Introducing Attribute Association Graphs to Facilitate Medical Data Exploration: Development and Evaluation Using Epidemiological Study Data.

BACKGROUND: Interpretability and intuitive visualization facilitate medical knowledge generation through big data. In addition, robustness to high-dimensional and missing data is a requirement for statistical approaches in the medical domain. A method tailored to the needs of physicians must meet all the abovementioned criteria. OBJECTIVE: This study aims to develop an accessible tool for visual data exploration without the need for programming knowledge, adjusting complex parameterizations, or handling missing data. We sought to use statistical analysis using the setting of disease and control cohorts familiar to clinical researchers. We aimed to guide the user by identifying and highlighting data patterns associated with disease and reveal relations between attributes within the data set. METHODS: We introduce the attribute association graph, a novel graph structure designed for visual data exploration using robust statistical metrics. The nodes capture frequencies of participant attributes in disease and control cohorts as well as deviations between groups. The edges represent conditional relations between attributes. The graph is visualized using the Neo4j (Neo4j, Inc) data platform and can be interactively explored without the need for technical knowledge. Nodes with high deviations between cohorts and edges of noticeable conditional relationship are highlighted to guide the user during the exploration. The graph is accompanied by a dashboard visualizing variable distributions. For evaluation, we applied the graph and dashboard to the Hamburg City Health Study data set, a large cohort study conducted in the city of Hamburg, Germany. All data structures can be accessed freely by researchers, physicians, and patients. In addition, we developed a user test conducted with physicians incorporating the System Usability Scale, individual questions, and user tasks. RESULTS: We evaluated the attribute association graph and dashboard through an exemplary data analysis of participants with a general cardiovascular disease in the Hamburg City Health Study data set. All results extracted from the graph structure and dashboard are in accordance with findings from the literature, except for unusually low cholesterol levels in participants with cardiovascular disease, which could be induced by medication. In addition, 95% CIs of Pearson correlation coefficients were calculated for all associations identified during the data analysis, confirming the results. In addition, a user test with 10 physicians assessing the usability of the proposed methods was conducted. A System Usability Scale score of 70.5% and average successful task completion of 81.4% were reported. CONCLUSIONS: The proposed attribute association graph and dashboard enable intuitive visual data exploration. They are robust to high-dimensional as well as missing data and require no parameterization. The usability for clinicians was confirmed via a user test, and the validity of the statistical results was confirmed by associations known from literature and standard statistical inference.

A Unified Data Architecture for Assessing Motor Symptoms in Parkinson's Disease.

INTRODUCTION: The diagnosis and treatment of Parkinson's disease depend on the assessment of motor symptoms. Wearables and machine learning algorithms have emerged to collect large amounts of data and potentially support clinicians in clinical and ambulant settings. STATE OF THE ART: However, a systematical and reusable data architecture for storage, processing, and analysis of inertial sensor data is not available. Consequently, datasets vary significantly between studies and prevent comparability. CONCEPT: To simplify research on the neurodegenerative disorder, we propose an efficient and real-time-optimized architecture compatible with HL7 FHIR backed by a relational database schema. LESSONS LEARNED: We can verify the adequate performance of the system on an experimental benchmark and in a clinical experiment. However, existing standards need to be further optimized to be fully sufficient for data with high temporal resolution.

Evaluating REDCap as the Central Data Collection Tool for the Hamburg City Health Study.

INTRODUCTION: The collection of examination data for large clinical studies is often done with proprietary systems, which are accompanied by several disadvantages such as high cost and low flexibility. With the use of open-source tools, these disadvantages can be overcome and thereby improve data collection as well as data quality. Here we exemplary use the data collection process of the Hamburg City Health Study (HCHS), carried out at the University Medical Center Hamburg-Eppendorf (UKE). We evaluated how the recording of the examination data can be converted from an established, proprietary electronic healthcare record (EHR) system to the free-to-use Research Electronic Data Capture (REDCap) software. METHODS: For this purpose, a technical conversion of the EHR system is described first. Metafiles derived from the EHR system were used for REDCap electronic case report form (eCRF) building. The REDCap system was tested by HCHS study assistants via completion of self-developed tasks mimicking their everyday study life. Usability was quantitatively evaluated via the IBM Computer System Usability Questionnaire (CSUQ) and qualitatively assessed with a semi-structured interview. RESULTS: With the IBM CSUQ, the study assistants rated the usage of the basic REDCap system for HCHS examination data collection with an overall score of 4.39, which represents a medium acceptance. The interview feedback was used to formulate user stories to subsequently increase the administrative sovereignty and to conceptualize a REDCap HCHS information technology (IT) infrastructure. CONCLUSION: Our work aims to serve as a template for evaluating the feasibility of a conversion from a proprietary to a free-to-use data collection tool for large clinical studies such as the HCHS. REDCap has great potential, but extensions and an integration to the current IT infrastructure are required.

Understanding Human-Computer Interactions in Restricted Clinical Environments.

INTRODUCTION: Conducting research on human-computer interaction and information retrieval requires unobtrusive observations within existing network architectures. STATE OF THE ART: Most of the available tools are not suitable to be applied within restricted clinical systems. The specific requirements hinder analysis of the human factors in health sciences. CONCEPT: We identified extensions for popular web browsers as a suitable way to conduct studies in highly regulated environments. IMPLEMENTATION: Considering the specialized requirements and an adequate level of transparency for the recorded clinician, we developed an open-source Web Extension compatible with major web browsers. LESSONS LEARNED: We identified the challenges associated with the specific tool and are preparing its use to understand clinical reasoning in personalized oncology.

Mapping the Oncological Basis Dataset to the Standardized Vocabularies of a Common Data Model: A Feasibility Study.

In their joint effort against cancer, all involved parties within the German healthcare system are obligated to report diagnostics, treatments, progression, and follow-up information for tumor patients to the respective cancer registries. Given the federal structure of Germany, the oncological basis dataset (oBDS) operates as the legally required national standard for oncological reporting. Unfortunately, the usage of various documentation software solutions leads to semantic and technical heterogeneity of the data, complicating the establishment of research networks and collective data analysis. Within this feasibility study, we evaluated the transferability of all oBDS characteristics to the standardized vocabularies, a metadata repository of the observational medical outcomes partnership (OMOP) common data model (CDM). A total of 17,844 oBDS expressions were mapped automatically or manually to standardized concepts of the OMOP CDM. In a second step, we converted real patient data retrieved from the Hamburg Cancer Registry to the new terminologies. Given our pipeline, we transformed 1773.373 cancer-related data elements to the OMOP CDM. The mapping of the oBDS to the standardized vocabularies of the OMOP CDM promotes the semantic interoperability of oncological data in Germany. Moreover, it allows the participation in network studies of the observational health data sciences and informatics under the usage of federated analysis beyond the level of individual countries.

The formins FHOD1 and INF2 regulate inter- and intra-structural contractility of podosomes.

Podosomes are actin-rich adhesion structures that depend on Arp2/3-complex-based actin nucleation. We now report the identification of the formins FHOD1 and INF2 as novel components and additional actin-based regulators of podosomes in primary human macrophages. FHOD1 surrounds the podosome core and is also present at podosome-connecting cables, whereas INF2 localizes at the podosome cap structure. Using a variety of microscopy-based methods; including a semiautomated podosome reformation assay, measurement of podosome oscillations, FRAP analysis of single podosomes, and structured illumination microscopy, both formins were found to regulate different aspects of podosome-associated contractility, with FHOD1 mediating actomyosin contractility between podosomes, and INF2 regulating contractile events at individual podosomes. Moreover, INF2 was found to be a crucial regulator of podosome de novo formation and size. Collectively, we identify FHOD1 and INF2 as novel regulators of inter- and intra-structural contractility of podosomes. Podosomes thus present as one of the few currently identified structures which depend on the concerted activity of both Arp2/3 complex and specific formins and might serve as a model system for the analysis of complex actin architectures in cells.

A novel marker, ARM58, confers antimony resistance to Leishmania spp.

Protozoa of the Leishmania genus cause a variety of disease forms that rank at the top of the list of neglected tropical diseases. Anti-leishmanial drugs based on pentavalent antimony have been the mainstay of therapy for over 60 years and resistance against them is increasingly encountered in the field. The biochemical basis for this is poorly understood and likely diverse. No stringent correlation between genetic markers and antimony resistance has so far been shown, prompting us to use a functional cloning approach to identify markers of resistance. Using gene libraries derived from drug-resistant and drug-sensitive Leishmania braziliensis clinical isolates in a functional cloning strategy, we repeatedly selected one gene locus located on chromosome 20 whose amplification confers increased antimony (III) resistance in vitro to an otherwise sensitive L. braziliensis clone. The gene responsible for the effect encodes a previously hypothetical protein that we dubbed LbrARM58. It comprises four repeats of a domain of unknown function, DUF1935, one of them harbouring a potential trans-membrane domain. The gene is so far unique to the Leishmania genus, while a structurally related gene without antimony resistance functionality is also found in Trypanosoma spp. Overexpression of LbrARM58 also confers antimony resistance to promastigotes and intracellular amastigotes of the related species Leishmania infantum, indicating a conserved function in Old World and New World Leishmania species. Our results also show that in spite of their RNAi system, L. braziliensis promastigotes can serve as acceptor cells for episomally propagated cosmid libraries, at least for the initial stages of functional cloning efforts.

Thr202Ala in thyA is a marker for the Latin American Mediterranean lineage of the Mycobacterium tuberculosis complex rather than para-aminosalicylic acid resistance.

Single nucleotide polymorphisms (SNPs) involved in the development of resistance represent powerful markers for the rapid detection of first- and second-line resistance in clinical Mycobacterium tuberculosis complex (MTBC) isolates. However, the association between particular mutations and phenotypic resistance is not always clear-cut, and phylogenetic SNPs have been misclassified as resistance markers in the past. In the present study, we investigated the utility of a specific polymorphism in thyA (Thr202Ala) as a marker for resistance to para-aminosalicyclic acid (PAS). Sixty-three PAS-susceptible MTBC strains comprising all major phylogenetic lineages, reference strain H37Rv, and 135 multidrug-resistant (MDR) strains from Germany (comprising 8 PAS-resistant isolates) were investigated for the presence of Thr202Ala. In both strain collections, the Thr202Ala SNP was found exclusively in strains of the Latin American Mediterranean (LAM) lineage irrespective of PAS resistance. Furthermore, PAS MICs (0.5 mg/liter) for selected LAM strains (all containing the SNP) and non-LAM strains (not containing the SNP), as well as the results of growth curve analyses performed in liquid 7H9 medium in the presence of increasing PAS concentrations (0 to 2.0 mg/liter), were identical. In conclusion, our data demonstrate that the Thr202Ala polymorphism in thyA is not a valid marker for PAS resistance but, instead, represents a phylogenetic marker for the LAM lineage of the M. tuberculosis complex. These findings challenge some of the previous understanding of PAS resistance and, as a consequence, warrant further in-depth investigations of the genetic variation in PAS-resistant clinical isolates and spontaneous mutants.