The metabolome, although very dynamic, is sufficiently stable to provide specific quantitative traits related to health and disease. Metabolomics requires balanced use of state-of-the-art study design, chemical analytics, biostatistics, and bioinformatics to deliver meaningful answers to contemporary questions in human disease research. The technology is now frequently employed for biomarker discovery and for elucidating the mechanisms underlying endocrine-related diseases. Metabolomics has also enriched genome-wide association studies (GWAS) in this area by providing functional data. The contributions of rare genetic variants to metabolome variance and to the human phenotype have been underestimated until now.

中文翻译：

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内分泌学遇到代谢组学：成就、陷阱和挑战

代谢组虽然非常动态，但足够稳定以提供与健康和疾病相关的特定数量特征。代谢组学需要平衡使用最先进的研究设计、化学分析、生物统计学和生物信息学，为人类疾病研究中的当代问题提供有意义的答案。该技术现在经常用于生物标志物的发现和阐明内分泌相关疾病的机制。代谢组学还通过提供功能数据丰富了该领域的全基因组关联研究 (GWAS)。迄今为止，罕见的遗传变异对代谢组变异和人类表型的贡献一直被低估。