Iprindole: A Cornerstone in the Neurobiological Investigation of Antidepressant Treatments

2015 ◽  
pp. 102-116 ◽  
Author(s):  
Claude de Montigny
Keyword(s):  
Antidepressant Treatments

scholarly journals Conditional power of antidepressant network meta-analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Lisa Holper
Keyword(s):  
Meta Analysis ◽  
Indirect Evidence ◽  
Dropout Rate ◽  
Conclusive Evidence ◽  
Effect Sizes ◽  
Current Evidence ◽  
Hamilton Depression Scale ◽  
Conditional Power ◽  
Sample Sizes ◽  
Antidepressant Treatments

Abstract Background Conditional power of network meta-analysis (NMA) can support the planning of randomized controlled trials (RCTs) assessing medical interventions. Conditional power is the probability that updating existing inconclusive evidence in NMA with additional trial(s) will result in conclusive evidence, given assumptions regarding trial design, anticipated effect sizes, or event probabilities. Methods The present work aimed to estimate conditional power for potential future trials on antidepressant treatments. Existing evidence was based on a published network of 502 RCTs conducted between 1979-2018 assessing acute antidepressant treatment in major depressive disorder (MDD). Primary outcomes were efficacy in terms of the symptom change on the Hamilton Depression Scale (HAMD) and tolerability in terms of the dropout rate due to adverse events. The network compares 21 antidepressants consisting of 231 relative treatment comparisons, 164 (efficacy) and 127 (tolerability) of which are currently assumed to have inconclusive evidence. Results Required sample sizes to achieve new conclusive evidence with at least 80% conditional power were estimated to range between N = 894 - 4190 (efficacy) and N = 521 - 1246 (tolerability). Otherwise, sample sizes ranging between N = 49 - 485 (efficacy) and N = 40 - 320 (tolerability) may require stopping for futility based on a boundary at 20% conditional power. Optimizing trial designs by considering multiple trials that contribute both direct and indirect evidence, anticipating alternative effect sizes or alternative event probabilities, may increase conditional power but required sample sizes remain high. Antidepressants having the greatest conditional power associated with smallest required sample sizes were identified as those on which current evidence is low, i.e., clomipramine, levomilnacipran, milnacipran, nefazodone, and vilazodone, with respect to both outcomes. Conclusions The present results suggest that conditional power to achieve new conclusive evidence in ongoing or future trials on antidepressant treatments is low. Limiting the use of the presented conditional power analysis are primarily due to the estimated large sample sizes which would be required in future trials as well as due to the well-known small effect sizes in antidepressant treatments. These findings may inform researchers and decision-makers regarding the clinical relevance and justification of research in ongoing or future antidepressant RCTs in MDD.

Effects of repeated mild stress and two antidepressant treatments on the behavioral response to 5HT1C receptor activation in rats

1993 ◽  
Vol 110 (1-2) ◽  
pp. 140-144 ◽  
Author(s):  
Jean-Luc Moreau ◽  
François Jenck ◽  
James R. Martin ◽  
Sabine Perrin ◽  
Willy E. Haefely
Keyword(s):  
Behavioral Response ◽  
Receptor Activation ◽  
Mild Stress ◽  
Antidepressant Treatments

Plasma and serum brain-derived neurotrophic factor (BDNF) in depressed patients during 1 year of antidepressant treatments

2008 ◽  
Vol 105 (1-3) ◽  
pp. 279-283 ◽  
Author(s):  
Armando Piccinni ◽  
Donatella Marazziti ◽  
Mario Catena ◽  
Luciano Domenici ◽  
Alessandro Del Debbio ◽  
...  
Keyword(s):  
Neurotrophic Factor ◽  
Brain Derived Neurotrophic Factor ◽  
Antidepressant Treatments ◽  
Depressed Patients

Depression: A Long-Term Illness

1994 ◽  
Vol 165 (S26) ◽  
pp. 9-15 ◽  
Author(s):  
Martin B. Keller
Keyword(s):  
Health Care ◽  
Health Care Providers ◽  
Maintenance Treatment ◽  
Depressive Disorders ◽  
Care Providers ◽  
Serious Illness ◽  
Antidepressant Treatments ◽  
Continued Education ◽  
Low Levels

The realisation that major depression is often both chronic and recurrent has slowly begun to change the way that depression is diagnosed and treated. In particular, the need for continuation and maintenance treatment is an issue that now deserves increased attention, especially with the availability of new classes of antidepressant treatments, which have excellent efficacy and more favourable side-effect profiles. Although the serious consequences of depressive disorders clearly indicate the need for effective and prompt intervention on the part of clinicians, the results of several studies indicate that patients with depression consistently receive no or low levels of antidepressant therapy. It is hoped that, through continued education of health care providers and patients about the consequences of depression, the issue of undertreatment of this serious illness will be resolved.

scholarly journals Genome-wide association study of treatment-resistance in depression and meta-analysis of three independent samples

2018 ◽  
Vol 214 (1) ◽  
pp. 36-41 ◽  
Author(s):  
Chiara Fabbri ◽  
Siegfried Kasper ◽  
Alexander Kautzky ◽  
Lucie Bartova ◽  
Markus Dold ◽  
...  
Keyword(s):  
Genome Wide Association Study ◽  
Meta Analysis ◽  
Adenosine Monophosphate ◽  
Research Support ◽  
Antidepressant Treatments ◽  
Advisory Boards ◽  
Gene Sets ◽  
Genome Wide ◽  
A Genome ◽  
Resistant Depression

BackgroundTreatment-resistant depression (TRD) is the most problematic outcome of depression in terms of functional impairment, suicidal thoughts and decline in physical health.AimsTo investigate the genetic predictors of TRD using a genome-wide approach to contribute to the development of precision medicine.MethodA sample recruited by the European Group for the Study of Resistant Depression (GSRD) including 1148 patients with major depressive disorder (MDD) was characterised for the occurrence of TRD (lack of response to at least two adequate antidepressant treatments) and genotyped using the Infinium PsychArray. Three clinically relevant patient groups were considered: TRD, responders and non-responders to the first antidepressant trial, thus outcomes were based on comparisons of these groups. Genetic analyses were performed at the variant, gene and gene-set (i.e. functionally related genes) level. Additive regression models of the outcomes and relevant covariates were used in the GSRD participants and in a fixed-effect meta-analysis performed between GSRD, STAR*D (n = 1316) and GENDEP (n = 761) participants.ResultsNo individual polymorphism or gene was associated with TRD, although some suggestive signals showed enrichment in cytoskeleton regulation, transcription modulation and calcium signalling. Two gene sets (GO:0043949 and GO:0000183) were associated with TRD versus response and TRD versus response and non-response to the first treatment in the GSRD participants and in the meta-analysis, respectively (corrected P = 0.030 and P = 0.027).ConclusionsThe identified gene sets are involved in cyclic adenosine monophosphate mediated signal and chromatin silencing, two processes previously implicated in antidepressant action. They represent possible biomarkers to implement personalised antidepressant treatments and targets for new antidepressants.Declaration of interestD.S. has received grant/research support from GlaxoSmithKline and Lundbeck; has served as a consultant or on advisory boards for AstraZeneca, Bristol-Myers Squibb, Eli Lilly, Janssen and Lundbeck. S.M. has been a consultant or served on advisory boards for: AstraZeneca, Bristol-Myers Squibb, Forest, Johnson & Johnson, Leo, Lundbeck, Medelink, Neurim, Pierre Fabre, Richter. S.K. has received grant/research support from Eli Lilly, Lundbeck, Bristol-Myers Squibb, GlaxoSmithKline, Organon, Sepracor and Servier; has served as a consultant or on advisory boards for AstraZeneca, Bristol-Myers Squibb, GlaxoSmithKline, Eli Lilly, Lundbeck, Pfizer, Organon, Schwabe, Sepracor, Servier, Janssen and Novartis; and has served on speakers' bureaus for AstraZeneca, Eli Lily, Lundbeck, Schwabe, Sepracor, Servier, Pierre Fabre, Janssen and Neuraxpharm. J.Z. has received grant/research support from Lundbeck, Servier, Brainsway and Pfizer, has served as a consultant or on advisory boards for Servier, Pfizer, Abbott, Lilly, Actelion, AstraZeneca and Roche and has served on speakers' bureaus for Lundbeck, Roch, Lilly, Servier, Pfizer and Abbott. J.M. is a member of the Board of the Lundbeck International Neuroscience Foundation and of Advisory Board of Servier. A.S. is or has been consultant/speaker for: Abbott, AbbVie, Angelini, Astra Zeneca, Clinical Data, Boehringer, Bristol Myers Squibb, Eli Lilly, GlaxoSmithKline, Innovapharma, Italfarmaco, Janssen, Lundbeck, Naurex, Pfizer, Polifarma, Sanofi and Servier. C.M.L. receives research support from RGA UK Services Limited.

scholarly journals Glutamatergic Neurotransmission: Pathway to Developing Novel Rapid-Acting Antidepressant Treatments

2018 ◽  
Vol 22 (2) ◽  
pp. 119-135 ◽  
Author(s):  
Bashkim Kadriu ◽  
Laura Musazzi ◽  
Ioline D Henter ◽  
Morgan Graves ◽  
Maurizio Popoli ◽  
...  
Keyword(s):  
Glutamatergic Neurotransmission ◽  
Antidepressant Treatments

Insight Gained from Genome-wide Interaction and Enrichment Analysis on Weight Gain During Citalopram Treatment

2017 ◽  
Vol 41 (S1) ◽  
pp. S163-S163
Author(s):  
H. Corfitsen ◽  
A. Drago
Keyword(s):  
Weight Gain ◽  
Myogenic Differentiation ◽  
Antidepressant Treatment ◽  
Enrichment Analysis ◽  
Molecular Pathways ◽  
Present Contribution ◽  
White Adipocyte ◽  
Antidepressant Treatments ◽  
Molecular Events ◽  
Genome Wide

IntroductionWeight gain is a side effect of pharmacological antidepressant treatments, causing a poorer compliance, increasing the risk of metabolic syndrome and periods of untreated disease.ObjectivesThe ability to precisely prescribe pharmacological treatments based on personal genetic makeups would increase the quality of the current antidepressant treatments.AimsThe molecular pathways enriched during citalopram induced weight gain are identified.Methods643 depressed citalopram treated individuals with available clinical and genome-wide genetic information were investigated in the present contribution in order to identify the molecular pathways that holds the key to weight gain. Statistics were conducted in R environment (Bioconductor and Reactome packages), ANOVA and MANCOVA served when appropriate. Plink was used for genetic analysis in a linux environment.ResultsOne hundred and eleven individuals had their weight increased after treatment with citalopram. The axon guidance (P. adjust = 0.005) and the developmental biology pathway (P. adjust = 0.01) were found to be enriched in genetic variations associated with weight gain.ConclusionsThe development biology pathway includes molecular cascades involved in the regulation of beta-cell development, and the transcriptional regulation of white adipocyte differentiation. A number of variations were harboured by genes whose products are involved in the synthesis of collagen (COL4A3, COL5A1 and ITGA1), activity of the thyroid-hormones (NCOR1 and NCOR2), energy metabolism (ADIPOQ, PPARGC1A) and myogenic differentiation (CDON). A molecular pathway analysis conducted in a sample of depressed patients identifies new candidate genes whose future investigation may grant relevant insights in the molecular events that drive weight gain during antidepressant treatment.

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