Genetic and environmental factors associated with the risk of cognitive decline and dementia

AD is the most common age related neurodegenerative disease in the industrialized world. Clinically AD is defined as a progressing decline of cognitive functions. Neuropathologically, AD is characterized by the aggregation of b-amyloid (Ab) peptide in the form of extracellular senile plaques, and hyperphosphorlylated tau protein in the form of intracellular neurofibrillary tangles. These neuropathological hallmarks are often accompanied by abundant microvascular damage and pronounced inflammation of the affected brain regions. In this thesis we investigated several aspects of AD focusing on the genetic aspect. We confirmed that Alpha 1 antichymotrypsin (ACT), an acute phase protein, was associated to AD subjects, being plasma levels higher in AD cases than controls. In addition, in a GWA study we demonstrated that two different gene, Clusterin and CR1 were strongly associated to AD. A single gene association not explain such a complex disease like AD. The goal should be to created a network of genetic, phenotypic and clinical data associated to AD. We used a new algorithm, the ANNs, aimed to map variables and search for connectivity among variables. We found specific variables associated to AD like cholesterol levels, the presence of variation in HMGCR enzyme and the age. Other factors such as the BMI, the amount of HDL and blood folate levels were also associated with AD. Pathogen infections, above all viral infections, have been previously associated to AD. The hypothesis suggests that virus and in particular herpes virus could enter the brain when an individual becomes older, perhaps because of a decline in the immune system. Our new hypothesis is that the presence of SNPs in our GWA gene study results in a genetic signature that might affect individual brain susceptibility to infection by herpes virus family during aging.

Interaction between APOE4 genotype and environmental risk factors in Alzheimer's disease

Alzheimer's disease (AD) is probably caused by both genetic and environmental risk factors. The major genetic risk factor is the E4 variant of apolipoprotein E gene called apoE4. Several risk factors for developing AD have been identified including lifestyle, such as dietary habits. The mechanisms behind the AD pathogenesis and the onset of cognitive decline in the AD brain are presently unknown. In this study we wanted to characterize the effects of the interaction between environmental risk factors and apoE genotype on neurodegeneration processes, with particular focus on behavioural studies and neurodegenerative processes at molecular level. Towards this aim, we used 6 months-old apoE4 and apoE3 Target Replacement (TR) mice fed on different diets (high intake of cholesterol and high intake of carbohydrates). These mice were evaluated for learning and memory deficits in spatial reference (Morris Water Maze (MWM)) and contextual learning (Passive Avoidance) tasks, which involve the hippocampus and the amygdala, respectively. From these behavioural studies we found that the initial cognitive impairments manifested as a retention deficit in apoE4 mice fed on high carbohydrate diet. Thus, the genetic risk factor apoE4 genotype associated with a high carbohydrate diet seems to affect cognitive functions in young mice, corroborating the theory that the combination of genetic and environmental risk factors greatly increases the risk of developing AD and leads to an earlier onset of cognitive deficits. The cellular and molecular bases of the cognitive decline in AD are largely unknown. In order to determine the molecular changes for the onset of the early cognitive impairment observed in the behavioural studies, we performed molecular studies, with particular focus on synaptic integrity and Tau phosphorylation. The most relevant finding of our molecular studies showed a significant decrease of Brain-derived Neurotrophic Factor (BDNF) in apoE4 mice fed on high carbohydrate diet. Our results may suggest that BDNF decrease found in apoE4 HS mice could be involved in the earliest impairment in long-term reference memory observed in behavioural studies. The second aim of this thesis was to study possible involvement of leptin in AD. There is growing evidence that leptin has neuroprotective properties in the Central Nervous System (CNS). Recent evidence has shown that leptin and its receptors are widespread in the CNS and may provide neuronal survival signals. However, there are still numerous questions, regarding the molecular mechanism by which leptin acts, that remain unanswered. Thus, given to the importance of the involvement of leptin in AD, we wanted to clarify the function of leptin in the pathogenesis of AD and to investigate if apoE genotype affect leptin levels through studies in vitro, in mice and in human. Our findings suggest that apoE4 TR mice showed an increase of leptin in the brain. Leptin levels are also increased in the cerebral spinal fluid of AD patients and apoE4 carriers with AD have higher levels of leptin than apoE3 carriers. Moreover, leptin seems to be expressed by reactive glial cells in AD brains. In vitro, ApoE4 together with Amyloid beta increases leptin production by microglia and astrocytes. Taken together, all these findings suggest that leptin replacement might not be a good strategy for AD therapy. Our results show that high leptin levels were found in AD brains. These findings suggest that, as high leptin levels do not promote satiety in obese individuals, it might be possible that they do not promote neuroprotection in AD patients. Therefore, we hypothesized that AD brain could suffer from leptin resistance. Further studies will be critical to determine whether or not the central leptin resistance in SNC could affect its potential neuroprotective effects.

Valutazione dei disturbi cognitivi nei pazienti sottoposti a Rivascolarizzazione Carotidea (Endoarterectomia vs Stenting) mediante dosaggio di marker di danno neuronale, Mini Mental State Examination e Risonanza Magnetica

Scopo del nostro studio è quello di valutare i disturbi cognitivi in relazione al tasso di microembolia cerebrale in due gruppi di pazienti trattati per lesione carotidea asintomatica con endoarterectomia (CEA) o stenting (CAS). Comparando le due metodiche mediante l’utilizzo di risonanza magnetica in diffusione (DW-MRI), neuromarkers (NSE e S100β) e test neuropsicometrici. MATERIALE E METODI: 60 pazienti sono stati sottoposti a rivascolarizzazione carotidea (CEA n=32 e CAS n=28). Sono stati tutti valutati con DW-MRI e Mini-Mental State Examination (MMSE) test nel preoperatorio, a 24 ore, a 6 ed a 12 mesi dall’intervento. In tutti sono stati dosati i livelli sierici di NSE e S100β mediante 5 prelievi seriati nel tempo, quello basale nel preoperatorio, l’ultimo a 24 ore. L’ananlisi statistica è stata effettuata con test t di Student per confronti multipli per valori continui e con test χ2 quadro e Fisher per le variabili categoriche. Significatività P <0,05. RISULTATI: Non vi è stato alcun decesso. Un paziente del gruppo CAS ha presentato un ictus ischemico. In 6 pazienti CAS ed in 1 paziente CEA si sono osservate nuove lesioni subcliniche alla RMN-DWI post-operatoria (21,4% vs 3% p=0,03). Nel gruppo CAS le nuove lesioni presenti alla RMN sono risultate significativamente associate ad un declino del punteggio del MMSE (p=0,001). L’analisi dei livelli di NSE e S100β ha mostrato un significativo aumento a 24 ore nei pazienti CAS (P = .02). A 12 mesi i pazienti che avevano presentato nuove lesioni ischemiche nel post-operatorio hanno mostrato minor punteggio al MMSE, non statisticamente significativo. CONCLUSIONI: I neuromarkers in combinazione con MMSE e RMN-DWI possono essere utilizzati nella valutazione del declino cognitivo correlato a lesioni silenti nell’immediato postoperatorio di rivascolarizzazione carotidea. Quest’ultime dovrebbero essere valutate quindi non solo rispetto al tasso di mortalità e ictus, ma anche rispetto al tasso di microembolia.

Human herpes virus and Alzheimer’s disease

Alzheimer’s disease (AD) is a chronic and progressive neurodegenerative disorder and according to the WHO it is estimated that 36 millions of people worldwide currently suffer from AD. Genetic and environmental factors interact in a complex interplay that might affect pathogenic mechanisms leading to age-related neurodegeneration. The hypothesis is that the presence of allelic polymorphisms in selected genes affecting individual brain susceptibility to infection by the herpes virus family during aging, may contribute to neuronal loss, inflammation and amyloid deposition. Herpes virus family show features relevant to AD, since they infect a large proportion of human population, develop a latent form persisting for several years, are difficult to eliminate by immune responses especially when latency has been established and are able to infect neurons. The association between AD and herpes viruses infection has been investigated. In particular the investigation focused on CMV, EBV and HHV-6 in DNA samples from peripheral blood of a large cohort of patients with clinical diagnosis of AD and age matched CTR, from a longitudinal population study, and DNA samples from brain tissue of patients with neuropathological diagnosis of definitive AD. An association between the presence of EBV and HHV-6 DNA from PBL positivity with the cognitive deterioration and progression to AD has been focused. Moreover, IgG plasma levels in CTR and AD to these viruses were tested. CMV and EBV IgG plasma levels were higher in elderly subjects that developed clinical AD at the end of the five year follow up. Our findings support the notion that persistent cycles of latency and reactivation of herpes viruses may contribute to impair systemic immune response and induce altered inflammatory process that in turn affect cognitive decline during aging.

Fractal descriptors for quantifying brain complexity in MRI

Magnetic Resonance Imaging (MRI) is the in vivo technique most commonly employed to characterize changes in brain structures. The conventional MRI-derived morphological indices are able to capture only partial aspects of brain structural complexity. Fractal geometry and its most popular index, the fractal dimension (FD), can characterize self-similar structures including grey matter (GM) and white matter (WM). Previous literature shows the need for a definition of the so-called fractal scaling window, within which each structure manifests self-similarity. This justifies the existence of fractal properties and confirms Mandelbrot’s assertion that "fractals are not a panacea; they are not everywhere". In this work, we propose a new approach to automatically determine the fractal scaling window, computing two new fractal descriptors, i.e., the minimal and maximal fractal scales (mfs and Mfs). Our method was implemented in a software package, validated on phantoms and applied on large datasets of structural MR images. We demonstrated that the FD is a useful marker of morphological complexity changes that occurred during brain development and aging and, using ultra-high magnetic field (7T) examinations, we showed that the cerebral GM has fractal properties also below the spatial scale of 1 mm. We applied our methodology in two neurological diseases. We observed the reduction of the brain structural complexity in SCA2 patients and, using a machine learning approach, proved that the cerebral WM FD is a consistent feature in predicting cognitive decline in patients with small vessel disease and mild cognitive impairment. Finally, we showed that the FD of the WM skeletons derived from diffusion MRI provides complementary information to those obtained from the FD of the WM general structure in T1-weighted images. In conclusion, the fractal descriptors of structural brain complexity are candidate biomarkers to detect subtle morphological changes during development, aging and in neurological diseases.

Development and characterization of deep learning techniques for neuroimaging data

Deep learning methods are extremely promising machine learning tools to analyze neuroimaging data. However, their potential use in clinical settings is limited because of the existing challenges of applying these methods to neuroimaging data. In this study, first a data leakage type caused by slice-level data split that is introduced during training and validation of a 2D CNN is surveyed and a quantitative assessment of the model’s performance overestimation is presented. Second, an interpretable, leakage-fee deep learning software written in a python language with a wide range of options has been developed to conduct both classification and regression analysis. The software was applied to the study of mild cognitive impairment (MCI) in patients with small vessel disease (SVD) using multi-parametric MRI data where the cognitive performance of 58 patients measured by five neuropsychological tests is predicted using a multi-input CNN model taking brain image and demographic data. Each of the cognitive test scores was predicted using different MRI-derived features. As MCI due to SVD has been hypothesized to be the effect of white matter damage, DTI-derived features MD and FA produced the best prediction outcome of the TMT-A score which is consistent with the existing literature. In a second study, an interpretable deep learning system aimed at 1) classifying Alzheimer disease and healthy subjects 2) examining the neural correlates of the disease that causes a cognitive decline in AD patients using CNN visualization tools and 3) highlighting the potential of interpretability techniques to capture a biased deep learning model is developed. Structural magnetic resonance imaging (MRI) data of 200 subjects was used by the proposed CNN model which was trained using a transfer learning-based approach producing a balanced accuracy of 71.6%. Brain regions in the frontal and parietal lobe showing the cerebral cortex atrophy were highlighted by the visualization tools.

Design, synthesis and biological evaluation of dual inhibitors of GSK-3B and Fyn kinases for the study of inflammatory pathways in neurodegenerative diseases

Neuroinflammation represents a key hallmark of neurodegenerative diseases and is the result of a complex network of signaling cascades within microglial cells. A positive feedback loop exists between inflammation, microglia activation and protein misfolding processes, that, together with oxidative stress and excitotoxicity, lead to neuronal degeneration. Therefore, targeting this vicious cycle can be beneficial for mitigating neurodegeneration and cognitive decline in central nervous system disorders. At molecular level, GSK-3B and Fyn kinases play a crucial role in microglia activation and their deregulation has been associated to many neurodegenerative diseases. Thus, we envisioned their combined targeting as an effective approach to disrupt this toxic loop. Specifically in this project, a hit compound, based on a 7-azaindole-3-aminothiazole structure, was first identified in a virtual screening campaign, and displayed a weak dual inhibitory activity on GSK-3B and Fyn, unbalanced towards the former. Then, in a commitment to uncover the structural features required for modulating the activity on the two targets, we systematically manipulated this compound by inserting various substitution patterns in different positions. The most potent compounds obtained were advanced to deeper investigations to test their ability of tackling the inflammatory burden also in cellular systems and to unveil their binding modes within the catalytic pocket. The new class of molecules synthesized emerged as a valuable tool to deepen our understanding of the complex network governing the inflammatory events in neurodegenerative disorders.

Sonno e funzioni cognitive: ruolo della microstruttura del sonno NREM

STUDY OBJECTIVE: Cyclic Alternating Pattern (CAP) is a fluctuation of the arousal level during NREM sleep and consists of the alternation between two phases: phase A (divided into three subtypes A1, A2, and A3) and phase B. A1 is thought to be generated by the frontal cortex and is characterized by the presence of K complexes or delta bursts; additionally, CAP A1 seems to have a role in the involvement of sleep slow wave activity in cognitive processing. Our hypothesis was that an overall CAP rate would have a negative influence on cognitive performance due to excessive fluctuation of the arousal level during NREM sleep. However, we also predicted that CAP A1 would be positively correlated with cognitive functions, especially those related to frontal lobe functioning. For this reason, the objective of our study was to correlate objective sleep parameters with cognitive behavioral measures in normal healthy adults. METHODS: 8 subjects (4 males; 4 females; mean age 27.75 years, range 2334) were recruited for this study. Two nocturnal polysomnography (night 2 and 3 = N2 and N3) were carried out after a night of adaptation. A series of neuropsychological tests were performed by the subjects in the morning and afternoon of the second day (D2am; D2pm) and in the morning of the third day (D3am). Raw scores from the neuropsychological tests were used as dependent variables in the statistical analysis of the results. RESULTS: We computed a series of partial correlations between sleep microstructure parameters (CAP, A1, A2 and A3 rate) and a number of indices of cognitive functioning. CAP rate was positively correlated with visuospatial working memory (Corsi block test), Trial Making Test Part A (planning and motor sequencing) and the retention of words from the Hopkins Verbal Learning Test (HVLT). Conversely, CAP was negatively correlated with visuospatial fluency (Ruff Figure Fluency Test). CAP A1 were correlated with many of the tests of neuropsychological functioning, such as verbal fluency (as measured by the COWAT), working memory (as measured by the Digit Span – Backward test), and both delay recall and retention of the words from the HVLT. The same parameters were found to be negatively correlated with CAP A2 subtypes. CAP 3 were negatively correlated with the Trial Making Test Parts A and B. DISCUSSION: To our knowledge this is the first study indicating a role of CAP A1 and A2 on behavioral cognitive performance of healthy adults. The results suggest that high rate of CAP A1 might be related to an improvement whereas high rate of CAP A2 to a decline of cognitive functions. Further studies need to be done to better determine the role of the overall CAP rate and CAP A3 on cognitive behavioral performances.