Heart-brain connections: Phenotypic and genetic insights from magnetic resonance images

Zhao, Bingxin; Li, Tengfei; Fan, Zirui; Yang, Yue; Shu, Juan; Yang, Xiaochen; Wang, Xifeng; Luo, Tianyou; Tang, Junnan; Xiong, Dandan; Wu, Zhenyi; Li, Bingxuan; Chen, Jiawen; Shan, Yue; Tomlinson, Chal E.; Zhu, Ziliang; Li, Yun; Stein, Jason L.; Zhu, Hongtu

doi:10.1126/science.abn6598

Cited by 82 publications

(40 citation statements)

References 153 publications

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“…This cell-type enrichment signature was not found for MDD or CVD alone, suggesting that a distinct biological mechanism involving thalamic circuits underlies the shared liability to MDD-CVD. Altered thalamic function has indeed been implicated previously in CVD 32–34 and MDD 35,36 , and white matter integrity in thalamic radiations show associations with aortic area and myocardial wall thickness, suggesting that it has a role in the ‘heart-brain’ connection 37 .…”

Section: Discussionmentioning

confidence: 73%

Distinct genomic signatures and modifiable risk factors underly the comorbidity between major depressive disorder and cardiovascular disease

Bergstedt,

Pasman,

et al. 2023

Preprint

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Major depressive disorder (MDD) and cardiovascular disease (CVD) are often comorbid, resulting in excess morbidity and mortality. Using genetic data, this study elucidates biological mechanisms, key risk factors, and causal pathways underlying the comorbidity. We show that CVDs share a large proportion of their genetic risk factors with MDD. Multivariate genome-wide association analysis of the shared genetic liability between MDD and CVD revealed seven novel loci and distinct patterns of tissue and brain cell-type enrichments, suggesting a role for the thalamus. Part of the genetic overlap was explained by shared inflammatory, metabolic, and psychosocial risk factors. Finally, we found support for causal effects of genetic liability to MDD on CVD risk, but not vice versa, and demonstrated that the causal effects are partly explained by metabolic and psychosocial factors. The distinct signature of MDD-CVD comorbidity aligns with the idea of an immunometabolic sub-type of MDD more strongly associated with CVD than overall MDD. In summary, we identify plausible biological mechanisms underlying MDD-CVD comorbidity, as well as key modifiable risk factors for prevention of CVD in individuals with MDD.

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Section: Discussionmentioning

confidence: 73%

Distinct genomic signatures and modifiable risk factors underly the comorbidity between major depressive disorder and cardiovascular disease

Bergstedt,

Pasman,

et al. 2023

Preprint

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“…Despite the increasing number of association studies investigating the brain-heart interaction 40,73 , causal genetic links within these systems remain largely uncharted. In this study, we identified causal connections from hypertension to DTI parameters in multiple white matter tracts, including the SCR, BCC, and GCC.…”

Section: Brain-heart Causal Connectionsmentioning

confidence: 99%

“…There are also some other traits, such as regional phenotypes of the left ventricle myocardial-wall thickness and strain (Table S1). The summary-level GWAS data of these 82 CMR traits were obtained from Zhao, et al 40 .…”

mentioning

confidence: 99%

Inferring Multi-Organ Genetic Causal Connections using Imaging and Clinical Data through Mendelian Randomization

Shu

Zheng

Copana

et al. 2023

Preprint

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Functional and morphological architectures of major human organs have been well characterized using imaging biomarkers. Nevertheless, deciphering the causal relationships between imaging biomarkers and major clinical outcomes, as well as understanding the causal interplay across multiple organs, remains a formidable challenge. Mendelian randomization (MR) presents a framework for inferring causality by using genetic variants as instrumental variables. Here we report a systematic multi-organ MR analysis between 402 imaging biomarkers and 88 clinical outcomes. We identified 488 genetic causal links for 62 diseases and 130 imaging biomarkers from 9 organs, tissue, or systems, including the brain, heart, liver, kidney, lung, pancreas, spleen, adipose tissue, and skeleton system. We prioritized crucial intra-organ causal connections, such as the bidirectional genetic links between Alzheimer's disease and brain function, as well as inter-organ causal effects, such as the adverse impact of heart diseases on brain health. Our findings uncover the genetic causal links spanning multiple organs, offering a more profound understanding of the intricate relationships between organ imaging biomarkers and clinical outcomes.

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“…Mounting evidence has suggested that the genetic effects on the anatomical phenotypes of the human brain are spatially heterogeneous [1][2][3][4][5] , demonstrating the vital roles of genes in establishing the configuration of brain space, such as the anatomical hierarchy 6 and the wiring diagram [7][8][9] .…”

Section: Introductionmentioning

confidence: 99%

“…Mounting evidence has suggested that the genetic effects on the anatomical phenotypes of the human brain are spatially heterogeneous ( 1–5 ), demonstrating the vital roles of genes in establishing the configuration of brain space, such as the anatomical hierarchy ( 6 ) and the wiring diagram ( 7–9 ). Especially the profile of cortical wiring that can be characterized by using neuroimaging-based tractography is a reliable source to indicate the heterogeneity across cortical areas ( 10, 11 ), reflecting the differentiation in local microstructures and connectivity patterns.…”

Section: Introductionmentioning

confidence: 99%

Topographic Axes of Wiring Space Converge to Genetic Topography in Shaping Human Cortical Layout

Li,

Wang,

et al. 2023

Preprint

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Genetic factors have involved the gradual emergence of cortical areas since the neural tube begins to form, shaping the specialization of neural circuits in the human brain. Informed by invasive tract-tracing measurements, the cortex exhibits marked interareal variation in connectivity profiles, yet how this spatial variation is encoded in genetics remains unclear. Instead of considering a complex one-to-one mapping between genetic coding and interareal connectivity variation, we hypothesized the existence of a more efficient way that the organizing principles are embedded in genetic profiles to underpin the configuration of connectivity across the human cortex. Specifically, we found that a noninvasive neuroimaging measure, i.e., global connectopy derived from diffusion-weighted MRI tractography, reliably indexes the organizing principles of interareal connectivity variation, and it captures three dominant topographic patterns along the dorsoventral, rostrocaudal, and mediolateral axes of the cortex. We further found that the global connectopies converge to the gradients of vertex-by-vertex genetic correlation matrix on the phenotype of cortical morphology and the cortex-wide spatiomolecular gradients. Moreover, we found the critical role of genes related to brain morphogenesis in scaffolding the global connectopies. Our findings identify a common space linking genetic profilings and interareal connectivity variation, which may contribute to the accurate formation of cortical connections and arealization.

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Heart-brain connections: Phenotypic and genetic insights from magnetic resonance images

Cited by 82 publications

References 153 publications

Distinct genomic signatures and modifiable risk factors underly the comorbidity between major depressive disorder and cardiovascular disease

Distinct genomic signatures and modifiable risk factors underly the comorbidity between major depressive disorder and cardiovascular disease

Inferring Multi-Organ Genetic Causal Connections using Imaging and Clinical Data through Mendelian Randomization

Topographic Axes of Wiring Space Converge to Genetic Topography in Shaping Human Cortical Layout

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