FKBP5 Genotype Linked to Combined PTSD-Depression Symptom in Chinese Earthquake Survivors
Bibliographic record
Abstract
Background: Post-traumatic stress disorder (PTSD) and depression are common mental disorders in individuals experiencing traumatic events. To date, few studies have studied the relationship between genetic basis and phenotypic heterogeneity of traumatized individuals. The present study examined the effects of four FKBP5 SNPs (rs1360780, rs3800373, rs9296158, and rs9470080) in four postdisaster groups (low symptom, predominantly depressive, predominantly PTSD, and combined PTSD-depression symptom groups) as identified by latent profile analysis. Methods: A total of 1,140 adults who experienced the 2008 Wenchuan earthquake participated in our study. Earthquake-related trauma, PTSD, and depressive symptoms were measured using standard psychometric instruments. The four FKBP5 SNPs were genotyped using a custom-by-design 2 × 48-Plex SNP scan™ Kit. Results: After adjusting for covariates, the main and gene–environment interaction effects of rs9470080 were all significant when the combined PTSD-depression group was compared with the low symptoms, predominantly depression and predominantly PTSD groups. rs9470080 TT genotype carriers had a higher risk of developing high co-occurring PTSD and depression symptoms than the C allele carriers. However, when trauma exposure was severe, the TT genotype carriers and C allele carriers did not differ in the risk of developing high co-occurring PTSD and depressive symptoms. The other three SNPs demonstrated no significant effects. Moreover, the rs3800373-rs9296158-rs1360780-rs9470080 haplotype A-G-C-T was found significantly associated with combined PTSD-depression symptoms. Conclusion: Our findings support the genetic basis of phenotypic heterogeneity in people exposed to trauma. Furthermore, the results reveal the possibility that the variants of FKBP5 gene may be associated with depression-PTSD comorbidity.
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.
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 | 0.000 | 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) | 0.002 | 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".