Histopathology and spatial transcriptomics jointly map myofiber-specific pathological programs in mTORC1-driven myopathy.

Authors

Jer-En Hsu, Qingyang Zhao, Weiqiu Cheng, Hyun Min Kang, Susan V Brooks, Myungjin Kim, Jun Hee Lee

Published in

JCI insight. Aug 20, 2026. Epub Aug 20, 2026.

Abstract

Skeletal muscle is composed of heterogeneous myofiber types and non-myocyte populations. Myopathies occur in many diseases, but mechanisms driving these pathologies remain largely unknown, partly because conventional approaches cannot link histopathological features to molecular states at single-fiber resolution. To address this challenge, we brought histopathology and spatial transcriptomics together by applying high-resolution Seq-Scope technology to a mouse model of mTORC1 hyperactivation. Cross-sections from extensor digitorum longus (EDL) and soleus (SOL), two muscles with distinct fiber-type compositions, were profiled to determine how transcriptome changes are linked to histopathological outcomes. mTORC1 hyperactivation elicited distinct, fiber-type-dependent pathological programs. Type I and IIa fibers were largely resistant to mTORC1-induced pathology, exhibiting relatively limited morphological alterations. In contrast, type IIx fibers diverged into opposing fates: in SOL, they underwent abnormal enlargement associated with sustained growth signaling, cytoskeletal remodeling, and impaired proteostasis; in EDL, they developed basophilia associated with increased RNA content and lipid, oxidative, and nucleotide metabolism-related signatures. Within EDL, type IIb fibers displayed heterogeneity with discrete transcriptional states. Non-myocytic populations, including macrophages and fibroblasts, accumulated preferentially in SOL, forming a fibrotic microenvironment associated with inflammation, remodeling, and hypertrophy. These findings provide a link between histopathological phenotypes and molecular states at single-fiber resolution.

PMID:
42623145
Bibliographic data and abstract were imported from PubMed on 21 Aug 2026.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.