Integrative omics for health and disease

This article discusses how integrating different omics data types — such as DNA sequencing, transcriptomics and metabolomics — can provide a rich view of healthy and disease states, including novel clinical diagnoses. The authors discuss the value of the different data types, as well as strategies, considerations and challenges for multi-omic integration in various disease contexts. Advances in omics technologies — such as genomics, transcriptomics, proteomics and metabolomics — have begun to enable personalized medicine at an extraordinarily detailed molecular level. Individually, these technologies have contributed medical advances that have begun to enter clinical practice. However, each technology individually cannot capture the entire biological complexity of most human diseases. Integration of multiple technologies has emerged as an approach to provide a more comprehensive view of biology and disease. In this Review, we discuss the potential for combining diverse types of data and the utility of this approach in human health and disease. We provide examples of data integration to understand, diagnose and inform treatment of diseases, including rare and common diseases as well as cancer and transplant biology. Finally, we discuss technical and other challenges to clinical implementation of integrative omics.