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Queen's University Belfast

Development of a framework for multiomic analysis in disease research

Abstract

dc:description.abstract

Multi-omics is the combination of several -omic terms to develop an interconnected understanding of molecular biology, which can provide increased insights into disease. Commonly known –omic terms include genomics, epigenomics, transcriptomics, proteomics and metabolomics. The potentials of multi-omic disease research is particularly promising for patients with rare diseases, which affect one in 17 people in the United Kingdom and have a genetic component in ~80% of individuals. Comprehensive reviews of rare disease omics literature identified that multi-omics may offer improved diagnostic yields, increased understanding of pathogenesis and identify therapeutic targets. As part of the 100,000 Genomes Project (100KGP) and in collaboration with the Northern Ireland Genomic Medicine Centre (NIGMC), 815 PAXgene (for RNA analysis) and 738 buffy coats (for DNA and epigenetic analysis) were collected and stored, with the intention of further multi-omic analysis where whole genome sequencing by the 100KGP was insufficient to provide a diagnosis for patients with rare diseases. During the waiting period for return of results from the 100KGP, integrated epigenetic and transcriptomic analysis was conducted in kidney transplant recipients with a variety of rare and common primary renal diagnoses (n = 52) compared to controls with no evidence of kidney disease (n = 28), identifying novel (TTC21B and PLEKHA1) and previously known markers of kidney disease (UMOD, EGF). Following the return of results from the 100KGP, the NIGMC variant interpretation process was evaluated and genetic analysis was conducted of tier 3 variants, in this instance focusing on renal phenotypes. Several tier 3 variants of interest were identified for further follow up in a postdoctoral research project following completion of this PhD (including UROD, VDR, COL18A1, MST1, SCNN1B, BBS9, UMOD and MYH10). Qualitative analysis of perspectives surrounding multi-omics with participants of the 100KGP and carers identified that awareness of these technologies is low, but there is a desire to learn more, and inclusion of the basic concepts of multi-omics within genomics education may be beneficial. Finally, the utilisation of complementary and alternative medicines for management of rare diseases was explored in an online survey and workshop due to high reported usage, and determined there is a need for high quality research supporting safety and efficacy of these treatments. In conclusion, this exploratory, mixed-methodology studentship has highlighted the potentials for multiomics to improve disease research.

Degree

thesis:*
Name dc:type.qualificationname
Doctor of Philosophy
Level dc:type.qualificationlevel
Doctoral Thesis
Grantor dc:publisher.institution
Queen's University Belfast
Year dc:date.issued
2021

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Kerr, Katie
Advisors dc:contributor.advisor
  • McKnight, Amy
  • Smyth, Laura

Subjects

dc:subject × 5

Rights

Language dc:language
eng

Identifiers

dc:identifier.*
Identifier
oai:pure.qub.ac.uk/portal:studenttheses/c20e3eff-4b65-4659-beab-6205bbe5bb2a
OAI identifier oai:identifier
oai:pure.qub.ac.uk/portal:studenttheses/c20e3eff-4b65-4659-beab-6205bbe5bb2a

Chain of custody

source
Harvested from
Queen's University Belfast
Base URL
pureadmin.qub.ac.uk/ws/oai
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Kerr, Katie. Development of a framework for multiomic analysis in disease research. Doctoral Thesis thesis, Queen's University Belfast, 2021. https://pure.qub.ac.uk/en/studentTheses/c20e3eff-4b65-4659-beab-6205bbe5bb2a