Identification of pleiotropic genes between risk factors of stroke by multivariate metaCCA analysis

Multivariate canonical correlation analysis identifies additional genetic variants for chronic kidney disease

Chronic kidney diseases (CKD) have genetic associations with kidney function. Univariate genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with estimated glomerular filtration rate (eGFR) and blood urea nitrogen (BUN), two complementary kidney function markers. However, it is unknown whether additional SNPs for kidney function can be identified by multivariate statistical analysis. To address this, we applied canonical correlation analysis (CCA), a multivariate method, to two individual-level CKD genotype datasets, and metaCCA to two published GWAS summary statistics datasets. We identified SNPs previously associated with kidney function by published univariate GWASs with high replication rates, validating the metaCCA method. We then extended discovery and identified previously unreported lead SNPs for both kidney function markers, jointly. These showed expression quantitative trait loci (eQTL) colocalisation with genes having significant differential expression between CKD and healthy individuals. Several of these identified lead missense SNPs were predicted to have a functional impact, including in SLC14A2. We also identified previously unreported lead SNPs that showed significant correlation with both kidney function markers, jointly, in the European ancestry CKDGen, National Unified Renal Translational Research Enterprise (NURTuRE)-CKD and Salford Kidney Study (SKS) datasets. Of these, rs3094060 colocalised with FLOT1 gene expression and was significantly more common in CKD cases in both NURTURE-CKD and SKS, than in the general population. Overall, by using multivariate analysis by CCA, we identified additional SNPs and genes for both kidney function and CKD, that can be prioritised for further CKD analyses.

PDE3A and GSK3B as Atrial Fibrillation Susceptibility Genes in the Chinese Population via Bioinformatics and Genome-Wide Association Analysis

Background: Atrial fibrillation (AF) is the most common cardiac arrhythmia, with uncovered genetic etiology and pathogenesis. We aimed to screen out AF susceptibility genes with potential pathogenesis significance in the Chinese population. Methods: Differentially expressed genes (DEGs) were screened by the Limma package in three GEO data sets of atrial tissue. AF-related genes were identified by combination of DEGs and public GWAS susceptibility genes. Potential drug target genes were selected using the DrugBank, STITCH and TCMSP databases. Pathway enrichment analyses of AF-related genes were performed using the databases GO and KEGG databases. The pathway gene network was visualized by Cytoscape software to identify gene–gene interactions and hub genes. GWAS analysis of 110 cases of AF and 1201 controls was carried out through a genome-wide efficient mixed model in the Fangshan population to verify the results of bioinformatic analysis. Results: A total of 3173 DEGs were identified, 57 of which were found to be significantly associated with of AF in public GWAS results. A total of 75 AF-related genes were found to be potential therapeutic targets. Pathway enrichment analysis selected 79 significant pathways and classified them into 7 major pathway networks. A total of 35 hub genes were selected from the pathway networks. GWAS analysis identified 126 AF-associated loci. PDE3A and GSK3B were found to be overlapping genes between bioinformatic analysis and GWAS analysis. Conclusions: We screened out several pivotal genes and pathways involved in AF pathogenesis. Among them, PDE3A and GSK3B were significantly associated with the risk of AF in the Chinese population. Our study provided new insights into the mechanisms of action of AF.

Momordicine I alleviates isoproterenol-induced cardiomyocyte hypertrophy through suppression of PLA2G6 and DGK-ζ

This study aimed to observe the protective effect of momordicine I, a triterpenoid compound extracted from momordica charantia L., on isoproterenol (ISO)-induced hypertrophy in rat H9c2 cardiomyocytes and investigate its potential mechanism. Treatment with 10 μM ISO induced cardiomyocyte hypertrophy as evidenced by increased cell surface area and protein content as well as pronounced upregulation of fetal genes including atrial natriuretic peptide, β-myosin heavy chain, and α-skeletal actin; however, those responses were markedly attenuated by treatment with 12.5 μg/ml momordicine I. Transcriptome experiment results showed that there were 381 and 447 differentially expressed genes expressed in comparisons of model/control and momordicine I intervention/model, respectively. GO enrichment analysis suggested that the anti-cardiomyocyte hypertrophic effect of momordicine I may be mainly associated with the regulation of metabolic processes. Based on our transcriptome experiment results as well as literature reports, we selected glycerophospholipid metabolizing enzymes group VI phospholipase A₂ (PLA2G6) and diacylglycerol kinase ζ (DGK-ζ) as targets to further explore the potential mechanism through which momordicine I inhibited ISO-induced cardiomyocyte hypertrophy. Our results demonstrated that momordicine I inhibited ISO-induced upregulations of mRNA levels and protein expressions of PLA2G6 and DGK-ζ. Collectively, momordicine I alleviated ISO-induced cardiomyocyte hypertrophy, which may be related to its inhibition of the expression of glycerophospholipid metabolizing enzymes PLA2G6 and DGK-ζ.

Identification of novel functional CpG-SNPs associated with Type 2 diabetes and birth weight

Genome-wide association studies (GWASs) have identified hundreds of genetic loci for type 2 diabetes (T2D) and birth weight (BW); however, a large proportion of the total trait heritability remains unexplained. The previous studies were generally focused on individual traits and largely failed to identify the majority of the variants that play key functional roles in the etiology of the disease. Here, we aim to identify novel functional loci for T2D, BW and the pleiotropic variants shared between them by performing a targeted conditional false discovery rate (cFDR) analysis that integrates two independent GWASs with summary statistics for T2D (n = 26,676 cases and 132,532 controls) and BW (n = 153,781) which entails greater statistical power than individual trait analyses. In this analysis, we considered CpG-SNPs, which are SNPs that may influence DNA methylation status, and are therefore considered to be functionally important. We identified 103 novel CpG-SNPs for T2D, 182 novel CpG-SNPs for BW (cFDR < 0.05), and 52 novel pleiotropic loci for both (conjunction cFDR [ccFDR] < 0.05). Among the identified novel CpG-SNPs, 33 were annotated as methylation quantitative trait loci (meQTLs) in whole blood, and 145 displayed at least some effects on meQTL, metabolic QTL (metaQTL), and/or expression QTL (eQTL). These findings may provide further insights into the shared biological mechanisms and functional genetic determinants that overlap between T2D and BW, thereby providing novel potential targets for treatment/intervention development.