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Polymorphisms in the Receptor Tyrosine Kinase MERTK Gene Are Associated with Multiple Sclerosis Susceptibility

Overview of attention for article published in PLOS ONE, February 2011
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Title
Polymorphisms in the Receptor Tyrosine Kinase MERTK Gene Are Associated with Multiple Sclerosis Susceptibility
Published in
PLOS ONE, February 2011
DOI 10.1371/journal.pone.0016964
Pubmed ID
Authors

Gerry Z. M. Ma, Jim Stankovich, Trevor J. Kilpatrick, Michele D. Binder, Judith Field

Abstract

Multiple sclerosis (MS) is a debilitating, chronic demyelinating disease of the central nervous system affecting over 2 million people worldwide. The TAM family of receptor tyrosine kinases (TYRO3, AXL and MERTK) have been implicated as important players during demyelination in both animal models of MS and in the human disease. We therefore conducted an association study to identify single nucleotide polymorphisms (SNPs) within genes encoding the TAM receptors and their ligands associated with MS. Analysis of genotype data from a genome-wide association study which consisted of 1618 MS cases and 3413 healthy controls conducted by the Australia and New Zealand Multiple Sclerosis Genetics Consortium (ANZgene) revealed several SNPs within the MERTK gene (Chromosome 2q14.1, Accession Number NG_011607.1) that showed suggestive association with MS. We therefore interrogated 28 SNPs in MERTK in an independent replication cohort of 1140 MS cases and 1140 healthy controls. We found 12 SNPs that replicated, with 7 SNPs showing p-values of less than 10(-5) when the discovery and replication cohorts were combined. All 12 replicated SNPs were in strong linkage disequilibrium with each other. In combination, these data suggest the MERTK gene is a novel risk gene for MS susceptibility.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 71 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
France 1 1%
Unknown 69 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 21%
Student > Ph. D. Student 11 15%
Student > Bachelor 7 10%
Student > Master 6 8%
Student > Doctoral Student 5 7%
Other 12 17%
Unknown 15 21%
Readers by discipline Count As %
Agricultural and Biological Sciences 20 28%
Medicine and Dentistry 16 23%
Neuroscience 4 6%
Computer Science 3 4%
Biochemistry, Genetics and Molecular Biology 2 3%
Other 8 11%
Unknown 18 25%