Biomarkers of Insulin Resistance and Their Performance as Predictors of Treatment Response in Overweight Adults.
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2025-12
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Abstract
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Insulin resistance (IR) contributes to the pathogenesis of type 2 diabetes mellitus and is a risk factor for cardiovascular and neurodegenerative diseases. Amino acid and lipid metabolomic biomarkers associate with future type 2 diabetes mellitus risk in several epidemiological cohorts. Whether these biomarkers can accurately monitor changes in IR status following treatment is unclear.Objective
Herein we evaluated the performance of clinical and metabolomic biomarker models to forecast altered IR, following lifestyle-based interventions.Design
We contrasted the performance of two distinct insulin assay types (high-sensitivity ELISA and immunoassay) and built IR diagnostic models using cross-sectional clinical and metabolomic data. These models were used to stratify IR status in preintervention fasting samples, from 3 independent cohorts (META-PREDICT (n = 179), STRRIDE-AT/RT (n = 116), and STRRIDE-PD (n = 149)). Linear and Bayesian projective prediction strategies were used to evaluate models for fasting insulin and homeostatic model assessment 2 for insulin resistance and change in fasting insulin with treatment.Results
Both insulin assays accurately quantified international standard insulin (R2 > 0.99), yet agreement between fasting insulins was less congruent (R2 = 0.65). A mean treatment effect on fasting insulin was only detectable using the ELISA. Clinical-metabolomic models were statistically related to fasting insulin (R2 0.33-0.39) but with modest capacity to classify IR at a clinically relevant homeostatic model assessment 2 for insulin resistance threshold. Furthermore, no model predicted treatment responses in any cohort.Conclusion
We demonstrate that the choice of insulin assay is critical when quantifying the influence of treatment on fasting insulin, whereas none of the clinical-metabolomic biomarkers, identified in cross-sectional studies, are suitable for monitoring longitudinally changes in IR status.Type
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Brogan, Robert J, Olav Rooyackers, Bethan E Phillips, Brigitte Twelkmeyer, Leanna M Ross, Philip J Atherton, William E Kraus, James A Timmons, et al. (2025). Biomarkers of Insulin Resistance and Their Performance as Predictors of Treatment Response in Overweight Adults. The Journal of clinical endocrinology and metabolism, 111(1). pp. 244–255. 10.1210/clinem/dgaf285 Retrieved from https://hdl.handle.net/10161/33845.
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Scholars@Duke
Leanna Ross
Dr. Ross's research focuses on understanding the mechanisms by which exercise interventions elicit short- and long-term cardiometabolic health benefits. As cardiometabolic disease remains the leading cause of morbidity and mortality in the United States, the goal of her translational research is to enhance the development of evidence-based, precision exercise interventions that optimally prevent and treat disease.
Areas of Research Interest
Exercise dose-response and cardiometabolic health
Insulin action and glucose homeostasis
Legacy health benefits of exercise
Heterogeneity of response to exercise intervention
Precision lifestyle medicine
Epidemiology of physical activity and cardiorespiratory fitness
William Erle Kraus
My training, expertise and research interests range from human integrative physiology and genetics to animal exercise models to cell culture models of skeletal muscle adaptation to mechanical stretch. I am trained clinically as an internist and preventive cardiologist, with particular expertise in preventive cardiology and cardiac rehabilitation. My research training spans molecular biology and cell culture, molecular genetics, and integrative human exercise physiology and metabolism. I practice as a preventive cardiologist with a focus on cardiometabolic risk and exercise physiology for older athletes. My research space has both a basic wet laboratory component and a human integrative physiology one.
One focus of our work is an integrative physiologic examination of exercise effects in human subjects in clinical studies of exercise training in normal individuals, in individuals at risk of disease (such as pre-diabetes and metabolic syndrome; STRRIDE), and in individuals with disease (such as coronary heart disease, congestive heart failure and cancer).
A second focus of my research group is exploration of genetic determinates of disease risk in human subjects. We conduct studies of early onset cardiovascular disease (GENECARD; CATHGEN), congestive heart failure (HF-ACTION), peripheral arterial disease (AMNESTI), and metabolic syndrome. We are exploring analytic models of predicting disease risk using established and innovative statistical methodology.
A third focus of my group’s work is to understand the cellular signaling mechanisms underlying the normal adaptive responses of skeletal muscle to physiologic stimuli, such as occur in exercise conditioning, and to understand the abnormal maladaptive responses that occur in response to pathophysiologic stimuli, such as occur in congestive heart failure, aging and prolonged exposure to microgravity.
Recently we have begun to investigate interactions of genes and lifestyle interventions on cardiometabolic outcomes. We have experience with clinical lifestyle intervention studies, particularly the contributions of genetic variants to interventions responses. We call this Lifestyle Medicopharmacogenetics.
KEY WORDS:
exercise, skeletal muscle, energy metabolism, cell signaling, gene expression, cell stretch, heart failure, aging, spaceflight, human genetics, early onset cardiovascular disease, lifestyle medicine
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