Tan Bing, Cheng Yan, Li Junfeng, Zheng Yuhao, Xiao Cong, Guo Haoning, Wang Bing, Ouyang Jianyuan, Wang Wenmin, Wang Jisheng
The Third Hospital of Mianyang, Sichuan Mental Health Center, Mianyang, 621000, China.
The Yangtze River Delta Biological Medicine Research and Development Center of Zhejiang Province, Yangtze Delta Region Institution of Tsinghua University, Hangzhou, Zhejiang, 314006, China.
Aging Clin Exp Res. 2025 Jan 21;37(1):28. doi: 10.1007/s40520-024-02923-3.
Osteopenia (ON) and osteoporosis (OP) are highly prevalent among postmenopausal women and poses a challenge for early diagnosis. Therefore, identifying reliable biomarkers for early prediction using metabolomics is critically important.
Initially, non-targeted metabolomics was employed to identify differential metabolites in plasma samples from cohort 1, which included healthy controls (HC, n = 23), osteonecrosis (ON, n = 36), and osteoporosis (OP, n = 37). Subsequently, we performed targeted metabolomic validation of 37 amino acids and their derivatives in plasma samples from cohort 2, consisting of healthy controls (HC, n = 10), osteonecrosis (ON, n = 10), and osteoporosis (OP, n = 10).
The non-targeted metabolomic analysis revealed an increase in differential metabolites with the progression of the disease, showing abnormalities in lipid and organic acid metabolism in ON and OP patients. Several substances were found to correlate positively or negatively with bone mineral density (BMD), for example, N-undecanoylglycine, sphingomyelins, and phosphatidylinositols exhibited positive correlations with BMD, while acetic acid, phenylalanine, taurine, inosine, and pyruvic acid showed negative correlations with BMD. Subsequently, targeted validation of 37 amino acids and their metabolites revealed six amino acids related to ON and OP.
Significant metabolomic features were identified between HC and patients with ON/OP, with multiple metabolites correlating positively or negatively with BMD. Integrating both targeted and non-targeted metabolomic results suggests that lipid, organic acid, and amino acid metabolism may represent important metabolomic characteristics of patients with OP, offering new insights into the development of metabolomic applications in OP.
骨质减少(ON)和骨质疏松症(OP)在绝经后女性中极为普遍,对早期诊断构成挑战。因此,利用代谢组学识别可靠的早期预测生物标志物至关重要。
首先,采用非靶向代谢组学方法识别队列1血浆样本中的差异代谢物,该队列包括健康对照(HC,n = 23)、骨坏死(ON,n = 36)和骨质疏松症(OP,n = 37)。随后,我们对队列2血浆样本中的37种氨基酸及其衍生物进行了靶向代谢组学验证,队列2由健康对照(HC,n = 10)、骨坏死(ON,n = 10)和骨质疏松症(OP,n = 10)组成。
非靶向代谢组学分析显示,随着疾病进展,差异代谢物增加,ON和OP患者的脂质和有机酸代谢出现异常。发现几种物质与骨密度(BMD)呈正相关或负相关,例如,N-十一烷酰甘氨酸、鞘磷脂和磷脂酰肌醇与BMD呈正相关,而乙酸、苯丙氨酸、牛磺酸、肌苷和丙酮酸与BMD呈负相关。随后,对37种氨基酸及其代谢物的靶向验证揭示了6种与ON和OP相关的氨基酸。
在HC与ON/OP患者之间识别出显著的代谢组学特征,多种代谢物与BMD呈正相关或负相关。整合靶向和非靶向代谢组学结果表明,脂质、有机酸和氨基酸代谢可能代表OP患者重要的代谢组学特征,为OP代谢组学应用的发展提供了新见解。