De-novo FAIRification via an Electronic Data Capture system by automated transformation of filled electronic Case Report Forms into machine-readable data.

INTRODUCTION: Existing methods to make data Findable, Accessible, Interoperable, and Reusable (FAIR) are usually carried out in a post hoc manner: after the research project is conducted and data are collected. De-novo FAIRification, on the other hand, incorporates the FAIRification steps in the process of a research project. In medical research, data is often collected and stored via electronic Case Report Forms (eCRFs) in Electronic Data Capture (EDC) systems. By implementing a de novo FAIRification process in such a system, the reusability and, thus, scalability of FAIRification across research projects can be greatly improved. In this study, we developed and implemented a novel method for de novo FAIRification via an EDC system. We evaluated our method by applying it to the Registry of Vascular Anomalies (VASCA). METHODS: Our EDC and research project independent method ensures that eCRF data entered into an EDC system can be transformed into machine-readable, FAIR data using a semantic data model (a canonical representation of the data, based on ontology concepts and semantic web standards) and mappings from the model to questions on the eCRF. The FAIRified data are stored in a triple store and can, together with associated metadata, be accessed and queried through a FAIR Data Point. The method was implemented in Castor EDC, an EDC system, through a data transformation application. The FAIRness of the output of the method, the FAIRified data and metadata, was evaluated using the FAIR Evaluation Services. RESULTS: We successfully applied our FAIRification method to the VASCA registry. Data entered on eCRFs is automatically transformed into machine-readable data and can be accessed and queried using SPARQL queries in the FAIR Data Point. Twenty-one FAIR Evaluator tests pass and one test regarding the metadata persistence policy fails, since this policy is not in place yet. CONCLUSION: In this study, we developed a novel method for de novo FAIRification via an EDC system. Its application in the VASCA registry and the automated FAIR evaluation show that the method can be used to make clinical research data FAIR when they are entered in an eCRF without any intervention from data management and data entry personnel. Due to the generic approach and developed tooling, we believe that our method can be used in other registries and clinical trials as well.

Attitudes of medical students to general practice: a multinational cross-sectional survey.

BACKGROUND: A shortage of general practitioners (GPs) is common to many European countries. To counteract this, it is essential to understand the factors that encourage or discourage medical students from choosing to become a GP. OBJECTIVE: To evaluate medical students' attitudes towards general practice and to identify factors that discourage them from considering a career as a GP. METHODS: In this multinational cross-sectional online survey, 29 284 students from nine German, four Austrian and two Slovenian universities were invited to answer a questionnaire consisting of 146 closed and 13 open-ended items. RESULTS: Of the 4486 students that responded (response rate: 15.3%), 3.6% wanted to become a GP, 48.1% were undecided and 34.6% did not want to be a GP. Significant predictors for interest in becoming a GP were higher age [odds ratio (OR) = 1.06; 95% confidence interval (CI) = 1.02-1.10], positive evaluation of the content of a GP's work (OR = 4.44; 95% CI = 3.26-6.06), organizational aspects (OR = 1.42; 95% CI = 1.13-1.78), practical experience of general practice (OR = 1.66; 95% CI = 1.08-2.56) and the country of the survey [Slovenian versus German students (Reference): OR = 2.19; 95% CI = 1.10-4.38; Austrian versus German students (Reference): OR = 0.50; 95% CI = 0.32-0.79]. CONCLUSION: Strategies to convince undecided students to opt for a career as a GP should include a positive representation of a GP's work and early and repeated experience of working in a general practice during medical school.

Consent Codes: Upholding Standard Data Use Conditions.

A systematic way of recording data use conditions that are based on consent permissions as found in the datasets of the main public genome archives (NCBI dbGaP and EMBL-EBI/CRG EGA).

MECP2 variation in Rett syndrome-An overview of current coverage of genetic and phenotype data within existing databases.

Rett syndrome (RTT) is a monogenic rare disorder that causes severe neurological problems. In most cases, it results from a loss-of-function mutation in the gene encoding methyl-CPG-binding protein 2 (MECP2). Currently, about 900 unique MECP2 variations (benign and pathogenic) have been identified and it is suspected that the different mutations contribute to different levels of disease severity. For researchers and clinicians, it is important that genotype-phenotype information is available to identify disease-causing mutations for diagnosis, to aid in clinical management of the disorder, and to provide counseling for parents. In this study, 13 genotype-phenotype databases were surveyed for their general functionality and availability of RTT-specific MECP2 variation data. For each database, we investigated findability and interoperability alongside practical user functionality, and type and amount of genetic and phenotype data. The main conclusions are that, as well as being challenging to find these databases and specific MECP2 variants held within, interoperability is as yet poorly developed and requires effort to search across databases. Nevertheless, we found several thousand online database entries for MECP2 variations and their associated phenotypes, diagnosis, or predicted variant effects, which is a good starting point for researchers and clinicians who want to provide, annotate, and use the data.

Meta-analysis of polycystic kidney disease expression profiles defines strong involvement of injury repair processes.

Polycystic kidney disease (PKD) is a major cause of end-stage renal disease. The disease mechanisms are not well understood and the pathogenesis toward renal failure remains elusive. In this study, we present the first RNASeq analysis of a Pkd1-mutant mouse model in a combined meta-analysis with other published PKD expression profiles. We introduce the PKD Signature, a set of 1,515 genes that are commonly dysregulated in PKD studies. We show that the signature genes include many known and novel PKD-related genes and functions. Moreover, genes with a role in injury repair, as evidenced by expression data and/or automated literature analysis, were significantly enriched in the PKD Signature, with 35% of the PKD Signature genes being directly implicated in injury repair. NF-κB signaling, epithelial-mesenchymal transition, inflammatory response, hypoxia, and metabolism were among the most prominent injury or repair-related biological processes with a role in the PKD etiology. Novel PKD genes with a role in PKD and in injury were confirmed in another Pkd1-mutant mouse model as well as in animals treated with a nephrotoxic agent. We propose that compounds that can modulate the injury-repair response could be valuable drug candidates for PKD treatment.

Preparing Data at the Source to Foster Interoperability across Rare Disease Resources.

The ability to combine heterogeneous data distributed across the globe is critically important to boost research on rare diseases, but it presents a number of methodological, representational and automation challenges. In this scenario, biomedical ontologies are of critical importance for enabling computers to aid in information retrieval and analysis across data collections.This chapter presents an approach to preparing rare disease data for integration through the application of a global standard for computer-readable data and knowledge. This includes the use of common data elements, ontological codes and computer-readable data. This approach was developed under a number of domain-relevant requirements, such as controlled access to data, independence of the original sources, and the desire to combining the data sources with other computational workflows and data platforms.

[Integrated Peer Teaching of Communication and Clinical Skills: How to Train Student Tutors?]. / Integriertes Peer Teaching klinischer und kommunikativer Kompetenzen: Wie bereiten wir studentische Tutoren darauf vor?

AIM: This paper describes the theory-based development of a standardized training model for peer tutors. The aim is to qualify tutors to teach communication skills integrated with practical clinical skills, to medical students in the pre-clinical curriculum. As a result, students are encouraged to form a basic understanding of the biopsychosocial model of diseases early in their studies. METHOD: The training model's design is based on the Kern model for curriculum development as adapted by McLean et al., who outlined the following steps: planning, implementation, and evaluation/feedback. Our focus is on development, review of feasibility, and evaluation as measured by the subjectively perceived effectiveness of the implemented training model. 2 target groups were considered: the peer tutors and the student tutees. RESULTS: In 2009, a 3-step training model consisting of 12 units was developed, based on the theory of patient-centered communication and the biopsychosocial model. The training was rated very positively on a 5-point Likert scale by all tutors at 2 points in time: t1 (directly after training) and t2 (after conducting 2 tutorials) (t1: M=1.67; SD=±0.86; t2: M=1.75; SD=±0.71). On a 6-point Likert scale, the tutees also evaluated their communication and clinical skills as being significantly better after completing the 10 tutorials (t2: scale for interaction and communication: M=4.81; SD: 1.09; scale for clinical examination: M=4.99; SD: 0.85) than before the tutorials (t0: scale for communication and interaction: M=3.18; SD=1.15; scale for clinical examination: M=2.88; SD: 1.09). CONCLUSIONS: By implementing a standardized tutor training model, one can qualify peer tutors to teach communication skills integrated with practical clinical skills during the pre-clinical phase. Practice teaching of the curricular material via role playing, tutorial simulation and an extensive feedback session, along with the definition of clinical standards for recording case histories and performing examinations, have proven themselves to be core elements of effective tutor training.

Re-profiling today's health care curricula for tomorrow's workforce: Establishing an interprofessional degree in Germany.

Laws regulating education of most health professional groups in Germany today mean that curricula re-profiling in response to changing priorities in the practice environment is a significant challenge. Legally dictated theoretical and clinical requirements for the vocational training of health professionals leaves little room for re-profiling in response to movements such as interprofessional education. An educational innovation was needed that worked within existing structures in Germany. The result was a formal collaboration between the Academy for Health Professionals and the University of Heidelberg allowing students undertaking vocational training to also complete a university degree in parallel. The aim of this article is to describe the curriculum development for the Bachelor of Science - Interprofessional Health Care. This article outlines an evidence-based approach to the process to curriculum development that resulted in a competency-based degree offering comprehensive interprofessional education at undergraduate level for healthcare students based in Germany.

Depression and vaccination behavior in patients with chronic physical illness - A cross-sectional survey.

OBJECTIVE: Chronically ill are vulnerable to vaccine preventable infections. Consequently, their vaccination behavior is highly relevant. Depressive comorbidities are frequent in these patients. Furthermore, these patients are mainly diagnosed, treated and vaccinated in primary care. Therefore, we aimed to investigate the associations between depression and vaccination behavior (COVID-19 and influenza) in adult chronically ill primary care patients. METHODS: In a cross-sectional survey, we examined depression (PHQ9), psychological antecedents of vaccinations (Confidence and Constraints), health care utilization, and vaccination status. Based on an effect model, descriptive statistics and mixed linear/logistic models were calculated. (German Clinical Trials Register, DRKS00030042). RESULTS: n = 795 patients were analyzed. Both psychological antecedents of vaccinations (Confidence and Constraints) mediated a negative association between depression and vaccination behavior, healthcare utilization mediated a positive association. The total effect of depression was negligible. CONCLUSIONS: As the effects of vaccination readiness and healthcare utilization are opposing, different total effects depending on the study population are possible. Further studies are needed to investigate additional predictors of vaccination behavior. PRACTICE IMPLICATIONS: We suggest tackling vaccine acceptance in chronically ill through increasing confidence using communication-based interventions, for which primary care is the suitable setting. Constraints might be reduced by reminder and recall systems.

Expectations of general practitioners on a practice based research network in Germany- a qualitative study within the Bavarian Research Practice Network (BayFoNet).

BACKGROUND: Despite general practitioners' (GPs') key role in Germany`s primary health care, clinical research in general practice is scarce. Clinical research is mainly conducted at inpatient facilities, although their results are rarely transferable. German GPs have no extra time or funding for research, as well as limited research training. To support clinical research in German primary health care, practice-based research networks (PBRNs) are developed. As they will be based on an active involvement of GPs, we need more information on GPs` participation-readiness. The aim of this study was to explore facilitators and barriers to participation in the Bavarian Research Practice Network (BayFoNet) from the GPs`perspective before clinical trials will be performed. METHODS: We have performed semi-structured qualitative interviews with a purposive sample of 20 Bavarian GPs in 2022 under the application of the consolidated framework for implementation research (CFIR). Transcriptions were analysed according to Kuckartz` qualitative content analysis. The five domains of the CFIR framework served as initial deductive codes. RESULTS: N = 14 interviewees already agreed to participate in BayFoNet, whereas n = 6 interviewees opted not to participate in BayFoNet at the time of data collection. Main facilitators to conduct clinical research within BayFoNet were the motivation to contribute to evidence strength and quality in general practice, professional development and training of practice staff, as well as networking. Barriers for an active participation were bad experiences with previous clinical studies and lack of resources. CONCLUSIONS: PBRNS in Germany have to be promoted and the entire practice team has to be involved at an early stage of development. Professional training of general practice staff and a living network might enhance engagement. Participatory approaches could help to develop acceptable and feasible study designs. Furthermore, PBRNs should support patient recruitment and data collection in general practices and disseminate the results of their research projects regularly to maintain GPs` engagement. TRIAL REGISTRATION: DRKS00028805, NCT05667207.

Automated workflow-based exploitation of pathway databases provides new insights into genetic associations of metabolite profiles.

BACKGROUND: Genome-wide association studies (GWAS) have identified many common single nucleotide polymorphisms (SNPs) that associate with clinical phenotypes, but these SNPs usually explain just a small part of the heritability and have relatively modest effect sizes. In contrast, SNPs that associate with metabolite levels generally explain a higher percentage of the genetic variation and demonstrate larger effect sizes. Still, the discovery of SNPs associated with metabolite levels is challenging since testing all metabolites measured in typical metabolomics studies with all SNPs comes with a severe multiple testing penalty. We have developed an automated workflow approach that utilizes prior knowledge of biochemical pathways present in databases like KEGG and BioCyc to generate a smaller SNP set relevant to the metabolite. This paper explores the opportunities and challenges in the analysis of GWAS of metabolomic phenotypes and provides novel insights into the genetic basis of metabolic variation through the re-analysis of published GWAS datasets. RESULTS: Re-analysis of the published GWAS dataset from Illig et al. (Nature Genetics, 2010) using a pathway-based workflow (http://www.myexperiment.org/packs/319.html), confirmed previously identified hits and identified a new locus of human metabolic individuality, associating Aldehyde dehydrogenase family1 L1 (ALDH1L1) with serine/glycine ratios in blood. Replication in an independent GWAS dataset of phospholipids (Demirkan et al., PLoS Genetics, 2012) identified two novel loci supported by additional literature evidence: GPAM (Glycerol-3 phosphate acyltransferase) and CBS (Cystathionine beta-synthase). In addition, the workflow approach provided novel insight into the affected pathways and relevance of some of these gene-metabolite pairs in disease development and progression. CONCLUSIONS: We demonstrate the utility of automated exploitation of background knowledge present in pathway databases for the analysis of GWAS datasets of metabolomic phenotypes. We report novel loci and potential biochemical mechanisms that contribute to our understanding of the genetic basis of metabolic variation and its relationship to disease development and progression.

[Clinical quality governance-a practical approach in general practice with the example of influenza vaccination]. / Klinische Qualitätssteuerung ­ ein praktischer Versuch in der Hausarztpraxis am Beispiel der Influenzaimpfung.

We understand clinical quality governance (CQG) as quality management in the clinical domain. In 2020, presumably due to the coronavirus pandemic, more patients requested to be vaccinated against influenza as compared to previous years so that it became apparent that there would be a shortage for high-risk patients. To meet the problem, we started a CQG process. This article is explicitly not a research article but an exemplary description of a CQG process intended as a stimulus and for discussion. We initiated the following process: (1) evaluation of the present state, (2) patients who already had requested a vaccination were prioritized and vaccinated first, and (3) contacting via telephone and vaccination of high-risk patients not on the list. We chose patients with chronic obstructive pulmonary disease (COPD) older than 60 years as an indicator for the group of highest priority. In the beginning only 3 (8%) of our 38 patients with COPD were vaccinated against influenza. After prioritization and vaccination of the high-risk collective in the list of those who had requested to be vaccinated, 25 (66%) of our 38 patients with COPD were vaccinated. After a phone call of high-risk patients not on the list, 28 (74%) patients were vaccinated. This represents an increase of vaccination coverage from 8% to 74% which is close to the rate recommended by the World Health Organization (WHO). In times of a pandemic, family physicians occasionally have to deal with a scarcity of resources and have to develop strategies for fair resource allocation. Not only in this context is CQG worth the effort. The generation of list queries could be improved by the providers of electronic patient records.

Psychological Determinants of Vaccination Readiness against COVID-19 and Seasonal Influenza of the Chronically Ill in Primary Care in Germany-A Cross-Sectional Survey.

Vaccines against COVID-19 and influenza are highly recommended for the chronically ill. They often suffer from co-morbid mental health issues. This cross-sectional observational study analyzes the associations between depression (PHQ-9) and anxiety (OASIS) with vaccination readiness (5C) against COVID-19 and influenza in chronically ill adults in primary care in Germany. Sociodemographic data, social activity (LSNS), patient activation measure (PAM), and the doctor/patient relationship (PRA) are examined as well. Descriptive statistics and linear mixed-effects regression models are calculated. We compare data from n = 795 study participants. The symptoms of depression are negatively associated with confidence in COVID-19 vaccines (p = 0.010) and positively associated with constraints to get vaccinated against COVID-19 (p = 0.041). There are no significant associations between symptoms of depression and vaccination readiness against influenza. Self-reported symptoms of a generalized anxiety disorder seem not to be associated with vaccination readiness. To address confidence in COVID-19 vaccines among the chronically ill, targeted educational interventions should be elaborated to consider mental health issues like depression. As general practitioners play a key role in the development of a good doctor/patient relationship, they should be trained in patient-centered communication. Furthermore, a standardized implementation of digital vaccination management systems might improve immunization rates in primary care.

Process evaluation in practice based research networks: a study protocol for a mixed-methods implementation study.

INTRODUCTION: General practitioners often criticise clinical trials for their poor applicability in primary care, which may at least partially explain why their engagement in primary care research remains limited. In order to enhance primary care research, the German government has funded six regional practice based research networks (PBRNs). Within the Bavarian PBRN (BayFoNet), two cluster-randomised pilot trials will be conducted. This paper presents the protocol of the process evaluation accompanying both trials, which aims to explore relevance, feasibility, acceptability and credibility of clinical research in primary care from the perspectives of BayFoNet researchers, general practitioners, and patients. METHODS AND ANALYSIS: The BayFoNet will be established by recruiting general practices (GPs) as prospective research collaborators in two cluster randomised pilot trials. Research teams will provide training in good clinical practice, and support practices in patient recruitment, data collection and documentation. Our process evaluation explores barriers and facilitators in the set up of the BayFoNet PBRN and both cluster randomised pilot trials, under the application of the consolidated framework for implementation research and the theoretical domains framework. In a mixed-methods concept, we will use qualitative and quantitative approaches to evaluate both pilot cluster-randomised trials as well as the BayFoNet itself: focus groups with researchers, semi-structured interviews with general practitioners and questionnaires for patients participating in the pilot cluster-randomised trials at three different time points. ETHICS AND DISSEMINATION: Research ethical approval for this study was granted by the Ethics Committee of the Medical Department, Ludwig-Maximilians-University Munich (AZ 21-1135). Results will be published in international peer-reviewed journals and summaries will be provided to the funders of the study as well as other PBRNs, GP teams and patients. TRIAL REGISTRATION NUMBERS: DRKS00028805, NCT05667207.

"What else to say?"-Primary health care in times of COVID-19 from the perspective of German general practitioners: An exploratory analysis of the open text field in the PRICOV-19 study.

BACKGROUND: The international collaboration study PRICOV-19 -Primary Health Care in times of COVID-19 aims to assess the impact of the COVID-19 pandemic on the organisation of primary health care. The German part focuses on the subjective perceptions of general practitioners on primary health care and the impact of political measures during the second wave of the COVID-19 pandemic. Within this survey, the "open text field" of the questionnaire was utilised remarkably frequently and extensively by the respondents. It became clear that the content that was named needed to be analysed in an exploratory manner. Accordingly, this paper addresses the following question: What preoccupies general practitioners in Germany during COVID-19 that we have not yet asked them enough? METHODS: The data collection took place throughout Germany from 01.02.2021 to 28.02.2021with a quantitative online questionnaire consisting of 53 items arranged across six topics as well as an "open text field" for further comments. The questionnaire's open text field was analysed following the premises of the qualitative content analysis. RESULTS: The topics discussed by the respondents were: insufficient support from health policies, not being prioritised and involved in the vaccination strategy, feeling insufficient prepared, that infrastructural changes and financial concerns threatened the practice, and perceiving the own role as important, as well as that health policies affected the wellbeing of the respondents. One of the main points was the way general practitioners were not sufficiently acknowledged for their contribution to ensuring high-quality care during the pandemic. DISCUSSION: German general practitioners perceived their work and role as highly relevant during the COVID-19 pandemic. In controversy with their perception, they described political conditions in which they were the ones who contributed significantly to the fight against the pandemic but were not given enough recognition.

The use of foundational ontologies in biomedical research.

BACKGROUND: The FAIR principles recommend the use of controlled vocabularies, such as ontologies, to define data and metadata concepts. Ontologies are currently modelled following different approaches, sometimes describing conflicting definitions of the same concepts, which can affect interoperability. To cope with that, prior literature suggests organising ontologies in levels, where domain specific (low-level) ontologies are grounded in domain independent high-level ontologies (i.e., foundational ontologies). In this level-based organisation, foundational ontologies work as translators of intended meaning, thus improving interoperability. Despite their considerable acceptance in biomedical research, there are very few studies testing foundational ontologies. This paper describes a systematic literature mapping that was conducted to understand how foundational ontologies are used in biomedical research and to find empirical evidence supporting their claimed (dis)advantages. RESULTS: From a set of 79 selected papers, we identified that foundational ontologies are used for several purposes: ontology construction, repair, mapping, and ontology-based data analysis. Foundational ontologies are claimed to improve interoperability, enhance reasoning, speed up ontology development and facilitate maintainability. The complexity of using foundational ontologies is the most commonly cited downside. Despite being used for several purposes, there were hardly any experiments (1 paper) testing the claims for or against the use of foundational ontologies. In the subset of 49 papers that describe the development of an ontology, it was observed a low adherence to ontology construction (16 papers) and ontology evaluation formal methods (4 papers). CONCLUSION: Our findings have two main implications. First, the lack of empirical evidence about the use of foundational ontologies indicates a need for evaluating the use of such artefacts in biomedical research. Second, the low adherence to formal methods illustrates how the field could benefit from a more systematic approach when dealing with the development and evaluation of ontologies. The understanding of how foundational ontologies are used in the biomedical field can drive future research towards the improvement of ontologies and, consequently, data FAIRness. The adoption of formal methods can impact the quality and sustainability of ontologies, and reusing these methods from other fields is encouraged.

"The measures taken by the government overburdened the daily practice" - insights of the PRICOV-19 study on German general practitioners in times of COVID-19.

BACKGROUND: The international study PRICOV-19 aims to assess the impact of the COVID-19 pandemic on the organisation of primary health care. The German part focuses on German general practitioners during the second wave of the COVID-19 pandemic. This paper addresses the following research questions: (1) How were changes in tasks on primary care and patient treatment perceived by GPs?, (2) What was the role of GPs during the pandemic, and how was their wellbeing?, (3) How did GPs perceive health policy measures?, and, (4) What influenced the attitudes of GPs on health policy measures? METHODS: This study pursues a multi-country cross-sectional design. Data collection took place throughout Germany from 01.02. to 28.02.2021 with a quantitative online questionnaire consisting of 53 items. The questionnaire was analysed through descriptive and inferential analyses using correlation and multiple regression models. RESULTS: The response rate was 20.4% (n = 349). The respondents were mainly GPs (59.6%) in single practices (62.5%) with a mean work experience of 15 to 20 years. GPs experienced a change in their work and practice organisation (80.3%). They felt a high responsibility (70.6%) and found their work has become more meaningful to them (76%). They also saw a lack of political support (75.2%) and that the measures taken by the government overburdened the daily practice (66.4%). Not many GPs were at risk of being distressed (53.4%) but rated the health policies rather negatively (60%). The multiple regression showed, the more GPs were exposed to risk of distress, the worse they assessed the government's measures. CONCLUSION: GPs perceived their work as relevant and felt confident they could fulfil their tasks, but noticed that health policy initially hardly supported the outpatient sector. Health policies should increase their competence in relation to primary care, ensure its needs and consider an active inclusion of GPs in preparedness plans.

Machine learning in Huntington's disease: exploring the Enroll-HD dataset for prognosis and driving capability prediction.

BACKGROUND: In biomedicine, machine learning (ML) has proven beneficial for the prognosis and diagnosis of different diseases, including cancer and neurodegenerative disorders. For rare diseases, however, the requirement for large datasets often prevents this approach. Huntington's disease (HD) is a rare neurodegenerative disorder caused by a CAG repeat expansion in the coding region of the huntingtin gene. The world's largest observational study for HD, Enroll-HD, describes over 21,000 participants. As such, Enroll-HD is amenable to ML methods. In this study, we pre-processed and imputed Enroll-HD with ML methods to maximise the inclusion of participants and variables. With this dataset we developed models to improve the prediction of the age at onset (AAO) and compared it to the well-established Langbehn formula. In addition, we used recurrent neural networks (RNNs) to demonstrate the utility of ML methods for longitudinal datasets, assessing driving capabilities by learning from previous participant assessments. RESULTS: Simple pre-processing imputed around 42% of missing values in Enroll-HD. Also, 167 variables were retained as a result of imputing with ML. We found that multiple ML models were able to outperform the Langbehn formula. The best ML model (light gradient boosting machine) improved the prognosis of AAO compared to the Langbehn formula by 9.2%, based on root mean squared error in the test set. In addition, our ML model provides more accurate prognosis for a wider CAG repeat range compared to the Langbehn formula. Driving capability was predicted with an accuracy of 85.2%. The resulting pre-processing workflow and code to train the ML models are available to be used for related HD predictions at: https://github.com/JasperO98/hdml/tree/main . CONCLUSIONS: Our pre-processing workflow made it possible to resolve the missing values and include most participants and variables in Enroll-HD. We show the added value of a ML approach, which improved AAO predictions and allowed for the development of an advisory model that can assist clinicians and participants in estimating future driving capability.

Personal Genomes in Practice: Exploring Citizen and Healthcare Professionals' Perspectives on Personalized Genomic Medicine and Personal Health Data Spaces Using a Mixed-Methods Design.

Ongoing health challenges, such as the increased global burden of chronic disease, are increasingly answered by calls for personalized approaches to healthcare. Genomic medicine, a vital component of these personalization strategies, is applied in risk assessment, prevention, prognostication, and therapeutic targeting. However, several practical, ethical, and technological challenges remain. Across Europe, Personal Health Data Space (PHDS) projects are under development aiming to establish patient-centered, interoperable data ecosystems balancing data access, control, and use for individual citizens to complement the research and commercial focus of the European Health Data Space provisions. The current study explores healthcare users' and health care professionals' perspectives on personalized genomic medicine and PHDS solutions, in casu the Personal Genetic Locker (PGL). A mixed-methods design was used, including surveys, interviews, and focus groups. Several meta-themes were generated from the data: (i) participants were interested in genomic information; (ii) participants valued data control, robust infrastructure, and sharing data with non-commercial stakeholders; (iii) autonomy was a central concern for all participants; (iv) institutional and interpersonal trust were highly significant for genomic medicine; and (v) participants encouraged the implementation of PHDSs since PHDSs were thought to promote the use of genomic data and enhance patients' control over their data. To conclude, we formulated several facilitators to implement genomic medicine in healthcare based on the perspectives of a diverse set of stakeholders.

Microattribution and nanopublication as means to incentivize the placement of human genome variation data into the public domain.

The advances in bioinformatics required to annotate human genomic variants and to place them in public data repositories have not kept pace with their discovery. Moreover, a law of diminishing returns has begun to operate both in terms of data publication and submission. Although the continued deposition of such data in the public domain is essential to maximize both their scientific and clinical utility, rewards for data sharing are few, representing a serious practical impediment to data submission. To date, two main strategies have been adopted as a means to encourage the submission of human genomic variant data: (1) database journal linkups involving the affiliation of a scientific journal with a publicly available database and (2) microattribution, involving the unambiguous linkage of data to their contributors via a unique identifier. The latter could in principle lead to the establishment of a microcitation-tracking system that acknowledges individual endeavor and achievement. Both approaches could incentivize potential data contributors, thereby encouraging them to share their data with the scientific community. Here, we summarize and critically evaluate approaches that have been proposed to address current deficiencies in data attribution and discuss ways in which they could become more widely adopted as novel scientific publication modalities.