CeVD-related brain network phenotype can provide insights into cognitive decline trajectory

Researchers have discovered new insights into how disruptions in brain function related to cerebrovascular disease (CeVD) interact with the pathology of Alzheimer’s disease (AD) to influence neurodegeneration and cognition in older adults. Led by Associate Professor Juan Helen Zhou, Director of the Center for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore (NUS Medicine), the research team revealed a brain functional connectome phenotype related to multiple CeVD markers and, in addition to AD, also contributes to cognitive decline and neurodegeneration. The study highlights CeVD as a global disruptor of brain connectivity, reshaping our understanding of its role in dementia.

CeVD, which often co-occurs with AD, has long been an important area of ​​investigation in aging and dementia research. It refers to a group of conditions that affect the blood vessels and blood flow in the brain, such as stroke, cerebral atherosclerosis (narrowing or hardening of larger cerebral arteries due to plaque buildup), and small vessel disease that affects the small blood vessels in the brain . the brain. These conditions can lead to brain damage by disrupting the supply of oxygen and nutrients, which are essential for normal brain function.

In the study, published in Alzheimer’s and Dementia: The Journal of the Alzheimer’s Associationthe team examined the functional organization of the brain in 529 older adult participants across the dementia spectrum, ranging from those with healthy cognition to those diagnosed with AD. By analyzing how the various markers of CeVD and brain activity patterns correlate and affect participants, the team identified a global functional connectome phenotype, or a unique pattern in the brain’s communication network, that is strongly associated with the high levels of strain on four markers of CeVD. seen on brain scans. A key finding of the study was the identification of divergent effects of p-tau181a blood-based biomarker for AD, and CeVD-related functional connectome phenotype on cognitive decline and brain atrophy. Although the two factors contributed additively to longitudinal cognitive decline and brain atrophy, the study found no evidence of a synergistic relationship between CeVD and brain atrophy. p-tau181suggesting that these factors may influence neurodegeneration in different pathways.

A/Prof Zhou said: “We found that a CeVD-related brain network phenotype, together with a key blood biomarker for Alzheimer’s disease, could provide powerful insights into the future trajectory of cognitive decline and neurodegeneration. Our findings highlight the potential of brain connectome-based markers to monitor cognitive decline, especially for individuals at risk for dementia, and underscore the importance of integrating neuroimaging and blood biomarkers to better understand the pathophysiology of these co-occurring diseases.”

Dr. Joanna Su Importantly, the combination of this pattern is linked to CeVD and plasma p-tau181a marker of Alzheimer’s disease, had independent and additive effects on long-term outcomes. Together they contributed to cognitive decline and increased brain atrophy at baseline and over time, but did not directly interact to amplify each other’s effects.” Both A/Prof Zhou and Dr. Chong are also from the Center for Sleep and Cognition and Healthy Longevity & Human Potential Translational Research Programs at NUS Medicine.

In the future, the team plans to investigate how the brain communication pattern associated with CeVD is influenced by the severity, cause and location of CeVD markers during disease progression. They also plan to investigate how this pattern interacts with various AD markers to contribute to brain degeneration and decline in multiple cognitive domains. Furthermore, they want to determine whether these brain network functions can be used as a reliable biomarker to monitor current and future cognitive decline, especially in individuals at risk for dementia. These features could provide more accurate predictions than traditional brain imaging methods and help identify long-term cognitive outcomes earlier. Their goal is to better understand the brain mechanisms behind CeVD and AD and develop advanced imaging tools for early detection and disease monitoring.

This research is supported by the National Research Foundation, Singapore under the NMRC Open Fund – Large Collaborative Grant (MOH-000500) and managed by the Singapore Ministry of Health through the NMRC Office, MOH Holdings Pte Ltd. Study participants were recruited from the National University Hospital and St Luke’s Hospital.