Evidence map›Paper›PMID 33504954›Full record

ArticleMolecular psychiatry2021

Similarities and dissimilarities between psychiatric cluster disorders.

Marissa A Smail, Xiaojun Wu, Nicholas D Henkel, Hunter M Eby, James P Herman, Robert E McCullumsmith, Rammohan Shukla

Open access · hybridAbstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.4field-weighted citation impact, top 24% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 22 citations in OpenAlex.

  1. Molecular Characterization of the Progressive Landscape of Depression.bioRxiv : the preprint server for biology · 2026
    Article
  2. Article
  3. Article
  4. The Ribosome Hypothesis: Decoding Mood Disorder Complexity.International journal of molecular sciences · 2024
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 4 institutions in 1 country.

Marissa A SmailDepartment of Pharmacology and Systems Physiology, University of Cincinnati, Cincinnati, OH, USA.
Xiaojun WuDepartment of Neurosciences, University of Toledo College of Medicine and Life Sciences, Toledo, OH, USA.
Nicholas D HenkelDepartment of Neurosciences, University of Toledo College of Medicine and Life Sciences, Toledo, OH, USA.
Hunter M EbyDepartment of Neurosciences, University of Toledo College of Medicine and Life Sciences, Toledo, OH, USA.
James P HermanDepartment of Pharmacology and Systems Physiology, University of Cincinnati, Cincinnati, OH, USA.
Robert E McCullumsmithDepartment of Neurosciences, University of Toledo College of Medicine and Life Sciences, Toledo, OH, USA.
Rammohan ShuklaDepartment of Neurosciences, University of Toledo College of Medicine and Life Sciences, Toledo, OH, USA. Rammohan.Shukla@utoledo.edu.ORCID http://orcid.org/0000-0001-5776-2506
University of Toledo · USNeurosciences Institute · USUniversity of Cincinnati · USVeterans Health Administration · US

Funding

Translational assessment of brain bioenergetic function in schizophreniaR01MH121102 · NIMH · UNIVERSITY OF MARYLAND BALTIMORE · PI MARANO, CHRISTOPHER, MCCULLUMSMITH, ROBERT E · 2020 to 2024
$3.7M
Cell-specific analysis of sub-kinomes in schizophreniaR01MH107487 · NIMH · UNIVERSITY OF TOLEDO HEALTH SCI CAMPUS · PI MCCULLUMSMITH, ROBERT E, MELLER, JAREK · 2016 to 2020
$1.9M
NIMH NIH HHS R01 MH107487NIMH NIH HHS R01 MH121102
6 · The paper itself

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.

Indexed as

Mental DisordersCluster AnalysisCognitionCohort StudiesGene ExpressionHumans

Identifiers

PMID33504954
PMCPMC8313609
OpenAlexW3122633773

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.