Models and methods: a perspective of the impact of six IMI translational data-centric initiatives for Alzheimer’s disease and other neuropsychiatric disorders

The Innovative Medicines Initiative (IMI), was a European public–private partnership (PPP) undertaking intended to improve the drug development process, facilitate biomarker development, accelerate clinical trial timelines, improve success rates, and generally increase the competitiveness of European pharmaceutical sector research. Through the IMI, pharmaceutical research interests and the research agenda of the EU are supported by academic partnership and financed by both the pharmaceutical companies and public funds. Since its inception, the IMI has funded dozens of research partnerships focused on solving the core problems that have consistently obstructed the translation of research into clinical success. In this post-mortem review paper, we focus on six research initiatives that tackled foundational challenges of this nature: Aetionomy, EMIF, EPAD, EQIPD, eTRIKS, and PRISM. Several of these initiatives focused on neurodegenerative diseases; we therefore discuss the state of neurodegenerative research both at the start of the IMI and now, and the contributions that IMI partnerships made to progress in the field. Many of the initiatives we review had goals including, but not limited to, the establishment of translational, data-centric initiatives and the implementation of trans-diagnostic approaches that move beyond the candidate disease approach to assess symptom etiology without bias, challenging the construct of disease diagnosis. We discuss the successes of these initiatives, the challenges faced, and the merits and shortcomings of the IMI approach with participating senior scientists for each. Here, we distill their perspectives on the lessons learned, with an aim to positively impact funding policy and approaches in the future

Insights into the Musa genome: Syntenic relationships to rice and between Musa species

<p>Abstract</p> <p>Background</p> <p><it>Musa </it>species (Zingiberaceae, Zingiberales) including bananas and plantains are collectively the fourth most important crop in developing countries. Knowledge concerning <it>Musa </it>genome structure and the origin of distinct cultivars has greatly increased over the last few years. Until now, however, no large-scale analyses of <it>Musa </it>genomic sequence have been conducted. This study compares genomic sequence in two <it>Musa </it>species with orthologous regions in the rice genome.</p> <p>Results</p> <p>We produced 1.4 Mb of <it>Musa </it>sequence from 13 BAC clones, annotated and analyzed them along with 4 previously sequenced BACs. The 443 predicted genes revealed that Zingiberales genes share GC content and distribution characteristics with eudicot and Poaceae genomes. Comparison with rice revealed microsynteny regions that have persisted since the divergence of the Commelinid orders Poales and Zingiberales at least 117 Mya. The previously hypothesized large-scale duplication event in the common ancestor of major cereal lineages within the Poaceae was verified. The divergence time distributions for <it>Musa</it>-Zingiber (Zingiberaceae, Zingiberales) orthologs and paralogs provide strong evidence for a large-scale duplication event in the <it>Musa </it>lineage after its divergence from the Zingiberaceae approximately 61 Mya. Comparisons of genomic regions from <it>M. acuminata </it>and <it>M. balbisiana </it>revealed highly conserved genome structure, and indicated that these genomes diverged circa 4.6 Mya.</p> <p>Conclusion</p> <p>These results point to the utility of comparative analyses between distantly-related monocot species such as rice and <it>Musa </it>for improving our understanding of monocot genome evolution. Sequencing the genome of <it>M. acuminata </it>would provide a strong foundation for comparative genomics in the monocots. In addition a genome sequence would aid genomic and genetic analyses of cultivated <it>Musa </it>polyploid genotypes in research aimed at localizing and cloning genes controlling important agronomic traits for breeding purposes.</p

Enhancing Discovery of Genetic Variants for Posttraumatic Stress Disorder Through Integration of Quantitative Phenotypes and Trauma Exposure Information

Funding Information: This work was supported by the National Institute of Mental Health / U.S. Army Medical Research and Development Command (Grant No. R01MH106595 [to CMN, IL, MBS, KJRe, and KCK], National Institutes of Health (Grant No. 5U01MH109539 to the Psychiatric Genomics Consortium ), and Brain & Behavior Research Foundation (Young Investigator Grant [to KWC]). Genotyping of samples was provided in part through the Stanley Center for Psychiatric Genetics at the Broad Institute supported by Cohen Veterans Bioscience . Statistical analyses were carried out on the LISA/Genetic Cluster Computer ( https://userinfo.surfsara.nl/systems/lisa ) hosted by SURFsara. This research has been conducted using the UK Biobank resource (Application No. 41209). This work would have not been possible without the financial support provided by Cohen Veterans Bioscience, the Stanley Center for Psychiatric Genetics at the Broad Institute, and One Mind. Funding Information: MBS has in the past 3 years received consulting income from Actelion, Acadia Pharmaceuticals, Aptinyx, Bionomics, BioXcel Therapeutics, Clexio, EmpowerPharm, GW Pharmaceuticals, Janssen, Jazz Pharmaceuticals, and Roche/Genentech and has stock options in Oxeia Biopharmaceuticals and Epivario. In the past 3 years, NPD has held a part-time paid position at Cohen Veterans Bioscience, has been a consultant for Sunovion Pharmaceuticals, and is on the scientific advisory board for Sentio Solutions for unrelated work. In the past 3 years, KJRe has been a consultant for Datastat, Inc., RallyPoint Networks, Inc., Sage Pharmaceuticals, and Takeda. JLM-K has received funding and a speaking fee from COMPASS Pathways. MU has been a consultant for System Analytic. HRK is a member of the Dicerna scientific advisory board and a member of the American Society of Clinical Psychopharmacology Alcohol Clinical Trials Initiative, which during the past 3 years was supported by Alkermes, Amygdala Neurosciences, Arbor Pharmaceuticals, Dicerna, Ethypharm, Indivior, Lundbeck, Mitsubishi, and Otsuka. HRK and JG are named as inventors on Patent Cooperative Treaty patent application number 15/878,640, entitled “Genotype-guided dosing of opioid agonists,” filed January 24, 2018. RP and JG are paid for their editorial work on the journal Complex Psychiatry. OAA is a consultant to HealthLytix. All other authors report no biomedical financial interests or potential conflicts of interest. Funding Information: This work was supported by the National Institute of Mental Health/ U.S. Army Medical Research and Development Command (Grant No. R01MH106595 [to CMN, IL, MBS, KJRe, and KCK], National Institutes of Health (Grant No. 5U01MH109539 to the Psychiatric Genomics Consortium), and Brain & Behavior Research Foundation (Young Investigator Grant [to KWC]). Genotyping of samples was provided in part through the Stanley Center for Psychiatric Genetics at the Broad Institute supported by Cohen Veterans Bioscience. Statistical analyses were carried out on the LISA/Genetic Cluster Computer (https://userinfo.surfsara.nl/systems/lisa) hosted by SURFsara. This research has been conducted using the UK Biobank resource (Application No. 41209). This work would have not been possible without the financial support provided by Cohen Veterans Bioscience, the Stanley Center for Psychiatric Genetics at the Broad Institute, and One Mind. This material has been reviewed by the Walter Reed Army Institute of Research. There is no objection to its presentation and/or publication. The opinions or assertions contained herein are the private views of the authors and are not to be construed as official or as reflecting true views of the U.S. Department of the Army or the Department of Defense. We thank the investigators who comprise the PGC-PTSD working group and especially the more than 206,000 research participants worldwide who shared their life experiences and biological samples with PGC-PTSD investigators. We thank Mark Zervas for his critical input. Full acknowledgments are in Supplement 1. MBS has in the past 3 years received consulting income from Actelion, Acadia Pharmaceuticals, Aptinyx, Bionomics, BioXcel Therapeutics, Clexio, EmpowerPharm, GW Pharmaceuticals, Janssen, Jazz Pharmaceuticals, and Roche/Genentech and has stock options in Oxeia Biopharmaceuticals and Epivario. In the past 3 years, NPD has held a part-time paid position at Cohen Veterans Bioscience, has been a consultant for Sunovion Pharmaceuticals, and is on the scientific advisory board for Sentio Solutions for unrelated work. In the past 3 years, KJRe has been a consultant for Datastat, Inc. RallyPoint Networks, Inc. Sage Pharmaceuticals, and Takeda. JLM-K has received funding and a speaking fee from COMPASS Pathways. MU has been a consultant for System Analytic. HRK is a member of the Dicerna scientific advisory board and a member of the American Society of Clinical Psychopharmacology Alcohol Clinical Trials Initiative, which during the past 3 years was supported by Alkermes, Amygdala Neurosciences, Arbor Pharmaceuticals, Dicerna, Ethypharm, Indivior, Lundbeck, Mitsubishi, and Otsuka. HRK and JG are named as inventors on Patent Cooperative Treaty patent application number 15/878,640, entitled ?Genotype-guided dosing of opioid agonists,? filed January 24, 2018. RP and JG are paid for their editorial work on the journal Complex Psychiatry. OAA is a consultant to HealthLytix. All other authors report no biomedical financial interests or potential conflicts of interest. Publisher Copyright: © 2021 Society of Biological PsychiatryBackground: Posttraumatic stress disorder (PTSD) is heritable and a potential consequence of exposure to traumatic stress. Evidence suggests that a quantitative approach to PTSD phenotype measurement and incorporation of lifetime trauma exposure (LTE) information could enhance the discovery power of PTSD genome-wide association studies (GWASs). Methods: A GWAS on PTSD symptoms was performed in 51 cohorts followed by a fixed-effects meta-analysis (N = 182,199 European ancestry participants). A GWAS of LTE burden was performed in the UK Biobank cohort (N = 132,988). Genetic correlations were evaluated with linkage disequilibrium score regression. Multivariate analysis was performed using Multi-Trait Analysis of GWAS. Functional mapping and annotation of leading loci was performed with FUMA. Replication was evaluated using the Million Veteran Program GWAS of PTSD total symptoms. Results: GWASs of PTSD symptoms and LTE burden identified 5 and 6 independent genome-wide significant loci, respectively. There was a 72% genetic correlation between PTSD and LTE. PTSD and LTE showed largely similar patterns of genetic correlation with other traits, albeit with some distinctions. Adjusting PTSD for LTE reduced PTSD heritability by 31%. Multivariate analysis of PTSD and LTE increased the effective sample size of the PTSD GWAS by 20% and identified 4 additional loci. Four of these 9 PTSD loci were independently replicated in the Million Veteran Program. Conclusions: Through using a quantitative trait measure of PTSD, we identified novel risk loci not previously identified using prior case-control analyses. PTSD and LTE have a high genetic overlap that can be leveraged to increase discovery power through multivariate methods.publishersversionpublishe

An open-label, multicenter evaluation of the long-term safety and efficacy of risperidone in adolescents with schizophrenia

<p>Abstract</p> <p>Background</p> <p>Data on the long-term efficacy, safety, and tolerability of risperidone in adolescents with schizophrenia are limited. The objective of this study was to evaluate the efficacy and safety of maintenance risperidone treatment in adolescents with schizophrenia.</p> <p>Methods</p> <p>This open-label study of adolescents aged 13 to 17 years with schizophrenia was a single extension study of two short-term double-blind risperidone studies and also enrolled subjects directly in open-label risperidone treatment. The risperidone dose was flexible and ranged from 2 to 6 mg/day. Most subjects enrolled for 6 months; a subset enrolled for 12 months. Assessment tools included the Positive and Negative Syndrome Scale total and factor scores, Clinical Global Impressions, Children’s Global Assessment Scale, adverse event (AE) monitoring, vital signs, laboratory testing, and extrapyramidal symptom rating scales.</p> <p>Results</p> <p>A total of 390 subjects were enrolled; 48 subjects had received placebo in a previous double-blind study; 292 subjects had received risperidone as part of their participation in one of two previous controlled studies; and 50 subjects were enrolled directly for this study. A total of 279 subjects enrolled for 6 months of treatment, and 111 subjects enrolled for 12 months of treatment. Overall, 264 (67.7%) subjects completed this study: 209 of the 279 subjects (75%) in the 6-month group and 55 of the 111 subjects (50%) in the 12-month group. The median mode dose was 3.8 mg/day. At 6 months, all three groups experienced improvement from open-label baseline in symptoms of schizophrenia as well as general assessments of global functioning. Improvements were generally maintained for the duration of treatment. The most common AEs (≥10% of subjects) were somnolence, headache, weight increase, hypertonia, insomnia, tremor, and psychosis. Potentially prolactin-related AEs (PPAEs) were reported by 36 (9%) subjects. The AE profile in this study was qualitatively similar to those of other studies in adult subjects with schizophrenia and in other psychiatric studies of risperidone in pediatric populations.</p> <p>Conclusions</p> <p>Risperidone maintenance treatment in adolescents over 6 to 12 months was well tolerated, consistent with related studies in this clinical population, and associated with continued efficacy.</p> <p>Clinical trials</p> <p>ClinicalTrials.gov registration number: NCT00246285 <url>http://clinicaltrials.gov/ct2/show/NCT00246285?term=NCT00246285&rank=1</url></p

The preclinical data forum network : A new ECNP initiative to improve data quality and robustness for (preclinical) neuroscience

Current limitations impeding on data reproducibility are often poor statistical design, underpowered studies, lack of robust data, lack of methodological detail, biased reporting and lack of open data sharing, coupled with wrong research incentives. To improve data reproducibility, robustness and quality for brain disease research, a Preclinical Data Forum Network was formed under the umbrella of the European College of Neuropsychopharmacology (ECNP). The goal of this network, members of which met for the first time in October 2014, is to establish a forum to collaborate in precompetitive space, to exchange and develop best practices, and to bring together the members from academia, pharmaceutical industry, publishers, journal editors, funding organizations, public/private partnerships and non-profit advocacy organizations. To address the most pertinent issues identified by the Network, it was decided to establish a data sharing platform that allows open exchange of information in the area of preclinical neuroscience and to develop an educational scientific program. It is also planned to reach out to other organizations to align initiatives to enhance efficiency, and to initiate activities to improve the clinical relevance of preclinical data. Those Network activities should contribute to scientific rigor and lead to robust and relevant translational data. Here we provide a synopsis of the proceedings from the inaugural meeting

Deep Learning for Daily Monitoring of Parkinson&rsquo;s Disease Outside the Clinic Using Wearable Sensors

Now that wearable sensors have become more commonplace, it is possible to monitor individual healthcare-related activity outside the clinic, unleashing potential for early detection of events in diseases such as Parkinson&rsquo;s disease (PD). However, the unsupervised and &ldquo;open world&rdquo; nature of this type of data collection make such applications difficult to develop. In this proof-of-concept study, we used inertial sensor data from Verily Study Watches worn by individuals for up to 23 h per day over several months to distinguish between seven subjects with PD and four without. Since motor-related PD symptoms such as bradykinesia and gait abnormalities typically present when a PD subject is walking, we initially used human activity recognition (HAR) techniques to identify walk-like activity in the unconstrained, unlabeled data. We then used these &ldquo;walk-like&rdquo; events to train one-dimensional convolutional neural networks (1D-CNNs) to determine the presence of PD. We report classification accuracies near 90% on single 5-s walk-like events and 100% accuracy when taking the majority vote over single-event classifications that span a duration of one day. Though based on a small cohort, this study shows the feasibility of leveraging unconstrained wearable sensor data to accurately detect the presence or absence of PD

Attractivité des carrières scientifiques et technologiques.: Identification des freins et proposition de leviers d'action

L'étude menée à l'initiative du Haut Conseil de la Science et de la Technologie sur l'attractivité des carrières scientifiques et technologiques a permis une approche globale de cette question. Les facteurs susceptibles d'avoir un impact significatif sur cette attractivité ont pu être identifiés, analysés et regroupés dans sept champs d'action qui sont plus ou moins liés les uns aux autres : 1) acquisition des compétences et système éducatif 2) connaissance des métiers et orientation 3) caractéristiques de l'emploi scientifique et technologique 4) perspectives de mobilité des acteurs de la recherche 5) perceptions et représentations sociales des sciences et des technologies 6) pratiques de médiation scientifique et technologique 7) pilotage et suivi des mesures en faveur de l'attractivité des carrières scientifiques et technologiques