Meta‐analysis of association between obsessive‐compulsive disorder and the 3′ region of neuronal glutamate transporter gene <i>SLC1A1</i>
Bibliographic record
Abstract
The neuronal glutamate transporter gene SLC1A1 is a candidate gene for obsessive-compulsive disorder (OCD) based on linkage studies and convergent evidence implicating glutamate in OCD etiology. The 3' end of SLC1A1 is the only genomic region with consistently demonstrated OCD association, especially when analyzing male-only probands. However, specific allele associations have not been consistently replicated, and recent OCD genome-wide association and meta-analysis studies have not incorporated all previously associated SLC1A1 SNPs. To clarify the nature of association between SLC1A1 and OCD, pooled analysis was performed on all available relevant raw study data, comprising a final sample of 815 trios, 306 cases and 634 controls. This revealed weak association between OCD and one of nine tested SLC1A1 polymorphisms (rs301443; uncorrected P = 0.046; non-significant corrected P). Secondary analyses of male-affecteds only (N = 358 trios and 133 cases) demonstrated modest association between OCD and a different SNP (rs12682807; uncorrected P = 0.012; non-significant corrected P). Findings of this meta-analysis are consistent with the trend of previous candidate gene studies in psychiatry and do not clarify the putative role of SLC1A1 in OCD pathophysiology. Nonetheless, it may be important to further examine the potential associations demonstrated in this amalgamated sample, especially since the SNPs with modest associations were not included in the more highly powered recent GWAS or in a past meta-analysis including five SLC1A1 polymorphisms. This study underscores the need for much larger sample sizes in future genetic association studies and suggests that next-generation sequencing may be beneficial in examining the potential role of rare variants in OCD.
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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 | 0.011 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.030 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".