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Distinct cytokine profiles in patients with preeclampsia
Objective Preeclampsia (PE) is a common but serious pregnancy complication that adversely affects both maternal and fetal health. However, the mechanisms of its pathogenesis remain unclear, and effective biomarkers for early diagnosis are still lacking. Methods In this retrospective study, comprehen...
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| Published in: | Inflammation research 2023-04, Vol.72 (4), p.847-858 |
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| container_end_page | 858 |
| container_issue | 4 |
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| container_title | Inflammation research |
| container_volume | 72 |
| creator | Guo, Ling Lan, Xiangxin Liu, Shanshan Xu, Lianqiong Zhu, Shiqin Zhao, Hong-jin Meng, Jinlai Li, Yan |
| description | Objective
Preeclampsia (PE) is a common but serious pregnancy complication that adversely affects both maternal and fetal health. However, the mechanisms of its pathogenesis remain unclear, and effective biomarkers for early diagnosis are still lacking.
Methods
In this retrospective study, comprehensive bioinformatic analysis and logistic regression analysis were used to compare profiles of 48 serum cytokines in 27 PE patients with those in 41 normotensive pregnant subjects.
Results
The results revealed that serum cytokine profiles accumulated to different levels between the two groups, which had significant correlations with the clinical features of PE. Nine cytokines with high discriminatory capacity for diagnosising PE (AUC ≥ 0.7) were selected for inclusion in a multivariate logistic regression model for PE and calculated as a probability diagnostic formula. This model constructed from the panel of nine cytokines had better diagnostic performance than any individual cytokine (AUC = 0.97, 95% CI 0.94–1.00,
P
|
| doi_str_mv | 10.1007/s00011-023-01709-z |
| format | article |
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Preeclampsia (PE) is a common but serious pregnancy complication that adversely affects both maternal and fetal health. However, the mechanisms of its pathogenesis remain unclear, and effective biomarkers for early diagnosis are still lacking.
Methods
In this retrospective study, comprehensive bioinformatic analysis and logistic regression analysis were used to compare profiles of 48 serum cytokines in 27 PE patients with those in 41 normotensive pregnant subjects.
Results
The results revealed that serum cytokine profiles accumulated to different levels between the two groups, which had significant correlations with the clinical features of PE. Nine cytokines with high discriminatory capacity for diagnosising PE (AUC ≥ 0.7) were selected for inclusion in a multivariate logistic regression model for PE and calculated as a probability diagnostic formula. This model constructed from the panel of nine cytokines had better diagnostic performance than any individual cytokine (AUC = 0.97, 95% CI 0.94–1.00,
P
< 0.0001), with a sensitivity of 96.30% and a specificity of 90.24%.
Conclusions
The set of cytokine profiles and risk assessment model described here can serve as a basis for developing early clinical diagnostic and therapeutic strategies for PE.</description><identifier>ISSN: 1023-3830</identifier><identifier>EISSN: 1420-908X</identifier><identifier>DOI: 10.1007/s00011-023-01709-z</identifier><identifier>PMID: 36907923</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Allergology ; Biomarkers ; Biomedical and Life Sciences ; Biomedicine ; Cytokines ; Dermatology ; Diagnostic systems ; Female ; Fetuses ; Humans ; Immunology ; Neurology ; Original Research Paper ; Pathogenesis ; Pharmacology/Toxicology ; Pre-eclampsia ; Pre-Eclampsia - diagnosis ; Pre-Eclampsia - etiology ; Preeclampsia ; Pregnancy ; Pregnancy complications ; Regression analysis ; Regression models ; Retrospective Studies ; Rheumatology ; Risk assessment ; Statistical analysis</subject><ispartof>Inflammation research, 2023-04, Vol.72 (4), p.847-858</ispartof><rights>The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><rights>2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c375t-d96b5e78bd16accc78fa183ca25ddcec7eb20f3441a40ddca7ff83646480498f3</citedby><cites>FETCH-LOGICAL-c375t-d96b5e78bd16accc78fa183ca25ddcec7eb20f3441a40ddca7ff83646480498f3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27903,27904</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36907923$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Guo, Ling</creatorcontrib><creatorcontrib>Lan, Xiangxin</creatorcontrib><creatorcontrib>Liu, Shanshan</creatorcontrib><creatorcontrib>Xu, Lianqiong</creatorcontrib><creatorcontrib>Zhu, Shiqin</creatorcontrib><creatorcontrib>Zhao, Hong-jin</creatorcontrib><creatorcontrib>Meng, Jinlai</creatorcontrib><creatorcontrib>Li, Yan</creatorcontrib><title>Distinct cytokine profiles in patients with preeclampsia</title><title>Inflammation research</title><addtitle>Inflamm. Res</addtitle><addtitle>Inflamm Res</addtitle><description>Objective
Preeclampsia (PE) is a common but serious pregnancy complication that adversely affects both maternal and fetal health. However, the mechanisms of its pathogenesis remain unclear, and effective biomarkers for early diagnosis are still lacking.
Methods
In this retrospective study, comprehensive bioinformatic analysis and logistic regression analysis were used to compare profiles of 48 serum cytokines in 27 PE patients with those in 41 normotensive pregnant subjects.
Results
The results revealed that serum cytokine profiles accumulated to different levels between the two groups, which had significant correlations with the clinical features of PE. Nine cytokines with high discriminatory capacity for diagnosising PE (AUC ≥ 0.7) were selected for inclusion in a multivariate logistic regression model for PE and calculated as a probability diagnostic formula. This model constructed from the panel of nine cytokines had better diagnostic performance than any individual cytokine (AUC = 0.97, 95% CI 0.94–1.00,
P
< 0.0001), with a sensitivity of 96.30% and a specificity of 90.24%.
Conclusions
The set of cytokine profiles and risk assessment model described here can serve as a basis for developing early clinical diagnostic and therapeutic strategies for PE.</description><subject>Allergology</subject><subject>Biomarkers</subject><subject>Biomedical and Life Sciences</subject><subject>Biomedicine</subject><subject>Cytokines</subject><subject>Dermatology</subject><subject>Diagnostic systems</subject><subject>Female</subject><subject>Fetuses</subject><subject>Humans</subject><subject>Immunology</subject><subject>Neurology</subject><subject>Original Research Paper</subject><subject>Pathogenesis</subject><subject>Pharmacology/Toxicology</subject><subject>Pre-eclampsia</subject><subject>Pre-Eclampsia - diagnosis</subject><subject>Pre-Eclampsia - etiology</subject><subject>Preeclampsia</subject><subject>Pregnancy</subject><subject>Pregnancy complications</subject><subject>Regression analysis</subject><subject>Regression models</subject><subject>Retrospective Studies</subject><subject>Rheumatology</subject><subject>Risk assessment</subject><subject>Statistical analysis</subject><issn>1023-3830</issn><issn>1420-908X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNp9kE1LxDAURYMozjj6B1xIwY2b6kvSNulSxk8YcKPgLqRpohn7ZZMiM7_ejB0VXLhKyD3v5nEQOsZwjgHYhQMAjGMgNAbMII_XO2iKEwJxDvx5N9w3EeUUJujAuWXAOeFkH01olgPLCZ0ifmWdt43ykVr59s02Our61thKu8g2USe91Y130Yf1ryHRWlWy7pyVh2jPyMrpo-05Q08314_zu3jxcHs_v1zEirLUx2WeFalmvChxJpVSjBuJOVWSpGWptGK6IGBokmCZQHiRzBhOsyRLOCQ5N3SGzsbesNb7oJ0XtXVKV5VsdDs4QRjPUowJowE9_YMu26FvwnaCcEgZzSjPAkVGSvWtc702outtLfuVwCA2XsXoVQR54surWIehk231UNS6_Bn5FhkAOgIuRM2L7n___qf2E2zFg5Q</recordid><startdate>20230401</startdate><enddate>20230401</enddate><creator>Guo, Ling</creator><creator>Lan, Xiangxin</creator><creator>Liu, Shanshan</creator><creator>Xu, Lianqiong</creator><creator>Zhu, Shiqin</creator><creator>Zhao, Hong-jin</creator><creator>Meng, Jinlai</creator><creator>Li, Yan</creator><general>Springer International Publishing</general><general>Springer Nature B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QL</scope><scope>7T5</scope><scope>7T7</scope><scope>7TM</scope><scope>7TO</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8FD</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>H94</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope></search><sort><creationdate>20230401</creationdate><title>Distinct cytokine profiles in patients with preeclampsia</title><author>Guo, Ling ; Lan, Xiangxin ; Liu, Shanshan ; Xu, Lianqiong ; Zhu, Shiqin ; Zhao, Hong-jin ; Meng, Jinlai ; Li, Yan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c375t-d96b5e78bd16accc78fa183ca25ddcec7eb20f3441a40ddca7ff83646480498f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Allergology</topic><topic>Biomarkers</topic><topic>Biomedical and Life Sciences</topic><topic>Biomedicine</topic><topic>Cytokines</topic><topic>Dermatology</topic><topic>Diagnostic systems</topic><topic>Female</topic><topic>Fetuses</topic><topic>Humans</topic><topic>Immunology</topic><topic>Neurology</topic><topic>Original Research Paper</topic><topic>Pathogenesis</topic><topic>Pharmacology/Toxicology</topic><topic>Pre-eclampsia</topic><topic>Pre-Eclampsia - diagnosis</topic><topic>Pre-Eclampsia - etiology</topic><topic>Preeclampsia</topic><topic>Pregnancy</topic><topic>Pregnancy complications</topic><topic>Regression analysis</topic><topic>Regression models</topic><topic>Retrospective Studies</topic><topic>Rheumatology</topic><topic>Risk assessment</topic><topic>Statistical analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Guo, Ling</creatorcontrib><creatorcontrib>Lan, Xiangxin</creatorcontrib><creatorcontrib>Liu, Shanshan</creatorcontrib><creatorcontrib>Xu, Lianqiong</creatorcontrib><creatorcontrib>Zhu, Shiqin</creatorcontrib><creatorcontrib>Zhao, Hong-jin</creatorcontrib><creatorcontrib>Meng, Jinlai</creatorcontrib><creatorcontrib>Li, Yan</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Immunology Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Nucleic Acids Abstracts</collection><collection>Oncogenes and Growth Factors Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Health Medical collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>PML(ProQuest Medical Library)</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><jtitle>Inflammation research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Guo, Ling</au><au>Lan, Xiangxin</au><au>Liu, Shanshan</au><au>Xu, Lianqiong</au><au>Zhu, Shiqin</au><au>Zhao, Hong-jin</au><au>Meng, Jinlai</au><au>Li, Yan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Distinct cytokine profiles in patients with preeclampsia</atitle><jtitle>Inflammation research</jtitle><stitle>Inflamm. Res</stitle><addtitle>Inflamm Res</addtitle><date>2023-04-01</date><risdate>2023</risdate><volume>72</volume><issue>4</issue><spage>847</spage><epage>858</epage><pages>847-858</pages><issn>1023-3830</issn><eissn>1420-908X</eissn><abstract>Objective
Preeclampsia (PE) is a common but serious pregnancy complication that adversely affects both maternal and fetal health. However, the mechanisms of its pathogenesis remain unclear, and effective biomarkers for early diagnosis are still lacking.
Methods
In this retrospective study, comprehensive bioinformatic analysis and logistic regression analysis were used to compare profiles of 48 serum cytokines in 27 PE patients with those in 41 normotensive pregnant subjects.
Results
The results revealed that serum cytokine profiles accumulated to different levels between the two groups, which had significant correlations with the clinical features of PE. Nine cytokines with high discriminatory capacity for diagnosising PE (AUC ≥ 0.7) were selected for inclusion in a multivariate logistic regression model for PE and calculated as a probability diagnostic formula. This model constructed from the panel of nine cytokines had better diagnostic performance than any individual cytokine (AUC = 0.97, 95% CI 0.94–1.00,
P
< 0.0001), with a sensitivity of 96.30% and a specificity of 90.24%.
Conclusions
The set of cytokine profiles and risk assessment model described here can serve as a basis for developing early clinical diagnostic and therapeutic strategies for PE.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><pmid>36907923</pmid><doi>10.1007/s00011-023-01709-z</doi><tpages>12</tpages></addata></record> |
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| subjects | Allergology Biomarkers Biomedical and Life Sciences Biomedicine Cytokines Dermatology Diagnostic systems Female Fetuses Humans Immunology Neurology Original Research Paper Pathogenesis Pharmacology/Toxicology Pre-eclampsia Pre-Eclampsia - diagnosis Pre-Eclampsia - etiology Preeclampsia Pregnancy Pregnancy complications Regression analysis Regression models Retrospective Studies Rheumatology Risk assessment Statistical analysis |
| title | Distinct cytokine profiles in patients with preeclampsia |
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