LRP1 Diagnostic Model for Endometriosis: Multi-Omics and Single-Cell Evidence

A 2026 study by Chengmao Xie identifies low-density lipoprotein receptor-related protein 1 (LRP1) as a potential diagnostic and immunomodulatory target for endometriosis. The dataset likely contains results from integrated multi-omics analyses, including 1,404 differentially expressed genes and 30 hub genes identified via machine learning from three merged GEO datasets. Experimental validation confirmed elevated LRP1 expression in ectopic lesions.

Use Cases

• Validate LRP1 as a diagnostic biomarker for endometriosis based on the identified hub genes.
• Investigate the role of LRP1 in M2 macrophage infiltration based on the reported strong positive correlation (r=0.62).
• Study cell-cell communication in endometriosis via the MIF signaling pathway, as suggested by single-cell RNA sequencing findings.
• Assess causal relationships in disease progression using the Mendelian randomization analysis results (OR = 1.35).

Strengths

• Integrates data from three GEO datasets (GSE7305, GSE11691, GSE25628) for analysis.
• Includes experimental validation at both mRNA and protein levels for key findings.
• Applies multiple analytical methods: WGCNA, machine learning for hub gene identification, Mendelian randomization, and single-cell RNA sequencing.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The 584.2 KB file size suggests a limited scope, likely containing summary results rather than raw sequencing data.

Provenance

Source

Chengmao Xie via figshare.

Collection Method

Integrated analysis of public GEO datasets, WGCNA, machine learning, Mendelian randomization, and single-cell RNA sequencing.

Time Range

Study published in 2026; underlying GEO dataset collection dates are unknown.

Freshness

Last updated 2026-04-15 04:22:08.

Geography

Geographic coverage of the source samples is not specified.