The interplay between SLC6A4 and HTR1A genetic variants that may lead to antidepressant failure
Bibliographic record
Abstract
The serotonin transporter (SLC6A4) and the serotonin autoreceptor (HTR1A) are two of the most extensively studied genes in the field of psychiatry, and their variants have been implicated in antidepressant response, specifically with selective serotonin reuptake inhibitors (SSRIs) which are widely regarded as the first-line medications for depression and anxiety. Variants of SLC6A4 and HTR1A have also been studied as risk factors for depression. In this retrospective study, we aim to investigate the relationship between all possible serotonin transporter (SLC6A4) and autoreceptor (HTR1A) variant expression combinations that may have contributed to the therapeutic failure of an SSRI and subsequent disability. In this study, we utilize data from a cohort of 302 European patients diagnosed with depression and/or anxiety who were referred to Personalized Prescribing Inc. (PPI) in 2022 as result of a mental health disability claim to determine whether statistical differences are present in this cohort as compared to general European population allele frequencies. Our data reveals the presence and relevance of significant differences in the presentation of SLC6A4 and HTR1A, specifically in a disability cohort, relative to the average European population. The SLC6A4 gene codes for the serotonin transporter; the SSRI drug target that aims to be blocked to prevent the recycling of serotonin, whereas the HTR1A plays an indirect role as an autoreceptor allowing serotonin levels to be maintained by the SSRI, as well as a direct role in modulating mood through post-synaptic serotonin interaction. This study has revealed statistically significant differences in the expression of these two genes together in increasing the likelihood of drug failure, specifically the presence of one or more G alleles at HTR1A rs6295 in combination with the SLC6A4 SS variant. The most significantly overrepresented combination in this cohort of patients suffering from depression and anxiety that have failed to achieve adequate symptom remission on previous SSRI trials is HTR1A rs6295 GG-SLC6A4 SS which is overrepresented in this study by over 74% at a p-value well below 0.01. Genotyping anti-depressant drug targets may play an important role in optimizing anti-depressant drug response and research developments for future therapies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".