Plasma metabolic signature of cardiovascular and cerebrovascular diseases from a large cohort study

doi:10.3969/j.issn.1674-8115.2022.03.001

Abstract

Abstract: Objective

·To explore the metabolic differences for the occurrence and development of cardiovascular and cerebrovascular diseases, the study performed the plasma metabolic analysis by nano-enhanced laser desorption ionization-mass spectrometry (NELDI-MS) on a large cohort.

Methods

·People were enrolled from general population establishment and follow-up cohort in Pudong New Area, Shanghai. Plasma samples were prospectively collected from 14 419 cohort people who met the criteria from February to August 2019. All the cohort people were divided into coronary heart disease (CHD) group (n=1 608), stroke group (n=461), cardiovascular and cerebrovascular diseases (CHD+stroke) group (n=145) and the control group (n=12 205). The plasma metabolic fingerprints (PMFs) of the enrolled samples were collected by NELDI-MS and then analyzed by statistical analysis for identifying the typical metabolic biomakers in patients with stroke, patients with CHD, and patients with both CHD and stroke.

Results

·Three hundred and forty-five metabolic signal peaks were extracted as PMFs. Six metabolic biomarkers with differential regulations were identified as the potential risk factor for cardiovascular and cerebrovascular diseases respectively by mass spectrometry data analysis. Further, the six metabolic biomarkers were mapped into the altered ketone body and fatty acid metabolism clusters. In the cluster of ketone body metabolism, the intensities of amidosulfonic acid, acetoacetic acid and methylmalonic acid were significantly increased in patients with CHD, but significantly decreased in patients with stroke and cardiovascular cerebrovascular diseases. In the cluster of fatty acid metabolism, the intensities of glucose, galacturonic acid and α-linolenic acid were significantly decreased in patients with cardiovascular and cerebrovascular diseases, but significantly increased in patients with stroke. According to the above six metabolic biomakers, three related metabolic pathways were identified in the cluster of ketone body metabolism, and two related metabolic pathways were identified in the cluster of fatty acid metabolism.

Conclusion

·The novel solid-phase MS approach used in this study has realized the high-efficiency collection of PMFs in a large cohort of people. Six plasma metabolic biomarkers with differential regulation are identified in cohort people with cardiovascular and cerebrovascular diseases, shedding light on the molecular pathological mechanisms of cardiovascular and cerebrovascular diseases from metabolic perspectives. It is expected to provide metabolic clues for the pathogenesis of cardiovascular and cerebrovascular diseases.

Key words: cardiovascular and cerebrovascular disease, coronary heart disease (CHD), stroke, plasma metabolic fingerprint (PMF), metabolomics, biomaker

CLC Number:

R540.4

ZHANG Mengji, HUANG Lin, LI Zheng, MA Zhuoran, WEI Lin, YUAN Ancai, HU Liuhua, ZHANG Wei, QIAN Kun, PU Jun. Plasma metabolic signature of cardiovascular and cerebrovascular diseases from a large cohort study[J]. Journal of Shanghai Jiao Tong University (Medical Science), 2022, 42(3): 259-266.

Figures/Tables 5

TrendMD

References 23

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Item	Stroke （n=461）	CHD （n=1 608）	Stroke+CHD （n=145）	Control （n=12 205）	P value
Gender/n （%）					0.000
Male	220 （47.7）	587 （36.5）	50 （34.5）	5 861 （48.0）
Female	241 （52.3）	1 021 （63.5）	95 （65.5）	6 344 （52.0）
Age/year	69.0 （58.0‒90.0）	69.0 （55.0‒89.0）	72.0 （59.0‒87.0）	67.0 （39.0‒96.0）	0.000
Body fat percentage/%	24.7 （16.7‒34.3）	24.6 （15.8‒50.0）	24.5 （17.7‒32.4）	24.3 （12.70‒49.92）	0.000
Height/cm	160.0 （126.0‒183.0）	160.0 （100.0‒184.0）	159.0 （143.0‒175.0）	162.0 （123.0‒193.0）	0.000
Weight/kg	63.7 （40.7‒101.8）	63.0 （36.0‒120.0）	63.0 （39.8‒89.0）	64.0 （34.7.0‒117.5）	0.206
Hypertension/n （%）	114 （24.7）	451 （28.0）	31 （21.4）	5 459 （44.7）	0.000
Diabetes/n （%）	342 （74.2）	1 280 （79.6）	111 （76.6）	10 351 （84.8）	0.000
Hyperlipidemia/n （%）	346 （75.1）	1 311 （81.5）	97 （66.9）	11 280 （92.4）	0.000

Item	Stroke （n=461）	CHD （n=1 608）	Stroke+CHD （n=145）	Control （n=12 205）	P value
Gender/n （%）					0.000
Male	220 （47.7）	587 （36.5）	50 （34.5）	5 861 （48.0）
Female	241 （52.3）	1 021 （63.5）	95 （65.5）	6 344 （52.0）
Age/year	69.0 （58.0‒90.0）	69.0 （55.0‒89.0）	72.0 （59.0‒87.0）	67.0 （39.0‒96.0）	0.000
Body fat percentage/%	24.7 （16.7‒34.3）	24.6 （15.8‒50.0）	24.5 （17.7‒32.4）	24.3 （12.70‒49.92）	0.000
Height/cm	160.0 （126.0‒183.0）	160.0 （100.0‒184.0）	159.0 （143.0‒175.0）	162.0 （123.0‒193.0）	0.000
Weight/kg	63.7 （40.7‒101.8）	63.0 （36.0‒120.0）	63.0 （39.8‒89.0）	64.0 （34.7.0‒117.5）	0.206
Hypertension/n （%）	114 （24.7）	451 （28.0）	31 （21.4）	5 459 （44.7）	0.000
Diabetes/n （%）	342 （74.2）	1 280 （79.6）	111 （76.6）	10 351 （84.8）	0.000
Hyperlipidemia/n （%）	346 （75.1）	1 311 （81.5）	97 （66.9）	11 280 （92.4）	0.000

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