Disease Progression Modeling and Prediction through Random Effect Gaussian Processes and Time Transformation

The development of statistical approaches for the joint modelling of the temporal changes of imaging, biochemical, and clinical biomarkers is of paramount importance for improving the understanding of neurodegenerative disorders, and for providing a reference for the prediction and quantification of the pathology in unseen individuals. Nonetheless, the use of disease progression models for probabilistic predictions still requires investigation, for example for accounting for missing observations in clinical data, and for accurate uncertainty quantification. We tackle this problem by proposing a novel Gaussian process-based method for the joint modeling of imaging and clinical biomarker progressions from time series of individual observations. The model is formulated to account for individual random effects and time reparameterization, allowing non-parametric estimates of the biomarker evolution, as well as high flexibility in specifying correlation structure, and time transformation models. Thanks to the Bayesian formulation, the model naturally accounts for missing data, and allows for uncertainty quantification in the estimate of evolutions, as well as for probabilistic prediction of disease staging in unseen patients. The experimental results show that the proposed model provides a biologically plausible description of the evolution of Alzheimer's pathology across the whole disease time-span as well as remarkable predictive performance when tested on a large clinical cohort with missing observations.Comment: 13 pages, 2 figure

Comparison of the effects of transdermal and oral rivastigmine on cognitive function and EEG markers in patients with Alzheimer’s disease

Background: Alzheimer's disease (AD) is the most common cause of dementia in older patients. Rivastigmine (RV, Exelon®, Novartis), a reversible cholinesterase inhibitor, improves clinical manifestations of AD and may enhance ACh-modulated electroencephalogram (EEG) alpha frequency. This pilot study aimed to determine the effects of two formulations of RV (transdermal patch [TV-RDP] and oral capsules [TV-CP]) on alpha frequency, in particular the posterior dominant rhythm, and cognitive function (assessed by the Mini-Mental State Examination [MMSE]) in patients with AD.Methods: Subjects with AD were assigned to receive either RV-TDP 10 cm2 or RV-CP 12 mg/day. All patients underwent EEG recordings at the beginning and end of the 18-month study period using P3, P4, O1 and O2 electrodes, each at high (10.5–13.0 Hz) and low (8.0–10.5 Hz) frequency. MMSE scores were determined at the start of the study (T0) and at three successive 6-month intervals (T1, T2 and T3).Results: RV-TDP administration (n=10) maintained cognitive function as evidenced by stable MMSE scores from baseline to 18 months (21.07 ± 2.4 to 21.2 ± 3.1) compared with a decrease in MMSE score with RV-CP (n=10) over 18 months (18.3 ± 3.6 to 13.6 ± 5.06 [adjusted for covariates p=0.006]). MMSE scores were significantly different between treatment groups from 6 months (p=0.04). RV-TDP also increased the spectral power of alpha waves in the posterior region measured with electrode P3 in a significantly great percentage of patients than TV-CP from baseline to 18 months; 80% versus 30%, respectively (p=0.025 [χ2 test]).Conclusion: RV-TDP was associated with a greater proportion of patients with increased posterior region alpha wave spectral power and significantly higher cognitive function at 18 months, compared with RV-CP treatment. Our findings suggest that RV-TDP provides an effective long-term management option in patients with AD compared with oral RV-CP. This study is a pilot, open-label study with

Anatomical Substrate and Scalp EEG Markers are Correlated in Subjects with Cognitive Impairment and Alzheimer's Disease

Dementia is a syndromic diagnosis, encompassing various stage of severity and different anatomo-physiological substrates. The hippocampus is one of the first and most affected brain regions affected by both Alzheimer's disease (AD) and mild cognitive impairment (MCI). Moreover, chronic cerebrovascular disease (CVD) is one of the major risk factor for developing dementia. Recent studies have demonstrated different relationship between the anatomical substrate and scalp electroencephalography (EEG) markers. Indeed, modifications of EEG rhythmicity is not proportional to the hippocampal atrophy, whereas changes in EEG activity are directly proportional to the load of subcortical CVD. The computation of the EEG spectral power and the analysis of the functional coupling of brain areas, through linear coherence, are two of the most known processing methods in EEG research. Two specific EEG markers, theta/gamma and alpha3/alpha2 frequency ratio have been reliable associated to the atrophy of amygdalo–hippocampal complex. Moreover, theta/gamma ratio has been related to MCI conversion in dementia and alpha3/alpha2 ratio has been specifically related to MCI conversion in AD. The functional coupling of brain areas is also modulated by hippocampal atrophy. In the MCI subjects, hippocampal atrophy is linked to an increase of interhemispheric coherence seen on frontal and temporal regions whereas subcortical CVD is linked to a decrease of coherence in fronto-parietal regions. In the present study the most significant results of recent studies on correlation between scalp EEG, cognitive decline, and anatomical substrate have been reviewed, with particular attention to the relationships between EEG changes and hippocampal atrophy. The following review is not intended to provide a comprehensive summary of the literature. Rather it identifies and discusses selected studies that are designed to find the specific correlation between scalp EEG markers and anatomo-pathological substrate. The principal aim is to propose a plausible neurophysiological theoretical model of the cognitive decline as mirrored by both structural and functional tools of research

The heterogeneity of subjective cognitive decline: A data‐driven approach on a population‐based sample

AbstractBackgroundSubjective Cognitive Decline (SCD) has been largely studied as a risk condition for cognitive decline, mainly in memory clinics or research settings. SCD samples are highly heterogeneous, including both individuals with early Alzheimer's disease and others with psychological vulnerabilities and/or physical comorbidity. Aims: identify distinct SCD subgroups in a population‐based sample of cognitively normal (CN) older adults; explore cross‐sectional differences among SCD subgroups and controls (noSCD); investigate the effect of SCD status on 8‐year cognitive changes.MethodThe InveCe.Ab population‐based study (NCT01345110) enrolled people aged 70‐74 years residing in Abbiategrasso (Milan). Participants underwent multidimensional assessment (blood sampling, lifestyle interview, medical and neuropsychological assessment) at baseline (Nov 2009‐Jan 2011) and after 2, 4 and 8 years. CN participants at baseline completing at least 60% of neuropsychological assessment were included in the present investigation. Those reporting any cognitive complaints to the geriatrician were classified as SCD. Hierarchical cluster analysis was conducted in SCD including 9 relevant variables: education, depressive symptoms, cardiovascular risk, comorbidity, subjective cognitive complaints (numbers) and 4 neuropsychological scores measuring memory, executive functions, visuospatial abilities and language respectively. Cross‐sectional differences among the SCD subgroups identified and noSCD were performed using Kruskal‐Wallis test. Longitudinal cognitive changes according to baseline SCD status (noSCD, SCD subgroups) were estimated using linear mixed models, adjusted for age and education.ResultTwo clusters were identified in SCD. Table 1 shows cross‐sectional results. SCD1 (N=141), compared to SCD2 and CN, were less educated, have higher comorbidities, depressive symptoms and SCD complaints. SCD1 showed lower performances on executive and visuospatial functions, while SCD2, despite being healthier and more educated, showed reduced episodic memory. At longitudinal analysis, all cognitive functions declined due to aging (Time; p<.001). SCD2 displayed a steeper worsening on executive function (Group*Time; p<.001).ConclusionThe presence of SCD at the population level could be informative of future cognitive decline when reported by individuals with higher education. Future studies are needed to clarify the meaning of this condition in the aged population, in order to identify early those at increased risk of actual cognitive decline

Electroencephalographic Rhythms in Alzheimer's Disease

Physiological brain aging is characterized by synapses loss and neurodegeneration that slowly lead to an age-related decline of cognition. Neural/synaptic redundancy and plastic remodelling of brain networking, also due to mental and physical training, promotes maintenance of brain activity in healthy elderly subjects for everyday life and good social behaviour and intellectual capabilities. However, age is the major risk factor for most common neurodegenerative disorders that impact on cognition, like Alzheimer's disease (AD). Brain electromagnetic activity is a feature of neuronal network function in various brain regions. Modern neurophysiological techniques, such as electroencephalography (EEG) and event-related potentials (ERPs), are useful tools in the investigation of brain cognitive function in normal and pathological aging with an excellent time resolution. These techniques can index normal and abnormal brain aging analysis of corticocortical connectivity and neuronal synchronization of rhythmic oscillations at various frequencies. The present review suggests that discrimination between physiological and pathological brain aging clearly emerges at the group level, with suggested applications also at the level of single individual. The possibility of combining the use of EEG together with biological/neuropsychological markers and structural/functional imaging is promising for a low-cost, non-invasive, and widely available assessment of groups of individuals at-risk

P1‐245: Mapping local structural hippocampal changes in Alzheimer's disease and normal aging on MR imaging at 3T

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Resting State Cortical Electroencephalographic Rhythms in Alzheimer`s Disease

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Effect of a probiotic administration on inflammatory profile and clinical features in patients with Alzheimer's disease

AbstractBackgroundIncreasing evidence shows that the gut microbiota (GMB) may affect the inflammatory status and influence the pathogenesis of several brain disorders, including Alzheimer's Disease. Moreover, it has been suggested that probiotics may have potential beneficial effects on the immune system via microbiome composition, influencing in turn also cognitive performances.MethodSixty‐two old subjects with normal cognitive performance and 37 AD patients were recruited and stool and blood samples were collected. Moreover, the group of AD patients received a probiotic administration for three months and stool and blood samples were collected again at the end of the treatment. Plasma levels of a panel of pro‐inflammatory cytokines were measured by using the High Sensitivity 9‐Plex Human ProcartaPlex™ Panel (IFN‐ϒ, IL‐1b, IL‐2, IL‐4, IL‐6, IL‐10, IL‐12p70, IL‐17A and TNFα, Thermo Fisher Scientific) on Luminex Bio‐Plex® 200™ system. Moreover, we also measured the plasma levels of C‐Reactive Protein (CRP) using the CRP Human Instant ELISA Kit (Thermo Fisher Scientific). Bacterial composition of fecal samples was inferred using 16s sequencing; the levels of the short chain fatty acids acetate, propionate, valerate and butyrate were measured by mass spectrometry and adhesion molecules by FACS.ResultWe found higher levels of the pro‐inflammatory cytokines IL‐6, IFN gamma, TNF‐alpha, IL‐1beta, and il12p70 and of IL‐2 and lower levels of the anti‐inflammatory cytokine IL‐10 in AD patients as compared to control subjects (all p<0.05). Moreover, we found a positive correlation between MMSE score and the levels of pro‐inflammatory cytokine IL‐6 (p=0.03, r=0.56). Interestingly, the three months treatment with the probiotic composition was able to significantly reduce the level of IL‐6 (p=0.03) and increase the levels of IL‐10 (p=0.023). Bioinformatic analyses on the 16s sequencing data as well as on the SCFAs and endothelial markers are ongoing.ConclusionInflammatory status is higher in AD patients as compared to control subjects and it correlates with cognitive performances. Interestingly probiotic composition is able to push down the inflammatory status in patients, possibly via changes in microbiome composition. Probiotics may be beneficial in delaying neurodegeneration and cognitive deficits in subjects at risk of developing Alzheimer Disease