Coronary heart disease (CHD) is a major public health problem worldwide, contributing to 180 million disability-adjusted life years and 9.14 million deaths annually (Jeemon et al., 2021). According to Global Burden of Disease study estimates, China accounts for about 38.2% of the increased deaths as a result of CHD in the world (Zhou et al., 2019; Roth et al., 2020). With the aging of population, the prevalence of CHD continues to increase (Tzoulaki et al., 2016; Wirtz et al., 2016; Wang et al., 2017). Epidemiological investigations have shown that various risk factors, including smoking, alcohol intake, diabetes, hypertension, obesity, and family history, contribute to CHD occurrence and development (Dinicolantonio et al., 2016; Khera and Kathiresan, 2017). Such investigations have facilitated the development of prevention and treatment strategies, leading to a reduction in mortality rates. Coronary angiography is the gold standard method to diagnose CHD; however, it is not only invasive and expensive but also unsuitable for early risk screening at a large scale. Thus, a non-invasive, safe, and effective clinical method needs to be developed for the early diagnosis of CHD.

Metabolites, which are downstream products of metabolic reactions and include very low-density lipoproteins, low-density lipoproteins, and triglyceride (TG)-rich lipoproteins, are involved in lipid oxidation and plaque formation, and they have been associated with a high risk of CHD (Ambrose et al., 1985; Pongrac et al., 2020). However, the roles of these metabolites identified from epidemiological studies are unclear; thus, they cannot be used for the early diagnosis of CHD. The development of serum metabolic biomarkers for diagnosing CHD is therefore highly desirable.

Metabolomics refer to global analyses of small molecule metabolites in a biological system (Nicholson and Lindon, 2008). High-throughput metabolomics-based methods have been widely employed for screening novel biomarkers and elucidating the multiple targets and metabolic pathways of heart disease (Jiang et al., 2020; Deidda et al., 2021; Gladding et al., 2021). Further, metabolic profiling provides integrative information on physiological as well as pathological changes (Mamas et al., 2011; Johnson and Gonzalez, 2012). Few previous studies have indicated the significance of metabolomics in the screening of biomarkers in several diseases, including Alzheimer’s disease (Sato et al., 2012; Trushina et al., 2012; Polis and Samson, 2020), diabetes (Yan et al., 2020), tuberculosis (Albors-Vaquer et al., 2020; Luies and du Preez, 2020), and cancer (Conroy et al., 2020; Ishak et al., 2020; Wang et al., 2020). Paynter et al. (2018) identified that metabolites were significantly dysregulated in CHD, and could act as predictors of incident CHD in women. Dugani et al. (2021) found that the lipid, inflammatory, and metabolic biomarkers were associated with age at onset for incident CHD in women. However, CHD led to much more death in men than women. Meanwhile, due to the differences in diet structure and race between the east and the west countries, the results cannot fully reflect the metabolomic changes of CHD in Chinese patients.

In this metabolomics-based study, our objective was to identify serum metabolic biomarkers that could be used for the early diagnosis of CHD. Further, a clinical model was developed and validated based on logistic regression and fold cross-validation analyses.

Coronary heart disease is a complex human disease associated with inflammation and oxidative stress, and its onset is related to diverse environmental and genetic factors. Its incidence is increasing each year, consequently leading to a major socioeconomic burden. Advancements in metabolomics have facilitated the elucidation of potential mechanisms underlying CHD development and progression. In this study, we performed UM and TM analyses to detect differential metabolites between CHD and HCs. Our findings indicated that oxyneurine, acetylcarnitine, and PC(17:0/0:0) were significantly dysregulated in patients with CHD. Furthermore, the inclusion of oxyneurine, TG, and weight in our clinical model markedly increased its robustness (AUC = 0.731), suggesting that they can serve as biomarkers for the early diagnosis of CHD.

Oxidative stress evidently plays a crucial role in atherosclerotic cardiovascular diseases, and some of its effects are mediated by lipid oxidation (Pouralijan et al., 2019; Chandler et al., 2020; Gianazza et al., 2021). Herein KEGG pathway analysis showed that differential metabolites were associated with the phosphotransferase system, bile secretion, insulin secretion, and cholesterol metabolism. However, there were also different roles on the activation of pathways. For example, the upregulation of acetylcholine was associated with bile secretion, neuroactive ligand-receptor interaction, synaptic vesicle cycle, cholinergic synapse, regulation of actin cytoskeleton, salivary secretion, gastric acid secretion, and pancreatic secretion. However, the downregulation of glycocholate, was not only involved in bile secretion, but also associated with cholesterol metabolism, secondary bile acid biosynthesis, primary bile acid biosynthesis. These results indicated that the dysregulated metabolites constituted the interaction network of metabolic-related signaling pathways, which may involve in progression of CHD.

Four dysregulated metabolites–oxyneurine, acetylcarnitine, PC(17:0/0:0), and isoundecylic acid–showed significant differences in their abundance levels between the CHD patient and HC groups. Oxyneurine, a methyl glycine derivative and a commonly used nutrient supplement, shows antioxidant activity in animals and plants; it has also been reported to increase plasma glutathione peroxidase levels and regulate insulin secretion (Goncalves et al., 2020; Hall et al., 2020; Hassanpour et al., 2020; Sofy et al., 2020). Acetylcarnitine, a product of the reaction between acetyl-CoA and carnitine in mitochondria, is an effective antioxidant and anti-inflammatory marker. It has been found to attenuate arsenic-induced oxidative stress and hippocampal mitochondrial dysfunction, modulate the antioxidant defense capacity, and protect hippocampal neurons from oxidative damage (Farrell et al., 1986; Keshavarz-Bahaghighat et al., 2018). PC(17:0/0:0), a lysophospholipid, is involved in the acylation cycle and regulates the composition of lipids and sugars (Lingwood and Simons, 2010). Isoundecylic acid has been reported to exhibit 5-lipoxygenase inhibitory activities in vitro (Ohkuma et al., 1993). Based on this information, it appears that the four aforementioned dysregulated metabolites play a pivotal role in lipid oxidative stress in patients with CHD; thus, targeting them may be a novel approach for the clinical treatment of CHD. Nevertheless, further studies are warranted to elucidate their precise role and underlying mechanisms.

In the current study, we further detected changes in metabolic profiles by performing UM and TM analyses. A metabolite-based clinical model was developed; however, as isoundecylic acid was not found in HMDB, only oxyneurine, acetylcarnitine, and PC(17:0/0:0) were subjected to TM analysis. The role of isoundecylic acid needs to be further explored. Finally, as the clinic model was validated using a small sample, its sensitivity and specificity warrant deeper investigations.

To summarize, we found that oxyneurine, acetylcarnitine, PC(17:0/0:0), and isoundecylic acid were dysregulated in patients with CHD, which is suggestive of their involvement in the development of this chronic disease. Moreover, using the combination of serum oxyneurine, TG, and weight seems promising for the early diagnosis of CHD.

The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding authors.

The studies involving human participants were reviewed and approved by the Ethics Committee of the Dongguan Tungwah Hospital. The patients/participants provided their written informed consent to participate in this study.

HJ, LL, WC, BC, and HL performed all experiments, prepared the figures, and drafted the manuscript. HJ, SW, and YL participated in data analyses and interpretation. HJ and MW designed the study and participated in data analyses. All authors have read and approved the manuscript.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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