Genetic susceptibility to multiple sclerosis: Brain structure and cognitive function in the general population

Mohammad Arfan Ikram*, Meike W. Vernooij, Gennady V. Roshchupkin, Albert Hofman, Cornelia M. van Duijn, André G. Uitterlinden, Wiro J. Niessen, Rogier Q. Hintzen, Hieab H. Adams

*Corresponding author for this work

    Research output: Contribution to journalArticleScientificpeer-review

    7 Citations (Scopus)

    Abstract

    Background: Multiple sclerosis (MS) affects brain structure and cognitive function and has a heritable component. Over a 100 common genetic risk variants have been identified, but most carriers do not develop MS. For other neurodegenerative diseases, risk variants have effects outside patient populations, but this remains uninvestigated for MS. Objectives: To study the effect of MS-associated genetic variants on brain structure and cognitive function in the general population. Methods: We studied middle-aged and elderly individuals (mean age = 65.7 years) from the population-based Rotterdam Study. We determined 107 MS variants and additionally created a risk score combining all variants. Magnetic resonance imaging (N = 4710) was performed to obtain measures of brain macrostructure, white matter microstructure, and gray matter voxel-based morphometry. A cognitive test battery (N = 7556) was used to test a variety of cognitive domains. Results: The MS risk score was associated with smaller gray matter volume over the whole brain (βstandardized = −0.016; p = 0.044), but region-specific analyses did not survive multiple testing correction. Similarly, no significant associations with brain structure were observed for individual variants. For cognition, rs2283792 was significantly associated with poorer memory (β = −0.064; p = 3.4 × 10−5). Conclusion: Increased genetic susceptibility to MS may affect brain structure and cognition in persons without disease, pointing to a “hidden burden” of MS.

    Original languageEnglish
    Pages (from-to)1697-1706
    Number of pages10
    JournalMultiple Sclerosis
    Volume23
    Issue number13
    DOIs
    Publication statusPublished - 1 Nov 2017

    Keywords

    • Epidemiology
    • genetics
    • magnetic resonance imaging
    • multiple sclerosis

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