Background A subset of individuals with type 1 diabetes mellitus (T1DM) are predisposed to developing diabetic kidney disease (DKD), the most common cause globally of end-stage kidney disease (ESKD). Emerging evidence suggests epigenetic changes in DNA methylation may have a causal role in both T1DM and DKD. The aim of this exploratory investigation was to assess differences in blood-derived DNA methylation patterns between individuals with T1DM-ESKD and individuals with long-duration T1DM but no evidence of kidney disease upon repeated testing to identify potential blood-based biomarkers. Blood-derived DNA from individuals (107 cases, 253 controls and 14 experimental controls) were bisulphite treated before DNA methylation patterns from both groups were generated and analysed using Illumina’s Infinium MethylationEPIC BeadChip arrays (n = 862,927 sites). Differentially methylated CpG sites (dmCpGs) were identified (false discovery rate adjusted p ≤ × 10–8 and fold change ± 2) by comparing methylation levels between ESKD cases and T1DM controls at single site resolution. Gene annotation and functionality was investigated to enrich and rank methylated regions associated with ESKD in T1DM. Results Top-ranked genes within which several dmCpGs were located and supported by functional data with methylation look-ups in other cohorts include: AFF3, ARID5B, CUX1, ELMO1, FKBP5, HDAC4, ITGAL, LY9, PIM1, RUNX3, SEPTIN9 and UPF3A. Top-ranked enrichment pathways included pathways in cancer, TGF-β signalling and Th17 cell differentiation. Conclusions Epigenetic alterations provide a dynamic link between an individual’s genetic background and their environmental exposures. This robust evaluation of DNA methylation in carefully phenotyped individuals has identified biomarkers associated with ESKD, revealing several genes and implicated key pathways associated with ESKD in individuals with T1DM.

Hereditary hemorrhagic telangiectasia (HHT) is an autosomal dominant multisystemic vascular dysplasia, characterized by arteriovenous malformations (AVMs), mucocutaneous telangiectasia and nosebleeds. HHT is caused by a heterozygous null allele in ACVRL1, ENG, or SMAD4, which encode proteins mediating bone morphogenetic protein (BMP) signaling. Several missense and stop-gain variants identified in GDF2 (encoding BMP9) have been reported to cause a vascular anomaly syndrome similar to HHT, however none of these patients met diagnostic criteria for HHT. HHT families from UK NHS Genomic Medicine Centres were recruited to the Genomics England 100,000 Genomes Project. Whole genome sequencing and tiering protocols identified a novel, heterozygous GDF2 sequence variant in all three affected members of one HHT family who had previously screened negative for ACVRL1, ENG, and SMAD4. All three had nosebleeds and typical HHT telangiectasia, and the proband also had severe pulmonary AVMs from childhood. In vitro studies showed the mutant construct expressed the proprotein but lacked active mature BMP9 dimer, suggesting the mutation disrupts correct cleavage of the protein. Plasma BMP9 levels in the patients were significantly lower than controls. In conclusion, we propose that this

Background: Patients with rare diseases face unique challenges in obtaining a diagnosis, appropriate medical care and access to support services. Whole genome and exome sequencing have increased identification of causal variants compared to single gene testing alone, with diagnostic rates of approximately 50% for inherited diseases, however integrated multi-omic analysis may further increase diagnostic yield. Additionally, multi-omic analysis can aid the explanation of genotypic and phenotypic heterogeneity, which may not be evident from single omic analyses. Main body: This scoping review took a systematic approach to comprehensively search the electronic databases MEDLINE, EMBASE, PubMed, Web of Science, Scopus, Google Scholar, and the grey literature databases OpenGrey / GreyLit for journal articles pertaining to multi-omics and rare disease, written in English and published prior to the 30th December 2018. Additionally, The Cancer Genome Atlas publications were searched for relevant studies and forward citation searching / screening of reference lists was performed to identify further eligible articles. Following title, abstract and full text screening, 66 articles were found to be eligible for inclusion in this review. Of these 42 (64%) were studies of multi-omics and rare cancer, two (3%) were studies of multi-omics and a pre-cancerous condition, and 22 (33.3%) were studies of non-cancerous rare diseases. The average age of participants (where known) across studies was 39.4 years. There has been a significant increase in the number of multi-omic studies in recent years, with 66.7% of included studies conducted since 2016 and 33% since 2018. Fourteen combinations of multi-omic analyses for rare disease research were returned spanning genomics, epigenomics, transcriptomics, proteomics, phenomics and metabolomics. Conclusions: This scoping review emphasises the value of multi-omic analysis for rare disease research in several ways compared to single omic analysis, ranging from the provision of a diagnosis, identification of prognostic biomarkers, distinct molecular subtypes (particularly for rare cancers), and identification of novel therapeutic targets. Moving forward there is a critical need for collaboration of multi-omic rare disease studies to increase the potential to generate robust outcomes and development of standardised biorepository collection and reporting structures for multi-omic studies.

Type 1 diabetes affects over nine million individuals globally, with approximately 40% developing diabetic kidney disease. Emerging evidence suggests that epigenetic alterations, such as DNA methylation, are involved in diabetic kidney disease. Here we assess differences in blood-derived genome-wide DNA methylation associated with diabetic kidney disease in 1304 carefully characterised individuals with type 1 diabetes and known renal status from two cohorts in the United Kingdom-Republic of Ireland and Finland. In the meta-analysis, we identify 32 differentially methylated CpGs in diabetic kidney disease in type 1 diabetes, 18 of which are located within genes differentially expressed in kidneys or correlated with pathological traits in diabetic kidney disease. We show that methylation at 21 of the 32 CpGs predict the development of kidney failure, extending the knowledge and potentially identifying individuals at greater risk for diabetic kidney disease in type 1 diabetes.

Background The challenges in diagnosis of rare renal conditions can negatively impact patient prognosis, quality of life and result in significant healthcare costs. Differential methylation is emerging as an important biomarker for rare diseases and should be evaluated for rare renal conditions. Methods A comprehensive systematic review of methylation and rare renal disorders was conducted by searching the electronic databases MEDLINE, EMBASE, PubMed, Cochrane Library, alongside grey literature from GreyLit and OpenGrey databases, for publications published before September 2018. Additionally, the reference lists of the included papers were searched. Data was extracted and appraised including the primary focus, measurement and methodological rigour of the source. Eligibility criteria were adapted using the inclusion criteria from ‘The 100,000 Genomes Project’ and The National Registry of Rare Kidney Diseases, with additional focus on methylation. Results Thirteen full text articles were included in the review. Diseases analysed for differential methylation included glomerular disease, IgA nephropathy, ADPKD, rare causes of proteinuria, congenital renal agenesis, and membranous nephropathy. Conclusions Differential methylation has been observed for several rare renal diseases, highlighting its potential for improving molecular characterisation of these disorders. Further investigation of methylation following a standardised reporting structure is necessary to improve research quality. Multi-omic data will provide insights for improved diagnosis, prognosis and support for individuals living and working with rare renal diseases. Electronic supplementary material The online version of this article (10.1186/s12882-019-1517-5) contains supplementary material, which is available to authorized users.