The phenotype-genotype relationship is a key for personalized and precision medicine for complex diseases. To unravel the complexity of the clinical phenotype-genotype network, we used cardiovascular diseases (CVDs) and associated non-coding RNAs (ncRNAs) (i.e. miRNAs, long ncRNAs, etc.) as the case for the study of CVDs at a systems or network level. We first integrated a database of CVDs and ncRNAs (CVDncR, http://sysbio.org.cn/cvdncr/) to construct CVD-ncRNA networks and annotate their clinical associations. To characterize the networks, we then separated the miRNAs into two groups, i.e. universal miRNAs associated with at least two types of CVDs and specific miRNAs related only to one type of CVD. Our analyses indicated two interesting patterns in these CVD-ncRNA networks. First, scale-free features were present within both CVD-miRNA and CVD-lncRNA networks; second, universal miRNAs were more likely to be CVDs biomarkers. These results were confirmed by computational functional analyses. The findings offer theoretical guidance for decoding CVD-ncRNA associations and will facilitate the screening of CVD ncRNA biomarkers. Database URL: http://sysbio.org.cn/cvdncr/.

中文翻译：

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表型-基因型网络的构建和表征：心血管疾病和相关非编码RNA的案例研究。

表型与基因型的关系是复杂疾病个性化和精准医学的关键。为了阐明临床表型-基因型网络的复杂性，我们使用心血管疾病（CVD）和相关的非编码RNA（ncRNA）（即miRNA，长ncRNA等）作为在系统或系统上研究CVD的案例。网络级别。我们首先整合了CVD和ncRNA的数据库（CVDncR，http：//sysbio.org.cn/cvdncr/），以构建CVD-ncRNA网络并注释其临床关联。为了表征网络，我们将miRNA分为两组，即与至少两种类型的CVD相关的通用miRNA和仅与一种类型的CVD相关的特定miRNA。我们的分析表明在这些CVD-ncRNA网络中有两种有趣的模式。第一，CVD-miRNA和CVD-IncRNA网络中均存在无鳞特征。第二，通用miRNA更有可能是CVD的生物标志物。这些结果通过计算功能分析得到了证实。这些发现为解码CVD-ncRNA关联提供了理论指导，并将有助于CVD ncRNA生物标志物的筛选。数据库URL：http：//sysbio.org.cn/cvdncr/。