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南京医科大学学报(自然科学版)                                  第46卷第6期
               ·864  ·                    Journal of Nanjing Medical University(Natural Sciences)   2026年6月


             ·临床研究·

              肥胖共患中枢性性早熟女童的脂质组学分析



              陈冠宇 ,张泽楷 ,龚          袁 ,蒋 婷 ,刘       今 ,汤涌泉 ,周文娣          1,2*
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               南京医科大学附属淮安第一医院儿科,江苏 淮安                  223300;徐州医科大学淮安临床学院儿科,江苏              淮安 223300
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             [摘    要] 目的:通过脂质组学分析技术,系统筛选儿童肥胖共患中枢性性早熟(childhood obesity comorbid with central preco⁃
              cious puberty,CO⁃CPP)的潜在生物标志物,并探索差异脂质联合疾病相关临床指标应用于CO⁃CPP早期识别和预警的可行性,
              为临床实践提供新依据。方法:选取2024年1月—2025年6月首次就诊于南京医科大学附属淮安第一医院儿科内分泌门诊的
              6~8 岁肥胖女童 20 例,根据是否合并中枢性性早熟(central precocious puberty,CPP)或外周性性早熟(peripheral precocious
              puberty,PPP)分为 CO⁃CPP 组(10 例)和肥胖共患外周性性早熟(childhood obesity comorbid with peripheral precocious puberty,
              CO⁃PPP)组(10例)。比较两组一般临床资料,采集血清样本进行非靶向脂质组学分析。筛选差异脂质后开展受试者工作特征
             (receiver operating characteristic,ROC)曲线分析,进一步结合临床指标通过二元 Logistic 回归构建联合预测模型,并开展联合
              ROC分析评估预测效能。结果:脂质组学分析共鉴定出42种差异有统计学意义的脂质分子,其中神经酰胺(ceramide,Cer)、磷
              脂酰胆碱(phosphatidylcholine,PC)表达上调,磷脂酰乙醇胺(phosphatidylethanolamine,PE)表达下调。Cer、PC、PE 单独预测
              CO⁃CPP的ROC曲线下面积(area under the curve,AUC)分别为0.810、0.798、0.834,均展现出良好的判别效能(P均< 0.05)。Cer
              联合基础黄体生成素(luteinizing hormone,LH)的预测模型AUC可达0.970。结论:CO⁃CPP女童体内与青春期发育相关的关键
              脂质Cer、PC表达上调,PE表达下调,上述脂质或可作为CO⁃CPP的潜在生物学标志物。Cer联合基础LH的判别效能优于单一
              脂质指标,具有较好的临床应用潜力。
             [关键词] 肥胖;性早熟;共病;脂质组学;儿童
             [中图分类号] R725.8                   [文献标志码] A                       [文章编号] 1007⁃4368(2026)06⁃864⁃09
              doi:10.7655/NYDXBNSN260112



              Lipidomics analysis of childhood obesity comorbid with central precocious puberty
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              CHEN Guanyu ,ZHANG Zekai ,GONG Yuan ,JIANG Ting ,LIU Jin ,TANG Yongquan ,ZHOU Wendi      1,2*
              1 Department of Pediatrics,The Affiliated Huai’an No. 1 People’s Hospital of Nanjing Medical University,Huai’an
              223300;Department of Pediatrics,Huai’an Clinical College of Xuzhou Medical University,Huai’an 223300,China
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             [Abstract] Objective:This study employed lipidomics analysis to systematically screen potential biomarkers of childhood obesity
              comorbid with central precocious puberty(CO⁃CPP),and explored the feasibility of combining these biomarkers with disease⁃related
              clinical indicators to provide new evidence for early identification and warning of CO ⁃ CPP. Methods:A total of 20 obese female
              children aged 6 to 8 years who first visited the Pediatric Endocrinology Clinic of the Affiliated Huai’an No. 1 People’s Hospital of
              Nanjing Medical University between January 2024 and June 2025 were enrolled. They were divided into the CO⁃CPP group(n=10)and
              the comorbidity of childhood obesity comorbid with peripheral precocious puberty(CO⁃PPP)group(n=10)based on the presence of
              central precocious puberty(CPP)or peripheral precocious puberty(PPP). General clinical data were compared between the two
              groups,and serum samples were collected for non ⁃ targeted lipidomics analysis. Differential lipids were screened using receiver
              operating characteristic(ROC)curve analysis,and a combined predictive model was constructed with clinical indicators via binary
              logistic regression,followed by further combined ROC analysis. Results:Lipidomics analysis identified 42 lipid molecules with
              significant differences. Among them,the expression of ceramide(Cer)and phosphatidylcholine(PC)were up ⁃ regulated,while the
              expression of phosphatidylethanolamine(PE)was down⁃regulated. The area under the curve(AUC)of ROC for predicting CO⁃CPP by
              Cer,PC,and PE alone was 0.810,0.798,and 0.834,respectively,all of which showed good discriminative efficacy(all P < 0.05). The

             [基金项目] 江苏省妇幼保健协会科研基金(FYX202213)
              通信作者(Corresponding author),E⁃mail:hayyzwd@163.com(ORCID:0000⁃0003⁃1880⁃4982)
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