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首页> 外文期刊>OMICS: A journal of integrative biology >Development of Biomarkers Based on Diet-Dependent Metabolic Serotypes: Concerns and Approaches for Cohort and Gender Issues in Serum Metabolome Studies
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Development of Biomarkers Based on Diet-Dependent Metabolic Serotypes: Concerns and Approaches for Cohort and Gender Issues in Serum Metabolome Studies

机译:基于饮食依赖性代谢血清型的生物标志物的开发:血清代谢组学研究中队列和性别问题的关注和方法

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Mathematical models that reflect the effects of dietary restriction (DR) on the sera metabolome may have utility in understanding the mechanisms of DR and in applying this knowledge to human epidemiological studies. Previous studies demonstrated both the feasibility of identifying biomarkers through metabolome analysis and the validity of our approach in independent cohorts of 6-month-old male and female ad libitum fed or DR rats. Cross-cohort studies showed that cohort-specific effects distorted the dataset. The present study extends these observations across the entire sample set, thereby validating our markers independently of specific cohorts. Metabolites originally identified in males were examined in females and vice-versa. DR's effect on the metabolome is partially gender-specific and is modulated by environmental factors. DR reduces inter-gender differences in the metabolome. Univariate statistical methods showed that 56/93 metabolites in the female samples and 39/93 metabolites in the male samples were significantly altered (using our previous cut-off criteria of p ≤0.2) by DR. The metabolites modulated by DR present a wide spectrum of concentration, redox reactivity and hydrophilicity, suggesting that our serotype is broadly representative of the metabolome and that DR has broad effects on the metabolome. These studies, coupled with those in the preceding and following reports, also highlight the utility for consideration of the metabolome as a network of metabolites using appropriate data analysis approaches. The inter-cohort and inter-gender differences addressed herein suggest potential cautions, and potential approaches, for identification of multivariate biomarker profiles that reflect changes in physiological status, such as a metabolism that predisposes to increased risk of neoplasia.
机译:反映饮食限制(DR)对血清代谢组的影响的数学模型可能对理解DR的机制以及将此知识应用于人类流行病学研究具有实用性。先前的研究证明了通过代谢组分析鉴定生物标志物的可行性以及我们的方法在6个月大的雄性和雌性随意喂养或DR大鼠的独立队列中的有效性。跨队列研究表明,特定于队列的效应使数据集失真。本研究将这些观察结果扩展到整个样本集,从而独立于特定队列验证了我们的标记。最初在男性中鉴定出的代谢产物在女性中进行了检查,反之亦然。 DR对代谢组的影响部分是性别特异性的,并受环境因素调节。 DR可减少代谢组中的性别差异。单变量统计方法表明,DR对雌性样品中的56/93代谢物和雄性样品中的39/93代谢物有显着改变(使用我们之前的临界值p≤0.2)。 DR调节的代谢物具有广泛的浓度,氧化还原反应性和亲水性,这表明我们的血清型是代谢组的广泛代表,DR对代谢组有广泛的影响。这些研究,加上之前和之后的报告,也突出了使用适当的数据分析方法将代谢组作为代谢物网络的实用性。本文所述的人群之间和性别之间的差异提示了潜在的注意事项和潜在的方法,用于鉴定反映生理状态变化的多元生物标志物谱,例如易患肿瘤形成风险的新陈代谢。

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