Heidi Yuan1, David Mischoulon2, Maurizio Fava2, Michael W Otto3. 1. Department of Psychological and Brain Sciences, Boston University, United States; Pomona College, Claremont, CA, United States. 2. Depression Clinical and Research Program, Massachusetts General Hospital and Harvard Medical School, United States. 3. Department of Psychological and Brain Sciences, Boston University, United States. Electronic address: mwotto@bu.edu.
Abstract
BACKGROUND: Recent research has highlighted the potential of microRNAs to serve as physiological indicators of disease process among clinically depressed patients. METHODS: In a comprehensive literature search through PubMed, we identified 23 articles comparing circulating (blood, plasma, or serum) microRNA expression levels in depressed versus healthy human subjects. Six studies examining circulatory microRNA expression through animal models of depression were also identified through the search and details of each study were outlined. A meta-analytic evaluation of these studies was not considered feasible, given the absence of concordance in the literature to date. RESULTS: A total of 178 specific microRNA candidates were identified in the human studies as significantly expressed among depressed samples. Ninety-seven of these microRNAs were upregulated, 75 were downregulated, and 6 showed mixed expression in depressed samples. Few microRNAs were consistently expressed across studies; the most consistent evidence was for microRNA-132, with replication in 4 different studies. Among animal studies, 2 studies investigated microRNA-16 through distinct stress-induced depression models. LIMITATIONS: Structural variations in microRNA sequences, methodological inconsistencies in technology used among studies to measure microRNA expression levels, differences in the clinical severity and forms of depression among subjects, and the overall paucity of studies make it difficult to ascertain any robust, preliminary targets deserving of biomarker potential. CONCLUSIONS: Ongoing research needs to address this high rate of non-replication as well as the methodological and reporting challenges of microRNA experimentation in order to determine valid effect sizes for the more proliferative candidates associated with depression.
BACKGROUND: Recent research has highlighted the potential of microRNAs to serve as physiological indicators of disease process among clinically depressed patients. METHODS: In a comprehensive literature search through PubMed, we identified 23 articles comparing circulating (blood, plasma, or serum) microRNA expression levels in depressed versus healthy human subjects. Six studies examining circulatory microRNA expression through animal models of depression were also identified through the search and details of each study were outlined. A meta-analytic evaluation of these studies was not considered feasible, given the absence of concordance in the literature to date. RESULTS: A total of 178 specific microRNA candidates were identified in the human studies as significantly expressed among depressed samples. Ninety-seven of these microRNAs were upregulated, 75 were downregulated, and 6 showed mixed expression in depressed samples. Few microRNAs were consistently expressed across studies; the most consistent evidence was for microRNA-132, with replication in 4 different studies. Among animal studies, 2 studies investigated microRNA-16 through distinct stress-induced depression models. LIMITATIONS: Structural variations in microRNA sequences, methodological inconsistencies in technology used among studies to measure microRNA expression levels, differences in the clinical severity and forms of depression among subjects, and the overall paucity of studies make it difficult to ascertain any robust, preliminary targets deserving of biomarker potential. CONCLUSIONS: Ongoing research needs to address this high rate of non-replication as well as the methodological and reporting challenges of microRNA experimentation in order to determine valid effect sizes for the more proliferative candidates associated with depression.
Authors: Pei X Luo; Claire E Manning; Joe N Fass; Alexia V Williams; Rebecca Hao; Katharine L Campi; Brian C Trainor Journal: Behav Brain Res Date: 2020-12-22 Impact factor: 3.332
Authors: Marina Xavier Carpena; Mara H Hutz; Angélica Salatino-Oliveira; Guilherme V Polanczyk; Cristian Zeni; Marcelo Schmitz; Rodrigo Chazan; Julia P Genro; Luis Augusto Rohde; Luciana Tovo-Rodrigues Journal: Genes (Basel) Date: 2019-01-28 Impact factor: 4.096
Authors: Yann Ehinger; Khanhky Phamluong; David Darevesky; Melanie Welman; Jeffrey J Moffat; Samuel A Sakhai; Ellanor L Whiteley; Anthony L Berger; Sophie Laguesse; Mehdi Farokhnia; Lorenzo Leggio; Marie Lordkipanidzé; Dorit Ron Journal: Addict Biol Date: 2020-03-05 Impact factor: 4.280