BackgroundOne in eleven people is affected by chronic kidney disease, a condition characterized by kidney fibrosis and progressive loss of kidney function. Epidemiological studies indicate that adverse intrauterine and postnatal environments have a long-lasting role in chronic kidney disease development. Epigenetic information represents a plausible carrier for mediating this programming effect. Here we demonstrate that genome-wide cytosine methylation patterns of healthy and chronic kidney disease tubule samples obtained from patients show significant differences.ResultsWe identify differentially methylated regions and validate these in a large replication dataset. The differentially methylated regions are rarely observed on promoters, but mostly overlap with putative enhancer regions, and they are enriched in consensus binding sequences for important renal transcription factors. This indicates their importance in gene expression regulation. A core set of genes that are known to be related to kidney fibrosis, including genes encoding collagens, show cytosine methylation changes correlating with downstream transcript levels.ConclusionsOur report raises the possibility that epigenetic dysregulation plays a role in chronic kidney disease development via influencing core pro-fibrotic pathways and can aid the development of novel biomarkers and future therapeutics.

Chronic kidney disease (CKD) is a complex gene-environmental disease affecting close to 10% of the US population. Genome-wide association studies (GWASs) have identified sequence variants, localized to non-coding genomic regions, associated with kidney function. Despite these robust observations, the mechanism by which variants lead to CKD remains a critical unanswered question. Expression quantitative trait loci (eQTL) analysis is a method to identify genetic variation associated with gene expression changes in specific tissue types. We hypothesized that an integrative analysis combining CKD GWAS and kidney eQTL results can identify candidate genes for CKD. We performed eQTL analysis by correlating genotype with RNA-seq-based gene expression levels in 96 human kidney samples. Applying stringent statistical criteria, we detected 1,886 genes whose expression differs with the sequence variants. Using direct overlap and Bayesian methods, we identified new potential target genes for CKD. With respect to one of the target genes, lysosomal beta A mannosidase (MANBA), we observed that genetic variants associated with MANBA expression in the kidney showed statistically significant colocalization with variants identified in CKD GWASs, indicating that MANBA is a potential target gene for CKD. The expression of MANBA was significantly lower in kidneys of subjects with risk alleles. Suppressing manba expression in zebrafish resulted in renal tubule defects and pericardial edema, phenotypes typically induced by kidney dysfunction. Our analysis shows that gene-expression changes driven by genetic variation in the kidney can highlight potential new target genes for CKD development.

Chronic kidney disease (CKD) has diverse phenotypic manifestations including structural (such as fibrosis) and functional (such as glomerular filtration rate and albuminuria) alterations. Gene expression profiling has recently gained popularity as an important new tool for precision medicine approaches. Here we used unbiased and directed approaches to understand how gene expression captures different CKD manifestations in patients with diabetic and hypertensive CKD.Transcriptome data from ninety-five microdissected human kidney samples with a range of demographics, functional and structural changes were used for the primary analysis. Data obtained from 41 samples were available for validation. Using the unbiased Weighted Gene Co-Expression Network Analysis (WGCNA) we identified 16 co-expressed gene modules.We found that modules that strongly correlated with eGFR primarily encoded genes with metabolic functions. Gene groups that mainly encoded T-cell receptor and collagen pathways, showed the strongest correlation with fibrosis level, suggesting that these two phenotypic manifestations might have different underlying mechanisms. Linear regression models were then used to identify genes whose expression showed significant correlation with either structural (fibrosis) or functional (eGFR) manifestation and mostly corroborated the WGCNA findings.We concluded that gene expression is a very sensitive sensor of fibrosis, as the expression of 1654 genes correlated with fibrosis even after adjusting to eGFR and other clinical parameters. The association between GFR and gene expression was mostly mediated by fibrosis. In conclusion, our transcriptome-based CKD trait dissection analysis suggests that the association between gene expression and renal function is mediated by structural changes and that there may be differences in pathways that lead to decline in kidney function and the development of fibrosis, respectively.

Genome-wide association studies have identified multiple novel genomic loci associated with vascular diseases. Many of these loci are common non-coding variants that affect the expression of disease-relevant genes within coronary vascular cells. To identify such genes on a genome-wide level, we performed deep transcriptomic analysis of genotyped primary human coronary artery smooth muscle cells (HCASMCs) and coronary endothelial cells (HCAECs) from the same subjects, including splicing Quantitative Trait Loci (sQTL), allelespecific expression (ASE), and colocalization analyses. We identified sQTLs for TARS2, YAP1, CFDP1, and STAT6 in HCASMCs and HCAECs, and 233 ASE genes, a subset of which are also GTEx eGenes in arterial tissues. Colocalization of GWAS association signals for coronary artery disease (CAD), migraine, stroke and abdominal aortic aneurysm with GTEx eGenes in aorta, coronary artery and tibial artery discovered novel candidate risk genes for these diseases. At the CAD and stroke locus tagged by rs2107595 we demonstrate colocalization with expression of the proximal gene TWIST1. We show that disrupting the rs2107595 locus alters TWIST1 expression and that the risk allele has increased binding of the NOTCH signaling protein RBPJ. Finally, we provide data that TWIST1 expression influences vascular SMC phenotypes, including proliferation and calcification, as a potential mechanism supporting a role for TWIST1 in CAD.

Only a few percent of the 3 billion pairs of chemical letters in the human genome is responsible for protein-coding sequences. Recent advances in the field of epigenomics have helped us to understand how most of the remaining sequences are responsible for gene regulation at baseline and in disease conditions. Here we discuss recent advances in the area of epigenetics--specifically in cytosine modifications--and its application in the field of nephrology.