Specifically neuropathic Gaucher's mutations accelerate cognitive decline in Parkinson's.

OBJECTIVE: We hypothesized that specific mutations in the β-glucocerebrosidase gene (GBA) causing neuropathic Gaucher's disease (GD) in homozygotes lead to aggressive cognitive decline in heterozygous Parkinson's disease (PD) patients, whereas non-neuropathic GD mutations confer intermediate progression rates. METHODS: A total of 2,304 patients with PD and 20,868 longitudinal visits for up to 12.8 years (median, 4.1) from seven cohorts were analyzed. Differential effects of four types of genetic variation in GBA on longitudinal cognitive decline were evaluated using mixed random and fixed effects and Cox proportional hazards models. RESULTS: Overall, 10.3% of patients with PD and GBA sequencing carried a mutation. Carriers of neuropathic GD mutations (1.4% of patients) had hazard ratios (HRs) for global cognitive impairment of 3.17 (95% confidence interval [CI], 1.60-6.25) and a hastened decline in Mini-Mental State Exam scores compared to noncarriers (p = 0.0009). Carriers of complex GBA alleles (0.7%) had an HR of 3.22 (95% CI, 1.18-8.73; p = 0.022). By contrast, the common, non-neuropathic N370S mutation (1.5% of patients; HR, 1.96; 95% CI, 0.92-4.18) or nonpathogenic risk variants (6.6% of patients; HR, 1.36; 95% CI, 0.89-2.05) did not reach significance. INTERPRETATION: Mutations in the GBA gene pathogenic for neuropathic GD and complex alleles shift longitudinal cognitive decline in PD into "high gear." These findings suggest a relationship between specific types of GBA mutations and aggressive cognitive decline and have direct implications for improving the design of clinical trials. Ann Neurol 2016;80:674-685

UK Space Agency ``Mars Utah Rover Field Investigation 2016'' (MURFI 2016): Overview of Mission, Aims, and Progress

The Mars Utah Rover Field Investigation “MURFI 2016” is a Mars Rover field analogue mission run by the UK Space Agency (UKSA) in collaboration with the Canadian Space Agency (CSA). MURFI 2016 took place between 22nd October and 13th November 2016 and consisted of a field team including an instrumented Rover platform, at the field site near Hanksville (Utah, USA), and an ‘Operations Team’ based in the Mission Control Centre (MOC) at the Harwell Campus near Oxford in the UK.The field site was chosen based on the collaboration with the CSA and its Mars-like local geology. It was used by the CSA in 2015 for Mars Rover trials, and in 2016, several teams used the site, each with their own designated working areas. The two main aims of MURFI 2016 were (i) to develop logistical and leadership experience in running field trials within the UKSA, and (ii) to provide members of the Mars Science community with Rover Operations experience, and hence to build expertise that could be used in the 2020 ExoMars Rover mission, or other future Rover missions. Because MURFI 2016 was the first solely UKSA-led Rover analogue trial, the most important objective was to learn how to best implement Rover trials in general. This included aspects of planning, logistics, field safety, MOC setup and support, communications, person management and science team development. Some aspects were based on past experience from previous trials but the focus was on ‘learning through experience’ - especially in terms of the Operations Team, who each took on a variety of roles during the mission

The 2016 UK Space Agency Mars Utah Rover Field Investigation (MURFI)

The 2016 Mars Utah Rover Field Investigation (MURFI) was a Mars rover field trial run by the UK Space Agency in association with the Canadian Space Agency's 2015/2016 Mars Sample Return Analogue Deployment mission. MURFI had over 50 participants from 15 different institutions around the UK and abroad. The objectives of MURFI were to develop experience and leadership within the UK in running future rover field trials; to prepare the UK planetary community for involvement in the European Space Agency/Roscosmos ExoMars 2020 rover mission; and to assess how ExoMars operations may differ from previous rover missions. Hence, the wider MURFI trial included a ten-day (or ten-‘sol’) ExoMars rover-like simulation. This comprised an operations team and control centre in the UK, and a rover platform in Utah, equipped with instruments to emulate the ExoMars rovers remote sensing and analytical suite. The operations team operated in ‘blind mode’, where the only available data came from the rover instruments, and daily tactical planning was performed under strict time constraints to simulate real communications windows. The designated science goal of the MURFI ExoMars rover-like simulation was to locate in-situ bedrock, at a site suitable for sub-surface core-sampling, in order to detect signs of ancient life. Prior to “landing”, the only information available to the operations team were Mars-equivalent satellite remote sensing data, which were used for both geologic and hazard (e.g., slopes, loose soil) characterisation of the area. During each sol of the mission, the operations team sent driving instructions and imaging/analysis targeting commands, which were then enacted by the field team and rover-controllers in Utah. During the ten-sol mission, the rover drove over 100 m and obtained hundreds of images and supporting observations, allowing the operations team to build up geologic hypotheses for the local area and select possible drilling locations. On sol 9, the team obtained a subsurface core sample that was then analyzed by the Raman spectrometer. Following the conclusion of the ExoMars-like component of MURFI, the operations and field team came together to evaluate the successes and failures of the mission, and discuss lessons learnt for ExoMars rover and future field trials. Key outcomes relevant to ExoMars rover included a key recognition of the importance of field trials for (i) understanding how to operate the ExoMars rover instruments as a suite, (ii) building an operations planning team that can work well together under strict time-limited pressure, (iii) developing new processes and workflows relevant to the ExoMars rover, (iv) understanding the limits and benefits of satellite mapping and (v) practicing efficient geological interpretation of outcrops and landscapes from rover-based data, by comparing the outcomes of the simulated mission with post-trial, in-situ field observations. In addition, MURFI was perceived by all who participated as a vital learning experience, especially for early and mid-career members of the team, and also demonstrated the UK capability of implementing a large rover field trial. The lessons learnt from MURFI are therefore relevant both to ExoMars rover, and to future rover field trials

Online Learning for 3D LiDAR-based Human Detection: Experimental Analysis of Point Cloud Clustering and Classification Methods

This paper presents a system for online learning of human classifiers by mobile service robots using 3D~LiDAR sensors, and its experimental evaluation in a large indoor public space. The learning framework requires a minimal set of labelled samples (e.g. one or several samples) to initialise a classifier. The classifier is then retrained iteratively during operation of the robot. New training samples are generated automatically using multi-target tracking and a pair of "experts" to estimate false negatives and false positives. Both classification and tracking utilise an efficient real-time clustering algorithm for segmentation of 3D point cloud data. We also introduce a new feature to improve human classification in sparse, long-range point clouds. We provide an extensive evaluation of our the framework using a 3D LiDAR dataset of people moving in a large indoor public space, which is made available to the research community. The experiments demonstrate the influence of the system components and improved classification of humans compared to the state-of-the-art

Prediction of cognition in Parkinson's disease with a clinical-genetic score: a longitudinal analysis of nine cohorts

Cognitive decline is a debilitating manifestation of disease progression in Parkinson's disease. We aimed to develop a clinical-genetic score to predict global cognitive impairment in patients with the disease.In this longitudinal analysis, we built a prediction algorithm for global cognitive impairment (defined as Mini Mental State Examination [MMSE] ≤25) using data from nine cohorts of patients with Parkinson's disease from North America and Europe assessed between 1986 and 2016. Candidate predictors of cognitive decline were selected through a backward eliminated Cox's proportional hazards analysis using the Akaike's information criterion. These were used to compute the multivariable predictor on the basis of data from six cohorts included in a discovery population. Independent replication was attained in patients from a further three independent longitudinal cohorts. The predictive score was rebuilt and retested in 10 000 training and test sets randomly generated from the entire study population.3200 patients with Parkinson's disease who were longitudinally assessed with 27 022 study visits between 1986 and 2016 in nine cohorts from North America and Europe were assessed for eligibility. 235 patients with MMSE ≤25 at baseline and 135 whose first study visit occurred more than 12 years from disease onset were excluded. The discovery population comprised 1350 patients (after further exclusion of 334 with missing covariates) from six longitudinal cohorts with 5165 longitudinal visits over 12·8 years (median 2·8, IQR 1·6-4·6). Age at onset, baseline MMSE, years of education, motor exam score, sex, depression, and β-glucocerebrosidase (GBA) mutation status were included in the prediction model. The replication population comprised 1132 patients (further excluding 14 patients with missing covariates) from three longitudinal cohorts with 19 127 follow-up visits over 8·6 years (median 6·5, IQR 4·1-7·2). The cognitive risk score predicted cognitive impairment within 10 years of disease onset with an area under the curve (AUC) of more than 0·85 in both the discovery (95% CI 0·82-0·90) and replication (95% CI 0·78-0·91) populations. Patients scoring in the highest quartile for cognitive risk score had an increased hazard for global cognitive impairment compared with those in the lowest quartile (hazard ratio 18·4 [95% CI 9·4-36·1]). Dementia or disabling cognitive impairment was predicted with an AUC of 0·88 (95% CI 0·79-0·94) and a negative predictive value of 0·92 (95% 0·88-0·95) at the predefined cutoff of 0·196. Performance was stable in 10 000 randomly resampled subsets.Our predictive algorithm provides a potential test for future cognitive health or impairment in patients with Parkinson's disease. This model could improve trials of cognitive interventions and inform on prognosis.National Institutes of Health, US Department of Defense.We thank all study participants, their families, and friends for their support and participation, and our study coordinators. The co-investigators and contributors from Parkinson's Disease Biomarkers Program, Harvard Biomarkers Study, Drug Interaction with Genes in Parkinson's Disease (DIGPD), Parkinson Research Examination of CEP-1347 Trial (PreCEPT) and a longitudinal follow-up of the PRECEPT study cohort (PostCEPT), Parkinsonism Incidence, Cognition and Non-motor heterogeneity in Cambridgeshire (PICNICS), Cambridgeshire Parkinson's Incidence from GP to Neurologist (CamPaIGN), PROfiling PARKinson's disease study (PROPARK), as well as acknowledgments for Parkinson's Progression Marker Initiative and Deprenyl and Tocopherol Antioxidative Therapy of Parkinsonism (DATATOP) are listed in the appendix. This work was supported in part by National Institutes of Health grants U01 NS082157, U01NS095736 (to CRS), US Department of Defense grants W81XWH-1–0007 (BR) and W81XWH-15–10007 (to CRS); MEMO Hoffman Foundation (to CRS); Brigham and Women's Hospital Departmental Funds (to BB). The Harvard Biomarkers Study is supported by the Harvard NeuroDiscovery Center, the Parkinson's Disease Biomarkers Program U01 NS082157, U01NS100603 of the National Institute of Neurological Disorders and Stroke (NINDS), and the Massachusetts Alzheimer's Disease Research Center P50 AG005134 grant of the National Institute on Aging, Harvard Aging Brain Study grant P01 AG036694. The PreCEPT and PostCEPT cohort was funded by Cephalon Inc and Lundbeck for the parent PRECEPT clinical trial and follow-up PostCEPT cohort, and the Department of Defense Neurotoxin Exposure Treatment Parkinson's Research Program (W23RRYX7022N606), NINDS Data and Organizing Center's (NS050095), the Parkinson's Disease Foundation (New York, NY, USA). Additional funding information for the PreCEPT and PostCEPT cohort and corresponding investigators is listed in Ravina et al. The CamPaIGN and PICNICS studies received funding support from the Wellcome Trust, MRC, Parkinson's UK, Cure-PD, the Patrick Berthoud Trust, the Van Geest Foundation, and National Institute for Health Research funding of a Biomedical Research Centre at the University of Cambridge and Addenbrooke's Hospital. DIGPD cohort was promoted by the Assistance Publique Hôpitaux de Paris, and funded by the French clinical research hospital programme (code AOR08010). The research leading to these results has received funding from the programme Investissements d'Avenir ANR-10-IAIHU-06. DATATOP was supported by NIH grant NS24778. The PROPARK study was funded by the Prinses Beatrix Fonds (project number WAR05–0120), the van Alkemade-Keuls Foundation (Stichting Alkemade-Keuls), and the International Parkinson Foundation (Stichting ParkinsonFonds)

Parkinson's disease in GTP cyclohydrolase 1 mutation carriers.

"This is the peer reviewed version of the following article: Mencacci et al. 2014. Parkinson’s disease in GTP cyclohydrolase 1 mutation carriers, which has been published in final form at Brain, Volume 137, Issue 9, 1 September 2014, Pages 2480–2492, https://doi.org/10.1093/brain/awu179. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions."GTP cyclohydrolase 1, encoded by the GCH1 gene, is an essential enzyme for dopamine production in nigrostriatal cells. Loss-of-function mutations in GCH1 result in severe reduction of dopamine synthesis in nigrostriatal cells and are the most common cause of DOPA-responsive dystonia, a rare disease that classically presents in childhood with generalized dystonia and a dramatic long-lasting response to levodopa. We describe clinical, genetic and nigrostriatal dopaminergic imaging ([(123)I]N-ω-fluoropropyl-2β-carbomethoxy-3β-(4-iodophenyl) tropane single photon computed tomography) findings of four unrelated pedigrees with DOPA-responsive dystonia in which pathogenic GCH1 variants were identified in family members with adult-onset parkinsonism. Dopamine transporter imaging was abnormal in all parkinsonian patients, indicating Parkinson's disease-like nigrostriatal dopaminergic denervation. We subsequently explored the possibility that pathogenic GCH1 variants could contribute to the risk of developing Parkinson's disease, even in the absence of a family history for DOPA-responsive dystonia. The frequency of GCH1 variants was evaluated in whole-exome sequencing data of 1318 cases with Parkinson's disease and 5935 control subjects. Combining cases and controls, we identified a total of 11 different heterozygous GCH1 variants, all at low frequency. This list includes four pathogenic variants previously associated with DOPA-responsive dystonia (Q110X, V204I, K224R and M230I) and seven of undetermined clinical relevance (Q110E, T112A, A120S, D134G, I154V, R198Q and G217V). The frequency of GCH1 variants was significantly higher (Fisher's exact test P-value 0.0001) in cases (10/1318 = 0.75%) than in controls (6/5935 = 0.1%; odds ratio 7.5; 95% confidence interval 2.4-25.3). Our results show that rare GCH1 variants are associated with an increased risk for Parkinson's disease. These findings expand the clinical and biological relevance of GTP cycloydrolase 1 deficiency, suggesting that it not only leads to biochemical striatal dopamine depletion and DOPA-responsive dystonia, but also predisposes to nigrostriatal cell loss. Further insight into GCH1-associated pathogenetic mechanisms will shed light on the role of dopamine metabolism in nigral degeneration and Parkinson's disease.This study was supported by the Wellcome Trust/Medical Research Council (MRC) Joint Call in Neurodegeneration award (WT089698) to the UK Parkinson's Disease Consortium. This project was also supported by the National Institute for Health Research University College London Hospitals Biomedical Research Centre and the Grigioni Foundation for Parkinson Disease. This work was also supported in part by the Intramural Research Programs of the National Institute of Neurological Disorders and Stroke (NINDS), the National Institute on Aging (NIA), and the National Institute of Environmental Health Sciences both part of the National Institutes of Health, Department of Health and Human Services; project numbers Z01-AG000949-02 and Z01-ES101986. In addition this work was supported by the Department of Defense (award W81XWH-09-2-0128), and the Michael J Fox Foundation for Parkinson’s Disease Research. This work was supported by National Institutes of Health grants R01NS037167, R01CA141668, American Parkinson Disease Association (APDA); Barnes Jewish Hospital Foundation; Greater St Louis Chapter of the APDA; Hersenstichting Nederland; Neuroscience Campus Amsterdam; the Deutsche Forschungsgemeinschaft (SFB 936). This study was also funded by the German National Genome Network (NGFNplus number 01GS08134, German Ministry for Education and Research); by the German Federal Ministry of Education and Research (NGFN 01GR0468, PopGen); and 01EW0908 in the frame of ERA-NET NEURON and Helmholtz Alliance Mental Health in an Ageing Society (HA-215), which was funded by the Initiative and Networking Fund of the Helmholtz Association. Funding for the project was provided by the Wellcome Trust under award 076113, 085475 and 090355. The work was also funded in part by Parkinson's UK (Grants 8047 and J-1101) and the Medical Research Council UK (G0700943, G1100643) for H.R.M and S.J.L

Genome-wide survival study identifies a novel synaptic locus and polygenic score for cognitive progression in Parkinson's disease

A key driver of patients' well-being and clinical trials for Parkinson's disease (PD) is the course that the disease takes over time (progression and prognosis). To assess how genetic variation influences the progression of PD over time to dementia, a major determinant for quality of life, we performed a longitudinal genome-wide survival study of 11.2 million variants in 3,821 patients with PD over 31,053 visits. We discover RIMS2 as a progression locus and confirm this in a replicate population (hazard ratio (HR) = 4.77, P = 2.78 x 10(-11)), identify suggestive evidence for TMEM108 (HR = 2.86, P = 2.09 x 10(-8)) and WWOX (HR = 2.12, P = 2.37 x 10(-8)) as progression loci, and confirm associations for GBA (HR = 1.93, P = 0.0002) and APOE (HR = 1.48, P = 0.001). Polygenic progression scores exhibit a substantial aggregate association with dementia risk, while polygenic susceptibility scores are not predictive. This study identifies a novel synaptic locus and polygenic score for cognitive disease progression in PD and proposes diverging genetic architectures of progression and susceptibility.A genome-wide survival study identifies variants at RIMS2 associated with progression of Parkinson's disease to dementia and highlights divergence in the genetic architecture of disease onset and progression.Neurological Motor Disorder

A blood atlas of COVID-19 defines hallmarks of disease severity and specificity.

Treatment of severe COVID-19 is currently limited by clinical heterogeneity and incomplete description of specific immune biomarkers. We present here a comprehensive multi-omic blood atlas for patients with varying COVID-19 severity in an integrated comparison with influenza and sepsis patients versus healthy volunteers. We identify immune signatures and correlates of host response. Hallmarks of disease severity involved cells, their inflammatory mediators and networks, including progenitor cells and specific myeloid and lymphocyte subsets, features of the immune repertoire, acute phase response, metabolism, and coagulation. Persisting immune activation involving AP-1/p38MAPK was a specific feature of COVID-19. The plasma proteome enabled sub-phenotyping into patient clusters, predictive of severity and outcome. Systems-based integrative analyses including tensor and matrix decomposition of all modalities revealed feature groupings linked with severity and specificity compared to influenza and sepsis. Our approach and blood atlas will support future drug development, clinical trial design, and personalized medicine approaches for COVID-19