Role of telomeres and sex hormones in pulmonary fibrosis

Disease susceptibility can be driven by genetic mutations and epigenetic changes such as DNA methylation, histone acetylation and expression of non-coding RNA (ncRNA). Tissue damage results in so-called circulating DNA (circDNA) and ncRNA entering the bloodstream. CircDNA can now be used as a 'liquid biopsy' to aid cancer diagnosis. Assessment of epigenetic changes would be more widely applicable to other diseases, but is still in its infancy. Lung disease accounts for >20% of all deaths in the UK, and novel biomarkers which will improve disease classification and prediction of drug response ('personalised medicine') are urgently required. A key example is fibrosing lung disease (FLD), characterised by dysfunctional tissue repair and destruction of the lung architecture. In the UK, >5000 people die each year from the commonest form; there is marked heterogeneity in clinical phenotype but FLD patients experience disabling shortness of breath and vastly reduced life expectancy. Incidence is rising, prevalence is far higher than previously thought and there are no cures, thus FLD has an epidemiology and prognosis worse than many common cancers. Our central hypothesis is that epigenetic analysis of circDNA and ncRNA (Lindsay, 2014) in blood offers an opportunity to identify novel biomarkers to stratify FLD patients according to disease phenotype and predict responsiveness to therapy - something which current tests are unable to offer. Transcriptomic/epigenomic profiles of FLD lung tissue are well established, but lung tissue biopsies are fraught with risk, so routine use is limited. In many other diseases, epigenetic profiles in blood can serve as useful biomarkers, including our own studies in Alzheimer's disease (Lunnon, 2015).

Our principal aims are:

1) Isolate circDNA and ncRNA from patients with FLD (or healthy controls) and identify epigenetic changes by genome wide DNA methylation analysis and next generation sequencing.

2) Compare signatures to the published transcriptomic and epigenomic profiles of FLD lung tissue (our own datasets and those freely available through the gene expression omnibus [GEO]).

3) Correlate findings with epigenomic profiles in the Human Epigenome Atlas, to help define the contribution of other tissue subsets to the circulating epigenomic signature (notably liver and leukocytes). Determine whether DNA methylation is at specific locations (CpG islands, enhancers etc.).

4) In a subset of patients, isolate DNA/ncRNA from matched lung tissue biopsy (or laser-capture microdissected cellular subsets, namely epithelium and fibroblasts) to determine direct concordance between circDNA/ncRNA profiles and diseased lung tissue, with opportunities for co-epigenomic/expression and pathway analyses.

5) If enrichment analysis identifies particular ncRNA or gene-specific methylation patterns, further interrogate the functional role using in vitro (and potentially in vivo) model systems.


Citations:

IIott, N.E... and Lindsay, M.A. Long non-coding RNAs and enhancer RNA regulate the lipopolysaccharide-induced inflammatory response in human monocytes. Nature Communications. 5: 3979 (2014)

Lunnon et al. Blood methylomic signatures of presymptomatic dementia in elderly subjects with type 2 diabetes mellitus. Neurobiological Aging. 36(3):1600.e1-4 (2015)