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多平台血清代谢表型分析结合通路图谱以识别吸烟者的生化差异。

Multiplatform serum metabolic phenotyping combined with pathway mapping to identify biochemical differences in smokers.

作者信息

Kaluarachchi Manuja R, Boulangé Claire L, Garcia-Perez Isabel, Lindon John C, Minet Emmanuel F

机构信息

Metabometrix Ltd, Bioincubator, Prince Consort Road, South Kensington, London, SW7 2BP, UK.

British American Tobacco, Research & Development, Regents Park Road, Southampton, SO15 8TL, UK.

出版信息

Bioanalysis. 2016 Oct;8(19):2023-43. doi: 10.4155/bio-2016-0108. Epub 2016 Sep 16.

Abstract

AIM

Determining perturbed biochemical functions associated with tobacco smoking should be helpful for establishing causal relationships between exposure and adverse events.

RESULTS

A multiplatform comparison of serum of smokers (n = 55) and never-smokers (n = 57) using nuclear magnetic resonance spectroscopy, UPLC-MS and statistical modeling revealed clustering of the classes, distinguished by metabolic biomarkers. The identified metabolites were subjected to metabolic pathway enrichment, modeling adverse biological events using available databases. Perturbation of metabolites involved in chronic obstructive pulmonary disease, cardiovascular diseases and cancer were identified and discussed.

CONCLUSION

Combining multiplatform metabolic phenotyping with knowledge-based mapping gives mechanistic insights into disease development, which can be applied to next-generation tobacco and nicotine products for comparative risk assessment.

摘要

目的

确定与吸烟相关的生物化学功能紊乱,应有助于建立暴露与不良事件之间的因果关系。

结果

使用核磁共振波谱、超高效液相色谱-质谱联用技术和统计建模,对吸烟者(n = 55)和从不吸烟者(n = 57)的血清进行多平台比较,结果显示,这些类别通过代谢生物标志物得以区分并聚类。将鉴定出的代谢物进行代谢途径富集分析,利用现有数据库对不良生物事件进行建模。确定并讨论了参与慢性阻塞性肺疾病、心血管疾病和癌症的代谢物的紊乱情况。

结论

将多平台代谢表型分析与基于知识的图谱相结合,可为疾病发展提供机制性见解,这可应用于下一代烟草和尼古丁产品的比较风险评估。

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