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512 results for “Antidepressant”
Insights from a Methylome-Wide Association Study of Antidepressant Exposure
<p>Results datasets from the paper: </p> <p><strong>Insights from a Methylome-Wide Association Study of Antidepressant Exposure</strong></p> <p><strong>Methylome-wide association study (MWAS) summary statistics: </strong></p> <p><strong>All individuals: </strong></p> <p>MWAS of prescription-derived antidepressant exposure (n = 7,951): </p> <p> <a href="https://zenodo.org/uploads/14203230" target="_blank" rel="noopener noreferrer">GRM_unadjusted_antidep_pheno1_clean_appt_MOA_ORM_residph_standard_06_10.moa</a></p> <p>MWAS of self-reported antidepressant exposure (n = 16,531):</p> <p> <a href="https://zenodo.org/uploads/14203230" target="_blank" rel="noopener noreferrer">GRM_unadjusted_selfrep_pheno3_MOA_ORM_residph_standard_06_10.moa</a></p> <p><strong>Individuals with a lifetime status of Major Depressive Disorder (MDD, MDD-subgroup): </strong></p> <p>MWAS of prescription-derived antidepressant exposure (n = 792)</p> <p><a href="https://zenodo.org/uploads/14203230" target="_blank" rel="noopener noreferrer">GRM_unadjusted_antidep_pheno2_clean_appt_MOA_ORM_residph_standard_06_10.moa</a></p> <p>MWAS of self-reported antidepressant exposure (n = 2,268):</p> <p><a href="https://zenodo.org/api/records/14203230/draft/files/GRM_unadjusted_selfrep_pheno4_MOA_ORM_residph_standard_06_10.moa/content" target="_blank" rel="noopener noreferrer">GRM_unadjusted_selfrep_pheno4_MOA_ORM_residph_standard_06_10.moa</a></p> <p><strong>Downstream functional analyses: </strong></p> <p><strong>Differentially methylated region (DMRFF) analysis:</strong></p> <p>Prescription-derived antidepressant exposure:</p> <p><a href="https://zenodo.org/api/records/14203230/draft/files/gtex_v8_ts_DEG_PD.txt/content" target="_blank" rel="noopener noreferrer">antidep_pheno1_clean_appt_dmr_res.tsv</a></p> <p>Self-report antidepressant exposure: </p> <p><a href="https://zenodo.org/api/records/14203230/draft/files/gtex_v8_ts_DEG_PD.txt/content" target="_blank" rel="noopener noreferrer">selfrep_pheno3_dmr_res.tsv</a></p> <p><strong>GO Biological Pathway (msigdbr) enrichment:</strong></p> <p>Prescription-derived antidepressant exposure:</p> <p><a href="https://zenodo.org/api/records/14203230/draft/files/gtex_v8_ts_DEG_PD.txt/content" target="_blank" rel="noopener noreferrer">gtex_v8_ts_DEG_PD.txt</a></p> <p>Self-report antidepressant exposure: </p> <p><a href="https://zenodo.org/api/records/14203230/draft/files/gtex_v8_ts_DEG_PD.txt/content" target="_blank" rel="noopener noreferrer">gtex_v8_ts_DEG_SR.txt</a></p> <p><strong>SynGo pathway (web-portal) enrichment:</strong></p> <p>Prescription-derived antidepressant exposure:</p> <p><a href="https://zenodo.org/api/records/14203230/draft/files/syngo_annotations_matching_user_input_PD.xlsx/content" target="_blank" rel="noopener noreferrer">syngo_annotations_matching_user_input_PD.xlsx</a></p> <p><a href="https://zenodo.org/api/records/14203230/draft/files/syngo_ontologies_with_annotations_matching_user_input_PD.xlsx/content" target="_blank" rel="noopener noreferrer">syngo_ontologies_with_annotations_matching_user_input_PD.xlsx</a></p> <p>Self-report antidepressant exposure: </p> <p><a href="https://zenodo.org/api/records/14203230/draft/files/syngo_annotations_matching_user_input_PD.xlsx/content" target="_blank" rel="noopener noreferrer">syngo_annotations_matching_user_input_SR.xlsx</a></p> <p><a href="https://zenodo.org/api/records/14203230/draft/files/syngo_ontologies_with_annotations_matching_user_input_PD.xlsx/content" target="_blank" rel="noopener noreferrer">syngo_ontologies_with_annotations_matching_user_input_SR.xlsx</a></p> <p><strong>Tissue enrichment (FUMA GENE2FUNC):</strong></p> <p>Prescription-derived antidepressant exposure:</p> <p><a href="https://zenodo.org/api/records/14203230/draft/files/gtex_v8_ts_DEG_PD.txt/content" target="_blank" rel="noopener noreferrer">gtex_v8_ts_DEG_PD.txt</a></p> <p>Self-report antidepressant exposure: </p> <p><a href="https://zenodo.org/api/records/14203230/draft/files/gtex_v8_ts_DEG_PD.txt/content" target="_blank" rel="noopener noreferrer">gtex_v8_ts_DEG_SR.txt</a></p> <p><strong>Antidepressant exposure methylation profile score (MPS): </strong></p> <p><a href="https://zenodo.org/api/records/14203230/draft/files/gtex_v8_ts_DEG_PD.txt/content" target="_blank" rel="noopener noreferrer">GS_AD_MRS_weights.txt</a></p> <p><strong>Source Data:</strong></p> <p>Source data for Figures and Supplementary Figures which do not represent individual-level data.</p> <p><a href="https://zenodo.org/api/records/14203230/draft/files/gtex_v8_ts_DEG_PD.txt/content" target="_blank" rel="noopener noreferrer">source_data.xlsx </a></p> <p> </p>
How Confidence in Prior Attitudes, Social Tag Popularity, and Source Credibility Shape Confirmation Bias Toward Antidepressants and Psychotherapy in a Representative German Sample: Randomized Controlled Web-Based Study
<p>ABSTRACT</p> <p>Background: In health-related, Web-based information search, people should select information in line with expert (vs nonexpert) information, independent of their prior attitudes and consequent confirmation bias.</p> <p>Objective: This study aimed to investigate confirmation bias in mental health–related information search, particularly (1) if high confidence worsens confirmation bias, (2) if social tags eliminate the influence of prior attitudes, and (3) if people successfully distinguish high and low source credibility.</p> <p>Methods: In total, 520 participants of a representative sample of the German Web-based population were recruited via a panel company. Among them, 48.1% (250/520) participants completed the fully automated study. Participants provided <em>prior attitudes</em> about antidepressants and psychotherapy. We manipulated (1) <em>confidence</em> in prior attitudes when participants searched for blog posts about the treatment of depression, (2) <em>tag popularity</em> —either psychotherapy or antidepressant tags were more popular, and (3) <em>source credibility</em> with banners indicating high or low expertise of the tagging community. We measured <em>tag</em> and <em>blog post</em> selection, and <em>treatment</em><em>efficacy ratings</em> after navigation.</p> <p>Results: Tag popularity predicted the proportion of selected antidepressant tags (beta=.44, SE 0.11; <em>P</em><.001) and blog posts (beta=.46, SE 0.11; <em>P</em><.001). When confidence was low (−1 SD), participants selected more blog posts consistent with prior attitudes (beta=−.26, SE 0.05; <em>P</em><.001). Moreover, when confidence was low (−1 SD) and source credibility was high (+1 SD), the efficacy ratings of attitude-consistent treatments increased (beta=.34, SE 0.13; <em>P</em>=.01).</p> <p>Conclusions: We found correlational support for defense motivation account underlying confirmation bias in the mental health–related search context. That is, participants tended to select information that supported their prior attitudes, which is not in line with the current scientific evidence. Implications for presenting persuasive Web-based information are also discussed.</p> <p>Trial Registration: ClinicalTrials.gov NCT03899168; https://clinicaltrials.gov/ct2/show/NCT03899168 (Archived by WebCite at http://www.webcitation.org/77Nyot3Do)</p> <p>J Med Internet Res 2019;21(4):e11081</p> <p>doi:10.2196/11081</p>
Impact of the COVID-19 pandemic on antidepressant use in eleven European regions: a comparative time series analysis 2018–2022
<p>Data and code supporting the article:</p> <p>Impact of the COVID-19 pandemic on antidepressant use in eleven European regions: a comparative time series analysis 2018–2022</p> <p>Prescription, prevalence and incidence data from January 2018 to December 2022 for Croatia, the Czech Republic, Finland, Germany, Slovenia, Sweden, and the United Kingdom (England, Northern Ireland, Scotland, and Wales).<br>Data include the numbers of dispensed defined daily doses (DDDs) and packs, aggregated by country and month, and prevalence and incidence of antidepressant dispensing.</p> <p>For more information, see the accompanying document ReadMe.md.</p>
Efficacy, Safety and Tolerability of Cariprazine as an Adjunctive Treatment to Antidepressant Therapy (ADT) in Patients With Major Depressive Disorder (MDD) Who Have Had an Inadequate Response to Anti
ClinicalTrials.gov study NCT03738215. IPD Sharing: YES. Countries: 7. Publications: 1.
The Objective of This Study is to Evaluate the Efficacy, Safety and Tolerability of Cariprazine as an Adjunctive Treatment to Antidepressant Therapy (ADT) in Patients With Major Depressive Disorder (M
ClinicalTrials.gov study NCT03739203. IPD Sharing: YES. Countries: 8. Publications: 1.
Prenatal treatment with the antidepressant fluoxetine on maternal and neonatal behavior in sheep
Open the record for dataset details and reuse information.
Biomarkers of neurodegeneration in isolated and antidepressant-related REM sleep behavior disorder.
<p>Dataset relative to the manuscript "Biomarkers of neurodegeneration in isolated and antidepressant-related REM sleep behavior disorder."</p>
The effect of antidepressants on genes of endoplasmic reticulum stress in human astrocyte cell line.
<p>Many central nervous system (CNS) diseases, including major depressive disorder (MDD), are underpinned by the unfolded protein response (UPR) activated under endoplasmic reticulum (ER) stress. New, more efficient, therapeutic options for MDD are needed to avoid adverse effects and drug resistance. Therefore, the aim of the work was to determine whether UPR signalling pathway activation in astrocytes may serve as a novel target for antidepressant drugs. Among the tested antidepressants (escitalopram, amitriptyline, S-ketamine), only S-ketamine induced the expression of most ER stress-responsive genes in astrocytes.</p> <p><a href="https://doi.org/10.3390/pharmaceutics14040846">https://doi.org/10.3390/pharmaceutics14040846</a></p> <p> </p>
Antidepressant use among children and adolescents in Denmark, Norway and Sweden
<p>Dataset consists of 3 files:</p> <ol> <li>drug_use.csv</li> <li>census.csv</li> <li>drug_names.csv</li> </ol> <p>Drug and census data were derived from the following national resources in the public domain:</p> <p><strong>Drug statistics data:</strong></p> <ul> <li>https://sdb.socialstyrelsen.se/if_lak/val.aspx (download date: 24.10.2018)</li> <li>http://www.norpd.no/ (download date: 24.10.2018)</li> <li>http://www.medstat.dk/ (download date: 10.01.2018)</li> </ul> <p><strong>Census data:</strong></p> <ul> <li>https://statistikbanken.dk (download date: 24.10.2018)</li> <li>https://www.ssb.no/ (download date: 24.10.2018)</li> <li>http://www.statistikdatabasen.scb.se (download date: 10.01.2018)</li> </ul> <p>The source data owners take no responsibily for interpretation or analysis of data performed by third parties. Source data owners should be attributed when data are used. Consult data owners websites for details about attribution.</p> <p><strong>File descriptions:</strong></p> <p>drug_use.csv</p> <p>contains aggregated information about the number of unique users and the amount (measured in drug daily dose - DDD). Drugs are identified by ATC codes and counts are grouped by the following categorical variables:</p> <p>country (DK, NO, SE)<br> year (2007 - 2017)<br> agegroup (5-9, 10-14, 15-19)<br> sex (F, M)</p> <p>The variables users_pr_1000 and ddd_pr_1000 are the results of dividing the variables n_users and ddd by the total population size in that country, year, agegroup and sex category. These census informations are also available in the census.csv file<br> </p> <p>census.csv contains census data for each country grouped by sex and age. Use this file if you want to calculate population denominators for alternative aggregations of data in the drug_use.csv file</p> <p>drug_names.csv provides the drug name associated to each ATC code</p> <p> </p>
A Study to Evaluate the Efficacy, Safety, and Tolerability of Flexible Doses of Intranasal Esketamine Plus an Oral Antidepressant in Adult Participants With Treatment-resistant Depression
ClinicalTrials.gov study NCT02418585. IPD Sharing: Not stated. Countries: 5. Publications: 16.
Racial Disparities in Antidepressant Treatment After a Psychiatric Consultation
ClinicalTrials.gov study NCT06799078. IPD Sharing: UNDECIDED. Countries: 1. Publications: 15.
SPD489 in Combination With an Antidepressant in the Treatment of Adults With Major Depressive Disorder
ClinicalTrials.gov study NCT01435759. IPD Sharing: Not stated. Countries: 5. Publications: 1.
Mechanisms of Antidepressant Non-Response in Late-Life Depression
ClinicalTrials.gov study NCT01931202. IPD Sharing: NO. Countries: 1. Publications: 1.
Antidepressant Medication Treatment for Depression in Individuals With Chronic Heart Failure
ClinicalTrials.gov study NCT00078286. IPD Sharing: Not stated. Countries: 1. Publications: 4.
A Study to Compare the Efficacy, Safety, and Tolerability of JNJ-42847922 Versus Quetiapine Extended-Release as Adjunctive Therapy to Antidepressants in Adult Participants With Major Depressive Disord
ClinicalTrials.gov study NCT03321526. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Study of Antidepressant Efficacy of a Selective, High Affinity Enkephalinergic Agonist in Anxious Major Depressive Disorder (AMDD)
ClinicalTrials.gov study NCT00759395. IPD Sharing: Not stated. Countries: 1. Publications: 1.
This is a Study to Determine the Antidepressant Effects of AZD6765
ClinicalTrials.gov study NCT00986479. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Testosterone Antidepressant Augmentation in Women
ClinicalTrials.gov study NCT01783574. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Effects of Adding Motivational Interviewing to Antidepressant Treatment for Hispanic Adults With Depression
ClinicalTrials.gov study NCT00564278. IPD Sharing: NO. Countries: 1. Publications: 1.
Antidepressant Treatments and Cognitive Function of Bipolar Patients
ClinicalTrials.gov study NCT04564573. IPD Sharing: YES. Countries: 1. Publications: 1.
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