Identification of the transcriptome signatures and immune-inflammatory responses in postmenopausal osteoporosis

Gao, Pan1,2,3; Pan, Xiaoguang4; Wang, Shang6; Guo, Sijia3; Dong, Zhanying3; Wang, Zhefeng6; Liang, Xue4; Chen, Yan3; Fang, Fang3; Yang, Ling3; Huang, Jinrong3,5; Zhang, Chenxi3; Li, Conghui3,4,5; Luo, Yonglun1,3,4; Peng, Songlin6; Xu, Fengping1,2,3

2024-01-15

10.1016/j.heliyon.2023.e23675

HELIYON   影响因子和分区

2405-8440

Postmenopausal osteoporosis is the most common type of osteoporosis in women. To date, little is known about their transcriptome signatures, although biomarkers from peripheral blood mononuclear cells are attractive for postmenopausal osteoporosis diagnoses. Here, we performed bulk RNA sequencing of 206 samples (124 postmenopausal osteoporosis and 82 normal samples) and described the clinical phenotypic characteristics of postmenopausal women. We then highlighted the gene set enrichment analyses between the extreme T-score group and the heathy control group, revealing that some immune-inflammatory responses were enhanced in postmenopausal osteoporosis, with representative pathways including the mitogen-activated protein kinase (NES = 1.6, FDR <0.11) pathway and B_CELL_RECEPTOR (NES = 1.69, FDR <0.15) pathway. Finally, we developed a combined risk prediction model based on lasso-logistic regression to predict postmenopausal osteoporosis, which combined eleven genes (PTGS2, CXCL16, NECAP1, RPS23, SSR3, CD74, IL4R, BTBD2, PIGS, LILRA2, MAP3K11) and three pieces of clinical information (age, procollagen I N-terminal propeptide, beta isomer of C-terminal telopeptide of type I) and provided the best prediction ability (AUC = 0.97). Taken together, this study filled a gap in the large-scale transcriptome signature profiles and revealed the close relationship between immune-inflammatory responses and postmenopausal osteoporosis, providing a unique perspective for understanding the occurrence and development of postmenopausal osteoporosis.

Postmenopausal osteoporosis Transcriptome signatures RNA sequencing Immune-inflammatory responses Risk prediction model

SCI

英语

通讯

Science, Technology, and Innovation Commission of Shenzhen Municipality["JCYJ20160301151248779","JCYJ20200109150410232"] ; Basic and Applied Basic Research Foundation of Guangdong Province[2019B1515120034]

Science & Technology - Other Topics

Multidisciplinary Sciences

WOS:001138800300001

CELL PRESS

Web of Science

1.Univ Chinese Acad Sci, Coll Life Sci, Beijing 100049, Peoples R China
2.BGI Cell, Shenzhen 518083, Peoples R China
3.BGI Res, Shenzhen 518083, Peoples R China
4.BGI Shenzhen, Qingdao Europe Adv Inst Life Sci, Qingdao 266555, Peoples R China
5.BGI Shenzhen, BGI Qingdao, Lars Bolund Inst Regenerat Med, Qingdao 266555, Peoples R China
6.Southern Univ Sci & Technol, Shenzhen Peoples Hosp, Affiliated Hosp 1, Dept Spine Surg, Shenzhen 518020, Guangdong, Peoples R China

Gao, Pan,Pan, Xiaoguang,Wang, Shang,et al. Identification of the transcriptome signatures and immune-inflammatory responses in postmenopausal osteoporosis[J]. HELIYON,2024,10(1).

Gao, Pan.,Pan, Xiaoguang.,Wang, Shang.,Guo, Sijia.,Dong, Zhanying.,...&Xu, Fengping.(2024).Identification of the transcriptome signatures and immune-inflammatory responses in postmenopausal osteoporosis.HELIYON,10(1).

Gao, Pan,et al."Identification of the transcriptome signatures and immune-inflammatory responses in postmenopausal osteoporosis".HELIYON 10.1(2024).