Segmenting white matter hyperintensities on isotropic three-dimensional Fluid Attenuated Inversion Recovery magnetic resonance images: Assessing deep learning tools on a Norwegian imaging database

An important step in the analysis of magnetic resonance imaging (MRI) data for neuroimaging is the automated segmentation of white matter hyperintensities (WMHs). Fluid Attenuated Inversion Recovery (FLAIR-weighted) is an MRI contrast that is particularly useful to visualize and quantify WMHs, a hallmark of cerebral small vessel disease and Alzheimer's disease (AD). In order to achieve high spatial resolution in each of the three voxel dimensions, clinical MRI protocols are evolving to a three-dimensional (3D) FLAIR-weighted acquisition. The current study details the deployment of deep learning tools to enable automated WMH segmentation and characterization from 3D FLAIR-weighted images acquired as part of a national AD imaging initiative. Based on data from the ongoing Norwegian Disease Dementia Initiation (DDI) multicenter study, two 3D models-one off-the-shelf from the NVIDIA nnU-Net framework and the other internally developed-were trained, validated, and tested. A third cutting-edge Deep Bayesian network model (HyperMapp3r) was implemented without any de-novo tuning to serve as a comparison architecture. The 2.5D in-house developed and 3D nnU-Net models were trained and validated in-house across five national collection sites among 441 participants from the DDI study, of whom 194 were men and whose average age was (64.91 +/- 9.32) years. Both an external dataset with 29 cases from a global collaborator and a held-out subset of the internal data from the 441 participants were used to test all three models. These test sets were evaluated independently. The ground truth human-in-the-loop segmentation was compared against five established WMH performance metrics. The 3D nnU-Net had the highest performance out of the three tested networks, outperforming both the internally developed 2.5D model and the SOTA Deep Bayesian network with an average dice similarity coefficient score of 0.76 +/- 0.16. Our findings demonstrate that WMH segmentation models can achieve high performance when trained exclusively on FLAIR input volumes that are 3D volumetric acquisitions. Single image input models are desirable for ease of deployment, as reflected in the current embedded clinical research project. The 3D nnU-Net had the highest performance, which suggests a way forward for our need to automate WMH segmentation while also evaluating performance metrics during on-going data collection and model retraining

Drug repositioning and repurposing for Alzheimer disease

This is the author accepted manuscript. The final version is available from Nature Research via the DOI in this recordDrug repositioning and repurposing can enhance traditional drug development efforts and could accelerate the identification of new treatments for individuals with Alzheimer disease (AD) dementia and mild cognitive impairment. Transcriptional profiling offers a new and highly efficient approach to the identification of novel candidates for repositioning and repurposing. In the future, novel AD transcriptional signatures from cells isolated at early stages of disease, or from human neurons or microglia that carry mutations that increase risk of AD, might be used as probes to identify additional candidate drugs. Phase II trials assessing repurposed agents must consider the best target population for a specific candidate therapy as well as the mechanism of action of the treatment. In this Review, we highlight promising compounds to prioritise for clinical trials in individuals with AD, and discuss the value of Delphi consensus methodology and evidence-based reviews to inform this prioritization process. We also describe emerging work, focussing on the potential value of transcript signatures as a cost-effective approach to identify novel candidates for repositioning.KMANIGMSNIND

FLAME: A computerized neuropsychological composite for trials in early dementia

Introduction: Sensitive neuropsychological tests are needed to improve power for clinical trials in early Alzheimer's disease (AD). Methods: To develop a neuropsychological composite (FLAME - Factors of Longitudinal Attention, Memory and Executive Function), we assessed, 10,714 participants over the age of 50 from PROTECT with validated computerized assessments for 2 years. A factorial analysis was completed to identify the key cognitive factors in all participants, and further analyses examined sensitivity to change in people with stage 2/3 early Alzheimer's disease (AD) according to the US Food and Drug Administration (FDA) framework. Results: The FLAME composite score (speed of attention, accuracy of attention, memory, and executive function) distinguished between normal cognition and stage 2/3 early AD at baseline, and was sensitive to cognitive and global/functional decline over 2 years, with the potential to improve power for clinical trials. Discussion: FLAME is sensitive to change, providing a straightforward approach to reduce sample size for RCTs in early AD. Conclusion: FLAME is a useful computerized neuropsychology composite with utility for clinical trials focusing on cognition.This article is freely available via Open Access. Click on the Publisher URL to access it via the publisher's site.NIHR Maudsley Biomedical Research Centre for Mental Health Biomedical Research Centre for mental health at South London and Maudsley NHS Foundation Trust and King’s College London, Alzheimer’s Society, UK. Sponsor: The University of Exeter, UK Helen Brooker reports personal fees from Wesnes Cognition Ltd, owner of CogTrack, personal fees from University of Exeter, outside the submitted work. Professor Williams reports no conflict of interests. Professor Hampshire is owner and director of Future Cognition Ltd, which develops bespoke online cognitive tests for third parties. Dr. Corbett has nothing to disclose. Professor Aarsland reports grants and personal fees from Astra-Zeneca, grants and personal fees from H. Lundbeck, grants and personal fees from Novartis Pharmaceuticals, grants and personal fees from GE Health, grants and personal fees from Eisai, and grants and personal fees from Axovant, outside the submitted work. This paper represents independent research [part] funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR, or the Department of Health. Dr. Cummings has provided consultation to Acadia, Actinogen, AgeneBio, Alkahest, Alzheon, AnnovisBio, Avanir, Axsome, Biogen, BioXcel, Cassava, Cerecin, Cerevel, Cortexyme, EIP Pharma, Eisai, Foresight, GemVax, Genentech, Green Valley, Grifols, Karuna, Merck, Novo Nordisk, Otsuka, Resverlogix, Roche, Samumed, Samus, Signant Health, Suven, Third Rock, and United Neuroscience pharmaceutical and assessment companies. Dr.Cummings has stock options in ADAMAS, AnnovisBio, MedAvante, BiOasis. Dr. Cummings owns the copyright of the Neuropsychiatric Inventory. Dr Cummings is supported by Keep Memory Alive (KMA); National Institute of Health (NIH) grant P20GM109025; National Institute of Stroke and neurological Disease grant U01NS093334; and National Institute of Aging grant R01AG053798. Jose Luis Molinuevo has served/serves as a consultant or at advisory boards for the following for-profit companies, or has given lectures in symposia sponsored by the following for-profit companies: Roche Diagnostics, Genentech, Novartis, Lundbeck, Oryzon, Biogen, Lilly, Janssen, Green Valley, MSD, Eisai, Alector, BioCross, GE Healthcare, ProMIS Neurosciences, and NovoNordisk. Alireza Atri reported receiving honoraria for consulting; participating in independent data safety monitoring boards; providing educational lectures, programs, and materials; or serving on advisory boards for Allergan, the Alzheimer’s Association, Axovant, Biogen, Grifols, Harvard Medical School Graduate Continuing Education, Lundbeck, Merck, Roche/Genentech, Sunovion, and Suven; receiving book royalties from Oxford University Press; and having institutional contracts or receiving investigational clinical trial–related funding from the American College of Radiology, AbbVie, Avid, Biogen, Lilly, Lundbeck, Merck, and vTV Therapeutics. Dr. Ismail reports grants and personal fees from Janssen, personal fees from Lundbeck, and personal fees from Otsuka, outside the submitted work. Dr. Creese has nothing to disclose. Professor Fladby reports no conflicts of interest. Dr Hansen is an employee of Novo Nordisk A/S and holds stock/shares in Novo Nordisk A/SÐ outside the submitted work. Keith Wesnes is CEO of Cogtrack. Professor Ballard reports grants and personal fees from Acadia pharmaceutical company, grants and personal fees from Lundbeck, personal fees from Roche, personal fees from Otsuka, personal fees from Biogen, personal fees from Eli Lilly, personal fees from Novo Nordisk, personal fees from AARP, grants and personal fees from Synexus, and personal fees from Exciva outside the submitted work.published version, accepted version (12 month embargo), submitted versio

Developmental regulation of MURF E3 ubiquitin ligases in skeletal muscle

The striated muscle-specific tripartite motif (TRIM) proteins TRIM63/MURF1, TRIM55/MURF2 and TRIM54/MURF3 can function as E3 ubiquitin ligases in ubiquitin-mediated muscle protein turnover. Despite the well-characterised role of MURF1 in skeletal muscle atrophy, the dynamics of MURF isogene expression in the development and early postnatal adaptation of skeletal muscle is unknown. Here, we show that MURF2 is the isogene most highly expressed in embryonic skeletal muscle at E15.5, with the 50 kDa A isoform predominantly expressed. MURF1 and MURF3 are upregulated only postnatally. Knockdown of MURF2 p50A by isoform-specific siRNA results in delayed myogenic differentiation and myotube formation in vitro, with perturbation of the stable, glutamylated microtubule population. This underscores that MURF2 plays an important role in the earliest stages of skeletal muscle differentiation and myofibrillogenesis. During further development, there is a shift towards the 60 kDa A isoform, which dominates postnatally. Analysis of the fibre-type expression shows that MURF2 A isoforms are predominantly slow-fibre associated, whilst MURF1 is largely excluded from these fibres, and MURF3 is ubiquitously distributed in both type I and II fibres

GBA and APOE ε4 associate with sporadic dementia with Lewy bodies in European genome wide association study

Dementia with Lewy Bodies (DLB) is a common neurodegenerative disorder with poor prognosis and mainly unknown pathophysiology. Heritability estimates exceed 30% but few genetic risk variants have been identified. Here we investigated common genetic variants associated with DLB in a large European multisite sample. We performed a genome wide association study in Norwegian and European cohorts of 720 DLB cases and 6490 controls and included 19 top-associated single-nucleotide polymorphisms in an additional cohort of 108 DLB cases and 75545 controls from Iceland. Overall the study included 828 DLB cases and 82035 controls. Variants in the ASH1L/GBA (Chr1q22) and APOE ε4 (Chr19) loci were associated with DLB surpassing the genome-wide significance threshold (p < 5 × 10). One additional genetic locus previously linked to psychosis in Alzheimer's disease, ZFPM1 (Chr16q24.2), showed suggestive association with DLB at p-value < 1 × 10. We report two susceptibility loci for DLB at genome-wide significance, providing insight into etiological factors. These findings highlight the complex relationship between the genetic architecture of DLB and other neurodegenerative disorders

Fourteen sequence variants that associate with multiple sclerosis discovered by meta-analysis informed by genetic correlations

A meta-analysis of publicly available summary statistics on multiple sclerosis combined with three Nordic multiple sclerosis cohorts (21,079 cases, 371,198 controls) revealed seven sequence variants associating with multiple sclerosis, not reported previously. Using polygenic risk scores based on public summary statistics of variants outside the major histocompatibility complex region we quantified genetic overlap between common autoimmune diseases in Icelanders and identified disease clusters characterized by autoantibody presence/absence. As multiple sclerosis-polygenic risk scores captures the risk of primary biliary cirrhosis and vice versa (P = 1.6 x 10(-7), 4.3 x 10(-9)) we used primary biliary cirrhosis as a proxy-phenotype for multiple sclerosis, the idea being that variants conferring risk of primary biliary cirrhosis have a prior probability of conferring risk of multiple sclerosis. We tested 255 variants forming the primary biliary cirrhosis-polygenic risk score and found seven multiple sclerosis-associating variants not correlated with any previously established multiple sclerosis variants. Most of the variants discovered are close to or within immune-related genes. One is a low-frequency missense variant in TYK2, another is a missense variant in MTHFR that reduces the function of the encoded enzyme affecting methionine metabolism, reported to be dysregulated in multiple sclerosis brain.publishedVersio

Reversing the Outcome of Synapse Elimination at Developing Neuromuscular Junctions In Vivo: Evidence for Synaptic Competition and Its Mechanism

Competition between neurons for the same synaptic sites at the developing neuromuscular junction drives synaptic rearrangements

A genome-wide association study with 1,126,563 individuals identifies new risk loci for Alzheimer's disease

Late-onset Alzheimer’s disease is a prevalent age-related polygenic disease that accounts for 50–70% of dementia cases. Currently, only a fraction of the genetic variants underlying Alzheimer’s disease have been identified. Here we show that increased sample sizes allowed identification of seven previously unidentified genetic loci contributing to Alzheimer’s disease. This study highlights microglia, immune cells and protein catabolism as relevant to late-onset Alzheimer’s disease, while identifying and prioritizing previously unidentified genes of potential interest. We anticipate that these results can be included in larger meta-analyses of Alzheimer’s disease to identify further genetic variants that contribute to Alzheimer’s pathology