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

Epigenomics. 2019 May;11(7):739-749. doi: 10.2217/epi-2018-0177. Epub 2019 May 29.

Abstract

Aim: Salivary miRNA can be easily accessible biomarkers of alcohol dependence (AD). Materials & methods: 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. Results: 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. Conclusion: This study provided the first evidence that salivary miRNAs are AD biomarkers.

Keywords: alcohol dependence; differential expression; machine learning; salivary microRNA; small RNA sequencing.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Adult
  • Alcoholism / diagnosis*
  • Alcoholism / ethnology
  • Alcoholism / genetics
  • Biomarkers / metabolism*
  • Black or African American
  • Case-Control Studies
  • Female
  • Gene Expression Regulation
  • Humans
  • Machine Learning*
  • Male
  • MicroRNAs / metabolism*
  • Middle Aged
  • Saliva / metabolism*
  • Sequence Analysis, RNA
  • White People

Substances

  • Biomarkers
  • MicroRNAs