DOI: 10.1002/alz.079544 ISSN: 1552-5260

Baseline cognitive dispersion is related to increases in white matter hyperintensities in cognitively preserved older individuals

Lídia Mulet‐Pons, Lídia Vaqué‐Alcázar, Cristina Solé‐Padullés, María Cabello‐Toscano, Kilian Abellaneda‐Pérez, Ruben Perellón‐Alfonso, Oriol Perera‐Cruz, Núria Bargalló, David Bartrés‐Faz
  • Psychiatry and Mental health
  • Cellular and Molecular Neuroscience
  • Geriatrics and Gerontology
  • Neurology (clinical)
  • Developmental Neuroscience
  • Health Policy
  • Epidemiology



Cognitive dispersion (CD), understood as intra‐individual variability in performance, is considered a sensitive marker of prodromal stages of Alzheimer’s Disease (AD; Halliday et al. J. Intell 2018;6(1):12), and it is thought to complement cognitive performance (CP) in predicting age‐related changes (Costa et al. ClinicNeuropsychol 2019;33(2)). Moreover, white matter hyperintensities (WMH) are a common age‐associated finding that especially impacts processing speed (Boutzoukas et al. Front in AgingNeurosci 2021;13) and executive function (Papp et al. NeuropsycholDev 2014;21(2)). Therefore, we aimed to investigate (i) associations between CD, CP, and WMH, and (ii) whether WMH age‐related changes can be better predicted by baseline CD or CP in a cognitively normal aging sample.


One hundred and three healthy elders (age: 68.61±3.01 years; 72 females) underwent a neuropsychological assessment and a magnetic resonance image acquisition and repeated them after 2 years. Based on processing speed and executive function scores, we computed a baseline CD (i.e., CD‐tp1; using the intraindividual standard deviation method, Costa et al. Clinic Neuropsychol 2019;33(2)) and a CP (calculated with principal component analysis) at both time‐points (i.e., CP‐tp1, CP‐tp2). 3D‐FLAIR sequence was used to estimate WMH volumes (i.e., WMH‐tp1, WMH‐tp2) using the SPM12 Lesion Segmentation Toolbox (Schmidt et al. Neuroimage 2012;59(4)). The baseline volumes were subtracted from the follow‐up ones to obtain the difference (i.e., CP‐diff, WMH‐diff). Statistical analyses were linear regressions adjusted by age, sex, years of education, and intracranial volume for WMH analyses. Paired t‐tests were used for the longitudinal approach.


There was a negative cross‐sectional relationship between CD‐tp1 and CP‐tp1 (B = ‐.240, t = ‐3.034, p = .004; Fig1), while those cognitive measures were unrelated to WMH‐tp1 volumes. Longitudinally, we detected a significant increase in WMH (t = 7.244, p<.001), while CP remained stable and there were no significant associations between CP‐diff and WMH‐diff. The main finding was the significant relationship found between WMH volume increases (i.e., WMH‐diff) and CD‐tp1 (B = ‐.320, t = ‐3.060, p = .003; Fig2), but not with CP‐tp1.


The results show that in healthy elderly individuals who evidenced cognitive stability in processing speed and executive function, the CD is a sensitive marker to predict significant age‐related increases in WMH, which would be beneficial in the AD‐continuum.

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