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Co-Occurring Cardiovascular/Metabolic Abnormalities Linked to Widespread Alterations In Brain Connectivity

Key findings

  • This study investigated how cardiovascular/metabolic (CVM) health associates with whole-brain functional connectivity and how cumulative CVM risk affects network-level functional connectivity
  • The subjects were 930 healthy participants aged between 36 to 90+ years old in the Human Connectome Project in Aging (HCP-A) study who underwent functional MRI and were free of stroke, dementia symptoms, and other causes of cognitive decline
  • A composite index of CVM health factors was calculated for each participant from variables such as heart rate, blood pressure, creatinine clearance, body mass index, hemoglobin A1c, cholesterol, triglycerides, C-reactive protein, and albumin
  • Regardless of any CVM diagnosis, worse index scores were associated with reduced functional connectivity globally and among higher-order brain networks that support cognitive function; this was true across the lifespan
  • These findings add to the imperative to screen adults early and regularly for CVM risk factors so that intervention can lead to optimal brain health and functioning

Cardiovascular and metabolic (CVM) disorders, such as dyslipidemia and insulin resistance, overweight and obesity, hypertension, and inflammation, have been associated with Alzheimer's disease and other forms of dementia in older adults. Even subclinical CVM abnormalities have been tied to cognitive impairment.

Researchers at Massachusetts General Hospital recently published insights into the impact of CVM abnormalities on whole-brain functional integrity, concluding that earlier attention to them might improve brain health across adulthood.

Barnaly Rashid, PhD, an instructor in the Department of Neurology, David H. Salat, PhD, director of the Brain Aging and Dementia Laboratory at the Martinos Center for Biomedical Imaging, Steven E. Arnold, MD, director of the Clinical and Translational Research Unit (CTRU), and managing director of the Interdisciplinary Brain Center at Massachusetts General Hospital, and colleagues report in NeuroImage.


The researchers used data on 930 of 1,200 healthy participants in the Human Connectome Project in Aging (HCP-A) study who were 36 to 90+ years old. All were free of stroke, dementia symptoms, and other causes of cognitive decline. They underwent functional MRI at rest at four sites that used matching acquisition and analysis protocols.

A composite index of CVM health factors was calculated for each participant from 12 variables: heart rate, heart rate variability, blood pressure, creatinine clearance, body mass index, hemoglobin A1c, total low-density and high-density lipoprotein cholesterol, triglycerides, vitamin D, C-reactive protein, and albumin.

Whole-Brain Functional Connectivity

Regardless of any particular CVM diagnosis, worsening of the CVM index was associated with reduced whole-brain functional connectivity, emphasizing the importance of even subclinical interindividual variation. The effects were particularly strong in the insular, medial frontal, medial parietal, and superior temporal regions.

This was true across the adult lifespan. The association was strongest among younger and middle-aged adults, but it was still statistically significant in older adults.

Network-Level Findings

As the CVM index worsened, the higher-order brain networks that are vital to everyday cognitive function showed altered functional connectivity among themselves as well as with other brain networks. Those included the default-mode network, cingulo-opercular network, and dorsal attention network.

Clinical Relevance

These findings suggest brain alterations due to classic CVM risk factors may occur even earlier than previously reported, emphasizing the importance of screening younger adults for CVM disorders. Early detection will allow the greatest opportunity for diet, lifestyle, and medical therapy to preserve functional connectivity, maximize cerebral reserve and resilience, and prevent common neurocognitive disorders of aging.

Learn more about the Martinos Center for Biomedical Imaging

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Massachusetts General Hospital's Clinical and Translational Research Unit (CTRU) supports investigators conducting complex brain disorders research.


Binyin Li, MD, David H. Salat, PhD, and colleagues created a machine learning classifier that detected Alzheimer's disease–like brain patterns in younger adults (40 to 59 years old) and in a cohort with mild cognitive impairment.