TGF-β1 is associated with deficits in cognition and cerebral cortical thickness in first-episode schizophrenia
Bibliographic record
Abstract
Background: Evidence indicates that cytokines are associated with cognitive deficits in schizophrenia; however, the underlying brain–behaviour mechanisms remain unclear. We hypothesized that aberrations in brain structural connectivity mediate the cytokine effect in schizophrenia. Methods: In this study, we recruited patients with first-episode schizophrenia ( n = 75, average illness duration 12.3 months, average medication period 0.6 days) and healthy controls ( n = 44) of both sexes. We first conducted whole-blood RNA sequencing to detect differentially expressed genes. We also explored transcriptomic data on the dorsal lateral prefrontal cortices (dlPFC) retrieved from the CommonMind Consortium for gene functional clustering; we measured plasma transforming growth factor β1 (TGF-β1) levels by enzyme-linked immunosorbent assay; we acquired high-resolution T 1 -weighted MRI data on cortical thickness MRI; and we assessed cognitive function using the validated Chinese version of the MATRICS Consensus Cognitive Battery. We compared these parameters in patients with schizophrenia and controls, and analyzed their associations. Results: Patients with schizophrenia had higher TGF-β1 at both the mRNA level (log 2 fold change = 0.24; adjusted p = 0.026) and the protein level (12.85 ± 6.01 μg/mL v. 8.46 ± 5.15 μg/mL, adjusted p < 0.001) compared to controls. Genes coexpressed with TGFB1 in the dlPFC were less abundant in patients with schizophrenia compared to healthy controls. In patients with schizophrenia, TGF-β1 protein levels were inversely correlated with cortical thickness, especially of the lateral occipital cortex ( r = −0.47, adjusted p = 0.001), and with the MATRICS Consensus Cognitive Battery visual learning and memory domain ( r = −0.50, adjusted p < 0.001). We found a complete mediation effect of the thickness of the lateral occipital cortex on the negative relationship between TGF-β1 and visual cognition ( p < 0.05). Limitations: We did not explore the effect of other blood cytokines on neurocognitive performance and cortical thickness. Participants from the CommonMind Consortium did not all have first-episode schizophrenia and they were not all antipsychotic-naive, so we could not exclude an effect of antipsychotics on TGF-β1 signalling in the dlPFC. The sample size and cross-sectional design of our study were additional limitations. Conclusion: These findings highlighted an association between upregulated blood levels of TGF-β1 and impairments in brain structure and function in schizophrenia.
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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 | 0.001 |
| 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) | 0.000 | 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".