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Brain aging and psychometric intelligence: a longitudinal study

Abstract

In this study, we examined a large sample of 231 generally healthy older adults across 4 years with regard to several brain anatomical measures (volumes of total grey matter volume: GM, normal appearing white matter: NAWM, lateral ventricle: LV, and white matter hypointensities: WMH) and psychometric intelligence (verbal and non-verbal). The dataset comprised four measurement occasions (baseline, 1-, 2-, and 4-year follow-ups). With this longitudinal data set, we evaluated level–level, level–change, and change–change relationships between the anatomical and psychometric measures using latent growth curve models. Our analyses indicate that GM and NAWM decreased significantly over the course of 4 years with annual percent changes of − 0.73% and − 0.79%, respectively. WMH and LV volumes increase with annual percent changes of 7.3% and 4%, respectively. Verbal and nonverbal IQ measures remained stable in our sample. In addition, we uncovered evidence for level–level and -change associations between several of the brain anatomical measures. With regard to brain-IQ associations, we observed a positive level–level association for GM and NAWM, indicating that participants with larger brain volumes demonstrate higher IQ measures. No substantial evidence was identified for level- or change–change associations between any of the brain metrics and the IQ measures. Taken together, these results suggest that while healthy older adults demonstrated age-related neuroanatomical decline over a time span of 4 years, these degenerative changes are not necessarily linked to simultaneous cognitive deterioration.

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Acknowledgements

The current analysis incorporates data from the Longitudinal Healthy Aging Brain (LHAB) database project, which is carried out as one of the core projects at the International Normal Aging and Plasticity Imaging Center/INAPIC and the University Research Priority Program “Dynamics of Healthy Aging” of the University of Zurich. The following members of the core INAPIC team were involved in the design, set-up, maintenance, and support of the LHAB database: Anne Eschen, Lutz Jäncke, Mike Martin, Susan Merillat, Christina Rocke, and Jacqueline Zöllig.

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Jäncke, L., Sele, S., Liem, F. et al. Brain aging and psychometric intelligence: a longitudinal study. Brain Struct Funct 225, 519–536 (2020). https://doi.org/10.1007/s00429-019-02005-5

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Keywords

  • Brain aging
  • Psychometric intelligence
  • Longitudinal study
  • Level–level-association
  • Level–change-association
  • Change–change-association