Gene networks and pathways for plasma lipid traits via multitissue multiomics systems analysis

The thrombin receptor PAR4 supports visceral adipose tissue inflammation

Thrombin inhibition suppresses adiposity, WAT inflammation and metabolic dysfunction in mice. Protease-activated receptor (PAR)1 does not account for thrombin-driven obesity, so we explored the culprit role of PAR4 in this context. Male WT and PAR-4-/- mice received a high fat diet (HFD) for 8 weeks, WT controls received standard chow. Body fat was quantified by NMR. Epididymal WAT was assessed by histology, immunohistochemistry, qPCR and lipase activity assay. 3T3-L1 preadipocytes were differentiated ± thrombin, acutely stimulated ± PAR4 activating peptide (AP) and assessed by immunoblot, qPCR and U937 monocyte adhesion. Epicardial adipose tissue (EAT) from obese and lean patients was assessed by immunoblot. PAR4 was upregulated in mouse WAT under HFD. PAR4-/- mice developed less visceral adiposity and glucose intolerance under HFD, featuring smaller adipocytes, fewer macrophages and lower expression of adipogenic (leptin, PPARγ) and pro-inflammatory genes (CCL2, IL-1β) in WAT. HFD-modified activity and expression of lipases or perilipin were unaffected by PAR4 deletion. 3T3-L1 adipocytes differentiated with thrombin retained Ki67 expression, further upregulated IL-1β and CCL2 and were more adhesive for monocytes. In mature adipocytes, PAR4-AP increased phosphorylated ERK1/2 and AKT, upregulated Ki67, CCl2, IL-β and hyaluronan synthase 1 but not TNF-α mRNA, and augmented hyaluronidase-sensitive monocyte adhesion. Obese human EAT expressed more PAR4, CD68 and CD54 than lean EAT. PAR4 upregulated in obesity supports adipocyte hypertrophy, WAT expansion and thrombo-inflammation. The emerging PAR4 antagonists provide a therapeutic perspective in this context beyond their canonical antiplatelet action.

Shared and distinct pathways and networks genetically linked to coronary artery disease between human and mouse

Mouse models have been used extensively to study human coronary artery disease (CAD) or atherosclerosis and to test therapeutic targets. However, whether mouse and human share similar genetic factors and pathogenic mechanisms of atherosclerosis has not been thoroughly investigated in a data-driven manner. We conducted a cross-species comparison study to better understand atherosclerosis pathogenesis between species by leveraging multiomics data. Specifically, we compared genetically driven and thus CAD-causal gene networks and pathways, by using human GWAS of CAD from the CARDIoGRAMplusC4D consortium and mouse GWAS of atherosclerosis from the Hybrid Mouse Diversity Panel (HMDP) followed by integration with functional multiomics human (STARNET and GTEx) and mouse (HMDP) databases. We found that mouse and human shared >75% of CAD causal pathways. Based on network topology, we then predicted key regulatory genes for both the shared pathways and species-specific pathways, which were further validated through the use of single cell data and the latest CAD GWAS. In sum, our results should serve as a much-needed guidance for which human CAD-causal pathways can or cannot be further evaluated for novel CAD therapies using mouse models.

Shared and distinct pathways and networks genetically linked to coronary artery disease between human and mouse

Mouse models have been used extensively to study human coronary artery disease (CAD) or atherosclerosis and to test therapeutic targets. However, whether mouse and human share similar genetic factors and pathogenic mechanisms of atherosclerosis has not been thoroughly investigated in a data-driven manner. We conducted a cross-species comparison study to better understand atherosclerosis pathogenesis between species by leveraging multiomics data. Specifically, we compared genetically driven and thus CAD-causal gene networks and pathways, by using human GWAS of CAD from the CARDIoGRAMplusC4D consortium and mouse GWAS of atherosclerosis from the Hybrid Mouse Diversity Panel (HMDP) followed by integration with functional multiomics human (STARNET and GTEx) and mouse (HMDP) databases. We found that mouse and human shared >75% of CAD causal pathways. Based on network topology, we then predicted key regulatory genes for both the shared pathways and species-specific pathways, which were further validated through the use of single cell data and the latest CAD GWAS. In sum, our results should serve as a much-needed guidance for which human CAD-causal pathways can or cannot be further evaluated for novel CAD therapies using mouse models.

Single-cell RNA sequencing reveals a novel inhibitory effect of ApoA4 on NAFL mediated by liver-specific subsets of myeloid cells

The liver immune microenvironment is a key element in the development of hepatic inflammation in NAFLD. ApoA4 deficiency increases the hepatic lipid burden, insulin resistance, and metabolic inflammation. However, the effect of ApoA4 on liver immune cells and the precise immune cell subsets that exacerbate fatty liver remain elusive. The aim of this study was to profile the hepatic immune cells affected by ApoA4 in NAFL. We performed scRNA-seq on liver immune cells from WT and ApoA4-deficient mice administered a high-fat diet. Immunostaining and qRT-PCR analysis were used to validate the results of scRNA-seq. We identified 10 discrete immune cell populations comprising macrophages, DCs, granulocytes, B, T and NK&NKT cells and characterized their subsets, gene expression profiles, and functional modules. ApoA4 deficiency led to significant increases in the abundance of specific subsets, including inflammatory macrophages (2-Mφ-Cxcl9 and 4-Mφ-Cxcl2) and activated granulocytes (0-Gran-Wfdc17). Moreover, ApoA4 deficiency resulted in higher Lgals3, Ctss, Fcgr2b, Spp1, Cxcl2, and Elane levels and lower Nr4a1 levels in hepatic immune cells. These genes were consistent with human NAFLD-associated marker genes linked to disease severity. The expression of NE and IL-1β in granulocytes and macrophages as key ApoA4 targets were validate in the presence or absence of ApoA4 by immunostaining. The scRNA-seq data analyses revealed reprogramming of liver immune cells resulted from ApoA4 deficiency. We uncovered that the emergence of ApoA4-associated immune subsets (namely Cxcl9+ macrophage, Cxcl2+ macrophage and Wfdc17+ granulocyte), pathways, and NAFLD-related marker genes may promote the development of NAFL. These findings may provide novel therapeutic targets for NAFL and the foundations for further studying the effects of ApoA4 on immune cells in various diseases.

Thromboinflammatory Processes at the Nexus of Metabolic Dysfunction and Prostate Cancer: The Emerging Role of Periprostatic Adipose Tissue

Simple Summary

As overweight and obesity increase among the population worldwide, a parallel increase in the number of individuals diagnosed with prostate cancer was observed. There appears to be a relationship between both diseases where the increase in the mass of fat tissue can lead to inflammation. Such a state of inflammation could produce many factors that increase the aggressiveness of prostate cancer, especially if this inflammation occurred in the fat stores adjacent to the prostate. Another important observation that links obesity, fat tissue inflammation, and prostate cancer is the increased production of blood clotting factors. In this article, we attempt to explain the role of these latter factors in the effect of increased body weight on the progression of prostate cancer and propose new ways of treatment that act by affecting how these clotting factors work.

Abstract

The increased global prevalence of metabolic disorders including obesity, insulin resistance, metabolic syndrome and diabetes is mirrored by an increased incidence of prostate cancer (PCa). Ample evidence suggests that these metabolic disorders, being characterized by adipose tissue (AT) expansion and inflammation, not only present as risk factors for the development of PCa, but also drive its increased aggressiveness, enhanced progression, and metastasis. Despite the emerging molecular mechanisms linking AT dysfunction to the various hallmarks of PCa, thromboinflammatory processes implicated in the crosstalk between these diseases have not been thoroughly investigated. This is of particular importance as both diseases present states of hypercoagulability. Accumulating evidence implicates tissue factor, thrombin, and active factor X as well as other players of the coagulation cascade in the pathophysiological processes driving cancer development and progression. In this regard, it becomes pivotal to elucidate the thromboinflammatory processes occurring in the periprostatic adipose tissue (PPAT), a fundamental microenvironmental niche of the prostate. Here, we highlight key findings linking thromboinflammation and the pleiotropic effects of coagulation factors and their inhibitors in metabolic diseases, PCa, and their crosstalk. We also propose several novel therapeutic targets and therapeutic interventions possibly modulating the interaction between these pathological states.

Genosets for APOE and CYP7A1-rs3808607 variants do not predict LDL cholesterol lowering upon intervention with plant sterols in a randomized, double-blind, placebo-controlled trial

BACKGROUND

The consumption of 2 g/d plant sterols (PSs) reduces circulating LDL cholesterol by ≤10%. The degree of LDL cholesterol lowering was associated with specific apolipoprotein E [APOE, Reference SNP (rs)429358] and cholesterol 7α-hydroxylase (CYP7A1, rs3808607) genosets in previous post hoc analyses of randomized controlled trials. However, because post hoc analyses do not conform to the randomization model, there is a greater potential that the findings could be due to type I error, thus warranting validation through an a priori-designed intervention trial.

OBJECTIVES

The GenePredict Plant Sterol study (GPS) was designed to validate associations of LDL cholesterol lowering with specific APOE and CYP7A1 genosets through a priori recruitment of individuals carrying prespecified genosets.

METHODS

A 2-center, double-blind, placebo-controlled, randomized 2-period crossover dietary intervention with 2 g/d PS for 28 d with a minimum 28-d washout was undertaken from July 2017 to December 2019. A priori recruitment of individuals with slightly elevated LDL cholesterol was based on genosets of APOE isoforms and CYP7A1 rs3808607. Randomization was performed with stratification by sex and genoset.

RESULTS

The recruitment target of 64 participants with prespecified genosets could not be reached, despite the screening of 477 individuals; 42 participants completed the intervention trial. Reductions in LDL cholesterol were similar across all 3 genosets (-0.298 ± 0.164, -0.357 ± 0.115, -0.293 ± 0.109 mmol/L; P = 0.0002 overall; P = 0.9126 for treatment × genoset), providing evidence that the shortfall in recruitment might not have stopped the trial from meeting the objective.

CONCLUSIONS

APOE and CYP7A1 genotypes did not influence the efficacy of LDL cholesterol reductions upon dietary intervention with PSs. Findings of previous post hoc analyses could not be validated in a trial using a priori genotype-based recruitment. Obtaining adequate numbers of participants is challenging in trials using genoset-based recruitment, even for common variants.

Molecular Biology Networks and Key Gene Regulators for Inflammatory Biomarkers Shared by Breast Cancer Development: Multi-Omics Systems Analysis

As key inflammatory biomarkers C-reactive protein (CRP) and interleukin-6 (IL6) play an important role in the pathogenesis of non-inflammatory diseases, including specific cancers, such as breast cancer (BC). Previous genome-wide association studies (GWASs) have neither explained the large proportion of genetic heritability nor provided comprehensive understanding of the underlying regulatory mechanisms. We adopted an integrative genomic network approach by incorporating our previous GWAS data for CRP and IL6 with multi-omics datasets, such as whole-blood expression quantitative loci, molecular biologic pathways, and gene regulatory networks to capture the full range of genetic functionalities associated with CRP/IL6 and tissue-specific key drivers (KDs) in gene subnetworks. We applied another systematic genomics approach for BC development to detect shared gene sets in enriched subnetworks across BC and CRP/IL6. We detected the topmost significant common pathways across CRP/IL6 (e.g., immune regulatory; chemokines and their receptors; interferon γ, JAK-STAT, and ERBB4 signaling), several of which overlapped with BC pathways. Further, in gene–gene interaction networks enriched by those topmost pathways, we identified KDs—both well-established (e.g., JAK1/2/3, STAT3) and novel (e.g., CXCR3, CD3D, CD3G, STAT6)—in a tissue-specific manner, for mechanisms shared in regulating CRP/IL6 and BC risk. Our study may provide robust, comprehensive insights into the mechanisms of CRP/IL6 regulation and highlight potential novel genetic targets as preventive and therapeutic strategies for associated disorders, such as BC.

Mergeomics 2.0: a web server for multi-omics data integration to elucidate disease networks and predict therapeutics

The Mergeomics web server is a flexible online tool for multi-omics data integration to derive biological pathways, networks, and key drivers important to disease pathogenesis and is based on the open source Mergeomics R package. The web server takes summary statistics of multi-omics disease association studies (GWAS, EWAS, TWAS, PWAS, etc.) as input and features four functions: Marker Dependency Filtering (MDF) to correct for known dependency between omics markers, Marker Set Enrichment Analysis (MSEA) to detect disease relevant biological processes, Meta-MSEA to examine the consistency of biological processes informed by various omics datasets, and Key Driver Analysis (KDA) to identify essential regulators of disease-associated pathways and networks. The web server has been extensively updated and streamlined in version 2.0 including an overhauled user interface, improved tutorials and results interpretation for each analytical step, inclusion of numerous disease GWAS, functional genomics datasets, and molecular networks to allow for comprehensive omics integrations, increased functionality to decrease user workload, and increased flexibility to cater to user-specific needs. Finally, we have incorporated our newly developed drug repositioning pipeline PharmOmics for prediction of potential drugs targeting disease processes that were identified by Mergeomics. Mergeomics is freely accessible at http://mergeomics.research.idre.ucla.edu and does not require login.