A Study of HLA-Linked Genes in a Monosymptomatic Psychotic Disorder in an Indian Bengali Population
Bibliographic record
Abstract
OBJECTIVE: The etiology of delusional disorder is imperfectly understood. Involvement of biological factors has long been suspected. We examined the incidence of class I human leukocyte antigens (HLAs) in patients with delusional disorder to understand the role of HLA genes and explore a possible immunogenetic etiology for delusional disorder. METHODS: We used a nested case-control study design. Psychiatric reference data were available for 27 500 patients registered between 1998 and 2003. Initially, we enrolled 150 patients with delusional disorder from the India-born Bengali population, using DSM-IV diagnostic criteria. After longitudinal follow-up, 80 patients were found to have only delusional disorder, while the remaining 70 patients represented different illnesses with paranoid symptoms and were excluded. We performed serological typing on all 150 patients and applied the polymerase chain reaction-based high-resolution molecular typing method to the 80 patients with delusional disorder. Eighty healthy donors of the same ethnic background, matched for age, sex, and other socioeconomic variables, formed the control group. RESULTS: Some of the HLA alleles were associated with delusional disorder, and the gene HLA-A*03 was found to be significantly more frequent. This gene may influence patients' susceptibility to delusional disorder. CONCLUSION: The study reveals important associations between HLA genes and delusional disorder. This preliminary observation may help our understanding of this disorder's genetic basis.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".