Multi-Omics Biomarkers for Early Tuberculosis Detection in Type 2 Diabetes Patients

A multi-omics dataset from a prospective cohort study of 198 individuals profiles immune-related biomarkers for early tuberculosis detection in type 2 diabetes mellitus. The data includes whole-transcriptome and plasma-proteome profiles, leading to the identification of 13 cross-platform biomarkers. The dataset was published by Zhaoyang Ye on figshare in March 2026 under a CC-BY-4.0 license.

Use Cases

• Training logistic regression models for early TB diagnosis based on the 13 identified immune-related biomarkers.
• Analyzing immune cell infiltration patterns based on the described 'pro-inflammatory-suppressive-reconstructive' imbalance.
• Investigating competing endogenous RNA (ceRNA) regulatory networks involving the identified lncRNAs and miRNAs.
• Validating biomarker signatures using external datasets like GSE181143 and GSE114192 mentioned in the description.

Strengths

• Derived from a prospective cohort study with 198 participants (71 healthy controls, 67 T2DM, 60 T2DM-TB).
• Eleven diagnostic models demonstrated high efficacy with reported AUC values ranging from 0.93 to 0.99.
• Includes multi-omics data covering mRNAs, miRNAs, lncRNAs, and proteins for integrated analysis.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is very small at 22.8 KB, indicating limited raw data or a summary document.

Provenance

Source

figshare, author Zhaoyang Ye.

Collection Method

Prospective cohort study involving whole-transcriptome and plasma-proteome profiling.

Freshness

Last updated 2026-03-18 07:43:06; freshness should be verified.