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Background: Major depressive disorder (MDD) is a leading cause of disability worldwide, and is commonly treated with antidepressant drugs (AD). Although effective, many patients fail to respond to AD treatment, and accordingly identifying factors that can predict AD response would greatly improve treatment outcomes. In this study, we developed a machine learning tool to integrate multi-omic datasets (gene expression, DNA methylation, and genotyping) to identify biomarker profiles associated with AD response in a cohort of individuals with MDD., Materials and Methods: Individuals with MDD (N = 111) were treated for 8 weeks with antidepressants and were separated into responders and non-responders based on the Montgomery-Åsberg Depression Rating Scale (MADRS). Using peripheral blood samples, we performed RNA-sequencing, assessed DNA methylation using the Illumina EPIC array, and performed genotyping using the Illumina PsychArray. To address this rich multi-omic dataset with high dimensional features, we developed integrative Geneset-Embedded non-negative Matrix factorization (iGEM), a non-negative matrix factorization (NMF) based model, supplemented with auxiliary information regarding gene sets and gene-methylation relationships. In particular, we factorize the subjects by features (i.e., gene expression or DNA methylation) into subjects-by-factors and factors-by-features. We define the factors as the meta-phenotypes as they represent integrated composite scores of the molecular measurements for each subject., Results: Using our model, we identified a number of meta-phenotypes which were related to AD response. By integrating geneset information into the model, we were able to relate these meta-phenotypes to biological processes, including a meta-phenotype related to immune and inflammatory functions as well as other genes related to depression or AD response. The meta-phenotype identified several genes including immune interleukin 1 receptor like 1 (IL1RL1) and interleukin 5 receptor (IL5) subunit alpha (IL5RA), AKT/PIK3 pathway related phosphoinositide-3-kinase regulatory subunit 6 (PIK3R6), and sphingomyelin phosphodiesterase 3 (SMPD3), which has been identified as a target of AD treatment., Conclusions: The derived meta-phenotypes and associated biological functions represent both biomarkers to predict response, as well as potential new treatment targets. Our method is applicable to other diseases with multi-omic data, and the software is open source and available on Github (https://github.com/li-lab-mcgill/iGEM)., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Fuh et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Astrocytes are the most numerous glial cell type with important roles in maintaining homeostasis and responding to diseases in the brain. Astrocyte function is subject to modulation by microRNAs (miRs), which are short nucleotide strands that regulate protein expression in a post-transcriptional manner. Understanding the miR expression profile of astrocytes in disease settings provides insight into the cellular stresses present in the microenvironment and may uncover pathways of therapeutic interest., Methods: Laser-capture microdissection was used to isolate human astrocytes surrounding stroke lesions and those from neurological control tissue. Astrocytic miR expression profiles were examined using quantitative reverse transcription polymerase chain reaction (RT-qPCR). Primary human fetal astrocytes were cultured under in vitro stress conditions and transfection of a miR mimic was used to better understand how altered levels of miR-210 affect astrocyte function. The astrocytic response to stress was studied using qPCR, enzyme-linked immunosorbent assays (ELISAs), measurement of released lactate, and Seahorse., Results: Here, we measured miR expression levels in astrocytes around human ischemic stroke lesions and observed differential expression of miR-210 in chronic stroke astrocytes compared to astrocytes from neurological control tissue. We also identified increased expression of miR-210 in mouse white matter tissue around middle cerebral artery occlusion (MCAO) brain lesions. We aimed to understand the role of miR-210 in primary human fetal astrocytes by developing an in vitro assay of hypoxic, metabolic, and inflammatory stresses. A combination of hypoxic and inflammatory stresses was observed to upregulate miR-210 expression. Transfection with miR-210-mimic (210M) increased glycolysis, enhanced lactate export, and promoted an anti-inflammatory transcriptional and translational signature in astrocytes. Additionally, 210M transfection resulted in decreased expression of complement 3 (C3) and semaphorin 5b (Sema5b)., Conclusions: We conclude that miR-210 expression in human astrocytes is modulated in response to ischemic stroke disease and under in vitro stress conditions, supporting a role for miR-210 in the astrocytic response to disease conditions. Further, the anti-inflammatory and pro-glycolytic impact of miR-210 on astrocytes makes it a potential candidate for further research as a neuroprotective agent., (© 2022. The Author(s).)