醫(yī)學(xué)代謝組學(xué)案例分析：通過GC-MS檢測血液樣本分析哮喘病人的代謝物組信息變化

研究對象：人血

分析檢測平臺(tái)：GC-TOF／MS （BIOTREE）

期刊：Acta Pharmacologica Sinica

影響因子：2.912

發(fā)表時(shí)間：2015

摘要：

Aim: To character the specific metabolomics profiles in the sera of Chinese patients with mild persistent asthma and to explore potential metabolic biomarkers.

Methods: Seventeen Chinese patients with mild persistent asthma and age- and sex-matched healthy controls were enrolled. Serum samples were collected, and serum metabolites were analyzed using GC-MS coupled with a series of multivariate statistical analyses.

Results: Clear intergroup separations existed between the asthmatic patients and control subjects. A list of differential metabolites and several top altered metabolic pathways were identified. The levels of succinate (an intermediate in tricarboxylic acid cycle) and inosine were highly upregulated in the asthmatic patients, suggesting a greater effort to breathe during exacerbation and hypoxic stress due to asthma. Other differential metabolites, such as 3,4-dihydroxybenzoic acid and phenylalanine, were also identified. Furthermore, the differential metabolites possessed higher values of area under the ROC curve (AUC), suggesting an excellent clinical ability for the prediction of asthma.

Conclusion: Metabolic activity is significantly altered in the sera of Chinese patients with mild persistent asthma. The data might be helpful for identifying novel biomarkers and therapeutic targets for asthma.

Keywords: mild persistent asthma; Chinese patients; serum metabolites; metabolomics; succinate; inosine; GC-MS

一、研究背景：

哮喘常由呼吸道炎癥導(dǎo)致，但目前診療中還缺乏簡便易行的呼吸道炎癥快速判定措施。來源于尿液、血液和呼出氣冷凝液的代謝物可用于疾病的分型和診斷，代謝組學(xué)技術(shù)通過檢測分析上述樣本的代謝物指紋圖譜可獲得與疾病相關(guān)的最重要的代謝物和代謝途徑。針對這些特異性較強(qiáng)的生物標(biāo)志物可進(jìn)一步建立快速檢測方法，用于類似哮喘等復(fù)雜疾病的分型和早期診斷。本研究嘗試通過GC-TOF/MS方法分析哮喘病人血樣，從而獲得可能用于早期診斷的潛力生物標(biāo)志物。

二、方法流程：

三、研究結(jié)果與討論：

1、發(fā)現(xiàn)血清代謝組數(shù)據(jù)在疾病與正常中出現(xiàn)明顯區(qū)分：

1）使用GC-MS數(shù)據(jù)可區(qū)分輕微持續(xù)性哮喘病人和健康人群

2）血清樣本代謝組變化證明哮喘可引起人體系統(tǒng)整體代謝變化

圖1 通過多元變量統(tǒng)計(jì)分析GC-MS數(shù)據(jù)建立PCA模型

2、篩選得到標(biāo)志性差異物：琥珀酸、二羥基苯甲酸、肌苷

1）TCA循環(huán)中僅琥珀酸表現(xiàn)差異：病癥可能出于早期，未造成全局變化；

2）許多代謝物與炎癥反應(yīng)、缺氧應(yīng)激等相關(guān)；

3）上述物質(zhì)可作為哮喘早期診斷生物標(biāo)志物

圖2 使用VIP篩選標(biāo)志性差異物，及相關(guān)物質(zhì)的ROC曲線

3、哮喘發(fā)病相關(guān)代謝途徑研究：

1）影響途徑：TCA循環(huán)、氮代謝、谷氨酸代謝、核糖代謝、苯丙氨酸代謝

2）TCA循環(huán)代謝強(qiáng)化：缺氧導(dǎo)致能量需求旺盛

3）炎癥反應(yīng)相關(guān)

4）氮代謝紊亂

圖3 哮喘發(fā)病可能涉及的代謝途徑

四、亮點(diǎn)和展望：

l 發(fā)現(xiàn)哮喘病人血清中特異性的代謝物信息；

l 提出哮喘早期診斷可能的標(biāo)志代謝物；

l 發(fā)現(xiàn)與哮喘發(fā)病相關(guān)的關(guān)鍵代謝途徑：

A、增加病例并對代謝物信息進(jìn)一步解讀有助于了解輕微持續(xù)性哮喘的發(fā)病原因

B、生物標(biāo)志物的最終認(rèn)定需在人群隊(duì)列實(shí)驗(yàn)中進(jìn)行證明

閱讀文獻(xiàn)下載地址：

Chun CHANG, et al, Investigation of metabolic alterations in asthma by GC-MS based metabolomics analysis. Acta Pharmacologica Sinica. 2015. 36:1356-1366.