Deep grading for MRI-based differential diagnosis of Alzheimer's disease and Frontotemporal dementia

Alzheimer's disease and Frontotemporal dementia are common forms of neurodegenerative dementia. Behavioral alterations and cognitive impairments are found in the clinical courses of both diseases and their differential diagnosis is sometimes difficult for physicians. Therefore, an accurate tool dedicated to this diagnostic challenge can be valuable in clinical practice. However, current structural imaging methods mainly focus on the detection of each disease but rarely on their differential diagnosis. In this paper, we propose a deep learning based approach for both problems of disease detection and differential diagnosis. We suggest utilizing two types of biomarkers for this application: structure grading and structure atrophy. First, we propose to train a large ensemble of 3D U-Nets to locally determine the anatomical patterns of healthy people, patients with Alzheimer's disease and patients with Frontotemporal dementia using structural MRI as input. The output of the ensemble is a 2-channel disease's coordinate map able to be transformed into a 3D grading map which is easy to interpret for clinicians. This 2-channel map is coupled with a multi-layer perceptron classifier for different classification tasks. Second, we propose to combine our deep learning framework with a traditional machine learning strategy based on volume to improve the model discriminative capacity and robustness. After both cross-validation and external validation, our experiments based on 3319 MRI demonstrated competitive results of our method compared to the state-of-the-art methods for both disease detection and differential diagnosis

Key questions for the evaluation of anti-amyloid immunotherapies for Alzheimer’s disease

The clinical benefit associated with anti-amyloid immunotherapies, a new class of drugs for the treatment of Alzheimer’s disease, is predicated on their ability to modify disease course by lowering brain amyloid levels. At the time of writing, two amyloid-lowering antibodies, aducanumab and lecanemab, have obtained United States Food and Drug Administration accelerated approval, with further agents of this class in the Alzheimer’s disease treatment pipeline. Based on limited published clinical trial data to date, regulators, payors and physicians will need to assess their efficacy, clinical effectiveness and safety, as well as cost and accessibility. We propose that attention to three important questions related to treatment efficacy, clinical effectiveness and safety should guide evidence-based consideration of this important class of drugs. These are: (1) Were trial statistical analyses appropriate and did they convincingly support claims of efficacy? (2) Do reported treatment effects outweigh safety concerns and are they generalizable to a representative clinical population of people with Alzheimer’s disease? and (3) Do the data convincingly demonstrate disease course modification, suggesting that increasing clinical benefits beyond the duration of the trials are likely? We suggest specific approaches to interpreting trial results for these drugs and highlight important areas of uncertainty where additional data and a cautious interpretation of existing results is warranted. Safe, effective and accessible treatments for Alzheimer’s disease are eagerly awaited by millions of patients and their caregivers worldwide. While amyloid-targeting immunotherapies may be promising disease-modifying Alzheimer’s disease treatments, rigorous and unbiased assessment of clinical trial data is critical to regulatory decision-making and subsequently determining their provision and utility in routine clinical practice. Our recommendations provide a framework for evidence-based appraisal of these drugs by regulators, payors, physicians and patients

Brain Communications

Brain charts for the human lifespan have been recently proposed to build dynamic models of brain anatomy in normal aging and various neurological conditions. They offer new possibilities to quantify neuroanatomical changes from preclinical stages to death, where longitudinal MRI data are not available. In this study, we used brain charts to model the progression of brain atrophy in progressive supranuclear palsy – Richardson syndrome (PSPRS). We combined multiple datasets (n=8170 quality controlled MRI of healthy subjects from 22 cohorts covering the entire lifespan, and n=62 MRI of PSP-RS patients from the 4 Repeat Tauopathy Neuroimaging Initiative) to extrapolate lifetime volumetric models of healthy and PSP-RS brain structures. We then mapped in time and space the sequential divergence between healthy and PSP-RS charts. We found six major consecutive stages of atrophy progression: (i) ventral diencephalon (including subthalamic nuclei, substantia nigra, and red nuclei), (ii) pallidum, (iii) brainstem, striatum and amygdala, (iv) thalamus, (v) frontal lobe and (vi) occipital lobe. The three structures with most severe atrophy over time were the thalamus, followed by the pallidum and the brainstem. These results match the neuropathological staging of tauopathy progression in PSP-RS, where the pathology is supposed to start in the pallido-nigro-luysian system and spreads rostrally via the striatum and the amygdala to the cerebral cortex, and caudally to the brainstem. This study supports the use of brain charts for the human lifespan to study the progression of neurodegenerative diseases, especially in the absence of specific biomarkers as in PSP.Apprentissage profond pour la volumétrie cérébrale : vers le BigData en neuroscienceInitiative d'excellence de l'Université de Bordeau

Regional hippocampal vulnerability in early multiple sclerosis: a dynamic pathological spreading from dentate gyrus to CA1

"This is the peer reviewed version of the following article: Planche, V., Koubiyr, I., Romero, J. E., Manjon, J. V., Coupé, P., Deloire, M., ... & Tourdias, T. (2018). Regional hippocampal vulnerability in early multiple sclerosis: Dynamic pathological spreading from dentate gyrus to CA 1. Human brain mapping, 39(4), 1814-1824., which has been published in final form at https://doi.org/10.1002/hbm.23970. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving."[EN] Background: Whether hippocampal subfields are differentially vulnerable at the earliest stages of multiple sclerosis (MS) and how this impacts memory performance is a current topic of debate. Method: We prospectively included 56 persons with clinically isolated syndrome (CIS) suggestive of MS in a 1-year longitudinal study, together with 55 matched healthy controls at baseline. Participants were tested for memory performance and scanned with 3T MRI to assess the volume of 5 distinct hippocampal subfields using automatic segmentation techniques. Results: At baseline, CA4/dentate gyrus was the only hippocampal subfield with a volume significantly smaller than controls (p < .01). After one year, CA4/dentate gyrus atrophy worsened (-6.4%, p < .0001) and significant CA1 atrophy appeared (both in the stratum-pyramidale and the stratum radiatum-lacunosum-moleculare, -5.6%, p < .001 and -6.2%, p < .01, respectively). CA4/dentate gyrus volume at baseline predicted CA1 volume one year after CIS (R-2 = 0.44 to 0.47, p < .001, with age, T2 lesion-load, and global brain atrophy as covariates). The volume of CA4/dentate gyrus at baseline was associated with MS diagnosis during follow-up, independently of T2-lesion load and demographic variables (p < .05). Whereas CA4/dentate gyrus volume was not correlated with memory scores at baseline, CA1 atrophy was an independent correlate of episodic verbal memory performance one year after CIS (beta = 0.87, p < .05). Conclusion: The hippocampal degenerative process spread from dentate gyrus to CA1 at the earliest stage of MS. This dynamic vulnerability is associated with MS diagnosis after CIS and will ultimately impact hippocampal-dependent memory performance.ARSEP Foundation; Bordeaux University Hospital; TEVA Laboratories; French Agence Nationale de la Recherche, Grant/Award Numbers: ANR-10-LABX-57, ANR-10-LABX-43, ANR-10-IDEX-03-02, ANR-10-COHO-002; UPV, Grant/Award Numbers: UPV2016-0099, TIN2013-43457-R; Ministerio de Economia y competitividadPlanche, V.; Koubiyr, I.; Romero Gómez, JE.; Manjón Herrera, JV.; Coupe, P.; Deloire, M.; Dousset, V.... (2018). Regional hippocampal vulnerability in early multiple sclerosis: a dynamic pathological spreading from dentate gyrus to CA1. Human Brain Mapping. 39(4):1814-1824. https://doi.org/10.1002/hbm.23970S18141824394Avants, B. B., Tustison, N. J., Song, G., Cook, P. A., Klein, A., & Gee, J. C. (2011). A reproducible evaluation of ANTs similarity metric performance in brain image registration. NeuroImage, 54(3), 2033-2044. doi:10.1016/j.neuroimage.2010.09.025Bakker, A., Kirwan, C. B., Miller, M., & Stark, C. E. L. (2008). Pattern Separation in the Human Hippocampal CA3 and Dentate Gyrus. Science, 319(5870), 1640-1642. doi:10.1126/science.1152882Coupé, P., Manjón, J. V., Chamberland, M., Descoteaux, M., & Hiba, B. (2013). Collaborative patch-based super-resolution for diffusion-weighted images. NeuroImage, 83, 245-261. doi:10.1016/j.neuroimage.2013.06.030De Stefano, N., Airas, L., Grigoriadis, N., Mattle, H. P., O’Riordan, J., Oreja-Guevara, C., … Kieseier, B. C. (2014). Clinical Relevance of Brain Volume Measures in Multiple Sclerosis. CNS Drugs, 28(2), 147-156. doi:10.1007/s40263-014-0140-zDu, A. 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Mapping local hippocampal changes in Alzheimer’s disease and normal ageing with MRI at 3 Tesla. Brain, 131(12), 3266-3276. doi:10.1093/brain/awn280Gold, S. M., Kern, K. C., O’Connor, M.-F., Montag, M. J., Kim, A., Yoo, Y. S., … Sicotte, N. L. (2010). Smaller Cornu Ammonis 2–3/Dentate Gyrus Volumes and Elevated Cortisol in Multiple Sclerosis Patients with Depressive Symptoms. Biological Psychiatry, 68(6), 553-559. doi:10.1016/j.biopsych.2010.04.025Habbas, S., Santello, M., Becker, D., Stubbe, H., Zappia, G., Liaudet, N., … Volterra, A. (2015). Neuroinflammatory TNFα Impairs Memory via Astrocyte Signaling. Cell, 163(7), 1730-1741. doi:10.1016/j.cell.2015.11.023Hulst, H. E., Schoonheim, M. M., Van Geest, Q., Uitdehaag, B. M., Barkhof, F., & Geurts, J. J. (2015). Memory impairment in multiple sclerosis: Relevance of hippocampal activation and hippocampal connectivity. Multiple Sclerosis Journal, 21(13), 1705-1712. doi:10.1177/1352458514567727Jack, C. R., Petersen, R. C., Xu, Y., O’Brien, P. C., Smith, G. E., Ivnik, R. J., … Kokmen, E. (2000). Rates of hippocampal atrophy correlate with change in clinical status in aging and AD. Neurology, 55(4), 484-490. doi:10.1212/wnl.55.4.484Jack, C. R., Barkhof, F., Bernstein, M. A., Cantillon, M., Cole, P. E., DeCarli, C., … Foster, N. L. (2011). Steps to standardization and validation of hippocampal volumetry as a biomarker in clinical trials and diagnostic criterion for Alzheimer’s disease. Alzheimer’s & Dementia, 7(4), 474-485.e4. doi:10.1016/j.jalz.2011.04.007Kerchner, G. A., Bernstein, J. D., Fenesy, M. C., Deutsch, G. K., Saranathan, M., Zeineh, M. M., & Rutt, B. K. (2013). Shared Vulnerability of Two Synaptically-Connected Medial Temporal Lobe Areas to Age and Cognitive Decline: A Seven Tesla Magnetic Resonance Imaging Study. Journal of Neuroscience, 33(42), 16666-16672. doi:10.1523/jneurosci.1915-13.2013La Joie, R., Fouquet, M., Mézenge, F., Landeau, B., Villain, N., Mevel, K., … Chételat, G. (2010). Differential effect of age on hippocampal subfields assessed using a new high-resolution 3T MR sequence. NeuroImage, 53(2), 506-514. doi:10.1016/j.neuroimage.2010.06.024Longoni, G., Rocca, M. A., Pagani, E., Riccitelli, G. C., Colombo, B., Rodegher, M., … Filippi, M. (2013). Deficits in memory and visuospatial learning correlate with regional hippocampal atrophy in MS. Brain Structure and Function, 220(1), 435-444. doi:10.1007/s00429-013-0665-9Manjón, J. V., & Coupé, P. (2016). volBrain: An Online MRI Brain Volumetry System. Frontiers in Neuroinformatics, 10. doi:10.3389/fninf.2016.00030Manjón, J. V., Coupé, P., Martí-Bonmatí, L., Collins, D. L., & Robles, M. (2009). Adaptive non-local means denoising of MR images with spatially varying noise levels. Journal of Magnetic Resonance Imaging, 31(1), 192-203. doi:10.1002/jmri.22003Manjón, J. V., Eskildsen, S. F., Coupé, P., Romero, J. E., Collins, D. L., & Robles, M. (2014). Nonlocal Intracranial Cavity Extraction. International Journal of Biomedical Imaging, 2014, 1-11. doi:10.1155/2014/820205Maruszak, A., & Thuret, S. (2014). Why looking at the whole hippocampus is not enough—a critical role for anteroposterior axis, subfield and activation analyses to enhance predictive value of hippocampal changes for Alzheimer’s disease diagnosis. Frontiers in Cellular Neuroscience, 8. doi:10.3389/fncel.2014.00095Miller, D. H., Chard, D. T., & Ciccarelli, O. (2012). Clinically isolated syndromes. The Lancet Neurology, 11(2), 157-169. doi:10.1016/s1474-4422(11)70274-5Morra, J. H., Tu, Z., Apostolova, L. G., Green, A. E., Avedissian, C., … Madsen, S. K. (2009). Automated 3D mapping of hippocampal atrophy and its clinical correlates in 400 subjects with Alzheimer’s disease, mild cognitive impairment, and elderly controls. Human Brain Mapping, 30(9), 2766-2788. doi:10.1002/hbm.20708Ny�l, L. G., & Udupa, J. K. (1999). On standardizing the MR image intensity scale. Magnetic Resonance in Medicine, 42(6), 1072-1081. doi:10.1002/(sici)1522-2594(199912)42:63.0.co;2-mPapadopoulos, D., Dukes, S., Patel, R., Nicholas, R., Vora, A., & Reynolds, R. (2009). Substantial Archaeocortical Atrophy and Neuronal Loss in Multiple Sclerosis. Brain Pathology, 19(2), 238-253. doi:10.1111/j.1750-3639.2008.00177.xPérez-Miralles, F., Sastre-Garriga, J., Tintoré, M., Arrambide, G., Nos, C., Perkal, H., … Montalban, X. (2013). Clinical impact of early brain atrophy in clinically isolated syndromes. Multiple Sclerosis Journal, 19(14), 1878-1886. doi:10.1177/1352458513488231Planche, V., Ruet, A., Coupé, P., Lamargue-Hamel, D., Deloire, M., Pereira, B., … Tourdias, T. (2016). Hippocampal microstructural damage correlates with memory impairment in clinically isolated syndrome suggestive of multiple sclerosis. Multiple Sclerosis Journal, 23(9), 1214-1224. doi:10.1177/1352458516675750Planche, V., Panatier, A., Hiba, B., Ducourneau, E.-G., Raffard, G., Dubourdieu, N., … Tourdias, T. (2017). Selective dentate gyrus disruption causes memory impairment at the early stage of experimental multiple sclerosis. Brain, Behavior, and Immunity, 60, 240-254. doi:10.1016/j.bbi.2016.11.010Planche, V., Ruet, A., Charré-Morin, J., Deloire, M., Brochet, B., & Tourdias, T. (2017). Pattern separation performance is decreased in patients with early multiple sclerosis. Brain and Behavior, 7(8), e00739. doi:10.1002/brb3.739Polman, C. H., Reingold, S. C., Banwell, B., Clanet, M., Cohen, J. A., Filippi, M., … Wolinsky, J. S. (2011). Diagnostic criteria for multiple sclerosis: 2010 Revisions to the McDonald criteria. Annals of Neurology, 69(2), 292-302. doi:10.1002/ana.22366Rocca, M. A., Longoni, G., Pagani, E., Boffa, G., Colombo, B., Rodegher, M., … Filippi, M. (2015). In vivo evidence of hippocampal dentate gyrus expansion in multiple sclerosis. Human Brain Mapping, 36(11), 4702-4713. doi:10.1002/hbm.22946Romero, J. E., Coupe, P., & Manjón, J. V. (2016). High Resolution Hippocampus Subfield Segmentation Using Multispectral Multiatlas Patch-Based Label Fusion. Lecture Notes in Computer Science, 117-124. doi:10.1007/978-3-319-47118-1_15Romero, J. E., Coupé, P., & Manjón, J. V. (2017). HIPS: A new hippocampus subfield segmentation method. NeuroImage, 163, 286-295. doi:10.1016/j.neuroimage.2017.09.049Schmidt, P., Gaser, C., Arsic, M., Buck, D., Förschler, A., Berthele, A., … Mühlau, M. (2012). An automated tool for detection of FLAIR-hyperintense white-matter lesions in Multiple Sclerosis. NeuroImage, 59(4), 3774-3783. doi:10.1016/j.neuroimage.2011.11.032Sicotte, N. L., Kern, K. C., Giesser, B. S., Arshanapalli, A., Schultz, A., Montag, M., … Bookheimer, S. Y. (2008). Regional hippocampal atrophy in multiple sclerosis. Brain, 131(4), 1134-1141. doi:10.1093/brain/awn030Small, S. A. (2014). Isolating Pathogenic Mechanisms Embedded within the Hippocampal Circuit through Regional Vulnerability. Neuron, 84(1), 32-39. doi:10.1016/j.neuron.2014.08.030Stark, S. M., Yassa, M. A., Lacy, J. W., & Stark, C. E. L. (2013). A task to assess behavioral pattern separation (BPS) in humans: Data from healthy aging and mild cognitive impairment. Neuropsychologia, 51(12), 2442-2449. doi:10.1016/j.neuropsychologia.2012.12.014Thompson, P. M., Hayashi, K. M., de Zubicaray, G. I., Janke, A. L., Rose, S. E., Semple, J., … Toga, A. W. (2004). Mapping hippocampal and ventricular change in Alzheimer disease. NeuroImage, 22(4), 1754-1766. doi:10.1016/j.neuroimage.2004.03.040Tustison, N. J., Avants, B. B., Cook, P. A., Yuanjie Zheng, Egan, A., Yushkevich, P. A., & Gee, J. C. (2010). N4ITK: Improved N3 Bias Correction. IEEE Transactions on Medical Imaging, 29(6), 1310-1320. doi:10.1109/tmi.2010.2046908Wang, L., Swank, J. S., Glick, I. E., Gado, M. H., Miller, M. I., Morris, J. C., & Csernansky, J. G. (2003). Changes in hippocampal volume and shape across time distinguish dementia of the Alzheimer type from healthy aging☆. NeuroImage, 20(2), 667-682. doi:10.1016/s1053-8119(03)00361-6West, M. ., Coleman, P. ., Flood, D. ., & Troncoso, J. . (1994). Differences in the pattern of hippocampal neuronal loss in normal ageing and Alzheimer’s disease. The Lancet, 344(8925), 769-772. doi:10.1016/s0140-6736(94)92338-8Winterburn, J. L., Pruessner, J. C., Chavez, S., Schira, M. M., Lobaugh, N. J., Voineskos, A. N., & Chakravarty, M. M. (2013). A novel in vivo atlas of human hippocampal subfields using high-resolution 3T magnetic resonance imaging. NeuroImage, 74, 254-265. doi:10.1016/j.neuroimage.2013.02.003Wisse, L. E. M., Daugherty, A. M., Olsen, R. K., Berron, D., Carr, V. A., … Stark, C. E. L. (2016). A harmonized segmentation protocol for hippocampal and parahippocampal subregions: Why do we need one and what are the key goals? Hippocampus, 27(1), 3-11. doi:10.1002/hipo.22671Yushkevich, P. A., Amaral, R. S. C., Augustinack, J. C., Bender, A. R., Bernstein, J. D., Boccardi, M., … Zeineh, M. M. (2015). Quantitative comparison of 21 protocols for labeling hippocampal subfields and parahippocampal subregions in in vivo MRI: Towards a harmonized segmentation protocol. NeuroImage, 111, 526-541. doi:10.1016/j.neuroimage.2015.01.00

Mult Scler

Background: Investigating the degeneration of specific thalamic nuclei in multiple sclerosis (MS) remains challenging. Methods: White-matter-nulled (WMn) MPRAGE, MP-FLAIR, and standard T1-weighted magnetic resonance imaging (MRI) were performed on MS patients (n = 15) and matched controls (n = 12). Thalamic lesions were counted in individual sequences and lesion contrast-to-noise ratio (CNR) was measured. Volumes of 12 thalamic nuclei were measured using an automatic segmentation pipeline specifically developed for WMn-MPRAGE. Results: WMn-MPRAGE showed more thalamic MS lesions (n = 35 in 9 out of 15 patients) than MP-FLAIR (n = 25) and standard T1 (n = 23), which was associated with significant improvement of CNR (p < 0.0001). MS patients had whole thalamus atrophy (p = 0.003) with lower volumes found for the anteroventral (p < 0.001), the pulvinar (p < 0.0001), and the habenular (p = 0.004) nuclei. Conclusion: WMn-MPRAGE and automatic thalamic segmentation can highlight thalamic MS lesions and measure patterns of focal thalamic atrophy. © The Author(s), 2019.Translational Research and Advanced Imaging LaboratoryBordeaux Region Aquitaine Initiative for Neuroscienc

Brain Commun.

The chronological progression of brain atrophy over decades, from pre-symptomatic to dementia stages, has never been formally depicted in Alzheimer's disease. This is mainly due to the lack of cohorts with long enough MRI follow-ups in cognitively unimpaired young participants at baseline. To describe a spatiotemporal atrophy staging of Alzheimer's disease at the whole-brain level, we built extrapolated lifetime volumetric models of healthy and Alzheimer's disease brain structures by combining multiple large-scale databases (n = 3512 quality controlled MRI from 9 cohorts of subjects covering the entire lifespan, including 415 MRI from ADNI1, ADNI2 and AIBL for Alzheimer's disease patients). Then, we validated dynamic models based on cross-sectional data using external longitudinal data. Finally, we assessed the sequential divergence between normal aging and Alzheimer's disease volumetric trajectories and described the following staging of brain atrophy progression in Alzheimer's disease: (i) hippocampus and amygdala; (ii) middle temporal gyrus; (iii) entorhinal cortex, parahippocampal cortex and other temporal areas; (iv) striatum and thalamus and (v) middle frontal, cingular, parietal, insular cortices and pallidum. We concluded that this MRI scheme of atrophy progression in Alzheimer's disease was close but did not entirely overlap with Braak staging of tauopathy, with a 'reverse chronology' between limbic and entorhinal stages. Alzheimer's disease structural progression may be associated with local tau accumulation but may also be related to axonal degeneration in remote sites and other limbic-predominant associated proteinopathies. © 2022 The Author(s). Published by Oxford University Press on behalf of the Guarantors of Brain.Apprentissage profond pour la volumétrie cérébrale : vers le BigData en neuroscienceTranslational Research and Advanced Imaging Laborator

Alzheimers Dement

This study aims to examine whether physical activity moderates the association between biomarkers of brain pathologies and dementia risk. From the Memento cohort, we analyzed 1044 patients with mild cognitive impairment, aged 60 and older. Self-reported physical activity was assessed using the International Physical Activity Questionnaire. Biomarkers of brain pathologies comprised medial temporal lobe atrophy (MTA), white matter lesions, and plasma amyloid beta (Aβ)42/40 and phosphorylated tau181. Association between physical activity and risk of developing dementia over 5 years of follow-up, and interactions with biomarkers of brain pathologies were tested. Physical activity moderated the association between MTA and plasma Aβ42/40 level and increased dementia risk. Compared to participants with low physical activity, associations of both MTA and plasma Aβ42/40 on dementia risk were attenuated in participants with high physical activity. Although reverse causality cannot be excluded, this work suggests that physical activity may contribute to cognitive reserve. Physical activity is an interesting modifiable target for dementia prevention. Physical activity may moderate the impact of brain pathology on dementia risk. Medial temporal lobe atrophy and plasma amyloid beta 42/40 ratio were associated with increased dementia risk especially in those with low level of physical activity

Associations among hypertension, dementia biomarkers, and cognition: The MEMENTO cohort

Introduction Approximately 40% of dementia cases could be delayed or prevented acting on modifiable risk factors including hypertension. However, the mechanisms underlying the hypertension–dementia association are still poorly understood. Methods We conducted a cross-sectional analysis in 2048 patients from the MEMENTO cohort, a French multicenter clinic-based study of outpatients with either isolated cognitive complaints or mild cognitive impairment. Exposure to hypertension was defined as a combination of high blood pressure (BP) status and antihypertensive treatment intake. Pathway associations were examined through structural equation modeling integrating extensive collection of neuroimaging biomarkers and clinical data. Results Participants treated with high BP had significantly lower cognition compared to the others. This association was mediated by higher neurodegeneration and higher white matter hyperintensities load but not by Alzheimer's disease (AD) biomarkers. Discussion These results highlight the importance of controlling hypertension for prevention of cognitive decline and offer new insights on mechanisms underlying the hypertension–dementia association. Highlights Paths of hypertension–cognition association were assessed by structural equation models. The hypertension–cognition association is not mediated by Alzheimer's disease biomarkers. The hypertension–cognition association is mediated by neurodegeneration and leukoaraiosis. Lower cognition was limited to participants treated with uncontrolled blood pressure. Blood pressure control could contribute to promote healthier brain aging.Stopping cognitive decline and dementia by fighting covert cerebral small vessel diseas

Adjunctive rifampicin for Staphylococcus aureus bacteraemia (ARREST): a multicentre, randomised, double-blind, placebo-controlled trial.

BACKGROUND: Staphylococcus aureus bacteraemia is a common cause of severe community-acquired and hospital-acquired infection worldwide. We tested the hypothesis that adjunctive rifampicin would reduce bacteriologically confirmed treatment failure or disease recurrence, or death, by enhancing early S aureus killing, sterilising infected foci and blood faster, and reducing risks of dissemination and metastatic infection. METHODS: In this multicentre, randomised, double-blind, placebo-controlled trial, adults (≥18 years) with S aureus bacteraemia who had received ≤96 h of active antibiotic therapy were recruited from 29 UK hospitals. Patients were randomly assigned (1:1) via a computer-generated sequential randomisation list to receive 2 weeks of adjunctive rifampicin (600 mg or 900 mg per day according to weight, oral or intravenous) versus identical placebo, together with standard antibiotic therapy. Randomisation was stratified by centre. Patients, investigators, and those caring for the patients were masked to group allocation. The primary outcome was time to bacteriologically confirmed treatment failure or disease recurrence, or death (all-cause), from randomisation to 12 weeks, adjudicated by an independent review committee masked to the treatment. Analysis was intention to treat. This trial was registered, number ISRCTN37666216, and is closed to new participants. FINDINGS: Between Dec 10, 2012, and Oct 25, 2016, 758 eligible participants were randomly assigned: 370 to rifampicin and 388 to placebo. 485 (64%) participants had community-acquired S aureus infections, and 132 (17%) had nosocomial S aureus infections. 47 (6%) had meticillin-resistant infections. 301 (40%) participants had an initial deep infection focus. Standard antibiotics were given for 29 (IQR 18-45) days; 619 (82%) participants received flucloxacillin. By week 12, 62 (17%) of participants who received rifampicin versus 71 (18%) who received placebo experienced treatment failure or disease recurrence, or died (absolute risk difference -1·4%, 95% CI -7·0 to 4·3; hazard ratio 0·96, 0·68-1·35, p=0·81). From randomisation to 12 weeks, no evidence of differences in serious (p=0·17) or grade 3-4 (p=0·36) adverse events were observed; however, 63 (17%) participants in the rifampicin group versus 39 (10%) in the placebo group had antibiotic or trial drug-modifying adverse events (p=0·004), and 24 (6%) versus six (2%) had drug interactions (p=0·0005). INTERPRETATION: Adjunctive rifampicin provided no overall benefit over standard antibiotic therapy in adults with S aureus bacteraemia. FUNDING: UK National Institute for Health Research Health Technology Assessment