Diversity and molecular network patterns of symptom phenotypes

Abstract Symptom phenotypes have continuously been an important clinical entity for clinical diagnosis and management. However, non-specificity of symptom phenotypes for clinical diagnosis is one of the major challenges that need be addressed to advance symptom science and precision health. Network...

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Autores principales:	Zixin Shu, Jingjing Wang, Hailong Sun, Ning Xu, Chenxia Lu, Runshun Zhang, Xiaodong Li, Baoyan Liu, Xuezhong Zhou
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/1802325a07ef4963a85768cbff6172f2
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spelling	oai:doaj.org-article:1802325a07ef4963a85768cbff6172f22021-12-05T12:10:44ZDiversity and molecular network patterns of symptom phenotypes10.1038/s41540-021-00206-52056-7189https://doaj.org/article/1802325a07ef4963a85768cbff6172f22021-11-01T00:00:00Zhttps://doi.org/10.1038/s41540-021-00206-5https://doaj.org/toc/2056-7189Abstract Symptom phenotypes have continuously been an important clinical entity for clinical diagnosis and management. However, non-specificity of symptom phenotypes for clinical diagnosis is one of the major challenges that need be addressed to advance symptom science and precision health. Network medicine has delivered a successful approach for understanding the underlying mechanisms of complex disease phenotypes, which will also be a useful tool for symptom science. Here, we extracted symptom co-occurrences from clinical textbooks to construct phenotype network of symptoms with clinical co-occurrence and incorporated high-quality symptom-gene associations and protein–protein interactions to explore the molecular network patterns of symptom phenotypes. Furthermore, we adopted established network diversity measure in network medicine to quantify both the phenotypic diversity (i.e., non-specificity) and molecular diversity of symptom phenotypes. The results showed that the clinical diversity of symptom phenotypes could partially be explained by their underlying molecular network diversity (PCC = 0.49, P-value = 2.14E-08). For example, non-specific symptoms, such as chill, vomiting, and amnesia, have both high phenotypic and molecular network diversities. Moreover, we further validated and confirmed the approach of symptom clusters to reduce the non-specificity of symptom phenotypes. Network diversity proposes a useful approach to evaluate the non-specificity of symptom phenotypes and would help elucidate the underlying molecular network mechanisms of symptom phenotypes and thus promotes the advance of symptom science for precision health.Zixin ShuJingjing WangHailong SunNing XuChenxia LuRunshun ZhangXiaodong LiBaoyan LiuXuezhong ZhouNature PortfolioarticleBiology (General)QH301-705.5ENnpj Systems Biology and Applications, Vol 7, Iss 1, Pp 1-14 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Zixin Shu Jingjing Wang Hailong Sun Ning Xu Chenxia Lu Runshun Zhang Xiaodong Li Baoyan Liu Xuezhong Zhou Diversity and molecular network patterns of symptom phenotypes
description	Abstract Symptom phenotypes have continuously been an important clinical entity for clinical diagnosis and management. However, non-specificity of symptom phenotypes for clinical diagnosis is one of the major challenges that need be addressed to advance symptom science and precision health. Network medicine has delivered a successful approach for understanding the underlying mechanisms of complex disease phenotypes, which will also be a useful tool for symptom science. Here, we extracted symptom co-occurrences from clinical textbooks to construct phenotype network of symptoms with clinical co-occurrence and incorporated high-quality symptom-gene associations and protein–protein interactions to explore the molecular network patterns of symptom phenotypes. Furthermore, we adopted established network diversity measure in network medicine to quantify both the phenotypic diversity (i.e., non-specificity) and molecular diversity of symptom phenotypes. The results showed that the clinical diversity of symptom phenotypes could partially be explained by their underlying molecular network diversity (PCC = 0.49, P-value = 2.14E-08). For example, non-specific symptoms, such as chill, vomiting, and amnesia, have both high phenotypic and molecular network diversities. Moreover, we further validated and confirmed the approach of symptom clusters to reduce the non-specificity of symptom phenotypes. Network diversity proposes a useful approach to evaluate the non-specificity of symptom phenotypes and would help elucidate the underlying molecular network mechanisms of symptom phenotypes and thus promotes the advance of symptom science for precision health.
format	article
author	Zixin Shu Jingjing Wang Hailong Sun Ning Xu Chenxia Lu Runshun Zhang Xiaodong Li Baoyan Liu Xuezhong Zhou
author_facet	Zixin Shu Jingjing Wang Hailong Sun Ning Xu Chenxia Lu Runshun Zhang Xiaodong Li Baoyan Liu Xuezhong Zhou
author_sort	Zixin Shu
title	Diversity and molecular network patterns of symptom phenotypes
title_short	Diversity and molecular network patterns of symptom phenotypes
title_full	Diversity and molecular network patterns of symptom phenotypes
title_fullStr	Diversity and molecular network patterns of symptom phenotypes
title_full_unstemmed	Diversity and molecular network patterns of symptom phenotypes
title_sort	diversity and molecular network patterns of symptom phenotypes
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/1802325a07ef4963a85768cbff6172f2
work_keys_str_mv	AT zixinshu diversityandmolecularnetworkpatternsofsymptomphenotypes AT jingjingwang diversityandmolecularnetworkpatternsofsymptomphenotypes AT hailongsun diversityandmolecularnetworkpatternsofsymptomphenotypes AT ningxu diversityandmolecularnetworkpatternsofsymptomphenotypes AT chenxialu diversityandmolecularnetworkpatternsofsymptomphenotypes AT runshunzhang diversityandmolecularnetworkpatternsofsymptomphenotypes AT xiaodongli diversityandmolecularnetworkpatternsofsymptomphenotypes AT baoyanliu diversityandmolecularnetworkpatternsofsymptomphenotypes AT xuezhongzhou diversityandmolecularnetworkpatternsofsymptomphenotypes
_version_	1718372176498786304

Diversity and molecular network patterns of symptom phenotypes

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