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M171. THE GENE-SHARING RELATIONSHIP OF SCHIZOPHRENIA WITH OTHER MENTAL OR SYSTEMIC DISORDERS: A DISEASE-SIMILARITY NETWORK ANALYSIS FOCUSED ON EGOCENTRIC NETWORK

BACKGROUND: Schizophrenia is an archetypal example that a psychiatric illness may not merely be a mental or a brain disorder but rather a systemic illness. It can be glimpsed from a wide range of biomarkers that span all the imaginable body systems, and from higher co-morbidity with other systemic i...

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Autores principales: Hoon Jeong, Seong, Jung, Hee-Yeon, Won Chung, In, Sik Kim, Yong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7234452/
http://dx.doi.org/10.1093/schbul/sbaa030.483
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author Hoon Jeong, Seong
Jung, Hee-Yeon
Won Chung, In
Sik Kim, Yong
author_facet Hoon Jeong, Seong
Jung, Hee-Yeon
Won Chung, In
Sik Kim, Yong
author_sort Hoon Jeong, Seong
collection PubMed
description BACKGROUND: Schizophrenia is an archetypal example that a psychiatric illness may not merely be a mental or a brain disorder but rather a systemic illness. It can be glimpsed from a wide range of biomarkers that span all the imaginable body systems, and from higher co-morbidity with other systemic illnesses. However, quantitative analysis of schizophrenia’s relationship with other diseases are not yet satisfactory. Genome-wide association studies have identified more than hundreds of genetic loci associated with schizophrenia. In turn, these loci are associated with a wide variety of other diseases. From this gene-disease relationship, a bipartite network can be built which, after appropriate projection, could help to map a complex disease-similarity network. In case of schizophrenia, it would reveal the position of schizophrenia among the broader categories of systemic illnesses. METHODS: DisGeNET is a discovery platform which contains one of the largest collections of gene-disease association data. The major source of the integrated data is the automatized curation from MEDLINE abstract. Therefore, it contains the timestamp of reported gene-disease association. Gene-disease-timestamp (year of publication) triplet was fed into a Neo4J graph database platform. From this, disease-disease relationships with shared gene count and Jaccard similarity score was extracted. The network structure of level 1.5 egocentric network centered upon schizophrenia was inspected. Louvain community detection algorithm was applied to expose underlying group structure among the 1st order alters. For comparison, similar ego-networks centered upon several major psychiatric illnesses were also inspected. Finally, the yearly variation of Jaccard score which reflected the accumulation of research data were monitored. RESULTS: The diseases which showed the highest Jaccard score (j) were bipolar disorder (j=0.203) and depressive disorder (j=0.190) as expected. Other diseases with meaningful similarity could be grouped into three communities: 1) psychiatric illness including bipolar/depressive disorder, 2) a variety of malignancies including neuroblastoma (j=0.083), stomach cancer (j=0.070) and pancreatic cancer (j=0.065) 3) other systemic illnesses including multiple sclerosis (j=0.088), metabolic syndrome (j=0.076), myocardial infarction (j=0.073), rheumatoid arthritis (j=0.070), lupus erythematosus (0.056). The gene-sharing relationship with systemic illnesses (malignancies and other) began to be revealed after 2005. Since then, more and more evidences were accumulated to solidify the schizophrenia’s link with systemic illnesses. DISCUSSION: Recently, a couple of large-scale epidemiological studies verified the significant correlation between prevalence of schizophrenia and cancer/autoimmune disorders. The present study results may augment these epidemiological data and thus strongly support the concept of schizophrenia as a systemic illness. Gene-sharing and its reflection in prevalence data would indicate deeper link at the level of pathogenesis with systemic illnesses. Recently, many authors contemplated the possible link between schizophrenia and cancer in terms of cell cycle regulation and control of apoptosis. Likewise, others suspected immunological disturbance as the fundamental mechanism of schizophrenia. In this vein, the need for extending the concept of mental disorders as a focused manifestation of systemic illness seems gaining impetus.
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spelling pubmed-72344522020-05-23 M171. THE GENE-SHARING RELATIONSHIP OF SCHIZOPHRENIA WITH OTHER MENTAL OR SYSTEMIC DISORDERS: A DISEASE-SIMILARITY NETWORK ANALYSIS FOCUSED ON EGOCENTRIC NETWORK Hoon Jeong, Seong Jung, Hee-Yeon Won Chung, In Sik Kim, Yong Schizophr Bull Poster Session II BACKGROUND: Schizophrenia is an archetypal example that a psychiatric illness may not merely be a mental or a brain disorder but rather a systemic illness. It can be glimpsed from a wide range of biomarkers that span all the imaginable body systems, and from higher co-morbidity with other systemic illnesses. However, quantitative analysis of schizophrenia’s relationship with other diseases are not yet satisfactory. Genome-wide association studies have identified more than hundreds of genetic loci associated with schizophrenia. In turn, these loci are associated with a wide variety of other diseases. From this gene-disease relationship, a bipartite network can be built which, after appropriate projection, could help to map a complex disease-similarity network. In case of schizophrenia, it would reveal the position of schizophrenia among the broader categories of systemic illnesses. METHODS: DisGeNET is a discovery platform which contains one of the largest collections of gene-disease association data. The major source of the integrated data is the automatized curation from MEDLINE abstract. Therefore, it contains the timestamp of reported gene-disease association. Gene-disease-timestamp (year of publication) triplet was fed into a Neo4J graph database platform. From this, disease-disease relationships with shared gene count and Jaccard similarity score was extracted. The network structure of level 1.5 egocentric network centered upon schizophrenia was inspected. Louvain community detection algorithm was applied to expose underlying group structure among the 1st order alters. For comparison, similar ego-networks centered upon several major psychiatric illnesses were also inspected. Finally, the yearly variation of Jaccard score which reflected the accumulation of research data were monitored. RESULTS: The diseases which showed the highest Jaccard score (j) were bipolar disorder (j=0.203) and depressive disorder (j=0.190) as expected. Other diseases with meaningful similarity could be grouped into three communities: 1) psychiatric illness including bipolar/depressive disorder, 2) a variety of malignancies including neuroblastoma (j=0.083), stomach cancer (j=0.070) and pancreatic cancer (j=0.065) 3) other systemic illnesses including multiple sclerosis (j=0.088), metabolic syndrome (j=0.076), myocardial infarction (j=0.073), rheumatoid arthritis (j=0.070), lupus erythematosus (0.056). The gene-sharing relationship with systemic illnesses (malignancies and other) began to be revealed after 2005. Since then, more and more evidences were accumulated to solidify the schizophrenia’s link with systemic illnesses. DISCUSSION: Recently, a couple of large-scale epidemiological studies verified the significant correlation between prevalence of schizophrenia and cancer/autoimmune disorders. The present study results may augment these epidemiological data and thus strongly support the concept of schizophrenia as a systemic illness. Gene-sharing and its reflection in prevalence data would indicate deeper link at the level of pathogenesis with systemic illnesses. Recently, many authors contemplated the possible link between schizophrenia and cancer in terms of cell cycle regulation and control of apoptosis. Likewise, others suspected immunological disturbance as the fundamental mechanism of schizophrenia. In this vein, the need for extending the concept of mental disorders as a focused manifestation of systemic illness seems gaining impetus. Oxford University Press 2020-05 2020-05-18 /pmc/articles/PMC7234452/ http://dx.doi.org/10.1093/schbul/sbaa030.483 Text en © The Author(s) 2020. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Poster Session II
Hoon Jeong, Seong
Jung, Hee-Yeon
Won Chung, In
Sik Kim, Yong
M171. THE GENE-SHARING RELATIONSHIP OF SCHIZOPHRENIA WITH OTHER MENTAL OR SYSTEMIC DISORDERS: A DISEASE-SIMILARITY NETWORK ANALYSIS FOCUSED ON EGOCENTRIC NETWORK
title M171. THE GENE-SHARING RELATIONSHIP OF SCHIZOPHRENIA WITH OTHER MENTAL OR SYSTEMIC DISORDERS: A DISEASE-SIMILARITY NETWORK ANALYSIS FOCUSED ON EGOCENTRIC NETWORK
title_full M171. THE GENE-SHARING RELATIONSHIP OF SCHIZOPHRENIA WITH OTHER MENTAL OR SYSTEMIC DISORDERS: A DISEASE-SIMILARITY NETWORK ANALYSIS FOCUSED ON EGOCENTRIC NETWORK
title_fullStr M171. THE GENE-SHARING RELATIONSHIP OF SCHIZOPHRENIA WITH OTHER MENTAL OR SYSTEMIC DISORDERS: A DISEASE-SIMILARITY NETWORK ANALYSIS FOCUSED ON EGOCENTRIC NETWORK
title_full_unstemmed M171. THE GENE-SHARING RELATIONSHIP OF SCHIZOPHRENIA WITH OTHER MENTAL OR SYSTEMIC DISORDERS: A DISEASE-SIMILARITY NETWORK ANALYSIS FOCUSED ON EGOCENTRIC NETWORK
title_short M171. THE GENE-SHARING RELATIONSHIP OF SCHIZOPHRENIA WITH OTHER MENTAL OR SYSTEMIC DISORDERS: A DISEASE-SIMILARITY NETWORK ANALYSIS FOCUSED ON EGOCENTRIC NETWORK
title_sort m171. the gene-sharing relationship of schizophrenia with other mental or systemic disorders: a disease-similarity network analysis focused on egocentric network
topic Poster Session II
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7234452/
http://dx.doi.org/10.1093/schbul/sbaa030.483
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