ArticleBiological psychiatry global open science2024
Integrated Long Noncoding RNA and Messenger RNA Expression Analysis Identifies Molecules Specifically Associated With Resiliency and Susceptibility to Depression and Antidepressant Response.
Article in Biological psychiatry global open science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Recent developments in omics studies and artificial intelligence in depression and suicide.Translational psychiatry · 2025Pooled it
- Aberrant expression of long non-coding RNAs and their regulatory role in chromatin-mediated gene expression changes in the prefrontal cortex of major depressive disorder subjects.Molecular psychiatry · 2026Article
- Cross-Trait Cross-Genome Cross-Organ Analysis of Gastrointestinal Disorders and Depression.Digestive diseases and sciences · 2025Article
- Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Background: Depression involves maladaptive processes impairing an individual's ability to interface with the environment appropriately. Long noncoding RNAs (lncRNAs) are gaining traction for their role in higher-order brain functioning. Recently, we reported that lncRNA coexpression modules may underlie abnormal responses to stress in rats showing depression-like behavior. The current study explored the global expression regulation of lncRNAs and messenger RNAs (mRNAs) in the hippocampus of rats showing susceptibility (learned helplessness [LH]) or resiliency (non-LH) to depression and fluoxetine response to LH (LH+FLX). Methods: Multiple comparison analysis was performed with an analysis of variance via the Results: Multiple comparison analyses revealed differentially expressed mRNAs and lncRNAs with each phenotype. Integrated bioinformatics analysis identified novel transcripts, specific modules, and regulatory pairs of mRNA-lncRNA in each phenotype. In addition, the machine learning approach predicted lncRNA-regulated Conclusions: The study shows a novel role for lncRNAs in the development of specific depression phenotypes and in identifying newer targets for therapeutic development.
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Registered trials
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