Processing speed (PS) decline is the most commonly observed cognitive deficit in people with multiple sclerosis (MS) resulting in a significant impact on quality of life. Despite its importance, knowledge of the underlying neural substrates is lacking. As MS is increasingly recognised as a disconnection syndrome, our aim was to carry out a systematic literature review to clarify the relationship between PS performance and MRI measures of structural and functional brain connectivity in people with MS. A literature search was carried out on PubMed and Web of Science that included publications predating September 2017. Additional articles were added after inspection of the reference lists of all selected papers. All selected papers were categorised in three sections according to the MRI measures investigated, independently or both. Quality assessment was carried out using a customised set of criteria. Thirty-two articles met the inclusion criteria and were included in the review. Microstructural integrity of the anterior corpus callosum and functional connectivity of frontal areas were more consistently found to correlate with PS performance, though high variability of findings was observed across studies. Several methodological flaws emerged from the reviewed literature. Despite the observed trends, no definite conclusions can be drawn on the relationship between brain connectivity and PS decline in MS given the limitations of the current literature. Future investigations may benefit from theoretical and methodological advances to clarify how MS-related brain damage affects patients' cognition.

White matter hyperintensities (WMHs) are acquired lesions that accumulate and disrupt neuron-to-neuron connectivity. We tested the associations between WMH load and (1) regional grey matter volumes and (2) functional connectivity of resting-state networks, in a sample of 51 healthy adults. Specifically, we focused on the positive associations (more damage, more volume/connectivity) to investigate a potential route of adaptive plasticity. WMHs were quantified with an automated procedure. Voxel-based morphometry was carried out to model grey matter. An independent component analysis was run to extract the anterior and posterior default-mode network, the salience network, the left and right frontoparietal networks, and the visual network. Each model was corrected for age, global levels of atrophy, and indices of brain and cognitive reserve. Positive associations were found with morphometry and functional connectivity of the anterior default-mode network and salience network. Within the anterior default-mode network, an association was found in the left mediotemporal-limbic complex. Within the salience network, an association was found in the right parietal cortex. The findings support the suggestion that, even in the absence of overt disease, the brain actuates a compensatory (neuroplastic) response to the accumulation of WMH, leading to increases in regional grey matter and modified functional connectivity.

Blood-based biomarkers (BBM) are becoming easily detectable tools to reveal pathological changes in Alzheimer’s disease (AD). A comprehensive and up-to-date overview of the association between BBM and brain MRI parameters is not available. This systematic review aimed to summarize the literature on the associations between the main BBM and MRI markers across the clinical AD continuum. A systematic literature search was carried out on PubMed and Web of Science and a total of 33 articles were included. Hippocampal volume was positively correlated with Aβ42 and Aβ42/Aβ40 and negatively with Aβ40 plasma levels. P-tau181 and p-tau217 concentrations were negatively correlated with temporal grey matter volume and cortical thickness. NfL levels were negatively correlated with white matter microstructural integrity, whereas GFAP levels were positively correlated with myo-inositol values in the posterior cingulate cortex/precuneus. These findings highlight consistent associations between various BBM and brain MRI markers even in the pre-clinical and prodromal stages of AD. This suggests a possible advantage in combining multiple AD-related markers to improve accuracy of early diagnosis, prognosis, progression monitoring and treatment response.

Blood-based biomarkers are minimally invasive tools to detect the pathological changes of Alzheimer’s Disease (AD). This meta-analysis aims to investigate the use of blood-derived p-tau isoforms (181, 217, 231) to predict conversion from mild cognitive impairment (MCI) to AD dementia (ADD). Studies involving MCI patients with data on blood p-tau isoforms at baseline and clinical diagnosis at follow-up (≥1 year) were included. Twelve studies on p-tau 181 (4340 MCI, conversion rate 20.6%), four on p-tau 217 (913 MCI, conversion rate 33.4%), and one on p-tau 231 (135 MCI, conversion rate 33%) were included. For p-tau 181, the pooled area under the receiver operating characteristic curve (AUC) was 0.73 (95% CI = 0.68–0.78), and for p-tau 217 was 0.85 (95% CI = 0.75–0.91). Plasma levels of p-tau 181 had good discriminatory power to identify MCI patients who will convert to ADD. Although only four studies on p-tau 217 have been included in the meta-analysis, in the last year the predictive power of p-tau 217 is emerging as superior to that of other isoforms. However, given the high heterogeneity detected in the p-tau 217 studies included in this meta-analysis, additional supportive evidence is needed. Insufficient results were available for p-tau 231. These findings support the prognostic utility of p-tau 181 and p-tau 217 measured in blood to predict progression to ADD in MCI and encourage its future implementation in clinical practice.

Introduction: Depression in patients with mild cognitive impairment (MCI) and dementia of the Alzheimer’s type (AD) is associated with worse prognosis. Indeed, depressed MCI patients have worse cognitive performance and greater loss of gray-matter volume in several brain areas. To date, knowledge of the factors that can mitigate this detrimental effect is still limited. The aim of the present study was to understand in what way cognitive reserve/brain reserve and depression interact and are linked to regional atrophy in early stage AD. Methods: Depression was evaluated with the Patient Health Questionnaire-9 in 90 patients with early AD, and a cutoff of ≥ 5 was used to separate depressed (n = 44) from non-depressed (n = 46) patients. Each group was further stratified into high/low cognitive reserve/brain reserve. Cognitive reserve was calculated using years of education as proxy, while normalized parenchymal volumes were used to estimate brain reserve. Voxel-based morphometry was carried out to extract and analyze gray-matter maps. 2 × 2 ANCOVAs were run to test the effect of the reserve-by-depression interaction on gray matter. Age and hippocampal ratio were used as covariates. Composite indices of major cognitive domains were also analyzed with comparable models. Results: No reserve-by-depression interaction was found in the analytical models of gray matter. Depression was associated with less gray matter volume in the cerebellum and parahippocampal gyrus. The brain reserve-by-depression interaction was a significant predictor of executive functioning. Among those with high brain reserve, depressed patients had poorer executive skills. No significant results were found in association with cognitive reserve. Conclusion: These findings suggest that brain reserve may modulate the association between neurodegeneration and depression in patients with MCI and dementia of the AD type, influencing in particular executive functioning.