基于CiteSpace可视化分析代谢组学在中医药领域的研究现状及趋势＊

目的 应用可视化方法分析代谢组学在中医药领域的现状及趋势。方法 检索中国知网数据库（CNKI）和Web of Science 核心合集数据库2021年3月15日之前收录的中医药领域代谢组学研究的相关文献，应用CiteSpace软件对纳入的文献进行关键词、作者、研究机构等内容进行可视化分析。结果 共纳入中文文献247篇，英文文献350篇。文献数量在波动中迅速上升。中、英文文献作者合作网络显示，张爱华是中医药领域代谢组学研究发文量最多的作者，并形成了核心研究团队。发文机构显示，中国医学科学院是该领域的重要研究机构，机构间合作紧密。中、英文文献关键词分析显示，研究内容主要集中在核磁共振、代谢标记物、冠心病、质谱技术、代谢通路等相关领域。结论 中医药领域代谢组学研究的热点主要为中医药治疗代谢性疾病的机制研究。研究趋势为卵泡代谢组学研究及中药有效成分的研究。     

基于代谢组学探讨艾灸关元穴对老年大鼠肾能量代谢的影响＊

目的 通过UHPLC-Q-TOF-MS代谢组学探讨艾灸关元穴对老年大鼠肾代谢物的影响，进而为艾灸关元穴的作用机制提供参考。方法 将8月龄SD雄性大鼠设为成年对照组（8只），21月龄SD雄性大鼠随机分为老年对照组（8只）、老年金匮肾气丸组（7只）、老年艾灸组（8只）。老年金匮肾气丸组每日按体重给药，老年艾灸组每日艾灸关元穴15 min，均每周5天。实验持续13周后检测大鼠肾组织线粒体呼吸耗氧速率、琥珀酸脱氢酶（SDH）活性以及血清肾功能指标，观察肾脏病理变化，结合UHPLC-Q-TOF-MS技术对大鼠的肾组织进行代谢轮廓分析，筛选代谢差异物并进行鉴定。结果 与老年对照组比较，老年艾灸组大鼠肾线粒体的呼吸耗氧速率和SDH酶的活力显著提高（P<0.01）。代谢组学结果显示，肾组织中筛选出13个共同差异化合物，分别是丁酸十二烷基酯、亚油酰胺、5-甲基四氢叶酸、PC（16∶0/22∶5（7Z，10Z，13Z，16Z，19Z））、6，8-二羟基嘌呤、1，2，3-丙烷三羧酸、3-（4-甲氧基苯基）-2-氧代丙酸、吲哚-3-乙酰甘氨酸、亚麻油酸、9，10-环氧十八烷酸、二十二碳五烯酸（22n-6）、牛磺胆酸、LysoPS （18∶0/0∶0）。结论 艾灸关元穴可通过调控老年大鼠的牛磺酸和亚牛磺酸代谢、α-亚麻酸代谢、亚油酸代谢、甘油磷脂代谢来调节肾的能量代谢。     

Erythrocyte sphingolipid species as biomarkers of Alzheimer's disease

Diagnosing Alzheimer's disease (AD) in the early stage is challenging. Informative biomarkers can be of great value for population-based screening. Metabolomics studies have been used to find potential biomarkers, but commonly used tissue sources can be difficult to obtain. The objective of this study was to determine the potential utility of erythrocyte metabolite profiles in screening for AD. Unlike some commonly-used sources such as cerebrospinal fluid and brain tissue, erythrocytes are plentiful and easily accessed. Moreover, erythrocytes are metabolically active, a feature that distinguishes this sample source from other bodily fluids like plasma and urine. In this preliminary pilot study, the erythrocyte metabolomes of 10 histopathologically confirmed AD patients and 10 patients without AD (control (CTRL)) were compared. Whole blood was collected post-mortem and erythrocytes were analyzed using ultra-performance liquid chromatography tandem mass spectrometry. Over 750 metabolites were identified in AD and CTRL erythrocytes. Seven were increased in AD while 24 were decreased (P<0.05). The majority of the metabolites increased in AD were associated with amino acid metabolism and all of the decreased metabolites were associated with lipid metabolism. Prominent among the potential biomarkers were 10 sphingolipid or sphingolipid-related species that were consistently decreased in AD patients. Sphingolipids have been previously implicated in AD and other neurological conditions. Furthermore, previous studies have shown that erythrocyte sphingolipid concentrations vary widely in normal, healthy adults. Together, these observations suggest that certain erythrocyte lipid phenotypes could be markers of risk for development of AD.     

肠道菌群及联用组学技术在中药领域上的研究进展

肠道菌群与各脏器相关联,能够反映中医药整体观特点。肠道菌群在中药作用机制、配伍应用和毒理等领域广泛应用。中药可影响肠道菌群数量和组成,改善肠菌丰度和多样性,同时肠道菌群也可代谢转化中药活性成分,与中药相互影响,促进中药药效发挥。肠道菌群联合代谢组学等多组学技术通过多层次分析,有利于全面阐释肠道菌群与中药作用机制。本文利用数据库综合检索近十年发表的相关文献,阐释肠道菌群和中药之间的相互作用,归纳总结肠道菌群在中药药效、配伍、炮制、毒理领域的研究进展以及与代谢组学等多组学技术联合应用,为深入研究肠道菌群和中药之间的关系及多组学技术在肠道菌群与中药之间的应用提供理论依据和参考。     

基于代谢组学技术的黄芩-白芍对2型糖尿病模型小鼠的作用机制

目的：在肾脏代谢组学技术基础上,探讨黄芩-白芍药对对2型糖尿病（T2DM）的防治机制,并通过寻找内源性潜在生物标志物,寻找其相关代谢通路。方法：非糖尿病健康同窝出生仔畜(db/m小鼠）为空白组,同时选择血糖值高于11.1 mol/L的糖尿病瘦素受体基因缺陷（db/db）小鼠进行分组,分为模型组、黄芩-白芍组（5.625 g/kg）、阳性药组（二甲双胍250 mg/kg）,给药体积为7.5 mL/kg,1次/d,连续8周,并采用超高效液相色谱与串联四级杆飞行时间质谱仪联用技术(UPLC-Q-TOF-MS/MS)法进行小鼠肾脏代谢组学分析,探寻潜在的生物标志物,联合人类代谢组学数据库（HMDB）和京都基因与基因组百科全书数据库（KEGG）找出相关代谢通路。结果：黄芩-白芍组可改善T2DM模型小鼠代谢轨迹的偏离,同时,寻找出与DN模型及给予黄芩汤干预后具有共同差异的生物标志物14个,涉及8条相关代谢通路,应用相关代谢通路分析方法发现,影响最为广泛的代谢通路可能是甘油磷脂代谢、嘌呤代谢和嘧啶代谢。结论：黄芩-白芍药对治疗T2DM的作用机制可能与其通过调节脂质代谢、能量代谢等多条代谢通路,改善内源性代谢物的水平,恢复机体正常代谢活动有关。     

Obesity,metabolic health and omics: Current status and future directions

The growing obesity epidemic is becoming a major public health concern, and the associated costs represent a considerable burden on societies. Among the most common complications of severe obesity are the development of hypertension, dyslipidemia, type 2 diabetes, cardiovascular disease, and various types of cancer. Interestingly, some obese individuals have a favorable metabolic profile and appear to be somehow protected from the detrimental effects of excessive adipose tissue accumulation. These individuals remain normoglycemic, insulin sensitive, and hypotensive with proper blood lipid levels, despite their high body mass index and/or waist circumference. Multiple independent observations have led to the concept of the metabolically healthy obese (MHO) phenotype, yet no consensus has been reached to date regarding a universal definition or the main mechanism behind this phenomenon. Recent technological advances and the use of high-throughput analysis techniques have revolutionized different areas of biomedical research. A multi-omics approach, which is used to investigate changes at different molecular levels in an organism or tissue, may provide valuable insights into the interplay between the molecules or pathways and the roles of different factors involved in the mechanisms underlying metabolic health deterioration. The aim of this review is to present the current status regarding the use of omics technologies to investigate the MHO phenotype, as well as the results of targeted analyses conducted in MHO individuals.     

Diagnosing,discarding, or de-VUSsing: A practical guide to (un)targeted metabolomics as variant-transcending functional tests

PurposeFor patients with inherited metabolic disorders (IMDs), any diagnostic delay should be avoided because early initiation of personalized treatment could prevent irreversible health damage. To improve diagnostic interpretation of genetic data, gene function tests can be valuable assets. For IMDs, variant-transcending functional tests are readily available through (un)targeted metabolomics assays. To support the application of metabolomics for this purpose, we developed a gene-based guide to select functional tests to either confirm or exclude an IMD diagnosis.MethodsUsing information from a diagnostic IMD exome panel, Kyoto Encyclopedia of Genes and Genomes, and Inborn Errors of Metabolism Knowledgebase, we compiled a guide for metabolomics-based gene function tests. From our practical experience with this guide, we retrospectively selected illustrative cases for whom combined metabolomic/genomic testing improved diagnostic success and evaluated the effect hereof on clinical management.ResultsThe guide contains 2047 metabolism-associated genes for which a validated or putative variant-transcending gene function test is available. We present 16 patients for whom metabolomic testing either confirmed or ruled out the presence of a second pathogenic variant, validated or ruled out pathogenicity of variants of uncertain significance, or identified a diagnosis initially missed by genetic analysis.ConclusionMetabolomics-based gene function tests provide additional value in the diagnostic trajectory of patients with suspected IMD by enhancing and accelerating diagnostic success.     

Application of metabolomics in establishing primary nephrotic syndrome diagnosis model

Objective To establish diagnosis model and explore related metabolic pathways by analyzing the serum metabolic profile of patients with primary nephrotic syndrome (PNS) through metabolomics. Methods Thirty PNS patients hospitalized in Huai'an First People's Hospital between December 2010 and April 2012 were enrolled. High performance liquid chromatography-mass spectrometry (LC-MS) was employed to detect metabolites in the serum of 30 PNS patients and 30 healthy controls. Metabolic fingerprint profiling and multivariate pattern recognition analysis were combined to establish disease-specific metabolic diagnosis model, and metabolic pathway analysis was performed. Results PNS group and control group could be well separated by principal component analysis (PCA) model as well as partial least-squares discriminant analysis (PLS-DA) model with Q2 of 0.300. There was well interpretation in PLA-DA model (R2X=0.581，R2Y=0.452). Compared with healthy controls，PNS patients had decreased cholestane 3, 7, 12, 15 alcohol, acyl glycerine, phytosphingosine and tryptophan, and increased sphingomyelin, arginine and glutamic acid (all VIP＞1, P＜0.05). The metabolic disorders pathways of PNS patients included sphingolipid metabolism, arginine and proline metabolism, linoleic acid metabolism and pyrimidine metabolism (all impact＞0.10 and P＜0.05). Conclusions Metabolomics combined with multivariate pattern recognition analysis may be a new tool for diagnosis and monitoring of PNS.