[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

Paleobiology of titanosaurs: reproduction, development, histology, pneumaticity, locomotion and neuroanatomy from the South American fossil record

Fil: García, Rodolfo A.. Instituto de Investigación en Paleobiología y Geología. Museo Provincial Carlos Ameghino. Cipolletti; ArgentinaFil: Salgado, Leonardo. Instituto de Investigación en Paleobiología y Geología. General Roca. Río Negro; ArgentinaFil: Fernández, Mariela. Inibioma-Centro Regional Universitario Bariloche. Bariloche. Río Negro; ArgentinaFil: Cerda, Ignacio A.. Instituto de Investigación en Paleobiología y Geología. Museo Provincial Carlos Ameghino. Cipolletti; ArgentinaFil: Carabajal, Ariana Paulina. Museo Carmen Funes. Plaza Huincul. Neuquén; ArgentinaFil: Otero, Alejandro. Museo de La Plata. Universidad Nacional de La Plata; ArgentinaFil: Coria, Rodolfo A.. Instituto de Paleobiología y Geología. Universidad Nacional de Río Negro. Neuquén; ArgentinaFil: Fiorelli, Lucas E.. Centro Regional de Investigaciones Científicas y Transferencia Tecnológica. Anillaco. La Rioja; Argentin

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

New insights into the genetic etiology of Alzheimer's disease and related dementias

Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele

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

Axonal damage and astrocytosis are biological correlates of grey matter network integrity loss: a cohort study in autosomal dominant Alzheimer disease

AbstractBrain development and maturation leads to grey matter networks that can be measured using magnetic resonance imaging. Network integrity is an indicator of information processing capacity which declines in neurodegenerative disorders such as Alzheimer disease (AD). The biological mechanisms causing this loss of network integrity remain unknown. Cerebrospinal fluid (CSF) protein biomarkers are available for studying diverse pathological mechanisms in humans and can provide insight into decline. We investigated the relationships between 10 CSF proteins and network integrity in mutation carriers (N=219) and noncarriers (N=136) of the Dominantly Inherited Alzheimer Network Observational study. Abnormalities in Aβ, Tau, synaptic (SNAP-25, neurogranin) and neuronal calcium-sensor protein (VILIP-1) preceded grey matter network disruptions by several years, while inflammation related (YKL-40) and axonal injury (NfL) abnormalities co-occurred and correlated with network integrity. This suggests that axonal loss and inflammation play a role in structural grey matter network changes.Key points-Abnormal levels of fluid markers for neuronal damage and inflammatory processes in CSF are associated with grey matter network disruptions.-The strongest association was with NfL, suggesting that axonal loss may contribute to disrupted network organization as observed in AD.-Tracking biomarker trajectories over the disease course, changes in CSF biomarkers generally precede changes in brain networks by several years.</jats:sec

Application of harmonic analysis of water levels to determine vertical hydraulic conductivities in clay-rich aquitards

A harmonic analysis method was used to determine vertical hydraulic conductivities (Kv) in geologic media between vertically separated piezometers using water level measurements. In this method, each water level time series was filtered and then decomposed using harmonic analysis into a sum of trigonometric components. The phase and amplitude of each harmonic function were calculated. These data were used to estimate Kv values between vertically separated data sets assuming one-dimensional transient flow. The method was applied to water level data collected from nested piezometers at two thick clay-rich till aquitards in Saskatchewan, Canada. At one site, routine water levels were measured in 12 piezometers (installed between 1 and 29 m below ground surface) since installation (1995). At the other site, water levels were measured in seven piezometers (installed between 4 and 53 m below ground surface) since installation (1998–1999). The Kv calculated using harmonic analysis decreased with depth below the water table at both sites, approaching matrix estimates of hydraulic conductivity between 10 and 11 m and between 21 and 43 m below ground surface. These depths reflected the depth of extensive vertical fracturing at the sites and showed that the depth of fracturing may be site specific