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Selective Serotonin Reuptake Inhibitor Pharmaco-Omics: Mechanisms and Prediction.

ABSTRACT: Selective serotonin reuptake inhibitors (SSRIs) are a standard of care for the pharmacotherapy of patients suffering from Major Depressive Disorder (MDD). However, only one-half to two-thirds of MDD patients respond to SSRI therapy. Recently, a "multiple omics" research strategy was applied to identify genetic differences between patients who did and did not respond to SSRI therapy. As a first step, plasma metabolites were assayed using samples from the 803 patients in the PGRN-AMPS SSRI MDD trial. The metabolomics data were then used to "inform" genomics by performing a genome-wide association study (GWAS) for plasma concentrations of the metabolite most highly associated with clinical response, serotonin (5-HT). Two genome-wide or near genome-wide significant single nucleotide polymorphism (SNP) signals were identified, one that mapped near the TSPAN5 gene and another across the ERICH3 gene, both genes that are highly expressed in the brain. Knocking down TSPAN5 and ERICH3 resulted in decreased 5-HT concentrations in neuroblastoma cell culture media and decreased expression of enzymes involved in 5-HT biosynthesis and metabolism. Functional genomic studies demonstrated that ERICH3 was involved in clathrin-mediated vesicle formation and TSPAN5 was an ethanol-responsive gene that may be a marker for response to acamprosate pharmacotherapy of alcohol use disorder (AUD), a neuropsychiatric disorder highly co-morbid with MDD. In parallel studies, kynurenine was the plasma metabolite most highly associated with MDD symptom severity and application of a metabolomics-informed pharmacogenomics approach identified DEFB1 and AHR as genes associated with variation in plasma kynurenine levels. Both genes also contributed to kynurenine-related inflammatory pathways. Finally, a multiply replicated predictive algorithm for SSRI clinical response with a balanced predictive accuracy of 76% (compared with 56% for clinical data alone) was developed by including the SNPs in TSPAN5, ERICH3, DEFB1 and AHR. In summary, application of a multiple omics research strategy that used metabolomics to inform genomics, followed by functional genomic studies, identified novel genes that influenced monoamine biology and made it possible to develop a predictive algorithm for SSRI clinical outcomes in MDD. A similar pharmaco-omic research strategy might be broadly applicable for the study of other neuropsychiatric diseases and their drug therapy.

SUBMITTER: Nguyen TTL

PROVIDER: S-EPMC7836019 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Selective Serotonin Reuptake Inhibitor Pharmaco-Omics: Mechanisms and Prediction.

Nguyen Thanh Thanh L TTL Liu Duan D Ho Ming-Fen MF Athreya Arjun P AP Weinshilboum Richard R

Frontiers in pharmacology 20210111

Selective serotonin reuptake inhibitors (SSRIs) are a standard of care for the pharmacotherapy of patients suffering from Major Depressive Disorder (MDD). However, only one-half to two-thirds of MDD patients respond to SSRI therapy. Recently, a "multiple omics" research strategy was applied to identify genetic differences between patients who did and did not respond to SSRI therapy. As a first step, plasma metabolites were assayed using samples from the 803 patients in the PGRN-AMPS SSRI MDD tri ...[more]

PMID: 33510640

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Project description:Importance:In 2006, the US Food and Drug Administration (FDA) issued an advisory warning on the risk of serotonin syndrome with concomitant use of triptans and selective serotonin reuptake inhibitor (SSRI) or selective norepinephrine reuptake inhibitor (SNRI) antidepressants, but the true risk of serotonin syndrome in these patients remains unknown. Objective:To assess the risk of serotonin syndrome with concomitant use of triptans and SSRI or SNRI antidepressants. Design, Setting, and Participants:This study used electronic health record data from the Partners Research Data Registry (RPDR) to identify patients who had received an International Classification of Diseases, Ninth Revision diagnosis compatible with serotonin syndrome who had been coprescribed triptans and SSRI or SNRI antidepressants in the Greater Boston, Massachusetts, area from January 1, 2001, through December 31, 2014 (14 years). Clinical information was extracted to determine whether the case met formal diagnostic criteria and had coprescription within a calendar year. Both conservative and broad case definitions were used to better characterize the spectrum of risk. Data analysis was performed from November 23, 2016, to July 15, 2017. Main Outcomes and Measures:Incidence of serotonin syndrome. Results:The RPDR search revealed 47?968 (±3) unique patients who were prescribed triptans during the 14-year period of the study. A total of 19?017 (±3) patients were coprescribed triptans and antidepressants during the study, with a total of 30?928 person-years of exposure. Serotonin syndrome was suspected in 17 patients. Only 2 patients were classified as having definite serotonin syndrome (incidence rate, 0.6 cases per 10?000 person-years of exposure; 95% CI, 0.0-1.5). Five patients were classified as having possible serotonin syndrome (incidence rate with these 5 cases added to the 2 definite cases, 2.3 cases per 10?000 person-years of exposure; 95% CI, 0.6-3.9). The proportion of patients with triptan prescriptions who were coprescribed an SSRI or SNRI antidepressant was relatively stable during the study, ranging from 21% to 29%. Conclusions and Relevance:The risk of serotonin syndrome associated with concomitant use of triptans and SSRIs or SNRIs was low. Coprescription of these drugs is common and did not decrease after the 2006 FDA advisory. Our results cast doubt on the validity of the FDA advisory and suggest that it should be reconsidered.

Project description:Animal studies using selective serotonin reuptake inhibitors (SSRIs) and learning paradigms have demonstrated that serotonin is important for flexibility in executive functions and learning. SSRIs might facilitate relearning through neuroplastic processes and thus exert their clinical effects in psychiatric diseases where cognitive functioning is affected. However, translation of these mechanisms to humans is missing. In this randomized placebo-controlled trial, we assessed functional brain activation during learning and memory retrieval in healthy volunteers performing associative learning tasks aiming to translate facilitated relearning by SSRIs. To this extent, seventy-six participants underwent three MRI scanning sessions: (1) at baseline, (2) after three weeks of daily associative learning and subsequent retrieval (face-matching or Chinese character-noun matching) and (3) after three weeks of relearning under escitalopram (10 mg/day) or placebo. Associative learning and retrieval tasks were performed during each functional MRI (fMRI) session. Statistical modeling was done using a repeated-measures ANOVA, to test for content-by-treatment-by-time interaction effects. During the learning task, a significant substance-by-time interaction was found in the right insula showing a greater deactivation in the SSRI cohort after 21 days of relearning compared to the learning phase. In the retrieval task, there was a significant content-by-time interaction in the left angular gyrus (AG) with an increased activation in face-matching compared to Chinese-character matching for both learning and relearning phases. A further substance-by-time interaction was found in task performance after 21 days of relearning, indicating a greater decrease of performance in the placebo group. Our findings that escitalopram modulate insula activation demonstrates successful translation of relearning as a mechanism of SSRIs in human. Furthermore, we show that the left AG is an active component of correct memory retrieval, which coincides with previous literature. We extend the function of this region by demonstrating its activation is not only stimulus dependent but also time constrained. Finally, we were able to show that escitalopram aids in relearning, irrespective of content.

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Selective Serotonin Reuptake Inhibitor Pharmaco-Omics: Mechanisms and Prediction.

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Selective Serotonin Reuptake Inhibitor Pharmaco-Omics: Mechanisms and Prediction.

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