ArticleMolecular psychiatry2021
Similarities and dissimilarities between psychiatric cluster disorders.
Article in Molecular psychiatry, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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
10 citing papers in PubMed, 22 citations in OpenAlex.
- Molecular Characterization of the Progressive Landscape of Depression.bioRxiv : the preprint server for biology · 2026Article
- Transcriptomic Analysis of the Amygdala in Subjects with Schizophrenia, Bipolar Disorder and Major Depressive Disorder Reveals Differentially Altered Metabolic Pathways.Schizophrenia bulletin · 2026Article
- Differentially Altered Metabolic Pathways in the Amygdala of Subjects with Schizophrenia, Bipolar Disorder and Major Depressive Disorder.medRxiv : the preprint server for health sciences · 2024Article
- The Ribosome Hypothesis: Decoding Mood Disorder Complexity.International journal of molecular sciences · 2024Article
- Ribosomal dysregulation: A conserved pathophysiological mechanism in human depression and mouse chronic stress.PNAS nexus · 2023Article
- Article
- Differential vulnerability of anterior cingulate cortex cell types to diseases and drugs.Molecular psychiatry · 2022Article
- Transdiagnostic connectome signatures from resting-state fMRI predict individual-level intellectual capacity.Translational psychiatry · 2022Article
- A Retrospective Study on the Factors Associated with Long-Stay Hospitalization in a Child Neuropsychiatry Unit.Healthcare (Basel, Switzerland) · 2021Article
- Comorbid Chronic Pain and Depression: Shared Risk Factors and Differential Antidepressant Effectiveness.Frontiers in psychiatry · 2021Article
Corrections and comments
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Authors and funding
7 authors at 4 institutions in 1 country.
Funding
Abstract
The common molecular mechanisms underlying psychiatric disorders are not well understood. Prior attempts to assess the pathological mechanisms responsible for psychiatric disorders have been limited by biased selection of comparable disorders, datasets/cohort availability, and challenges with data normalization. Here, using DisGeNET, a gene-disease associations database, we sought to expand such investigations in terms of number and types of diseases. In a top-down manner, we analyzed an unbiased cluster of 36 psychiatric disorders and comorbid conditions at biological pathway, cell-type, drug-target, and chromosome levels and deployed density index, a novel metric to quantify similarities (close to 1) and dissimilarities (close to 0) between these disorders at each level. At pathway level, we show that cognition and neurotransmission drive the similarity and are involved across all disorders, whereas immune-system and signal-response coupling (cell surface receptors, signal transduction, gene expression, and metabolic process) drives the dissimilarity and are involved with specific disorders. The analysis at the drug-target level supports the involvement of neurotransmission-related changes across these disorders. At cell-type level, dendrite-targeting interneurons, across all layers, are most involved. Finally, by matching the clustering pattern at each level of analysis, we showed that the similarity between the disorders is influenced most at the chromosomal level and to some extent at the cellular level. Together, these findings provide first insights into distinct cellular and molecular pathologies, druggable mechanisms associated with several psychiatric disorders and comorbid conditions and demonstrate that similarities between these disorders originate at the chromosome level and disperse in a bottom-up manner at cellular and pathway levels.
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