Wu Dan-Ni, Fajiculay Erickson, Hsu Chao-Ping, Hu Chun-Mei, Lee Li-Wen, Tzou Der-Lii M
Institute of Biochemical Sciences, National Taiwan University, Taipei, Taiwan.
TIGP, Chemical Biology and Molecular Biophysics Program, Academia Sinica, Taipei, Taiwan.
Int J Obes (Lond). 2025 Apr;49(4):688-697. doi: 10.1038/s41366-024-01695-0. Epub 2024 Dec 10.
Human urine is highly favorable for H NMR metabolomics analyses of obesity-related diseases, such as non-alcoholic fatty liver, type 2 diabetes, and hyperlipidemia (HL), due to its non-invasiveness and ease of large-scale collection. However, the wide range of intrinsic urine pH (5.5-8.5) results in inevitably chemical shift and signal intensity modulations in the H NMR spectra. For patients where acidic urine pH is closely linked to obesity-related disease phenotypes, the pH-dependent modulations complicate the spectral analysis and deteriorate quantifications of urine metabolites.
We characterized human urine metabolites by NMR at intrinsic urine pH, across urine pH 4.5 to 9.5, to account for pH-dependent modulations. A pH-dependent chemical shift database for quantifiable urine metabolites was generated and integrated into a "pH intelligence" program developed for quantifications of pH-dependent modulations at various pH. The H NMR spectra of urines collected from patients with Ob-HL and healthy controls were compared to uncover potential metabolic biomarkers of Ob-HL disease.
Three urine metabolites were unveiled by pH-dependent NMR approach, i.e., TMAO, glycine, and pyruvic acid, with VIP score >1.0 and significant q-value < 0.05, that represent as potential biomarkers for discriminating Ob-HL from healthy controls. Further ROC-AUC analyses revealed that TMAO alone achieved the highest diagnostic accuracy (AUC 0.902), surpassed to that obtained by neutralizing pH approach (AUC 0.549) and enabled better recovering potential urine metabolites from the Ob-HL disease phenotypes.
We concluded that H NMR-derived urine metabolite profile represents a snapshot that can reveal the physiological condition of humans in either a healthy or diseased state under intrinsic urine pH. We demonstrated a systematic analysis of pH-dependent modulations on the human urine metabolite signals and further developed software for quantification of urine metabolite profiles with high accuracy, enabling the uncovering of potential metabolite biomarkers in clinical diagnosis applications.
由于人体尿液具有非侵入性且易于大规模收集的特点，因此非常适合用于对肥胖相关疾病（如非酒精性脂肪肝、2型糖尿病和高脂血症（HL））进行氢核磁共振代谢组学分析。然而，尿液固有pH值范围较宽（5.5 - 8.5），这不可避免地导致氢核磁共振谱中的化学位移和信号强度调制。对于酸性尿液pH值与肥胖相关疾病表型密切相关的患者，pH值依赖性调制会使光谱分析复杂化，并降低尿液代谢物的定量准确性。
我们通过核磁共振对人体尿液代谢物在固有尿液pH值以及pH值从4.5至9.5的范围内进行了表征，以考虑pH值依赖性调制。生成了一个可量化尿液代谢物的pH值依赖性化学位移数据库，并将其整合到一个为在不同pH值下对pH值依赖性调制进行定量而开发的“pH智能”程序中。比较了从肥胖合并高脂血症患者和健康对照者收集的尿液的氢核磁共振谱，以发现肥胖合并高脂血症疾病的潜在代谢生物标志物。
通过pH值依赖性核磁共振方法揭示了三种尿液代谢物，即氧化三甲胺、甘氨酸和丙酮酸，其VIP得分>1.0且显著q值<0.05，它们可作为区分肥胖合并高脂血症与健康对照的潜在生物标志物。进一步的ROC - AUC分析表明，仅氧化三甲胺就达到了最高的诊断准确性（AUC 0.902），超过了通过中和pH值方法获得的准确性（AUC 0.549），并且能够更好地从肥胖合并高脂血症疾病表型中恢复潜在的尿液代谢物。
我们得出结论，氢核磁共振衍生的尿液代谢物谱代表了一个快照，它可以揭示人体在固有尿液pH值下处于健康或患病状态的生理状况。我们展示了对人体尿液代谢物信号的pH值依赖性调制的系统分析，并进一步开发了用于高精度定量尿液代谢物谱的软件，从而能够在临床诊断应用中发现潜在的代谢物生物标志物。
