Related Experiment Video
Updated: Mar 1, 2026

Generation of High Quality Chromatin Immunoprecipitation DNA Template for High-throughput Sequencing ChIP-seq
Published on: April 19, 2013
Association of genetic risk and physical activity with incident type 2 diabetes
Xuan Zhou1, Germán D Carrasquilla1, Malene R Christiansen1
1Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen 2200, Denmark.
Objective:
The aim of this study was to assess whether daily step counts and genetic risk interact to influence the risk of developing type 2 diabetes.
Research Design And Methods:
We analyzed data from 9501 participants in the All of Us Research Program with both genetic and wearable device-derived physical activity data and without diabetes at baseline and a median age of 56 years (42-66). Physical activity was quantified using daily step counts. Genetic risk was assessed using a global polygenic score. Incident type 2 diabetes was identified using electronic health record-linked diagnostic codes. Multivariable Cox proportional hazards models estimated hazard ratios (HRs) for type 2 diabetes across genetic risk and physical activity levels. We tested for additive interaction using the relative excess risk due to interaction (RERI). In secondary analyses, we used physical-activity intensity measures using wearable-derived and self-reported intensity levels.
Results:
Type 2 diabetes incidence rates ranged from 4.1 per 1000 person-years (95% CI, 2.5-5.7) in individuals with high physical activity and low genetic risk to 18.4 (95% CI, 15.2-21.6) in those with low physical activity and high genetic risk (HR, 6.2 (95% CI: 3.97, 9.6)). A significant additive interaction was observed (RERI, 0.20; 95% CI, 0.04-0.36; P = .007), with 15% (95% CI, 2-27) of excess risk attributed to the interaction. Similar interaction patterns were found using device-based intensity metrics and self-reported physical activity measures.
Conclusion:
These findings provide evidence of additive interactions between genetic risk and physical activity, underscoring the potential value of integrating genomic and device-derived data to identify individuals who would more likely benefit from increasing physical activity.
More Related Videos
07:22Glycemic Impact on Knee Osteoarthritis Symptoms on Physical, Radiographic, and Inflammatory Markers among Individuals Aged 50 and Over with Diabetes
Published on: March 7, 2025
05:59Visualization of Intensity Levels to Reduce the Gap Between Self-Reported and Directly Measured Physical Activity
Published on: March 7, 2019
Related Concept Videos
Diabetes Mellitus: Type 2 and Gestational
Carbohydrate Metabolism
Starch accounts for approximately 60% of the carbohydrates consumed by humans. Since amylase enzymes cannot function in the stomach's acidic environment, starch can only be digested in the mouth and small intestine. Simple sugars are found naturally in milk and fruits in...
Genome-wide Association Studies-GWAS
GWAS does not require the identification of the target gene involved in...
Coronary Artery Disease I: Introduction
Pathophysiology of Diabetes
Type 1 diabetes is characterized by autoimmune-mediated destruction of pancreatic β cells, with environmental factors potentially triggering this process in genetically susceptible individuals. Despite many not having a family history, certain genes increase susceptibility,...
Diabetes: Symptoms, Diagnosis, and Complications