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Prioritizing putative influential genes in early life cardiovascular disease susceptibility by applying tissue-specific Mendelian randomization

By Kurt Taylor, George Davey Smith, Caroline L. Relton, Tom Gaunt, Tom G Richardson

Posted 11 Apr 2018
bioRxiv DOI: 10.1101/298687 (published DOI: 10.1186/s13073-019-0613-2)

Background: The extent to which changes in gene expression can influence cardiovascular disease risk across different tissue types has not yet been systematically explored. We have developed an analytical framework that integrates tissue-specific gene expression, Mendelian randomization and multiple-trait colocalization to develop functional mechanistic insight into the causal pathway from genetic variant to complex trait. Methods: We undertook a transcriptome-wide association study in a population of young individuals to uncover genetic variants associated with both nearby gene expression and cardiovascular traits. Two-sample Mendelian randomization was then applied using large-scale datasets to investigate whether changes in gene expression within certain tissue types may influence cardiovascular trait variation. We subsequently performed Bayesian multiple-trait colocalization to further interrogate findings and also gain insight into whether DNA methylation, as well as gene expression, may play a role in disease susceptibility. Results: Eight genetic loci were associated with changes in gene expression and early life measures of cardiovascular function. Our Mendelian randomization analysis provided evidence of tissue-specific effects at multiple loci, of which the effects at the ADCY3 and FADS1 loci for body mass index and cholesterol respectively were particularly insightful. Multiple trait colocalization uncovered evidence which suggested that changes in DNA methylation at the promoter region upstream of FADS1/TMEM258 may also play a role in cardiovascular trait variation along with gene expression. Furthermore, colocalization analyses were able to uncover evidence of tissue-specificity, most prominantly between SORT1 expression in liver tissue and cholesterol levels. Conclusions: Disease susceptibility can be influenced by differential changes in tissue-specific gene expression and DNA methylation. Our analytical framework should prove valuable in elucidating mechanisms in disease, as well as helping prioritize putative causal genes at associated loci where multiple nearby genes may be co-regulated. Future studies which continue to uncover quantitative trait loci for molecular traits across various tissue and cell types will further improve our capability to understand and prevent disease.

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