{"title":"Olink 蛋白质组学用于绝经后骨质疏松症早期诊断生物标志物的鉴定。","authors":"Chunyan Li, Xinwei Zang, Heng Liu, Shangqi Yin, Xiang Cheng, Wei Zhang, Xiangyu Meng, Liyuan Chen, Shuai Lu, Jun Wu","doi":"10.1021/acs.jproteome.4c00470","DOIUrl":null,"url":null,"abstract":"<p><p>This investigation aims to employ Olink proteomics in analyzing the distinct serum proteins associated with postmenopausal osteoporosis (PMOP) and identifying prognostic markers for early detection of PMOP via molecular mechanism research on postmenopausal osteoporosis. Postmenopausal women admitted to Beijing Jishuitan Hospital were randomly selected and categorized into three groups based on their dual-energy X-ray absorptiometry (DXA) T-scores: osteoporosis group (<i>n =</i> 24), osteopenia group (<i>n =</i> 20), and normal bone mass group (<i>n =</i> 16). Serum samples from all participants were collected for clinical and bone metabolism marker measurements. Olink proteomics was utilized to identify differentially expressed proteins (DEPs) that are highly associated with postmenopausal osteoporosis. The functional analysis of DEPs was performed using Gene Ontology and Kyto Encyclopedia Genes and Genomes (KEGG). The biological characteristics of these proteins and their correlation with PMOP were subsequently analyzed. ROC curve analysis was performed to identify potential biomarkers with the highest diagnostic accuracy for early stage PMOP. Through Olink proteomics, we identified five DEPs highly associated with PMOP, including two upregulated and three downregulated proteins. TWEAK and CDCP1 markers exhibited the highest area under the curve (0.8188 and 0.8031, respectively). TWEAK and CDCP1 have the potential to serve as biomarkers for early prediction of postmenopausal osteoporosis.</p>","PeriodicalId":3,"journal":{"name":"ACS Applied Electronic Materials","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11460326/pdf/","citationCount":"0","resultStr":"{\"title\":\"Olink Proteomics for the Identification of Biomarkers for Early Diagnosis of Postmenopausal Osteoporosis.\",\"authors\":\"Chunyan Li, Xinwei Zang, Heng Liu, Shangqi Yin, Xiang Cheng, Wei Zhang, Xiangyu Meng, Liyuan Chen, Shuai Lu, Jun Wu\",\"doi\":\"10.1021/acs.jproteome.4c00470\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>This investigation aims to employ Olink proteomics in analyzing the distinct serum proteins associated with postmenopausal osteoporosis (PMOP) and identifying prognostic markers for early detection of PMOP via molecular mechanism research on postmenopausal osteoporosis. Postmenopausal women admitted to Beijing Jishuitan Hospital were randomly selected and categorized into three groups based on their dual-energy X-ray absorptiometry (DXA) T-scores: osteoporosis group (<i>n =</i> 24), osteopenia group (<i>n =</i> 20), and normal bone mass group (<i>n =</i> 16). Serum samples from all participants were collected for clinical and bone metabolism marker measurements. Olink proteomics was utilized to identify differentially expressed proteins (DEPs) that are highly associated with postmenopausal osteoporosis. The functional analysis of DEPs was performed using Gene Ontology and Kyto Encyclopedia Genes and Genomes (KEGG). The biological characteristics of these proteins and their correlation with PMOP were subsequently analyzed. ROC curve analysis was performed to identify potential biomarkers with the highest diagnostic accuracy for early stage PMOP. Through Olink proteomics, we identified five DEPs highly associated with PMOP, including two upregulated and three downregulated proteins. TWEAK and CDCP1 markers exhibited the highest area under the curve (0.8188 and 0.8031, respectively). TWEAK and CDCP1 have the potential to serve as biomarkers for early prediction of postmenopausal osteoporosis.</p>\",\"PeriodicalId\":3,\"journal\":{\"name\":\"ACS Applied Electronic Materials\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2024-10-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11460326/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Electronic Materials\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1021/acs.jproteome.4c00470\",\"RegionNum\":3,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/9/3 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Electronic Materials","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1021/acs.jproteome.4c00470","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/9/3 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Olink Proteomics for the Identification of Biomarkers for Early Diagnosis of Postmenopausal Osteoporosis.
This investigation aims to employ Olink proteomics in analyzing the distinct serum proteins associated with postmenopausal osteoporosis (PMOP) and identifying prognostic markers for early detection of PMOP via molecular mechanism research on postmenopausal osteoporosis. Postmenopausal women admitted to Beijing Jishuitan Hospital were randomly selected and categorized into three groups based on their dual-energy X-ray absorptiometry (DXA) T-scores: osteoporosis group (n = 24), osteopenia group (n = 20), and normal bone mass group (n = 16). Serum samples from all participants were collected for clinical and bone metabolism marker measurements. Olink proteomics was utilized to identify differentially expressed proteins (DEPs) that are highly associated with postmenopausal osteoporosis. The functional analysis of DEPs was performed using Gene Ontology and Kyto Encyclopedia Genes and Genomes (KEGG). The biological characteristics of these proteins and their correlation with PMOP were subsequently analyzed. ROC curve analysis was performed to identify potential biomarkers with the highest diagnostic accuracy for early stage PMOP. Through Olink proteomics, we identified five DEPs highly associated with PMOP, including two upregulated and three downregulated proteins. TWEAK and CDCP1 markers exhibited the highest area under the curve (0.8188 and 0.8031, respectively). TWEAK and CDCP1 have the potential to serve as biomarkers for early prediction of postmenopausal osteoporosis.