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Record W4410153274 · doi:10.1038/s41397-025-00370-5

The interplay between SLC6A4 and HTR1A genetic variants that may lead to antidepressant failure

2025· article· en· W4410153274 on OpenAlexaff
Salma Toma Hanna, Mark Faiz, Sanjida Ahmed, Sara Temkit, Cristina Núñez, Feng C. Zhou

Bibliographic record

VenueThe Pharmacogenomics Journal · 2025
Typearticle
Languageen
FieldMedicine
TopicBipolar Disorder and Treatment
Canadian institutionsYork Central Hospital
Fundersnot available
KeywordsAntidepressantLead (geology)GeneticsPsychologyNeuroscienceBiologyPaleontology

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.330
Threshold uncertainty score0.467

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.021
GPT teacher head0.333
Teacher spread0.312 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2025
Admission routes1
Has abstractyes

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