Browsing by Subject "Myopathy"

Now showing 1 - 4 of 4
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    Correction: Unraveling calcium dysregulation and autoimmunity in immune mediated rippling muscle disease
    (Springer Nature, 2025-03-24) Nath, Samir R.; Dasgupta, Aneesha; Dubey, Divyanshu; Kokesh, Eileen; Beecher, Grayson; Fadra, Numrah; Liewluck, Teerin; Pittock, Sean; Doles, Jason D.; Litchy, William; Milone, Margherita; Anatomy, Cell Biology and Physiology, School of Medicine
    Correction: Acta Neuropathologica Communications (2025) 13:11 10.1186/s40478-025-01926-z In this article [1], the author’s name Teerin Liewluck was incorrectly written as Teerin Liewuck. The original article has been corrected.
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    Glucocorticoid Excess in Bone and Muscle
    (Springer, 2018-03) Sato, Amy Y.; Peacock, Munro; Bellido, Teresita; Anatomy and Cell Biology, School of Medicine
    Glucocorticoids (GC), produced and released by the adrenal glands, regulate numerous physiological processes in a wide range of tissues. Because of their profound immunosuppressive and anti-inflammatory actions, GC are extensively used for the treatment of immune and inflammatory conditions, the management of organ transplantation, and as a component of chemotherapy regimens for cancers. However, both pathologic endogenous elevation and long-term use of exogenous GC are associated with severe adverse effects. In particular, excess GC has devastating effects on the musculoskeletal system. GC increase bone resorption and decrease formation leading to bone loss, microarchitectural deterioration and fracture. GC also induce loss of muscle mass and strength leading to an increased incidence of falls. The combined effects on bone and muscle account for the increased fracture risk with GC. This review summarizes the advance in knowledge in the last two decades about the mechanisms of action of GC in bone and muscle and the attempts to interfere with the damaging actions of GC in these tissues with the goal of developing more effective therapeutic strategies.
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    Mixture drug-count response model for the high-dimensional drug combinatory effect on myopathy
    (Wiley, 2018-02-20) Wang, Xueying; Zhang, Pengyue; Chiang, Chien-Wei; Wu, Hengyi; Shen, Li; Ning, Xia; Zeng, Donglin; Wang, Lei; Quinney, Sara K.; Feng, Weixing; Li, Lang; Radiology and Imaging Sciences, School of Medicine
    Drug-drug interactions (DDIs) are a common cause of adverse drug events (ADEs). The electronic medical record (EMR) database and the FDA's adverse event reporting system (FAERS) database are the major data sources for mining and testing the ADE associated DDI signals. Most DDI data mining methods focus on pair-wise drug interactions, and methods to detect high-dimensional DDIs in medical databases are lacking. In this paper, we propose 2 novel mixture drug-count response models for detecting high-dimensional drug combinations that induce myopathy. The "count" indicates the number of drugs in a combination. One model is called fixed probability mixture drug-count response model with a maximum risk threshold (FMDRM-MRT). The other model is called count-dependent probability mixture drug-count response model with a maximum risk threshold (CMDRM-MRT), in which the mixture probability is count dependent. Compared with the previous mixture drug-count response model (MDRM) developed by our group, these 2 new models show a better likelihood in detecting high-dimensional drug combinatory effects on myopathy. CMDRM-MRT identified and validated (54; 374; 637; 442; 131) 2-way to 6-way drug interactions, respectively, which induce myopathy in both EMR and FAERS databases. We further demonstrate FAERS data capture much higher maximum myopathy risk than EMR data do. The consistency of 2 mixture models' parameters and local false discovery rate estimates are evaluated through statistical simulation studies.
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    Unraveling calcium dysregulation and autoimmunity in immune mediated rippling muscle disease
    (Springer Nature, 2025-01-16) Nath, Samir R.; Dasgupta, Aneesha; Dubey, Divyanshu; Kokesh, Eileen; Beecher, Grayson; Fadra, Numrah; Liewuck, Teerin; Pittock, Sean; Doles, Jason D.; Litchy, William; Milone, Margherita; Anatomy, Cell Biology and Physiology, School of Medicine
    Rippling Muscle Disease (RMD) is a rare skeletal myopathy characterized by abnormal muscular excitability manifesting with wave-like muscle contractions and percussion-induced muscle mounding. Hereditary RMD is associated with caveolin-3 or cavin-1 mutations. Recently, we identified cavin 4 autoantibodies as a biomarker of immune-mediated RMD (iRMD), though the underlying disease-mechanisms remain poorly understood. Transcriptomic studies were performed on muscle biopsies of 8 patients (5 males; 3 females; ages 26-to-80) with iRMD. Subsequent pathway analysis compared iRMD to human non-disease control and disease control (dermatomyositis) muscle samples. Transcriptomic studies demonstrated changes in key pathways of muscle contraction and development. All iRMD samples had significantly upregulated cavin-4 expression compared to controls, likely compensatory for autoantibody-mediated protein degradation. Proteins involved in muscle relaxation (including SERCA1, PMCA and PLN) were significantly increased in iRMD compared to controls. Comparison of iRMD to dermatomyositis transcriptomics demonstrated significant overlap in immune pathways, and the IL-6 signaling pathway was markedly increased in all iRMD patient muscle biopsies and increased in the majority of iRMD patients' serum. This study represents the first muscle transcriptomic analysis of iRMD patients and dissects underlying disease mechanisms. Increase of sarcolemmal and cellular calcium channels as well as PLN, an inhibitor of the SERCA pump for calcium into the sarcoplasm, likely alters the calcium dynamics in iRMD. These changes in crucial components of muscle relaxation may underlie rippling by altering calcium flux. Our findings provide crucial insights into the differential expression of genes regulating muscle relaxation and highlight potential disease pathomechanisms.