Cohort Profile: Research Advancement through Cohort Cataloguing and Harmonization (ReACH).
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ABSTRACT:
SUBMITTER: Bergeron J
PROVIDER: S-EPMC8128473 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundThe lack of accessible and structured documentation creates major barriers for investigators interested in understanding, properly interpreting and analyzing cohort data and biological samples. Providing the scientific community with open information is essential to optimize usage of these resources. A cataloguing toolkit is proposed by Maelstrom Research to answer these needs and support the creation of comprehensive and user-friendly study- and network-specific web-based metadata catalogues.MethodsDevelopment of the Maelstrom Research cataloguing toolkit was initiated in 2004. It was supported by the exploration of existing catalogues and standards, and guided by input from partner initiatives having used or pilot tested incremental versions of the toolkit.ResultsThe cataloguing toolkit is built upon two main components: a metadata model and a suite of open-source software applications. The model sets out specific fields to describe study profiles; characteristics of the subpopulations of participants; timing and design of data collection events; and datasets/variables collected at each data collection event. It also includes the possibility to annotate variables with different classification schemes. When combined, the model and software support implementation of study and variable catalogues and provide a powerful search engine to facilitate data discovery.ConclusionsThe Maelstrom Research cataloguing toolkit already serves several national and international initiatives and the suite of software is available to new initiatives through the Maelstrom Research website. With the support of new and existing partners, we hope to ensure regular improvements of the toolkit.
| S-EPMC6057635 | biostudies-literature
Project description: Not available
| S-EPMC9557858 | biostudies-literature
Project description:Pseudoenzymes are present within many, but not all, known enzyme families and lack one or more conserved canonical amino acids that help define their catalytically active counterparts. Recent findings in the pseudokinase field confirm that evolutionary repurposing of the structurally defined bilobal protein kinase fold permits distinct biological functions to emerge, many of which rely on conformational switching, as opposed to canonical catalysis. In this analysis, we evaluate progress in evaluating several members of the 'dark' pseudokinome that are pertinent to help drive this expanding field. Initially, we discuss how adaptions in erythropoietin-producing hepatocellular carcinoma (Eph) receptor tyrosine kinase domains resulted in two vertebrate pseudokinases, EphA10 and EphB6, in which co-evolving sequences generate new motifs that are likely to be important for both nucleotide binding and catalysis-independent signalling. Secondly, we discuss how conformationally flexible Tribbles pseudokinases, which have radiated in the complex vertebrates, control fundamental aspects of cell signalling that may be targetable with covalent small molecules. Finally, we show how species-level adaptions in the duplicated canonical kinase protein serine kinase histone (PSKH)1 sequence have led to the appearance of the pseudokinase PSKH2, whose physiological role remains mysterious. In conclusion, we show how the patterns we discover are selectively conserved within specific pseudokinases, and that when they are modelled alongside closely related canonical kinases, many are found to be located in functionally important regions of the conserved kinase fold. Interrogation of these patterns will be useful for future evaluation of these, and other, members of the unstudied human kinome.
| S-EPMC7586955 | biostudies-literature
Project description:Myasthenia gravis (MG) is an autoimmune neuromuscular junction disease mediated by antibodies against the acetylcholine receptor (AChR). The etiology and immunopathogenesis of MG remain unclear. Recent research has shown the involvement of autoantibodies, lymphocytes, cytokines and chemokines, in the pathogenesis of MG. Systematic factors are also demonstrated, such as inheritance and endocrine. This review indicates the research development in immunopathogenesis of MG.
| S-EPMC5560374 | biostudies-other
Project description:Background/study contextHarmonizing measures in order to conduct pooled data analyses has become a scientific priority in aging research. Retrospective harmonization where different studies lack common measures of comparable constructs presents a major challenge. This study compared different approaches to harmonization with a crosswalk sample who completed multiple versions of the measures to be harmonized.MethodsThrough online recruitment, 1061 participants aged 30 to 98 answered two different depression scales, and 1065 participants answered multiple measures of subjective health. Rational and configural methods of harmonization were applied, using the crosswalk sample to determine their success; and empirical item response theory (IRT) methods were applied in order empirically to compare items from different measures as answered by the same person.ResultsFor depression, IRT worked well to provide a conversion table between different measures. The rational method of extracting semantically matched items from each of the two scales proved an acceptable alternative to IRT. For subjective health, only configural harmonization was supported. The subjective health items used in most studies form a single robust factor.ConclusionCaution is required in aging research when pooling data across studies using different measures of the same construct. Of special concern are response scales that vary widely in the number of response options, especially if the anchors are asymmetrical. A crosswalk sample that has completed items from each of the measures being harmonized allows the investigator to use empirical approaches to identify flawed assumptions in rational or configural approaches to harmonizing.
| S-EPMC4772674 | biostudies-literature
Project description:BackgroundIt is widely accepted and acknowledged that data harmonization is crucial: in its absence, the co-analysis of major tranches of high quality extant data is liable to inefficiency or error. However, despite its widespread practice, no formalized/systematic guidelines exist to ensure high quality retrospective data harmonization.MethodsTo better understand real-world harmonization practices and facilitate development of formal guidelines, three interrelated initiatives were undertaken between 2006 and 2015. They included a phone survey with 34 major international research initiatives, a series of workshops with experts, and case studies applying the proposed guidelines.ResultsA wide range of projects use retrospective harmonization to support their research activities but even when appropriate approaches are used, the terminologies, procedures, technologies and methods adopted vary markedly. The generic guidelines outlined in this article delineate the essentials required and describe an interdependent step-by-step approach to harmonization: 0) define the research question, objectives and protocol; 1) assemble pre-existing knowledge and select studies; 2) define targeted variables and evaluate harmonization potential; 3) process data; 4) estimate quality of the harmonized dataset(s) generated; and 5) disseminate and preserve final harmonization products.ConclusionsThis manuscript provides guidelines aiming to encourage rigorous and effective approaches to harmonization which are comprehensively and transparently documented and straightforward to interpret and implement. This can be seen as a key step towards implementing guiding principles analogous to those that are well recognised as being essential in securing the foundational underpinning of systematic reviews and the meta-analysis of clinical trials.
| S-EPMC5407152 | biostudies-literature
Project description:BackgroundClinical trials remain key to the development of evidence-based medical practice. However, they are becoming increasingly complex, mainly in a multinational setting. To address these challenges, the European Union (EU) adopted the Clinical Trial Regulation EU No. 536/2014 (CTR). Once in force, the CTR will lead to more consistent rules and simplification of procedures for conducting clinical trials throughout the EU. Existing harmonization initiatives and "research infrastructures" for clinical trials may facilitate this process. This publication offers a snapshot of the current level of harmonization activities in academic clinical research in Europe.MethodsA survey was performed among the member and observer countries of the European Clinical Research Infrastructure Network (ECRIN), using a standardized questionnaire. Three rounds of data collection were performed to maximize completeness and comparability of the received answers. The survey aimed to describe the harmonization of academic clinical research processes at national level, to facilitate the exchange of expertise and experience among countries, and to identify new fields of action.ResultsMost scientific partners already have in place various working groups and harmonization activities at national level. Furthermore, they are involved in and open to sharing their know-how and documents. Since harmonization was mainly a bottom-up approach up until now, the extent and topics dealt with are diverse and there is only little cross-networking and cross-country exchange so far.ConclusionsCurrently, the ECRIN member countries offer a very solid base and collaborative spirit for further aligning processes and exchanging best practices for clinical research in Europe. They can support a smooth implementation of the EU CTR and may act as single contact with consolidated expertise in a country.
| S-EPMC8051345 | biostudies-literature
Project description: Not available
| S-EPMC9365637 | biostudies-literature
Project description:The Applied Research Group for Kids (TARGet Kids!) is an ongoing open longitudinal cohort study enrolling healthy children (from birth to 5 years of age) and following them into adolescence. The aim of the TARGet Kids! cohort is to link early life exposures to health problems including obesity, micronutrient deficiencies and developmental problems. The overarching goal is to improve the health of Canadians by optimizing growth and developmental trajectories through preventive interventions in early childhood. TARGet Kids!, the only child health research network embedded in primary care practices in Canada, leverages the unique relationship between children and families and their trusted primary care practitioners, with whom they have at least seven health supervision visits in the first 5 years of life. Children are enrolled during regularly scheduled well-child visits. To date, we have enrolled 5062 children. In addition to demographic information, we collect physical measurements (e.g. height, weight), lifestyle factors (nutrition, screen time and physical activity), child behaviour and developmental screening and a blood sample (providing measures of cardiometabolic, iron and vitamin D status, and trace metals). All data are collected at each well-child visit: twice a year until age 2 and every year until age 10. Information can be found at: http://www.targetkids.ca/contact-us/.
| S-EPMC4521122 | biostudies-literature
Project description:Cancer epidemiologists have a long history of combining data sets in pooled analyses, often harmonizing heterogeneous data from multiple studies into 1 large data set. Although there are useful websites on data harmonization with recommendations and support, there is little research on best practices in data harmonization; each project conducts harmonization according to its own internal standards. The field would be greatly served by charting the process of data harmonization to enhance the quality of the harmonized data. Here, we describe the data harmonization process utilized at the Fred Hutchinson Cancer Research Center (Seattle, Washington) by the coordinating centers of several research projects. We describe a 6-step harmonization process, including: 1) identification of questions the harmonized data set is required to answer; 2) identification of high-level data concepts to answer those questions; 3) assessment of data availability for data concepts; 4) development of common data elements for each data concept; 5) mapping and transformation of individual data points to common data elements; and 6) quality-control procedures. Our aim here is not to claim a "correct" way of doing data harmonization but to encourage others to describe their processes in order that we can begin to create rigorous approaches. We also propose a research agenda around this issue.
| S-EPMC4675662 | biostudies-literature