Use of Epigenetic signatures and machine learning for improving the diagnosis
  
Epigenetics signature are identified by the Greenwood Genetic Center researchers for contribute to better methods of diagnosis the nine neurodevelopment disorders. The American Journal of Human Genetics was firstly developed the epigenetics signature through methylation array analysis. Genes which encode the cell’s epigenetics machinery (the component that read, write and erase post-translational signals on histones and DNA and remodel the DNA) causes the 14 neurodevelopment disorders. Among these 14 disorders, nine of them are revealed unique methylation signatures.

As the study suggest that these unique epigenetic signatures could be used in screening for multiple syndromes with a high degree of specificity and sensitivity. For accurate diagnosis of the disorders, the team built a single machine classification tool based on the degree of the overlap between these signatures. By this method, nine disorders are distinguished from one another and the chances of patients with other forms of intellectual and development delay are decreases. An innovative approach is provided by these unique signatures for solving ambiguous cases presenting with variants of uncertain significance from targeted gene sequencing, whole exome sequencing or whole genome sequencing. 

The benefits of this approach includes the lack of need of parental samples and the potential of functional results to be obtained from peripheral blood samples rather than other inaccessible target tissues such as brain. If the mutation is in noncoding region then this method is have a potential to identify a diagnosis.

See more at: https://epigenetics.geneticconferences.com/