Human Genetics and Genomic Medicine, Southampton General Hospital, University of Southampton, Duthie Building (Mailpoint 808), Southampton, SO16 6YD, UK.
Institute for Life Sciences, University of Southampton, Southampton, UK.
Sci Rep. 2022 Aug 18;12(1):14101. doi: 10.1038/s41598-022-18178-9.
Crohn's disease (CD) is characterised by chronic inflammation. We aimed to identify a relationship between plasma inflammatory metabolomic signature and genomic data in CD using blood plasma metabolic profiles. Proton NMR spectroscopy were achieved for 228 paediatric CD patients. Regression (OPLS) modelling and machine learning (ML) approaches were independently applied to establish the metabolic inflammatory signature, which was correlated against gene-level pathogenicity scores generated for all patients and functional enrichment was analysed. OPLS modelling of metabolomic spectra from unfasted patients revealed distinctive shifts in plasma metabolites corresponding to regions of the spectrum assigned to N-acetyl glycoprotein, glycerol and phenylalanine that were highly correlated (R = 0.62) with C-reactive protein levels. The same metabolomic signature was independently identified using ML to predict patient inflammation status. Correlation of the individual peaks comprising this metabolomic signature of inflammation with pathogenic burden across 15,854 unselected genes identified significant enrichment for genes functioning within 'intrinsic component of membrane' (p = 0.003) and 'inflammatory bowel disease (IBD)' (p = 0.003). The seven genes contributing IBD enrichment are critical regulators of pro-inflammatory signaling. Overall, a metabolomic signature of inflammation can be detected from blood plasma in CD. This signal is correlated with pathogenic mutation in pro-inflammatory immune response genes.
克罗恩病(CD)的特征是慢性炎症。我们旨在使用血液血浆代谢谱来鉴定 CD 中血浆炎症代谢组特征与基因组数据之间的关系。对 228 例儿科 CD 患者进行了质子 NMR 光谱分析。分别应用回归(OPLS)建模和机器学习(ML)方法来建立代谢炎症特征,该特征与针对所有患者生成的基因水平致病性评分相关联,并分析了功能富集。对未禁食患者的代谢组图谱进行 OPLS 建模,发现与谱区域分配给 N-乙酰糖蛋白、甘油和苯丙氨酸对应的血浆代谢物发生明显变化,与 C-反应蛋白水平高度相关(R=0.62)。使用 ML 独立识别相同的代谢组学特征,以预测患者的炎症状态。构成该炎症代谢组学特征的各个峰与 15854 个未筛选基因的致病性负担相关联,鉴定出与“膜固有成分”(p=0.003)和“炎症性肠病(IBD)”(p=0.003)功能相关的基因显著富集。导致 IBD 富集的七个基因是促炎信号的关键调节因子。总体而言,CD 患者的血液血浆中可以检测到炎症的代谢组学特征。该信号与促炎免疫反应基因中的致病性突变相关。