Suppr超能文献

探索甘油三酯-葡萄糖指数在抑郁症和认知功能障碍中的作用:来自美国国家健康与营养检查调查(NHANES)并得到机器学习支持的证据。

Exploring the triglyceride-glucose index's role in depression and cognitive dysfunction: Evidence from NHANES with machine learning support.

作者信息

Ding Chao, Lu Renjie, Kong Zhiyu, Huang Rong

机构信息

Putuo Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China.

South China University of Technology, Guangzhou, China.

出版信息

J Affect Disord. 2025 Apr 1;374:282-289. doi: 10.1016/j.jad.2025.01.051. Epub 2025 Jan 11.

Abstract

BACKGROUND

Depression and cognitive impairments are prevalent among older adults, with evidence suggesting potential links to obesity and lipid metabolism disturbances. This study investigates the relationships between the triglyceride-glucose (TyG) index, body mass index (BMI), depression, and cognitive dysfunction in older adults, leveraging data from the NHANES survey and employing machine learning techniques.

METHODS

We analysed 1352 participants aged 60-79 from the 2011-2014 NHANES dataset, who underwent cognitive function testing, depression assessments, and TyG index measurements. Multivariate linear regression and subgroup analyses were conducted to examine associations between the TyG index and depression/cognitive impairment. Machine learning models evaluated the importance of predictive factors for depression, while Mendelian randomization (MR) was employed to explore the causal relationship between BMI and depression/cognitive function.

RESULTS

The TyG index was negatively associated with cognitive function scores and positively associated with depression scores in adjusted models (p < 0.001). In fully adjusted subgroup analyses, among obese individuals (BMI ≥ 28), a 100-unit increase in the TyG index was linked to a 3.79-point decrease in depression scores. Machine learning models (Xgboost, AUC = 0.960) identified BMI, TyG-BMI, gender, and comorbidities (e.g., asthma, stroke, emphysema) as key determinants of depression. MR analyses revealed a negative association between BMI and depression risk [OR: 0.9934; 95 % CI (0.9901-0.9968), p = 0.0001] and cognitive dysfunction risk [OR: 0.8514; 95 % CI (0.7929-0.9143), p < 0.05]. No evidence of heterogeneity or pleiotropy was detected.

LIMITATIONS

Depression and cognitive impairments were self-reported, potentially introducing bias. The observed associations may be influenced by unmeasured confounders, necessitating further research into the underlying mechanisms.

CONCLUSIONS

Our findings reveal associations between the TyG index and psychocognitive health in older adults. While these results highlight lipid metabolism as a potential factor in depression and cognitive dysfunction, further studies are needed to validate these findings and explore underlying mechanisms.

摘要

背景

抑郁症和认知障碍在老年人中很普遍,有证据表明它们可能与肥胖和脂质代谢紊乱有关。本研究利用美国国家健康与营养检查调查(NHANES)的数据并采用机器学习技术,调查老年人中甘油三酯-葡萄糖(TyG)指数、体重指数(BMI)、抑郁症和认知功能障碍之间的关系。

方法

我们分析了2011 - 2014年NHANES数据集中1352名年龄在60 - 79岁之间的参与者,他们接受了认知功能测试、抑郁症评估和TyG指数测量。进行了多变量线性回归和亚组分析,以检验TyG指数与抑郁症/认知障碍之间的关联。机器学习模型评估了抑郁症预测因素的重要性,同时采用孟德尔随机化(MR)来探索BMI与抑郁症/认知功能之间的因果关系。

结果

在调整后的模型中,TyG指数与认知功能评分呈负相关,与抑郁症评分呈正相关(p < 0.001)。在完全调整后的亚组分析中,在肥胖个体(BMI≥28)中,TyG指数每增加100个单位,抑郁症评分下降3.79分。机器学习模型(Xgboost,AUC = 0.960)将BMI、TyG - BMI、性别和合并症(如哮喘、中风、肺气肿)确定为抑郁症的关键决定因素。MR分析显示BMI与抑郁症风险呈负相关[比值比(OR):0.9934;95%置信区间(CI)(0.9901 - 0.9968),p = 0.0001]以及与认知功能障碍风险呈负相关[OR:0.8514;95%CI(0.7929 - 0.9143),p < 0.05]。未检测到异质性或多效性的证据。

局限性

抑郁症和认知障碍是自我报告的,可能存在偏差。观察到的关联可能受到未测量的混杂因素的影响,需要进一步研究潜在机制。

结论

我们的研究结果揭示了老年人中TyG指数与心理认知健康之间的关联。虽然这些结果突出了脂质代谢作为抑郁症和认知功能障碍的一个潜在因素,但需要进一步研究来验证这些发现并探索潜在机制。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验