Transcriptomic Analysis of Human ALS Skeletal Muscle Reveals Disease-Specific Pattern of Dysregulated circRNAs


“In this work, we have identified distinct patterns of circRNA expression in human ALS muscle tissue, many appearing to be disease-specific, that display expression gradients at different levels within the CNS.”

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BUFFALO, NY- January 12, 2023 – A new research paper was published in Aging (listed as "Aging (Albany NY)" by MEDLINE/PubMed and "Aging-US" by Web of Science) Volume 14, Issue 24, entitled, “Transcriptomic analysis of human ALS skeletal muscle reveals a disease-specific pattern of dysregulated circRNAs.”

Circular RNAs are abundant, covalently closed transcripts that arise in cells through back-splicing and display distinct expression patterns across cells and developmental stages. While their functions are largely unknown, their intrinsic stability has made them valuable biomarkers in many diseases.

In this new study, researchers Dimitrios Tsitsipatis, Krystyna Mazan-Mamczarz, Ying Si, Allison B. Herman, Jen-Hao Yang, Abhishek Guha, Yulan Piao, Jinshui Fan, Jennifer L. Martindale, Rachel Munk, Xiaoling Yang, Supriyo De, Brijesh K. Singh, Ritchie Ho, Myriam Gorospez, and Peter H. King from the National Institutes of Health’s National Institute on Aging, The University of Alabama at Birmingham, Birmingham Veterans Affairs Medical Center, and Cedars-Sinai Medical Center set out to examine circRNA patterns in amyotrophic lateral sclerosis (ALS). By RNA-sequencing analysis, the researchers first identified circRNAs and linear RNAs that were differentially abundant in skeletal muscle biopsies from ALS compared to normal individuals. 

“By RT-qPCR analysis, we confirmed that 8 circRNAs were significantly elevated and 10 were significantly reduced in ALS, while the linear mRNA counterparts, arising from shared precursor RNAs, generally did not change.” 

Several of these circRNAs were also differentially abundant in motor neurons derived from human induced pluripotent stem cells (iPSCs) bearing ALS mutations, and across different disease stages in skeletal muscle from a mouse model of ALS (SOD1G93A). Interestingly, a subset of the circRNAs significantly elevated in ALS muscle biopsies were significantly reduced in the spinal cord samples from ALS patients and ALS (SOD1G93A) mice. In sum, the researchers identified differentially abundant circRNAs in ALS-relevant tissues (muscle and spinal cord) that could inform about neuromuscular molecular programs in ALS and guide the development of therapies.

“As our studies advance, we will investigate the function of the most promising and abundant circRNAs, among the 18 circRNAs reported here. We are especially interested in those that appeared to be specific for ALS (Figure 2), as they may help to characterize disease-associated molecular pathways that could be targeted therapeutically.”


Corresponding Authors: Myriam Gorospe, Dimitrios Tsitsipatis, Peter H. King

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Keywords: amyotrophic lateral sclerosis, circular RNAs, neurodegenerative disease, human skeletal muscle, human spinal cord tissue

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About Aging-US:

Aging publishes research papers in all fields of aging research including but not limited, aging from yeast to mammals, cellular senescence, age-related diseases such as cancer and Alzheimer’s diseases and their prevention and treatment, anti-aging strategies and drug development and especially the role of signal transduction pathways such as mTOR in aging and potential approaches to modulate these signaling pathways to extend lifespan. The journal aims to promote treatment of age-related diseases by slowing down aging, validation of anti-aging drugs by treating age-related diseases, prevention of cancer by inhibiting aging. Cancer and COVID-19 are age-related diseases.

Aging is indexed by PubMed/Medline (abbreviated as “Aging (Albany NY)”), PubMed CentralWeb of Science: Science Citation Index Expanded (abbreviated as “Aging‐US” and listed in the Cell Biology and Geriatrics & Gerontology categories), Scopus (abbreviated as “Aging” and listed in the Cell Biology and Aging categories), Biological Abstracts, BIOSIS Previews, EMBASE, META (Chan Zuckerberg Initiative) (2018-2022), and Dimensions (Digital Science).

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