MDBiomarkers: A queryable biomarkers database integrating multiple serum and tissue datasets for Duchenne muscular dystrophy

Journal of Neuromuscular Diseases, pp. 22143602261458436

Abstract

BackgroundFit-for-purpose biomarkers are urgently needed in Duchenne muscular dystrophy (DMD). However, biomarker efforts in DMD have traditionally been hampered by a lack of reproducibility due to small sample sizes, confounders such as treatment and age, and discordant findings from different technologies. Moreover, there is no central resource to get an overview of cumulative published evidence. Hence, many researchers often start with new discovery studies, which are time-consuming and costly.ObjectiveBuild a dynamic, searchable, and easy-to-use biomarker platform for DMD.MethodsThousands of molecular (serum proteins and muscle mRNA) markers from multiple studies (28 analyses) were compiled. Findings were obtained from supplemental material of published manuscripts or by following standardized pipelines on available raw data. These findings were annotated with important attributes (e.g., age range, treatment, etc.). Evidence was aggregated around each biomarker's association with DMD, treatment, age, clinical outcomes, as well as other markers.ResultsThe interactive Shiny application on https://www.mdbiomarkers.com provides exportable summaries of serum protein and muscle tissue mRNA findings. This also permits new knowledge to be generated for nuanced meta-analyses, rather than being restricted by a single study's finding and p-value. A tutorial is provided on the website. This resource is planned to be continually updated with new/additional findings to fulfill the aim of a living biomarker resource.ConclusionsThe resource developed will reduce preparatory time to distill evidence around important biomarker candidates providing summary estimates around individual studies' effect sizes, help assess cumulative evidence, and help with experimental design of future experiments.

Authors 13

1. Wangshu Tu

   Carleton University

   Affiliation as printed

   Department of Health Sciences, Carleton University

2. Rebecca A. Tobin

   Carleton University

   Affiliation as printed

   Department of Health Sciences, Carleton University

3. Leenah Abdelrazeq

   Carleton University

   Affiliation as printed

   Department of Health Sciences, Carleton University

4. Kaitey Guite

   Carleton University

   Affiliation as printed

   Department of Health Sciences, Carleton University

5. Cristina Al‐Khalili Szigyarto

   KTH Royal Institute of Technology

   Affiliation as printed

   Department of Protein Science, KTH The Royal Institute of Technology

6. Roula Tsonaka Aachen

   Leiden University Medical Center

   Affiliation as printed

   Leiden University Medical Center

7. C. Degan Aachen

   Leiden University Medical Center

   Affiliation as printed

   Leiden University Medical Center

8. Yuri E. M. van der Burgt Aachen

   Leiden University Medical Center

   Affiliation as printed

   Leiden University Medical Center

9. Jordi Díaz-Manera

   Newcastle University

   Affiliation as printed

   John Walton Muscular Dystrophy Research Centre, Newcastle University and Newcastle Hospitals NHS Foundation Trust

10. Michela Guglieri

    Newcastle University

    Affiliation as printed

    John Walton Muscular Dystrophy Research Centre, Newcastle University and Newcastle Hospitals NHS Foundation Trust

11. Pietro Spitali Aachen

    Leiden University Medical Center

    Affiliation as printed

    Leiden University Medical Center

12. Yetrib Hathout

    Binghamton University

    Affiliation as printed

    Binghamton University

13. Utkarsh J. Dang corresponding

    Carleton University

    Affiliation as printed

    Department of Health Sciences, Carleton University