Proteomic Analysis of Renal Biomarkers of Kidney Allograft Fibrosis-A Study in Renal Transplant Patients.

Renal transplantation is the preferred treatment of end stage renal disease, but allograft survival is limited by the development of interstitial fibrosis and tubular atrophy in response to various stimuli. Much effort has been put into identifying new protein markers of fibrosis to support the diagnosis. In the present work, we performed an in-depth quantitative proteomics analysis of allograft biopsies from 31 prevalent renal transplant patients and correlated the quantified proteins with the volume fraction of fibrosis as determined by a morphometric method. Linear regression analysis identified four proteins that were highly associated with the degree of interstitial fibrosis, namely Coagulation Factor XIII A chain (estimate 18.7, adjusted p < 0.03), Uridine Phosphorylase 1 (estimate 19.4, adjusted p < 0.001), Actin-related protein 2/3 subunit 2 (estimate 34.2, adjusted p < 0.05) and Cytochrome C Oxidase Assembly Factor 6 homolog (estimate -44.9, adjusted p < 0.002), even after multiple testing. Proteins that were negatively associated with fibrosis (p < 0.005) were primarily related to normal metabolic processes and respiration, whereas proteins that were positively associated with fibrosis (p < 0.005) were involved in catabolic processes, cytoskeleton organization and the immune response. The identified proteins may be candidates for further validation with regards to renal fibrosis. The results support the notion that cytoskeleton organization and immune responses are prevalent processes in renal allograft fibrosis.

DNA methylome profiling of all-cause mortality in comparison with age-associated methylation patterns.

BACKGROUND: Multiple epigenome-wide association studies have been performed to identify DNA methylation patterns regulated by aging or correlated with risk of death. However, the inter-relatedness of the epigenetic basis of aging and mortality has not been well investigated. METHODS: Using genome-wide DNA methylation data from the Lothian Birth Cohorts, we conducted a genome-wide association analysis of all-cause mortality and compared this with age-associated methylation patterns reported on the same samples. RESULTS: Survival analysis using the Cox regression model identified 2552 CpG sites with genome-wide significance (false discovery rate < 0.05) for all-cause mortality. CpGs whose methylation levels are associated with increased mortality appear more distributed from the gene body to the intergenic regions whereas CpGs whose methylation levels are associated with decreased mortality is more concentrated at the promoter regions. In comparison with reported CpGs displaying significant age-dependent methylation patterns in the same samples, we observed a limited but highly significant overlap between mortality-associated and age-associated CpGs (p value 2.52e-06). Most importantly, the overlapping CpGs are dominated by those whose overall age-related methylation patterns reduce the risk of death. CONCLUSION: All-cause mortality is significantly associated with altered methylation at multiple genomic sites with differential distribution in gene regions for CpGs correlated with increased or decreased risk of death. The age-dependent methylation changes could reflect an active response to the aging process that contributes to maintain individual survival.

Advanced Parental Age at Conception and Sex Affects Mitochondrial DNA Copy Number in Human and Fruit Flies.

Aging is a multifactorial trait caused by early as well as late-life circumstances. A society trend that parents deliberately delay having children is of concern to health professionals, for example as advanced parental age at conception increases disease risk profiles in offspring. We here aim to study if advanced parental age at conception affects mitochondrial DNA content, a cross-species biomarker of general health, in adult human twin offspring and in a model organism. We find no deteriorated mitochondrial DNA content at advanced parental age at conception, but human mitochondrial DNA content was higher in females than males, and the difference was twofold higher at advanced maternal age at conception. Similar parental age effects and sex-specific differences in mitochondrial DNA content were found in Drosophila melanogaster. In addition, parental longevity in humans associates with both mitochondrial DNA content and parental age at conception; thus, we carefully propose that a poorer disease risk profile from advanced parental age at conception might be surpassed by superior effects of parental successful late-life reproduction that associate with parental longevity.

DNA Methylation and All-Cause Mortality in Middle-Aged and Elderly Danish Twins.

Several studies have linked DNA methylation at individual CpG sites to aging and various diseases. Recent studies have also identified single CpGs whose methylation levels are associated with all-cause mortality. In this study, we perform an epigenome-wide study of the association between CpG methylation and mortality in a population of 435 monozygotic twin pairs from three Danish twin studies. The participants were aged 55-90 at the time of blood sampling and were followed for up to 20 years. We validated our results by comparison with results from a British and a Swedish cohort, as well as results from the literature. We identified 2806 CpG sites associated with mortality (false discovery rate ( FDR ) < 0.05 ), of which 24 had an association p-value below 10 - 7 . This was confirmed by intra-pair comparison controlling for confounding effects. Eight of the 24 top sites could be validated in independent datasets or confirmed by previous studies. For all these eight sites, hypomethylation was associated with poor survival prognosis, and seven showed monozygotic correlations above 35%, indicating a potential moderate to strong heritability, but leaving room for substantial shared or unique environmental effects. We also set up a predictor for mortality using least absolute shrinkage and selection operator (LASSO) regression. The predictor showed good performance on the Danish data under cross-validation, but did not perform very well in independent samples.