MRC Integrative Epidemiology Unit, Bristol Medical School (Population Health Sciences), University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.
National Institute for Health Research Biomedical Research Centre, Bristol, UK.
Genome Med. 2019 Jan 31;11(1):6. doi: 10.1186/s13073-019-0613-2.
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 analysis pipeline that integrates tissue-specific gene expression, Mendelian randomization and multiple-trait colocalization to develop functional mechanistic insight into the causal pathway from a genetic variant to a complex trait.
We undertook an expression quantitative trait loci-wide association study to uncover genetic variants associated with both nearby gene expression and cardiovascular traits. Fine-mapping was performed to prioritize possible causal variants for detected associations. Two-sample Mendelian randomization (MR) was then applied using findings from genome-wide association studies (GWAS) to investigate whether changes in gene expression within certain tissue types may influence cardiovascular trait variation. We subsequently used Bayesian multiple-trait colocalization to further interrogate the findings and also gain insight into whether DNA methylation, as well as gene expression, may play a role in disease susceptibility. Finally, we applied our analysis pipeline genome-wide using summary statistics from large-scale GWAS.
Eight genetic loci were associated with changes in gene expression and measures of cardiovascular function. Our MR 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 affect cardiovascular trait variation along with gene expression. Furthermore, colocalization analyses uncovered evidence of tissue specificity between gene expression in liver tissue and cholesterol levels. Applying our pipeline genome-wide using summary statistics from GWAS uncovered 233 association signals at loci which represent promising candidates for further evaluation.
Disease susceptibility can be influenced by differential changes in tissue-specific gene expression and DNA methylation. The approach undertaken in our study can be used to elucidate 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.
基因表达的变化在多大程度上可以影响不同组织类型的心血管疾病风险，尚未得到系统的探索。我们开发了一种分析管道，该管道集成了组织特异性基因表达、孟德尔随机化和多性状共定位，以深入了解从遗传变异到复杂性状的因果途径的功能机制。
我们进行了表达数量性状基因座全基因组关联研究，以发现与附近基因表达和心血管特征都相关的遗传变异。精细映射用于优先考虑检测到的关联的可能因果变异。然后使用全基因组关联研究（GWAS）的结果进行两样本孟德尔随机化（MR），以研究特定组织类型中基因表达的变化是否可能影响心血管性状的变异。我们随后使用贝叶斯多性状共定位进一步探究这些发现，并深入了解 DNA 甲基化以及基因表达是否可能在疾病易感性中发挥作用。最后，我们使用来自大规模 GWAS 的汇总统计数据在全基因组范围内应用我们的分析管道。
有 8 个遗传位点与基因表达和心血管功能测量值的变化相关。我们的 MR 分析提供了多个位点存在组织特异性效应的证据，其中 ADCY3 和 FADS1 位点分别对体重指数和胆固醇的影响特别有启发性。多性状共定位发现，FADS1/TMEM258 启动子区域的 DNA 甲基化变化也可能影响心血管性状的变异以及基因表达。此外，共定位分析发现肝脏组织中的基因表达与胆固醇水平之间存在组织特异性。使用 GWAS 的汇总统计数据在全基因组范围内应用我们的管道发现，在代表进一步评估的有希望的候选基因的 233 个位点存在关联信号。
疾病易感性可以受到组织特异性基因表达和 DNA 甲基化变化的影响。我们研究中采用的方法可以用于阐明疾病机制，并有助于优先考虑相关位点中可能存在多个附近基因共调控的假定因果基因。继续在各种组织和细胞类型中发现分子性状的数量性状基因座的未来研究将进一步提高我们理解和预防疾病的能力。
