Associations of leptin levels with psychopathology, BDNF and inflammatory cytokines in patients with chronic schizophrenia as well as gender differences
Bibliographic record
Abstract
BACKGROUND: Metabolic syndrome significantly contributes to mortality among individuals suffering from chronic schizophrenia (CS), and there is a strong correlation between this condition and plasma leptin (LEP) levels. However, there are relatively few studies on the factors affecting leptin levels in chronic schizophrenia, and findings are often inconsistent. The purpose of this study was to investigate the leptin levels and their association with psychopathology, BDNF and inflammatory cytokines in patients with chronic schizophrenia, as well as potential gender differences. METHODS: The study enrolled 301 individuals diagnosed with chronic schizophrenia. Participants were assessed for psychotic symptoms, insomnia severity, and depressive symptoms using the Positive and Negative Syndrome Scale (PANSS), Insomnia Severity Index (ISI), and Calgary Depression Scale for Schizophrenia (CDSS), respectively. Leptin, BDNF and inflammatory cytokines levels were also detected. RESULTS: Among the patients, Log LEP levels were positively correlated with females, body mass index (BMI), systolic and diastolic blood pressures, Log BDNF, Log IL-6, and Log IL-17 A levels, and negatively correlated with the total score on the PANSS, as well as scores on the positive, negative, and general psychopathology subscales (all p < 0.05). Multiple linear regression analyses revealed that Log LEP levels were independently correlated with gender (β = 0.514, t = 15.601, p < 0.001), BMI (β = 0.053, t = 12.096, p < 0.001), diastolic blood pressure (β = 0.005, t = 2.334, p = 0.020), and Log IL-17 A levels (β = 0.062, t = 2.097, p = 0.037). Notably, these associations between leptin and the above factors were only observed in the male patients. CONCLUSIONS: A significant link was identified between leptin levels and the presence of psychotic symptoms, BDNF, and inflammatory cytokines (especially IL-6 and IL-17 A) in individuals suffering from chronic schizophrenia, with notable variations observed between genders. Future research, including more longitudinal studies and animal models, is necessary to delve deeper into these associations and uncover their underlying mechanisms.
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 | 0.000 | 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) | 0.001 | 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".