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Metabolomic characterization of hypertension and dyslipidemia

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Abstract

Background

Hypertension and dyslipidemia are two main risk factors for cardiovascular diseases (CVD). Moreover, their coexistence predisposes individuals to a considerably increased risk of CVD. However, the regulatory mechanisms involved in hypertension and dyslipidemia as well as their interactions are incompletely understood.

Objectives

The aims of our study were to identify metabolic biomarkers and pathways for hypertension and dyslipidemia, and compare the metabolic patterns between hypertension and dyslipidemia.

Methods

In this study, we performed metabolomic investigations into hypertension and dyslipidemia based on a “healthy” UK population. Metabolomic data from the Husermet project were acquired by gas chromatography–mass spectrometry and ultra-performance liquid chromatography–mass spectrometry. Both univariate and multivariate statistical methods were used to facilitate biomarker selection and pathway analysis.

Results

Serum metabolic signatures between individuals with and without hypertension or dyslipidemia exhibited considerable differences. Using rigorous selection criteria, 26 and 46 metabolites were identified as potential biomarkers of hypertension and dyslipidemia respectively. These metabolites, mainly involved in fatty acid metabolism, glycerophospholipid metabolism, alanine, aspartate and glutamate metabolism, are implicated in insulin resistance, vascular remodeling, macrophage activation and oxidised LDL formation. Remarkably, hypertension and dyslipidemia exhibit both common and distinct metabolic patterns, revealing their independent and synergetic biological implications.

Conclusion

This study identified valuable biomarkers and pathways for hypertension and dyslipidemia, and revealed common and different metabolic patterns between hypertension and dyslipidemia. The information provided in this study could shed new light on the pathologic mechanisms and offer potential intervention targets for hypertension and dyslipidemia as well as their related diseases.

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Abbreviations

ALP:

Alkaline phosphatase

ALT:

Alanine aminotransferase

AST:

Aspartate aminotransferase

BMI:

Body mass index

CMP:

Cytidine monophosphate

DBP:

Diastolic blood pressure

DG:

Diglyceride

EI:

Electron impact

FDR:

False discovery rate

GGT:

Gamma-glutamyl transpeptidase

GC/MS:

Gas chromatography–mass spectrometry

HDLC:

High density lipoprotein cholesterol

LDH:

Lactate dehydrogenase

LDL:

Low density lipoprotein

LDLC:

Low density lipoprotein cholesterol

LPC:

Lysophosphatidylcholine

MG:

Monoglyceride

MSI:

Metabolomics Standards Initiative

OxLDL:

Oxidised low density lipoprotein

PLS-DA:

Partial least squares discriminant analysis

PC:

Phosphatidylcholine

RBC:

Red blood cell

VIP:

Variable importance in the projection

SBP:

Systolic blood pressure

SM:

Sphingomyelin

TC:

Total cholesterol

TCA:

Tricarboxylic acid

TG:

Triglyceride

TREM2:

Triggering receptor expressed on myeloid cells 2

UPLC/MS:

Ultra-performance liquid chromatography–mass spectrometry

WBC:

White blood cell

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Acknowledgements

We especially thank the team from the Husermet project for gathering and sharing all the data. In addition, this work was funded by National Natural Science Foundation of China (project number 81703316) and Natural Science Foundation of Jiangsu Province (project number BK20170350).

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Authors and Affiliations

  1. Department of Epidemiology and Biostatistics, School of Public Health, Medical College of Soochow University, 199 Renai Road, Suzhou, 215123, People’s Republic of China

    Chaofu Ke, Yuxia Zhang & Yueping Shen

  2. Suzhou Industrial Park Centers for Disease Control and Prevention (Institute of Health Inspection and Supervision), Suzhou, 215021, Jiangsu, People’s Republic of China

    Xiaohong Zhu

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  1. Chaofu Ke
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CK and YS conceived and designed the research; XZ and YS wrote the manuscript; CK and YZ performed the data analysis. All authors reviewed the manuscript.

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Correspondence to Yueping Shen.

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Ke, C., Zhu, X., Zhang, Y. et al. Metabolomic characterization of hypertension and dyslipidemia. Metabolomics 14, 117 (2018). https://doi.org/10.1007/s11306-018-1408-y

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