New European Research Uncovers Hidden Cardiovascular Risk Profiles and Patterns Within Type 1 Diabetes

New European study reveals why BMI and glucose alone fail to predict heart risks in T1D, offering a smarter way to catch cardiac complications early.

By: AXL Media

Published: Apr 20, 2026, 8:07 AM EDT

Source: Information for this report was sourced from Nature Communications

A Departure From Traditional Glucose Focused Metrics

The inherent difficulty in predicting heart disease for those with type 1 diabetes stems from a complex interplay between chronic hyperglycemia and shifting metabolic markers. While clinicians have long relied on blood sugar management as the primary barometer for health, this new analysis published in Nature Communications suggests that cardiovascular risk remains stubbornly high even when glucose levels appear stable. According to Dr. Liji Thomas, the study utilized a phenotype-driven tool to bridge this diagnostic gap, focusing specifically on the discordance between a patient’s body mass index and their internal cardiometabolic biomarkers.

Mapping Metabolic Diversity Across European Cohorts

To validate these findings, researchers scrutinized cross-sectional data from approximately 44,000 patients across three major European cohorts, including the KUL, DPV, and SIDIAP groups. The methodology involved the use of Uniform Manifold Approximation and Projection to plot vast arrays of demographic and biological data, effectively creating a visual map of risk. This process revealed that type 1 diabetes patients do not fit into a single risk category but instead manifest through three primary profiles: concordant, inflammatory, and a heavily overrepresented hyperglycemic phenotype.

The Dominance of the Hyperglycemic Phenotype

One of the most striking revelations from the research is the sheer prevalence of the discordant hyperglycemic profile, which affected between 55 percent and 76 percent of the type 1 diabetes population. In contrast, this same profile is found in only 2.5 percent of the general population, highlighting a unique physiological burden for those with the condition. The data indicates that while lower glycated hemoglobin levels align with a lower-risk profile similar to the general public, the vast majority of patients remain trapped in a high-risk state that traditional BMI measurements alone cannot capture.