Big data in severe mental illness: the role of electronic monitoring tools and metabolomics.

Journal: Personalized medicine
PMID:

Abstract

There is an increasing interest in the development of effective early detection and intervention strategies in severe mental illness (SMI). Ideally, these efforts should lead to the delineation of accurate staging models of SMI enabling personalized interventions. It is plausible that big data approaches will be instrumental in describing the developmental trajectories of SMI by facilitating the incorporation of data from multiple sources, including those pertaining to the biological make-up of affected subjects. In this review, we first aimed to offer a perspective on how big data are helping the delineation of personalized approaches in SMI, and, second, to offer a quantitative synthesis of big data approaches in metabolomics of SMI. We finally described future directions of this research area.

Authors

  • Hema Sekhar Reddy Rajula
    Neonatal Intensive Care Unit, Department of Surgical Sciences, AOU and University of Cagliari, 09042 Cagliari, Italy.
  • Mirko Manchia
    Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy.
  • Bernardo Carpiniello
    Department of Medical Science & Public Health, Section of Psychiatry, University of Cagliari, Cagliari, Italy.
  • Vassilios Fanos
    Neonatal Intensive Care Unit, Department of Surgical Sciences, AOU and University of Cagliari, 09042 Cagliari, Italy.