Gene Linkage Study of Multiple Sclerosis Sibling Pairs
Location(s): United States
Multiple sclerosis (MS), the prototypic demyelinating disease in humans, is a common cause of neurological dysfunction arising from early to middle adulthood. No curative therapy is currently available and approximately 90% of afflicted individuals are ultimately disabled. The socioeconomic consequences of this long-lasting disease are staggering as 75-85% of patients are eventually unemployed and at high risk for social isolation. MS is the second most costly neurological disorder after Alzheimer's disease. We aim to map genes that code for products involved in MS susceptibility. We anticipate that there may be several genes involved in MS. These genes may work independently or together, and affect susceptibility in concert with environmental factors. Particular combinations of inherited genes may also determine when symptoms develop, or how the disease progresses. Their identification will help to define the basic etiology of MS, improve risk assessment, and influence therapeutics.
Multiple sclerosis (MS) is a common and severe disorder of the central nervous system characterized by chronic inflammation, myelin loss, gliosis, varying degrees of axonal and oligodendrocyte pathology, and progressive neurological dysfunction. MS pathogenesis includes a complex genetic component. In spite of intensive long-standing efforts, the knowledge of MS genetics remains incomplete. Our overall objective is to characterize the repertoire of genes that predispose to MS and modulate its presentation. Their identification is now possible as a result of rapid progress in defining the landscape of genetic organization and cataloging variation across the human genome. This proposal builds on the availability of new, high-quality genome-wide association results and comprehensive phenotypic data in a large longitudinal MS cohort. We propose three main research goals: Specific Aim 1 describes a 1,000 cases/1,000 controls high-resolution genome-wide association screen, together with a multi-analytical approach to map unambiguous association signals from sequence and copy number polymorphisms, leading to testable hypotheses as to which are the specific allelic variants conferring susceptibility. In addition, confirmed disease SNPs will be tested in a multi-case familial dataset to determine the minimal combination of genes that differentiate affected and unaffected family members. Data will be analyzed to model the relative contribution of the confirmed allelic variants in susceptibility. Specific Aim 2 takes advantage of the wealth of phenotypic data available for the different datasets to assess disease course, clinical variables, and correlations to genotype. Cross-sectional and longitudinal clinical data, such as age and site of disease onset, disability at entry of study and progression, treatment, and changes in lesion distribution and burden will be incorporated into the analysis of genetic data. This aim directly addresses the question of clinical heterogeneity in MS and the correlation between different phenotypes and genotypes. The availability of a large and well-characterized cohort as described here, coupled with the aid of high-powered laboratory technologies, provides an outstanding opportunity to identify and characterize MS-related genes. This information may reveal novel targets for therapy.