Genetic Associations between Delusional Disorder and Paranoid Schizophrenia: A Novel Etiologic Approach
Bibliographic record
Abstract
OBJECTIVES: Genetic associations between delusional disorder and paranoid schizophrenia are not well understood, although involvement of biological factors has been suspected. We investigated the incidence of human leukocyte antigen (HLA) class I alleles in patients with delusional disorder and paranoid schizophrenia, first, to explore a possible immunogenetic etiology of these paranoid disorders and, second, to determine whether they share similar etiologic mechanisms. METHOD: We employed a nested case-control study design. Psychiatric reference data were available for 38,500 patients attending a hospital-based psychiatric outpatient department between 1998 and 2005. We enrolled 100 patients with delusional disorder and 50 patients with paranoid schizophrenia as the subject cases, using DSM-IV criteria. We considered equivalent numbers of healthy volunteers matched for age and ethnic background as control subjects. All subjects came from an India-born Bengali population. We applied the polymerase chain reaction-based molecular typing method to all patients and healthy subjects. RESULTS: The HLA-A*03 gene is significantly associated with delusional disorder as well as with paranoid schizophrenia. This HLA gene alone or in linkage disequilibrium with other HLA genes or other closely linked non-HLA genes may influence susceptibility to delusional disorder and paranoid schizophrenia. CONCLUSIONS: The study reveals important associations between HLA genes and paranoid disorders. Delusional disorder and paranoid schizophrenia may share similar etiologic mechanisms. This preliminary observation may help our understanding of the genetic basis of these paranoid disorders.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".