Microarray Analysis in Cardiac Arrhythmias: A New Perspective?

• Published in: Pacing and clinical electrophysiology Vol. 36; no. 7; pp. 911 - 917
• Main Authors: MORIC-JANISZEWSKA, EWA, HIBNER, GRZEGORZ
• Format: Journal Article
• Language: English
• Published: United States Blackwell Publishing Ltd 01-07-2013
• Subjects: Arrhythmias, Cardiac - diagnosis; Arrhythmias, Cardiac - metabolism; Biomarkers - analysis; cardiac arrhythmias; expression analysis; Forecasting; Gene Expression Profiling - methods; Gene Expression Profiling - trends; Humans; Metabolome; microarray analysis; Oligonucleotide Array Sequence Analysis - methods; Oligonucleotide Array Sequence Analysis - trends; TaqMan technique; microarray analysis; expression analysis; TaqMan technique; cardiac arrhythmias
• ISSN: 0147-8389; 1540-8159
• DOI: 10.1111/pace.12143

The opportunity to distinguish an accurate set of genes associated with multigenic diseases such as cardiomyopathies or cardiac arrhythmias was very limited before the genomic era. Numerous methods of measuring RNA abundance exist, including northern blotting, multiplex polymerase chain reaction (PCR), and quantitative real‐time reverse transcriptase‐PCR. However, these techniques might be used to assess the expression levels of only 10–50 genes at time. Today, DNA microarrays provide us with opportunity to simultaneously analyze tens of thousands of genes, giving a remarkable possibility to investigate the genomic contribution to cardiovascular diseases. A particular tissue at any stage of health or disease may be used to generate a genomic profile. Microarray techniques are already used in infectious diseases, oncology, and pharmacology to facilitate clinicians, risk‐stratify patients, as well as to predict and assess therapeutic responses to drugs. In this paper, we describe recent advances in the use of various types of microarray technique in the diagnosis of arrhythmogenic heart disease. We also highlight other strategies and methods of differential gene typing comparing with pros and cons of microarray analysis.