDF-15 was positively correlated with NfL (correlation coefficient 0.520; p <0.001) and negatively correlated with MoCA score (correlation coefficient -0.213; p = 0.036). In linear regression, log-transformed GDF-15 was associated with higher NfL and lower MoCA score with adjusted coefficients 1.33 (95%CI 0.69,1.98; p <0.001) and -1.20 (95%CI -2.13, -0.26; p = 0.013) respectively. Mediation analysis showed that PP accounted for 15.7% of association between GDF-15 and NfL (p = 0.046). CONCLUSION: GDF-15 was associated with higher NfL and lower cognitive function in older individuals, with mediation from PP. GDF-15 may play a potential role in cognitive impairment. These results may pave the way for future longitudinal studies and interventions targeting GDF-15 and even PP in an effort to screen and prevent cognitive impairment.
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 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".