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Fibrinogen beta chain may be a potential predict biomarker for pre-eclampsia: A preliminary study.
Shi, Junzhu; Zeng, Shanshui; Zhang, Yonggang; Zuo, Zhihua; Tan, Xiaoyu.
Afiliação
  • Shi J; Department of Clinical Laboratory, Shenzhen Longhua District Central Hospital, Shenzhen 518110, China.
  • Zeng S; Department of Clinical Laboratory, Guangzhou Women and Children's Medical Center, Guangzhou 510623, China.
  • Zhang Y; Department of Clinical Laboratory, Shenzhen Longhua District Central Hospital, Shenzhen 518110, China.
  • Zuo Z; Department of Clinical Laboratory, Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical College, China.
  • Tan X; Department of Nursing, Shenzhen Longhua District Central Hospital, No. 187 Guanlan Avenue, Longhua District, Shenzhen, 518110, China. Electronic address: 751025537@qq.com.
Clin Chim Acta ; 539: 206-214, 2023 Jan 15.
Article em En | MEDLINE | ID: mdl-36566955
ABSTRACT

OBJECTIVE:

There are no approaches for the early detection of pre-eclampsia (PE). Using parallel reaction monitoring proteomics, we investigated 79 maternal serum protein changes before PE onset and its predictive capability.

METHODS:

We conducted a nested case-control study with 60 PE patients and 60 normotensive pregnant women matched for age and gestational week. These differentially expressed proteins were quantified using the data-dependent acquisition (DDA) combined parallel response monitoring (PRM) approach, and a PE prediction model was developed using the least absolute shrinkage and selection operator (LASSO) regression. We further examined the link between these biomarkers and PE using bioinformatics. ELISA assay was used to investigate the expression and clinical significance of the critical variables.

RESULTS:

Among the 79 analyzed proteins, we identified 11 serum proteins with significantly abnormal expression. Fibrinogen beta chain (FGB) was likely connected with the progression of PE due to the positive correlation between their levels and those of hypertension and proteinuria. In addition, an early prediction model for PE with an AUC of 92% was developed using LASSO regression.

CONCLUSION:

Our research employs predictive algorithms and screens for relevant variables, which could result in a potential approach to enhancing PE prediction.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Pré-Eclâmpsia Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Limite: Female / Humans / Pregnancy Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Pré-Eclâmpsia Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Limite: Female / Humans / Pregnancy Idioma: En Ano de publicação: 2023 Tipo de documento: Article