Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, United States of America.
Department of Oncologic Sciences, Morsani College of Medicine, University of South Florida, Tampa, FL, United States of America.
PLoS One. 2023 Jun 8;18(6):e0286205. doi: 10.1371/journal.pone.0286205. eCollection 2023.
The objective of this research focuses on the development of a statistical methodology able to answer the question of whether variation in the intake of sulfur amino acids (SAA) affects the metabolic process. Traditional approaches, which evaluate specific biomarkers after a series of preprocessing procedures, have been criticized as not being fully informative, as well as inappropriate for translation of methodology. Rather than focusing on particular biomarkers, our proposed methodology involves the multifractal analysis that measures the inhomogeneity of regularity of the proton nuclear magnetic resonance (1H-NMR) spectrum by wavelet-based multifractal spectrum. With two different statistical models (Model-I and Model-II), three different geometric features of the multifractal spectrum of each 1H-NMR spectrum (spectral mode, left slope, and broadness) are employed to evaluate the effect of SAA and discriminate 1H-NMR spectra associated with different treatments. The investigated effects of SAA include group effect (high and low doses of SAA), depletion/repletion effect, and time over data effect. The 1H-NMR spectra analysis outcomes show that group effect is significant for both models. The hourly variation in time and depletion/repletion effects does not show noticeable differences for the three features in Model-I. However, these two effects are significant for the spectral mode feature in Model-II. The 1H-NMR spectra of the SAA low groups exhibit highly regular patterns with more variability than that of the SAA high groups for both models. Moreover, the discriminatory analysis conducted using the support vector machine and the principal components analysis shows that the 1H-NMR spectra of SAA high and low groups can be easily discriminatory for both models, while the spectra of depletion and repletion within these groups are discriminatory for Model-I and Model-II. Therefore, the study outcomes imply that the amount of SAA is important and that SAA intake affects mostly the hourly variation of the metabolic process and the difference between depletion and repletion each day. In conclusion, the proposed multifractal analysis of 1H-NMR spectra provides a novel tool to investigate metabolic processes.
本研究的目的是开发一种统计方法，以回答摄入硫氨基酸 (SAA) 的变化是否会影响代谢过程的问题。传统方法在一系列预处理程序后评估特定的生物标志物，已被批评为信息不完整，并且不适合方法的转化。我们提出的方法不是关注特定的生物标志物，而是涉及多重分形分析，该分析通过基于小波的多重分形谱来测量质子磁共振（1H-NMR）谱的不规则性的非均匀性。使用两种不同的统计模型（模型 I 和模型 II），对每个 1H-NMR 谱的多重分形谱的三个不同的几何特征（谱型、左斜率和宽度）进行分析，以评估 SAA 的影响并区分不同处理方式下的 1H-NMR 谱。研究的 SAA 影响包括组效应（SAA 的高剂量和低剂量）、耗竭/补充效应和数据时间效应。1H-NMR 谱分析结果表明，两种模型的组效应均显著。对于模型 I 的三个特征，时间的小时变化和耗竭/补充效应没有明显的差异。然而，这两种效应在模型 II 的谱型特征中是显著的。对于两种模型，SAA 低剂量组的 1H-NMR 谱显示出高度规则的模式，比 SAA 高剂量组的变异性更大。此外，使用支持向量机和主成分分析进行的判别分析表明，两种模型都可以轻松区分 SAA 高和低组的 1H-NMR 谱，而这些组内的耗竭和补充谱则在模型 I 和模型 II 中具有区分性。因此，研究结果表明 SAA 的量很重要，SAA 的摄入主要影响代谢过程的小时变化以及每天的耗竭和补充之间的差异。总之，提出的 1H-NMR 谱多重分形分析为研究代谢过程提供了一种新工具。
