Scientists at the Icahn School of Medicine at Mount Sinai have uncovered new molecular drivers of Parkinson's disease using a sophisticated statistical technique called multiscale gene network analysis (MGNA). The team was also able to determine how these molecular drivers impact the functions of genes involved in the disease. The results, which may point to potential new treatments, were published online on November 20, 2019 in Nature Communications. The open-access article is titled “The Landscape of Multiscale Transcriptomic Networks and Key Regulators in Parkinson’s Disease.” Some cases of Parkinson's are directly caused by genetic mutations, but these cases are rare. Approximately 80 percent of cases have no known cause, and though there are some genes that may slightly increase an individual's risk of developing the disease, the biological impacts of these genes remain unclear. "This study offers a novel approach to understanding the majority of cases of Parkinson's," said Bin Zhang, PhD, Professor of Genetics and Genomic Sciences at the Icahn Institute for Data Science and Genomic Technology and Director of the Mount Sinai Center for Transformative Disease Modeling at the Icahn School of Medicine at Mount Sinai. "The strategy not only reveals new drivers, but it also elucidates the functional context of the known Parkinson's disease risk factor genes."
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