Novel DNA Methylation Sites Influence GPR15 Expression in Relation to Smoking

The association of cigarette smoking with DNA methylation and gene expression in human tissue samples

Cigarette smoking adversely affects many aspects of human health, and epigenetic responses to smoking may reflect mechanisms that mediate or defend against these effects. Prior studies of smoking and DNA methylation (DNAm), typically measured in leukocytes, have identified numerous smoking-associated regions (e.g., AHRR). To identify smoking-associated DNAm features in typically inaccessible tissues, we generated array-based DNAm data for 916 tissue samples from the GTEx (Genotype-Tissue Expression) project representing 9 tissue types (lung, colon, ovary, prostate, blood, breast, testis, kidney, and muscle). We identified 6,350 smoking-associated CpGs in lung tissue (n = 212) and 2,735 in colon tissue (n = 210), most not reported previously. For all 7 other tissue types (sample sizes 38-153), no clear associations were observed (false discovery rate 0.05), but some tissues showed enrichment for smoking-associated CpGs reported previously. For 1,646 loci (in lung) and 22 (in colon), smoking was associated with both DNAm and local gene expression. For loci detected in both lung and colon (e.g., AHRR, CYP1B1, CYP1A1), top CpGs often differed between tissues, but similar clusters of hyper- or hypomethylated CpGs were observed, with hypomethylation at regulatory elements corresponding to increased expression. For lung tissue, 17 hallmark gene sets were enriched for smoking-associated CpGs, including xenobiotic- and cancer-related gene sets. At least four smoking-associated regions in lung were impacted by lung methylation quantitative trait loci (QTLs) that co-localize with genome-wide association study (GWAS) signals for lung function (FEV1/FVC), suggesting epigenetic alterations can mediate the effects of smoking on lung health. Our multi-tissue approach has identified smoking-associated regions in disease-relevant tissues, including effects that are shared across tissue types.

From multi-omics approaches to personalized medicine in myocardial infarction

Myocardial infarction (MI) is a prevalent cardiovascular disease characterized by myocardial necrosis resulting from coronary artery ischemia and hypoxia, which can lead to severe complications such as arrhythmia, cardiac rupture, heart failure, and sudden death. Despite being a research hotspot, the etiological mechanism of MI remains unclear. The emergence and widespread use of omics technologies, including genomics, transcriptomics, proteomics, metabolomics, and other omics, have provided new opportunities for exploring the molecular mechanism of MI and identifying a large number of disease biomarkers. However, a single-omics approach has limitations in understanding the complex biological pathways of diseases. The multi-omics approach can reveal the interaction network among molecules at various levels and overcome the limitations of the single-omics approaches. This review focuses on the omics studies of MI, including genomics, epigenomics, transcriptomics, proteomics, metabolomics, and other omics. The exploration extended into the domain of multi-omics integrative analysis, accompanied by a compilation of diverse online resources, databases, and tools conducive to these investigations. Additionally, we discussed the role and prospects of multi-omics approaches in personalized medicine, highlighting the potential for improving diagnosis, treatment, and prognosis of MI.

Emerging roles of a chemoattractant receptor GPR15 and ligands in pathophysiology

Chemokine receptors play a central role in the maintenance of immune homeostasis and development of inflammation by directing leukocyte migration to tissues. GPR15 is a G protein-coupled receptor (GPCR) that was initially known as a co-receptor for human immunodeficiency virus (HIV) and simian immunodeficiency virus (SIV), with structural similarity to other members of the chemoattractant receptor family. Since the discovery of its novel function as a colon-homing receptor of T cells in mice a decade ago, GPR15 has been rapidly gaining attention for its involvement in a variety of inflammatory and immune disorders. The recent identification of its natural ligand C10orf99, a chemokine-like polypeptide strongly expressed in gastrointestinal tissues, has established that GPR15-C10orf99 is a novel signaling axis that controls intestinal homeostasis and inflammation through the migration of immune cells. In addition, it has been demonstrated that C10orf99-independent functions of GPR15 and GPR15-independent activities of C10orf99 also play significant roles in the pathophysiology. Therefore, GPR15 and its ligands are potential therapeutic targets. To provide a basis for the future development of GPR15- or GPR15 ligand-targeted therapeutics, we have summarized the latest advances in the role of GPR15 and its ligands in human diseases as well as the molecular mechanisms that regulate GPR15 expression and functions.

Refining epigenetic prediction of chronological and biological age

BACKGROUND

Epigenetic clocks can track both chronological age (cAge) and biological age (bAge). The latter is typically defined by physiological biomarkers and risk of adverse health outcomes, including all-cause mortality. As cohort sample sizes increase, estimates of cAge and bAge become more precise. Here, we aim to develop accurate epigenetic predictors of cAge and bAge, whilst improving our understanding of their epigenomic architecture.

METHODS

First, we perform large-scale (N = 18,413) epigenome-wide association studies (EWAS) of chronological age and all-cause mortality. Next, to create a cAge predictor, we use methylation data from 24,674 participants from the Generation Scotland study, the Lothian Birth Cohorts (LBC) of 1921 and 1936, and 8 other cohorts with publicly available data. In addition, we train a predictor of time to all-cause mortality as a proxy for bAge using the Generation Scotland cohort (1214 observed deaths). For this purpose, we use epigenetic surrogates (EpiScores) for 109 plasma proteins and the 8 component parts of GrimAge, one of the current best epigenetic predictors of survival. We test this bAge predictor in four external cohorts (LBC1921, LBC1936, the Framingham Heart Study and the Women's Health Initiative study).

RESULTS

Through the inclusion of linear and non-linear age-CpG associations from the EWAS, feature pre-selection in advance of elastic net regression, and a leave-one-cohort-out (LOCO) cross-validation framework, we obtain cAge prediction with a median absolute error equal to 2.3 years. Our bAge predictor was found to slightly outperform GrimAge in terms of the strength of its association to survival (HRGrimAge = 1.47 [1.40, 1.54] with p = 1.08 × 10-52, and HRbAge = 1.52 [1.44, 1.59] with p = 2.20 × 10-60). Finally, we introduce MethylBrowsR, an online tool to visualise epigenome-wide CpG-age associations.

CONCLUSIONS

The integration of multiple large datasets, EpiScores, non-linear DNAm effects, and new approaches to feature selection has facilitated improvements to the blood-based epigenetic prediction of biological and chronological age.

suPAR as a risk Prediction Biomarker in Extracorporeal Membrane Oxygenation

suPAR is a promising biomarker of cardiovascular diseases, as it reflects “low-grade inflammation” and is associated with lifestyle factors such as smoking, alcohol, and an inactive lifestyle. suPAR is expressed in various cells involved in the development of atherosclerosis, including macrophages, endothelial cells, and smooth muscle cells, and an accumulation of suPAR in the atheroma has also been found. suPAR plays a role in the coagulation cascade during plasminogen activation and fibrinolysis. This abstract provides description of three case series showing the utility of suPAR as a risk prediction biomarker on VA extracorporeal membrane oxygenation (ECMO). We used SUPAR in 15 patients undergoing cardiac surgery of which three went on VA ECMO. Herein, we describe in detail three such patients and discuss each with good review of the literature.

G Protein-Coupled Receptor 15 Expression Is Associated with Myocardial Infarction

Beyond the influence of lifestyle-related risk factors for myocardial infarction (MI), the mechanisms of genetic predispositions for MI remain unclear. We sought to identify and characterize differentially expressed genes in early-onset MI in a translational approach. In an observational case−control study, transcriptomes from 112 early-onset MI individuals showed upregulated G protein-coupled receptor 15 (GPR15) expression in peripheral blood mononuclear cells compared to controls (fold change = 1.4, p = 1.87 × 10−7). GPR15 expression correlated with intima-media thickness (β = 0.8498, p = 0.111), C-reactive protein (β = 0.2238, p = 0.0052), ejection fraction (β = −0.9991, p = 0.0281) and smoking (β = 0.7259, p = 2.79 × 10−10). The relation between smoking and MI was diminished after the inclusion of GPR15 expression as mediator in mediation analysis (from 1.27 (p = 1.9 × 10−5) to 0.46 (p = 0.21)). The DNA methylation of two GPR15 sites was 1%/5% lower in early-onset MI individuals versus controls (p = 2.37 × 10−6/p = 0.0123), with site CpG3.98251219 significantly predicting risk for incident MI (hazard ratio = 0.992, p = 0.0177). The nucleotide polymorphism rs2230344 (C/T) within GPR15 was associated with early-onset MI (odds ratio = 3.61, p = 0.044). Experimental validation showed 6.3-fold increased Gpr15 expression in an ischemic mouse model (p < 0.05) and 4-fold increased Gpr15 expression in cardiomyocytes under ischemic stress (p < 0.001). After the induction of MI, Gpr15gfp/gfp mice showed lower survival (p = 0.042) and deregulated gene expression for response to hypoxia and signaling pathways. Using a translational approach, our data provide evidence that GPR15 is linked to cardiovascular diseases, mediating the adverse effects of smoking.

FeCO3, constructing the network biomarkers using the inter-feature correlation coefficients and its application in detecting high-order breast cancer biomarkers

Aims:

This study aims to formulate the inter-feature correlation as the engineered features.

Background:

Modern biotechnologies tend to generate a huge number of characteristics of a sample, while an OMIC dataset usually has a few dozens or hundreds of samples due to the high costs of generating the OMIC data. So many bio-OMIC studies assumed the inter-feature independence and selected a feature with a high phenotype-association.

Objective:

However, many features are closely associated with each other due to their physical or functional interactions, which may be utilized as a new view of features.

Method:

This study proposed a feature engineering algorithm based on the correlation coefficients (FeCO3) by utilizing the correlations between a given sample and a few reference samples. A comprehensive evaluation was carried out for the proposed FeCO3 network features using 24 bio-OMIC datasets.

Result:

The experimental data suggested that the newly calculated FeCO3 network features tended to achieve better classification performances than the original features, using the same popular feature selection and classification algorithms. The FeCO3 network features were also consistently supported by the literature. FeCO3 was utilized to investigate the high-order engineered biomarkers of breast cancer, and detected the PBX2 gene (Pre-B-Cell Leukemia Transcription Factor 2) as one of the candidate breast cancer biomarkers. Although the two methylated residues cg14851325 (Pvalue=8.06e-2) and cg16602460 (Pvalue=1.19e-1) within PBX2 did not have statistically significant association with breast cancers, the high-order inter-feature correlations showed a significant association with breast cancers.

Conclusion:

The proposed FeCO3 network features calculated the high-order inter-feature correlations as novel features, and may facilitate the investigations of complex diseases from this new perspective. The source code is available in FigShare at 10.6084/m9.figshare.13550051 or the web site http://www.healthinformaticslab.org/supp/ .

The Role of GPR15 Function in Blood and Vasculature

Since the first prominent description of the orphan G protein-coupled receptor 15 (GPR15) on lymphocytes as a co-receptor for the human immunodeficiency virus (HIV) type 1 and 2 and the first report about the GPR15-triggered cytoprotective effect on vascular endothelial cells by recombinant human thrombomodulin, several decades passed before the GPR15 has been recently deorphanized. Because of new findings on GPR15, this review will summarize the consequences of GPR15 signaling considering the variety of GPR15-expressing cell types and of GPR15 ligands, with a focus on blood and vasculature.

Tobacco Smoking Increases Methylation of Polypyrimidine Tract Binding Protein 1 Promoter in Intracranial Aneurysms

DNA methylation at the gene promoter region is reportedly involved in the development of intracranial aneurysm (IA). This study aims to investigate the methylation levels of polypyrimidine tract-binding protein 1 (PTBP1) in IA, as well as its potential to predict IA. Forty-eight patients with IA and 48 age- and sex-matched healthy controls were recruited into this study. Methylation levels of CpG sites were determined via bisulfite pyrosequencing. The PTBP1 levels in the blood were determined using a real-time quantitative reverse transcription-polymerase chain reaction test. Significant differences were found between IAs and controls in CpG1 (p = 0.001), CpG2 (p < 0.001), CpG3 (p = 0.037), CpG4 (p = 0.003), CpG5 (p = 0.006), CpG6 (p = 0.02), and mean methylation (p < 0.001). The mRNA level of PTBP1 in the blood was much lower in IAs compared with controls (p = 0.002), and the PTBP1 expression was significantly associated with DNA methylation promoter levels in individuals (r = −0.73, p < 0.0001). In addition, stratification analysis comparing smokers and non-smokers revealed that tobacco smokers had significantly higher levels of DNA methylation in PTBP1 than non-smokers (p = 0.002). However, no statistical difference in PTBP1 methylation was found between ruptured and unruptured IA groups (p > 0.05). The ROC analyses of curves revealed that PTBP1 methylation may be a predictor of IA regardless of sex (both sexes, area under curve (AUC) = 0.78, p < 0.0001; male, AUC = 0.76, p = 0.002; female, AUC = 0.79, p < 0.0001). These findings suggest that long-term tobacco smoke exposure led to DNA methylation in the promoter region of the PTBP1 gene, which further decreased PTBP1 gene expression and participated in the pathogenesis of IA. The methylation of PTBP1 may be a potential predictive marker for the occurrence of IA.

Biomarkers for Heart Failure Prognosis: Proteins, Genetic Scores and Non-coding RNAs

Heart failure (HF) is a complex disease in which cardiomyocyte injury leads to a cascade of inflammatory and fibrosis pathway activation, thereby causing decrease in cardiac function. As a result, several biomolecules are released which can be identified easily in circulating body fluids. The complex biological processes involved in the development and worsening of HF require an early treatment strategy to stop deterioration of cardiac function. Circulating biomarkers provide not only an ideal platform to detect subclinical changes, their clinical application also offers the opportunity to monitor disease treatment. Many of these biomarkers can be quantified with high sensitivity; allowing their clinical application to be evaluated beyond diagnostic purposes as potential tools for HF prognosis. Though the field of biomarkers is dominated by protein molecules, non-coding RNAs (microRNAs, long non-coding RNAs, and circular RNAs) are novel and promising biomarker candidates that encompass several ideal characteristics required in the biomarker field. The application of genetic biomarkers as genetic risk scores in disease prognosis, albeit in its infancy, holds promise to improve disease risk estimation. Despite the multitude of biomarkers that have been available and identified, the majority of novel biomarker candidates are not cardiac-specific, and instead may simply be a readout of systemic inflammation or other pathological processes. Thus, the true value of novel biomarker candidates in HF prognostication remains unclear. In this article, we discuss the current state of application of protein, genetic as well as non-coding RNA biomarkers in HF risk prognosis.

An Integrated Pan-Cancer Analysis and Structure-Based Virtual Screening of GPR15

G protein-coupled receptor 15 (GPR15, also known as BOB) is an extensively studied orphan G protein-coupled receptors (GPCRs) involving human immunodeficiency virus (HIV) infection, colonic inflammation, and smoking-related diseases. Recently, GPR15 was deorphanized and its corresponding natural ligand demonstrated an ability to inhibit cancer cell growth. However, no study reported the potential role of GPR15 in a pan-cancer manner. Using large-scale publicly available data from the Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases, we found that GPR15 expression is significantly lower in colon adenocarcinoma (COAD) and rectal adenocarcinoma (READ) than in normal tissues. Among 33 cancer types, GPR15 expression was significantly positively correlated with the prognoses of COAD, neck squamous carcinoma (HNSC), and lung adenocarcinoma (LUAD) and significantly negatively correlated with stomach adenocarcinoma (STAD). This study also revealed that commonly upregulated gene sets in the high GPR15 expression group (stratified via median) of COAD, HNSC, LUAD, and STAD are enriched in immune systems, indicating that GPR15 might be considered as a potential target for cancer immunotherapy. Furthermore, we modelled the 3D structure of GPR15 and conducted structure-based virtual screening. The top eight hit compounds were screened and then subjected to molecular dynamics (MD) simulation for stability analysis. Our study provides novel insights into the role of GPR15 in a pan-cancer manner and discovered a potential hit compound for GPR15 antagonists.

Diagnostic Value of Soluble Urokinase-Type Plasminogen Activator Receptor in Addition to High-Sensitivity Troponin I in Early Diagnosis of Acute Myocardial Infarction

The soluble urokinase-type plasminogen activator receptor (suPAR) is a new marker for immune activation and inflammation and may provide diagnostic value on top of established biomarkers in patients with suspected acute myocardial infarction (AMI). Here, we evaluate the diagnostic potential of suPAR levels on top of high-sensitivity troponin I (hs-TnI) in a cohort of patients with suspected AMI. A total of 1220 patients presenting to the emergency department with suspected AMI were included, of whom 245 were diagnosed with AMI. Median suPAR levels at admission were elevated in subjects with AMI compared to non-AMI (3.8 ng/mL vs. 3.3 ng/mL, p = 0.001). In C-statistics, the area under the curve (AUC) regarding the diagnosis of AMI was low (0.57 at an optimized cut-off of 3.7 ng/mL). Moreover, baseline suPAR levels on top of troponin values at admission and hour 1 reduced the number of patients who were correctly ruled-out as non-AMI, and who were correctly ruled-in as AMI. Our study shows that circulating levels of suPAR on top of high-sensitivity troponin I do not improve the early diagnosis of AMI.