Leveraging Molecular Data Analysis to Understand Drug Response in Systemic Sclerosis  Antonio Julià  Journal of Investigative Dermatology  Volume 137, Issue 5, Pages 1000-1002 (May 2017) DOI: 10.1016/j.jid.2017.01.009 Copyright © 2017 The Author Terms and Conditions

Figure 1 Alternative approaches to identifying the biological mechanisms underlying a phenotype. High throughput analysis of gene expression can be associated with the phenotype of interest (e.g., response to a drug) using three different approaches. At the lowest level, the expression of each gene is tested individually for association with the trait of interest (top figure). This approach is used most commonly because it identifies the genes with highest changes in mRNA levels associated with the phenotype. Another common approach is to use previous knowledge to determine sets of functionally related genes or pathways (middle figure). Analysis using pathways has the benefits of reducing the number of tested hypotheses and providing more biologically interpretable results. A recent approach integrates tissue-specific genetic information to contextualize the observed gene expression changes in the tissue targeted by the disease (e.g., skin in systemic sclerosis) and identifies genes that are highly relevant for the phenotype, despite not necessarily showing significant changes at the transcriptomic level (gene in green, bottom figure). Journal of Investigative Dermatology 2017 137, 1000-1002DOI: (10.1016/j.jid.2017.01.009) Copyright © 2017 The Author Terms and Conditions