Supplementary File 6: Multi-Omics Integration for Atherosclerosis Biomarker Discovery

A research article from figshare, authored by Yirong Ma and last updated in May 2026, describes a multi-omics study of atherosclerosis. The work integrates proteomic and transcriptomic data, identifies lactylation-related genes, and validates candidate biomarkers using machine learning and experimental models. The dataset is a 1.4 MB PDF file.

Use Cases

• Identifying lactylation-related gene signatures in atherosclerosis based on the integrated multi-omics analysis described.
• Training diagnostic machine learning models for atherosclerosis based on the ensemble algorithm approach and candidate biomarkers (UAP1, NRP1, QPRT, NDST1) mentioned.
• Analyzing immune cell infiltration in atherosclerotic plaques based on the CIBERSORT and single-cell data characterization described.
• Prioritizing candidate therapeutic compounds for atherosclerosis based on the Connectivity Map and molecular docking simulations discussed.

Strengths

• The underlying analysis integrated proteomic data (472 differentially expressed proteins) and transcriptomic data (2,544 DEGs) from public repositories.
• Machine learning validation achieved a high diagnostic performance, with a reported mean AUC of 0.979 for the ensemble model.
• Candidate biomarkers were experimentally validated in an Apoe−/− mouse model using RT-qPCR, Western blot, and immunofluorescence.

Limitations

• The provided file is a PDF research article; the underlying raw or processed data tables are not directly accessible.
• Row count and column-level documentation for any associated datasets are unknown, limiting suitability assessment.
• Description metadata is limited; actual data quality and structure require manual inspection after download.

Provenance

Source

figshare, author Yirong Ma.

Collection Method

Data-independent proteomics on HUVECs exposed to oxidized LDL, integrated with public transcriptomic datasets (GEO).

Time Range

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Freshness

Last updated 2026-05 08 05:52:43; freshness should be verified.

Geography

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