Abstract
While disrupted lipid metabolism is a well-established risk factor for hypertension in animal models, the links between various lipidomic signatures and hypertension in human studies remain unclear. We aimed to examine associations between plasma lipidomic profiles and prevalence of hypertension among 2248 community-living Chinese aged 50–70 years. Hypertension was defined according to 2020 International Society of Hypertension global hypertension practice guidelines and 2018 Chinese guidelines. In total, 728 plasma lipidomic species were profiled using high-coverage targeted lipidomics. After multivariate adjustment, including lifestyle, body mass index, blood lipids, and sodium intake, 110 metabolites from nine lipidomic subclasses showed significant associations with hypertension, among which phosphatidylethanolamines (PEs) had the strongest association. Eleven lipidomic signals for hypertension risk were further identified from the nine subclasses, including PE(18:0/18:2) (OR per SD, 1.49; 95% confidence intervals, 1.30–1.69), phosphatidylcholine (PC) (18:0/18:2) (1.27; 1.13–1.43), phosphatidylserine (18:0/18:0) (1.24; 1.09–1.41), lysophosphatidylinositol (18:1) (1.17; 1.06–1.29), triacylglycerol (52:5) (1.38; 1.18–1.61), diacylglycerol (16:0/18:2) (1.42; 1.19–1.69), dihydroceramide (24:0) (1.25; 1.09–1.43), hydroxyl-sphingomyelins (SM[2OH])C34:1 (1.19; 1.07–1.33), lysophosphatidylcholine (20:1) (0.86; 0.78–0.95), SM(OH)C38:1 (0.87; 0.79–0.96), and PC (18:2/20:1) (0.84; 0.75–0.94). Principal component analysis also showed that a factor mainly containing specific PEs was positively associated with hypertension (1.20; 1.09–1.33). Collectively, our study revealed that disturbances in multiple circulating lipidomic subclasses and signatures, especially PEs, were significantly associated with the prevalence of hypertension in middle-aged and elderly Chinese. Future studies are warranted to confirm our findings and determine the mechanisms underlying these associations.
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Availability of Data and Materials
The datasets used during the current study are not publicly available due to ethics restrictions, but are available from the corresponding author on reasonable request.
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Abbreviations
- BMI:
-
Body mass index
- CE:
-
Cholesteryl ester
- Cer:
-
Ceramide
- CI:
-
Confidence interval
- CRP:
-
C-reactive protein
- CV:
-
Coefficient of variation
- CVD:
-
Cardiovascular disease
- DAG:
-
Diacylglycerol
- DBP:
-
Diastolic blood pressure
- dhCer:
-
Dihydroceramide
- FDR:
-
False-discovery rate
- GlcCer:
-
Glucosylceramide
- HDL-C:
-
High-density lipoprotein cholesterol
- HexCer:
-
Hexosylceramide
- LacCer:
-
Lactosylceramide
- LC–ESI–MS/MS:
-
Liquid chromatography–electrospray ionization tandem mass spectrometry
- LCPUFA:
-
Long-chain polyunsaturated fatty acid
- LDL-C:
-
Low-density lipoprotein cholesterol
- LPC:
-
Lysophosphatidylcholine
- LPI:
-
Lysophosphatidylinositol
- MUFA:
-
Monounsaturated fatty acid
- NHAPC:
-
Nutrition and Health of Aging Population in China
- NO:
-
Nitric oxide
- OR:
-
Odds ratio
- PC:
-
Phosphatidylcholine
- PCA:
-
Principal component analysis
- PE:
-
Phosphatidylethanolamine
- PE-O:
-
Alkylphosphatidylethanolamine
- PE-P:
-
Alkenylphosphatidylethanolamine
- PS:
-
Phosphatidylserine
- PUFA:
-
Polyunsaturated fatty acid
- SBP:
-
Systolic blood pressure
- SD:
-
Standard deviation
- SFA:
-
Saturated fatty acid
- SM:
-
Sphingomyelin
- TAG:
-
Triacylglycerol
- TCH:
-
Total cholesterol
- TG:
-
Triglyceride
- T2D:
-
Type 2 diabetes
- VLCPUFA:
-
Very-long-chain polyunsaturated fatty acid
- WC:
-
Waist circumference
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Acknowledgements
We are grateful to Feijie Wang, Yiwei Ma, Quan Xiong, Shaofeng Huo, Huan Yun, Shuangshuang Chen, Boyu Song, Puchen Zhou, and Qianlu Jin of Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences for their kind assistance at various stages of this study. We especially acknowledge all the participants involved in this study.
Funding
The study was supported by the Strategic Priority CAS Project (XDB38000000), the Ministry of Science and Technology of China (2017YFC0909701), the National Natural Science Foundation of China (81561128018, 81700700, and 81970684), the Chinese Academy of Sciences (KSCX2-EW-R-10, KJZD-EW-L14-2-2), and Shanghai Municipal Science and Technology Major Project (2017SHZDZX01).
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ZHN and QQW contributed to data analysis and interpretation and writing the manuscript. YGL, DW, HZ, YPW, and XWY helped analyze the data. XL, LS, and RZ contributed substantially to study design and data supervision, to acquisition and interpretation of data, and to revising the article. All authors read and approved the final version to be published.
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The study was approved by the Institutional Review Board of the Institute for Nutritional Sciences, Chinese Academy of Sciences.
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Zhenhua Niu and Qingqing Wu are Co-first authors, who have equal contributions to this work.
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Niu, Z., Wu, Q., Luo, Y. et al. Plasma Lipidomic Subclasses and Risk of Hypertension in Middle-Aged and Elderly Chinese. Phenomics 2, 283–294 (2022). https://doi.org/10.1007/s43657-022-00057-y
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DOI: https://doi.org/10.1007/s43657-022-00057-y