Proteomics

Dataset Information

0

Novel phenotypes of immune-mediated necrotizing myopathy identified independent of myositis-specific antibody specificity that improve prognostic stratification


ABSTRACT: Immune-mediated necrotizing myopathy (IMNM) is a severe autoimmune myopathy with high clinical heterogeneity. Current classification relies on myositis-specific antibodies (MSA: anti-HMGCR, anti-SRP) but fails to explain differences in manifestations, interstitial lung disease (ILD) incidence, and survival. We enrolled 133 IMNM patients, used unsupervised machine learning (MSA-independent) to identify three phenotypes: Phenotype 1 (56.4%, muscle weakness, favorable prognosis), Phenotype 2 (10.5%, high muscle damage indicators, intermediate prognosis), Phenotype 3 (33.1%, high ILD/mortality, poor prognosis). Label-free DIA quantitative proteomics on these phenotypes and noninflammatory controls revealed distinct protein expression patterns, providing molecular evidence for IMNM subtyping, mechanism exploration, and prognosis evaluation.

ORGANISM(S): Homo Sapiens

SUBMITTER: Xuefan Yu  

PROVIDER: PXD078154 | iProX | Wed May 06 00:00:00 GMT+01:00 2026

REPOSITORIES: iProX

altmetric image

Publications

Novel phenotypes of immune-mediated necrotizing myopathy identified independent of myositis-specific antibody specificity that improve prognostic stratification.

Wei Xiaojing X   Sun Hui H   Pang Zhidan Z   Bai Na N   Guo Tiantian T   Nie Changpu C   Yang Xuan X   Lu Zhen Z   Bao Liye L   Miao Jing J   Yu Xuefan X  

Frontiers in immunology 20260514


<h4>Aim</h4>To systematically investigate the clinical characteristics and prognosis of patients with immune-mediated necrotizing myopathy (IMNM), and to explore the proteomic landscape associated with different clinical phenotypes.<h4>Methods</h4>A total of 133 IMNM patients were enrolled in this retrospective study. The clinical features and outcomes were compared across three subgroups: anti-HMGCR-positive, anti-SRP-positive, and seronegative patients. Unsupervised machine learning algorithms  ...[more]

Similar Datasets

2026-02-06 | GSE307297 | GEO
2024-10-17 | PXD052594 | Pride
2021-06-12 | GSE177043 | GEO
2019-08-14 | GSE128169 | GEO
2021-06-02 | GSE171896 | GEO
2020-12-03 | GSE162229 | GEO
2022-09-02 | GSE212109 | GEO
2016-08-01 | E-GEOD-81293 | biostudies-arrayexpress
2016-08-01 | E-GEOD-81292 | biostudies-arrayexpress
2025-01-09 | GSE286228 | GEO