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Unraveling mechanistic insights through interstitial lung disease multiomics.

作者信息

Menon Aravind A, Ghosh Auyon J

机构信息

Division of Pulmonary, Critical Care, Allergy, and Sleep Medicine, Medical University of South Carolina, Charleston, South Carolina.

Division of Pulmonary, Critical Care, and Sleep Medicine.

出版信息

Curr Opin Pulm Med. 2025 Sep 1;31(5):512-517. doi: 10.1097/MCP.0000000000001192. Epub 2025 Jul 7.

DOI:10.1097/MCP.0000000000001192
PMID:40620193
Abstract

PURPOSE OF REVIEW

Interstitial lung disease (ILD) and consequent pulmonary fibrosis are associated with significant morbidity and mortality with limited treatment options. There are more than 200 different etiologies that can lead to ILD. As a result, diagnostic accuracy and delay, prognostication, and treatment responses are still rife with challenges. The integration of bioinformatics with clinical practice is gaining momentum, evolving from a research tool to a practical resource with potential applications at the bedside. Work in this field has opened avenues into the pursuit of precision medicine in ILD.

RECENT FINDINGS

Across various 'omics-based technologies, numerous studies highlight the potential of using molecular data to disentangle the complex processes that lead to pulmonary fibrosis. Recent studies point toward integrating signals across domains to filter out noise and identify true signals. However, there is still a need for functional work to connect the high-dimensional signals to the biology underlying pulmonary fibrosis.

SUMMARY

Pursuing a multiomic approach across multiple domains in ILD holds promise for better biomarkers, clinical trial enrichment, and developing a deeper understanding of disease pathology.

摘要

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