Multi-omic modeling of antidepressant response implicates dynamic immune and inflammatory changes in individuals who respond to treatment.

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.

MicroRNA-210 regulates the metabolic and inflammatory status of primary human astrocytes.

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.

Recurrent disease progression networks for modelling risk trajectory of heart failure.

Motivation: Recurrent neural networks (RNN) are powerful frameworks to model medical time series records. Recent studies showed improved accuracy of predicting future medical events (e.g.

Astrocytes in the Pathogenesis of Multiple Sclerosis: An In Situ MicroRNA Study.

Astrocytes are increasingly recognized as active contributors to the disease process in multiple sclerosis (MS), rather than being merely reactive. We investigated the expression of a selected microRNA (miRNA) panel that could contribute both to the injury and to the recovery phases of the disease. Individual astrocytes were laser microdissected from brain sections.

MicroRNA Expression Patterns in Human Astrocytes in Relation to Anatomical Location and Age.

Anatomic distribution and age are variables linked to functions of astrocytes under physiologic and pathologic conditions. We measured the relative expression of a panel of microRNAs (miRNAs) in astrocytes captured by laser micro-dissection from normal human adult white and grey matter, human fetal white matter and germinal matrix samples. Although expression of most miRNAs was comparable between adult and fetal samples, regional differences were observed.