Literature DB >> 29331712

Genetic biomarkers for differential diagnosis of major depressive disorder and bipolar disorder: A systematic and critical review.

Itiana Castro Menezes1, Cristiane von Werne Baes1, Riccardo Lacchini2, Mario Francisco Juruena3.   

Abstract

Depressive symptoms are present in the depressive mood state of bipolar disorder (BPD) and major depression disorder (MDD). Often, in clinical practice, BPD patients are misdiagnosed with MDD. Therefore, genetic biomarkers could contribute to the improvement of differential diagnosis between BPD and MDD. This systematic and critical review aimed to find in literature reliable genetic biomarkers that may show differences between BPD and MDD. This systematic review followed the PRISMA-P method. The terms used to search PubMed, Scopus, PsycINFO, and Web of Science were depress*, bipolar, diagnos*, genetic*, biomark*. After applying the selection criteria, N = 27 studies were selected, being n = 9 about biomarkers for BPD; n = 15, about MDD; and n = 3 for distinguishing MDD from BPD. A total of N = 3086 subjects were assessed in the selected studies (n = 486 in BPD group; n = 1212 in MDD group; and n = 1388, healthy control group). The articles were dated up to June 2017. Of the N = 27 studies, n = 16 assessed gene, n = 1 miRNA, n = 2 lcnRNA and n = 3 protein expressions, n = 4 methylation, and n = 4 polymorphisms. Some studies applied more than one of these genetic analyses. To find reliable genetic biomarkers we have taken into account the methodological care during the studies development and their validity. The genetic biomarkers selected are related to genes that play a fundamental role in synaptic plasticity, neurogenesis, mood control, brain ageing, immune-inflammatory processes and mitochondrial respiratory chain. BDNF gene expression was one of the genetic biomarkers that highlighted because of its capacity of distinguishing BPD and MDD groups, and being adequately reproduced by more than one selected study.
Copyright © 2018 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Bipolar; Depression; Diagnosis; Genetic biomarker

Mesh:

Year:  2018        PMID: 29331712     DOI: 10.1016/j.bbr.2018.01.008

Source DB:  PubMed          Journal:  Behav Brain Res        ISSN: 0166-4328            Impact factor:   3.332


  8 in total

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2.  An integrative network analysis framework for identifying molecular functions in complex disorders examining major depressive disorder as a test case.

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8.  A Predictive Model of Risk Factors for Conversion From Major Depressive Disorder to Bipolar Disorder Based on Clinical Characteristics and Circadian Rhythm Gene Polymorphisms.

Authors:  Zhi Xu; Lei Chen; Yunyun Hu; Tian Shen; Zimu Chen; Tingting Tan; Chenjie Gao; Suzhen Chen; Wenji Chen; Bingwei Chen; Yonggui Yuan; Zhijun Zhang
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  8 in total

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