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探索甘油三酯-葡萄糖指数对青春期前儿童骨代谢的影响:一项回顾性研究,来自传统方法和基于机器学习的骨重塑预测的见解

Exploring the effect of the triglyceride-glucose index on bone metabolism in prepubertal children, a retrospective study: insights from traditional methods and machine-learning-based bone remodeling prediction.

作者信息

Cao Shunshun, Chen Aolei, Song Botian, Hu Yangyang

机构信息

Pediatric Endocrinology, Genetics and Metabolism, The Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.

Reproductive Medicine Center, Obstetrics and Gynecology, The Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.

出版信息

PeerJ. 2025 May 20;13:e19483. doi: 10.7717/peerj.19483. eCollection 2025.

Abstract

BACKGROUND

Childhood obesity poses a significant risk to bone health, but the impact of insulin resistance (IR) on bone metabolism in prepubertal children, as assessed by the triglyceride-glucose (TyG) index, remains underexplored. Bone turnover markers (BTMs) provide a non-invasive method for evaluating bone remodeling, but their relationship to obesity-related metabolic changes requires further study.

METHODS

In this retrospective study of 332 prepubertal children (163 boys and 169 girls), we used multivariate linear regression and five machine learning (ML) algorithms to explore the association between the TyG index and BTMs, including β-C-terminal telopeptide of type 1 collagen (β-CTx), total procollagen type 1 N-terminal propeptide (T-P1NP), and N-terminal mid-fragment of osteocalcin (N-MID). The categorical boosting (CatBoost) models selected based on optimal performance metrics were interpreted using SHapley Additive exPlanation (SHAP) analysis to identify key features affecting prediction.

RESULTS

The TyG index was negatively correlated with β-CTx, T-P1NP, and N-MID levels ( < 0.05), with a dose-response effect. The CatBoost model showed higher predictive accuracy and robustness, with the area under the receiver operating characteristic curve (AUROC) values of 0.782 (95% CI [0.68-0.885]), 0.789 (95% CI [0.691-0.874]), and 0.727 (95% CI [0.619-0.827]) for β-CTx, T-P1NP, and N-MID predictions, respectively. The SHAP analysis highlighted body mass index (BMI) and HbA1c as the key predictors.

CONCLUSIONS

The TyG index is a reliable predictor of bone metabolic disorders in prepubertal obese children, and the interpretable CatBoost model provides a cost-effective tool for early intervention. This study has important implications for prevention strategies for disorders of bone metabolism in prepubertal obese children to reduce the risk of skeletal fragility in adulthood or old age.

摘要

背景

儿童肥胖对骨骼健康构成重大风险,但通过甘油三酯-葡萄糖(TyG)指数评估的胰岛素抵抗(IR)对青春期前儿童骨代谢的影响仍未得到充分研究。骨转换标志物(BTMs)为评估骨重塑提供了一种非侵入性方法,但其与肥胖相关代谢变化的关系需要进一步研究。

方法

在这项对332名青春期前儿童(163名男孩和169名女孩)的回顾性研究中,我们使用多元线性回归和五种机器学习(ML)算法来探索TyG指数与BTMs之间的关联,包括1型胶原蛋白β-羧基末端肽(β-CTx)、1型前胶原N端前肽(T-P1NP)和骨钙素N端中段(N-MID)。基于最佳性能指标选择的分类提升(CatBoost)模型使用SHapley加性解释(SHAP)分析进行解释,以识别影响预测的关键特征。

结果

TyG指数与β-CTx、T-P1NP和N-MID水平呈负相关(<0.05),具有剂量反应效应。CatBoost模型显示出更高的预测准确性和稳健性,β-CTx、T-P1NP和N-MID预测的受试者工作特征曲线下面积(AUROC)值分别为0.782(95%CI[0.68-0.885])、0.789(95%CI[0.691-0.874])和0.727(95%CI[0.619-0.827])。SHAP分析突出了体重指数(BMI)和糖化血红蛋白(HbA1c)作为关键预测因素。

结论

TyG指数是青春期前肥胖儿童骨代谢紊乱的可靠预测指标,可解释的CatBoost模型为早期干预提供了一种经济有效的工具。本研究对青春期前肥胖儿童骨代谢紊乱的预防策略具有重要意义,以降低成年期或老年期骨骼脆弱的风险。

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