Research Paper Volume 11, Issue 5 pp 1440—1456

Genetic variation underlying cognition and its relation with neurological outcomes and brain imaging

Maria J. Knol1, , Alis Heshmatollah1,2, , Lotte G.M. Cremers1,3, , M. Kamran Ikram1,2, , André G. Uitterlinden4, , Cornelia M. van Duijn1, , Wiro J. Niessen3,5,6, , Meike W. Vernooij1,3, , M. Arfan Ikram1, , Hieab H.H. Adams1,3, ,

  • 1 Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands
  • 2 Department of Neurology, Erasmus MC University Medical Center, Rotterdam, the Netherlands
  • 3 Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, the Netherlands
  • 4 Department of Internal Medicine, Erasmus MC University Medical Center, Rotterdam, the Netherlands
  • 5 Department of Medical Informatics, Erasmus MC University Medical Center, Rotterdam, the Netherlands
  • 6 Faculty of Applied Sciences, Delft University of Technology, Delft, the Netherlands
* Equal contribution

Received: November 28, 2018       Accepted: February 21, 2019       Published: March 4, 2019
How to Cite

Copyright: © 2019 Knol et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


Cognition in adults shows variation due to developmental and degenerative components. A recent genome-wide association study identified genetic variants for general cognitive function in 148 independent loci. Here, we aimed to elucidate possible developmental and neurodegenerative pathways underlying these genetic variants by relating them to functional, clinical and neuroimaging outcomes. This study was conducted within the population-based Rotterdam Study (N=11,496, mean age 65.3±9.9 years, 58.0% female). We used lead variants for general cognitive function to construct a polygenic score (PGS), and additionally excluded developmental variants at multiple significance thresholds. A higher PGS was related to more years of education (β=0.29, p=4.3x10-7) and a larger intracranial volume (β=0.05, p=7.5x10-4). To a smaller extent, the PGS was associated with less cognitive decline (βΔG-factor=0.03, p=1.3x10-3), which became non-significant after adjusting for education (p=1.6x10-2). No associations were found with daily functioning, dementia, parkinsonism, stroke or microstructural white matter integrity. Excluding developmental variants attenuated nearly all associations. In conclusion, this study suggests that the genetic variants identified for general cognitive function are acting mainly through the developmental pathway of cognition. Therefore, cognition, assessed cross-sectionally, seems to have limited value as a biomarker for neurodegeneration.


15-WLT: 15-word verbal learning test; BADL: basic activities of daily living; FA: fractional anisotropy; GWAS: genome-wide association study; IADL: instrumental activities of daily living; LDST: letter-digit substitution task; MD: mean diffusivity; MMSE: Mini-Mental State Examination; MRI: magnetic resonance imaging; PPB: Purdue pegboard; PGS: polygenic score.