表观遗传衰老中的精确营养:shap优化的机器学习识别omega-3成分与衰老生物标志物的特异性关联。

IF 4.4 4区 医学 Q1 GERIATRICS & GERONTOLOGY
Zhaoqi Yan, Yifeng Xu, Ting Peng, Xiufan Du
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引用次数: 0

摘要

这项横断面研究旨在研究老年人饮食中的omega-3脂肪酸(包括α-亚麻酸[ALA]、二十碳五烯酸[EPA]和二十二碳六烯酸[DHA])与细胞衰老的生物标志物,特别是DNA甲基化年龄(Horvathage)和端粒长度(Horvathtelo)之间的关系。我们的分析利用了1999-2002年NHANES周期中2136名年龄≥50岁的参与者的全国代表性数据。建立了具有调查权重的多变量线性回归模型来评估剂量-反应关系,并辅以限制三次样条(RCS)进行非线性检测。机器学习优化包括通过五次交叉验证对九种算法进行比较评估,并通过SHapley加性解释(SHAP)分析增强模型的可解释性。较高的omega-3摄入量(Tertile 3 [T3] vs Tertile 1 [T1])与HorvathAge呈负相关(β = -1.07),特别是ALA摄入量(T3≥1.512 g/d: β = -1.11)。相反,中高ω -3摄入量(T2≥0.917 g/d: β = 0.04;T3: β = 0.04)和单个成分(ALA_T3: β = 0.04;DHA_T3≥0.041 g/d: β = 0.05;EPA_T3≥0.011 g/d: β = 0.03)与HorvathTelo呈正相关。RCS模型显示了不同的模式:HorvathAge与Horvathtelo呈线性负相关,而与Horvathtelo呈非线性j形相关。在机器学习模型中,线性支持向量机取得了较好的预测性能。SHAP特征重要性分析一致将omega-3复合措施列为最高,其次是组成成分(ALA b> DHA b> EPA)。我们的研究结果表明,omega-3在生物衰老调节中具有潜在的双重作用:高摄入量与减缓表观遗传衰老有关,同时维持端粒长度的稳态。这些观察结果强调了在营养老年学研究中同时考虑综合措施和个体成分的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Precision nutrition in epigenetic aging: SHAP-optimized machine learning identifies omega-3 constituent-specific associations with aging biomarkers.

This cross-sectional investigation seeks to examine the association between dietary omega-3 fatty acids (including α-linolenic acid [ALA], eicosapentaenoic acid [EPA], and docosahexaenoic acid [DHA]) and biomarkers of cellular aging, specifically DNA methylation age (Horvathage) and telomere length (Horvathtelo), in older adults. Our analysis leveraged nationally representative data from 2,136 participants aged ≥ 50 years in the 1999-2002 NHANES cycles. Multivariable linear regression models with survey weights were constructed to evaluate dose-response relationships, complemented by restricted cubic splines (RCS) for nonlinearity detection. Machine learning optimization included comparative evaluation of nine algorithms through five-fold cross-validation, with model interpretability enhanced via SHapley Additive exPlanations (SHAP) analysis. Higher omega-3 intake (Tertile 3 [T3] vs Tertile 1 [T1]) demonstrated inverse associations with HorvathAge (β = -1.07), particularly for ALA intake (T3 ≥ 1.512 g/d: β = -1.11). Contrastingly, moderate-to-high omega-3 intake (T2 ≥ 0.917 g/d: β = 0.04; T3: β = 0.04) and individual components (ALA_T3: β = 0.04; DHA_T3 ≥ 0.041 g/d: β = 0.05; EPA_T3 ≥ 0.011 g/d: β = 0.03) exhibited positive correlations with HorvathTelo. RCS modeling revealed distinct patterns: linear inverse correlation for HorvathAge versus nonlinear J-shaped association with Horvathtelo. Among ML models, Linear Support Vector Machines achieved superior predictive performance. SHAP feature importance analysis consistently ranked omega-3 composite measures highest, followed by constituent components (ALA > DHA > EPA). Our findings suggest a potential dual role of omega-3 in biological aging modulation: higher intake associates with decelerated epigenetic aging while maintaining telomere length homeostasis. These observations underscore the importance of considering both composite measures and individual components in nutritional gerontology research.

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来源期刊
Biogerontology
Biogerontology 医学-老年医学
CiteScore
8.00
自引率
4.40%
发文量
54
审稿时长
>12 weeks
期刊介绍: The journal Biogerontology offers a platform for research which aims primarily at achieving healthy old age accompanied by improved longevity. The focus is on efforts to understand, prevent, cure or minimize age-related impairments. Biogerontology provides a peer-reviewed forum for publishing original research data, new ideas and discussions on modulating the aging process by physical, chemical and biological means, including transgenic and knockout organisms; cell culture systems to develop new approaches and health care products for maintaining or recovering the lost biochemical functions; immunology, autoimmunity and infection in aging; vertebrates, invertebrates, micro-organisms and plants for experimental studies on genetic determinants of aging and longevity; biodemography and theoretical models linking aging and survival kinetics.
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