Use of "omics" technologies to dissect neurologic disease

Over the past 5 years, the advent of massively parallel technologies for understanding disease at the molecular level accompanied by simultaneous rapid development of the computational tools needed to analyze and filter such data has revolutionized medical science. These "next-generation" "omics" technologies include next-generation sequencing technology for detection of disease-associated DNA sequence variants, RNA sequencing for transcriptome and noncoding RNA analysis, quantitative detection of epigenomic dynamics, and chromatin immunoprecipitation sequencing analysis for DNA-protein interactions, interactome analysis for networks formed by protein-protein interactions, and metabolome analysis for metabolic systems. The analysis and integration of data derived from massively parallel technologies will significantly deepen our understanding of human disease, will inform functional studies, in vitro and in vivo model generation, and will advance the development of improved, personalized diagnostic tools and more effective therapeutic targets. In this chapter we review the classic genomic approaches for identifying mechanisms underlying human disease, and summarize the emerging "omics" technologies allowing massively parallel interrogation of biologic systems.