Cargando…

Similarities and dissimilarities between psychiatric cluster disorders

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 n...

Descripción completa

Detalles Bibliográficos
Autores principales: Smail, Marissa A., Wu, Xiaojun, Henkel, Nicholas D., Eby, Hunter M., Herman, James P., McCullumsmith, Robert E., Shukla, Rammohan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8313609/
https://www.ncbi.nlm.nih.gov/pubmed/33504954
http://dx.doi.org/10.1038/s41380-021-01030-3
_version_ 1783729385477505024
author Smail, Marissa A.
Wu, Xiaojun
Henkel, Nicholas D.
Eby, Hunter M.
Herman, James P.
McCullumsmith, Robert E.
Shukla, Rammohan
author_facet Smail, Marissa A.
Wu, Xiaojun
Henkel, Nicholas D.
Eby, Hunter M.
Herman, James P.
McCullumsmith, Robert E.
Shukla, Rammohan
author_sort Smail, Marissa A.
collection PubMed
description 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.
format Online
Article
Text
id pubmed-8313609
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-83136092021-11-17 Similarities and dissimilarities between psychiatric cluster disorders Smail, Marissa A. Wu, Xiaojun Henkel, Nicholas D. Eby, Hunter M. Herman, James P. McCullumsmith, Robert E. Shukla, Rammohan Mol Psychiatry Article 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. Nature Publishing Group UK 2021-01-27 2021 /pmc/articles/PMC8313609/ /pubmed/33504954 http://dx.doi.org/10.1038/s41380-021-01030-3 Text en © This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Smail, Marissa A.
Wu, Xiaojun
Henkel, Nicholas D.
Eby, Hunter M.
Herman, James P.
McCullumsmith, Robert E.
Shukla, Rammohan
Similarities and dissimilarities between psychiatric cluster disorders
title Similarities and dissimilarities between psychiatric cluster disorders
title_full Similarities and dissimilarities between psychiatric cluster disorders
title_fullStr Similarities and dissimilarities between psychiatric cluster disorders
title_full_unstemmed Similarities and dissimilarities between psychiatric cluster disorders
title_short Similarities and dissimilarities between psychiatric cluster disorders
title_sort similarities and dissimilarities between psychiatric cluster disorders
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8313609/
https://www.ncbi.nlm.nih.gov/pubmed/33504954
http://dx.doi.org/10.1038/s41380-021-01030-3
work_keys_str_mv AT smailmarissaa similaritiesanddissimilaritiesbetweenpsychiatricclusterdisorders
AT wuxiaojun similaritiesanddissimilaritiesbetweenpsychiatricclusterdisorders
AT henkelnicholasd similaritiesanddissimilaritiesbetweenpsychiatricclusterdisorders
AT ebyhunterm similaritiesanddissimilaritiesbetweenpsychiatricclusterdisorders
AT hermanjamesp similaritiesanddissimilaritiesbetweenpsychiatricclusterdisorders
AT mccullumsmithroberte similaritiesanddissimilaritiesbetweenpsychiatricclusterdisorders
AT shuklarammohan similaritiesanddissimilaritiesbetweenpsychiatricclusterdisorders