scholarly journals Effects of Antidepressant Treatment on Neurotrophic Factors (BDNF and IGF-1) in Patients with Major Depressive Disorder (MDD)

2021 ◽  
Vol 10 (15) ◽  
pp. 3377
Author(s):  
Anna Mosiołek ◽  
Jadwiga Mosiołek ◽  
Sławomir Jakima ◽  
Aleksandra Pięta ◽  
Agata Szulc

Major depressive disorder (MDD) remains the subject of ongoing research as a multifactorial disease and a serious public health problem. There is a growing body of literature focusing on the role of neurotrophic factors in pathophysiology of MDD. A neurotrophic hypothesis of depression proposes that abnormalities of neurotrophins serum levels lead to neuronal atrophy and decreased neurogenesis, resulting in mood disorders. Consequently, in accordance with recent findings, antidepressant treatment modifies the serum levels of neurotrophins and thus leads to a clinical improvement of MDD. The purpose of this review is to summarize the available data on the effects of various antidepressants on serum levels of neurotrophins such as brain-derived neurotrophic factor (BDNF) and insulin-like growth factor (IGF-1). In addition, the authors discuss their role as prognostic factors for treatment response in MDD. A literature search was performed using the PubMed database. Following the inclusion and exclusion criteria, nine original articles and three meta-analyses were selected. The vast majority of studies have confirmed the effect of antidepressants on BDNF levels. Research on IGF-1 is limited and insufficient to describe the correlation between different antidepressant drugs and factor serum levels; however, four studies indicated a decrease in IGF-1 after treatment. Preliminary data suggest BDNF as a promising predictor of treatment response in MDD patients. The role of IGF-1 needs further investigation.

2021 ◽  
Vol 3 ◽  
Author(s):  
Anzar Abbas ◽  
Colin Sauder ◽  
Vijay Yadav ◽  
Vidya Koesmahargyo ◽  
Allison Aghjayan ◽  
...  

Objectives: Multiple machine learning-based visual and auditory digital markers have demonstrated associations between major depressive disorder (MDD) status and severity. The current study examines if such measurements can quantify response to antidepressant treatment (ADT) with selective serotonin reuptake inhibitors (SSRIs) and serotonin–norepinephrine uptake inhibitors (SNRIs).Methods: Visual and auditory markers were acquired through an automated smartphone task that measures facial, vocal, and head movement characteristics across 4 weeks of treatment (with time points at baseline, 2 weeks, and 4 weeks) on ADT (n = 18). MDD diagnosis was confirmed using the Mini-International Neuropsychiatric Interview (MINI), and the Montgomery–Åsberg Depression Rating Scale (MADRS) was collected concordantly to assess changes in MDD severity.Results: Patient responses to ADT demonstrated clinically and statistically significant changes in the MADRS [F(2, 34) = 51.62, p < 0.0001]. Additionally, patients demonstrated significant increases in multiple digital markers including facial expressivity, head movement, and amount of speech. Finally, patients demonstrated significantly decreased frequency of fear and anger facial expressions.Conclusion: Digital markers associated with MDD demonstrate validity as measures of treatment response.


Author(s):  
Meysam Amidfar ◽  
Gislaine Zilli Réus ◽  
Airam Barbosa de Moura ◽  
João Quevedo ◽  
Yong-Ku Kim

Depression ◽  
2019 ◽  
pp. 475-486
Author(s):  
Madhukar H. Trivedi ◽  
Farra Kahalnik ◽  
Tracy L. Greer

Although in recent years we have gained a deeper understanding of the pathophysiology of major depressive disorder, this improved understanding has not translated into improved treatment outcomes. Therefore, the screening of putative biological markers may be crucial to facilitate more rapid, successful treatment. Ongoing research has explored the importance of studying physiological biomarkers, including neuroimaging, neurophysiology, genomics, proteomics, and metabolomics, as well as cognition, to gain a better understanding of subtypes of depression and treatment response. However, only through an integrated, multimodal biomarker approach can we truly achieve better outcomes.


2015 ◽  
Vol 180 ◽  
pp. 207-213 ◽  
Author(s):  
Frank M. Schmidt ◽  
Claudia Nowak ◽  
Juergen Kratzsch ◽  
Christian Sander ◽  
Ulrich Hegerl ◽  
...  

2021 ◽  
Vol 10 (8) ◽  
pp. 1706
Author(s):  
Anna Mosiołek ◽  
Aleksandra Pięta ◽  
Sławomir Jakima ◽  
Natalia Zborowska ◽  
Jadwiga Mosiołek ◽  
...  

Major depressive disorder (MDD) is one of the most prevalent mental illness and a leading cause of disability worldwide. Despite a range of effective treatments, more than 30% of patients do not achieve remission as a result of conventional therapy. In these circumstances the identification of novel drug targets and pathogenic factors becomes essential for selecting more efficacious and personalized treatment. Increasing evidence has implicated the role of inflammation in the pathophysiology of depression, revealing potential new pathways and treatment options. Moreover, convergent evidence indicates that MDD is related to disturbed neurogenesis and suggests a possible role of neurotrophic factors in recovery of function in patients. Although the influence of antidepressants on inflammatory cytokines balance was widely reported in various studies, the exact correlation between drugs used and specific cytokines and neurotrophins serum levels often remains inconsistent. Available data suggest anti-inflammatory properties of selective serotonin reuptake inhibitors (SSRIs), selective serotonin and noradrenaline inhibitors (SNRIs), and tricyclic antidepressants (TCAs) as a possible additional mechanism of reduction of depressive symptoms. In this review, we outline emerging data regarding the influence of different antidepressant drugs on a wide array of peripheral biomarkers such as interleukin (IL)-1ß, IL-2, IL-5, IL-6, IL-8, IL-10, C-reactive protein (CRP), or interferon (IFN)-γ. Presented results indicate anti-inflammatory effect for selected drugs or lack of such effect. Research in this field is insufficient to define the role of inflammatory markers as a predictor of treatment response in MDD.


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