Selected Grantee Publications
Transcriptomic Analysis of Skeletal Muscle Regeneration Across Mouse Lifespan Identifies Altered Stem Cell States
Walter et al., Nature Aging. 2024.
https://pubmed.ncbi.nlm.nih.gov/39578558
Age-related skeletal muscle regeneration dysfunction is poorly understood. Using single-cell transcriptomics and high-resolution spatial transcriptomics, researchers evaluated factors contributing to age-related decline in skeletal muscle regeneration after injury in young, old, and geriatric male and female mice (5, 20, and 26 months old). Eight immune cell types were identified and associated with age-related dynamics and distinct muscle stem cell states specific to old and geriatric tissue. The findings emphasize the role of extrinsic and intrinsic factors, including cellular senescence, in disrupting muscle repair. This study provides a spatial and molecular framework for understanding regenerative decline and cellular heterogeneity in aging skeletal muscle. Supported by ORIP (F30OD032097), NIA, NIAID, NIAMS, NICHD, and NIDA.
The Monarch Initiative in 2024: An Analytic Platform Integrating Phenotypes, Genes and Diseases Across Species
Putman et al., Nucleic Acids Research. 2024.
https://pubmed.ncbi.nlm.nih.gov/38000386/
The Monarch Initiative aims to bridge the gap between the genetic variations, environmental determinants, and phenotypic outcomes critical for translational research. The Monarch app provides researchers access to curated data sets with information on genes, phenotypes, and diseases across species and advanced analysis tools for such diverse applications as variant prioritization, deep phenotyping, and patient profile matching. Researchers describe upgrades to the app, including scalable cloud-based infrastructure, simplified data ingestion and knowledge graph integration systems, enhanced data mapping and integration standards, and a new user interface with novel search and graph navigation features. A customized plugin for OpenAI’s ChatGPT allows the use of large language models to interrogate knowledge in the Monarch graph and increase the reliability of the responses of Monarch’s analytic tools. These upgrades will enhance clinical diagnosis and the understanding of disease mechanisms. Supported by ORIP (R24OD011883), NLM, and NHGRI.
PGRN Deficiency Exacerbates, Whereas a Brain Penetrant PGRN Derivative Protects, GBA1 Mutation–Associated Pathologies and Diseases
Zhao et al., Proc Natl Acad Sci USA. 2023.
https://www.pnas.org/doi/10.1073/pnas.2210442120
Mutations in GBA1 are associated with Gaucher disease (GD) and are also genetic risks in developing Parkinson’s disease (PD). Investigators created a mouse model and demonstrated that progranulin (PGRN) deficiency in Gba1 mutant mice caused early onset and exacerbated GD phenotypes, leading to substantial increases in substrate accumulation and inflammation in visceral organs and the central nervous system. These in vivo and ex vivo data demonstrated that PGRN plays a crucial role in the initiation and progression. In addition, the mouse model provides a clinically relevant system for testing therapeutic approaches for GD and PD. Supported by ORIP (R21OD033660), NIAMS, and NINDS.
Creb5 Establishes the Competence for Prg4 Expression in Articular Cartilage
Zhang et al., Communications Biology. 2021.
https://doi.org/10.1038/s42003-021-01857-0
Cells comprising the superficial zone of articular cartilage express lubricin, encoded by the Prg4 gene, that lubricates joints. Researchers identified Creb5 as a transcription factor that is required for TGF-β and EGFR signaling to induce Prg4 expression. Forced expression of Creb5 in deep-zone chondrocytes of articular cartilage confers competence for TGF-β and EGFR signals to induce Prg4 expression. The researchers showed that Creb5 directly binds to two Prg4 promoter-proximal regulatory elements, which work together with a more distal regulatory element to drive induction of Prg4 by TGF-β. Thus, Creb5 is a critical regulator of Prg4/lubricin expression in the articular cartilage. Supported by ORIP (U42OD11158), NIAMS, and NIDDK.