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A Molecular signature for Delayed Graft Function

ABSTRACT: A Molecular signature for Delayed Graft Function

PROVIDER: PRJNA356242 | ENA |

REPOSITORIES: ENA

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Dataset's files

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			Action	DRS
	SRR5076690.fastq.gz	Fastqsanger.gz
	SRR5076690_1.fastq.gz	Fastqsanger.gz
	SRR5076690_2.fastq.gz	Fastqsanger.gz
	SRR5076700.fastq.gz	Fastqsanger.gz
	SRR5076700_1.fastq.gz	Fastqsanger.gz

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Project description:This SuperSeries is composed of the SubSeries listed below.

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A molecular signature for delayed graft function.

Project description:Chronic kidney disease and associated comorbidities (diabetes, cardiovascular diseases) manifest with an accelerated ageing phenotype, leading ultimately to organ failure and renal replacement therapy. This process can be modulated by epigenetic and environmental factors which promote loss of physiological function and resilience to stress earlier, linking biological age with adverse outcomes post-transplantation including delayed graft function (DGF). The molecular features underpinning this have yet to be fully elucidated. We have determined a molecular signature for loss of resilience and impaired physiological function, via a synchronous genome, transcriptome and proteome snapshot, using human renal allografts as a source of healthy tissue as an in vivo model of ageing in humans. This comprises 42 specific transcripts, related through IFNγ signalling, which in allografts displaying clinically impaired physiological function (DGF) exhibited a greater magnitude of change in transcriptional amplitude and elevated expression of noncoding RNAs and pseudogenes, consistent with increased allostatic load. This was accompanied by increased DNA methylation within the promoter and intragenic regions of the DGF panel in preperfusion allografts with immediate graft function. Pathway analysis indicated that an inability to sufficiently resolve inflammatory responses was enabled by decreased resilience to stress and resulted in impaired physiological function in biologically older allografts. Cross-comparison with publically available data sets for renal pathologies identified significant transcriptional commonality for over 20 DGF transcripts. Our data are clinically relevant and important, as they provide a clear molecular signature for the burden of "wear and tear" within the kidney and thus age-related physiological capability and resilience.

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