Identification of a gene network driving the attenuated response to lipopolysaccharide of monocytes from hypertensive coronary artery disease patients

Introduction

The impact of cardiovascular disease (CVD) risk factors, encompassing various biological determinants and unhealthy lifestyles, on the functional dynamics of circulating monocytes-a pivotal cell type in CVD pathophysiology remains elusive. In this study, we aimed to elucidate the influence of CVD risk factors on monocyte transcriptional responses to an infectious stimulus.

Methods

We conducted a comparative analysis of monocyte gene expression profiles from the CTMM - CIRCULATING CELLS Cohort of coronary artery disease (CAD) patients, at baseline and after lipopolysaccharide (LPS) stimulation. Gene co-expression analysis was used to identify gene modules and their correlations with CVD risk factors, while pivotal transcription factors controlling the hub genes in these modules were identified by regulatory network analyses. The identified gene module was subjected to a drug repurposing screen, utilizing the LINCS L1000 database.

Results

Monocyte responsiveness to LPS showed a highly significant, negative correlation with blood pressure levels (ρ< -0.4; P<10-80). We identified a ZNF12/ZBTB43-driven gene module closely linked to diastolic blood pressure, suggesting that monocyte responses to infectious stimuli, such as LPS, are attenuated in CAD patients with elevated diastolic blood pressure. This attenuation appears associated with a dampening of the LPS-induced suppression of oxidative phosphorylation. Finally, we identified the serine-threonine inhibitor MW-STK33-97 as a drug candidate capable of reversing this aberrant LPS response.

Conclusions

Monocyte responses to infectious stimuli may be hampered in CAD patients with high diastolic blood pressure and this attenuated inflammatory response may be reversed by the serine-threonine inhibitor MW-STK33-97. Whether the identified gene module is a mere indicator of, or causal factor in diastolic blood pressure and the associated dampened LPS responses remains to be determined.

Identification of a PRDM1-regulated T cell network to regulate T cell driving plaque inflammation in human and mouse atherosclerosis

 

T cells have a prominent role in the pathogenesis of atherosclerosis, although their exact function remains elusive. Here, we pursued a network-driven approach to identify T cell-associated gene programs driving the transition from low- to high-risk human plaques.

In this study 43 human carotid arterial plaques were collected and stratified based on absence (low-risk) or presence (high-risk) of intraplaque haemorrhage (IPH). Lesion RNA was subjected to microarray gene expression analysis and analysed by Weighted Gene Co-expression Network Analysis (WGCNA). We identified a co-expressed gene cluster displaying a strong T cell signalling signature in high- versus low-risk plaque, which was tightly connected to subnetworks of angiogenesis and interferon-signalling. WGCNA-based Bayesian network inference, cell-type deconvolution and single-cell gene expression revealed that this T cell-associated gene program was likely linked to effector-memory cytotoxic CD8+ T cells, underpinning the central role of T cells in plaque destabilization. Gene regulatory analysis identified cytotoxic T cell-related transcription factors, like PRDM1, regulating this plaque T cell gene program. Moreover, we demonstrated in LDL receptor knockout mice with T cell-specific Prdm1 deficiency, that lack of Prdm1 in T cells resulted in larger, more advanced plaques.

In conclusion, our study reveals a PRDM1-regulated T cell footprint in high- versus low-risk human atherosclerotic lesions and murine atherosclerotic plaque development, thereby identifying this network as a potential target for intervention in adverse T cell responses.

Funding Acknowledgement

Type of funding sources: Public grant(s) – EU funding. Main funding source(s): The European Research Area Network on Cardiovascular Diseases (ERA-CVD and Dutch Heart Foundation)

Identification of CD8+ T cell PRDM1 in high-risk human plaques and its regulatory role in murine lesion development

Funding Acknowledgements

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Fritz Thyssen Stiftung

T cells have a prominent role in the pathogenesis of atherosclerosis, although their function in atherosclerotic plaques is only partly understood. In this study, we utilize the advantages of high-throughput techniques and data analytic strategies to compare the inherent biological changes of T cells during plaque transition from a stable, non-haemorrhaged (low-risk) to a rupture-prone, haemorrhaged (high-risk) phenotype.

We classified 43 human carotid arterial lesions into high- and low-risk plaques based on the presence/absence of intraplaque hemorrhages. RNA from these lesions was isolated and microarray gene expression data was obtained and analyzed by Weighted Gene Co-expression Network Analysis. A strong T cell signalling signature was identified in high- versus low-risk plaques, influencing angiogenesis and interferon-related processes. Bayesian network inference, cell type deconvolution and single-cell RNA sequencing analysis revealed that the T cell-associated gene program was linked to effector-memory cytotoxic, CD8+ T cells. This gene program appeared driven by CD8+ T cell-related transcription factors, including RUNX3, IRF7 and most importantly PRDM1. To validate these findings, we demonstrated in a murine model that T cell PRDM1 plays a key role in plaque formation, as atherosclerotic mice with a T cell specific Prdm1 deficiency developed larger and more advanced atherosclerotic plaques compared to control mice.

In conclusion, our study unveils a clear PRDM1-regulated effector-memory cytotoxic CD8+ T cell footprint in plaque development and the shift from low- to high-risk plaques, thereby revealing CD8+ T cells and PRMD1 as potential targets for intervention in adverse T cell responses in human atherosclerotic lesions.

Integrative multiomics analysis of human atherosclerosis reveals a serum response factor-driven network associated with intraplaque hemorrhage

BACKGROUND

While single-omics analyses on human atherosclerotic plaque have been very useful to map stage- or disease-related differences in expression, they only partly capture the array of changes in this tissue and suffer from scale-intrinsic limitations. In order to better identify processes associated with intraplaque hemorrhage and plaque instability, we therefore combined multiple omics into an integrated model.

METHODS

In this study, we compared protein and gene makeup of low- versus high-risk atherosclerotic lesion segments from carotid endarterectomy patients, as judged from the absence or presence of intraplaque hemorrhage, respectively. Transcriptomic, proteomic, and peptidomic data of this plaque cohort were aggregated and analyzed by DIABLO, an integrative multivariate classification and feature selection method.

RESULTS

We identified a protein-gene associated multiomics model able to segregate stable, nonhemorrhaged from vulnerable, hemorrhaged lesions at high predictive performance (AUC >0.95). The dominant component of this model correlated with αSMA- PDGFRα+ fibroblast-like cell content (p = 2.4E-05) and Arg1+ macrophage content (p = 2.2E-04) and was driven by serum response factor (SRF), possibly in a megakaryoblastic leukemia-1/2 (MKL1/2) dependent manner. Gene set overrepresentation analysis on the selected key features of this model pointed to a clear cardiovascular disease signature, with overrepresentation of extracellular matrix synthesis and organization, focal adhesion, and cholesterol metabolism terms, suggestive of the model's relevance for the plaque vulnerability. Finally, we were able to corroborate the predictive power of the selected features in several independent mRNA and proteomic plaque cohorts.

CONCLUSIONS

In conclusion, our integrative omics study has identified an intraplaque hemorrhage-associated cardiovascular signature that provides excellent stratification of low- from high-risk carotid artery plaques in several independent cohorts. Further study revealed suppression of an SRF-regulated disease network, controlling lesion stability, in vulnerable plaque, which can serve as a scaffold for the design of targeted intervention in plaque destabilization.

Wavelet-sparsity based regularization over time in the inverse problem of electrocardiography

Noninvasive, detailed assessment of electrical cardiac activity at the level of the heart surface has the potential to revolutionize diagnostics and therapy of cardiac pathologies. Due to the requirement of noninvasiveness, body-surface potentials are measured and have to be projected back to the heart surface, yielding an ill-posed inverse problem. Ill-posedness ensures that there are non-unique solutions to this problem, resulting in a problem of choice. In the current paper, it is proposed to restrict this choice by requiring that the time series of reconstructed heart-surface potentials is sparse in the wavelet domain. A local search technique is introduced that pursues a sparse solution, using an orthogonal wavelet transform. Epicardial potentials reconstructed from this method are compared to those from existing methods, and validated with actual intracardiac recordings. The new technique improves the reconstructions in terms of smoothness and recovers physiologically meaningful details. Additionally, reconstruction of activation timing seems to be improved when pursuing sparsity of the reconstructed signals in the wavelet domain.

Towards unobtrusive in vivo monitoring of patients prone to falling

Falling is a serious health problem for many elderly. To investigate whether the higher fall incidence in elderly is due to a higher probability of experiencing near falls in daily life, it is necessary to evaluate the stumble incidence of elderly in daily life. Accelerometers are already frequently used for in vivo activity monitoring. The current study investigates whether an ambulant and unobtrusive accelerometer can identify stumbles from treadmill walking using a wavelet based detection approach. Seventy nine healthy subjects walked on a treadmill with a triaxial accelerometer attached at the level of the sacrum. Stumbles were induced using a specially designed braking system (The TRiP). The TRiP evoked 30 stumbles at different phases of the swing phase. A wavelet-based detection algorithm is used to isolate the stumbles from treadmill walking, with a specificity of 99.9% and a sensitivity of 98.4%.

Measures for the evaluation of bias field removal procedures in MRI and the design of wavelets for suppression of RF inhomogeneities

RF inhomogeneities are illumination artifacts in MR images which manifest as a multiplicative bias field. To measure the quality of an MR image with respect to RF inhomogeneities, existing multi-valued criteria are in use. Here we propose a useful conversion of these multi-valued criteria into a single measure of quality which simplifies image quality evaluation and comparison. Next, to remove such a bias field, a novel wavelet based approach is employed, that extends a previous 1D wavelet design methodology to a 2D setting. This method is found to perform well on images with strong small details. The results for brain MR images are subject to improvement, however our results hint to a future scenario for improved image quality.

Multiwavelet design for cardiac signal processing

An approach for designing multiwavelets is introduced, for use in cardiac signal processing. The parameterization of the class of multiwavelets is in terms of associated FIR polyphase all-pass filters. Orthogonality and a balanced vanishing moment of order 1 are built into the parameterization. An optimization criterion is developed to associate the wavelets with different meaningful segments of a signal. This approach is demonstrated on the simultaneous detection of QRS-complexes and T-peaks in ECG signals.