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Author Notes:

Peng Jin, Tel.: +1 404 727 3729. Email: peng.jin@emory.edu

The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

Subjects:

Research Funding:

The authors are funded by the National Institute of Neurological Disorders and Stroke (grant no.: NS111602) and Woodruff Health Sciences Center Synergy Award.

Keywords:

  • Science & Technology
  • Life Sciences & Biomedicine
  • Genetics & Heredity
  • brain disorders
  • cell-free DNA
  • diagnostic tool
  • DNA methylation
  • AMYOTROPHIC-LATERAL-SCLEROSIS
  • ALZHEIMERS-DISEASE
  • PLASMA DNA
  • BLOOD
  • PATTERNS
  • CANCER

Cell-free DNA methylation as a potential biomarker in brain disorders

Tools:

Journal Title:

EPIGENOMICS

Volume:

Volume 14, Number 7

Publisher:

, Pages 369-374

Type of Work:

Article | Final Publisher PDF

Abstract:

The diagnosis of many brain disorders is challenging due to the nonspecific clinical presentation and/or the lack of accurate biomarkers. In addition, many neurological disorders show slow progression with a long asymptomatic period followed by a stage with mild clinical symptoms. This limits the potential for early detection with effective therapeutic treatment only occurring late in the course of the disease. Clearly, developing noninvasive and accurate diagnostic tools for detecting brain disorders is an unmet medical need. Altered methylation patterns in circulating cell-free DNA (cfDNA) have been implicated as useful tools for noninvasive cancer detection, prenatal diagnostics and organ transplantation assessment. Given the critical roles of DNA methylation in many brain disorders, unusual DNA methylation alternations in cfDNA could be a promising biomarker for disease diagnosis. This commentary presents an overview of investigational applications of cfDNA methylation signatures as potential molecular markers to diagnose various brain disorders. The authors' views on the technologies for cfDNA methylation analysis based on next-generation sequencing are also discussed.
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