Positive association between the <i>PDLIM5</i> gene and bipolar disorder in the Chinese Han population
Bibliographic record
Abstract
Background: Bipolar disorder is a widespread and severe brain disorder that is strongly affected by genetic factors. The PDZ and LIM domain 5 ( PDLIM5) gene encodes a protein as an Enigma homologue LIM domain protein, which has been widely reported as being expressed in various brain regions. The analysis of DNA microarrays in the frontal lobes of patients with bipolar disorder has indicated changes in the expression level of PDLIM5, and subsequent studies have suggested that PDLIM5 might play a role in susceptibility to bipolar disorder. We sought to examine the association between PDLIM5 and bipolar disorder. Methods: We recruited 502 patients with bipolar disorder and 507 controls from Anhui Province, China. We conducted a case–control study of 4 single-nucleotide polymorphisms (SNPs) of PDLIM5 that have been reported to be significantly associated with bipolar disorder in the Japanese and Chinese population: rs10008257, rs2433320, rs2433322 and rs2438146. Results: We found that rs2433322 showed significantly different frequencies between patients and controls ( p = 0.002). Three of the SNPs, rs10008257, rs2433320 and rs2438146, showed no statistical association with bipolar disorder; however, haplotypes constructed from 3 SNPs, rs2433320, rs2433322 and rs2438146, were significantly associated with bipolar disorder (global p = 0.004 after Bonferroni correction). Limitations: Our genetic association study only offered evidence for susceptibility of PDLIM5 to bipolar disorder, but the positive SNP rs2433322 could not indicate a direct cause of this complicated brain disorder. In addition, the 4 tagged SNPs that we selected could not cover the whole region of PDLIM5, thus additional reproducible studies of more SNPS in large non-Asian populations are needed. Conclusion: Our results suggest that PDLIM5 might play a role in susceptibility to bipolar disorder among the Chinese Han population.
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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) | 0.003 | 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".