Analysis of treatment-resistant schizophrenia and 384 markers from candidate genes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The treatment of patients with schizophrenia who fail to respond to antipsychotics is a major challenge and the proportion of treatment-resistant patients is estimated to be 20 to 40%. There are few genetic association studies that have compared resistant versus non-resistant schizophrenic patients; however, many genetic association studies focusing on antipsychotic response have been published. This contribution investigates the genetics of treatment-resistant schizophrenia, testing 384 candidate gene loci related to the neurobiology of the disease. First, we identified a subgroup of treatment-resistant patients in a sample of 240 schizophrenia patients using the American Psychiatric Association criteria and then we genotyped all patients using a custom Illumina Bead Chip comprising of 384 single nucleotide polymorphisms. We screened all markers for nominal significance and for statistical significance after multiple-testing correction. The most significant single nucleotide polymorphism was the rs2152324 marker in the NALCN gene (P=0.004); however, after the FDR correction, the P-value was not significant. Our analysis of 384 markers across candidate genes did not indicate any robust association with treatment-resistant schizophrenia. However, this phenotype can be assessed retrospectively in cross-sectional studies and these preliminary results point out the importance of choosing alternative phenotypes in psychiatric pharmacogenetics.
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.
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 it