172
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Salivary microRNAs Identified by Small RNA Sequencing and Machine Learning as Potential Biomarkers of Alcohol Dependence

, , , , , , , & show all
Pages 739-749 | Received 15 Oct 2018, Accepted 04 Feb 2019, Published online: 29 May 2019

References

  • Hietala J , KoivistoH , AnttilaP , NiemelaO. Comparison of the combined marker GGT-CDT and the conventional laboratory markers of alcohol abuse in heavy drinkers, moderate drinkers and abstainers. Alcohol Alcohol.41(5), 528–533 (2006).
  • Seppa K , LaippalaP , SaarniM. Macrocytosis as a consequence of alcohol abuse among patients in general practice. Alcohol. Clin. Exp. Res.15(5), 871–876 (1991).
  • Davenport J . Macrocytic anemia. Am. Fam. Physician53(1), 155–162 (1996).
  • Peterson K . Biomarkers for alcohol use and abuse – a summary. Alcohol Res. Health28(1), 30–37 (2004).
  • Justice AC , McGinnisKA , TateJPet al. Validating harmful alcohol use as a phenotype for genetic discovery using phosphatidylethanol and a polymorphism in ADH1B. Alcohol. Clin. Exp. Res.41(5), 998–1003 (2017).
  • Quillen EE , ChenXD , AlmasyLet al. ALDH2 is associated to alcohol dependence and is the major genetic determinant of “daily maximum drinks” in a GWAS study of an isolated rural Chinese sample. Am. J. Med. Genet. B Neuropsychiatr. Genet.165B(2), 103–110 (2014).
  • Gelernter J , KranzlerHR , ShervaRet al. Genome-wide association study of alcohol dependence: significant findings in African– and European–Americans including novel risk loci. Mol. Psychiatry19(1), 41–49 (2014).
  • Edenberg HJ . Common and rare variants in alcohol dependence. Biol. Psychiatry70(6), 498–499 (2011).
  • Filipowicz W , BhattacharyyaSN , SonenbergN. Mechanisms of post-transcriptional regulation by microRNAs: are the answers in sight?Nat. Rev. Genet.9(2), 102–114 (2008).
  • Liu X , FortinK , MourelatosZ. MicroRNAs: biogenesis and molecular functions. Brain Pathol.18(1), 113–121 (2008).
  • Bartel DP . MicroRNAs: target recognition and regulatory functions. Cell136(2), 215–233 (2009).
  • Krol J , LoedigeI , FilipowiczW. The widespread regulation of microRNA biogenesis, function and decay. Nat. Rev. Genet.11(9), 597–610 (2010).
  • Nebbioso A , TambaroFP , Dell’AversanaC , AltucciL. Cancer epigenetics: moving forward. PLoS Genet.14(6), e1007362 (2018).
  • Tapocik JD , SolomonM , FlaniganMet al. Coordinated dysregulation of mRNAs and microRNAs in the rat medial prefrontal cortex following a history of alcohol dependence. Pharmacogenomics J.13(3), 286–296 (2013).
  • Lewohl JM , NunezYO , DoddPR , TiwariGR , HarrisRA , MayfieldRD. Up-regulation of microRNAs in brain of human alcoholics. Alcohol. Clin. Exp. Res.35(11), 1928–1937 (2011).
  • Wang F , GelernterJ , ZhangH. Differential expression of miR-130a in postmortem prefrontal cortex of subjects with alcohol use disorders. J. Addict. Res. Ther.4(155), pii 18179 (2013).
  • Hunter MP , IsmailN , ZhangXet al. Detection of microRNA expression in human peripheral blood microvesicles. PLoS ONE3(11), e3694 (2008).
  • Zernecke A , BidzhekovK , NoelsHet al. Delivery of microRNA-126 by apoptotic bodies induces CXCL12-dependent vascular protection. Sci. Signal.2(100), ra81 (2009).
  • Arroyo JD , ChevilletJR , KrohEMet al. Argonaute2 complexes carry a population of circulating microRNAs independent of vesicles in human plasma. Proc. Natl Acad. Sci. USA108(12), 5003–5008 (2011).
  • Vickers KC , PalmisanoBT , ShoucriBM , ShamburekRD , RemaleyAT. MicroRNAs are transported in plasma and delivered to recipient cells by high-density lipoproteins. Nat. Cell Biol.13(4), 423–433 (2011).
  • Bahn JH , ZhangQ , LiFet al. The landscape of microRNA, Piwi-interacting RNA, and circular RNA in human saliva. Clin. Chem.61(1), 221–230 (2015).
  • Li F , YoshizawaJM , KimKMet al. Discovery and validation of salivary extracellular RNA biomarkers for noninvasive detection of gastric cancer. Clin. Chem.64(10), 1513–1521 (2018).
  • Pierucci-Lagha A , GelernterJ , FeinnRet al. Diagnostic reliability of the semi-structured assessment for drug dependence and alcoholism (SSADDA). Drug Alcohol Depend.80(3), 303–312 (2005).
  • Pierucci-Lagha A , GelernterJ , ChanGet al. Reliability of DSM-IV diagnostic criteria using the semi-structured assessment for drug dependence and alcoholism (SSADDA). Drug Alcohol Depend.91(1), 85–90 (2007).
  • Friedlander MR , ChenW , AdamidiCet al. Discovering microRNAs from deep sequencing data using miRDeep. Nat. Biotech.26(4), 407–415 (2008).
  • Ambros V , BartelB , BartelDPet al. A uniform system for microRNA annotation. RNA9(3), 277–279 (2003).
  • Robinson BG , MealyK , WilmoreDW , MajzoubJA. The effect of insulin-induced hypoglycemia on gene expression in the hypothalamic-pituitary-adrenal axis of the rat. Endocrinology130(2), 920–925 (1992).
  • Mccarthy DJ , ChenY , SmythGK. Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation. Nucleic Acids Res.40(10), 4288–4297 (2012).
  • Dweep H , StichtC , PandeyP , GretzN. miRWalk–database: prediction of possible miRNA binding sites by “walking” the genes of three genomes. J. Biomed. Inform.44(5), 839–847 (2011).
  • Dweep H , GretzN. miRWalk2.0: a comprehensive atlas of microRNA-target interactions. Nat. Methods12(8), 697 (2015).
  • Lewis BP , BurgeCB , BartelDP. Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell120(1), 15–20 (2005).
  • Wong N , WangX. miRDB: an online resource for microRNA target prediction and functional annotations. Nucleic Acids Res.43(Database issue), D146–D152 (2015).
  • Chou CH , ShresthaS , YangCDet al. miRTarBase update 2018: a resource for experimentally validated microRNA-target interactions. Nucleic Acids Res.46(D1), D296–D302 (2018).
  • Huang Da W , ShermanBT , LempickiRA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat. Protoc.4(1), 44–57 (2009).
  • Breiman L . Random forests. Machine Learning45, 5–32 (2001).
  • Menze BH , KelmBM , MasuchRet al. A comparison of random forest and its Gini importance with standard chemometric methods for the feature selection and classification of spectral data. BMC Bioinform.10(1), 213 (2009).
  • Wang L , RishishwarL , Marino-RamirezL , JordanIK. Human population-specific gene expression and transcriptional network modification with polymorphic transposable elements. Nucleic Acids Res.45(5), 2318–2328 (2017).
  • Wickramasinghe SN , CorridanB , IzaguirreJ , HasanR , MarjotDH. Ethnic differences in the biological consequences of alcohol abuse: a comparison between south Asian and European males. Alcohol Alcohol.30(5), 675–680 (1995).
  • Bourgon R , GentlemanR , HuberW. Independent filtering increases detection power for high-throughput experiments. Proc. Natl Acad. Sci. USA107(21), 9546–9551 (2010).
  • Park NJ , ZhouH , ElashoffDet al. Salivary microRNA: discovery, characterization, and clinical utility for oral cancer detection. Clin. Cancer. Res.15(17), 5473–5477 (2009).
  • Matse JH , YoshizawaJ , WangXet al. Discovery and prevalidation of salivary extracellular microRNA biomarkers panel for the noninvasive detection of benign and malignant parotid gland tumors. Clin. Cancer Res.19(11), 3032–3038 (2013).
  • Lu J , GetzG , MiskaEAet al. MicroRNA expression profiles classify human cancers. Nature435(7043), 834–838 (2005).
  • Jiang J , LeeEJ , GusevY , SchmittgenTD. Real-time expression profiling of microRNA precursors in human cancer cell lines. Nucleic Acids Res.33(17), 5394–5403 (2005).
  • Salim A , AmjeshR , ChandraSS. An approach to forecast human cancer by profiling microRNA expressions from NGS data. BMC Cancer17(1), 77 (2017).
  • Kranzler HR , SmithRV , SchnollR , MoustafaA , Greenstreet-AkmanE. Precision medicine and pharmacogenetics: what does oncology have that addiction medicine does not?Addiction112(12), 2086–2094 (2017).
  • Beleites C , NeugebauerU , BocklitzT , KrafftC , PoppJ. Sample size planning for classification models. Anal. Chim. Acta760, 25–33 (2013).
  • Tam S , DeBorja R , TsaoMS , McPhersonJD. Robust global microRNA expression profiling using next-generation sequencing technologies. Lab. Invest.94(3), 350–358 (2014).

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.