title: Revisiting Chaos Theorem to Understand the Nature of miRNAs in Response to Drugs of Abuse.
abstract: Just like Matryoshka dolls, biological systems follow a hierarchical order that is based on dynamic bidirectional communication among its components. In addition to the convoluted inter-relationships, the complexity of each component spans several folds. Therefore, it becomes rather challenging to investigate phenotypes resulting from these networks as it requires the integration of reductionistic and holistic approaches. One dynamic system is the transcriptome which comprises a variety of RNA species. Some, like microRNAs, have recently received a lot of attention. miRNAs are very pleiotropic and have been considered as therapeutic and diagnostic candidates in the biomedical fields. In this review, we survey miRNA profiles in response to drugs of abuse (DA) using 118 studies. After providing a summary of miRNAs related to substance use disorders (SUD), general patterns of miRNA signatures are compared among studies for single or multiple drugs of abuse. Then, current challenges and drawbacks in the field are discussed. Finally, we provide support for considering miRNAs as a chaotic system in normal versus disrupted states particularly in SUD and propose an integrative approach for studying and analyzing miRNA data.
authors.affiliation: Department of Biology, East Carolina University, Greenville, North Carolina.
authors.forename: Faten A
authors.initials: FA
authors.lastname: Taki
authors.affiliation: Department of Biology, East Carolina University, Greenville, North Carolina.
authors.forename: Xiaoping
authors.initials: X
authors.lastname: Pan
authors.affiliation: Department of Biology, East Carolina University, Greenville, North Carolina.
authors.forename: Baohong
authors.initials: B
authors.lastname: Zhang
mesh_terms: D000818:Animals; D020869:Gene Expression Profiling / Q000379:methods; D005786:Gene Expression Regulation / Q000187:drug effects; D005819:Genetic Markers; D006801:Humans; D035683:MicroRNAs / Q000235:genetics* / Q000378:metabolism; D008957:Models, Genetic; D017711:Nonlinear Dynamics; D019966:Substance-Related Disorders / Q000235:genetics* / Q000378:metabolism
chemical_list: D005819:Genetic Markers; D035683:MicroRNAs