Data Provenance in Biomedical Research: Scoping Review.

BACKGROUND: Data provenance refers to the origin, processing, and movement of data. Reliable and precise knowledge about data provenance has great potential to improve reproducibility as well as quality in biomedical research and, therefore, to foster good scientific practice. However, despite the increasing interest on data provenance technologies in the literature and their implementation in other disciplines, these technologies have not yet been widely adopted in biomedical research. OBJECTIVE: The aim of this scoping review was to provide a structured overview of the body of knowledge on provenance methods in biomedical research by systematizing articles covering data provenance technologies developed for or used in this application area; describing and comparing the functionalities as well as the design of the provenance technologies used; and identifying gaps in the literature, which could provide opportunities for future research on technologies that could receive more widespread adoption. METHODS: Following a methodological framework for scoping studies and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines, articles were identified by searching the PubMed, IEEE Xplore, and Web of Science databases and subsequently screened for eligibility. We included original articles covering software-based provenance management for scientific research published between 2010 and 2021. A set of data items was defined along the following five axes: publication metadata, application scope, provenance aspects covered, data representation, and functionalities. The data items were extracted from the articles, stored in a charting spreadsheet, and summarized in tables and figures. RESULTS: We identified 44 original articles published between 2010 and 2021. We found that the solutions described were heterogeneous along all axes. We also identified relationships among motivations for the use of provenance information, feature sets (capture, storage, retrieval, visualization, and analysis), and implementation details such as the data models and technologies used. The important gap that we identified is that only a few publications address the analysis of provenance data or use established provenance standards, such as PROV. CONCLUSIONS: The heterogeneity of provenance methods, models, and implementations found in the literature points to the lack of a unified understanding of provenance concepts for biomedical data. Providing a common framework, a biomedical reference, and benchmarking data sets could foster the development of more comprehensive provenance solutions.

Open tools for quantitative anonymization of tabular phenotype data: literature review.

Precision medicine relies on molecular and systems biology methods as well as bidirectional association studies of phenotypes and (high-throughput) genomic data. However, the integrated use of such data often faces obstacles, especially in regards to data protection. An important prerequisite for research data processing is usually informed consent. But collecting consent is not always feasible, in particular when data are to be analyzed retrospectively. For phenotype data, anonymization, i.e. the altering of data in such a way that individuals cannot be identified, can provide an alternative. Several re-identification attacks have shown that this is a complex task and that simply removing directly identifying attributes such as names is usually not enough. More formal approaches are needed that use mathematical models to quantify risks and guide their reduction. Due to the complexity of these techniques, it is challenging and not advisable to implement them from scratch. Open software libraries and tools can provide a robust alternative. However, also the range of available anonymization tools is heterogeneous and obtaining an overview of their strengths and weaknesses is difficult due to the complexity of the problem space. We therefore performed a systematic review of open anonymization tools for structured phenotype data described in the literature between 1990 and 2021. Through a two-step eligibility assessment process, we selected 13 tools for an in-depth analysis. By comparing the supported anonymization techniques and further aspects, such as maturity, we derive recommendations for tools to use for anonymizing phenotype datasets with different properties.

Antiviral metabolite 3'-deoxy-3',4'-didehydro-cytidine is detectable in serum and identifies acute viral infections including COVID-19.

BACKGROUND: There is a critical need for rapid viral infection diagnostics to enable prompt case identification in pandemic settings and support targeted antimicrobial prescribing. METHODS: Using untargeted high-resolution liquid chromatography coupled with mass spectrometry, we compared the admission serum metabolome of emergency department patients with viral infections (including COVID-19), bacterial infections, inflammatory conditions, and healthy controls. Sera from an independent cohort of emergency department patients admitted with viral or bacterial infections underwent profiling to validate findings. Associations between whole-blood gene expression and the identified metabolite of interest were examined. FINDINGS: 3'-Deoxy-3',4'-didehydro-cytidine (ddhC), a free base of the only known human antiviral small molecule ddhC-triphosphate (ddhCTP), was detected for the first time in serum. When comparing 60 viral with 101 non-viral cases in the discovery cohort, ddhC was the most significantly differentially abundant metabolite, generating an area under the receiver operating characteristic curve (AUC) of 0.954 (95% CI: 0.923-0.986). In the validation cohort, ddhC was again the most significantly differentially abundant metabolite when comparing 40 viral with 40 bacterial cases, generating an AUC of 0.81 (95% CI 0.708-0.915). Transcripts of viperin and CMPK2, enzymes responsible for ddhCTP synthesis, were among the five genes most highly correlated with ddhC abundance. CONCLUSIONS: The antiviral precursor molecule ddhC is detectable in serum and an accurate marker for acute viral infection. Interferon-inducible genes viperin and CMPK2 are implicated in ddhC production in vivo. These findings highlight a future diagnostic role for ddhC in viral diagnosis, pandemic preparedness, and acute infection management. FUNDING: NIHR Imperial BRC; UKRI.

A comparative genomics examination of desiccation tolerance and sensitivity in two sister grass species.

Desiccation tolerance is an ancient and complex trait that spans all major lineages of life on earth. Although important in the evolution of land plants, the mechanisms that underlay this complex trait are poorly understood, especially for vegetative desiccation tolerance (VDT). The lack of suitable closely related plant models that offer a direct contrast between desiccation tolerance and sensitivity has hampered progress. We have assembled high-quality genomes for two closely related grasses, the desiccation-tolerant Sporobolus stapfianus and the desiccation-sensitive Sporobolus pyramidalis Both species are complex polyploids; S. stapfianus is primarily tetraploid, and S. pyramidalis is primarily hexaploid. S. pyramidalis undergoes a major transcriptome remodeling event during initial exposure to dehydration, while S. stapfianus has a muted early response, with peak remodeling during the transition between 1.5 and 1.0 grams of water (gH2O) g-1 dry weight (dw). Functionally, the dehydration transcriptome of S. stapfianus is unrelated to that for S. pyramidalis A comparative analysis of the transcriptomes of the hydrated controls for each species indicated that S. stapfianus is transcriptionally primed for desiccation. Cross-species comparative analyses indicated that VDT likely evolved from reprogramming of desiccation tolerance mechanisms that evolved in seeds and that the tolerance mechanism of S. stapfianus represents a recent evolution for VDT within the Chloridoideae. Orthogroup analyses of the significantly differentially abundant transcripts reconfirmed our present understanding of the response to dehydration, including the lack of an induction of senescence in resurrection angiosperms. The data also suggest that failure to maintain protein structure during dehydration is likely critical in rendering a plant desiccation sensitive.

Composite modeling of leaf shape along shoots discriminates Vitis species better than individual leaves.

PREMISE: Leaf morphology is dynamic, continuously deforming during leaf expansion and among leaves within a shoot. Here, we measured the leaf morphology of more than 200 grapevines (Vitis spp.) over four years and modeled changes in leaf shape along the shoot to determine whether a composite leaf shape comprising all the leaves from a single shoot can better capture the variation and predict species identity compared with individual leaves. METHODS: Using homologous universal landmarks found in grapevine leaves, we modeled various morphological features as polynomial functions of leaf nodes. The resulting functions were used to reconstruct modeled leaf shapes across the shoots, generating composite leaves that comprehensively capture the spectrum of leaf morphologies present. RESULTS: We found that composite leaves are better predictors of species identity than individual leaves from the same plant. We were able to use composite leaves to predict the species identity of previously unassigned grapevines, which were verified with genotyping. DISCUSSION: Observations of individual leaf shape fail to capture the true diversity between species. Composite leaf shape-an assemblage of modeled leaf snapshots across the shoot-is a better representation of the dynamic and essential shapes of leaves, in addition to serving as a better predictor of species identity than individual leaves.

Inequities in the global representation of sites participating in large, multicentre dialysis trials: a systematic review.

BACKGROUND: The number of dialysis recipients is growing worldwide, making it important that the full range of patient populations are represented in randomised trials. As trial recruitment has not previously been examined at a global level, we compared the location of trial sites recruiting to large multicentre randomised controlled trials (RCTs) in dialysis to the global distribution of dialysis recipients. METHODS: A systematic review (2007-2016) was conducted to identify RCTs enrolling ≥100 dialysis patients from ≥2 sites. The number and location of sites were extracted from manuscripts and trial registration. The proportion of sites from each International Society of Nephrology global region was divided by the proportion of the global dialysis population in that region to determine a 'representation index' (RI), where 1.0 indicated that the number of sites was proportionate to the number of dialysis recipients in that region. RESULTS: We identified 180 RCTs, recruiting from 6172 sites in 54 countries. Eastern and Central Europe had the highest RI at 2.45. Other well-represented regions were Western Europe (2.20), North America (2.06), and Russia and newly independent states (1.36). Africa had the lowest RI at 0.05, followed by South Asia (0.08), Latin America (0.15), Middle East (0.27), North-East Asia (0.41), and South-East Asia and Oceania (0.62). CONCLUSIONS: Regions of the world with growing numbers of dialysis patients are poorly represented in large, multicentre RCTs. Efforts to boost trial participation in these regions are required to ensure that generalisable and relevant information is available to local healthcare providers.

Representativeness of Randomized Clinical Trial Cohorts in End-stage Kidney Disease: A Meta-analysis.

IMPORTANCE: Systematic differences between patients included in randomized clinical trials (RCTs) and the general patient population may influence the generalizability of RCT findings. Comprehensive national registries of patients with end-stage kidney disease who are undergoing dialysis provide a unique opportunity to compare trial and real-world patient cohorts. OBJECTIVE: To determine if participants in large, multicenter dialysis trials were similar to the general population undergoing dialysis in terms of age, comorbidities, and mortality rate. DATA SOURCES: MEDLINE, PubMed, and the Cochrane Central Register of Controlled Trials were systematically searched on January 6, 2017, for studies published from January 1, 2007, to December 31, 2016. Data sources were published manuscripts, supplementary material, and trial registration information. Data on the general population undergoing dialysis were derived from the US Renal Data System (USRDS). Data were analyzed from March 17 to July 22, 2018. STUDY SELECTION: Randomized clinical trials enrolling only participants undergoing dialysis for end-stage kidney disease with 100 or more adult participants from 2 or more sites. DATA EXTRACTION AND SYNTHESIS: Abstract screening and data extraction were performed independently by 2 researchers. Data were pooled using a random-effects model. MAIN OUTCOMES AND MEASURES: The primary outcome was difference in mean age between the RCT and USRDS populations. Secondary outcomes included differences in mortality rate and comorbidities. RESULTS: The search identified 186 RCTs, enrolling 79 104 participants. Compared with the 2011 USRDS population, RCT participants were younger (mean age, 58.9 years; 95% CI, 58.3-59.5 years vs 61.2 years; P < .001), more likely to be male (58.9%; 95% CI, 57.6%-60.1% vs 55.7%; P < .001), and have coronary artery disease (26.9%; 95% CI, 22.2%-31.7% vs 17.7%; P < .001) and less likely to have diabetes (40.2%; 95% CI, 36.7%-43.6% vs 44.2%; P = .03) or heart failure (19.6%; 95% CI, 15.1%-24.0% vs 29.8%; P < .001). The mortality rate per 100 patient-years during trial participation was less than half that of the USRDS population (8.9; 95% CI, 7.8-10.0 vs 18.6; P < .001). The differences in age, mortality, and coronary artery disease remained when studies recruiting only from the United States were considered. Diabetes was more common in RCT participants from the United States than in the registry population. CONCLUSIONS AND RELEVANCE: Participants in large, multicenter RCTs of patients with end-stage kidney disease undergoing dialysis are younger, have a different pattern of comorbidities, and have a lower mortality rate than the general population of patients undergoing dialysis. This finding has implications for the generalization of trial results to the broader patient population and for future trial design.