Integrating Multi-Omics and Network Toxicology to Identify FIS1 in Male Infertility

A 668.9 KB research document authored by Qi Yu, uploaded on figshare in March 2026. It details a study integrating blood transcriptomics, GWAS, and QTL data to investigate environmental pollutant targets in male infertility. The work identifies 232 dysregulated mitochondrial genes and validates the protective role of the FIS1 gene.

Use Cases

• Validate causal gene-environment links based on multi-omics integration and Summary-data-based Mendelian Randomization (SMR).
• Screen environmental pollutants targeting specific genes based on criteria like bioaccumulation potential (Log P > 5) and predicted toxicity.
• Evaluate molecular docking binding affinity for candidate pollutants based on reported ΔG values (< -5.0 kcal/mol).
• Analyze mitochondrial dysfunction pathways based on identified dysregulated mitochondrial genes and in vitro functional validation results.

Strengths

• The study integrates multiple data types: blood transcriptomics, GWAS summary statistics, and QTL data (methylation, expression, protein).
• Identifies a specific number of dysregulated mitochondrial genes (232) and validates a key candidate (FIS1) across three molecular levels.
• Provides preliminary experimental evidence for six predicted pollutant targets, confirmed by molecular docking.

Limitations

• The dataset is a single 668.9 KB DOCX file, likely containing a research paper rather than raw data tables.
• Column-level documentation and sample data are unavailable, making direct data analysis impossible.
• Row count is unknown, which may limit suitability assessment for computational reuse.

Provenance

Source

figshare

Collection Method

The document describes a research methodology integrating publicly available omics data (GWAS, QTL) with patient transcriptomics and computational toxicology screening.

Freshness

Last updated 2026-03-19 06:49:36