BACKGROUND Urinary metabolomics has demonstrated considerable potential to assess kidney function and its metabolic corollaries in health and disease. However, applications in epidemiology remain sparse due to technical challenges. METHODS We added 17 metabolites to an open-access urinary nuclear magnetic resonance metabolomics platform, extending the panel to 61 metabolites (n = 994). We also introduced automated quantification for 11 metabolites, extending the panel to 12 metabolites (+creatinine). Epidemiological associations between these 12 metabolites and 49 clinical measures were studied in three independent cohorts (up to 5989 participants). Detailed regression analyses with various confounding factors are presented for body mass index (BMI) and smoking. RESULTS Sex-specific population reference concentrations and distributions are provided for 61 urinary metabolites (419 men and 575 women), together with methodological intra-assay metabolite variations as well as the biological intra-individual and epidemiological population variations. For the 12 metabolites, 362 associations were found. These are mostly novel and reflect potential molecular proxies to estimate kidney function, as the associations cannot be simply explained by estimated glomerular filtration rate. Unspecific renal excretion results in leakage of amino acids (and glucose) to urine in all individuals. Seven urinary metabolites associated with smoking, providing questionnaire-independent proxy measures of smoking status in epidemiological studies. Common confounders did not affect metabolite associations with smoking, but insulin had a clear effect on most associations with BMI, including strong effects on 2-hydroxyisobutyrate, valine, alanine, trigonelline and hippurate. CONCLUSIONS Urinary metabolomics provides new insight on kidney function and related biomarkers on the renal-cardiometabolic system, supporting large-scale applications in epidemiology.

中文翻译：

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尿液代谢物的临床和生化关联：肾-心脏代谢生物标志物的定量流行病学方法。

背景尿代谢组学已显示出评估肾功能及其在健康和疾病中的代谢推论的巨大潜力。然而，由于技术挑战，流行病学中的应用仍然很少。方法 我们将 17 种代谢物添加到开放式尿核磁共振代谢组学平台中，将代谢物组扩展到 61 种（n = 994）。我们还引入了 11 种代谢物的自动定量，将面板扩展到 12 种代谢物（+肌酐）。在三个独立队列（最多 5989 名参与者）中研究了这 12 种代谢物和 49 种临床指标之间的流行病学关联。对体重指数（BMI）和吸烟情况进行了各种混杂因素的详细回归分析。结果 提供了 61 种尿液代谢物（419 名男性和 575 名女性）的性别特异性人群参考浓度和分布，以及方法学内测定代谢物变化以及个体内生物学和流行病学人群变化。对于 12 种代谢物，发现了 362 种关联。这些大多是新颖的，反映了估计肾功能的潜在分子代理，因为这些关联不能简单地通过估计的肾小球滤过率来解释。非特异性肾脏排泄会导致所有个体的氨基酸（和葡萄糖）渗漏到尿液中。七种与吸烟相关的尿液代谢物，为流行病学研究中的吸烟状况提供了独立于问卷调查的替代指标。常见的混杂因素不会影响代谢物与吸烟的关联，但胰岛素对大多数与 BMI 的关联有明显影响，包括对 2-羟基异丁酸、缬氨酸、丙氨酸、葫芦巴碱和马尿酸的强烈影响。结论 尿液代谢组学为肾功能和肾-心脏代谢系统相关生物标志物提供了新的见解，支持在流行病学中的大规模应用。