PXD043324-1

PXD043324 is an original dataset announced via ProteomeXchange.

Title	Multi-omics approach reveals serum biomarker candidates for Congenital Zika Syndrome
Description	During pregnancy, the Zika virus (ZIKV) can be vertically transmitted, causing Congenital Zika Syndrome (CZS) in fetuses. ZIKV infection in early gestational trimesters increases the chances to develop CZS. This syndrome involves several pathologies with a difficult diagnosis, which usually occurs in the postnatal stage. In this work, we aim to identify biological processes and molecular pathways related to CZS development and propose a series of putative protein and metabolite biomarkers for CZS prognosis in early pregnancy trimesters. Twenty-five serum samples of pregnant women were analyzed. For biological analysis, samples were separated into 3 biological groups composed of a control group of healthy pregnant women and two groups of ZIKV-infected pregnant women bearing non- microcephalic and microcephalic fetuses. Control and ZIKV-infected groups - without microcephalic fetuses - were subdivided into healthy and Cognitive Developmental Delay (CDD) newborns for biomarker analysis. We detected over 1,000 proteins and 500 metabolites by bottom-up proteomics and untargeted metabolomics, respectively. Statistical approaches - (t-Student, Limma, ANOVA, and DIABLO) - were applied to find CZS differentially abundant proteins (DAP) and metabolites (DAM). Enrichment analysis (i.e., biological processes and molecular pathways) of the DAP and the DAM allowed us to identify the ECM organization and proteoglycans, amino acid metabolism, and arachidonic acid metabolism as signatures in the CZS development. Five proteins and four metabolites were selected as CZS biomarkers candidates. The protein-based model indicated superior performance values for the Vitamin K-dependent protein S, Selenoprotein P, Inter-alpha- trypsin inhibitor heavy chain H2, Kallistatin, and Protein Z-dependent protease inhibitor proteins. Furthermore, the metabolite-based model was able to predict CZS with a probability of 90%. Serum multi-omics analysis led us to propose for further studies nine potential biomarkers for CZS early prognosis with high sensitivity and specificity.
HostingRepository	PRIDE
AnnounceDate	2024-07-02
AnnouncementXML	Submission_2024-07-01_20:45:40.062.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Proteomics Unit
SpeciesList	scientific name: Homo sapiens (Human); NCBI TaxID: 9606;
ModificationList	acetylated residue; monohydroxylated residue; iodoacetamide derivatized residue
Instrument	Q Exactive

Revision	Datetime	Status	ChangeLog Entry
0	2023-06-26 20:09:52	ID requested
⏵ 1	2024-07-01 20:45:40	announced

10.1021/ACS.JPROTEOME.3C00677;

ProteomeXchange project tag: Biology/Disease-Driven Human Proteome Project (B/D-HPP), Human Proteome Project

submitter keyword: Zika virus

Proteomics

Metabolomics

Multi-omics

Congenital Zika Syndrome

microcephaly

serum

biomarkers

Fábio C. S. Nogueira
contact affiliation	Laboratory of Protein Chemistry - Proteomic Unit Department of Biochemistry, Institute of Chemistry, UFRJ Av. Athos da Silveira Ramos, 149, CT, Bl. A, 543, Cidade Universitária 21941-909, Rio de Janeiro, RJ, Brazil Ph: 55 21 39388266 / 55 21 39387353 Laboratory of Proteomics (LabProt) - LADETEC, Institute of Chemistry Av. Horácio Macedo, 1281, Polo de Química, Bl. C, Lab. 324, Cidade Universitária, 21941-598, Rio de Janeiro, RJ, Brazil
contact email	fabiocsn@gmail.com
lab head
Proteomics Unit
contact affiliation	UFRJ
contact email	unidadeproteomica@gmail.com
dataset submitter

Dataset FTP location NOTE: Most web browsers have now discontinued native support for FTP access within the browser window. But you can usually install another FTP app (we recommend FileZilla) and configure your browser to launch the external application when you click on this FTP link. Or otherwise, launch an app that supports FTP (like FileZilla) and use this address: ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2024/07/PXD043324

PRIDE project URI

• PRIDE
  1. PXD043324
     1. Label: PRIDE project
     2. Name: Multi-omics approach reveals serum biomarker candidates for Congenital Zika Syndrome