Genetic variants in PPARGC1B and CNTN4 are associated with thromboxane A2 formation and with cardiovascular event free survival in the Anglo-Scandinavian Cardiac Outcomes Trial (ASCOT)

Epigenetic Contributions to Clinical Risk Prediction of Cardiovascular Disease

BACKGROUND

Cardiovascular disease (CVD) is among the leading causes of death worldwide. The discovery of new omics biomarkers could help to improve risk stratification algorithms and expand our understanding of molecular pathways contributing to the disease. Here, ASSIGN-a cardiovascular risk prediction tool recommended for use in Scotland-was examined in tandem with epigenetic and proteomic features in risk prediction models in ≥12 657 participants from the Generation Scotland cohort.

METHODS

Previously generated DNA methylation-derived epigenetic scores (EpiScores) for 109 protein levels were considered, in addition to both measured levels and an EpiScore for cTnI (cardiac troponin I). The associations between individual protein EpiScores and the CVD risk were examined using Cox regression (ncases≥1274; ncontrols≥11 383) and visualized in a tailored R application. Splitting the cohort into independent training (n=6880) and test (n=3659) subsets, a composite CVD EpiScore was then developed.

RESULTS

Sixty-five protein EpiScores were associated with incident CVD independently of ASSIGN and the measured concentration of cTnI (P<0.05), over a follow-up of up to 16 years of electronic health record linkage. The most significant EpiScores were for proteins involved in metabolic, immune response, and tissue development/regeneration pathways. A composite CVD EpiScore (based on 45 protein EpiScores) was a significant predictor of CVD risk independent of ASSIGN and the concentration of cTnI (hazard ratio, 1.32; P=3.7×10-3; 0.3% increase in C-statistic).

CONCLUSIONS

EpiScores for circulating protein levels are associated with CVD risk independent of traditional risk factors and may increase our understanding of the etiology of the disease.

MiR-148a-3p attenuates apoptosis and inflammation by targeting CNTN4 in atherosclerosis

Background

Atherosclerosis (AS) seriously affects human health. The role of microRNAs (miRNAs) in the pathogenesis and progression of AS has become a focus of research. Our goal was to identify the biological effect of differentially expressed miRNAs (DE-miRNAs) in AS.

Methods

To analyze differentially expressed genes (DEGs), including differentially expressed mRNAs (DE-mRNAs) and DE-miRNAs, in AS by using the Gene Expression Omnibus (GEO) database and limma package. DEGs protein-protein interaction (PPI) network and functional enrichment analysis were constructed by using the search tool for the retrieval of interacting genes/proteins (STRING) database, Cytoscape software and Cytoscape plugin "ClueGO2.5.6". We established a coexpression network of dysregulated miRNAs and mRNAs to predict the function of miRNAs by using miRWalk database and Pearson correlation coefficient (PCC) analysis. Cellular experiments were used to validate the results of bioinformatics.

Results

First, 69 common DEGs were obtained from datasets GSE43292 and GSE97210 using the limma package in R. Next, a DEG PPI network was constructed. Functional enrichment analysis of DEGs showed that 11 functional pathways were significantly enriched, such as positive regulation of monocyte chemotaxis. Seven common DE-miRNAs were obtained from the GSE99685 dataset and DE-mRNAs predicted miRNAs through the miRWalk database. The miRNA-mRNA network constructed using Cytoscape software suggested that miR-148a-3p targeted contactin 4 (CNTN4). Quantitative real-time polymerase chain reaction (qRT-PCR) assay results indicated that miR-148a-3p was downregulated and CNTN4 was upregulated in the THP-1 + phorbol 12-myristate 13-acetate (PMA) + oxidized low-density lipoprotein (oxLDL) group compared with the THP-1 + PMA group. qRT-PCR, flow cytometry, and enzyme-linked immunosorbent assay (ELISA) found that upregulated miR-148a-3p significantly inhibited the expression of CNTN4, cell apoptosis, and interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α) concentrations in oxLDL-induced THP-1 macrophages. In addition, a dual-luciferase reporter assay demonstrated that CNTN4 was a target gene of miR-148a-3p.

Conclusions

Overall, these findings suggested that miR-148a-3p inhibited oxLDL-induced cell apoptosis and inflammation via targeting CNTN4 in THP-1 macrophages.

Integrated Analysis of Gene Expression and Methylation Data to Identify Potential Biomarkers Related to Atherosclerosis Onset

Atherosclerosis is a kind of chronic inflammatory cardiovascular disease. Epigenetic regulation plays a crucial role in atherosclerosis. Our study was aimed at finding potential biomarkers associated with the occurrence of atherosclerosis. Two datasets were downloaded from the Gene Expression Omnibus (GEO) database. The epigenome-wide association study (EWAS) analysis was performed on methylation data using CpGassoc package. The differential expression analysis was conducted on mRNA data using limma package. The GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) functional enrichment was done in clusterProfiler package. Finally, the logistic regression model was constructed using generalized linear model (glm) function. Between atherosclerotic vs. nonatherosclerotic samples, totally 4980 cytosine-phosphate-guanine (CpG) sites (annotated to 2860 genes) and 132 differentially expressed genes (DEGs) related to atherosclerosis were identified. The annotated 2860 genes and 132 DEGs were significantly enriched in 9 and 4 KEGG pathways and 289 and 132 GO terms, respectively. After cross-analysis, 6 crucial CpG sites were screened to build the model, including cg01187920, cg03422911, cg08018825, cg10967350, cg14473924, and cg25313204. The diagnostic model could reliably separate the atherosclerosis samples from nonatherosclerotic samples. In conclusion, the 6 CpG sites are probably potential diagnostic biomarkers for atherosclerosis, including cg01187920, cg03422911, cg08018825, cg10967350, cg14473924, and cg25313204.

Genetic risk score constructed from common genetic variants is associated with cardiovascular disease risk in type 2 diabetes mellitus

BACKGROUND

Patients with type 2 diabetes mellitus (T2DM) experience a two-fold increased risk of cardiovascular diseases. Genome-wide association studies (GWAS) have identified T2DM susceptibility genetic variants. Interestingly, the genetic variants associated with cardiovascular disease risk in T2DM Han Chinese remain to be elucidated. The present study aimed to investigate the genetic variants associated with cardiovascular disease risk in T2DM.

METHODS

We performed bootstrapping, GWAS and an investigation of genetic variants associated with cardiovascular disease risk in a discovery T2DM cohort and in a replication cohort. The discovery cohort included 326 cardiovascular disease patients and 1209 noncardiovascular disease patients. The replication cohort included 68 cardiovascular disease patients and 317 noncardiovascular disease patients. The main outcome measures were genetic variants for genetic risk score (GRS) in cardiovascular disease risk in T2DM.

RESULTS

In total, 35 genetic variants were associated with cardiovascular disease risk. A GRS was generated by combining risk alleles from these variants weighted by their estimated effect sizes (log odds ratio [OR]). T2DM patients with weighted GRS ≥ 12.63 had an approximately 15-fold increase in cardiovascular disease risk (odds ratio = 15.67, 95% confidence interval [CI] = 10.33-24.00) compared to patients with weighted GRS < 10.39. With the addition of weighted GRS, receiver-operating characteristic curves showed that area under the curve with conventional risk factors was improved from 0.719 (95% CI = 0.689-0.750) to 0.888 (95% CI = 0.866-0.910).

CONCLUSIONS

These 35 genetic variants are associated with cardiovascular disease risk in T2DM, alone and cumulatively. T2DM patients with higher levels of weighted genetic risk score have higher cardiovascular disease risks.

PPARGC1B Is Associated with Nontraumatic Osteonecrosis of the Femoral Head: A Genomewide Association Study on a Chart-Reviewed Cohort

BACKGROUND

Previous studies have demonstrated the influence of heritable factors on the development of nontraumatic osteonecrosis of the femoral head (ONFH). We hypothesized that genetic variation is associated with an increased risk of ONFH, and that variants could be identified by a genomewide association study (GWAS).

METHODS

Using data collected from the MyCode Community Health Initiative, we identified 118 adult patients with radiographically confirmed nontraumatic ONFH. Study patients were statistically compared with a control population of 56,811 unrelated individuals without a diagnosis of ONFH. A case-control GWAS was performed to identify single nucleotide variants (SNVs) associated with ONFH. Sensitivity analyses were performed to evaluate the association of the top SNVs with (cortico)steroid-associated ONFH and ONFH with femoral head collapse. Gene-based analyses were performed to identify potential causal genes.

RESULTS

Of the 118 patients, 114 (96.6%) had bilateral ONFH at a median of 5 years of follow-up; 90.7% had at least one 3-week steroid prescription compared with 68.3% in controls. A GWAS identified 4 SNVs reaching genomewide significance. rs116468452 near CACNA1E was significantly associated with ONFH (p = 3.26 × 10, odds ratio [OR] = 5.6, 95% confidence interval [CI] = 3.21 to 9.76). rs10953090 in SAMD9 was significantly associated with ONFH in the steroid-exposed subset (p = 2.96 × 10, OR = 2.57, 95% CI = 1.84 to 3.58). rs112467115 in PI4K1B showed enhanced association in the collapsed subset (p = 7.82 × 10, OR = 4.5, 95% CI = 2.60 to 7.79). Gene-based analyses identified PPARGC1B as the only gene significantly associated with ONFH after Bonferroni correction (p = 1 × 10), with the lead SNV being rs78814834 (OR = 2.86, 95% CI = 1.87 to 4.38).

CONCLUSIONS

We identified 4 SNVs and 1 gene, PPARGC1B, associated with ONFH.

LEVEL OF EVIDENCE

Prognostic Level IV. See Instructions for Authors for a complete description of levels of evidence.