Longitudinal genome-wide DNA methylation changes in response to kidney failure replacement therapy

Food to Prevent Vascular Calcification in Chronic Kidney Disease

Vascular calcification (VC) is a consequence of chronic kidney disease (CKD) which is of paramount importance regarding the survival of CKD patients. VC is far from being controlled with actual medication; as a result, in recent years, diet modulation has become more compelling. The concept of medical nutritional therapy points out the idea that food may prevent or treat diseases. The aim of this review was to evaluate the influence of food habits and nutritional intervention in the occurrence and progression of VC in CKD. Evidence reports the harmfulness of ultra-processed food, food additives, and animal-based proteins due to the increased intake of high absorbable phosphorus, the scarcity of fibers, and the increased production of uremic toxins. Available data are more supportive of a plant-dominant diet, especially for the impact on gut microbiota composition, which varies significantly depending on VC presence. Magnesium has been shown to prevent VC but only in experimental and small clinical studies. Vitamin K has drawn considerable attention due to its activation of VC inhibitors. There are positive studies; unfortunately, recent trials failed to prove its efficacy in preventing VC. Future research is needed and should aim to transform food into a medical intervention to eliminate VC danger in CKD.

Epigenetic clocks indicate that kidney transplantation and not dialysis mitigate the effects of renal ageing

BACKGROUND

Chronic kidney disease (CKD) is an age-related disease that displays multiple features of accelerated ageing. It is currently unclear whether the two treatment options for end-stage kidney disease (dialysis and kidney transplantation [KT]) ameliorate the accelerated uremic ageing process.

METHODS

Data on clinical variables and blood DNA methylation (DNAm) from CKD stage G3-G5 patients were used to estimate biological age based on blood biomarkers (phenotypic age [PA], n = 333), skin autofluorescence (SAF age, n = 199) and DNAm (Horvath, Hannum and PhenoAge clocks, n = 47). In the DNAm cohort, we also measured the change in biological age 1 year after the KT or initiation of dialysis. Healthy subjects recruited from the general population were included as controls.

RESULTS

All three DNAm clocks indicated an increased biological age in CKD G5. However, PA and SAF age tended to produce implausibly large estimates of biological age in CKD G5. By contrast, DNAm age was 4.9 years (p = 0.005) higher in the transplantation group and 5.9 years (p = 0.001) higher in the dialysis group compared to controls. This age acceleration was significantly reduced 1 year after KT, but not after 1 year of dialysis.

CONCLUSIONS

Kidney failure patients displayed an increased biological age as estimated by DNAm clocks compared to population-based controls. Our results suggest that KT, but not dialysis, partially reduces the age acceleration.

Association of DNA methylation signatures with premature ageing and cardiovascular death in patients with end-stage kidney disease: a pilot epigenome-wide association study

Patients with end-stage kidney disease (ESKD) display features of premature aging. There is strong evidence that changes in DNA methylation (DNAm) contribute to age-related pathologies; however, little is known about their association with premature aging and cardiovascular mortality in patients with ESKD. We assayed genome-wide DNAm in a pilot case-control study of 60 hemodialysis patients with (n=30, cases) and without (n=30, controls) a fatal cardiovascular event. DNAm was profiled on the Illumina EPIC BeadChip. Four established DNAm clocks (i.e., Horvath-, Hannum-, Pheno-, and GrimAge) were used to estimate epigenetic age (DNAmAge). Epigenetic age acceleration (EAA) was derived as the residuals of regressing DNAmAge on chronological age (chroAge), and its association with cardiovascular death was examined using multivariable conditional logistic regression. An epigenome-wide association study (EWAS) was performed to identify differentially methylated CpGs associated with cardiovascular death. All clocks performed well at predicting chroAge (correlation between DNAmAges and chroAge of r=0.76-0.89), with GrimAge showing the largest deviation from chroAge (a mean of +21.3 years). There was no significant association of EAAs with cardiovascular death. In the EWAS, a CpG (cg22305782) in the FBXL19 gene had the strongest association with cardiovascular death with significantly lower DNAm in cases vs. controls (P_FDR=2.0x10^-6). FBXL19 is involved in cell apoptosis, inflammation, and adipogenesis. Overall, we observed more accelerated aging in patients with ESKD, although there was no significant association of EAAs with cardiovascular death. EWAS suggests a potential novel DNAm biomarker for premature cardiovascular mortality in ESKD.

Identification of Genes Associated with Decreasing Abundance of Monocytes in Long-Term Peritoneal Dialysis Patients

Purpose

Chronic kidney disease (CKD) will become an end-stage renal disease (ESRD) at stage 5. Peritoneal dialysis (PD) is required for renal replacement therapy. This study aims to identify monocytes-related genes in peritoneal cells from long-term PD (LPD) patients and short-term PD (SPD) patients.

Methods

Bulk RNA-seq data (GSE125498 dataset) and ScRNA-seq data (GSE130888) were downloaded to identify differentially expressed genes, monocytes-related genes, and monocytes marker genes in LPD patients. Immune infiltration was analyzed in the GSE125498 dataset. Core genes associated with monocytes changes were screened out, followed by functional analysis and expression validation using RT-PCR.

Results

Monocytes are the most abundant immune cell in PD. The number of monocytes was remarkably decreased in LPD compared with SPD. A total of 16 up-regulated core genes negatively correlated with the abundance of monocytes were obtained in LPD. The expression of 16 core genes was lower in monocyte clusters than that in other cell clusters. In addition, LCK, CD3G, CD3E, CD3D, and LAT were involved in the signaling pathways of Th1 and Th2 cell differentiation, T cell receptor signaling pathway, and Th17 cell differentiation. CD2 was involved in hematopoietic cell lineage signaling pathway.

Conclusion

Identification of monocytes related-genes and related signaling pathways could be helpful in understanding the molecular mechanism of monocytes changes during PD.

Epigenetic regulation of mitochondrial-endoplasmic reticulum dynamics in kidney diseases

Kidney diseases are serious health problems affecting >800 million individuals worldwide. The high number of affected individuals and the severe consequences of kidney dysfunction demand an intensified effort toward more effective prevention and treatment. The pathophysiology of kidney diseases is complex and comprises diverse organelle dysfunctions including mitochondria and endoplasmic reticulum (ER). The recent findings prove interactions between the ER membrane and nearly all cell compartments and give new insights into molecular events involved in cellular mechanisms in health and disease. Interactions between the ER and mitochondrial membranes, known as the mitochondria-ER contacts regulate kidney physiology by interacting with each other via membrane contact sites (MCS). ER controls mitochondrial dynamics through ER stress sensor proteins or by direct communication via mitochondria-associated ER membrane to activate signaling pathways such as apoptosis, calcium transport, and autophagy. More importantly, these organelle dynamics are found to be regulated by several epigenetic mechanisms such as DNA methylation, histone modifications, and noncoding RNAs and can be a potential therapeutic target against kidney diseases. However, a thorough understanding of the role of epigenetic regulation of organelle dynamics and their functions is not well understood. Therefore, this review will unveil the role of epigenetic mechanisms in regulating organelle dynamics during various types of kidney diseases. Moreover, we will also shed light on different stress origins in organelles leading to kidney disease. Henceforth, by understanding this we can target epigenetic mechanisms to maintain/control organelle dynamics and serve them as a novel therapeutic approach against kidney diseases.

"Transplantomics" for predicting allograft rejection: real-life applications and new strategies from Network Medicine

Although decades of the reductionist approach achieved great milestones in optimizing the immunosuppression therapy, traditional clinical parameters still fail in predicting both acute and chronic (mainly) rejection events leading to higher rates across all solid organ transplants. To clarify the underlying immune-related cellular and molecular mechanisms, current biomedical research is increasingly focusing on "transplantomics" which relies on a huge quantity of big data deriving from genomics, transcriptomics, epigenomics, proteomics, and metabolomics platforms. The AlloMap (gene expression) and the AlloSure (donor-derived cell-free DNA) tests represent two successful examples of how omics and liquid biopsy can really improve the precision medicine of heart and kidney transplantation. One of the major challenges in translating big data in clinically useful biomarkers is the integration and interpretation of the different layers of omics datasets. Network Medicine offers advanced bioinformatic-molecular strategies which were widely used to integrate large omics datasets and clinical information in end-stage patients to prioritize potential biomarkers and drug targets. The application of network-oriented approaches to clarify the complex nature of graft rejection is still in its infancy. Here, we briefly discuss the real-life clinical applications derived from omics datasets as well as novel opportunities for establishing predictive tests in solid organ transplantation. Also, we provide an original "graft rejection interactome" and propose network-oriented strategies which can be useful to improve precision medicine of solid organ transplantation.

Harnessing the Full Potential of Multi-Omic Analyses to Advance the Study and Treatment of Chronic Kidney Disease

Chronic kidney disease (CKD) was the 12th leading cause of death globally in 2017 with the prevalence of CKD estimated at ~9%. Early detection and intervention for CKD may improve patient outcomes, but standard testing approaches even in developed countries do not facilitate identification of patients at high risk of developing CKD, nor those progressing to end-stage kidney disease (ESKD). Recent advances in CKD research are moving towards a more personalised approach for CKD. Heritability for CKD ranges from 30% to 75%, yet identified genetic risk factors account for only a small proportion of the inherited contribution to CKD. More in depth analysis of genomic sequencing data in large cohorts is revealing new genetic risk factors for common diagnoses of CKD and providing novel diagnoses for rare forms of CKD. Multi-omic approaches are now being harnessed to improve our understanding of CKD and explain some of the so-called 'missing heritability'. The most common omic analyses employed for CKD are genomics, epigenomics, transcriptomics, metabolomics, proteomics and phenomics. While each of these omics have been reviewed individually, considering integrated multi-omic analysis offers considerable scope to improve our understanding and treatment of CKD. This narrative review summarises current understanding of multi-omic research alongside recent experimental and analytical approaches, discusses current challenges and future perspectives, and offers new insights for CKD.

Challenges in Analyzing Functional Epigenetic Data in Perspective of Adolescent Psychiatric Health

The formative period of adolescence plays a crucial role in the development of skills and abilities for adulthood. Adolescents who are affected by mental health conditions are at risk of suicide and social and academic impairments. Gene-environment complementary contributions to the molecular mechanisms involved in psychiatric disorders have emphasized the need to analyze epigenetic marks such as DNA methylation (DNAm) and non-coding RNAs. However, the large and diverse bioinformatic and statistical methods, referring to the confounders of the statistical models, application of multiple-testing adjustment methods, questions regarding the correlation of DNAm across tissues, and sex-dependent differences in results, have raised challenges regarding the interpretation of the results. Based on the example of generalized anxiety disorder (GAD) and depressive disorder (MDD), we shed light on the current knowledge and usage of methodological tools in analyzing epigenetics. Statistical robustness is an essential prerequisite for a better understanding and interpretation of epigenetic modifications and helps to find novel targets for personalized therapeutics in psychiatric diseases.

Epigenetic Regulation in Kidney Transplantation

Kidney transplantation is a standard care for end stage renal disease, but it is also associated with a complex pathogenesis including ischemia-reperfusion injury, inflammation, and development of fibrosis. Over the past decade, accumulating evidence has suggested a role of epigenetic regulation in kidney transplantation, involving DNA methylation, histone modification, and various kinds of non-coding RNAs. Here, we analyze these recent studies supporting the role of epigenetic regulation in different pathological processes of kidney transplantation, i.e., ischemia-reperfusion injury, acute rejection, and chronic graft pathologies including renal interstitial fibrosis. Further investigation of epigenetic alterations, their pathological roles and underlying mechanisms in kidney transplantation may lead to new strategies for the discovery of novel diagnostic biomarkers and therapeutic interventions.

DNA Methylation Patterns According to Fatty Liver Index and Longitudinal Changes from the Korean Genome and Epidemiology Study (KoGES)

The role of differentially methylated regions (DMRs) in nonalcoholic fatty liver disease (NAFLD) is unclear. This study aimed to identify the role of DMR in NAFLD development and progression using the Korean Genome and Epidemiology Study (KoGES) cohort. We used laboratory evaluations and Illumina Methylation 450 k DNA methylation microarray data from KoGES. The correlation between fatty liver index (FLI) and genomic CpG sites was analyzed in 322 subjects. Longitudinal changes over 8 years were confirmed in 33 subjects. To identify CpG sites and genes related to FLI, we obtained enrichment terms for 6765 genes. DMRs were identified for both high (n = 128) and low (n = 194) groups on the basis of FLI 30 in 142 men and 180 women. To confirm longitudinal changes in 33 subjects, the ratio of follow-up and baseline investigation values was obtained. Correlations and group comparisons were performed for the 8 year change values. PITPNM3, RXFP3, and THRB were hypermethylated in the increased FLI groups, whereas SLC9A2 and FOXI3 were hypermethylated in the decreased FLI groups. DMRs describing NAFLD were determined, and functions related to inflammation were identified. Factors related to longitudinal changes are suggested, and blood circulation-related functions appear to be important in the management of NAFLD.