Real-World Gait Detection Using a Wrist-Worn Inertial Sensor: Validation Study.

BACKGROUND: Wrist-worn inertial sensors are used in digital health for evaluating mobility in real-world environments. Preceding the estimation of spatiotemporal gait parameters within long-term recordings, gait detection is an important step to identify regions of interest where gait occurs, which requires robust algorithms due to the complexity of arm movements. While algorithms exist for other sensor positions, a comparative validation of algorithms applied to the wrist position on real-world data sets across different disease populations is missing. Furthermore, gait detection performance differences between the wrist and lower back position have not yet been explored but could yield valuable information regarding sensor position choice in clinical studies. OBJECTIVE: The aim of this study was to validate gait sequence (GS) detection algorithms developed for the wrist position against reference data acquired in a real-world context. In addition, this study aimed to compare the performance of algorithms applied to the wrist position to those applied to lower back-worn inertial sensors. METHODS: Participants with Parkinson disease, multiple sclerosis, proximal femoral fracture (hip fracture recovery), chronic obstructive pulmonary disease, and congestive heart failure and healthy older adults (N=83) were monitored for 2.5 hours in the real-world using inertial sensors on the wrist, lower back, and feet including pressure insoles and infrared distance sensors as reference. In total, 10 algorithms for wrist-based gait detection were validated against a multisensor reference system and compared to gait detection performance using lower back-worn inertial sensors. RESULTS: The best-performing GS detection algorithm for the wrist showed a mean (per disease group) sensitivity ranging between 0.55 (SD 0.29) and 0.81 (SD 0.09) and a mean (per disease group) specificity ranging between 0.95 (SD 0.06) and 0.98 (SD 0.02). The mean relative absolute error of estimated walking time ranged between 8.9% (SD 7.1%) and 32.7% (SD 19.2%) per disease group for this algorithm as compared to the reference system. Gait detection performance from the best algorithm applied to the wrist inertial sensors was lower than for the best algorithms applied to the lower back, which yielded mean sensitivity between 0.71 (SD 0.12) and 0.91 (SD 0.04), mean specificity between 0.96 (SD 0.03) and 0.99 (SD 0.01), and a mean relative absolute error of estimated walking time between 6.3% (SD 5.4%) and 23.5% (SD 13%). Performance was lower in disease groups with major gait impairments (eg, patients recovering from hip fracture) and for patients using bilateral walking aids. CONCLUSIONS: Algorithms applied to the wrist position can detect GSs with high performance in real-world environments. Those periods of interest in real-world recordings can facilitate gait parameter extraction and allow the quantification of gait duration distribution in everyday life. Our findings allow taking informed decisions on alternative positions for gait recording in clinical studies and public health. TRIAL REGISTRATION: ISRCTN Registry 12246987; https://www.isrctn.com/ISRCTN12246987. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2021-050785.

Mobilise-D insights to estimate real-world walking speed in multiple conditions with a wearable device.

This study aimed to validate a wearable device's walking speed estimation pipeline, considering complexity, speed, and walking bout duration. The goal was to provide recommendations on the use of wearable devices for real-world mobility analysis. Participants with Parkinson's Disease, Multiple Sclerosis, Proximal Femoral Fracture, Chronic Obstructive Pulmonary Disease, Congestive Heart Failure, and healthy older adults (n = 97) were monitored in the laboratory and the real-world (2.5 h), using a lower back wearable device. Two walking speed estimation pipelines were validated across 4408/1298 (2.5 h/laboratory) detected walking bouts, compared to 4620/1365 bouts detected by a multi-sensor reference system. In the laboratory, the mean absolute error (MAE) and mean relative error (MRE) for walking speed estimation ranged from 0.06 to 0.12 m/s and - 2.1 to 14.4%, with ICCs (Intraclass correlation coefficients) between good (0.79) and excellent (0.91). Real-world MAE ranged from 0.09 to 0.13, MARE from 1.3 to 22.7%, with ICCs indicating moderate (0.57) to good (0.88) agreement. Lower errors were observed for cohorts without major gait impairments, less complex tasks, and longer walking bouts. The analytical pipelines demonstrated moderate to good accuracy in estimating walking speed. Accuracy depended on confounding factors, emphasizing the need for robust technical validation before clinical application.Trial registration: ISRCTN - 12246987.

Laboratory and free-living gait performance in adults with COPD and healthy controls.

Background: Gait characteristics are important risk factors for falls, hospitalisations and mortality in older adults, but the impact of COPD on gait performance remains unclear. We aimed to identify differences in gait characteristics between adults with COPD and healthy age-matched controls during 1) laboratory tests that included complex movements and obstacles, 2) simulated daily-life activities (supervised) and 3) free-living daily-life activities (unsupervised). Methods: This case-control study used a multi-sensor wearable system (INDIP) to obtain seven gait characteristics for each walking bout performed by adults with mild-to-severe COPD (n=17; forced expiratory volume in 1 s 57±19% predicted) and controls (n=20) during laboratory tests, and during simulated and free-living daily-life activities. Gait characteristics were compared between adults with COPD and healthy controls for all walking bouts combined, and for shorter (≤30 s) and longer (>30 s) walking bouts separately. Results: Slower walking speed (-11 cm·s-1, 95% CI: -20 to -3) and lower cadence (-6.6 steps·min-1, 95% CI: -12.3 to -0.9) were recorded in adults with COPD compared to healthy controls during longer (>30 s) free-living walking bouts, but not during shorter (≤30 s) walking bouts in either laboratory or free-living settings. Double support duration and gait variability measures were generally comparable between the two groups. Conclusion: Gait impairment of adults with mild-to-severe COPD mainly manifests during relatively long walking bouts (>30 s) in free-living conditions. Future research should determine the underlying mechanism(s) of this impairment to facilitate the development of interventions that can improve free-living gait performance in adults with COPD.

Assessing real-world gait with digital technology? Validation, insights and recommendations from the Mobilise-D consortium.

BACKGROUND: Although digital mobility outcomes (DMOs) can be readily calculated from real-world data collected with wearable devices and ad-hoc algorithms, technical validation is still required. The aim of this paper is to comparatively assess and validate DMOs estimated using real-world gait data from six different cohorts, focusing on gait sequence detection, foot initial contact detection (ICD), cadence (CAD) and stride length (SL) estimates. METHODS: Twenty healthy older adults, 20 people with Parkinson's disease, 20 with multiple sclerosis, 19 with proximal femoral fracture, 17 with chronic obstructive pulmonary disease and 12 with congestive heart failure were monitored for 2.5 h in the real-world, using a single wearable device worn on the lower back. A reference system combining inertial modules with distance sensors and pressure insoles was used for comparison of DMOs from the single wearable device. We assessed and validated three algorithms for gait sequence detection, four for ICD, three for CAD and four for SL by concurrently comparing their performances (e.g., accuracy, specificity, sensitivity, absolute and relative errors). Additionally, the effects of walking bout (WB) speed and duration on algorithm performance were investigated. RESULTS: We identified two cohort-specific top performing algorithms for gait sequence detection and CAD, and a single best for ICD and SL. Best gait sequence detection algorithms showed good performances (sensitivity > 0.73, positive predictive values > 0.75, specificity > 0.95, accuracy > 0.94). ICD and CAD algorithms presented excellent results, with sensitivity > 0.79, positive predictive values > 0.89 and relative errors < 11% for ICD and < 8.5% for CAD. The best identified SL algorithm showed lower performances than other DMOs (absolute error < 0.21 m). Lower performances across all DMOs were found for the cohort with most severe gait impairments (proximal femoral fracture). Algorithms' performances were lower for short walking bouts; slower gait speeds (< 0.5 m/s) resulted in reduced performance of the CAD and SL algorithms. CONCLUSIONS: Overall, the identified algorithms enabled a robust estimation of key DMOs. Our findings showed that the choice of algorithm for estimation of gait sequence detection and CAD should be cohort-specific (e.g., slow walkers and with gait impairments). Short walking bout length and slow walking speed worsened algorithms' performances. Trial registration ISRCTN - 12246987.

A multi-sensor wearable system for the assessment of diseased gait in real-world conditions.

Introduction: Accurately assessing people's gait, especially in real-world conditions and in case of impaired mobility, is still a challenge due to intrinsic and extrinsic factors resulting in gait complexity. To improve the estimation of gait-related digital mobility outcomes (DMOs) in real-world scenarios, this study presents a wearable multi-sensor system (INDIP), integrating complementary sensing approaches (two plantar pressure insoles, three inertial units and two distance sensors). Methods: The INDIP technical validity was assessed against stereophotogrammetry during a laboratory experimental protocol comprising structured tests (including continuous curvilinear and rectilinear walking and steps) and a simulation of daily-life activities (including intermittent gait and short walking bouts). To evaluate its performance on various gait patterns, data were collected on 128 participants from seven cohorts: healthy young and older adults, patients with Parkinson's disease, multiple sclerosis, chronic obstructive pulmonary disease, congestive heart failure, and proximal femur fracture. Moreover, INDIP usability was evaluated by recording 2.5-h of real-world unsupervised activity. Results and discussion: Excellent absolute agreement (ICC >0.95) and very limited mean absolute errors were observed for all cohorts and digital mobility outcomes (cadence ≤0.61 steps/min, stride length ≤0.02 m, walking speed ≤0.02 m/s) in the structured tests. Larger, but limited, errors were observed during the daily-life simulation (cadence 2.72-4.87 steps/min, stride length 0.04-0.06 m, walking speed 0.03-0.05 m/s). Neither major technical nor usability issues were declared during the 2.5-h acquisitions. Therefore, the INDIP system can be considered a valid and feasible solution to collect reference data for analyzing gait in real-world conditions.

Reverse Engineering of Digital Measures: Inviting Patients to the Conversation.

Background: Digital measures offer an unparalleled opportunity to create a more holistic picture of how people who are patients behave in their real-world environments, thereby establishing a better connection between patients, caregivers, and the clinical evidence used to drive drug development and disease management. Reaching this vision will require achieving a new level of co-creation between the stakeholders who design, develop, use, and make decisions using evidence from digital measures. Summary: In September 2022, the second in a series of meetings hosted by the Swiss Federal Institute of Technology in Zürich, the Foundation for the National Institutes of Health Biomarkers Consortium, and sponsored by Wellcome Trust, entitled "Reverse Engineering of Digital Measures," was held in Zurich, Switzerland, with a broad range of stakeholders sharing their experience across four case studies to examine how patient centricity is essential in shaping development and validation of digital evidence generation tools. Key Messages: In this paper, we discuss progress and the remaining barriers to widespread use of digital measures for evidence generation in clinical development and care delivery. We also present key discussion points and takeaways in order to continue discourse and provide a basis for dissemination and outreach to the wider community and other stakeholders. The work presented here shows us a blueprint for how and why the patient voice can be thoughtfully integrated into digital measure development and that continued multistakeholder engagement is critical for further progress.

Design and validation of a multi-task, multi-context protocol for real-world gait simulation.

BACKGROUND: Measuring mobility in daily life entails dealing with confounding factors arising from multiple sources, including pathological characteristics, patient specific walking strategies, environment/context, and purpose of the task. The primary aim of this study is to propose and validate a protocol for simulating real-world gait accounting for all these factors within a single set of observations, while ensuring minimisation of participant burden and safety. METHODS: The protocol included eight motor tasks at varying speed, incline/steps, surface, path shape, cognitive demand, and included postures that may abruptly alter the participants' strategy of walking. It was deployed in a convenience sample of 108 participants recruited from six cohorts that included older healthy adults (HA) and participants with potentially altered mobility due to Parkinson's disease (PD), multiple sclerosis (MS), proximal femoral fracture (PFF), chronic obstructive pulmonary disease (COPD) or congestive heart failure (CHF). A novelty introduced in the protocol was the tiered approach to increase difficulty both within the same task (e.g., by allowing use of aids or armrests) and across tasks. RESULTS: The protocol proved to be safe and feasible (all participants could complete it and no adverse events were recorded) and the addition of the more complex tasks allowed a much greater spread in walking speeds to be achieved compared to standard straight walking trials. Furthermore, it allowed a representation of a variety of daily life relevant mobility aspects and can therefore be used for the validation of monitoring devices used in real life. CONCLUSIONS: The protocol allowed for measuring gait in a variety of pathological conditions suggests that it can also be used to detect changes in gait due to, for example, the onset or progression of a disease, or due to therapy. TRIAL REGISTRATION: ISRCTN-12246987.

Technical validation of real-world monitoring of gait: a multicentric observational study.

INTRODUCTION: Existing mobility endpoints based on functional performance, physical assessments and patient self-reporting are often affected by lack of sensitivity, limiting their utility in clinical practice. Wearable devices including inertial measurement units (IMUs) can overcome these limitations by quantifying digital mobility outcomes (DMOs) both during supervised structured assessments and in real-world conditions. The validity of IMU-based methods in the real-world, however, is still limited in patient populations. Rigorous validation procedures should cover the device metrological verification, the validation of the algorithms for the DMOs computation specifically for the population of interest and in daily life situations, and the users' perspective on the device. METHODS AND ANALYSIS: This protocol was designed to establish the technical validity and patient acceptability of the approach used to quantify digital mobility in the real world by Mobilise-D, a consortium funded by the European Union (EU) as part of the Innovative Medicine Initiative, aiming at fostering regulatory approval and clinical adoption of DMOs.After defining the procedures for the metrological verification of an IMU-based device, the experimental procedures for the validation of algorithms used to calculate the DMOs are presented. These include laboratory and real-world assessment in 120 participants from five groups: healthy older adults; chronic obstructive pulmonary disease, Parkinson's disease, multiple sclerosis, proximal femoral fracture and congestive heart failure. DMOs extracted from the monitoring device will be compared with those from different reference systems, chosen according to the contexts of observation. Questionnaires and interviews will evaluate the users' perspective on the deployed technology and relevance of the mobility assessment. ETHICS AND DISSEMINATION: The study has been granted ethics approval by the centre's committees (London-Bloomsbury Research Ethics committee; Helsinki Committee, Tel Aviv Sourasky Medical Centre; Medical Faculties of The University of Tübingen and of the University of Kiel). Data and algorithms will be made publicly available. TRIAL REGISTRATION NUMBER: ISRCTN (12246987).

Evaluation of two in vitro assays for tumorigenicity assessment of CRISPR-Cas9 genome-edited cells.

Off-target editing is one of the main safety concerns for the use of CRISPR-Cas9 genome editing in gene therapy. These unwanted modifications could lead to malignant transformation, which renders tumorigenicity assessment of gene therapy products indispensable. In this study, we established two in vitro transformation assays, the soft agar colony-forming assay (SACF) and the growth in low attachment assay (GILA) as alternative methods for tumorigenicity evaluation of genome-edited cells. Using a CRISPR-Cas9-based approach to transform immortalized MCF10A cells, we identified PTPN12, a known tumor suppressor, as a valid positive control in GILA and SACF. Next, we measured the limit of detection for both assays and proved that SACF is more sensitive than GILA (0.8% versus 3.1% transformed cells). We further validated SACF and GILA by identifying a set of positive and negative controls and by testing the suitability of another cell line (THLE-2). Moreover, in contrast to SACF and GILA, an in vivo tumorigenicity study failed to detect the known tumorigenic potential of PTPN12 deletion, demonstrating the relevance of GILA and SACF in tumorigenicity testing. In conclusion, SACF and GILA are both attractive and valuable additions to preclinical safety assessment of gene therapy products.

Digital endpoints for self-administered home-based functional assessment in pediatric Friedreich's ataxia.

BACKGROUND: Friedreich's ataxia is an inherited, progressive, neurodegenerative disease that typically begins in childhood. Disease severity is commonly assessed with rating scales, such as the modified Friedreich's Ataxia Rating Scale, which are usually administered in the clinic by a neurology specialist. OBJECTIVE: This study evaluated the utility of home-based, self-administered digital endpoints in children with Friedreich's ataxia and unaffected controls and their relationship to standard clinical rating scales. METHODS: In a cross-sectional study with 25 participants (13 with Friedreich's ataxia and 12 unaffected controls, aged 6-15 years), home-based digital endpoints that reflect activities of daily living were recorded over 1 week. Domains analyzed were hand motor function with a digitized drawing, automated analysis of speech with a recorded oral diadochokinesis test, and gait and balance with wearable sensors. RESULTS: Hand-drawing and speech tests were easy to conduct and generated high-quality data. The sensor-based gait and balance tests suffered from technical limitations in this study setup. Several parameters discriminated between groups or correlated strongly with modified Friedreich's Ataxia Rating Scale total score and activities of daily living total score in the Friedreich's ataxia group. Hand-drawing parameters also strongly correlated with standard 9-hole peg test scores. INTERPRETATION: Deploying digital endpoints in home settings is feasible in this population, results in meaningful and robust data collection, and may allow for frequent sampling over longer periods of time to track disease progression. Care must be taken when training participants, and investigators should consider the complexity of the tasks and equipment used.

A Roadmap to Inform Development, Validation and Approval of Digital Mobility Outcomes: The Mobilise-D Approach.

Health care has had to adapt rapidly to COVID-19, and this in turn has highlighted a pressing need for tools to facilitate remote visits and monitoring. Digital health technology, including body-worn devices, offers a solution using digital outcomes to measure and monitor disease status and provide outcomes meaningful to both patients and health care professionals. Remote monitoring of physical mobility is a prime example, because mobility is among the most advanced modalities that can be assessed digitally and remotely. Loss of mobility is also an important feature of many health conditions, providing a read-out of health as well as a target for intervention. Real-world, continuous digital measures of mobility (digital mobility outcomes or DMOs) provide an opportunity for novel insights into health care conditions complementing existing mobility measures. Accepted and approved DMOs are not yet widely available. The need for large collaborative efforts to tackle the critical steps to adoption is widely recognised. Mobilise-D is an example. It is a multidisciplinary consortium of 34 institutions from academia and industry funded through the European Innovative Medicines Initiative 2 Joint Undertaking. Members of Mobilise-D are collaborating to address the critical steps for DMOs to be adopted in clinical trials and ultimately health care. To achieve this, the consortium has developed a roadmap to inform the development, validation and approval of DMOs in Parkinson's disease, multiple sclerosis, chronic obstructive pulmonary disease and recovery from proximal femoral fracture. Here we aim to describe the proposed approach and provide a high-level view of the ongoing and planned work of the Mobilise-D consortium. Ultimately, Mobilise-D aims to stimulate widespread adoption of DMOs through the provision of device agnostic software, standards and robust validation in order to bring digital outcomes from concept to use in clinical trials and health care.

Continuous Digital Monitoring of Walking Speed in Frail Elderly Patients: Noninterventional Validation Study and Longitudinal Clinical Trial.

BACKGROUND: Digital technologies and advanced analytics have drastically improved our ability to capture and interpret health-relevant data from patients. However, only limited data and results have been published that demonstrate accuracy in target indications, real-world feasibility, or the validity and value of these novel approaches. OBJECTIVE: This study aimed to establish accuracy, feasibility, and validity of continuous digital monitoring of walking speed in frail, elderly patients with sarcopenia and to create an open source repository of raw, derived, and reference data as a resource for the community. METHODS: Data described here were collected as a part of 2 clinical studies: an independent, noninterventional validation study and a phase 2b interventional clinical trial in older adults with sarcopenia. In both studies, participants were monitored by using a waist-worn inertial sensor. The cross-sectional, independent validation study collected data at a single site from 26 naturally slow-walking elderly subjects during a parcours course through the clinic, designed to simulate a real-world environment. In the phase 2b interventional clinical trial, 217 patients with sarcopenia were recruited across 32 sites globally, where patients were monitored over 25 weeks, both during and between visits. RESULTS: We have demonstrated that our approach can capture in-clinic gait speed in frail slow-walking adults with a residual standard error of 0.08 m per second in the independent validation study and 0.08, 0.09, and 0.07 m per second for the 4 m walk test (4mWT), 6-min walk test (6MWT), and 400 m walk test (400mWT) standard gait speed assessments, respectively, in the interventional clinical trial. We demonstrated the feasibility of our approach by capturing 9668 patient-days of real-world data from 192 patients and 32 sites, as part of the interventional clinical trial. We derived inferred contextual information describing the length of a given walking bout and uncovered positive associations between the short 4mWT gait speed assessment and gait speed in bouts between 5 and 20 steps (correlation of 0.23) and longer 6MWT and 400mWT assessments with bouts of 80 to 640 steps (correlations of 0.48 and 0.59, respectively). CONCLUSIONS: This study showed, for the first time, accurate capture of real-world gait speed in slow-walking older adults with sarcopenia. We demonstrated the feasibility of long-term digital monitoring of mobility in geriatric populations, establishing that sufficient data can be collected to allow robust monitoring of gait behaviors outside the clinic, even in the absence of feedback or incentives. Using inferred context, we demonstrated the ecological validity of in-clinic gait assessments, describing positive associations between in-clinic performance and real-world walking behavior. We make all data available as an open source resource for the community, providing a basis for further study of the relationship between standardized physical performance assessment and real-world behavior and independence.

Drug-induced chromatin accessibility changes associate with sensitivity to liver tumor promotion.

Liver cancer susceptibility varies amongst humans and between experimental animal models because of multiple genetic and epigenetic factors. The molecular characterization of such susceptibilities has the potential to enhance cancer risk assessment of xenobiotic exposures and disease prevention strategies. Here, using DNase I hypersensitivity mapping coupled with transcriptomic profiling, we investigate perturbations in cis-acting gene regulatory elements associated with the early stages of phenobarbital (PB)-mediated liver tumor promotion in susceptible versus resistant mouse strains (B6C3F1 versus C57BL/6J). Integrated computational analyses of strain-selective changes in liver chromatin accessibility underlying PB response reveal differential epigenetic regulation of molecular pathways associated with PB-mediated tumor promotion, including Wnt/ß-catenin signaling. Complementary transcription factor motif analyses reveal mouse strain-selective gene regulatory networks and a novel role for Stat, Smad, and Fox transcription factors in the early stages of PB-mediated tumor promotion. Mapping perturbations in cis-acting gene regulatory elements provides novel insights into the molecular basis for susceptibility to xenobiotic-induced rodent liver tumor promotion and has the potential to enhance mechanism-based cancer risk assessments of xenobiotic exposures.

Validity of accelerometry in step detection and gait speed measurement in orthogeriatric patients.

BACKGROUND: Mobile accelerometry is a powerful and promising option to capture long-term changes in gait in both clinical and real-world scenarios. Increasingly, gait parameters have demonstrated their value as clinical outcome parameters, but validation of these parameters in elderly patients is still limited. OBJECTIVE: The aim of this study was to implement a validation framework appropriate for elderly patients and representative of real-world settings, and to use this framework to test and improve algorithms for mobile accelerometry data in an orthogeriatric population. METHODS: Twenty elderly subjects wearing a 3D-accelerometer completed a parcours imitating a real-world scenario. High-definition video and mobile reference speed capture served to validate different algorithms. RESULTS: Particularly at slow gait speeds, relevant improvements in accuracy have been achieved. Compared to the reference the deviation was less than 1% in step detection and less than 0.05 m/s in gait speed measurements, even for slow walking subjects (< 0.8 m/s). CONCLUSION: With the described setup, algorithms for step and gait speed detection have successfully been validated in an elderly population and demonstrated to have improved performance versus previously published algorithms. These results are promising that long-term and/or real-world measurements are possible with an acceptable accuracy even in elderly frail patients with slow gait speeds.

Continuous Monitoring of Patient Mobility for 18 Months Using Inertial Sensors following Traumatic Knee Injury: A Case Study.

Continuous patient activity monitoring during rehabilitation, enabled by digital technologies, will allow the objective capture of real-world mobility and aligning treatment to each individual's recovery trajectory in real time. To explore the feasibility and added value of such approaches, we present a case study of a 36-year-old male participant monitored continuously for activity levels and gait parameters using a waist-worn inertial sensor following a tibial plateau fracture on the right side, sustained as a result of a high-energy trauma during a sporting accident. During rehabilitation, data were collected for a period of 553 days, with > 80% daytime compliance, until the participant returned to near full mobility. The participant completed a daily diary with the annotation of major events (falls, near falls, cycling periods, or physiotherapy sessions) and key dates in the patient's recovery, including medical interventions, transitioning off crutches, and returning to work. We demonstrate the feasibility of collecting, storing, and mining of continuous digital mobility data and show that such data can detect changes in mobility and provide insights into long-term rehabilitation. We make both raw data and annotations available as a resource with the aspiration that further methods and insights will be built on this initial exploration of added value and continue to demonstrate that continuous monitoring can be deployed to aid rehabilitation.

Optimization of 3-Pyrimidin-4-yl-oxazolidin-2-ones as Allosteric and Mutant Specific Inhibitors of IDH1.

High throughput screening and subsequent hit validation identified 4-isopropyl-3-(2-((1-phenylethyl)amino)pyrimidin-4-yl)oxazolidin-2-one as a potent inhibitor of IDH1R132H. Synthesis of the four separate stereoisomers identified the (S,S)-diastereomer (IDH125, 1f) as the most potent isomer. This also showed reasonable cellular activity and excellent selectivity vs IDH1wt. Initial structure-activity relationship exploration identified the key tolerances and potential for optimization. X-ray crystallography identified a functionally relevant allosteric binding site amenable to inhibitors, which can penetrate the blood-brain barrier, and aided rational optimization. Potency improvement and modulation of the physicochemical properties identified (S,S)-oxazolidinone IDH889 (5x) with good exposure and 2-HG inhibitory activity in a mutant IDH1 xenograft mouse model.

Informed consent in a vulnerable population group: supporting individuals aging with intellectual disability to participate in developing their own health and support programs.

Objective The aim of the present study was to explore the use of complementary consent methodologies to support a potentially vulnerable group of people, namely those aging with intellectual disability, to provide personal input. It was premised on the view that processes to determine capacity for consent, appropriately modified to account for individual capabilities and current circumstances, could facilitate meaningful participation in the development of personal health care plans of people previously excluded from contributing. Methods The present descriptive case study research was undertaken in New South Wales, Australia. A seven-step process for determining capacity for consent was developed, and 10 participants aged between 54 and 73 years with lifelong intellectual disability and health comorbidities were involved. A variety of assistive communication tools was used to support individuals to demonstrate their capacity for giving informed consent. Results After being provided with tailored support mechanisms, seven participants were considered to meet all seven components for determining capacity for consent. Three participants were deemed not to have capacity to give consent regardless of the type of support provided. Conclusions Three critical factors for facilitating personal involvement in decision making for individuals with an intellectual disability were identified: (1) defining consent specifically for the target outcome; (2) outlining the criteria needed for consent to be obtained; and (3) using appropriately modified alternative communication mechanisms as necessary. What is known about the topic? Self-determination is one of the fundamental principles of human rights legislation around the world and, as such, it is considered desirable to have personal input by individuals into the development of their own health care plans. However, this is not always considered feasible if the person comes from a group in the community perceived to be vulnerable to exploitation and viewed as lacking capacity to give informed consent. This results in the use of proxy respondents, who may not accurately represent the desires and life aspirations of the individual. What does this paper add? This paper examines the development and implementation of a targeted program to support individuals aging with lifelong intellectual disability to demonstrate their capacity to provide informed consent. Specifically, it outlines how alternative communications methods, tailored to personal needs and capacity, can assist an individual to both understand and then confirm their understanding of consent in order to participate in developing health care plans. What are the implications for practitioners? People with intellectual disability are now living longer and are increasingly at risk of serious health conditions. The development of long-term health management plans has traditionally not included individuals with more complex needs and moderate intellectual disability, but the present study shows that members of this cohort can successfully understand and consent to participate in health care decision making. By proactively supporting this process, community and healthcare settings may be able to directly facilitate contribution from more individuals, therefore better meeting the goal of person-centred support.

Reciprocal changes in DNA methylation and hydroxymethylation and a broad repressive epigenetic switch characterize FMR1 transcriptional silencing in fragile X syndrome.

BACKGROUND: Fragile X syndrome (FXS) is the most common form of inherited intellectual disability, resulting from the loss of function of the fragile X mental retardation 1 (FMR1) gene. The molecular pathways associated with FMR1 epigenetic silencing are still elusive, and their characterization may enhance the discovery of novel therapeutic targets as well as the development of novel clinical biomarkers for disease status. RESULTS: We have deployed customized epigenomic profiling assays to comprehensively map the FMR1 locus chromatin landscape in peripheral mononuclear blood cells (PBMCs) from eight FXS patients and in fibroblast cell lines derived from three FXS patient. Deoxyribonucleic acid (DNA) methylation (5-methylcytosine (5mC)) and hydroxymethylation (5-hydroxymethylcytosine (5hmC)) profiling using methylated DNA immunoprecipitation (MeDIP) combined with a custom FMR1 microarray identifies novel regions of DNA (hydroxy)methylation changes within the FMR1 gene body as well as in proximal flanking regions. At the region surrounding the FMR1 transcriptional start sites, increased levels of 5mC were associated to reciprocal changes in 5hmC, representing a novel molecular feature of FXS disease. Locus-specific validation of FMR1 5mC and 5hmC changes highlighted inter-individual differences that may account for the expected DNA methylation mosaicism observed at the FMR1 locus in FXS patients. Chromatin immunoprecipitation (ChIP) profiling of FMR1 histone modifications, together with 5mC/5hmC and gene expression analyses, support a functional relationship between 5hmC levels and FMR1 transcriptional activation and reveal cell-type specific differences in FMR1 epigenetic regulation. Furthermore, whilst 5mC FMR1 levels positively correlated with FXS disease severity (clinical scores of aberrant behavior), our data reveal for the first time an inverse correlation between 5hmC FMR1 levels and FXS disease severity. CONCLUSIONS: We identify novel, cell-type specific, regions of FMR1 epigenetic changes in FXS patient cells, providing new insights into the molecular mechanisms of FXS. We propose that the combined measurement of 5mC and 5hmC at selected regions of the FMR1 locus may significantly enhance FXS clinical diagnostics and patient stratification.