Circulating metabolic biomarkers and risk of new-onset hypertension: findings from the UK Biobank

Author:

Zhou Yan-Feng1,Ye Yi-Xiang2,Chen Jun-Xiang2,Zhang Yan-Bo2,Wang Yi2,Lu Qi3,Geng Tingting2,Liu Gang3,Pan An2

Affiliation:

1. Department of Social Medicine, School of Public Health, Guangxi Medical University, Nanning, Guangxi Province

2. Department of Epidemiology and Biostatistics

3. Department of Nutrition and Food Hygiene, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China

Abstract

Objective: The evidence regarding the associations of circulating metabolic biomarkers with hypertension risk is scarce. We aimed to examine the associations between circulating metabolites and risk of hypertension. Methods: We included 49 422 individuals free of hypertension at baseline with a mean (SD) age of 53.5 (8.0) years from the UK Biobank. Nuclear magnetic resonance spectroscopy was used to quantify 143 individual metabolites. Multivariable-adjusted Cox regression models were used to estimate hazard ratios and 95% confidence intervals (CIs). Results: During a mean (SD) follow-up of 11.2 (1.8) years, 2686 incident hypertension cases occurred. Out of 143 metabolites, 76 were associated with incident hypertension, among which phenylalanine (hazard ratio: 1.40; 95% CI: 1.24–1.58) and apolipoprotein A1 (hazard ratio: 0.76; 95% CI: 0.66–0.87) had the strongest association when comparing the highest to the lowest quintile. In general, very-low-density lipoprotein (VLDL) particles were positively, whereas high-density lipoprotein (HDL) particles were inversely associated with risk of hypertension. Similar patterns of cholesterol, phospholipids, and total lipids within VLDL and HDL particles were observed. Triglycerides within all lipoproteins were positively associated with hypertension risk. Other metabolites showed significant associations with risk of hypertension included amino acids, fatty acids, ketone bodies, fluid balance and inflammation markers. Adding 10 selected metabolic biomarkers to the traditional hypertension risk model modestly improved discrimination (C-statistic from 0.745 to 0.752, P < 0.001) for prediction of 10-year hypertension incidence. Conclusion: Among UK adults, disturbances in metabolic biomarkers are associated with incident hypertension. Comprehensive metabolomic profiling may provide potential novel biomarkers to identify high-risk individuals.

Publisher

Ovid Technologies (Wolters Kluwer Health)

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