Modelling the natural history of Huntington's disease progression.

BACKGROUND: The lack of reliable biomarkers to track disease progression is a major problem in clinical research of chronic neurological disorders. Using Huntington's disease (HD) as an example, we describe a novel approach to model HD and show that the progression of a neurological disorder can be predicted for individual patients. METHODS: Starting with an initial cohort of 343 patients with HD that we have followed since 1995, we used data from 68 patients that satisfied our filtering criteria to model disease progression, based on the Unified Huntington's Disease Rating Scale (UHDRS), a measure that is routinely used in HD clinics worldwide. RESULTS: Our model was validated by: (A) extrapolating our equation to model the age of disease onset, (B) testing it on a second patient data set by loosening our filtering criteria, (C) cross-validating with a repeated random subsampling approach and (D) holdout validating with the latest clinical assessment data from the same cohort of patients. With UHDRS scores from the past four clinical visits (over a minimum span of 2 years), our model predicts disease progression of individual patients over the next 2 years with an accuracy of 89-91%. We have also provided evidence that patients with similar baseline clinical profiles can exhibit very different trajectories of disease progression. CONCLUSIONS: This new model therefore has important implications for HD research, most obviously in the development of potential disease-modifying therapies. We believe that a similar approach can also be adapted to model disease progression in other chronic neurological disorders.This study was supported by the Cotswold Trust, the Rosetrees Trust, donations to the Huntington’s disease clinic in the John van Geest Centre for Brain Repair, and NIHR award of the Biomedical Research Centre - Cambridge University NHS Foundation Trust. This project was also supported by EPSRC through projects EP/I03210X/1 and EP/G066477/1.This article has been accepted for publication in Journal of Neurology, Neurosurgery, and Psychiatry, following peer review. The definitive copyedited, typeset version J Neurol Neurosurg Psychiatry doi:10.1136/jnnp-2014-308153 is available online at: http://jnnp.bmj.com/content/early/2014/12/16/jnnp-2014-308153.long

Predicting clinical diagnosis in Huntington's disease: An imaging polymarker

Objective Huntington's disease (HD) gene carriers can be identified before clinical diagnosis; however, statistical models for predicting when overt motor symptoms will manifest are too imprecise to be useful at the level of the individual. Perfecting this prediction is integral to the search for disease modifying therapies. This study aimed to identify an imaging marker capable of reliably predicting real‐life clinical diagnosis in HD. Method A multivariate machine learning approach was applied to resting‐state and structural magnetic resonance imaging scans from 19 premanifest HD gene carriers (preHD, 8 of whom developed clinical disease in the 5 years postscanning) and 21 healthy controls. A classification model was developed using cross‐group comparisons between preHD and controls, and within the preHD group in relation to “estimated” and “actual” proximity to disease onset. Imaging measures were modeled individually, and combined, and permutation modeling robustly tested classification accuracy. Results Classification performance for preHDs versus controls was greatest when all measures were combined. The resulting polymarker predicted converters with high accuracy, including those who were not expected to manifest in that time scale based on the currently adopted statistical models. Interpretation We propose that a holistic multivariate machine learning treatment of brain abnormalities in the premanifest phase can be used to accurately identify those patients within 5 years of developing motor features of HD, with implications for prognostication and preclinical trials

Making a HIIT: Methods for quantifying intensity in high-intensity interval training in schools and validity of session rating of perceived exertion

This is the final version. Available on open access from Routledge via the DOI in this recordUsing the data from Making a HIIT, this paper aimed to: 1) investigate the different heart rate (HR) quantification methods reported in school-based high-intensity interval training (HIIT) studies; and 2) assess the criterion validity of session rating of perceived exertion (RPE). During an 8-week HIIT intervention, 213 students (13.1 (0.6) years; 46% female) completed 10-minute HIIT workouts during physical education lessons. In total, 1057 HR and RPE measurements were collected across 68 HIIT workouts. For aim 1, the average and peak HR across all participants and workouts were 79% (8%) and 92% (6%) of HRmax, respectively. The average RPE was 6 (2) points on a 10-point scale. An average of 51% of students in a class had an average HR ≥ 80% for each workout. The between-person variation for peak and average HR were 19% and 30% , respectively. Both average and peak HR decreased by 0.5% each week (p < 0.001). To assess aim 2, a within-participant correlation was calculated for the internal training load produced using HR and RPE data. The correlation was 0.39 (p < 0.001), which suggests utility of using RPE when HR is not a viable option.QUEX InstituteSports Medicine Australi

The association between socioeconomic disadvantage and children’s working memory abilities: A systematic review and meta-analysis

Background and objective: Working memory is an essential cognitive skill for storing and processing limited amounts of information over short time periods. Researchers disagree about the extent to which socioeconomic position affects children’s working memory, yet no study has systematically synthesised the literature regarding this topic. The current review therefore aimed to investigate the relationship between socioeconomic position and working memory in children, regarding both the magnitude and the variability of the association. Methods: The review protocol was registered on PROSPERO and the PRISMA checklist was followed. Embase, Psycinfo and MEDLINE were comprehensively searched via Ovid from database inception until 3rd June 2021. Studies were screened by two reviewers at all stages. Studies were eligible if they included typically developing children aged 0–18 years old, with a quantitative association reported between any indicator of socioeconomic position and children’s working memory task performance. Studies were synthesised using two data-synthesis methods: random effects meta-analyses and a Harvest plot. Key findings: The systematic review included 64 eligible studies with 37,737 individual children (aged 2 months to 18 years). Meta-analyses of 36 of these studies indicated that socioeconomic disadvantage was associated with significantly lower scores working memory measures; a finding that held across different working memory tasks, including those that predominantly tap into storage (d = 0.45; 95% CI 0.27 to 0.62) as well as those that require processing of information (d = 0.52; 0.31 to 0.72). A Harvest plot of 28 studies ineligible for meta-analyses further confirmed these findings. Finally, meta-regression analyses revealed that the association between socioeconomic position and working memory was not moderated by task modality, risk of bias, socioeconomic indicator, mean age in years, or the type of effect size. Conclusion: This is the first systematic review to investigate the association between socioeconomic position and working memory in children. Socioeconomic disadvantage was associated with lower working memory ability in children, and that this association was similar across different working memory tasks. Given the strong association between working memory, learning, and academic attainment, there is a clear need to share these findings with practitioners working with children, and investigate ways to support children with difficulties in working memory

The comparative landscape of duplications in Heliconius melpomene and Heliconius cydno

Gene duplications can facilitate adaptation and may lead to interpopulation divergence, causing reproductive isolation. We used whole-genome resequencing data from 34 butterflies to detect duplications in two Heliconius species, Heliconius cydno and Heliconius melpomene. Taking advantage of three distinctive signals of duplication in short-read sequencing data, we identified 744 duplicated loci in H. cydno and H. melpomene and evaluated the accuracy of our approach using single-molecule sequencing. We have found that duplications overlap genes significantly less than expected at random in H. melpomene, consistent with the action of background selection against duplicates in functional regions of the genome. Duplicate loci that are highly differentiated between H. melpomene and H. cydno map to four different chromosomes. Four duplications were identified with a strong signal of divergent selection, including an odorant binding protein and another in close proximity with a known wing colour pattern locus that differs between the two species.AP is funded by a NERC studentship (PFZE/063). CDJ, SLB, JWD and SHM are funded by ERC grant SpeciationGenetics (Grant Number 339873). Pacific Biosciences sequencing was carried out by Karen Oliver in collaboration with Richard Durbin at the Sanger Institute, supported by European Research Council (ERC) Grant Number 339873, Wellcome Trust Grant Number 098051. We thank Jenny Barna and Stuart Rankin for computing support. Analyses were carried out using the Darwin Supercomputer of the University of Cambridge High Performance Computing Service (http://www.hpc.cam.ac.uk/), provided by Dell Inc. using Strategic Research Infrastructure Funding from the Higher Education Funding Council for England, and funding from the Science and Technology Facilities Council. We thank the editor and three anonymous reviewers for their comments that helped us to improve this manuscript

Validation and calibration for embedding rating of perceived exertion into high-intensity interval exercise in adolescents: a lab-based study

This is the author accepted manuscript. The final version is available from Human Kinetics via the DOI in this recordPURPOSE: Rating of perceived exertion (RPE) is a convenient and cost-effective tool that can be used to monitor high-intensity interval exercise (HIIE). However, no methodological study has demonstrated the validity of RPE in this context. Therefore, the aim of this study was to validate and calibrate RPE for monitoring HIIE in adolescents. METHODS: RPE, heart rate (HR), and oxygen uptake (V˙O2) data were retrospectively extracted from 3 lab-based crossover studies, with a pooled sample size of 45 adolescents, performing either cycling-based or running-based HIIE sessions. Within-participant correlations were calculated for RPE-HR and RPE-V˙O2, and receiver operator characteristic curve analysis was used to establish RPE cut points. RESULTS: The results showed that RPE-HR demonstrated acceptable criterion validity (r = .53-.74, P < .01), while RPE-V˙O2 had poor validity (r = .40-.48, P < .01), except for HIIE at 100% peak power (r = .59, P < .01). RPE cut points of 4 and 5 were established in corresponding to HR/V˙O2 based thresholds. CONCLUSION: RPE has some utility in evaluating intensity during lab-based running or cycling HIIE in adolescents. Future studies should expand the validation and calibration of RPE for prescribing and monitoring HIIE in children and adolescents in field-based contexts

Barriers and enablers to the implementation of the 6-PACK falls prevention program: A preimplementation study in hospitals participating in a cluster randomised controlled trial

Evidence for effective falls prevention interventions in acute wards is limited. One reason for this may be suboptimal program implementation. This study aimed to identify perceived barriers and enablers of the implementation of the 6-PACK falls prevention program to inform the implementation in a randomised controlled trial. Strategies to optimise successful implementation of 6-PACK were also sought. A mixed-methods approach was applied in 24 acute wards from 6 Australian hospitals. Participants were nurses working on participating wards and senior hospital staff including Nurse Unit Managers; senior physicians; Directors of Nursing; and senior personnel involved in quality and safety or falls prevention. Information on barriers and enablers of 6-PACK implementation was obtained through surveys, focus groups and interviews. Questions reflected the COM-B framework that includes three behaviour change constructs of: capability, opportunity and motivation. Focus group and interview data were analysed thematically, and survey data descriptively. The survey response rate was 60% (420/702), and 12 focus groups (n = 96 nurses) and 24 interviews with senior staff were conducted. Capability barriers included beliefs that falls could not be prevented; and limited knowledge on falls prevention in patients with complex care needs (e.g. cognitive impairment). Capability enablers included education and training, particularly face to face case study based approaches. Lack of resources was identified as an opportunity barrier. Leadership, champions and using data to drive practice change were recognised as opportunity enablers. Motivation barriers included complacency and lack of ownership in falls prevention efforts. Motivation enablers included senior staff articulating clear goals and a commitment to falls prevention; and use of reminders, audits and feedback. The information gained from this study suggests that regular practical face-to-face education and training for nurses; provision of equipment; audit, reminders and feedback; leadership and champions; and the provision of falls data is key to successful falls prevention program implementation in acute hospitals

Assessing connectivity between an overlying aquifer and a coal seam gas resource using methane isotopes, dissolved organic carbon and tritium

Coal seam gas (CSG) production can have an impact on groundwater quality and quantity in adjacent or overlying aquifers. To assess this impact we need to determine the background groundwater chemistry and to map geological pathways of hydraulic connectivity between aquifers. In south-east Queensland (Qld), Australia, a globally important CSG exploration and production province, we mapped hydraulic connectivity between the Walloon Coal Measures (WCM, the target formation for gas production) and the overlying Condamine River Alluvial Aquifer (CRAA), using groundwater methane (CH4) concentration and isotopic composition (δ13C-CH4), groundwater tritium (3H) and dissolved organic carbon (DOC) concentration. A continuous mobile CH4 survey adjacent to CSG developments was used to determine the source signature of CH4 derived from the WCM. Trends in groundwater δ13C-CH4 versus CH4 concentration, in association with DOC concentration and 3H analysis, identify locations where CH4 in the groundwater of the CRAA most likely originates from the WCM. The methodology is widely applicable in unconventional gas development regions worldwide for providing an early indicator of geological pathways of hydraulic connectivity

Maternal psychological distress in primary care and association with child behavioural outcomes at age three

Observational studies indicate children whose mothers have poor mental health are at increased risk of socio-emotional behavioural difficulties, but it is unknown whether these outcomes vary by the mothers’ mental health recognition and treatment status. To examine this question, we analysed linked longitudinal primary care and research data from 1078 women enrolled in the Born in Bradford cohort. A latent class analysis of treatment status and self-reported distress broadly categorised women as (a) not having a common mental disorder (CMD) that persisted through pregnancy and the first 2 years after delivery (N = 756, 70.1 %), (b) treated for CMD (N = 67, 6.2 %), or (c) untreated (N = 255, 23.7 %). Compared to children of mothers without CMD, 3-year-old children with mothers classified as having untreated CMD had higher standardised factor scores on the Strengths and Difficulties Questionnaire (d = 0.32), as did children with mothers classified as having treated CMD (d = 0.27). Results were only slightly attenuated in adjusted analyses. Children of mothers with CMD may be at risk for socio-emotional and behavioural difficulties. The development of effective treatments for CMD needs to be balanced by greater attempts to identify and treat women. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00787-015-0777-2) contains supplementary material, which is available to authorized users