Dataset Information

MULTI-OMIC ANALYSIS AND PLATELET FUNCTION DISTINGUISH TREATMENT RESPONSES TO HYDROXYTYROSOL IN CARDIOVASCULAR RISK

ABSTRACT: Many polyphenols, such as hydroxytyrosol (HT), have been recognized for their antioxidant and cardiovascular (CV) health benefits. To address the efficacy of HT, the present study aimed to identify the relevant mechanisms, associated with high-CV risk. Plasma unbiased multi-omics data were compared among two subgroups -HT responders and non-responders patients- and in a mice model. Lipid metabolism and proteomic responses were heterogeneous within two distinct ̶ responder and non-responder ̶ subgroups, associated mainly with thrombotic and hemostatic signals. The correlations between classical CV biomarkers, proteins, and metabolites offer a more comprehensive representation of the glutathione and coagulation pathways affected by HT treatment.

INSTRUMENT(S): timsTOF HT

ORGANISM(S): Homo Sapiens (human) Mus Musculus (mouse)

TISSUE(S): Blood Plasma

DISEASE(S): Cardiovascular System Disease

SUBMITTER: Sander Piersma

LAB HEAD: Dr Connie Ramona Jimenez

PROVIDER: PXD060820 | Pride | 2025-07-01

REPOSITORIES: Pride

ACCESS DATA

Dataset's files

Source:

Items per page:

1 - 5 of 76

Similar Datasets

Project description:Although current mass spectrometry (MS)-based proteomics identifies and quantifies thousands of proteins and (modified) peptides, only a minority of them are subjected to in-depth downstream analysis. With the advent of automated processing workflows, biologically or clinically important results within a study are rarely validated by visualization of the underlying raw information. Although several tools for this are in principle available, they are often not integrated into the overall analysis nor readily extendable with new approaches. To remedy this, we developed AlphaViz, an open-source Python package to superimpose output from common analysis workflows on the raw data for quick and easy visualization and validation of protein and peptide identifications. AlphaViz takes advantage of recent breakthroughs in the deep learning-assisted prediction of experimental peptide properties to allow manual assessment of the expected and measured peptide result deviation. We focused on the visualization of the 4-dimensional data cuboid provided by Bruker TimsTOF instruments, where the ion mobility dimension, besides intensity and retention time, can be predicted and used for verification. We illustrate how AlphaViz can quickly validate or invalidate peptide identifications regardless of the score given to them by automated workflows. Furthermore, we provide a â€˜predict modeâ€™ that can locate peptides present in the raw data but not reported by the search engine. This is illustrated with dilution series and the recovery of missing values from experimental replicates. Applied to phosphoproteomics of the EGF-signaling pathway, we show how key signaling nodes can be validated to enhance confidence for downstream interpretation or follow-up experiments. AlphaViz follows accepted standards for open-source software development, including extensive documentation, testing and continuous integration. It features an easy-to-install graphical user interface for end-users and a modular Python package for bioinformaticians. We hope that AlphaViz can help to make validation of critical proteomics results a standard feature in MS-based proteomics.

			Action	DRS
	Peptide_table_mouse.xlsx	Xlsx
	Peptides_human.xlsx	Xlsx
	Protein_table_mouse.xlsx	Xlsx
	Proteins_human.xlsx	Xlsx
	Sample_labeling_human.xlsx	Xlsx

Dataset Information

MULTI-OMIC ANALYSIS AND PLATELET FUNCTION DISTINGUISH TREATMENT RESPONSES TO HYDROXYTYROSOL IN CARDIOVASCULAR RISK

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets