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Genetic and Multiorgan Imaging Approach Reveals Heart–Brain Connections

by Zahraa Chorghay, PhD | Jun 30, 2023 | Clinical Diagnostics Insider, Diagnostic Testing and Emerging Technologies, Special Focus-dtet

Multiorgan analysis of biobank data elucidates heart–brain links that could enhance disease prevention and detection.

“The heart wants what it wants” and other such adages suggest that your heart and brain are disconnected from each other. But when it comes to physiology, a growing body of research links heart and brain health, and their underlying genetics. Mess with one and you mess with the other. For example, cardiovascular diseases have been implicated in brain diseases,¹ particularly in the aging brain, including in stroke, dementia, cerebral small vessel disease, and cognitive impairment.² Vice versa, people with schizophrenia, bipolar disorder, epilepsy, or depression can present with cardiovascular comorbidities.³ While small sample sizes and a focus on specific diseases has limited our current understanding of these heart–brain links and their genetic basis, a Human Genetics study published in June sheds light on these observations.⁴

Approaches for Studying Heart and Brain Traits

Magnetic resonance imaging (MRI) is one approach for evaluating cardiac and brain structure and function. In the clinic, cardiovascular MRI (CMR) is used to assess cardiovascular disease risk or status, while brain MRI is used to assess neurological disease or neuropsychiatric disorders. Some cardiovascular and brain MRI traits show moderate to high heritability in twin and family studies.

What Is a Genome-Wide Association Study (GWAS)?

According to the National Human Genome Research Institute, a GWAS “is a research approach used to identify genomic variants that are statistically associated with a risk for a disease or a particular trait.” In a GWAS, you survey the genomes of many people for genomic variants—genetic markers or single nucleotide polymorphisms (SNPs)—that occur more frequently in those with a specific disease or trait compared to those without it.⁵

GWASs have been conducted on CMR and brain MRI traits, including several large-scale efforts by the neuroscience community. However, the Human Genetics study addresses a notable gap in current research—the lack of “multiorgan MRI to examine heart–brain connections and identify the shared genetic signatures of the heart and the brain.”

Multiorgan Approach for Studying Heart–Brain Connections

In the Human Genetics study, the research team investigated heart–brain connections using multiorgan imaging data from the UK Biobank (UKB) study. From more than 40,000 study participants, the researchers identified relationships between 82 CMR traits and the following brain MRI traits:⁴

164 structural MRI traits, related to brain volume and cortical thickness

110 brain diffusion tensor MRI (DTI) traits, related to structural connectivity

92 global and more than 60,000 regional resting functional MRI (fMRI) traits, related to brain activity and connectivity at rest and during a task

The researchers conducted a GWAS on the 82 CMR traits to identify the genetic variation underlying heart and aorta architecture and their shared genetic components with brain MRI traits.

CMR and Brain MRI Traits Are Correlated

The CMR traits were associated with a wide variety of brain MRI traits, including regional brain volumes, cortical thickness, structural connectivity, and resting and task fMRI traits; more than 1,500 of these correlations showed significance in an independent validation dataset of 5,316 individuals. For example, smaller aortic areas were associated with measures indicating higher white matter integrity.

CMR Traits Show Moderate Heritability

The GWAS for more than 30,000 participants of White British ancestry from the UKB revealed a 22.9 percent SNP heritability for the 82 CMR traits, with specific traits having a higher heritability. There was more than 50 percent heritability for the ratio of the ascending to descending aorta areas, and more than 37 percent heritability for cardiac traits, including global wall thickness, end-systolic and end-diastolic volumes for the left and right ventricles, and left ventricular mass (LVM).

Genetic Associations of CMR and Brain MRI Traits

Within this White British cohort, there were significant associations in 80 genomic regions for 49 CMR traits, which also shared heritability with brain MRI traits, particularly white matter microstructure (structural connectivity). To replicate the identified loci, the team performed separate GWAS analyses using holdout datasets in the UKB study, as well as constructed polygenic risk scores to assess the genetic association patterns.

The researchers found significant associations for variants linked to the following variables:

Heart diseases, heart structure and function, and blood pressure

Lipid and blood traits

Diabetes

Stroke

Neurological and neuropsychiatric disorders

Psychological and cognitive traits

Lung function

Parental longevity

Smoking and drinking

Further Analysis of Genetic Associations Revealed Causal Links and Drug Targets

Given these genetic correlations between the heart and brain, the researchers wanted to uncover causal genetic links for the 82 CMR traits using Mendelian randomization. These links were typically from the heart to the brain, such as heart wall thickness leading to depression or even neurotic personality traits, although they also found causal genetic links of brain disorders affecting CMR traits.

Further analysis revealed which genes contributed to the CMR traits (163 significant genes contributed to 48 CMR traits), how variants mapped to genes, and where (cell and tissue types) these interactions played out. The genes turned out to be targets for the following drugs:

Cardiovascular system drugs that lower blood pressure or treat heart failure or heart rhythm disorders

Nervous system drugs to manage epilepsy and addictive disorders

Both heart and brain drugs, e.g., the ALDH2 gene, which is important for clearing toxic aldehydes—a mechanism related to heart and brain stroke

The Sum Is More Than Its Parts

Instead of relying on one source of information, integrating genetic and multiorgan imaging information provides a more detailed insight into multisystem diseases. With enough biobank-scale data, we can begin to understand the interorgan mechanisms of various multisystem diseases like diabetes, as well as prevent, detect, or track the prognosis of conditions in the brain and other organs.