Browsing by Author "Rewers, Marian"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Screening for Type 1 Diabetes in the General Population: A Status Report and Perspective
    (American Diabetes Association, 2022) Sims, Emily K.; Besser, Rachel E. J.; Dayan, Colin; Rasmussen, Cristy Geno; Greenbaum, Carla; Griffin, Kurt J.; Hagopian, William; Knip, Mikael; Long, Anna E.; Martin, Frank; Mathieu, Chantal; Rewers, Marian; Steck, Andrea K.; Wentworth, John M.; Rich, Stephen S.; Kordonouri, Olga; Ziegler, Anette-Gabriele; Herold, Kevan C.; NIDDK Type 1 Diabetes TrialNet Study Group; Pediatrics, School of Medicine
    Most screening programs to identify individuals at risk for type 1 diabetes have targeted relatives of people living with the disease to improve yield and feasibility. However, ∼90% of those who develop type 1 diabetes do not have a family history. Recent successes in disease-modifying therapies to impact the course of early-stage disease have ignited the consideration of the need for and feasibility of population screening to identify those at increased risk. Existing population screening programs rely on genetic or autoantibody screening, and these have yielded significant information about disease progression and approaches for timing for screening in clinical practice. At the March 2021 Type 1 Diabetes TrialNet Steering Committee meeting, a session was held in which ongoing efforts for screening in the general population were discussed. This report reviews the background of these efforts and the details of those programs. Additionally, we present hurdles that need to be addressed for successful implementation of population screening and provide initial recommendations for individuals with positive screens so that standardized guidelines for monitoring and follow-up can be established.
  • Thumbnail Image
    Item
    Tutorial: best practices and considerations for mass-spectrometry-based protein biomarker discovery and validation
    (Springer Nature, 2021) Nakayasu, Ernesto S.; Gritsenko, Marina; Piehowski, Paul D.; Gao, Yuqian; Orton, Daniel J.; Schepmoes, Athena A.; Fillmore, Thomas L.; Frohnert, Brigitte I.; Rewers, Marian; Krischer, Jeffrey P.; Ansong, Charles; Suchy-Dicey, Astrid M.; Evans-Molina, Carmella; Qian, Wei-Jun; Webb-Robertson, Bobbie-Jo M.; Metz, Thomas O.; Pediatrics, School of Medicine
    Mass-spectrometry-based proteomic analysis is a powerful approach for discovering new disease biomarkers. However, certain critical steps of study design such as cohort selection, evaluation of statistical power, sample blinding and randomization, and sample/data quality control are often neglected or underappreciated during experimental design and execution. This tutorial discusses important steps for designing and implementing a liquid-chromatography-mass-spectrometry-based biomarker discovery study. We describe the rationale, considerations and possible failures in each step of such studies, including experimental design, sample collection and processing, and data collection. We also provide guidance for major steps of data processing and final statistical analysis for meaningful biological interpretations along with highlights of several successful biomarker studies. The provided guidelines from study design to implementation to data interpretation serve as a reference for improving rigor and reproducibility of biomarker development studies.