AI Insight
This study developed neurotransmitter-based polygenic scores to predict antidepressant treatment outcomes in patients with major depressive disorder. Researchers analyzed genetic variants in serotonergic, GABAergic, dopaminergic, and glutamatergic pathways across two patient cohorts treated with SSRIs for at least 4 weeks. The GABAergic polygenic score showed significant association with treatment response, with patients in the highest genetic risk group having 2.59-fold higher odds of responding to SSRI treatment compared to the lowest group.
Why it matters
If validated in independent studies, GABAergic polygenic scores could potentially help clinicians predict which patients with depression are more likely to respond to SSRI medications, enabling more personalized treatment approaches. This could reduce the trial-and-error period many patients experience when finding effective antidepressant therapy.
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⚠️ Preprint – Noch nicht peer-reviewed
Dieser Artikel wurde noch nicht von unabhängigen Experten begutachtet. Die Ergebnisse sind vorläufig und sollten mit Vorsicht interpretiert werden.
Biologically informed polygenic scores (PGSs) may help interpret genetic associations with treatment outcomes. Here, we computed neurotransmitter-based PGSs (NeuroPGSs) for patients with major depressive disorder (MDD) and assessed their association with SSRI treatment outcomes. By targeting genetic variants involved in key neurotransmission pathways, we developed PGSs for serotonergic (5228), gamma-aminobutyric acid (GABA, 4103), dopaminergic (7061), and glutamatergic (5690) variants. We leveraged data from two cohorts of patients who received SSRIs for at least 4 weeks: the International SSRI Pharmacogenomics Consortium (ISPC) and the Pharmacogenomics Research Network Antidepressants Medication Pharmacogenomics Study (PGRN-AMPS). Treatment response was defined as [≥]50% reduction from baseline depression symptoms, measured using 17-item Hamilton Rating Scale for Depression (HRSD-17) in ISPC and 16-item Quick Inventory of Depressive Symptomatology (QIDS-C16) in PGRN-AMPS. Remission was defined as HRSD-17 [≤]7 (ISPC) or QIDS-C16[≤]5 (PGRN-AMPS). The association between each NeuroPGS and antidepressant response or remission was evaluated using logistic regression models, adjusting for age, sex and five genetic principal components, with statistical significance determined at Benjamini Hochberg-adjusted p<0.05. The GABAergic-based PGS was associated with SSRI response (aOR per SD = 1.45, 95%CI: 1.14-1.85). Patients with the highest GABAergic PGS (10th decile) had 2.59-fold higher odds of response (95%CI: 1.46-4.60) compared to those with the lowest decile (1st decile). These exploratory findings support further evaluation of NeuroPGSs; independent replication and assessment of incremental predictive value are needed before clinical application. Keywords: Polygenic score; Neurotransmitters; GABAergic; depression; SSRIs; pharmacogenomics