Dataset Information

Glycerophospholipid and amino acid metabolism impairment during Congenital Zika Syndrome development

ABSTRACT: Zika virus (ZIKV) can be transmitted vertically to the fetus, having a high chance to develop Congenital Zika Syndrome (CZS). Studies have shown that ZIKV impairs brain development. However, little is known about the molecular differences between non- microcephalic ZIKV-infected fetuses and microcephalic ones. Here, our main goal is to identify the alterations in the amniotic fluid (AF) metabolome in ZIKV-infected patients and their relation to CZS progression. We applied an untargeted metabolomics strategy to analyze seven AF of pregnant women: healthy women and ZIKV-infected women bearing non-microcephalic and microcephalic fetuses. Infected patients were characterized by glycerophospholipid metabolism impairment, which is accentuated in microcephalic phenotypes. Glycerophospholipid decreased concentration in AF can be a consequence of intracellular transport of lipids to the placental or fetal tissues under development. The increased intracellular concentration of lipids can lead to mitochondrial dysfunction and neurodegeneration caused by lipid droplet accumulation. Furthermore, the dysregulation of amino acid metabolism was a molecular fingerprint of microcephalic phenotypes, specifically serine, and proline metabolisms. Both amino acid deficiencies were related to neurodegenerative disorders, intrauterine growth retardation, and placental abnormalities. This study contributes to the understanding of CZS pathology and discovering potential biomarkers for CZS prognosis in the early stages of pregnancy.

INSTRUMENT(S):

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Amniotic Fluid

SUBMITTER: Proteomics Unit

LAB HEAD: Fábio César Sousa Nogueira

PROVIDER: PXD039643 | Pride | 2025-09-04

REPOSITORIES: Pride

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	20171115_LA_5001_ESIneg_A.raw	Raw
	20171115_LA_5001_ESIneg_B.raw	Raw
	20171115_LA_5001_ESIneg_C.raw	Raw
	20171115_LA_5001_ESIpos_A.raw	Raw
	20171115_LA_5001_ESIpos_B.raw	Raw

Items per page:

1 - 5 of 52

Similar Datasets

Project 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.

Dataset Information

Glycerophospholipid and amino acid metabolism impairment during Congenital Zika Syndrome development

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets