Objective: To explore the metabolite profile and metabolic pathways of newly diagnosed multiple myeloma (MM). Methods: Gas chromatography-mass spectrometry (GC-MS) was employed for the high-throughput detection and identification of serum samples from 55 patients with MM and 37 healthy controls matched for age and sex from 2016 to 2017 collected at the First Affiliated Hospital of Soochow University. The relative standard deviation (RSD) of quality control (QC) samples was employed to validate the reproducibility of GC-MS approach. The differential metabolites between patients with MM and healthy controls were detected by partial least squares discrimination analysis (PLS-DA), and t-test with false discovery rate (FDR) correction. Metabolomics pathway analysis (MetPA) was employed to construct metabolic pathways. Results: There were 55 MM patients, including 34 males and 21 females. The median age was 60 years old (42-73 years old). There were 30 cases of IgG type, 9 cases of IgA type, 1 case of IgM type, 2 cases of non-secreted type, 1 case of double clone type and 12 cases of light chain type, including 3 cases of kappa light chain type and 9 cases of lambda light chain type. The result of QC sample test showed that the proportion of compounds with the RSD of the relative content of metabolites < 15% was 70.21% obtained by the reproducibility of GC-MS experimental data, which implied that the experimental data were reliable. A total of 17 metabolites were screened differently with the healthy control group, including myristic acid, hydroxyproline, cysteine, palmitic acid, L-leucine, stearic acid, methionine, phenylalanine, glycerin, serine, isoleucine, tyrosine, valine, citric acid, inositol, threonine, and oxalic acid (VIP>1, P<0.05). Metabolic pathway analysis suggested that metabolic disorders in MM patients comprised mainly phenylalanine metabolism, glyoxylic acid and dicarboxylic acid metabolism, phosphoinositide metabolism, cysteine and methionine metabolism, glycerolipid metabolism, glycine, serine, and threonine metabolism. Conclusion: Compared with normal people, patients with newly diagnosed MM have obvious differences in metabolic profiles and metabolic pathways.
目的： 探讨初诊多发性骨髓瘤(MM)的代谢物轮廓和代谢通路。 方法： 收集2016—2017年苏州大学附属第一医院初次确诊MM患者(55例)的血清，收集年龄性别匹配的健康人群(37例)的血清作为对照。采用气相色谱-质谱联用(GC-MS)技术对初治MM患者与健康人群血清进行高通量检测及鉴定，通过计算质量控制(QC)样本的相对标准偏差值(RSD)对样品制备的重现性进行考察。运用偏最小二乘判别分析方法结合t检验校正的方法筛选MM患者及健康人群的差异性代谢物，使用代谢通路分析工具构建代谢通路。 结果： 55例MM患者中，男34例，女21例，中位年龄60岁(42~73岁)。根据M蛋白类型进行分型，IgG型30例，IgA型9例，IgM型1例，未分泌型2例，双克隆型1例，轻链型12例(kappa轻链型3例，lambda轻链型9例)。通过对GC-MS实验数据重现性考察，QC样本检测显示代谢物相对含量的RSD<15%的化合物比例为70.21%，提示实验数据可靠。MM患者区别于健康对照人群的17种差异性代谢物为肉豆蔻酸、羟脯氨酸、半胱氨酸、软脂酸、L-亮氨酸、硬脂酸、甲硫氨酸、苯丙氨酸、甘油、丝氨酸、异亮氨酸、酪氨酸、缬氨酸、柠檬酸、肌醇、苏氨酸、草酸(VIP>1，P<0.05)。MM患者的代谢紊乱主要涉及苯丙氨酸代谢、乙醛酸和二羧酸代谢、磷酸肌醇代谢、半胱氨酸和蛋氨酸代谢、甘油脂代谢、甘氨酸、丝氨酸和苏氨酸代谢。 结论： 与健康对照人群比较，初诊MM患者存在明显的代谢轮廓差异和代谢通路扰动。.
Keywords: Gas chromatography-mass spectrometry; Metabolic markers; Metabolic pathways; Multiple myeloma.