Cardiovascular Epigenomics

Our recent research has provided the first evidence from randomised trials that riboflavin, a key B-vitamin, modulates DNA methylation of hypertension-related genes in adults with the MTHFR 677TT genotype. MTHFR, through its role in one carbon metabolism, supplies methyl groups for DNA methylation which controls gene expression. Riboflavin is a co-factor for MTHFR, and this gene-nutrient interaction has previously been shown by collaborators in NICHE to play an important role in hypertension. Ongoing collaborative work with NICHE is providing novel insights into personalised hypertension management and treatment.

Regenerative approaches have been used to successfully create patient-specific induced pluripotent stem cell (iPSC) models in collaboration with University of Galway, with CRISPR-Cas9 gene-editing employed to generate MTHFR 677 isogenic iPSC lines to investigate epigenomic differences, a crucial step in decoding the biological significance of this genetic variant in hypertension pharmacogenomics.

We are currently combining different types of genetic and biological data derived from patients with hypertension to better understand the disease and identify potential drug targets against the disease. This will be achieved using bioinformatics analysis techniques such as Mendelian randomization and artificial intelligence methods.

Hypertension (high blood pressure) effects one in three adults and is the number one cause of stroke in Northern Ireland. Treatment-resistant hypertension (TRH) relates to hypertensive patients taking three or more antihypertensive medications. Around 10% of hypertensive patients are deemed to have TRH. Patients with TRH are at a higher risk of a range of diseases such as heart failure, cardiac death and all-cause death. Importantly, the causes of TRH and its progression to cardiovascular events and death are poorly understood.

Different types of genetic and biological data can be derived from patients to better understand a particular disease. Combining these different patient data types is advantageous as the data types are complementary to each other and thus allow for a better and more holistic analysis when compared to analysing the data types in isolation. For example, combining genetic and blood protein data from patients can determine if there are proteins associated with the cause or consequence of a particular disease. Combining genetic and blood protein data can also identify proteins which could be targeted by drugs to combat against a disease. This research is in collaboration with the Nutrition Innovation Centre for Food and Health (NICHE) group at Ulster University.

Our current research interests are associated with understanding the interplay between genomics, epigenomics and the environment on healthy development, healthy ageing and in complex/chronic disease manifestation. The overarching aim is to provide scientific substantiation for new healthcare strategies to promote healthy aging and disease prevention.

Harnessing large-scale research efforts from published genome-wide association studies, epigenome-wide association studies, and valuable resources such as the UK Biobank, our research team use bioinformatic approaches to meta-analyse data with that from interdisciplinary projects at Ulster University.  We also work closely with a network of multinational collaborators to analyse data from  powerful randomised control trials, studies of vitamin intake in pregnancy, obesity, exercise, DNA damage and bariatric surgery.

In addition to large -omics approaches, the research team are interested in gene-editing, and using molecular biology-based approaches to further investigate mechanistic processes in cell models and tissues.