Browsing by Subject "Serotonin Uptake Inhibitors"

Now showing 1 - 9 of 9
  • Thumbnail Image
    ItemOpen Access
    Alterations in acylcarnitines, amines, and lipids inform about the mechanism of action of citalopram/escitalopram in major depression.
    (Translational psychiatry, 2021-03-02) MahmoudianDehkordi, Siamak; Ahmed, Ahmed T; Bhattacharyya, Sudeepa; Han, Xianlin; Baillie, Rebecca A; Arnold, Matthias; Skime, Michelle K; John-Williams, Lisa St; Moseley, M Arthur; Thompson, J Will; Louie, Gregory; Riva-Posse, Patricio; Craighead, W Edward; McDonald, William; Krishnan, Ranga; Rush, A John; Frye, Mark A; Dunlop, Boadie W; Weinshilboum, Richard M; Kaddurah-Daouk, Rima; Mood Disorders Precision Medicine Consortium (MDPMC)
    Selective serotonin reuptake inhibitors (SSRIs) are the first-line treatment for major depressive disorder (MDD), yet their mechanisms of action are not fully understood and their therapeutic benefit varies among individuals. We used a targeted metabolomics approach utilizing a panel of 180 metabolites to gain insights into mechanisms of action and response to citalopram/escitalopram. Plasma samples from 136 participants with MDD enrolled into the Mayo Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS) were profiled at baseline and after 8 weeks of treatment. After treatment, we saw increased levels of short-chain acylcarnitines and decreased levels of medium-chain and long-chain acylcarnitines, suggesting an SSRI effect on β-oxidation and mitochondrial function. Amines-including arginine, proline, and methionine sulfoxide-were upregulated while serotonin and sarcosine were downregulated, suggesting an SSRI effect on urea cycle, one-carbon metabolism, and serotonin uptake. Eighteen lipids within the phosphatidylcholine (PC aa and ae) classes were upregulated. Changes in several lipid and amine levels correlated with changes in 17-item Hamilton Rating Scale for Depression scores (HRSD17). Differences in metabolic profiles at baseline and post-treatment were noted between participants who remitted (HRSD17 ≤ 7) and those who gained no meaningful benefits (<30% reduction in HRSD17). Remitters exhibited (a) higher baseline levels of C3, C5, alpha-aminoadipic acid, sarcosine, and serotonin; and (b) higher week-8 levels of PC aa C34:1, PC aa C34:2, PC aa C36:2, and PC aa C36:4. These findings suggest that mitochondrial energetics-including acylcarnitine metabolism, transport, and its link to β-oxidation-and lipid membrane remodeling may play roles in SSRI treatment response.
  • Thumbnail Image
    ItemOpen Access
    Inflammation-Induced Histamine Impairs the Capacity of Escitalopram to Increase Hippocampal Extracellular Serotonin.
    (The Journal of neuroscience : the official journal of the Society for Neuroscience, 2021-07) Hersey, Melinda; Samaranayake, Srimal; Berger, Shane N; Tavakoli, Navid; Mena, Sergio; Nijhout, H Frederik; Reed, Michael C; Best, Janet; Blakely, Randy D; Reagan, Lawrence P; Hashemi, Parastoo
    Commonly prescribed selective serotonin reuptake inhibitors (SSRIs) inhibit the serotonin transporter to correct a presumed deficit in extracellular serotonin signaling during depression. These agents bring clinical relief to many who take them; however, a significant and growing number of individuals are resistant to SSRIs. There is emerging evidence that inflammation plays a significant role in the clinical variability of SSRIs, though how SSRIs and inflammation intersect with synaptic serotonin modulation remains unknown. In this work, we use fast in vivo serotonin measurement tools to investigate the nexus between serotonin, inflammation, and SSRIs. Upon acute systemic lipopolysaccharide (LPS) administration in male and female mice, we find robust decreases in extracellular serotonin in the mouse hippocampus. We show that these decreased serotonin levels are supported by increased histamine activity (because of inflammation), acting on inhibitory histamine H3 heteroreceptors on serotonin terminals. Importantly, under LPS-induced histamine increase, the ability of escitalopram to augment extracellular serotonin is impaired because of an off-target action of escitalopram to inhibit histamine reuptake. Finally, we show that a functional decrease in histamine synthesis boosts the ability of escitalopram to increase extracellular serotonin levels following LPS. This work reveals a profound effect of inflammation on brain chemistry, specifically the rapidity of inflammation-induced decreased extracellular serotonin, and points the spotlight at a potentially critical player in the pathology of depression, histamine. The serotonin/histamine homeostasis thus, may be a crucial new avenue in improving serotonin-based treatments for depression.SIGNIFICANCE STATEMENT Acute LPS-induced inflammation (1) increases CNS histamine, (2) decreases CNS serotonin (via inhibitory histamine receptors), and (3) prevents a selective serotonin reuptake inhibitor (SSRI) from effectively increasing extracellular serotonin. A targeted depletion of histamine recovers SSRI-induced increases in extracellular hippocampal serotonin.
  • Thumbnail Image
    ItemOpen Access
    Metabolomic signature of exposure and response to citalopram/escitalopram in depressed outpatients.
    (Translational psychiatry, 2019-07-04) Bhattacharyya, Sudeepa; Ahmed, Ahmed T; Arnold, Matthias; Liu, Duan; Luo, Chunqiao; Zhu, Hongjie; Mahmoudiandehkordi, Siamak; Neavin, Drew; Louie, Gregory; Dunlop, Boadie W; Frye, Mark A; Wang, Liewei; Weinshilboum, Richard M; Krishnan, Ranga R; Rush, A John; Kaddurah-Daouk, Rima
    Metabolomics provides valuable tools for the study of drug effects, unraveling the mechanism of action and variation in response due to treatment. In this study we used electrochemistry-based targeted metabolomics to gain insights into the mechanisms of action of escitalopram/citalopram focusing on a set of 31 metabolites from neurotransmitter-related pathways. Overall, 290 unipolar patients with major depressive disorder were profiled at baseline, after 4 and 8 weeks of drug treatment. The 17-item Hamilton Depression Rating Scale (HRSD17) scores gauged depressive symptom severity. More significant metabolic changes were found after 8 weeks than 4 weeks post baseline. Within the tryptophan pathway, we noted significant reductions in serotonin (5HT) and increases in indoles that are known to be influenced by human gut microbial cometabolism. 5HT, 5-hydroxyindoleacetate (5HIAA), and the ratio of 5HIAA/5HT showed significant correlations to temporal changes in HRSD17 scores. In the tyrosine pathway, changes were observed in the end products of the catecholamines, 3-methoxy-4-hydroxyphenylethyleneglycol and vinylmandelic acid. Furthermore, two phenolic acids, 4-hydroxyphenylacetic acid and 4-hydroxybenzoic acid, produced through noncanconical pathways, were increased with drug exposure. In the purine pathway, significant reductions in hypoxanthine and xanthine levels were observed. Examination of metabolite interactions through differential partial correlation networks revealed changes in guanosine-homogentisic acid and methionine-tyrosine interactions associated with HRSD17. Genetic association studies using the ratios of these interacting pairs of metabolites highlighted two genetic loci harboring genes previously linked to depression, neurotransmission, or neurodegeneration. Overall, exposure to escitalopram/citalopram results in shifts in metabolism through noncanonical pathways, which suggest possible roles for the gut microbiome, oxidative stress, and inflammation-related mechanisms.
  • Thumbnail Image
    ItemOpen Access
    Pharmacogenomics-Driven Prediction of Antidepressant Treatment Outcomes: A Machine-Learning Approach With Multi-trial Replication.
    (Clinical pharmacology and therapeutics, 2019-10) Athreya, Arjun P; Neavin, Drew; Carrillo-Roa, Tania; Skime, Michelle; Biernacka, Joanna; Frye, Mark A; Rush, A John; Wang, Liewei; Binder, Elisabeth B; Iyer, Ravishankar K; Weinshilboum, Richard M; Bobo, William V
    We set out to determine whether machine learning-based algorithms that included functionally validated pharmacogenomic biomarkers joined with clinical measures could predict selective serotonin reuptake inhibitor (SSRI) remission/response in patients with major depressive disorder (MDD). We studied 1,030 white outpatients with MDD treated with citalopram/escitalopram in the Mayo Clinic Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS; n = 398), Sequenced Treatment Alternatives to Relieve Depression (STAR*D; n = 467), and International SSRI Pharmacogenomics Consortium (ISPC; n = 165) trials. A genomewide association study for PGRN-AMPS plasma metabolites associated with SSRI response (serotonin) and baseline MDD severity (kynurenine) identified single nucleotide polymorphisms (SNPs) in DEFB1, ERICH3, AHR, and TSPAN5 that we tested as predictors. Supervised machine-learning methods trained using SNPs and total baseline depression scores predicted remission and response at 8 weeks with area under the receiver operating curve (AUC) > 0.7 (P < 0.04) in PGRN-AMPS patients, with comparable prediction accuracies > 69% (P ≤ 0.07) in STAR*D and ISPC. These results demonstrate that machine learning can achieve accurate and, importantly, replicable prediction of SSRI therapy response using total baseline depression severity combined with pharmacogenomic biomarkers.
  • Thumbnail Image
    ItemOpen Access
    Pharmacometabolomics of response to sertraline and to placebo in major depressive disorder - possible role for methoxyindole pathway.
    (PloS one, 2013-01) Zhu, Hongjie; Bogdanov, Mikhail B; Boyle, Stephen H; Matson, Wayne; Sharma, Swati; Matson, Samantha; Churchill, Erik; Fiehn, Oliver; Rush, John A; Krishnan, Ranga R; Pickering, Eve; Delnomdedieu, Marielle; Kaddurah-Daouk, Rima; Pharmacometabolomics Research Network
    Therapeutic response to selective serotonin (5-HT) reuptake inhibitors in Major Depressive Disorder (MDD) varies considerably among patients, and the onset of antidepressant therapeutic action is delayed until after 2 to 4 weeks of treatment. The objective of this study was to analyze changes within methoxyindole and kynurenine (KYN) branches of tryptophan pathway to determine whether differential regulation within these branches may contribute to mechanism of variation in response to treatment. Metabolomics approach was used to characterize early biochemical changes in tryptophan pathway and correlated biochemical changes with treatment outcome. Outpatients with MDD were randomly assigned to sertraline (n = 35) or placebo (n = 40) in a double-blind 4-week trial; response to treatment was measured using the 17-item Hamilton Rating Scale for Depression (HAMD17). Targeted electrochemistry based metabolomic platform (LCECA) was used to profile serum samples from MDD patients. The response rate was slightly higher for sertraline than for placebo (21/35 [60%] vs. 20/40 [50%], respectively, χ(2)(1)  = 0.75, p = 0.39). Patients showing a good response to sertraline had higher pretreatment levels of 5-methoxytryptamine (5-MTPM), greater reduction in 5-MTPM levels after treatment, an increase in 5-Methoxytryptophol (5-MTPOL) and Melatonin (MEL) levels, and decreases in the (KYN)/MEL and 3-Hydroxykynurenine (3-OHKY)/MEL ratios post-treatment compared to pretreatment. These changes were not seen in the patients showing poor response to sertraline. In the placebo group, more favorable treatment outcome was associated with increases in 5-MTPOL and MEL levels and significant decreases in the KYN/MEL and 3-OHKY/MEL; changes in 5-MTPM levels were not associated with the 4-week response. These results suggest that recovery from a depressed state due to treatment with drug or with placebo could be associated with preferential utilization of serotonin for production of melatonin and 5-MTPOL.
  • Thumbnail Image
    ItemOpen Access
    Platelet aggregation and mental stress induced myocardial ischemia: Results from the Responses of Myocardial Ischemia to Escitalopram Treatment (REMIT) study.
    (Am Heart J, 2015-04) Jiang, Wei; Boyle, Stephen H; Ortel, Thomas L; Samad, Zainab; Velazquez, Eric J; Harrison, Robert W; Wilson, Jennifer; Kuhn, Cynthia; Williams, Redford B; O'Connor, Christopher M; Becker, Richard C
    BACKGROUND: Mental stress-induced myocardial ischemia (MSIMI) is common in patients with ischemic heart disease (IHD) and associated with a poorer cardiovascular prognosis. Platelet hyperactivity is an important factor in acute coronary syndrome. This study examined associations between MSIMI and resting and mental stress-induced platelet activity. METHODS: Eligible patients with clinically stable IHD underwent a battery of 3 mental stress tests during the recruitment phase of REMIT study. MSIMI was assessed by echocardiography and electrocardiography. Ex vivo platelet aggregation in response to ADP, epinephrine, collagen, serotonin, and combinations of serotonin plus ADP, epinephrine, and collagen were evaluated as was platelet serotonin transporter expression. RESULTS: Of the 270 participants who completed mental stress testing, and had both resting and post-stress platelet aggregation evaluation , 43.33% (n=117) met criteria for MSIMI and 18.15% (n=49) had normal left ventricular response to stress (NLVR). The MSIMI group, relative to the NLVR groups, demonstrated heightened mental stress-induced aggregation responses, as measured by area under the curve, to collagen 10μM (6.95[5.54] vs. -14.23[8.75].; P=0.045), epinephrine 10μM (12.84[4.84] vs. -6.40[7.61].; P=0.037) and to serotonin 10 μM plus ADP 1 μM (6.64[5.29] vs. -27.34[8.34]; P<.001). The resting platelet aggregation and serotonin transporter expression, however, were not different between the two groups. CONCLUSIONS: These findings suggest that the dynamic change of platelet aggregation caused by mental stress may underlie MSIMI. While the importance of these findings requires additional investigation, they raise concern given the recognized relationship between mental stress-induced platelet hyperactivity and cardiovascular events in patients with IHD.
  • Thumbnail Image
    ItemOpen Access
    Prediction of short-term antidepressant response using probabilistic graphical models with replication across multiple drugs and treatment settings.
    (Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology, 2021-06) Athreya, Arjun P; Brückl, Tanja; Binder, Elisabeth B; John Rush, A; Biernacka, Joanna; Frye, Mark A; Neavin, Drew; Skime, Michelle; Monrad, Ditlev; Iyer, Ravishankar K; Mayes, Taryn; Trivedi, Madhukar; Carter, Rickey E; Wang, Liewei; Weinshilboum, Richard M; Croarkin, Paul E; Bobo, William V
    Heterogeneity in the clinical presentation of major depressive disorder and response to antidepressants limits clinicians' ability to accurately predict a specific patient's eventual response to therapy. Validated depressive symptom profiles may be an important tool for identifying poor outcomes early in the course of treatment. To derive these symptom profiles, we first examined data from 947 depressed subjects treated with selective serotonin reuptake inhibitors (SSRIs) to delineate the heterogeneity of antidepressant response using probabilistic graphical models (PGMs). We then used unsupervised machine learning to identify specific depressive symptoms and thresholds of improvement that were predictive of antidepressant response by 4 weeks for a patient to achieve remission, response, or nonresponse by 8 weeks. Four depressive symptoms (depressed mood, guilt feelings and delusion, work and activities and psychic anxiety) and specific thresholds of change in each at 4 weeks predicted eventual outcome at 8 weeks to SSRI therapy with an average accuracy of 77% (p = 5.5E-08). The same four symptoms and prognostic thresholds derived from patients treated with SSRIs correctly predicted outcomes in 72% (p = 1.25E-05) of 1996 patients treated with other antidepressants in both inpatient and outpatient settings in independent publicly-available datasets. These predictive accuracies were higher than the accuracy of 53% for predicting SSRI response achieved using approaches that (i) incorporated only baseline clinical and sociodemographic factors, or (ii) used 4-week nonresponse status to predict likely outcomes at 8 weeks. The present findings suggest that PGMs providing interpretable predictions have the potential to enhance clinical treatment of depression and reduce the time burden associated with trials of ineffective antidepressants. Prospective trials examining this approach are forthcoming.
  • Thumbnail Image
    ItemOpen Access
    Vintage treatments for PTSD: a reconsideration of tricyclic drugs.
    (Journal of psychopharmacology (Oxford, England), 2015-03) Davidson, Jonathan
    Serotonin (SSRI) and serotonin-norepinephrine (SNRI) reuptake inhibitors (SSRI) are the first-line recommended drug treatments for post-traumatic stress disorder (PTSD); but despite their benefits, much residual pathology remains and no new drugs have yet emerged with a clearly demonstrated benefit for treating the disorder. A case is made that tricyclic drugs deserve a closer look, based on their ability to affect several of the main neurotransmitters that are relevant to PTSD. Their promising efficacy, which was shown 30 years ago, had not been followed up, until a recent trial of desipramine found advantages over a SSRI in PTSD with comorbid alcohol dependence. Opportunities exist for studying newer and purportedly safer tricyclic formulations, as well as further the work with older, established compounds. A reappraisal of their risk:benefit ratio seems in order, when treating PTSD.
  • Thumbnail Image
    ItemOpen Access
    What to Expect When Switching to a Second Antidepressant Medication Following an Ineffective Initial SSRI: A Report From the Randomized Clinical STAR*D Study.
    (The Journal of clinical psychiatry, 2020-08-11) Rush, A John; South, Charles; Jha, Manish K; Jain, Shailesh Bobby; Trivedi, Madhukar H
    OBJECTIVE:An antidepressant medication switch often follows a failed initial trial with selective serotonin reuptake inhibitors (SSRIs). When, for whom, and how often second-step response and remission occur are unclear, as is preferred second-step trial duration. As more treatments are approved for use following 2 failed "adequate" trials, researchers and clinicians require an evidence-based definition of "adequate." METHODS:Following citalopram in the randomized Sequenced Treatment Alternatives to Relieve Depression (STAR*D) clinical trial (which ran July 2001-September 2006), participants with score ≥ 11 on the 16-item Quick Inventory of Depressive Symptomatology-Self-Rated (QIDS-SR₁₆) were randomized to bupropion sustained release, sertraline, or venlafaxine extended release (up to 14 weeks). The QIDS-SR₁₆ defined response, remission, and no clinically meaningful benefit based on the modified intent-to-treat sample. RESULTS:About 80% of 438 participants completed ≥ 6 weeks of treatment with the switch medication. All treatments had comparable outcomes. Overall, 21% (91/438) remitted, 9% (40/438) responded without remission, and 58% (255/438) had no meaningful benefit. Half of the responses and two-thirds of remissions occurred after 6 weeks of treatment. Overall, 33% of responses (43/131) occurred after ≥ 9 weeks of treatment. No baseline features differentiated early from later responders or remitters. No early triage point was found, but those with at least 20% reduction from baseline in QIDS-SR₁₆ score around week 2 were 6 times more likely to respond or remit than those without this reduction. CONCLUSIONS:Following nonefficacy with an initial SSRI, only about 20% remit and more than half achieve no meaningful benefit with a second-step switch to another monoaminergic antidepressant. A 12-week trial duration seems necessary to capture as many second-step switch responders as possible. TRIAL REGISTRATION:ClinicalTrials.gov identifier: NCT00021528.