Glow Up: a single-centre observational study protocol to develop digital biomarkers for prediabetes screening and digital phenotyping

Introduction: Prediabetes, a key precursor to type 2 diabetes, is highly prevalent and underdiagnosed, particularly among adults aged ≥45 years with elevated body mass index (BMI). Early detection is critical because lifestyle interventions can delay or prevent progression to type 2 diabetes. The Glucose Observation and Wearable Use for Prevention (Glow Up) study aims to (1) test the feasibility of a digital biomarker for pre-diabetes screening using wearable- and smartphone-derived lifestyle factors (eg, sleep, physical activity and nutrition patterns) in daily life and to (2) characterise individual- and metabolic subgroup-level variability in lifestyle factors and glycaemic control. Specifically, we aim to examine how lifestyle factors relate to glycaemic status and identify personalised predictors of early metabolic dysregulation.

Methods and analysis: Glow Up is a prospective, single-centre, observational case-control study conducted in Switzerland. Adults (n=200) aged ≥45 years with body mass index (BMI) ≥25 kg/m² will be recruited, including n=100 individuals with pre-diabetes and n=100 age- and sex-matched normoglycaemic controls. Participants will undergo 4 weeks of continuous monitoring using a blinded continuous glucose monitor (CGM) and commercial- and medical-grade wearables; for example, capturing physical activity, sleep and physiological markers (heart rate variability, heart rate and skin temperature), in addition to completing daily image-based meal logs using smartphones. Glycated haemoglobin (HbA1c), fasting plasma glucose (FPG) and body anthropometrics will be collected at the enrolment visit (T0) and repeated at follow-up (T3), approximately 5 weeks apart. The primary outcome is glycaemic status at T3, classified from HbA1c and FPG using prespecified thresholds. Secondary outcomes include CGM metrics, lifestyle profiling (sleep, physical activity, stress and nutrition) and adherence to image-based meal logging.