The global Epigenetics Market is projected to reach USD 1.60 billion by 2022 from USD 0.85 billion in 2016, at a CAGR of 13.3% from 2017 to 2022, as per a report by MarketsandMarkets.
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Why use of epigenetics in non-oncology applications opening new opportunities?
With the major hold of epigenetics in oncology, it is also being used to study modifications in various other applications, such as cardiovascular, neurodegenerative, autoimmune, and metabolic diseases. These diseases involve epigenetic modifications which can be counteracted by epigenetic treatments. These modifications seem an ideal target because they are reversible, unlike DNA sequence mutations. The most popular of these treatments aim to alter either DNA methylation or histone acetylation. Thus, a comprehensive understanding of epigenetic mechanisms and their interactions and alterations in health and diseases has become a priority in biomedical research.
Various government organizations support epigenetic studies that help understand the pathways and mechanisms of various diseases and disorders and facilitate the development of specific inhibitors. For instance, the NIH funded Rush University Medical Center’s (US) study aimed at exploring the role of the brain epigenome. Similarly, it supported the University of North Carolina (US) in the integrative analysis of open chromatin, epigenome, and transcriptome data for studying the molecular role of DNA variants associated with Crohn’s disease. Furthermore, the National Natural Science Foundation of China supported a research study aimed at analyzing the emerging role of epigenetics in autoimmune thyroid diseases, published in 2017.
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Why dearth of trained professionals remains a challenge?
Epigenetics is a relatively new field and requires experts with a good knowledge of its science and technology. The analysis of the colossal volume data generated in genomic research is a major challenge. Due to the high complexity involved and the need for in-depth knowledge, it is necessary to hire trained professionals to analyze and interpret the results of sequenced data. Owing to the shortage of trained professionals, a number of end users face significant challenges in analyzing sequenced data.
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