Verbal fluency and intrinsic brain activity in Alzheimer's disease

Acute cognitive impairment after traumatic brain injury predicts the occurrence of brain atrophy patterns similar to those observed in Alzheimer's disease

Traumatic brain injuries (TBIs) are often followed by persistent structural brain alterations and by cognitive sequalae, including memory deficits, reduced neural processing speed, impaired social function, and decision-making difficulties. Although mild TBI (mTBI) is a risk factor for Alzheimer's disease (AD), the extent to which these conditions share patterns of macroscale neurodegeneration has not been quantified. Comparing such patterns can not only reveal how the neurodegenerative trajectories of TBI and AD are similar, but may also identify brain atrophy features which can be leveraged to prognosticate AD risk after TBI. The primary aim of this study is to systematically map how TBI affects white matter (WM) and gray matter (GM) properties in AD-analogous patterns. Our findings identify substantial similarities in the regional macroscale neurodegeneration patterns associated with mTBI and AD. In cerebral GM, such similarities are most extensive in brain areas involved in memory and executive function, such as the temporal poles and orbitofrontal cortices, respectively. Our results indicate that the spatial pattern of cerebral WM degradation observed in AD is broadly similar to the pattern of diffuse axonal injury observed in TBI, which frequently affects WM structures like the fornix, corpus callosum, and corona radiata. Using machine learning, we find that the severity of AD-like brain changes observed during the chronic stage of mTBI can be accurately prognosticated based on acute assessments of post-traumatic mild cognitive impairment. These findings suggest that acute post-traumatic cognitive impairment predicts the magnitude of AD-like brain atrophy, which is itself associated with AD risk.

Alteration of functional connectivity in patients with Alzheimer's disease revealed by resting-state functional magnetic resonance imaging

The main symptom of patients with Alzheimer’s disease is cognitive dysfunction. Alzheimer’s disease is mainly diagnosed based on changes in brain structure. Functional connectivity reflects the synchrony of functional activities between non-adjacent brain regions, and changes in functional connectivity appear earlier than those in brain structure. In this study, we detected resting-state functional connectivity changes in patients with Alzheimer’s disease to provide reference evidence for disease prediction. Functional magnetic resonance imaging data from patients with Alzheimer’s disease were used to show whether particular white and gray matter areas had certain functional connectivity patterns and if these patterns changed with disease severity. In nine white and corresponding gray matter regions, correlations of normal cognition, early mild cognitive impairment, and late mild cognitive impairment with blood oxygen level-dependent signal time series were detected. Average correlation coefficient analysis indicated functional connectivity patterns between white and gray matter in the resting state of patients with Alzheimer’s disease. Functional connectivity pattern variation correlated with disease severity, with some regions having relatively strong or weak correlations. We found that the correlation coefficients of five regions were 0.3–0.5 in patients with normal cognition and 0–0.2 in those developing Alzheimer’s disease. Moreover, in the other four regions, the range increased to 0.45–0.7 with increasing cognitive impairment. In some white and gray matter areas, there were specific connectivity patterns. Changes in regional white and gray matter connectivity patterns may be used to predict Alzheimer’s disease; however, detailed information on specific connectivity patterns is needed. All study data were obtained from the Alzheimer’s Disease Neuroimaging Initiative Library of the Image and Data Archive Database.

Role of neurodevelopment involved genes in psychiatric comorbidities and modulation of inflammatory processes in Alzheimer's disease

INTRODUCTION

With the increase of the population's average age, Alzheimer's disease (AD) is becoming one of the most disabling diseases worldwide. Recently, neurodevelopment processes have been involved in the AD etiopathogenesis. Genetic studies in this field could contribute to our knowledge and suggest new molecular targets for possible treatments.

METHODS

Our primary aim was to investigate the associations among single nucleotide polymorphisms (SNPs) within neurodevelopment related genes (BDNF, ST8SIA2, C15orf32, NCAPG2, ESYT2, WDR60, LOC154822, VIPR2, GSK3B, NR1I2, ZNF804A, SP4) and AD. A number of exploratory analyses was also performed to evaluate the associations with the presence of behavioral and psychiatric symptoms of dementia (BPSD), as well as with variations in hematological parameters. Two independent samples were investigated, one of 228 Greek subjects and one sample of 229 Italian subjects, including 156Alzheimer's Disease patients CE patients and 301 healthy controls. All patients were affected by late onset AD (LOAD).

RESULTS

None of the analyzed SNPs was associated with AD in our samples. In the exploratory analyses, several genetic variants were associated with inflammation parameters in the Greek sample and in the merged one, suggesting a relationship among these genes and the modulation of inflammation and the immune response. Other exploratory analyses showed associations among several SNPs and psychiatric symptomatology in the Greek sample, suggesting a possible modulation of these variants on psychiatric comorbidities in AD.

CONCLUSIONS

Although we failed to find a direct relationship between AD and the genetic variants investigated, possible connections with inflammation and psychiatric symptoms were suggested.