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Identification of key molecular targets in nicotine-induced spontaneous abortion through network toxicology and multi-omics integration

Introduction Spontaneous abortion (SA) remains a prevalent reproductive health challenge, with tobacco-derived nicotine emerging as a significant risk factor. This study sought to decipher the molecular underpinnings of nicotine-induced pregnancy loss through comprehensive multi-omics profiling to identify novel biomarkers and potential intervention targets. Methods An integrated bioinformatics approach was implemented combining network toxicology, transcriptomic profiling, and machine learning algorithms to elu…

By the Truvace desk1 min read1 sourcePeer-reviewedTRV-2026-1190· cite & verify
Identification of key molecular targets in nicotine-induced spontaneous abortion through network toxicology and multi-omics integration
Modeling second generation FLIR sensor detection recognition and identification range with polarization filtering by Yildirim, Mehmet.. Public domain

In brief

Introduction Spontaneous abortion (SA) remains a prevalent reproductive health challenge, with tobacco-derived nicotine emerging as a significant risk factor. This study sought to decipher the molecular underpinnings of nicotine-induced pregnancy loss through comprehensive multi-omics profiling to identify novel biomarkers and potential intervention targets.

Methods An integrated bioinformatics approach was implemented combining network toxicology, transcriptomic profiling, and machine learning algorithms to elucidate nicotine's pathological mechanisms in SA. MR analysis confirmed causal associations for RAD50 (OR=1.08; 95% CI: 1.01-1.15, p=0.019) and FGF2 (OR=1.21; 95% CI: 1.11-1.33, p=4.69×10 -5 ).

Main points

  1. Introduction Spontaneous abortion (SA) remains a prevalent reproductive health challenge, with tobacco-derived nicotine emerging as a significant risk factor.
  2. This study sought to decipher the molecular underpinnings of nicotine-induced pregnancy loss through comprehensive multi-omics profiling to identify novel biomarkers and potential intervention targets.
  3. Methods An integrated bioinformatics approach was implemented combining network toxicology, transcriptomic profiling, and machine learning algorithms to elucidate nicotine's pathological mechanisms in SA.

The problem

Identification of key molecular targets in nicotine-induced spontaneous abortion through network toxicology and multi-omics integration: Introduction Spontaneous abortion (SA) remains a prevalent reproductive health challenge, with tobacco-derived nicotine emerging as a significant risk factor.

The rundown

Methods An integrated bioinformatics approach was implemented combining network toxicology, transcriptomic profiling, and machine learning algorithms to elucidate nicotine's pathological mechanisms in SA. The analytical pipeline encompassed functional enrichment analysis, expression pattern characterization, diagnostic biomarker evaluation, immune microenvironment assessment, causal inference through Mendelian randomization (MR), single-cell RNA sequencing, and molecular docking simulations of nicotine-protein interactions.

Sources

  1. Peer-reviewedTobacco Induced Diseases2026-09-22

The debate