Proteomics reveals the hidden impact of interventions in diabetes
ABSTRACT
Type 2 diabetes typically manifests itself in adulthood, following years of progressively worsening health status, affecting multiple biological systems, pathways and organs. But beyond measuring HbA1c, it has been difficult and expensive to measure the impact of disease and/or interventions that might impact organ damage or risk.
Large-scale proteomics is an emerging field that has recently been shown to not only capture real-time health status, but also to predict or prognose risks of future organ damage, morbidity and mortality. Proteomic models, developed from multiple large clinical and observational studies, have been utilized here to provide a holistic summary of metabolic health and risk of future adverse outcomes from individuals undergoing diabetes intervention.
In this webcast, the impact of both therapeutic (drug) and lifestyle (diet and exercise) interventions will be discussed on a host of cardiometabolic and body composition measures in subjects undergoing intervention compared to placebo or standard of care. The speakers will discuss how these proteomic models can be implemented to design more precise treatment strategies for diabetic patients, moving the field ever closer to realizing the goal of providing personalized care.
Learn:
- What additional information broad scale proteomics can contribute to your research program
- How newly-discovered proteomic signatures can be applied to clinical research
- The benefits of being able to obtain raw proteomic data and clinical assessments from a single 55 µL blood sample
Svati H. Shah, MD, MHS
Professor of Medicine, Director of Precision Genomics
Duke University School of Medicine
Svati H. Shah, MD, MHS, is a physician scientist and Associate Dean of Genomics and Director of Precision Genomics Collaboratory in the Duke School of Medicine; Vice-Chief of Translational Research and Director of the Adult Cardiovascular Genetics Clinic in the Division of Cardiology, Department of Medicine; Co-Director of Translational Research in the Duke Molecular Physiology Institute (DMPI); and a faculty member in the Duke Clinical Research Institute (DCRI). Her research focus is on metabolic and genetic pathways of cardiometabolic diseases, integrating diverse genomic, metabolomic and proteomic techniques for identification of novel mechanisms of disease and biomarkers.
Stephen A. Williams, MD, PhD
Chief Medical Officer, Somalogic
Steve Williams, MD, Ph.D, practiced medicine for over a decade at Charing Cross Hospital before joining Pfizer, where he became the VP and Worldwide Head of Clinical Technology. Since 2009 he has been the Chief Medical Officer at SomaLogic, where his focus has been on developing clinical tests using proteomic signatures.
Naveed Sattar, FMedSci, FRCPath, FRCPGlas, FRSE
Professor of Metabolic Medicine University of Glasgow
Professor Sattar is a clinically active academic, researching the causes, prevention and management of diabetes, obesity and CVD. He has published >1,000 papers, and contributed to several guidelines and clinical trials. He has received multiple award lectures, including 2020’s EASD Camillo Golgi Prize, and is a global Highly Cited Researcher.
Proteomics reveals the hidden impact of interventions in diabetes
A presentation by Svati H. Shah, MD, MHS, Stephen A. Williams, MD, PhD, and Naveed Sattar, FMedSci, FRCPath, FRCPGlas, FRSE
More webinars
WebinarBoutique Webinar Aptamers with protein-like side chains as a versatile tool for high-content proteomics
Proteins, encoded in 20,000 genes in humans, do much of the work in biology. Measuring proteins, which change in response to various perturbations and represent targets for almost all drugs, offers insights about the health status of an organism. Since proteins operate in complex networks rather than in isolation, measuring multiple proteins simultaneously offers richer insights compared to single protein measurements.
WebinarUsing Proteomics To Advance Understanding of Alzheimer’s Disease
Limited understanding due to its complex pathophysiology and lack of definitive biomarkers currently constrains the diagnosis and treatment of Alzheimer’s disease (AD). But new research is uncovering dynamic brain changes during Alzheimer’s progression, offering potential therapeutic targets. This webinar explores how proteomics and systems biology can be integrated to elucidate AD pathology.
WebinarPredictive modeling and reliable biomarker discovery in clinical omics studies
High-content omic technologies coupled machine learning methods have transformed the biomarker discovery process. However, the translation of computational results into scalable clinical biomarkers remains challenging. A rate-limiting step is the rigorous selection of reliable biomarker candidates among a host of biological features. Drawing examples from real-world clinical omics studies, I will introduce Stabl, a general machine learning framework that identifies a sparse, reliable set of biomarkers by integrating noise injection and a data-driven signal-to-noise threshold into multivariable predictive modeling.