Integrative Analysis for Elucidating Transcriptomics Landscapes of Glucocorticoid-Induced Osteoporosis

Xiaoxia Ying; Xiyun Jin; Pingping Wang; Yuzhu He; Haomiao Zhang; Xiang Ren; Songling Chai; Wenqi Fu; Pengcheng Zhao; Chen Chen; Guowu Ma; Huiying Liu

doi:10.3389/fcell.2020.00252

Integrative Analysis for Elucidating Transcriptomics Landscapes of Glucocorticoid-Induced Osteoporosis

Xiaoxia Ying
, Xiyun Jin
, Pingping Wang
, Yuzhu He
, Haomiao Zhang
, Xiang Ren
, Songling Chai
, Wenqi Fu
, Pengcheng Zhao
, Chen Chen
, Guowu Ma^*
, Huiying Liu

^*Corresponding author for this work

Dalian Medical University
School of Life Science and Technology, Harbin Institute of Technology

Research output: Contribution to journal › Article › peer-review

5 Scopus citations

Abstract

Osteoporosis is the most common bone metabolic disease, characterized by bone mass loss and bone microstructure changes due to unbalanced bone conversion, which increases bone fragility and fracture risk. Glucocorticoids are clinically used to treat a variety of diseases, including inflammation, cancer and autoimmune diseases. However, excess glucocorticoids can cause osteoporosis. Herein we performed an integrated analysis of two glucocorticoid-related microarray datasets. The WGCNA analysis identified 3 and 4 glucocorticoid-related gene modules, respectively. Differential expression analysis revealed 1047 and 844 differentially expressed genes in the two datasets. After integrating differentially expressed glucocorticoid-related genes, we found that most of the robust differentially expressed genes were up-regulated. Through protein-protein interaction analysis, we obtained 158 glucocorticoid-related candidate genes. Enrichment analysis showed that these genes are significantly enriched in the osteoporosis related pathways. Our results provided new insights into glucocorticoid-induced osteoporosis and potential candidate markers of osteoporosis.

Original language	English
Article number	252
Journal	Frontiers in Cell and Developmental Biology
Volume	8
DOIs	https://doi.org/10.3389/fcell.2020.00252
State	Published - 16 Apr 2020
Externally published	Yes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

enrichment analysis
glucocorticoid
microarray
osteoporosis
protein-protein interaction

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10.3389/fcell.2020.00252

Cite this

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title = "Integrative Analysis for Elucidating Transcriptomics Landscapes of Glucocorticoid-Induced Osteoporosis",

abstract = "Osteoporosis is the most common bone metabolic disease, characterized by bone mass loss and bone microstructure changes due to unbalanced bone conversion, which increases bone fragility and fracture risk. Glucocorticoids are clinically used to treat a variety of diseases, including inflammation, cancer and autoimmune diseases. However, excess glucocorticoids can cause osteoporosis. Herein we performed an integrated analysis of two glucocorticoid-related microarray datasets. The WGCNA analysis identified 3 and 4 glucocorticoid-related gene modules, respectively. Differential expression analysis revealed 1047 and 844 differentially expressed genes in the two datasets. After integrating differentially expressed glucocorticoid-related genes, we found that most of the robust differentially expressed genes were up-regulated. Through protein-protein interaction analysis, we obtained 158 glucocorticoid-related candidate genes. Enrichment analysis showed that these genes are significantly enriched in the osteoporosis related pathways. Our results provided new insights into glucocorticoid-induced osteoporosis and potential candidate markers of osteoporosis.",

keywords = "enrichment analysis, glucocorticoid, microarray, osteoporosis, protein-protein interaction",

author = "Xiaoxia Ying and Xiyun Jin and Pingping Wang and Yuzhu He and Haomiao Zhang and Xiang Ren and Songling Chai and Wenqi Fu and Pengcheng Zhao and Chen Chen and Guowu Ma and Huiying Liu",

note = "Publisher Copyright: {\textcopyright} Copyright {\textcopyright} 2020 Ying, Jin, Wang, He, Zhang, Ren, Chai, Fu, Zhao, Chen, Ma and Liu.",

year = "2020",

month = apr,

day = "16",

doi = "10.3389/fcell.2020.00252",

language = "英语",

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TY - JOUR

T1 - Integrative Analysis for Elucidating Transcriptomics Landscapes of Glucocorticoid-Induced Osteoporosis

AU - Ying, Xiaoxia

AU - Jin, Xiyun

AU - Wang, Pingping

AU - He, Yuzhu

AU - Zhang, Haomiao

AU - Ren, Xiang

AU - Chai, Songling

AU - Fu, Wenqi

AU - Zhao, Pengcheng

AU - Chen, Chen

AU - Ma, Guowu

AU - Liu, Huiying

PY - 2020/4/16

Y1 - 2020/4/16

N2 - Osteoporosis is the most common bone metabolic disease, characterized by bone mass loss and bone microstructure changes due to unbalanced bone conversion, which increases bone fragility and fracture risk. Glucocorticoids are clinically used to treat a variety of diseases, including inflammation, cancer and autoimmune diseases. However, excess glucocorticoids can cause osteoporosis. Herein we performed an integrated analysis of two glucocorticoid-related microarray datasets. The WGCNA analysis identified 3 and 4 glucocorticoid-related gene modules, respectively. Differential expression analysis revealed 1047 and 844 differentially expressed genes in the two datasets. After integrating differentially expressed glucocorticoid-related genes, we found that most of the robust differentially expressed genes were up-regulated. Through protein-protein interaction analysis, we obtained 158 glucocorticoid-related candidate genes. Enrichment analysis showed that these genes are significantly enriched in the osteoporosis related pathways. Our results provided new insights into glucocorticoid-induced osteoporosis and potential candidate markers of osteoporosis.

AB - Osteoporosis is the most common bone metabolic disease, characterized by bone mass loss and bone microstructure changes due to unbalanced bone conversion, which increases bone fragility and fracture risk. Glucocorticoids are clinically used to treat a variety of diseases, including inflammation, cancer and autoimmune diseases. However, excess glucocorticoids can cause osteoporosis. Herein we performed an integrated analysis of two glucocorticoid-related microarray datasets. The WGCNA analysis identified 3 and 4 glucocorticoid-related gene modules, respectively. Differential expression analysis revealed 1047 and 844 differentially expressed genes in the two datasets. After integrating differentially expressed glucocorticoid-related genes, we found that most of the robust differentially expressed genes were up-regulated. Through protein-protein interaction analysis, we obtained 158 glucocorticoid-related candidate genes. Enrichment analysis showed that these genes are significantly enriched in the osteoporosis related pathways. Our results provided new insights into glucocorticoid-induced osteoporosis and potential candidate markers of osteoporosis.

KW - enrichment analysis

KW - glucocorticoid

KW - microarray

KW - osteoporosis

KW - protein-protein interaction

UR - https://www.scopus.com/pages/publications/85084058396

U2 - 10.3389/fcell.2020.00252

DO - 10.3389/fcell.2020.00252

M3 - 文章

AN - SCOPUS:85084058396

SN - 2296-634X

VL - 8

JO - Frontiers in Cell and Developmental Biology

JF - Frontiers in Cell and Developmental Biology

M1 - 252

ER -

Integrative Analysis for Elucidating Transcriptomics Landscapes of Glucocorticoid-Induced Osteoporosis

Abstract

UN SDGs

Keywords

Access to Document

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