【研究背景】随着我国老龄化进程加速，衰老带来的一系列健康问题给国家医疗卫生和经济带来严峻的挑战。脂代谢异常是全球范围内衰老研究的热点领域。已有研究表明其可促进衰老相关疾病的发生，但对衰老核心标志物（如端粒长度缩短和抗衰老蛋白α-Klotho 下降）的直接作用仍不明确。目前，传统血脂指标与衰老及疾病的关联存在争议。相比之下，非传统血脂标志物残余胆固醇（remnant cholesterol, RC），作为富含甘油三酯的脂蛋白残粒的主要成分，可以更全面反映脂代谢异常，可能为脂代谢与衰老的关系探索提供新的突破口。从机制层面来看，炎症和氧化应激不仅是衰老加速的核心驱动因素，更是脂代谢异常诱发多种疾病的关键通路。目前关于 RC 与衰老标志物之间的关系及炎症氧化应激在其中作用机制的研究仍较为匮乏。

2 型糖尿病（type 2 diabetes mellitus, T2DM）作为一种衰老相关疾病，患病率不断攀升，已成为全球公共卫生的重大挑战。脂代谢异常是 T2DM 发生的关键因素，细胞衰老可加速 T2DM 进展。进一步探讨脂代谢异常联合衰老标志物在 T2DM 发生机制中的作用，将有利于优化 T2DM 管理策略。

膳食营养素作为调控脂代谢的重要因素，对衰老也发挥关键调节作用。现有研究多聚焦于单一营养素与衰老标志物的关系，忽略了营养素间的相互作用，且未探索脂代谢在二者中的作用。基于整体营养素模式（nutrient patterns, NPs）的系统性研究，将有助于揭示不同营养素组合对衰老的综合影响，阐明“营养素组合-脂代谢-衰老”的级联效应，为精准营养干预提供科学依据。

饮食中的多种食物组分也可能通过影响血脂，进而调控炎症和氧化应激水平，最终影响衰老进程。因此，从饮食结构出发，研究血脂相关饮食模式对衰老标志物的影响，将为制定更具针对性的膳食干预策略提供理论支持。

【研究目的】

1. 探讨 RC 与关键衰老标志物（外周血白细胞端粒长度[leukocyte telomere length, LTL]、α-Klotho 蛋白）的关联及其影响因素，并揭示炎症和氧化应激的潜在作用机制。

2. 分析RC与衰老标志物在T2DM发生中的相互作用，并评估二者对 T2DM发生风险的预测价值。

3. 基于营养素模式解析其与衰老标志物的关联，并明确 RC 等血脂指标在其中的作用。

4. 基于食物组构建血脂相关饮食模式，探讨其对衰老标志物的影响，并分析炎症和氧化应激的介导作用。

综上，本研究以脂代谢异常为切入点，整合衰老标志物、T2DM、炎症氧化应激及饮食因素，系统探讨脂代谢异常与衰老的关系及其潜在机制，并构建基于脂代谢的膳食干预策略，为精准衰老管理提供科学依据和可行的干预方案。

【研究方法】

1. 研究对象：本研究的研究对象均来自在北京昌平地区长期动态进行的“农村 2 型糖尿病管理项目”的自然人群。第一和第三部分为横断面研究，研究对象均来自参与 2014 年至 2021 年调查的 898 例参与者。第二部分为前瞻性研究，研究对象来自 2014 年基线无糖尿病的 236 例参与者，3~10 年后进行第二次随访。第四部分同样为横断面分析，纳入既往无高脂血症史的 718 例参与者。

2. 资料收集和指标评估：参与者通过标准化的调查问卷获取一般人口学资料。采集空腹血糖、血脂、肝肾功等生化指标及糖化血红蛋白（glycosylated hemoglobin, HbA1c）。通过 75g 口服葡萄糖耐量试验（oral glucose tolerance trial, OGTT）明确糖代谢状态。RC 采用计算法评估，定义为总胆固醇（total cholesterol, TC）减低密度脂蛋白胆固醇（low density lipoprotein cholesterol, LDL-C）和高密度脂蛋白胆固醇（high density lipoprotein cholesterol, HDL-C）。通过实时定量聚合酶链式反应（quantitative real-time polymerase chain reaction, RT-qPCR）确定端粒长度，ELISA 测定血清α-Klotho 蛋白、超氧化物歧化酶（superoxide dismutase, SOD）、8-羟基-2-脱氧鸟苷（8-hydroxy-2-deoxyguanosine, 8-oHdG）等，多因子测量肿瘤坏死因子α（tumor necrosis factor α, TNFα）、白细胞介素-6（interleukin-6, IL-6）、白细胞介素-1β（interleukin-1β, IL-1β）。

3. 饮食分析：通过 24 小时膳食回顾采集饮食数据。基于主成分分析，对蛋白质、碳水化合物、脂肪、维生素 A/B1/B2/C/E、磷、钙、钾、镁、钠、铁、硒、锌、铜等 17 种营养素，进行营养素模式提取。在不同营养素模式中，依据因子载荷绝对值较大的营养素来命名该模式。对人群摄入的食物进行分类，共分为28 种食物组，以 RC 和甘油三酯（triglyceride, TG）两个血脂指标为反应变量，基于降秩回归构建血脂相关饮食模式。食物组的因子载荷代表其对血脂相关饮食模式的贡献，选择因子载荷绝对值较大的食物组来解释反应变量。

4. 统计学方法：采用多元线性回归分析 RC、营养素模式、血脂相关饮食模式与衰老标志物的关系。限制性立方样条（restricted cubic spline, RCS）探讨剂量-反应关系。Logistic 回归和受试者特征（receiver operating characteristic, ROC）曲线探讨 RC、衰老标志物对 T2DM 发生的影响和预测效能。采用中介效应对炎症、氧化应激进行机制探讨。亚组分析评估潜在的代谢影响因素。

【研究结果】

1. 非传统血脂标志物残余胆固醇与衰老标志物的关联及机制探索

对 898 名参与者基于 RC 水平四分位数分组，RC 较高组，表现出较低的 LTL和α-Klotho 蛋白，和较高的 TNFα、IL-6、IL-1β及 SOD（均 P＜0.05）。多元线性回归校正年龄、性别、总能量摄入和代谢指标（包括传统血脂谱）后，RC 与LTL 和 α-Klotho 蛋 白 均 呈 负 相 关 （ B[95%CI] 分 别 为 -0.194[-0.290,-0.098] 和-0.041[-0.063, -0.019]，均 P＜0.05）。RCS 显示，RC 与 LTL、α-Klotho 蛋白均呈非线性关系（P for nonlinear 分别 0.007 和 0.011），切点分别为 1.441mmol/L 和1.323mmol/L。在切点以下二者均呈负相关，高于切点则无显著关联。校正炎症氧化应激后，RC 与 LTL 的关联减弱（B=-0.136，P＜0.05），与α-Klotho 蛋白的关联消失（B=-0.024，P＞0.05）。中介分析显示，TNFα、IL-6 在 RC 与 LTL 的关系中分别介导 17.35%和 16.56%的中介作用；SOD 升高在 RC 与α-Klotho 蛋白的关系发挥 63.46%的中介作用。亚组分析发现，RC 与两种衰老标志物的负相关均在年轻组更显著。就性别而言，RC与LTL的关联在女性中更明显，而与α-Klotho蛋白的关系在男性中更明显。此外，代谢状态可影响 RC 与α-Klotho 蛋白的关系，特别是在无 DM、TG＜1.7mmol/L 和较高 ALT 的个体中关联更显著。

2. 残余胆固醇联合衰老标志物对 2 型糖尿病发生的预测价值

基线 236 人，经过 7 年的中位随访，75 人进展为 T2DM（进展组），161 人未进展（未进展组）。与未进展组相比，进展组 RC 水平更高，LTL 更短（均 P＜0.05）。多元 Logistic 回归校正混杂因素后，高 RC 与 T2DM 风险增加相关（OR[95%CI]: 2.272[1.050,4.917], P＜0.05），高 LTL 与 T2DM 风险降低有关（OR[95%CI]: 0.626 [0.443, 0.885], P＜0.05）。未发现α-Klotho 蛋白与 T2DM 风险的显著关联。中介分析显示 LTL 在 RC 与 T2DM 风险中发挥中介效应，中介比例为 14.38%。ROC 曲线表明单独 RC、LTL、年龄对 T2DM 风险均有预测价值（AUC 分别为 0.604、0.618 和 0.635，均 P＜0.05），三者联合后预测效能明显升高（AUC=0.709，P＜0.05），且有较高敏感性（83.6%）。进一步亚组分析表明，在女性、糖前期和 LDL-C≥ 2.6 mmol/L 组，RC 和 LTL 与 T2DM 风险的关联更强；仅在女性组 LTL 可显著介导这一关联（约占 24.02%）。

3. 基于主成分分析的营养素模式与衰老标志物的关系及血脂代谢在其中的作用

898 名参与者，通过主成分分析对 17 种营养素共提取出 4 种营养素模式，分别为“高蛋白-高微量营养素”、“高脂肪高钠低碳水”、“高维生素 C-高钙钾镁”、“高铁铜”模式。Spearman 相关性分析提示“高蛋白-高微量营养素”模式及其核心组分蛋白质、硒等与 LTL 呈正相关（均 P＜0.001），与 TC、RC 呈负相关（均P＜0.001）。多元线性回归和 RCS 显示“高蛋白-高微量营养素”模式与 LTL 呈线性正相关（B[95%CI]:0.080[0.039,0.120]; P for nonlinear =0.886），与α-Klotho 蛋白存在非线性关联（B[95%CI]: 0.005 [-0.005, 0.014]; P for nonlinear=0.019）。校正 RC 后，该营养素模式与 LTL 的关联有所减弱（B=0.059，P＜0.05）。未发现其他三种营养素模式与两种衰老标志物的显著关联（均 P＞0.05）。中介效应表明 RC 在“高蛋白-高微量营养素”模式与 LTL 关系中可发挥 22.37%的中介作用。

4. 血脂相关饮食模式与衰老标志物的关系及炎症氧化应激在其中的作用

718 名参与者，以 RC 和 TG 为反应变量，以 28 种食物组为自变量，通过降秩回归构建了中国北方农村人群的“血脂相关饮食模式”，其特征为高植物油、高盐摄入以及低全谷物、低深色蔬菜摄入。按饮食模式得分三分位分组，结果显示，高得分组 RC 和 TG 水平更高；LTL 和α-Klotho 蛋白更低，且伴随着更高的 TNFα、IL-1β以及 SOD（均 P＜0.05）。相关性分析表明饮食模式与 RC、TG 呈正相关（均 P＜0.05）。多元线性回归校正混杂变量后，饮食模式得分（作为连续性变量）与 LTL（B[95%CI]: -0.148 [-0.215, 0.081], P＜0.001）和α-Klotho 蛋白（B[95%CI]:-0.016 [-0.029, -0.002], P=0.022）均呈负相关；且随得分逐渐升高，这种负性关联逐渐加强（P for trend 分别＜0.001 和=0.025）。调整炎症和氧化应激指标后，饮食模式得分与 LTL 和α-Klotho 蛋白的关联分别减弱（B=-0.057，P=0.035）和消失（B=-0.010，P=0.069）。中介效应分析显示TNFα和IL-1β介导了12.07%和22.22%的血脂相关饮食模式与 LTL 的关联，IL-1β、SOD 则介导了 14.81%和 47.06%的该饮食模式与α-Klotho 蛋白的关联。

【研究结论】

1. RC 与 LTL 和α-Klotho 蛋白存在独立于传统血脂参数和多种代谢因素的负性和非线性关联，炎症和氧化应激在这一关联中发挥重要中介作用。降低 RC 可能通过减少炎症或氧化应激延缓衰老进程，为脂代谢在衰老干预中的应用提供了新视角。未来应根据不同人群特征制定相应的干预策略。

2. 基线 RC 升高和基线 LTL 缩短可增加 T2DM 发生风险，独立于年龄、性别、血压和传统血脂等，尤其是在女性、糖前期和 LDL-C≥2.6mmol/L 的个体。基线 LTL 缩短部分解释了 RC 升高对 T2DM 的不利影响，在女性中这种不利的中介作用更强。与单独应用 RC、LTL 和年龄，三者联合显著提高了对 T2DM 发生的预测效能和敏感性，从脂代谢和衰老轴为 T2DM 早期筛查提供了新方向。

3. “高蛋白-高微量营养素”模式与 LTL 呈线性正相关，且 RC 在这一关联中起到部分中介作用，揭示了“营养-脂代谢-衰老”间的复杂相互关联。靶向蛋白质和硒等微量营养素的营养干预策略有望通过改善血脂代谢延缓衰老进程。

4. 在中国人群中，以高植物油、高盐、低全谷物、低深色蔬菜摄入为特征的不良血脂饮食模式与端粒缩短及α-Klotho 蛋白水平下降有关。中介效应模型揭示这一关联可能是通过激活促炎因子和诱导氧化应激实现。提示优化饮食结构可能通过改善血脂、减轻炎症和氧化损伤等多重途径对衰老发挥有益作用。

本研究深入探讨了脂代谢异常、T2DM、饮食模式与衰老之间的复杂关系，从生物标志物关联、疾病预测、营养干预、饮食结构优化等四大创新维度，为衰老管理策略提供了新的干预思路。

【Background】

With the acceleration of population aging in China, the health issues associated with aging pose severe challenges to national healthcare and the economy. Abnormal lipid metabolism has long been a focal point in global aging research. Existing studies have demonstrated its role in promoting the onset of age-related diseases; however, its direct effects on core aging biomarkers, such as shortened leukocyte telomere length (LTL) and decreased anti-aging protein α-Klotho, remain unclear. Traditional lipid parameters have shown inconsistent associations with aging and disease. In contrast, the non-traditional lipid marker remnant cholesterol (RC), a major component of triglyceride-rich lipoprotein remnants, may provide a more comprehensive reflection of lipid metabolism abnormalities and potentially offer new insights into the link between lipid metabolism and aging. Mechanistically, inflammation and oxidative stress are not only key drivers of accelerated aging but also critical pathways through which abnormal lipid metabolism induces various diseases. Current research on the relationship between RC and aging biomarkers, as well as the underlying roles of inflammation and oxidative stress, is still limited.

Type 2 diabetes mellitus (T2DM), an aging-related disease with an ever-increasing prevalence, has become a severe global public health challenge. Abnormal lipid metabolism is a key factor in the development of T2DM, and cellular senescence can further accelerate its progression. Exploring the combined effects of abnormal lipid metabolism and aging biomarkers on the pathogenesis of T2DM will contribute to the optimization of T2DM management strategies.

Nutritional factors are crucial in regulating lipid metabolism and play a key role in modulating the aging process. Most existing studies have focused on the relationship between individual nutrients and aging biomarkers, neglecting the interactions among nutrients and the role of lipid metabolism in this relationship.

Systematic research based on overall nutrient patterns (NPs) will help elucidate the comprehensive impact of various nutrient combinations on aging and clarify the cascade effects of “nutrient combination–lipid metabolism–aging,” thereby providing scientific evidence for precision nutritional interventions.

Moreover, various dietary components may influence blood lipid profiles, thereby modulating levels of inflammation and oxidative stress and ultimately affecting the aging process. Therefore, investigating the impact of blood lipid-related dietary patterns on aging biomarkers from the perspective of overall dietary structure will offer theoretical support for developing more targeted dietary intervention strategies.

【Objectives】

1. To investigate the associations between RC and key aging biomarkers (leukocyte telomere length [LTL] and α-Klotho protein), explore influencing factors, and elucidate the potential roles of inflammation and oxidative stress in these associations.

2. To analyze the interaction between RC and aging biomarkers in the development of T2DM and assess their predictive values for T2DM risk.

3. To examine the effects of nutrient patterns on aging biomarkers and determine the roles of lipid parameters such as RC within these associations.

4. To construct blood lipid-related dietary patterns based on food groups, investigate their associations with aging biomarkers, and analyze the mediating roles of inflammation and oxidative stress.

In summary, this study uses abnormal lipid metabolism as a starting point to integrate aging biomarkers, T2DM, inflammation, oxidative stress, and dietary factors. It systematically explores the relationships and underlying mechanisms between abnormal lipid metabolism and aging, and establishes dietary intervention strategies based on lipid metabolism, thereby providing scientific evidence and feasible interventions for precision aging management.

【Methods】

1. Study Population: The study population was drawn from the “Rural Type 2 Diabetes Management Project” conducted in Changping District, Beijing. The first and third parts of the study are cross-sectional analyses involving 898 participants surveyed between 2014 and 2021. The second part is a prospective study with 236 participants who were non-diabetic at baseline in 2014 and were followed up 3 to 10 years later. The fourth part is also a cross-sectional analysis including 718 participants with no history of hyperlipidemia.

2. Data Collection and Assessment of Indicators: Participants completed standardized questionnaires to obtain demographic information. Fasting blood specimen were collected to assess biochemical indices including blood glucose, lipid profiles, liver and kidney function, and glycosylated hemoglobin (HbA1c). Besides, an oral glucose tolerance test (OGTT) with 75g of glucose was administered to determine glucose metabolism status. RC was calculated as total cholesterol (TC) minus low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C). Leukocyte telomere length was determined via real-time quantitative polymerase chain reaction (RT-qPCR), while α-Klotho protein, superoxide dismutase (SOD), and 8-hydroxy-2-deoxyguanosine (8-oHdG) were measured by enzyme-linked immunosorbent assay (ELISA). Additional inflammatory markers including tumor necrosis factor α (TNFα), interleukin-6 (IL-6), and interleukin-1β (IL-1β) were measured using multiplex assays.

3. Dietary Analysis: Dietary data were collected using 24-hour dietary recalls. Principal component analysis (PCA) was applied to 17 nutrients, involving protein, carbohydrates, fat, vitamins A/B1/B2/C/E, phosphorus, calcium, potassium, magnesium, sodium, iron, selenium, zinc, and copper, to extract NPs. Each nutrient pattern was named based on the nutrients with the higher absolute factor loadings. Dietary intake was categorized into 28 food groups, and blood lipid indicators RC and triglyceride (TG) were used as response variables in a reduced-rank regression to construct blood lipid-related dietary patterns. Factor loadings of food groups were examined, and those with higher absolute values were selected to characterize the dietary pattern and explain the response variables.

4. Statistical Methods: Adjusted linear regression analyses were employed to examine the associations of RC, NPs, and blood lipid-related dietary patterns with aging biomarkers. Potential nonlinear relationships were explored using restricted cubic spline (RCS) analysis. Logistic regression after adjusting for confounding factors and receiver operating characteristic (ROC) curve analyses were employed to explore the effects and predictive performance of RC and aging biomarkers on the development of T2DM. Mediation analyses were conducted to investigate the potential mechanisms involving inflammation and oxidative stress. Subgroup analyses were performed to identify potential modifying factors related to metabolic status.

【Results】

1. Associations between RC and Aging Biomarkers and Underlying Mechanisms

Among 898 participants stratified by RC quartiles, those in the highest RC group exhibited lower LTL and α-Klotho levels, along with higher levels of TNFα, IL-6, IL-1β, and SOD (all P<0.05). Through multivariate linear regression analyses, RC showed a negative association with both LTL (B [95% CI]: -0.194 [-0.290, -0.098]) and α-Klotho (B [95% CI]: -0.041 [-0.063, -0.019], both P<0.05), independent of age, sex, total energy intake, and metabolic parameters (including traditional lipid profiles). RCS analyses indicated nonlinear relationships between RC and both LTL (P for nonlinear = 0.007) and α-Klotho (P for nonlinear = 0.011), with inflection points at 1.441mmol/L and 1.323mmol/L, respectively. Below these inflection points, RC was negatively correlated with the aging biomarkers, whereas above the cut-off values, the associations were not significant. After further adjustment for inflammatory and oxidative stress markers, the association between RC and LTL was attenuated (B=-0.136, P<0.05) and the association with α-Klotho disappeared (B=-0.024, P>0.05). Mediation analyses indicated that TNFα and IL-6 mediated 17.35% and 16.56% of the association between RC and LTL, respectively, while an increase in SOD mediated 63.46% of the association between RC and α-Klotho. Subgroup analyses revealed that the negative correlations between RC and both aging biomarkers were more pronounced in younger participants. Sex-specific analysis showed that the association between RC and LTL was more evident in females, whereas the association with α-Klotho was more pronounced in males. Additionally, metabolic status influenced the relationship between RC and α-Klotho, particularly among individuals without diabetes, with TG levels <1.7 mmol/L, and with higher alanine aminotransferase (ALT) levels.

2. Predictive Value of Combined RC and Aging Biomarkers for T2DM

In this prospective study of 236 participants with a median follow-up of 7 years, 75 participants developed T2DM (progression group) while 161 did not (non-progression group). The individuals in the progression group had higher baseline RC levels and shorter LTL (both P<0.05) relative to those in the non-progression group. Elevated RC was associated with an increased risk of T2DM (OR [95% CI]:2.272 [1.050, 4.917], P<0.05), whereas longer LTL was associated with a decreased risk (OR [95% CI]: 0.626 [0.443, 0.885], P<0.05), in multivariate-adjusted logistic regression. No significant association was found between α-Klotho and T2DM risk. Mediation analysis revealed that LTL mediated 14.38% of the adverse effect of RC on T2DM risk. ROC curve analyses demonstrated that RC, LTL, and age individually had predictive value for T2DM risk (AUCs of 0.604, 0.618, and 0.635, respectively, all P<0.05), and their combined use significantly improved the predictive efficacy (AUC=0.709, P<0.05) with high sensitivity (83.6%). Subgroup analyses indicated that the associations between RC, LTL, and T2DM risk were more pronounced in females, individuals with prediabetes, and those with LDL-C ≥ 2.6 mmol/L, with LTL mediating approximately 24.02% of the association in females.

3. Nutrient Patterns, Aging Biomarkers, and the Role of Lipid Metabolism

Among the 898 participants, PCA of 17 nutrients extracted four nutrient patterns:“high protein–high micronutrients,” “high Fat–high sodium–low carbohydrate,” “high Vitamin C–high calcium, potassium, magnesium,” and “high iron and copper”patterns. Spearman correlation analysis indicated that the "high protein–high micronutrient" pattern and its core components, such as protein and selenium, were positively correlated with LTL (P<0.001), but negatively correlated with TC and RC (both P <0.001). Multivariate linear regression and RCS analyses demonstrated a linear positive association between the “High Protein–High Micronutrients” pattern and LTL (B [95% CI]: 0.080 [0.039, 0.120]; P for nonlinear=0.886), and a nonlinear association with α-Klotho (B [95% CI]: 0.005 [-0.005, 0.014]; P for nonlinear=0.019). After adjusting for RC, the association between this nutrient pattern and LTL was attenuated (B=-0.059, P>0.05). No significant associations were observed between the other three nutrient patterns and the two aging biomarkers. Through mediation analysis, RC was observed to mediate 22.37% of the positive correlation between the“High Protein–High Micronutrients” pattern and LTL.

4. Blood Lipid-Related Dietary Patterns, Aging Biomarkers, and the Roles of Inflammation and Oxidative Stress:

In 718 participants, reduced-rank regression using 28 food groups, with RC and TG as response variables, yielded a “blood lipid-related dietary pattern” characteristic of high intake of vegetable oil and salt, coupled with low consumption of wholegrains and dark green vegetables in the rural northern Chinese population. When participants were divided into tertiles based on dietary pattern scores, those in the highest tertile exhibited higher RC and TG levels; lower LTL and α-Klotho levels,along with higher levels of TNFα, IL-1β, and SOD (all P<0.05). Correlation analyses indicated that the dietary pattern was positively associated with RC and TG (all P<0.05). Multivariate linear regression analyses observed that the dietary pattern scores (as continuous variables) were negatively associated with LTL (B [95% CI]: -0.148 [-0.215, -0.081], P<0.001) and α-Klotho (B [95% CI]: -0.016 [-0.029, -0.002], P=0.022), with the strength of these associations increasing with higher scores (P for trend <0.001 and =0.025, respectively). After adjusting for inflammatory and oxidative stress markers, the associations of dietary pattern scores with LTL and α-Klotho were attenuated (B=-0.057, P=0.035) and no longer significant (B=-0.010, P=0.069), respectively. Mediation analyses indicated that TNFα and IL-1β mediated 12.07% and 22.22% of the association between the blood lipid-related dietary pattern and LTL, while IL-1β and SOD mediated 14.81% and 47.06% of its relationship with α-Klotho, respectively.

【Conclusions】

1. RC is negatively and nonlinearly associated with both LTL and α-Klotho, independent of traditional lipid parameters and various metabolic factors, with inflammation and oxidative stress playing significant mediating roles. Reducing RC may delay the aging process by mitigating inflammation or oxidative stress, offering new perspectives for the application of lipid metabolism in anti-aging interventions. Future strategies should be tailored to the characteristics of different populations.

2. Elevated baseline RC levels and shortened baseline LTL increase the risk of T2DM onset, independent of age, sex, blood pressure, and traditional lipid parameters, particularly among females, individuals with prediabetes, and those with LDL-C≥ 2.6mmol/L. Shortened baseline LTL partially mediated the adverse effect of elevated RC on T2DM risk, and this mediating effect was more pronounced in women. The combined use of RC, LTL, and age substantially enhanced predictive performance and sensitivity for incident T2DM, providing novel insights into T2DM early screening from the perspective of lipid metabolism and aging.

3. The “High Protein–High Micronutrients” pattern is linearly and positively associated with LTL, with RC partly mediating this association, thereby elucidating the complex interrelationships among nutrition, lipid metabolism, and aging. Nutritional interventions targeting protein and trace elements such as selenium may delay the aging process by improving lipid metabolism.

4. In the Chinese population, an adverse blood lipid-related dietary pattern characterized by high vegetable oil and salt intake and low consumption of whole grains and dark green vegetables is associated with telomere shortening and reduced α-Klotho levels. Mediation analyses suggest that this relationship may be driven by increased pro-inflammatory cytokines and oxidative stress. Optimizing dietary structure may beneficially influence aging through multiple pathways including improved lipid profiles, reduced inflammation, and decreased oxidative damage.

This study comprehensively investigates the intricate relationships among abnormal lipid metabolism, T2DM, dietary patterns, and aging from four innovative perspectives: biomarker associations, disease prediction, nutritional interventions, and dietary structure optimization, thereby providing new insights for aging management strategies