Abnormal lesions in the brain will affect your cognition over time. This concept is rather intuitive but hard to prove because of our past limitations in performing good cognitive exams and mapping brain volume loss. This however has changed with the advent of newer technology. The authors of this paper studied a subset of patients from the Atherosclerosis risk in Communities (ARIC) population who underwent a brain MRI scan. Those with poor cognitive scores suggestive of dementia were excluded. Participants were additionally administered a battery of neuropsychological tests. Cognitive domains included: Memory (Delayed Word Recall Test, Logical Memory immediate and delayed recall, and incidental Learning from the Wechsler Memory Scale-III), Psychomotor Speed/Executive Function (PS/EF) (Digit Symbol Substitution Test, Trail Making Test parts A and B and WAIS-R Digits Span Backwards), and Language (Letter fluency, Boston Naming Test, and Animal Naming). Additionally all participants also underwent an extensive evaluation of vascular risk factors at each visit with detailed medical history and APOE genotyping performed.
A 3 Tesla MRI scan with all standard sequences was performed. White matter hyper intensity burden was calculated using total intracranial volume as a covariate. Cortical infarctions were counted and characterized on flair sequences as large or small and subcortical infarctions were also sub classified. Regions of Interest (ROI’s) were identified based on relevance to cognition and cortical volumes of the right and left hippocampus, posterior regions and frontal lobes were estimated. Primary analyses were conducted using general linear models. Potential nonlinear relationships were examined with lowess smooth curves and modeled using fractional polynomial and linear-spline formulations. Potential outlier effects were assessed with DFFITS for influential points, Cook’s D statistic, and graphical displays such as residual and added-variable plots. Several statistical modifications were undertaken for the cognitive scores, MRI results and brain volume measurement that are detailed in the manuscript. All models were adjusted for clinical and demographic variables including age, sex, race, education, and history of diabetes, history of hypertension, history of alcohol use, and history of smoking, APOE ε4 genotype and total intracranial volume. Interaction terms were examined to assess potential modifying effects of sex and/or race; none were supported. Sensitivity analyses to for hippocampal ROIs, <60 mm3 for posterior cortical for frontal cortical ROIs, and using fractional polynomial formulations for examine stability of estimates were conducted examining adjustment model, nonlinearity threshold and sampling weight incorporation; similar results were found throughout.
Cross-sectional mediation analyses showed the posterior cortical regions and a group of frontal regions moderately mediated associations between WMH burden and a cognitive composite representing psychomotor speed and executive function (PS/EF). The association between infarcts, the variable representing the presence of any infarct, and the PS/EF composite was also moderately mediated by the posterior cortical ROI. In bivariate analyses, both CVD imaging features – WMH and infarcts – were associated with posterior cortical ROI volume. Only WMH were associated with frontal ROI volume.
This study is a complex yet valiant effort in establishing the link between brain lesions, brain volume and cognitive function. It is certainly hypothesis generating and lends credence to the theory that loss of brain volume mediates the cognitive slowing in patients with cerebrovascular disease.
