A growing amount of evidence points to interactions between heart health and brain health.
Cardiovascular diseases serve as a crucial backdrop for brain diseases like stroke, dementia, cerebral small vessel disease and cognitive impairment. Studies have shown, for example, that atrial fibrillation, even in stroke-free individuals, is associated with an increased incidence of dementia and silent cerebral damage. Heart failure has been linked to cognitive impairment and dementia due to reduced cerebral blood flow caused by a failing heart. Conversely, mental disorders and negative psychological factors may contribute to the onset and progression of cardiovascular diseases. Individuals with conditions such as schizophrenia, bipolar disorder, epilepsy or depression are more prone to cardiovascular diseases.
Despite this growing knowledge, previous studies on heart-brain interactions and associated risk factors have been limited in scope, focusing on specific diseases or utilizing small sample sizes. Consequently, the overall understanding of the structural and functional links between the heart and brain remains incomplete.
A new study conducted by researchers from UNC-Chapel Hill, the University of Pennsylvania and Purdue University leverages large magnetic resonance imaging (MRI) data to shed light on the close relationship between cardiovascular diseases and brain diseases such as stroke, dementia and cognitive impairment, unraveling the underlying genetic signatures and inter-organ connections between the heart and brain.
Led by the Biostatistics and Imaging Genomics Analysis Lab’s Statistics and Signal group (BIG-S2) at Carolina, the study was published today in“Science,” one of the top-ranked journals. The first author of the study is Bingxin Zhao, assistant professor of statistics and data science at the University of Pennsylvania and doctoral alumnus from the UNC Gillings School of Global Public Health.
With expertise in biostatistics, statistics, data science, radiology, computer science and genetics, the team conducted their investigation using data from over 40,000 subjects in the UK Biobank study. They employed a sophisticated pipeline to extract 82 cardiac MRI traits, encompassing measures of the heart’s chambers, aortic sections and regional characteristics. Simultaneously, they identified a wide array of brain MRI traits, including structural, diffusion and functional measures, providing a comprehensive understanding of brain abnormalities and connectivity.
The results, which controlled for various factors, confirmed that heart MRI traits significantly influenced brain health across different imaging modalities. Specifically, adverse features of the left ventricle were strongly associated with poorer white matter microstructure in the brain.
Through genome-wide association studies, the researchers successfully uncovered the genetic architecture underlying heart-brain connections. In total, 80 genomic loci were identified to be associated with heart MRI traits. The genetic effects on heart structure and function were consistent between both sexes. Furthermore, the study revealed shared genetic influences and colocalizations between heart and brain diseases and complex traits. As an example, adverse myocardial wall thickness was genetically linked to an increased risk of stroke. The researchers also employed Mendelian randomization to explore causal genetic links and found that adverse heart features may have genetic causal effects on psychiatric disorders and depression.
By deepening understanding of the intricate connections between the heart and brain, this study has significant implications for disease risk prediction and prevention. The multiorgan perspective in this study offers new opportunities to mitigate the negative impact of organ diseases on one another and improve overall human health.
The study’s extensive analysis results, which can be accessed through the heart imaging genetics knowledge portal (Heart-KP), serves as a valuable resource and insight for further research into the genetic basis of heart-brain connections and associated complex traits and disorders.
Published in journal: Science
Additional authors: include Yue Yang, Zirui Fan, Zhengyi Wu, Xifeng Wang, Tianyou Luo, Jiarui Tang, Di Xiong, Jie Chen, Yue Shan, Chalmer Tomlinson and Ziliang Zhu, as well as Professors Yun Li, Jason L. Stein, and Hongtu Zhu.
Source/Credit: University of North Carolina at Chapel Hill
Reference Number: bio061523_02
.jpg)
.jpg)
