The effectiveness of individualized morphosyntactic target identification and explicit intervention using the SHAPE CPDING System for children with developmental language disorder and the impact of within-session dosage

PURPOSE: We investigated the effectiveness of a highly individualized morphosyntactic intervention using the SHAPE CODING™ system delivered at different dosages. METHOD: Eight children with developmental language disorder aged 8;0-10;10 (years;months) received 10 hr of explicit individualized intervention for morphosyntax delivered in 30-min individual sessions once per week for 20 weeks. Following at least four baseline probe tests, two grammatical targets per session received explicit instruction until they reached criterion (90%), when the next target was introduced. To control for session length and teaching episode density, either both targets received 20 teaching episodes per session or one target received 10 teaching episodes and the other 30. Maintenance testing of completed targets was also carried out. RESULTS: Scores on probe tests post-intervention were significantly higher than during the baseline phase (d = 1.6) with no change during the baseline or maintenance phases. However, progress during the intervention phase was highly significant. One participant showed significantly faster progress with intervention, while one (with the lowest attention score) made little progress. When considering progress relative to cumulative intervention sessions, progress was faster with 30 teaching episodes per session and slower with 10. However, when cumulative teaching episodes were used as the predictor, all three within-session dosages showed very similar rates of progress, with the odds of a correct response increasing by 3.9% for each teaching episode. The targets that were achieved required an average of 40-60 teaching episodes. CONCLUSIONS: With the exception of one participant, the individualized intervention was highly effective and efficient. Thus, the individualized target identification process and intervention method merit further research in a larger group of children. The cumulative number of teaching episodes per target provided across sessions appeared to be key. Thus, clinicians should aim for high teaching episode rates, particularly if the number of sessions is constrained. Otherwise, intervention scheduling can be flexible. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.25996168

Epigenetic Contributions to Clinical Risk Prediction of Cardiovascular Disease

BACKGROUND: Cardiovascular disease (CVD) is among the leading causes of death worldwide. The discovery of new omics biomarkers could help to improve risk stratification algorithms and expand our understanding of molecular pathways contributing to the disease. Here, ASSIGN-a cardiovascular risk prediction tool recommended for use in Scotland-was examined in tandem with epigenetic and proteomic features in risk prediction models in ≥12 657 participants from the Generation Scotland cohort.METHODS: Previously generated DNA methylation-derived epigenetic scores (EpiScores) for 109 protein levels were considered, in addition to both measured levels and an EpiScore for cTnI (cardiac troponin I). The associations between individual protein EpiScores and the CVD risk were examined using Cox regression (n cases≥1274; n controls≥11 383) and visualized in a tailored R application. Splitting the cohort into independent training (n=6880) and test (n=3659) subsets, a composite CVD EpiScore was then developed. RESULTS: Sixty-five protein EpiScores were associated with incident CVD independently of ASSIGN and the measured concentration of cTnI ( P&lt;0.05), over a follow-up of up to 16 years of electronic health record linkage. The most significant EpiScores were for proteins involved in metabolic, immune response, and tissue development/regeneration pathways. A composite CVD EpiScore (based on 45 protein EpiScores) was a significant predictor of CVD risk independent of ASSIGN and the concentration of cTnI (hazard ratio, 1.32; P=3.7×10 - 3; 0.3% increase in C-statistic). CONCLUSIONS: EpiScores for circulating protein levels are associated with CVD risk independent of traditional risk factors and may increase our understanding of the etiology of the disease.</p

Refining epigenetic prediction of chronological and biological age

Background Epigenetic clocks can track both chronological age (cAge) and biological age (bAge). The latter is typically defined by physiological biomarkers and risk of adverse health outcomes, including all-cause mortality. As cohort sample sizes increase, estimates of cAge and bAge become more precise. Here, we aim to develop accurate epigenetic predictors of cAge and bAge, whilst improving our understanding of their epigenomic architecture. Methods First, we perform large-scale (N = 18,413) epigenome-wide association studies (EWAS) of chronological age and all-cause mortality. Next, to create a cAge predictor, we use methylation data from 24,674 participants from the Generation Scotland study, the Lothian Birth Cohorts (LBC) of 1921 and 1936, and 8 other cohorts with publicly available data. In addition, we train a predictor of time to all-cause mortality as a proxy for bAge using the Generation Scotland cohort (1214 observed deaths). For this purpose, we use epigenetic surrogates (EpiScores) for 109 plasma proteins and the 8 component parts of GrimAge, one of the current best epigenetic predictors of survival. We test this bAge predictor in four external cohorts (LBC1921, LBC1936, the Framingham Heart Study and the Women’s Health Initiative study). Results Through the inclusion of linear and non-linear age-CpG associations from the EWAS, feature pre-selection in advance of elastic net regression, and a leave-one-cohort-out (LOCO) cross-validation framework, we obtain cAge prediction with a median absolute error equal to 2.3 years. Our bAge predictor was found to slightly outperform GrimAge in terms of the strength of its association to survival (HRGrimAge = 1.47 [1.40, 1.54] with p = 1.08 × 10−52, and HRbAge = 1.52 [1.44, 1.59] with p = 2.20 × 10−60). Finally, we introduce MethylBrowsR, an online tool to visualise epigenome-wide CpG-age associations. Conclusions The integration of multiple large datasets, EpiScores, non-linear DNAm effects, and new approaches to feature selection has facilitated improvements to the blood-based epigenetic prediction of biological and chronological age

Development and validation of DNA Methylation scores in two European cohorts augment 10-year risk prediction of type 2 diabetes

This is the author accepted manuscriptAvailability of Data and Material: According to the terms of consent for Generation Scotland participants, access to data must be reviewed by the Generation Scotland Access Committee. Applications should be made to [email protected]. All code is available with open access at the following Gitlab repository: https://github.com/marioni-group MethylPipeR (version 1.0.0) is available at: https://github.com/marioni-group/MethylPipeR MethylPipeR-UI is available at: https://github.com/marioni-group/MethylPipeR-UI. The informed consents given by KORA study participants do not cover data posting in public databases. However, data are available upon request from KORA Project Application Self Service Tool (https://epi.helmholtz-muenchen.de/). Data requests can be submitted online and are subject to approval by the KORA Board.Type 2 diabetes mellitus (T2D) presents a major health and economic burden that could be alleviated with improved early prediction and intervention. While standard risk factors have shown good predictive performance, we show that the use of blood-based DNA methylation information leads to a significant improvement in the prediction of 10-year T2D incidence risk. Previous studies have been largely constrained by linear assumptions, the use of CpGs one-at43 a-time, and binary outcomes. We present a flexible approach (via an R package, MethylPipeR) based on a range of linear and tree-ensemble models that incorporate time-to-event data for prediction. Using the Generation Scotland cohort (training set ncases=374, ncontrols=9,461; test set ncases=252, ncontrols=4,526) our best-performing model (Area Under the Curve (AUC)=0.872, Precision Recall AUC (PRAUC)=0.302) showed notable improvement in 10-year onset prediction beyond standard risk factors (AUC=0.839, PRAUC=0.227). Replication was observed in the German-based KORA study (n=1,451, ncases = 142, p=1.6x10-5 49 ).Wellcome TrustChief Scientist Office of the Scottish Government Health DirectoratesScottish Funding Counci

Epigenetic contributions to clinical risk prediction of cardiovascular disease

BACKGROUND: Cardiovascular disease (CVD) is among the leading causes of death worldwide. The discovery of new omics biomarkers could help to improve risk stratification algorithms and expand our understanding of molecular pathways contributing to the disease. Here, ASSIGN—a cardiovascular risk prediction tool recommended for use in Scotland—was examined in tandem with epigenetic and proteomic features in risk prediction models in ≥12 657 participants from the Generation Scotland cohort. METHODS: Previously generated DNA methylation–derived epigenetic scores (EpiScores) for 109 protein levels were considered, in addition to both measured levels and an EpiScore for cTnI (cardiac troponin I). The associations between individual protein EpiScores and the CVD risk were examined using Cox regression (ncases≥1274; ncontrols≥11 383) and visualized in a tailored R application. Splitting the cohort into independent training (n=6880) and test (n=3659) subsets, a composite CVD EpiScore was then developed. RESULTS: Sixty-five protein EpiScores were associated with incident CVD independently of ASSIGN and the measured concentration of cTnI (P&lt;0.05), over a follow-up of up to 16 years of electronic health record linkage. The most significant EpiScores were for proteins involved in metabolic, immune response, and tissue development/regeneration pathways. A composite CVD EpiScore (based on 45 protein EpiScores) was a significant predictor of CVD risk independent of ASSIGN and the concentration of cTnI (hazard ratio, 1.32; P=3.7×10−3; 0.3% increase in C-statistic). CONCLUSIONS: EpiScores for circulating protein levels are associated with CVD risk independent of traditional risk factors and may increase our understanding of the etiology of the disease

Comparison of user groups' perspectives of barriers and facilitators to implementing electronic health records: a systematic review

<p>Abstract</p> <p>Background</p> <p>Electronic health record (EHR) implementation is currently underway in Canada, as in many other countries. These ambitious projects involve many stakeholders with unique perceptions of the implementation process. EHR users have an important role to play as they must integrate the EHR system into their work environments and use it in their everyday activities. Users hold valuable, first-hand knowledge of what can limit or contribute to the success of EHR implementation projects. A comprehensive synthesis of EHR users' perceptions is key to successful future implementation. This systematic literature review was aimed to synthesize current knowledge of the barriers and facilitators influencing shared EHR implementation among its various users.</p> <p>Methods</p> <p>Covering a period from 1999 to 2009, a literature search was conducted on nine electronic databases. Studies were included if they reported on users' perceived barriers and facilitators to shared EHR implementation, in healthcare settings comparable to Canada. Studies in all languages with an empirical study design were included. Quality and relevance of the studies were assessed. Four EHR user groups were targeted: physicians, other health care professionals, managers, and patients/public. Content analysis was performed independently by two authors using a validated extraction grid with pre-established categorization of barriers and facilitators for each group of EHR users.</p> <p>Results</p> <p>Of a total of 5,695 potentially relevant publications identified, 117 full text publications were obtained after screening titles and abstracts. After review of the full articles, 60 publications, corresponding to 52 studies, met the inclusion criteria. The most frequent adoption factors common to all user groups were design and technical concerns, ease of use, interoperability, privacy and security, costs, productivity, familiarity and ability with EHR, motivation to use EHR, patient and health professional interaction, and lack of time and workload. Each user group also identified factors specific to their professional and individual priorities.</p> <p>Conclusions</p> <p>This systematic review presents innovative research on the barriers and facilitators to EHR implementation. While important similarities between user groups are highlighted, differences between them demonstrate that each user group also has a unique perspective of the implementation process that should be taken into account.</p

Ten-year mortality, disease progression, and treatment-related side effects in men with localised prostate cancer from the ProtecT randomised controlled trial according to treatment received

Background The ProtecT trial reported intention-to-treat analysis of men with localised prostate cancer randomly allocated to active monitoring (AM), radical prostatectomy, and external beam radiotherapy. Objective To report outcomes according to treatment received in men in randomised and treatment choice cohorts. Design, setting, and participants This study focuses on secondary care. Men with clinically localised prostate cancer at one of nine UK centres were invited to participate in the treatment trial comparing AM, radical prostatectomy, and radiotherapy. Intervention Two cohorts included 1643 men who agreed to be randomised and 997 who declined randomisation and chose treatment. Outcome measurements and statistical analysis Analysis was carried out to assess mortality, metastasis and progression and health-related quality of life impacts on urinary, bowel, and sexual function using patient-reported outcome measures. Analysis was based on comparisons between groups defined by treatment received for both randomised and treatment choice cohorts in turn, with pooled estimates of intervention effect obtained using meta-analysis. Differences were estimated with adjustment for known prognostic factors using propensity scores. Results and limitations According to treatment received, more men receiving AM died of PCa (AM 1.85%, surgery 0.67%, radiotherapy 0.73%), whilst this difference remained consistent with chance in the randomised cohort (p = 0.08); stronger evidence was found in the exploratory analyses (randomised plus choice cohort) when AM was compared with the combined radical treatment group (p = 0.003). There was also strong evidence that metastasis (AM 5.6%, surgery 2.4%, radiotherapy 2.7%) and disease progression (AM 20.35%, surgery 5.87%, radiotherapy 6.62%) were more common in the AM group. Compared with AM, there were higher risks of sexual dysfunction (95% at 6 mo) and urinary incontinence (55% at 6 mo) after surgery, and of sexual dysfunction (88% at 6 mo) and bowel dysfunction (5% at 6 mo) after radiotherapy. The key limitations are the potential for bias when comparing groups defined by treatment received and changes in the protocol for AM during the lengthy follow-up required in trials of screen-detected PCa. Conclusions Analyses according to treatment received showed increased rates of disease-related events and lower rates of patient-reported harms in men managed by AM compared with men managed by radical treatment, and stronger evidence of greater PCa mortality in the AM group. Patient summary More than 95 out of every 100 men with low or intermediate risk localised prostate cancer do not die of prostate cancer within 10 yr, irrespective of whether treatment is by means of monitoring, surgery, or radiotherapy. Side effects on sexual and bladder function are better after active monitoring, but the risks of spreading of prostate cancer are more common