1D-1H-nuclear magnetic resonance metabolomics reveals age-related changes in metabolites associated with experimental venous thrombosis

代谢物 代谢组学 血栓 方差分析 血栓形成 内科学 医学 静脉血栓形成 生物 生物信息学
作者
Andrea Obi,Kathleen A. Stringer,José A. Díaz,Michael A. Finkel,Diana Farris,Larisa Yeomans,Thomas W. Wakefield,Daniel D. Myers
出处
期刊:Journal of vascular surgery. Venous and lymphatic disorders [Elsevier BV]
卷期号:4 (2): 221-230 被引量:19
标识
DOI:10.1016/j.jvsv.2015.09.010
摘要

Objective

Age is a significant risk factor for the development of venous thrombosis (VT), but the mechanism(s) that underlie this risk remain(s) undefined and poorly understood. Aging is known to adversely influence inflammation and affect metabolism. Untargeted metabolomics permits an agnostic assessment of the physiological landscape and lends insight into the mechanistic underpinnings of clinical phenotypes. The objective of this exploratory study was to test the feasibility of a metabolomics approach for identifying potential metabolic mechanisms of age-related VT.

Methods

We subjected whole blood samples collected from young and old nonthrombosed controls and VT mice 2 days after thrombus induction using the electrolytic inferior vena cava, to a methanol:chloroform extraction and assayed the resulting aqueous fractions using 1D-1H- nuclear magnetic resonance. Normalized mouse metabolite data were compared across groups using analysis of variance (ANOVA) with Holm-Sidak post-testing. In addition, associations between metabolite concentrations and parameters of thrombosis such as thrombus and vein wall weights, and markers of inflammation, vein wall P- and E-selectin levels, were assessed using linear regression. The relatedness of the found significant metabolites was visually assessed using a bioinformatics tool, Metscape, which generates compound-reaction-enzyme-gene networks to aid in the interpretation of metabolomics data.

Results

Old mice with VT had a greater mean vein wall weight compared with young mice with VT (P < .05). Clot weight differences between old and young mice followed the same trend as vein wall weight (0.011 ± 0.04 g vs 0.008 ± 0.003 g; P = not significant). Glutamine (ANOVA, P < .01), proline (ANOVA, P < .01), and phenylalanine (ANOVA, P < .05) levels were increased in old VT mice compared with age-matched controls and young VT mice. Betaine and/or trimethylamine N-oxide levels were increased in aged mice compared with young animals. Vein wall weight was strongly associated with glutamine (P < .05), and phenylalanine (P < .01) concentrations and there was a trend toward an association with proline (P = .09) concentration. Vein wall P-selectin, but not E-selectin levels, were increased in old VT mice and were associated with the three found metabolites of age-related VT. Collectively, with the addition of glutamate, these metabolites form a single compound-reaction-enzyme-gene network that was generated by Metscape.

Conclusions

We used 1D-1H-nuclear magnetic resonance-metabolite profiling to identify, for the first time, in an experimental model, three potential metabolites, glutamine, phenylalanine, and proline, associated with age-related VT. These metabolites are metabolically related and their levels are associated with vein wall weight and P-selectin concentrations. In aggregate, these findings provide a "roadmap" of pathways that could be interrogated in future studies, which could include provocation of the glutamine, phenylalanine, and proline pathways in the vein wall. This study introduces metabolomics as a new approach to furthering knowledge about the mechanisms of age-related VT.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
sheri1发布了新的文献求助10
刚刚
lwl666完成签到,获得积分10
刚刚
1秒前
阳阳语晗完成签到,获得积分10
1秒前
wangzheng完成签到,获得积分10
2秒前
优pp发布了新的文献求助30
2秒前
rrr完成签到,获得积分20
2秒前
Owen应助zyf采纳,获得10
2秒前
儒雅晓霜完成签到,获得积分10
2秒前
思源应助木婉清采纳,获得10
3秒前
SciGPT应助啦11采纳,获得10
4秒前
4秒前
4秒前
5秒前
科研通AI6.1应助cc采纳,获得50
5秒前
称心热狗完成签到,获得积分10
5秒前
6秒前
6秒前
Ray完成签到,获得积分20
7秒前
研友_VZG7GZ应助哈哈哈采纳,获得10
7秒前
NexusExplorer应助YMing采纳,获得10
7秒前
慕青应助星星点灯采纳,获得10
8秒前
Lucas应助科研通管家采纳,获得10
8秒前
小马甲应助科研通管家采纳,获得10
8秒前
叶叶叶完成签到,获得积分10
8秒前
8秒前
侯人雄应助科研通管家采纳,获得10
8秒前
nn应助科研通管家采纳,获得10
8秒前
所所应助科研通管家采纳,获得10
8秒前
8秒前
Ava应助科研通管家采纳,获得10
8秒前
大个应助科研通管家采纳,获得10
8秒前
乐乐应助科研通管家采纳,获得10
8秒前
荼荼发布了新的文献求助10
8秒前
Ing应助科研通管家采纳,获得10
9秒前
英俊的铭应助科研通管家采纳,获得10
9秒前
Hello应助科研通管家采纳,获得10
9秒前
9秒前
Orange应助科研通管家采纳,获得10
9秒前
脑洞疼应助科研通管家采纳,获得10
9秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
The Organometallic Chemistry of the Transition Metals 800
Chemistry and Physics of Carbon Volume 18 800
The Organometallic Chemistry of the Transition Metals 800
Leading Academic-Practice Partnerships in Nursing and Healthcare: A Paradigm for Change 800
The formation of Australian attitudes towards China, 1918-1941 640
Signals, Systems, and Signal Processing 610
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6437544
求助须知:如何正确求助?哪些是违规求助? 8251985
关于积分的说明 17557747
捐赠科研通 5495911
什么是DOI,文献DOI怎么找? 2898604
邀请新用户注册赠送积分活动 1875316
关于科研通互助平台的介绍 1716340