Objective
The primary objective of project IMPHEENITY is to develop and validate an AI model predicting cardiovascular risk in T1D by integrating diverse clinical and immunological features.
The secondary objectives are:
- Define immunophenotypic features associated with CV risk in people with T1D in primary prevention, risk-assessed with Steno Type 1 Risk Engine (WP1, WP2, WP3).
- Decipher the link between immune markers and key CV risk parameters in T1D: glycemic phenotypes, obesity, insulin resistance, myocardial function, endothelial dysfunction (selectin, VCAM), Lipoprotein(a) (Lp(a)) levels, genetic risk (i.e. haptoglobin 2-2 carriers) and inflammation (WP1).
- Develop and validate a multimodal AI model to predict CV risk in T1D, combining features from established Steno Type 1 Risk Engine variables, genetic parameters, continuous glucose monitoring (CGM) metrics and immune markers, to improve identification of persons with high CV risk (WP4).
- Identify immune-based targets for pharmacological therapies to reduce CV risk or prevent CVD in people with T1D (WP3, WP4).
Background Rationale
Cardiovascular diseases, such as heart attacks and strokes, are the leading cause of death globally, responsible for nearly one-third of all deaths. People with type 1 diabetes are especially at risk, with a significantly higher chance of developing heart problems compared to those without diabetes. This increased risk adds not only to their health burden but also leads to higher medical costs. In the United States, treating heart-related issues in people with type 1 diabetes can cost thousands of dollars more each year compared to those without these complications.
High blood sugar levels, which are common in people with type 1 diabetes, play a key role in increasing heart disease risk. Over time, high blood sugar can damage the blood vessels and contribute to the buildup of plaque in the arteries, which can lead to heart attacks and strokes. Other factors, like high cholesterol and high blood pressure, also contribute to heart disease risk, especially after living with type 1 diabetes for many years.
However, these factors alone do not explain why people who develop type 1 diabetes at a young age seem to be at greater risk of heart disease, even before the age of 40. One tool that researchers and clinicians can use to predict heart disease risk is called the Steno Type 1 Risk Engine, which calculates a risk score based on factors like age, gender, blood sugar levels, cholesterol, and kidney function. While helpful, this tool does not take into account the role of the immune system, even though we know the immune system plays a critical role in heart health.
Research shows that people with type 1 diabetes tend to have a more active immune system, which may lead to higher inflammation and a greater risk of heart disease. By taking the immune system into account, we may be able to find new ways to predict heart disease risk and better understand why people with type 1 diabetes are particularly at risk. This could help improve how doctors assess heart risk in people with type 1 diabetes and lead to more personalized treatments in the future.
Description of Project
Cardiovascular diseases, such as heart attacks and strokes, are the leading cause of death worldwide, responsible for nearly one-third of all deaths. People with type 1 diabetes are at a higher risk of developing these diseases, adding a significant burden on their health and healthcare systems. Besides, they even have a higher risk of developing cardiovascular diseases compared to the population without diabetes, even when they do not have any of the most frequent cardiovascular disease risk factors such as smoking, obesity, and high cholesterol levels, and it is unclear why. Currently, researchers and clinicians can rely on tools such as the Steno Type 1 Risk Engine to predict a person’s risk of developing heart problems in the next 5 to 10 years. This tool uses a variety of factors like age, gender, cholesterol levels, and physical activity. While helpful, there is a need to improve this prediction thanks to the integration of other markers such as the immune system and inflammation markers.
Our project, called IMPHEENITY, aims to explore how the immune system may influence the risk of heart problems in people with type 1 diabetes. We believe that by studying the immune system in detail, we can find new ways to predict heart risks more accurately and identify those at greatest risk earlier. The project will combine traditional heart risk factors (like cholesterol and blood sugar) with advanced information about a person's immune system to create better prediction tools.
To achieve this, our team will conduct large-scale studies to identify immune markers, genetic factors, and clinical parameters linked to heart disease in people with type 1 diabetes. We will also use artificial intelligence (AI) to analyze this large data and create a model that can give more personalized predictions about heart risks. Ultimately, this approach could help doctors develop more tailored treatments for people with type 1 diabetes, potentially preventing heart problems before they happen.
The IMPHEENITY project hopes to improve our understanding of how type 1 diabetes affects the heart, paving the way for better healthcare and outcomes for all people living with type 1 diabetes.
Anticipated Outcome
In the short term, our project aims to improve existing prediction models, such as the Steno Type 1 Risk Engine, and develop a powerful new AI-based tool that doctors can use to more accurately identify patients at high risk of cardiovascular diseases. This tool will help clinicians offer more personalized care and suggest preventive measures that could reduce the risk of heart disease.
In the long term, we expect our findings to guide the development of new treatments that target the underlying causes of heart disease in people with type 1 diabetes. Our research will help identify new potential therapies, either by designing new medications or by finding new uses for existing drugs. Eventually, these therapies will be tested in clinical trials, which will help determine how well they work in preventing heart problems in high-risk patients. By working with industrial partners, we aim to turn these discoveries into practical treatments that can improve the health and lives of people with type 1 diabetes.
Relevance to T1D
Type 1 diabetes is a lifelong condition that affects millions of people worldwide. Along with the daily challenges of managing blood sugar levels, people with type 1 diabetes are at a significantly higher risk of developing heart disease and other cardiovascular issues. People with type 1 diabetes are more likely to experience heart attacks or strokes compared to those without diabetes. This increased risk is particularly concerning because it often arises earlier in life, sometimes before the age of 40.
Current tools used by clinicians and researchers to predict heart disease in people with type 1 diabetes focus on traditional risk factors like cholesterol levels, blood pressure, and blood sugar control. However, these tools do not take into account the role of the immune system, even though inflammation and immune system activity are key factors in cardiovascular diseases.
Our project aims to close this gap by studying how the immune system contributes to cardiovascular risk in people with type 1 diabetes. By combining traditional risk factors with new insights from the immune system, we hope to develop a more accurate way to predict heart disease in people with type 1 diabetes. This will help doctors better identify which patients are at the highest risk and enable them to offer more personalized care.
Ultimately, the insights gained from this research could lead to new treatments that target the underlying causes of cardiovascular diseases in people with type 1 diabetes, improving their health and quality of life. Our work is a crucial step toward reducing the burden of cardiovascular diseases in people with type 1 diabetes and ensuring they receive the best possible care.