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Title: A mesenchymal stem cell-based approach for investigating cardiovascular disease-related genetic variants
Author: Rai, Sukhvir Kaur
ISNI:       0000 0004 5919 5228
Awarding Body: University of Leicester
Current Institution: University of Leicester
Date of Award: 2016
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Genome wide-association studies (GWASs) have identified many loci that contribute to coronary artery disease (CAD). A huge challenge of the post-GWAS era is identifying the biological pathways risk variants act through to contribute to disease. I explored the use of MSCs as a model to investigate the effects of CAD-related variants in vitro. To establish a MSC bank, cells were isolated from 114 umbilical cords and subsequently characterised. MSCs met the ISCT criteria; they adhered to plastic, expressed a characteristic cell surface profile and differentiated into three common lineages. As a proof of principle study, a BMI-associated variant was investigated. Speliotes et al., (2010) showed rs3810291 was an eQTL for ZC3H4 in adipose tissue. However, MSC-derived adipocytes did not recapitulate the effect of this variant. Analysis of another known eQTL (rs10840106) in adipose tissue was significantly associated with TRIM66 gene expression in MSCs and differentiated adipocytes. It is hypothesised CAD risk variants act in CAD-relevant cell types to exert their effects, so MSCs were differentiated towards a SMC lineage. A second proof of concept study focussed on a CAD-associated variant reported to be functional in SMCs. Pu et al., (2013) showed rs3825807 affected vascular SMC migration, ADAMTS7 maturation and COMP cleavage. I did not see a genotype effect of rs3825807 on ADAMTS7 prodomain cleavage or migration of differentiated SMCs. These findings suggest that MSCs may be robust enough to detect the association of variants on important genetic effects such as mRNA levels. However using MSCs to understand the effects of CAD-associated variants is still a difficult process. It is hindered by technical challenges such as MSC heterogeneity, variation in MSC differentiation and underpowered sample sizes. These barriers need to be overcome in order to successfully use MSCs to model disease.
Supervisor: Lodwick, David ; Samani, Nilesh Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available