In this large prospective cohort study involving over 50,000 participants, we identified 15 plasma metabolites associated with lifestyle factors, the majority of which were lipids. Through enrichment analysis, we hypothesize that lifestyle factors may influence the linoleic acid metabolism pathway and the glycerolipid metabolism pathway, thereby affecting overall health. Subsequently, we employed accelerated failure time models to explore the impact of various factors, including metabolites, on the latent period of chronic kidney disease (CKD). Our findings provide new insights into the potential for early intervention and prevention of kidney disease, although further experimental and clinical studies are required to validate these results.
In our study, 15 plasma metabolites were associated with a comprehensive lifestyle, involving various fatty acids, lipoprotein subclasses, and derived markers, such as saturated fatty acids, monounsaturated fatty acids, polyunsaturated fatty acids, linoleic acid, triglycerides, HDL, LDL, and VLDL, among others. Furthermore, previous studies have shown that plasma metabolites associated with different lifestyle combinations play a key role in elucidating the metabolic mechanisms through which lifestyle affects health. For instance, a multi-cohort study identified the metabolomic profiles of the Alternative Healthy Eating Index (AHEI), revealing robust and positive associations between AHEI scores and fatty acid unsaturation, as well as the proportion and concentration of polyunsaturated fatty acids, including omega-3 fatty acids (particularly docosahexaenoic acid) and omega-6 fatty acids (especially linoleic acid). Conversely, AHEI scores exhibited negative correlations with concentrations of saturated fatty acids and monounsaturated fatty acids30. Another EPIC cohort study found that obesity can lead to alterations in metabolic profiles characterized by changes in urinary amino acids, sphingomyelins, glutamate, and various phosphatidylcholines31. Furthermore, other lifestyle factors such as smoking32, sleep33, alcohol intake34, and physical activity35were associated with variations in amino acids, fatty acids, lipoproteins, and fluid balance metabolites, implicating the inherent metabolic effects of lifestyle behaviors on health status from a metabolomics standpoint. Furthermore, based on our research findings, we speculate that lifestyle may primarily influence health by affecting lipid metabolism in the body. Anne-Julie Tessier et al. demonstrated in four large cohort studies that lifestyle metabolomic profiling reflected lipid metabolic pathways, enhancing predictive capabilities for overall mortality, cause-specific mortality, and longevity36. In a cohort study, researchers discovered associations between lifestyle factors and 81 plasma metabolites spanning various categories: lipids, lipoprotein subclasses, amino acids, fatty acids, ketone bodies, fluid balance-related metabolites, glycolysis-related metabolites, and inflammation-related metabolites37. The metabolites most significantly associated with lifestyle included concentrations of HDL particles, total choline, citrate, linoleic acid, omega-3 fatty acids, and phosphatidylcholine. Another cohort study from Spain found that an integrated lifestyle based on diet, physical activity, smoking status, alcohol consumption and BMI led to changes in creatinine, acetone, citrate, and some lipid metabolites38. Furthermore, a separate UK Biobank study revealed associations between lifestyle and numerous lipid metabolites in plasma, including docosahexaenoic acid, omega-3 fatty acids to total fatty acids percentage, monounsaturated fatty acids to total fatty acids percentage, and linoleic acid to total fatty acids percentage, align with the results of our present study19. Nevertheless, due to the inconsistent definitions of lifestyle combinations and the different coverage of metabolites measured in various studies, there may be heterogeneity in metabolic profiles. More in-depth studies, such as standardized lifestyle definitions, plasma metabolite assessments and long-term follow-up studies, are needed to provide a robust scientific foundation for developing more effective health strategies. Additionally, as the lifestyle-related metabolites we identified are largely derived data rather than direct metabolite concentrations, we selected key metabolites related to lifestyle for enrichment analysis, instead of using derived indices. For instance, we used linoleic acid rather than the “Linoleic Acid to Total Fatty Acids percentage” for enrichment analysis. Moreover, some metabolites are only labeled by broad categories (e.g., polyunsaturated fatty acids, monounsaturated fatty acids, saturated fatty acids) without specific KEGG IDs, which limits the precise identification of metabolic pathways. Therefore, future studies will need to achieve more accurate metabolite measurements and further validation of metabolic pathways.
In this study, we utilized accelerated failure time models to explore the factors influencing the onset of CKD. Among traditional risk factors, smoking, hypertension, diabetes, and high BMI remain significant predictors of CKD development. These findings highlight the importance of preventing CKD by extending the period of effective survival without the disease, emphasizing the need for proper management of chronic conditions and the maintenance of healthy lifestyle habits. Additionally, using NMR-based metabolomics, we conducted further analysis of plasma metabolites and observed an association between triglycerides in large LDL particles and the onset of CKD. This underscores the critical role of a low-fat diet and the management of lipid levels in supporting kidney health. Triglycerides in large LDL particles are associated with accelerated CKD progression. The mechanisms by which triglycerides in low-density lipoprotein (LDL) contribute to kidney damage have become an important research focus in chronic kidney disease (CKD). Studies have shown that triglyceride-rich lipoproteins (TRLs) are elevated in CKD patients and may accelerate kidney injury through multiple pathways. Firstly, elevated triglyceride levels are often accompanied by disturbances in lipid metabolism, leading to lipid deposition in kidney tissues, particularly in the renal tubules and interstitial areas. These deposits can trigger localized oxidative stress, increasing the generation of reactive oxygen species (ROS), which in turn causes cell damage and apoptosis39. Furthermore, the elevation of triglycerides may alter the composition and function of lipoproteins, making them more likely to induce immune and inflammatory responses, thus exacerbating local inflammation in the kidneys. The release of inflammatory cytokines such as TNF-α and IL-6 activates immune cells, further damaging renal tubular epithelial cells and promoting the progression of kidney dysfunction.[45] Moreover, the increase in triglycerides may impact fatty acid metabolism, leading to elevated levels of free fatty acids in the kidneys. These free fatty acids can promote the fibrotic process in kidney tissues through various mechanisms, ultimately leading to further deterioration of renal function. Specifically, triglycerides, by altering lipid and fatty acid metabolism, activate signaling pathways related to fibrosis, oxidative stress, and inflammation, which contribute to structural and functional damage in the kidneys40. Therefore, in kidney health management, adopting a comprehensive lifestyle intervention is crucial. In addition to recommending at least 150 min of moderate-intensity aerobic exercise per week, maintaining a healthy BMI, ensuring 7–9 h of high-quality sleep, limiting alcohol intake, and promoting smoking cessation, diet and blood lipid management play key roles in protecting kidney function. A low-fat diet should prioritize sources of unsaturated fatty acids, such as fatty fish, fish oil, and plant-based oils. These foods not only provide healthy fats but are also rich in omega-3 fatty acids, which have been shown to help reduce inflammation, improve cardiovascular health, and support kidney function. In contrast, intake of animal fats should be minimized, particularly from red meat, full-fat dairy products, and fried foods, as these foods tend to increase blood lipid levels, promote oxidative stress, and trigger inflammatory responses, which can accelerate kidney damage. Furthermore, adequate dietary fiber intake, a low-sodium diet, and sufficient hydration are also essential components of maintaining optimal kidney function.
This study boasted several strengths, including a substantial sample size and a prospective cohort design. Moreover, we collected participants’ comprehensive lifestyle data from UK Biobank to create lifestyle scores. Leveraging Lasso regression and the Random Forest algorithm, we identified relevant metabolites and evaluated their associations with CKD. Furthermore, we employed accelerated failure time (AFT) models to investigate the factors associated with the acceleration or deceleration of the latent period of chronic kidney disease (CKD). However, several limitations should be noted: Firstly, lifestyle data were collected at baseline through surveys, physical measurements, and self-reports, lacking information on potential lifestyle changes during follow-up, which may introduce estimation errors for incident CKD cases. Secondly, the generalizability of our findings may be limited due to specific study constraints. The investigation was confined to the United Kingdom, with predominantly White participants aged 40–69 years. Dietary and lifestyle factors in this population might differ from those in other regions and ethnic groups. Additionally, we lacked data on CKD incidence in other age groups or healthy populations, which could offer additional insights.
