Atrophy patterns on MRI can reliably predict three neuropathological subtypes of Alzheimer’s disease (AD): typical, limbic-predominant, or hippocampal-sparing. A method to enable their investigation in the clinical routine is still lacking. We aimed to (1) validate the combined use of visual rating scales for identification of AD subtypes; (2) characterise these subtypes at baseline and over two years; and (3) investigate how atrophy patterns and non-memory cognitive domains contribute to memory impairment. AD patients were classified as either typical AD (n = 100), limbic-predominant (n = 33), or hippocampal-sparing (n = 35) by using the Scheltens’ scale for medial temporal lobe atrophy (MTA), the Koedam’s scale for posterior atrophy (PA), and the Pasquier’s global cortical atrophy scale for frontal atrophy (GCA-F). A fourth group with no atrophy was also identified (n = 30). 230 healthy controls were also included. There was great overlap among subtypes in demographic, clinical, and cognitive variables. Memory performance was more dependent on non-memory cognitive functions in hippocampal-sparing and the no atrophy group. Hippocampal-sparing and the no atrophy group showed less aggressive disease progression. Visual rating scales can be used to identify distinct AD subtypes. Recognizing AD heterogeneity is important and visual rating scales may facilitate investigation of AD heterogeneity in clinical routine.

Objective: Increased variability in cognition with age has been argued as an indication of pathological processes. Focusing on early detection of neurodegenerative disorders, we investigated variability in cognition in healthy middle-aged adults. In order to understand possible determinants of this variability, we also investigated associations with cognitive reserve, neuroimaging markers, subjective memory complaints, depressive symptomatology, and gender. Method: Thirty-one 50±2 years old individuals were investigated as target group and deviation was studied in comparison to a reference younger group of thirty individuals 40±2 years old. Comprehensive neuropsychological and structural imaging protocols were collected. Brain regional volumes and cortical thickness were calculated with FreeSurfer, white matter hyperintensities with CASCADE, and mean diffusivity with FSL. Results: Across-individuals variability showed greater dispersion in lexical access, processing speed, executive functions, and memory. Variability in global cognition correlated with, reduced cortical thickness in the right parietal-temporal-occipital association cortex, and increased mean diffusivity in the cingulum bundle and right inferior fronto-occipital fasciculus. A trend was also observed for the correlation between global cognition and hippocampal volume and female gender. All these associations were influenced by cognitive reserve. No correlations were found with subjective memory complaints, white matter hyperintensities and depressive symptomatology. Across-domains and across-tasks variability was greater in several executive components and cognitive processing speed. Conclusions: Variability in cognition during middle-age is associated with neurodegeneration in the parietal-temporal-occipital association cortex and white matter tracts connecting this to the prefrontal dorsolateral cortex and the hippocampus. Moreover, this effect is influenced by cognitive reserve. Studying variability offers valuable information showing that differences do not occur in the same magnitude and direction across individuals, cognitive domains and tasks. These findings may have important implications for early detection of subtle cognitive impairment and clinical interpretation of deviation from normality.

Introduction: Mild cognitive impairment is common in nondemented Parkinson disease patients (PD-MCI) and is considered as a risk factor for dementia (PDD). Recently, the Movement Disorder Society (MDS) published guidelines for PD-MCI, although the studies available are still limited. The aim of this work was to characterize PD-MCI and its progression to dementia. Moreover, the study variables could be considered as predictors for the progression of cognitive impairment. Method: The study included 43 patients with idiopathic PD (mean age = 59.19 years, SD = 9.64) and 20 healthy and neurologically normal controls (mean age = 60.85 years, SD = 12.26). The criteria proposed by the MDS Task Force were applied for the PD-MCI diagnosis. Follow-up assessments were conducted within six to eight years after the diagnosis of PD-MCI. Results: The results showed that 60.5% of the patients were diagnosed with PD-MCI when a comprehensive assessment was performed (MDS criteria Level 2), while 23.3% of the patients met MCI criteria when a brief assessment was used (MDS criteria Level 1). Multiple domain impairment was the most frequent impairment (96.2%). A total of 42.3% of PD-MCI patients had dementia in the follow-up study. Logistic regression showed that the Hoehn and Yahr stage and education significantly contributed to the prediction of PD-MCI. Moreover, the Hoehn and Yahr stage and memory domain significantly contributed to the prediction of dementia. Conclusions: The results of the study: (a) provide relevant data about the process of validation of the MDS PD-MCI criteria, (b) reinforce the hypothesis that PD-MCI is more frequent than previous studies showed without applying MDS criteria, and (c) confirm that PD-MCI is a risk factor for the onset of dementia. Finally, the study shows that neurological impairment, educational level and memory impairment were predictors for the progression of cognitive impairment.

To define the profile of age-related differences in cognition in healthy middle-aged adults in order to identify the most sensitive measures of early cognitive decline. To study whether these differences precede cognitive decline in the elderly. 141 cognitively normal participants (101 middle-aged adults with age 40-50±2; and 40 elderly individuals with age 65±2) were assessed with a comprehensive neuropsychological protocol covering processing speed, attention, executive functions, verbal and visual episodic memory, procedural memory, visuoconstructive, visuoperceptive and visuospatial functions, and language. Age-related differences were detected before the age of 50 in cognitive reaction time, executive control, initial learning in verbal episodic memory, complex visuoconstructive and visuospatial functions, and lexical access. These differences preceded more extensive cognitive decline present at the age of 65. Our findings suggest subtle executive dysfunction before the age of 50, together with slowing in processing speed later on in the transition to old age. This profile could be explained by changes in the frontal lobe and its connections, starting at middle-age. These findings, together with future research, may be important for the diagnosis, prognosis, and prevention of pathological aging at a very early level.