DocumentCode :
3742481
Title :
MicroRNA and gene expression profiling of response to lithium treatment for bipolar I disorder
Author :
Julia Tzu-Ya Weng;Yu-Xiang Chi;Lawrence Shih-Hsin Wu;Chau-Shoun Lee;Andrew T. A. Cheng
Author_Institution :
Department of Computer Science & Engineering, Innovation Center for Big Data & Digital Convergence, Yuan Ze University, Chung-Li, Taiwan
fYear :
2015
Firstpage :
446
Lastpage :
452
Abstract :
Bipolar is a debilitating mood disorder characterized by mixed episodes of depression and mania. It is classified into bipolar I and II according to the occurrences and frequencies of depressive and manic episodes. As the sixth leading cause of disability in the world, bipolar disorder exerts a huge amount of burden on the patient´s family and the society as a whole. Lithium is often the prescribed medication; however, not all patients are responsive to it. In fact, some may even develop adverse drug reactions to the drug. In an attempt to understand the mechanisms underlying the response to lithium among bipolar I patients, we profiled the gene and microRNA expression differences between the good and poor responders in peripheral blood. We identified a number of differentially expressed genes and microRNAs, determined their functions using gene ontology and pathway annotation tools, and assessed the potential interactions between these two types of molecules via target prediction algorithms, association analyses, and existing literature evidence. We found several microRNA-gene interaction biomarkers that differ between the poor and good lithium responders. With future validations, these biomarkers may provide insights into the mechanism underlying lithium response.
Keywords :
"Lithium","RNA","Blood","Correlation","Biomarkers","Gene expression","Mood"
Publisher :
ieee
Conference_Titel :
Biomedical Engineering and Informatics (BMEI), 2015 8th International Conference on
Type :
conf
DOI :
10.1109/BMEI.2015.7401546
Filename :
7401546
Link To Document :
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