Polygenic susceptibility for multiple sclerosis is associated with working memory in low-performing young adults
J Petrovska1, D Coynel2, V Freytag1
1Division of Molecular Neuroscience, Department of Biomedicine, University of Basel, CH-4055 Basel, Switzerland; Research Cluster Molecular and Cognitive Neurosciences, Department of Biomedicine, University of Basel, CH-4055 Basel, Switzerland.
Background:
Multiple sclerosis (MS) is a complex disease with substantial heritability estimates. Besides typical clinical manifestations such as motor and sensory deficits, MS is characterized by structural and functional brain abnormalities, and by cognitive impairment such as decreased working memory (WM) performance.
Objectives:
We investigated the possible link between the polygenic risk for MS and WM performance in healthy adults (18-35 years). Additionally, we addressed the relationship between polygenic risk for MS and white matter fractional anisotropy (FA).
Methods:
We generated a polygenic risk score (PRS) of MS susceptibility and investigated its association with WM performance in 3282 healthy adults (two subsamples, N1 = 1803, N2 = 1479). The association between MS-PRS and FA was studied in the second subsample. MS severity PRS associations were also investigated for the WM and FA measurements.
Results:
MS-PRS was significantly associated with WM performance within the 10% lowest WM-performing individuals (p = 0.001; pFDR = 0.018). It was not significantly associated with any of the investigated FA measurements. MS severity PRS was significantly associated with brain-wide mean FA (p = 0.041) and showed suggestive associations with additional FA measurements.
Conclusions:
By identifying a genetic link between MS and WM performance this study contributes to the understanding of the genetic complexity of MS, and hopefully to the possible identification of molecular pathways linked to cognitive deficits in MS. It also contributes to the understanding of genetic associations with MS severity, as these associations seem to involve distinct biological pathways compared to genetic variants linked to the overall risk of developing MS.
Insights
Genetic risk for multiple sclerosis (MS) is linked to lower working memory (WM) performance in healthy adults. MS polygenic risk scores (PRS) associated with WM, but not white matter integrity, suggesting distinct genetic pathways for MS risk and severity.
Area of Science:
- Neurogenetics
- Cognitive Neuroscience
- Neuroimmunology
Background:
- Multiple sclerosis (MS) is a complex neurological disorder with significant genetic heritability.
- MS is associated with cognitive impairments, particularly in working memory (WM).
- Brain abnormalities, including white matter changes, are characteristic of MS.
Purpose of the Study:
- To investigate the association between polygenic risk for MS and WM performance in healthy young adults.
- To examine the relationship between MS polygenic risk and white matter integrity (fractional anisotropy, FA).
- To explore genetic associations with MS severity in relation to WM and FA.
Main Methods:
- A polygenic risk score (PRS) for MS susceptibility was generated in 3282 healthy adults.
- The association between MS-PRS and WM performance was analyzed.
- The relationship between MS-PRS and white matter fractional anisotropy (FA) was assessed in a subsample.
Main Results:
- MS-PRS was significantly associated with lower WM performance in the lowest-performing individuals.
- No significant association was found between MS-PRS and white matter FA.
- MS severity PRS showed significant associations with mean FA, suggesting distinct genetic influences.
Conclusions:
- This study identifies a genetic link between MS susceptibility and WM performance in healthy individuals.
- The findings contribute to understanding the genetic complexity of MS and potential molecular pathways for cognitive deficits.
- Genetic associations with MS severity appear to involve different biological pathways than those related to overall MS risk.
Related Concept Videos
Working Memory
Information Processing Approach
Biological Influences on Intelligence


