The Effect of Vascular Risk Factors on the Efficacy of Rivastigmine Patch and Capsule Treatment in Alzheimer's Disease

Background: Vascular risk factors (VRF) may influence response to rivastigmine in Alzheimer’s disease (AD). Methods: AD patients who participated in a randomized, double-blind, placebo-controlled trial of rivastigmine patch and capsule treatment were stratified by baseline VRF status. Treatment response was evaluated using the AD Assessment Scale-cognitive subscale (ADAS-cog), AD Cooperative Study-Clinical Global Impression of Change (ADCS-CGIC) and the AD Cooperative Study-Activities of Daily Living (ADCS-ADL) scale. Results: ADAS-cog scores significantly improved in all rivastigmine-treated patients (p Conclusion: VRF may influence AD progression and response to rivastigmine

[Accepted Manuscript] Presymptomatic atrophy in autosomal dominant Alzheimer's disease: A serial MRI study.

Identifying at what point atrophy rates first change in Alzheimer's disease is important for informing design of presymptomatic trials. Serial T1-weighed magnetic resonance imaging scans of 94 participants (28 noncarriers, 66 carriers) from the Dominantly Inherited Alzheimer Network were used to measure brain, ventricular, and hippocampal atrophy rates. For each structure, nonlinear mixed-effects models estimated the change-points when atrophy rates deviate from normal and the rates of change before and after this point. Atrophy increased after the change-point, which occurred 1-1.5 years (assuming a single step change in atrophy rate) or 3-8 years (assuming gradual acceleration of atrophy) before expected symptom onset. At expected symptom onset, estimated atrophy rates were at least 3.6 times than those before the change-point. Atrophy rates are pathologically increased up to seven years before "expected onset". During this period, atrophy rates may be useful for inclusion and tracking of disease progression

Comprehensive analysis of epigenetic clocks reveals associations between disproportionate biological ageing and hippocampal volume

The concept of age acceleration, the difference between biological age and chronological age, is of growing interest, particularly with respect to age-related disorders, such as Alzheimer’s Disease (AD). Whilst studies have reported associations with AD risk and related phenotypes, there remains a lack of consensus on these associations. Here we aimed to comprehensively investigate the relationship between five recognised measures of age acceleration, based on DNA methylation patterns (DNAm age), and cross-sectional and longitudinal cognition and AD-related neuroimaging phenotypes (volumetric MRI and Amyloid-β PET) in the Australian Imaging, Biomarkers and Lifestyle (AIBL) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Significant associations were observed between age acceleration using the Hannum epigenetic clock and cross-sectional hippocampal volume in AIBL and replicated in ADNI. In AIBL, several other findings were observed cross-sectionally, including a significant association between hippocampal volume and the Hannum and Phenoage epigenetic clocks. Further, significant associations were also observed between hippocampal volume and the Zhang and Phenoage epigenetic clocks within Amyloid-β positive individuals. However, these were not validated within the ADNI cohort. No associations between age acceleration and other Alzheimer’s disease-related phenotypes, including measures of cognition or brain Amyloid-β burden, were observed, and there was no association with longitudinal change in any phenotype. This study presents a link between age acceleration, as determined using DNA methylation, and hippocampal volume that was statistically significant across two highly characterised cohorts. The results presented in this study contribute to a growing literature that supports the role of epigenetic modifications in ageing and AD-related phenotypes

Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference

The heterogeneity of neurodegenerative diseases is a key confound to disease understanding and treatment development, as study cohorts typically include multiple phenotypes on distinct disease trajectories. Here we introduce a machine-learning technique\u2014Subtype and Stage Inference (SuStaIn)\u2014able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available cross-sectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes; further the technique reveals within-genotype heterogeneity. In Alzheimer\u2019s disease, SuStaIn uncovers three subtypes, uniquely characterising their temporal complexity. SuStaIn provides fine-grained patient stratification, which substantially enhances the ability to predict conversion between diagnostic categories over standard models that ignore subtype (p = 7.18 7 10 124 ) or temporal stage (p = 3.96 7 10 125 ). SuStaIn offers new promise for enabling disease subtype discovery and precision medicine

An integrated multi-study analysis of intra-subject variability in cerebrospinal fluid amyloid-beta concentrations collected by lumbar puncture and indwelling lumbar catheter

Contains fulltext : 154021.pdf (publisher's version ) (Open Access)INTRODUCTION: Amyloid-beta (Abeta) has been investigated as a diagnostic biomarker and therapeutic drug target. Recent studies found that cerebrospinal fluid (CSF) Abeta fluctuates over time, including as a diurnal pattern, and increases in absolute concentration with serial collection. It is currently unknown what effect differences in CSF collection methodology have on Abeta variability. In this study, we sought to determine the effect of different collection methodologies on the stability of CSF Abeta concentrations over time. METHODS: Grouped analysis of CSF Abeta levels from multiple industry and academic groups collected by either lumbar puncture (n=83) or indwelling lumbar catheter (n=178). Participants were either placebo or untreated subjects from clinical drug trials or observational studies. Participants had CSF collected by lumbar puncture or lumbar catheter for quantitation of Abeta concentration by enzyme linked immunosorbent assay. Data from all sponsors was converted to percent of the mean for Abeta40 and Abeta42 for comparison. Repeated measures analysis of variance was performed to assess for factors affecting the linear rise of Abeta concentrations over time. RESULTS: Analysis of studies collecting CSF via lumbar catheter revealed tremendous inter-subject variability of Abeta40 and Abeta42 as well as an Abeta diurnal pattern in all of the sponsors' studies. In contrast, Abeta concentrations from CSF samples collected at two time points by lumbar puncture showed no significant differences. Repeated measures analysis of variance found that only time and draw frequency were significantly associated with the slope of linear rise in Abeta40 and Abeta42 concentrations during the first 6 hours of collection. CONCLUSIONS: Based on our findings, we recommend minimizing the frequency of CSF draws in studies measuring Abeta levels and keeping the frequency standardized between experimental groups. The Abeta diurnal pattern was noted in all sponsors' studies and was not an artifact of study design. Averaging Abeta concentrations at each time point is recommended to minimize the effect of individual variability. Indwelling lumbar catheters are an invaluable research tool for following changes in CSF Abeta over 24-48 hours, but factors affecting Abeta concentration such as linear rise and diurnal variation need to be accounted for in planning study designs