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Frontiers in immunology · 2026

Candidate molecular endotypes and dynamic risk prediction in anti-MDA5-positive dermatomyositis-associated interstitial lung disease: a systematic scoping review.

СтатьяСистематический обзорНазвание и аннотация: Перевод пока не подготовлен
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Zuo Zhiwei, Yang Jianguo, Li Jianbin, Li Renhe, Liu Wei

Аннотация

BACKGROUND: Anti-melanoma differentiation-associated protein 5 antibody-positive dermatomyositis (anti-MDA5+ DM) spans pulmonary states from no detectable interstitial lung disease (ILD) to rapidly progressive ILD (RP-ILD). We mapped molecular programs and prediction evidence to determine how recurrent biological states may support dynamic stratification.

METHODS: PubMed, Web of Science, Ovid and Embase were searched from inception to 22 August 2026. Two reviewers independently screened records and extracted data. Reporting followed PRISMA-ScR; evidence was synthesized across molecular and prediction domains.

RESULTS: Of 4, 166 records, 2, 317 remained after deduplication, 349 underwent full-text assessment, and 95 sources (80 primary studies and 15 syntheses) were included. Type I/III interferon signaling was the most reproducible program. Myeloid inflammatory-remodeling, adaptive activation with lymphocyte or natural-killer-cell loss, vascular-coagulation injury, and immunometabolic disturbance formed additional overlapping axes aligned with pulmonary-state transitions. Clinical and radiomic models showed strong short-term discrimination; harmonized landmarks, calibration, geographic validation, and decision-timed molecular sampling would strengthen clinical use.

CONCLUSION: The evidence supports an integrated map linking recurrent molecular programs to dynamic pulmonary risk. A calibrated clinical-imaging backbone, augmented by parsimonious molecular modules with incremental value and updated at prespecified landmarks, offers a practical framework for prospective endotype validation and treatment-aware prediction in anti-MDA5+ DM-ILD.

SYSTEMATIC REVIEW REGISTRATION: https://doi.org/10.37766/inplasy2026.10.0018, identifier INPLASY2026100018.