Guo Lining, Milburn Michael V, Ryals John A, Lonergan Shaun C, Mitchell Matthew W, Wulff Jacob E, Alexander Danny C, Evans Anne M, Bridgewater Brandi, Miller Luke, Gonzalez-Garay Manuel L, Caskey C Thomas
Metabolon, Inc., Durham, NC 27713;
Center for Molecular Imaging, Division of Genomics and Bioinformatics, The Brown Foundation Institute of Molecular Medicine, University of Texas Health Science Center, Houston, TX 77030;
Proc Natl Acad Sci U S A. 2015 Sep 1;112(35):E4901-10. doi: 10.1073/pnas.1508425112. Epub 2015 Aug 17.
Precision medicine, taking account of human individuality in genes, environment, and lifestyle for early disease diagnosis and individualized therapy, has shown great promise to transform medical care. Nontargeted metabolomics, with the ability to detect broad classes of biochemicals, can provide a comprehensive functional phenotype integrating clinical phenotypes with genetic and nongenetic factors. To test the application of metabolomics in individual diagnosis, we conducted a metabolomics analysis on plasma samples collected from 80 volunteers of normal health with complete medical records and three-generation pedigrees. Using a broad-spectrum metabolomics platform consisting of liquid chromatography and GC coupled with MS, we profiled nearly 600 metabolites covering 72 biochemical pathways in all major branches of biosynthesis, catabolism, gut microbiome activities, and xenobiotics. Statistical analysis revealed a considerable range of variation and potential metabolic abnormalities across the individuals in this cohort. Examination of the convergence of metabolomics profiles with whole-exon sequences (WESs) provided an effective approach to assess and interpret clinical significance of genetic mutations, as shown in a number of cases, including fructose intolerance, xanthinuria, and carnitine deficiency. Metabolic abnormalities consistent with early indications of diabetes, liver dysfunction, and disruption of gut microbiome homeostasis were identified in several volunteers. Additionally, diverse metabolic responses to medications among the volunteers may assist to identify therapeutic effects and sensitivity to toxicity. The results of this study demonstrate that metabolomics could be an effective approach to complement next generation sequencing (NGS) for disease risk analysis, disease monitoring, and drug management in our goal toward precision care.
精准医学通过考虑基因、环境和生活方式等人类个体因素来进行疾病早期诊断和个体化治疗,已展现出变革医疗保健的巨大潜力。非靶向代谢组学能够检测各类生化物质,可提供一种将临床表型与遗传和非遗传因素整合在一起的综合功能表型。为测试代谢组学在个体诊断中的应用,我们对80名身体健康、拥有完整病历和三代家系谱的志愿者采集的血浆样本进行了代谢组学分析。使用由液相色谱和气相色谱与质谱联用组成的广谱代谢组学平台,我们对近600种代谢物进行了分析,这些代谢物涵盖了生物合成、分解代谢、肠道微生物群活动和外源性物质等所有主要分支中的72条生化途径。统计分析揭示了该队列中个体间存在相当大的变异范围和潜在的代谢异常。对代谢组学图谱与全外显子序列(WES)的趋同性检查提供了一种评估和解释基因突变临床意义的有效方法,如在一些病例中所示,包括果糖不耐受、黄嘌呤尿症和肉碱缺乏症。在几名志愿者中发现了与糖尿病、肝功能障碍和肠道微生物群稳态破坏的早期迹象一致的代谢异常。此外,志愿者对药物的不同代谢反应可能有助于确定治疗效果和对毒性的敏感性。本研究结果表明,代谢组学可能是一种有效的方法,可在我们实现精准医疗的目标中,补充下一代测序(NGS)用于疾病风险分析、疾病监测和药物管理。