Medicine has benefited from the use of molecular biomarkers for estimating health risks, diagnosing disease, selecting treatments and predicting treatment response. Omic technologies make possible the comprehensive exploration of available biomarkers by quantifying a large proportion of the molecules that make up human cells. Unfortunately, generating omic datasets can be very costly, require extensive tissue collections, and consume large amounts of tissue. Consequently, large populations with measurements for multiple omics are somewhat rare. Furthermore, analyses are generally performed in peripheral tissues such as blood or saliva that can be collected using minimally invasive procedures. Such tissues may have minimal direct relevance to many health questions.
We propose to use biological variation captured by DNA methylation (DNAm) patterns in peripheral tissues as a way to overcome these limitations. Genome-wide DNAm profiles (methylomes) have been generated from peripheral blood and saliva samples for many populations studies because DNA can be easily extracted and stored without disrupting DNAm and because methylomes can be easily and cheaply measured using standardized protocols with the Illumina bead chip. Other -omes such as the proteome, transcriptome and metabolome are much less common but are being generated alongside methylomes for some studies. We propose to use these datasets to generate methylome models of the other -omes that can then be used as their surrogates in studies with only methylome measurements.
We propose a similar solution to compensate for the lack of methylomes measured in target tissues. A small but growing collection of studies have generated methylomes of both peripheral and non-peripheral tissues. We will use these datasets to generate peripheral tissue models of non-peripheral methylomes. These models can then be used to undertake tissue-specific analyses in studies with methylomes measured only in peripheral tissues.
Although we do not expect methylomes in peripheral tissues to capture all relevant biological variation, there is evidence that they can capture much useful variation which can then be used to improve biomarker performance. For example, in a study of lifespan prediction, performance was improved by generating predictors from methylome models of protein variation rather than directly from the methylome itself (Lu, Quach et al. 2019). Although many studies report extensive differences between tissue methylomes, thousands of genomic loci have been identified where inter-individual variation of blood DNAm captures at least a moderate proportion of the inter-individual variation in brain (Hannon, Lunnon et al. 2015, Braun, Han et al. 2019), adipose tissue (Huang, Chu et al. 2016), liver, subcutaneous fat, omentum and skeletal muscle (Slieker, Bos et al. 2013). Similar findings hold for saliva (Smith, Kilaru et al. 2015, Braun, Han et al. 2019). However, no study so far has attempted to construct models of biological variation in non-peripheral tissues using the entire methylome of a peripheral tissue rather than individual genomic loci.
The PhD will result in high impact journal articles, and results being presented at national/international meetings and conferences.
Applications are welcome from high performing individuals across a wide range of disciplines closely related to natural sciences, biostatistics, genetics, bio-chemistry, mathematics and computer science who have, or are expected to obtain, a 2.i or higher degree. Applications are particularly welcome from individuals with a relevant research Masters degree.
How to apply
Please make an online application for this project here: https://www.findaphd.com/phds/program/the-gw4-biomed-mrc-dtp-is-offering-up-to-18-fully-funded-studentships-across-a-range-of-biomedical-disciplines-with-a-start-date-of-october-2020/?p2940
The University of Bristol is offering a 3.5 year full time PhD in research around Population Health to start in 2020. This studentship is funded through GW4BioMed MRC Doctoral Training Partnership. It consists of full UK/EU tuition fees, as well as a Doctoral Stipend matching UK Research Council National Minimum (£15009 p.a. for 2019/20, updated each year).
Additional research and training funding is available over the course of the programme. This will cover costs such as research consumables, courses, conferences and travel. Additional competitive funds are available for high-cost training/research.
The studentship is based at the Bristol Medical School. For further information please see the website below.