New study links type 2 diabetes to accelerated cognitive decline

Type 2 diabetes is a chronic condition that affects millions globally. Characterised by insulin resistance and elevated blood glucose levels, the disease can lead to severe complications such as heart disease, kidney failure and nerve damage. Over time, the body’s ability to regulate blood sugar deteriorates, causing long-term damage to various organ systems. One of the less recognised yet equally alarming consequences of diabetes is its impact on brain health. Recent studies suggest that type 2 diabetes can accelerate cognitive decline, particularly through the loss of brain matter, including white matter, which plays a crucial role in efficient brain function. Understanding the relationship between diabetes and brain health could be key to developing therapies that preserve cognitive function and improve the quality of life for patients living with diabetes.

Sam Hashemi, Vice President of Artificial Intelligence and Research at Prenuvo, and his team have uncovered vital insights into the link between type 2 diabetes and cognitive decline, particularly in relation to white matter loss. This study enhances our understanding of how diabetes affects the brain and paves the way for future therapies aimed at slowing or preventing cognitive decline in diabetic patients. Prenuvo, recognised for its whole-body MRI technology, is advancing health diagnostics by combining AI and radiology tools. In this interview, Hashemi discusses how these innovations are shaping the future of healthcare.

AI’s role in early brain health detection

Prenuvo’s whole-body magnetic resonance imaging (MRI) is revolutionising the detection and monitoring of health conditions, offering the ability to scan the entire body in under an hour without the use of contrast or radiation. The technology can identify over 500 conditions, including early-stage tumours, metabolic disorders and even brain aneurysms. However, in the area of brain health Prenuvo’s MRI technology has shown particularly transformative potential. “We’re focused on advancing radiology-facing products that enable radiologists to garner patient-facing insights using our unique dataset of whole-body MRIs to define health norms,” Hashemi said. “Our work also aims to contribute to scientific understanding through high-impact publications on ageing and organ health correlations.”

AI played a key role in analysing Prenuvo’s MRI scans for this study, helping to identify subtle changes in brain structure and body composition that could easily go undetected. “Using advanced AI tools, we segmented the brain into 96 distinct regions to precisely measure white and grey matter,” Hashemi explained. The findings, which revealed a reduction in white matter volume, particularly within the occipital lobe, are causing a paradigm shift in how type 2 diabetes is understood in the context of brain health. The occipital lobe, responsible for visual processing, spatial reasoning and memory, is especially critical for cognitive functions. As Hashemi noted, “White matter is essential for keeping the brain connected, helping different regions share information efficiently. It’s what allows us to learn, focus and react.”

For the longest time, researchers believed that lower brain matter volumes in diabetics were primarily associated with factors like visceral fat, BMI and weight. However, Prenuvo’s study challenges this assumption by demonstrating that type 2 diabetes independently affects brain health, particularly through its impact on white matter volume. This stimulates new discussions within the diabetic community and sets the stage for further exploration into how diabetes may accelerate brain ageing and contribute to cognitive decline.

Cognitive decline in diabetic patients

The implications of these findings are profound, especially when considering the potential for future therapies. “White matter acts as the communication network within the brain, connecting different regions to ensure seamless cognitive function,” Hashemi pointed out. “In this study, we saw a loss of white matter, especially in the occipital lobe, which helps with visual processing, spatial reasoning and memory.”

While these changes may not manifest obvious symptoms in the short term, the cumulative effects over time could increase the risk of cognitive decline, including conditions like dementia. This emphasises the importance of monitoring brain health in diabetic patients early on, leading to more effective treatments or preventative strategies. For diabetics, maintaining brain health could soon become as critical as managing blood glucose levels. The emerging data suggests that early intervention could significantly slow the progression of brain matter loss and reduce the risk of more severe cognitive impairment later in life.

AI’s role in advancing drug discovery and biomarker identification

In addition to its utility in diagnosing and tracking disease progression, AI-powered tools are playing a pivotal role in uncovering new therapeutic targets and potential biomarkers for chronic diseases like diabetes. With its ability to process vast amounts of data with high precision, AI is enabling researchers to analyse complex datasets in ways that were once unimaginable. “The effectiveness of AI depends heavily on the quality and scope of the data it analyses,” Hashemi said. “Prenuvo’s extensive dataset, built from over 100,000 scans, provided the scale and depth necessary to identify meaningful patterns across organs and systems.”

For drug discovery and early-phase development, this represents a significant advantage. AI can quantify intricate details of biological structures in 3D, offering a level of insight far beyond the human eye. By combining data from over a hundred thousand scans, AI can help identify new biomarkers for diseases like type 2 diabetes and its complications, which may open the door for new, targeted treatments.

In the context of this study, the AI-driven analysis revealed structural brain changes linked to diabetes, providing potential biomarkers that could be used for early diagnosis and facilitating earlier interventions that may prevent or mitigate cognitive decline. “This highlights the importance of considering the bigger picture when designing intervention plans for patients,” Hashemi added. “Insights like the relationship between diabetes and brain health emphasise the need for comprehensive, personalised care, helping practitioners develop more effective strategies for patients managing one or both of these conditions.”

A new era of preventative healthcare

Prenuvo’s whole-body MRI and AI insights are advancing preventative healthcare. With over 100,000 scans completed and an ever-growing dataset, Prenuvo has amassed a wealth of data that benefits patients while advancing scientific understanding.

By offering patients a full-body scan that provides a comprehensive view of their health, Prenuvo empowers individuals to take a proactive approach to their wellbeing, shifting the focus from reactive treatment to prevention. This shift is especially crucial in addressing chronic conditions like type 2 diabetes, where early detection and intervention can significantly improve outcomes. As our understanding of diabetes’ impact on brain health grows, innovations like Prenuvo’s whole-body MRI are set to play a pivotal role in both early diagnosis and the development of more effective treatments. With continued progress in AI and data science, the future of healthcare looks promising, offering new hope for better health management and prevention strategies.