Salivary microRNAs identified by small RNA sequencing and machine learning as potential biomarkers of alcohol dependence.

Journal: Epigenomics
Published Date:

Abstract

Salivary miRNA can be easily accessible biomarkers of alcohol dependence (AD). The miRNA transcriptome in the saliva of 56 African-Americans (AAs; 28 AD patients/28 controls) and 64 European-Americans (EAs; 32 AD patients/32 controls) was profiled using small RNA sequencing. Differentially expressed miRNAs were identified. Salivary miRNAs were used to predict the AD presence using machine learning with Random Forests. Seven miRNAs were differentially expressed in AA AD patients, and five miRNAs were differentially expressed in EA AD patients. The AD prediction accuracy based on top five miRNAs (ranked by Gini index) was 79.1 and 72.2% in AAs and EAs, respectively. This study provided the first evidence that salivary miRNAs are AD biomarkers.

Authors

  • Andrew J Rosato
    Department of Psychiatry, Boston University School of Medicine, Boston, MA 02118, USA.
  • Xiaochun Chen
    Department of Psychiatry, Boston University School of Medicine, Boston, MA 02118, USA.
  • Yoshiaki Tanaka
    Department of Genetics, Yale University School of Medicine, New Haven, CT 06520, USA.
  • Lindsay A Farrer
    Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA 02118, USA.
  • Henry R Kranzler
    Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania & VISN4 MIRECC, Crescenz VAMC, Philadelphia, PA 19104, USA.
  • Yaira Z Nunez
    Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA.
  • David C Henderson
    Department of Psychiatry, Boston University School of Medicine, Boston, MA 02118, USA.
  • Joel Gelernter
    Department of Psychiatry, Yale University School of Medicine, New Haven, CT.
  • Huiping Zhang
    Department of Psychiatry, Boston University School of Medicine, Boston, MA 02118, USA.