Autoimmunity, Volume 35, Number 4/2002, Pages: 225 - 234
Bernadette Kalman A1, Ross H. Albert A2, Thomas P. Leist A3
A1 Department of Neurology, MS423, MCP Hahnemann University, 245N 15th Street, Philadelphia, PA 19102, USA
A2 Department of Biochemistry, MCP Hahnemann University, Philadelphia, PA, USA
A3 Department of Neurology, Thomas Jefferson University, Philadelphia, PA, USA
Since the first description of multiple sclerosis (MS) as an inheritable disease by Eichhorst accumulating epidemiological observations support a genetic hypothesis.
Population, family and twin studies have revealed that Mendelian transmission of a single susceptibility gene would not be compatible with the observed patterns of inheritance.
Like most other common diseases, MS is a complex trait, defined by several genes, each probably exerting a relatively small effect.
Complex interactions among susceptibility genes and the environment are believed to contribute to a predisposition to dysregulation of inflammatory pathways, demyelination and tissue degeneration in the central nervous system (CNS).
Natural history and pathological studies, however, define that MS represents a spectrum rather than a single entity of inflammatory demyelination.
Despite a growing need for identifying molecular markers of biological subtypes of MS, only limited information is available for genotype-phenotype correlations.
Four full genome scans using polymorphic microsatellite markers in nuclear and multiplex MS families indicated several chromosomal regions of susceptibility.
With the recently discovered, highly abundant single nucleotide polymorphisms (SNPs) and family-based association methods, the means are now available to confine these relatively large regions of interest to candidate genes and susceptibility alleles.
The currently available SNP maps favor indirect association studies based on linkage disequilibrium between marker and disease alleles.
Here, we review available genetic data in MS, and introduce an additional strategy which correlate genetic markers with major biological components of the disease such as autoimmunity and neurodegeneration.
This approach may yield important insights with utility in clinical practice.
© 2002, Taylor & Francis Group