Similarities and dissimilarities between psychiatric cluster disorders

• Published in: Molecular psychiatry Vol. 26; no. 9; pp. 4853 - 4863
• Main Authors: Smail, Marissa A., Wu, Xiaojun, Henkel, Nicholas D., Eby, Hunter M., Herman, James P., McCullumsmith, Robert E., Shukla, Rammohan
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 01-09-2021; Nature Publishing Group
• Subjects: 38; 631/378; 631/477; 692/699/476; Behavioral Sciences; Biological Psychology; Cell surface; Chromosomes; Cluster Analysis; Cognition; Cohort Studies; Comorbidity; Comparative analysis; Development and progression; Gene Expression; Genetic aspects; Humans; Interneurons; Medicine; Medicine & Public Health; Mental disorders; Mental Disorders - genetics; Molecular modelling; Neurosciences; Neurotransmission; Personality disorders; Pharmacotherapy; Psychiatry; Signal transduction; Therapeutic targets; United States
• ISSN: 1359-4184; 1476-5578
• DOI: 10.1038/s41380-021-01030-3

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.