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Researchers Reveal Associations of Metabolomics Profile with Kidney Function Decline and Hyperuricemia Risk in Chinese Population

2019-09-17

Parallel with rapid nutrition transition and growing populations of aging and obesity, chronic kidney disease (CKD) and hyperuricemia have become increasing public health challenges with prevalence of both higher than 10% among adult Chinese. CKD and hyperuricemia could lead to kidney failure or gout, thus it is critical to have diagnosis and prevention in the early stage of diseases by identifying their risk factors and early biomarkers. However, few studies have investigated the links between metabolomic biomarkers to kidney function decline or hyperuricemia in prospective cohort settings. 

Recently, Clinical Journal of the American Society of Nephrology and Arthritis Care & Research online published collaborating works which revealed the associations of metabolomics profile with kidney function decline and hyperuricemia risk in Chinese population. These studies were jointly accomplished by Professor LIN Xu’s group from Shanghai Institute of Nutrition and Health of Chinese Academy of Sciences (CAS), and Professor ZENG Rong’s group from CAS Key Laboratory of Systems Biology, respectively entitled “Associations of plasma amino acid and acylcarnitine profiles with incident reduced glomerular filtration rate” and “Associations of amino acid and acylcarnitine profiles with incident hyperuricemia in middle-aged and older Chinese”. 

In the study, a gas or liquid chromatography coupled with mass spectrometry was applied to detect 22 amino acids and 34 free carnitines/acylcarnitines in the cohort sample of the Nutrition and Health of Aging Population in China. Wang Feijie, a Ph.D. student in Professor Lin’s group, analyzed the prospective associations of plasma metabolomic biomarkers with 6-year incident kidney function decline and hyperuricemia among participants who completed both baseline and a 6-yearr follow-up survey. Researchers found that among 1,765 participants free of kidney function decline at baseline, increased plasma cysteine, long-chain acylcarnitines (C14:1OH, C18, C18:2 and C20:4) and other acylcarnitines (C3DC and C10) were significantly associated with higher incident kidney function decline defined as estimated glomerular filtration rate (eGFR) < 60 ml/min/1.73 m2, independently of conventional risk factors including eGFR at baseline (Figure 1). Among 1, 621 participants free of hyperuricemia at baseline, increased plasma cysteine, glutamine, threonine and long-chain acylcarnitines (C18, C20 and C20:4) were significantly associated with higher incident hyperuricemia defined as uric acid >420μmol/L in men and >360 μmol/L in women, independently of conventional risk factors including uric acid at baseline. Related results were further verified by multivariate analyses (principal component analysis or network analysis) (Figure 2). In reduced rank regression, these metabolites were shown to be partially driven by intakes of the hyperuricemia associated foods like red and processed meat, and soy products, suggesting underlying mechanistic link of diet-metabolite-disease.  

Overall, these studies provide clue to early biomarkers, dietary factors and underlying mechanisms of kidney function decline and hyperuricemia, thus laying a foundation for their early diagnosis and prevention. 

These works were funded by grants of the Major Project of the Ministry of Science and Technology of China, the National Natural Science Foundation of China and the Chinese Academy of Sciences.

Figure 1: Associations of amino acid and acylcarnitine profile with (A) eGFR change, and (B) incident kidney function decline. (Image by Prof. LIN Xu's Group) 

Figure 2: Network analysis of amino acids and acylcarnitines. (A) Network heatmap; (B) Sub-network of three modules; (C) Associations between network modules and uric acid change; (D) Associations between network module and incident hyperuricemia. (Image by Prof. LIN Xu's Group) 

 

Media Contact: 
WANG Jin (Ms.) 
Shanghai Institute of Nutrition and Health,
Chinese Academy of Sciences 
Email: sibssc@sibs.ac.cn