Periodic Reporting for period 1 - GLUCOTYPES (Glucose variability patterns for precision nutrition in diabetes)
Berichtszeitraum: 2024-10-01 bis 2025-09-30
Large clinical trials have consistently shown the effectiveness of dietary and lifestyle modification in preventing or delaying T2D onset in high-risk individuals. However, the challenge in effectively controlling T2D lies in its fundamental complexity. This complexity is partially rooted in the molecular heterogeneity underlying T2D and the varied impact of dietary interventions on glucose homeostasis and body weight loss. Prior research has shown that some individuals develop T2D because they have a predominant defect in insulin secretion pathways, while others have impaired insulin sensitivity and an impaired glycemic control due to alterations in adipose tissue metabolism or function or ectopic fat accumulation and insulin resistance in peripheral tissue like liver and skeletal muscle . This etiological heterogeneity, which could indicate different disease subtypes concealed within the current broad T2D definition, explains the large variability in response to dietary interventions and the underwhelming translation of effective prevention strategies. There is an urgent need for a paradigm shift in our approach to T2D prevention.
Building on large population-based cohorts, high-throughput molecular analyses, and novel analytical methodologies, the project has generated fundamental insights into human glycaemic variability, its molecular determinants, and its interactions with diet. These achievements lay the scientific and operational foundation for personalised dietary strategies that account for inter-individual metabolic heterogeneity.
A major accomplishment in this period has been the identification and validation of patterns of glycaemic fluctuations derived from CGM data. Through state-of-the-art analytical approaches, including generative AI models and functional data analysis, we identified glucotypes and show their longitudinal association with long-term glycaemic outcomes such as HbA1c and progression towards type 2 diabetes.
The project has also advanced the understanding of diet–glucose interactions, applying multivariable and functional regression models to link dietary patterns, macronutrient profiles, meal timing, and individual characteristics with glycaemic responses and longer-term outcomes. Analyses show that high glycaemic-load meals, starch-rich or dairy-rich meal compositions, age, BMI, and metabolic status substantially modulate postprandial glucose curves. CGM-derived indicators—such as time above range (TAR ≥130 mg/dL)—were independently predictive of diabetes risk over 10 years, demonstrating their value for early clinical identification and targeted prevention strategies. Collective findings from several high-impact publications confirm that glucotypes capture physiologically meaningful heterogeneity in dietary responses, providing a robust empirical basis for personalised nutritional advice.
Complementing these advancements, the consortium has made significant progress in molecular glycomics and glycoproteomics, a core innovation of GLUCOTYPES. High-throughput N-glycome profiling of 434 serum samples yielded 39 quantifiable glycan peaks, while a newly established plasma glycoproteomics workflow enabled the identification and validation of over 1,000 N-glycopeptides across 54 proteins. This workflow provides high analytical robustness, precise quantification of glycoforms, and scalable processing suitable for large cohorts. In parallel, pilot studies optimized glycomics methodologies for adipose and muscle tissue biopsies, detecting more than 100 glycans per tissue type and revealing biologically relevant differences between adipocytes and mixed-cell tissues. These efforts position GLUCOTYPES to integrate glycan signatures with CGM-derived glucotypes, enabling entirely new avenues for molecular phenotyping, disease risk assessment, and diet-induced glycosylation dynamics.
Operationally, substantial progress has been made in preparing the GAIN precision nutrition trial, which will be the first clinical evaluation of glucotype-based dietary recommendations. The protocol is nearing completion for ethics submission, with detailed work on glucotype assignment, dietary algorithms, and clinical research workflows. This future trial will translate observational findings into interventional evidence, marking a critical step toward clinical implementation.
A major accomplishment in this period has been the identification and validation of patterns of glycaemic fluctuations derived from CGM data. Through state-of-the-art analytical approaches, including generative AI models and functional data analysis, we identified glucotypes and show their longitudinal association with long-term glycaemic outcomes such as HbA1c and progression towards type 2 diabetes.
The project has also advanced the understanding of diet–glucose interactions, applying multivariable and functional regression models to link dietary patterns, macronutrient profiles, meal timing, and individual characteristics with glycaemic responses and longer-term outcomes. Analyses show that high glycaemic-load meals, starch-rich or dairy-rich meal compositions, age, BMI, and metabolic status substantially modulate postprandial glucose curves. CGM-derived indicators—such as time above range (TAR ≥130 mg/dL)—were independently predictive of diabetes risk over 10 years, demonstrating their value for early clinical identification and targeted prevention strategies. Collective findings from several high-impact publications confirm that glucotypes capture physiologically meaningful heterogeneity in dietary responses, providing a robust empirical basis for personalised nutritional advice.
Complementing these advancements, the consortium has made significant progress in molecular glycomics and glycoproteomics, a core innovation of GLUCOTYPES. High-throughput N-glycome profiling of 434 serum samples yielded 39 quantifiable glycan peaks, while a newly established plasma glycoproteomics workflow enabled the identification and validation of over 1,000 N-glycopeptides across 54 proteins. This workflow provides high analytical robustness, precise quantification of glycoforms, and scalable processing suitable for large cohorts. In parallel, pilot studies optimized glycomics methodologies for adipose and muscle tissue biopsies, detecting more than 100 glycans per tissue type and revealing biologically relevant differences between adipocytes and mixed-cell tissues. These efforts position GLUCOTYPES to integrate glycan signatures with CGM-derived glucotypes, enabling entirely new avenues for molecular phenotyping, disease risk assessment, and diet-induced glycosylation dynamics.
Operationally, substantial progress has been made in preparing the GAIN precision nutrition trial, which will be the first clinical evaluation of glucotype-based dietary recommendations. The protocol is nearing completion for ethics submission, with detailed work on glucotype assignment, dietary algorithms, and clinical research workflows. This future trial will translate observational findings into interventional evidence, marking a critical step toward clinical implementation.
GLUCOTYPES is generating significant advances beyond the current state of the art in diabetes prevention and precision nutrition.
For the first time, CGM-derived glucotypes, molecular glycomics, microbiome data, and diet records are being integrated into a single predictive modelling architecture, exceeding existing precision-nutrition approaches that rely primarily on glucose or dietary data alone. Robust fundational models demonstrate transferability of glucotype profiles across diverse populations over multiple years, enhancing the clinical viability of glucotype-based risk stratification.
The newly developed high-throughput platforms allow quantification of >1,000 glycopeptides per sample, offering unprecedented biological resolution for personalised health research.
Foundations for precision-nutrition clinical trials: The GAIN study design operationalises the first glucotype-specific dietary intervention, marking a major translational step beyond current guidelines.
Strengthened exploitation potential: Early industry engagement and the establishment of IPR governance lay the groundwork for downstream applications in digital health, diagnostic tools, and personalised nutrition services.
For the first time, CGM-derived glucotypes, molecular glycomics, microbiome data, and diet records are being integrated into a single predictive modelling architecture, exceeding existing precision-nutrition approaches that rely primarily on glucose or dietary data alone. Robust fundational models demonstrate transferability of glucotype profiles across diverse populations over multiple years, enhancing the clinical viability of glucotype-based risk stratification.
The newly developed high-throughput platforms allow quantification of >1,000 glycopeptides per sample, offering unprecedented biological resolution for personalised health research.
Foundations for precision-nutrition clinical trials: The GAIN study design operationalises the first glucotype-specific dietary intervention, marking a major translational step beyond current guidelines.
Strengthened exploitation potential: Early industry engagement and the establishment of IPR governance lay the groundwork for downstream applications in digital health, diagnostic tools, and personalised nutrition services.