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pmid:39265992

Proteome and Metabolome Profiling of Anticoagulant Disorders Induced by Familial Protein S Deficiency.

Caiping Zhang · Yimin Zhang · Binjie Liu · Yongxv Chen · Yue Xie · Huiting Huang · Zhongqiu Liu · Zhuoru He

Journal of proteome research · 2024 doi:10.1021/acs.jproteome.4c00399

Paper

complete

Experiment

complete

Data

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Analysis

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Execution

absent

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Proteome and Metabolome Profiling of Anticoagulant Disorders Induced by Familial Protein S Deficiency.
doi
10.1021/acs.jproteome.4c00399
pmid
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Caiping Zhang
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Yimin Zhang
[2]
Binjie Liu
[3]
Yongxv Chen
[4]
Yue Xie
[5]
Huiting Huang
[6]
Zhongqiu Liu
[7]
Zhuoru He
journal
Journal of proteome research
year
2024
abstract
Protein S deficiency (PSD) is an autosomal dominant disorder characterized by congenital thrombophilia. Studies on PSD are limited yet, resulting in a lack of clarity about molecular changes during abnormal coagulation. Proteomics and metabolomics analyses were conducted on the plasma of PSD patients based on liquid and gas chromatography-mass spectrometry (LC- and GC-MS). Differential proteins and metabolites of PSD were then filtered by univariate statistical analysis and subjected to network analysis using the ingenuity pathway analysis (IPA) platform. The proteome and metabolome of PSD were obviously disturbed, and the biological pathway of coagulation and complement cascades was the most affected. During PSD, overall levels of anticoagulant protein decreased and negative regulation of thrombin production was reduced, causing the formation of fibrin clots and platelet aggregation. Furthermore, 9 differential proteins correlated significantly with protein S, comprising A2M, AGT, APOE, FGG, GPLD1, IGHV1-69, CFHR5, CPN2, and CA1. The biological networks suggested that the pathways of acute phase response, FXR/RXR activation, serotonin receptor signaling, and p70S6K signaling were associated with PSD, indicating an interaction disorder of inflammatory immune and lipid metabolism. The findings may contribute to knowledge of available functional molecules and biological pathways of familial PSD and help with treatment improvement. Data are available via ProteomeXchange with identifier PXD055111 and MetaboLights with reference number MTBLS2653.
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Univariate analysis was conducted using SPSS software (version 22.0, IBM, IL, USA) with the Student’s t test to obtain P values. Simca-p (version 14.1, Umetrics, Sweden) was used to perform principal component analysis. The FDR value was obtained from the adjusted P value of FDR correction by the Benjamini–Hochberg method.
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Univariate analysis was conducted using SPSS software (version 22.0, IBM, IL, USA) with the Student’s t test to obtain P values. Simca-p (version 14.1, Umetrics, Sweden) was used to perform principal component analysis. The FDR value was obtained from the adjusted P value of FDR correction by the Benjamini–Hochberg method.
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Data Availability StatementThe MS proteomics data have been deposited to the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the PRIDE partner repository with the data set identifier PXD055111.34 The MS metabolomics data have been uploaded to MetaboLights (https://www.ebi.ac.uk/metabolights/) with the reference number MTBLS2653.35
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Data Availability StatementThe MS proteomics data have been deposited to the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the PRIDE partner repository with the data set identifier PXD055111.34 The MS metabolomics data have been uploaded to MetaboLights (https://www.ebi.ac.uk/metabolights/) with the reference number MTBLS2653.35
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