A Causal Network Analysis of the Fatty Acid Metabolome in African-Americans Reveals a Critical Role for Palmitoleate and Margarate.
A Causal Network Analysis of the Fatty Acid Metabolome in African-Americans Reveals a Critical Role for Palmitoleate and Margarate.
复制标题
非裔美国人脂肪酸代谢组的因果网络分析揭示了棕榈油酸酯和玛咖酸酯的关键作用。
DOI：
10.1089/omi.2016.0071
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发表时间：
2016
期刊：
影响因子：
--
通讯作者：
Boerwinkle,Eric
中科院分区：
文献类型：
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作者：
Yazdani,Azam;Yazdani,Akram;Boerwinkle,Eric
脂肪酸是能量的重要来源，也是许多常见复杂病理学（如心血管疾病、糖尿病和某些形式的癌症）的可能预测因子和病因因素。虽然脂肪酸被认为是相互协变的，但它们潜在的因果网络尚未完全阐明。本研究报告了15种主要长链脂肪酸之间的统计因果网络的识别和分析。在非裔美国人的人口样本，并使用基因组粒度定向无环图（GDAG）算法，我们确定的方向或因果关系的脂肪酸代谢。构建了一个有向因果网络，在15个节点中显示了29个显著边缘（p< 0.001）。我们报告说，两种脂肪酸代谢产物，棕榈油酸酯和十七酸酯，来自饮食摄入，共同影响网络中的每一个其他脂肪酸。另一方面，尽管其高连接性，二高亚油酸酯似乎并没有在整个脂肪酸网络中发挥重要作用。这些研究结果共同表明，新的治疗或预防方法可能具有战略切入点，可以对抗受脂肪酸代谢物影响的疾病，如心血管疾病，糖尿病和肥胖症。随着我们走向新的后基因组诊断和治疗，进一步研究独立人群样本中脂肪酸代谢物网络的嵌入式子结构将是及时和必要的。
Fatty acids are important sources of energy and possible predictors and etiologic factors in many common complex pathologies such as cardiovascular disease, diabetes, and certain forms of cancers. While fatty acids are thought to covary with each other, their underlying causal networks have not been fully elucidated. This study reports the identification and analysis of a statistical causal network among 15 mostly long-chain fatty acids. In an African-American population sample and using the Genome granularity-Directed Acyclic Graph (GDAG) algorithm, we determined directions or causal relationships in the fatty acid metabolome. A directed causal network was constructed that revealed 29 significant edges among the 15 nodes (p< 0.001). We report that two fatty acid metabolites, palmitoleate and margarate, which originate from dietary intake, together influence every other fatty acid in the network. On the other hand, despite its high connectivity, dihomo-linoleate did not appear to play an important role over the whole fatty acid network. These findings collectively suggest possible strategic entry points for new treatments or preventive modalities against diseases affected by fatty acid metabolites such as cardiovascular disease, diabetes, and obesity. Further studies examining the embedded substructure of the fatty acid metabolite networks in independent population samples would be timely and warranted as we move toward novel postgenomic diagnostics and therapeutics.