Population pharmacokinetic analysis of lanicemine (AZD6765), an NMDA channel blocker, in healthy subjects and patients with major depressive disorder

2017 ◽  
Vol 42 (5) ◽  
pp. 539-546 ◽  
Author(s):  
F. Agbo ◽  
K. H. Bui ◽  
D. Zhou
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Healthy Subjects ◽  
Channel Blocker ◽  
Population Pharmacokinetic Analysis ◽  
Pharmacokinetic Analysis ◽  
Population Pharmacokinetic ◽  
Major Depressive ◽  
Nmda Channel

Prolactin in patients with major depressive disorder and in healthy subjects

1988 ◽  
Vol 24 (3) ◽  
pp. 286-298 ◽  
Author(s):  
Andreas Baumgartner ◽  
Klaus-jürgen Gräf ◽  
Irene Kürten
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Healthy Subjects ◽  
Major Depressive

scholarly journals A Population Pharmacokinetic–Pharmacodynamic Meta‐Analysis of Vortioxetine in Patients with Major Depressive Disorder

2015 ◽  
Vol 118 (5) ◽  
pp. 344-355 ◽  
Author(s):  
Himanshu Naik ◽  
Serena Chan ◽  
Majid Vakilynejad ◽  
Grace Chen ◽  
Henrik Loft ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Meta Analysis ◽  
Population Pharmacokinetic ◽  
Major Depressive

scholarly journals Neural Response to Catecholamine Depletion in Unmedicated Subjects With Major Depressive Disorder in Remission and Healthy Subjects

2008 ◽  
Vol 65 (5) ◽  
pp. 521 ◽  
Author(s):  
Gregor Hasler ◽  
Stephen Fromm ◽  
Paul J. Carlson ◽  
David A. Luckenbaugh ◽  
Tracy Waldeck ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Healthy Subjects ◽  
Neural Response ◽  
Major Depressive

Effect of yoga and meditation on accelerated cellular aging in major depressive disorder patients

2017 ◽  
Vol 41 (S1) ◽  
pp. S543-S543
Author(s):  
T. Madhuri ◽  
R. Dada ◽  
R. Sagar
Keyword(s):  
Dna Damage ◽  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Peripheral Blood ◽  
Healthy Subjects ◽  
Rating Scale ◽  
Cellular Aging ◽  
Sirtuin 1 ◽  
Major Depressive ◽  
Telomere Attrition

IntroductionAccelerated aging is associated with major depressive disorder (MDD) and studies of yoga and meditation based lifestyle intervention (YMLI) on biomarkers of cellular aging are lacking.Aim and objectivesTo investigate the peripheral blood biomarkers of cellular aging in MDD patients after short term YMLI. Biomarkers include DNA damage, oxidative stress (OS), telomere attrition, and nutrition sensing assessed respectively by 8-hydroxy 2’- deoxyguanosine (8-OHdG); reactive oxygen species (ROS) and total antioxidant capacity (TAC); telomere length and telomerase activity; and sirtuin-1.MethodsWe consecutively enrolled 33 MDD patients and 40 healthy subjects; 30 MDD patients were followed up with 12- week YMLI. Biomarkers of cellular aging in peripheral blood were measured with assay kits. All patients were evaluated by examining the correlation between cellular aging markers and Montgomery–Asberg Depression Rating Scale (MADRS) scores.ResultsThe levels of DNA damage, OS, and telomere attrition in MDD patients were significantly higher than healthy subjects (all P = 0.005). The MADRS scores had a significantly positive association with 8-OHdG and ROS levels and negative association with TAC, telomerase and sirtuin-1 levels (all P < 0.01).ConclusionsPeripheral blood biomarker levels in our results suggest significant cellular aging in MDD patients compared to healthy subjects. There was strong correlation between the changes in biomarkers of cellular aging and clinical improvement in MDD. Our study is the first to show significant increase in sirtuin-1 levels in MDD patients after yoga and meditation. Therefore, biomarkers of cellular aging might be indicators of MDD severity and clinical remission after YMLI.Disclosure of interestThe authors have not supplied their declaration of competing interest.

scholarly journals Identification of major depressive disorder disease-related genes and functional pathways based on system dynamic changes of network connectivity

2020 ◽  
Author(s):  
Ruijie Geng ◽  
Xiao Huang
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Pathway Analysis ◽  
Healthy Subjects ◽  
Kegg Pathway ◽  
Network Connectivity ◽  
Differentially Expressed ◽  
Therapeutic Drug ◽  
Major Depressive ◽  
Kegg Pathway Analysis

Abstract Objective: Major depressive disorder (MDD) is a leading psychiatric disorder that involves complex abnormal biological functions and neural networks. This study aimed to compare the changes in the network connectivity of different brain tissues under different pathological conditions, analyzed the biological pathways and genes that are significantly related to disease progression, and further predicted the potential therapeutic drug targets.Methods: Expression of differentially expressed genes (DEGs) were analyzed with postmortem cingulate cortex (ACC) and prefrontal cortex (PFC) mRNA expression profile datasets downloaded from the Gene Expression Omnibus (GEO) database, including 76 MDD patients and 76 healthy subjects in ACC and 63 MDD patients and 63 healthy subjects in PFC. The co-expression network construction was based on system network analysis. The function of the genes was annotated by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Human Protein Reference Database (HPRD, http://www.hprd.org/) was used for gene interaction relationship mapping.Results: We filtered 586 DEGs in ACC and 616 DEGs in PFC for further analysis. By constructing the Co-expression network, we found that the gene connectivity was significantly reduced under disease conditions (P=0.04 in PFC and P=1.227e-09 in ACC). Crosstalk analysis showed that CD19, PTDSS2 and NDST2 were significantly differentially expressed in ACC and PFC of MDD patients. Among them, CD19 and PTDSS2 have been targeted by several drugs in the Drugbank database. KEGG pathway analysis demonstrated that the function of CD19 and PTDSS2 were enriched with the pathway of Glycerophospholipid metabolism and T cell receptor signaling pathway. Conclusion: Co-expression network and tissue comparing analysis can identify signaling pathways and cross talk genes related to MDD, which may provide novel insight for understanding the molecular mechanisms of MDD.

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