Long-term surveillance of SUDEP in drug-resistant epilepsy patients treated with VNS therapy.

Limited data are available regarding the evolution over time of the rate of sudden unexpected death in epilepsy patients (SUDEP) in drug-resistant epilepsy. The objective is to analyze a database of 40 443 patients with epilepsy implanted with vagus nerve stimulation (VNS) therapy in the United States (from 1988 to 2012) and assess whether SUDEP rates decrease during the postimplantation follow-up period. Patient vital status was ascertained using the Centers for Disease Control and Prevention's National Death Index (NDI). An expert panel adjudicated classification of cause of deaths as SUDEP based on NDI data and available narrative descriptions of deaths. We tested the hypothesis that SUDEP rates decrease with time using the Mann-Kendall nonparametric trend test and by comparing SUDEP rates of the first 2 years of follow-up (years 1-2) to longer follow-up (years 3-10). Our cohort included 277 661 person-years of follow-up and 3689 deaths, including 632 SUDEP. Primary analysis demonstrated a significant decrease in age-adjusted SUDEP rate during follow-up (S = -27 P = .008), with rates of 2.47/1000 for years 1-2 and 1.68/1000 for years 3-10 (rate ratio 0.68; 95% confidence interval [CI] 0.53-0.87; P = .002). Sensitivity analyses confirm these findings. Our data suggest that SUDEP risk significantly decreases during long-term follow-up of patients with refractory epilepsy receiving VNS Therapy. This finding might reflect several factors, including the natural long-term dynamic of SUDEP rate, attrition, and the impact of VNS Therapy. The role of each of these factors cannot be confirmed due to the limitations of the study

Academic language socialisation in high school writing conferences

This study examines multilingual high school writers’ individual talk with their teachers in two advanced English language development classes to observe how such talk shapes linguistically diverse adolescents’ writing. Addressing adolescent writers’ language socialization through microethnographic discourse analysis, the author argues that teachers’ oral responses during writing conferences can either scaffold or deter students’ socialization into valued ways of using academic language for school writing. She suggests what forms of oral response provide scaffolding and what forms might limit multilingual adolescent learners’ academic literacy. Constructive interactions engaged students in dialogue about their writing, and students included content or phrasing from the interaction in their texts. Unhelpful interactions failed to foster students’ language development in observable ways. Although teachers attempted to scaffold ideas and language, they often did not guide students’ discovery of appropriate forms or points. These interactions represent restrictive academic language socialization: while some students did create academic texts, they learned little about academic language use

[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