Abstract

Over the last twenty years, there has been a rapid expansion of high-throughput molecular profiling techniques for human samples as well as of their deployment at proper scale to generate highly significant, reproducible results. This experience and the resulting insights have laid a strong foundation that now informs the design of a new generation of studies. Specifically, no single dimension of information is sufficient to capture the onset or course of MS: an integrated multi-modal approach is necessary. In this section of the course, we will briefly review human genetic studies that have largely led the conceptual framework of high-dimensional analyses, especially the concept of data reduction and rigorous statistical methodologies that are essential for these studies. We will then move on to discuss their integration with the epigenome in an effort to systematically map the functional consequences of genetic variants. We will also touch on transcriptomic data, and their systematic analyses Then, using cerebrospinal fluid data, we will introduce new concepts of population structure and communication among cell subtype that are central to single cell analyses. However, all of these approaches are dependent on robust outcome measures that are often the limiting factor in MS studies. Thus, with a rapid tour of different modalities, we will review key concepts and study designs that can guide the development of new experiments to generate high-dimensional data that will enhance our understanding of MS.