Serum Lipids Profiling Perturbances in Patients with Stable Ischemic Heart Disease and Ischemic Cardiomyopathy

Background: Ischemic heart disease(IHD) is a common cardiovascular disorder associated with inadequate blood supply to the myocardium. Chronic coronary ischemia leads to ischemic cardiomyopathy (ICM). Despite their rising prevalence and morbidity, few studies have discussed the lipids alterations in these patients. Methods: In this cross-sectional study, we analyzed serum lipids profile in IHD and ICM patients using a lipidomics approach. Consecutive patients admitted to the hospital for stable IHD and ICM were enrolled. Serum samples were obtained after overnight fasting. Nontargeted metabolomics was applied to demonstrate lipids metabolic profile in control, stable IHD and ICM patients. Results: A total of 63 and 62 lipids were detected in negative and positive ion mode respectively. Among them, 16:0 Lyso PI, 18:1 Lyso PI in negative ion mode, and 19:0 Lyso PC, 12:0 SM d18:1/12:0, 15:0 Lyso PC, 17:0 PC, 18:1-18:0 PC in positive ion mode were significantly altered both in IHD and ICM as compared to control. 13:0 Lyso PI, 18:0 Lyso PI, 16:0 PE, 14:0 PC DMPC, 16:0 ceramide, 18:0 ceramide in negative ion mode, and 17:0 PE, 19:0 PC, 14:0 Lyso PC, 20:0 Lyso PC, 18:0 PC DSPC, 18:0-22:6 PC in positive ion mode were significantly altered only in ICM as compared to IHD and control. Conclusion: Using non-targeted metabolomic profiling, we have successfully identified a group of circulating lipids that were significantly altered in stable IHD and ICM. The lipids metabolic signatures shed light on potential new biomarkers and therapeutics for preventing and treating ICM.

Yet few studies have utilized metabolomics approach to describe metabolic profile and perturbances in IHD, especially during different stages of cardiac functions.
Metabolomics has emerged as a powerful tool for defining changes in both global and cardiac-specific metabolism that occur across a spectrum of cardiovascular disease states [6]. As an important branch of metabolomics, lipidomics describes the spatial and temporal alterations in the content and composition of different lipid molecular species [7]. Although metabolic disturbances have been well established in IHD, few studies have discussed metabolic alterations based on lipidomics.
It has been proven that cardiomyopathy is associated with profound changes in cardiac metabolism.
Pathological progression of ICM results in cardiac structural remodeling, leading to an increased reliance on glucose metabolism and decrease in fatty acid oxidation. [8,9] Moreover, during the transition from cardiac hypertrophy to failure, mitochondrial number and function progressively decline, leading to an overall decrease in the oxidative metabolites[10, 11] Metabolic disturbances have been previously in-depth investigated in heart failure. Yet few studies have analyzed metabolic profiles in ischemic cardiomyopathy, especially during the progression from IHD to ICM. Thus, elucidating lipids metabolic profile alteration and identifying novel circulatory markers are of critical importance in the treatment and evaluation of IHD and ICM.
In this study, by utilizing lipodomics approach, we sought to characterize and compare the serum lipids metabolic profile in stable IHD and ICM patients. We have found significant alterations in a number of lipids levels, which is more prominent in ICM patients. Altered serum lipids exhibited prognostic value for ICM and is closely correlated to clinical factors. Applied together, lipids profiling could be used to help identify patients in disease progression from IHD to ICM, and thus potentially add to our diagnostic armamentarium.

Study design and population
Consecutive patients admitted to the cardiology department of the First Affiliated Hospital of Xi'an Jiaotong University for chest pain who subsequently underwent coronary angiography from February 2018 to August 2018 were screened. IHD and ICM were defined according to the universal definition criteria by the American Cardiology College respectively [12]. IHD and ICM was diagnosed upon coronary angiography, echocardiography and laboratory assessment. The inclusion criteria were: (1) Confirmed clinical diagnosis of IHD and ICM; (2) Fully revasclarized. The exclusion criteria were: (1) Acute decompensated heart failure; (2) Acute myocardial infarction; (3) Unstable hemodynamics; (4) Hepatic, nephrotic, hematological or autoimmune disorders; (5) Severe noncardiac disease with expected survival of less than 1 year; (6) Cachexia; (7) Patients over the age of 80 years; (8)Unwillingness to participate.
Among more than 5000 patients screened, 642 patients met the inclusion and exclusion criteria, including 501 IHD and 141 ICM patients. Written informed consent was obtained from 364 patients. Of these, 25 IHD and 25 ICM patients were selected for serum lipidomics assessments. 25 healthy volunteers with coronary atherosclerosis less than 50% by angiography were randomly selected as control. Demographic and biochemical information was obtained as previously described [13][14][15] Serum sample preparation Serum samples were collected from IHD, ICM and control patients after coronary angiography. Venous blood was withdrawn the next morning after overnight fast and immediately centrifuged at 3000 rpm for 10 min at 4 °C. Serum was separated and stored at − 80 °C and aliquots were thawed for further processing as previously described [13,15].
Individual lipids levels among three groups were compared using one-way ANOVA. Data were presented as mean ± SE. P-values < 0.05 were considered as significant * <0.05, ** <0.01, and *** <0.001. Receiver operating characteristics(ROC) was used and areas under the ROC curve(AUC) were calculated to explore the discriminative capability of different lipids to identify ICM. Pearson analysis was performed to compare the interrelation between lipids and biochemical indicators and heat map was created using R studio.

Baseline characteristics
A total of 75 patients were enrolled in the study, including 25 IHD, ICM and 25 control patients. Table 1 describes the demographic and biochemical characteristics of the enrolled patients. The mean age was 59.89 ± 16.81 for ICM, 60.48 ± 8.94 for IHD and 52.71 ± 16.09 for control participants. The mean left ventricular ejection fraction (LVEF) was 34.53 ± 7.57 for ICM, 64.14 ± 9.27 for IHD and 68.30 ± 5.46 for control patients. No significant difference at baseline were seen in age, heart rate(HR), aspartate transaminase(AST), alanine aminotransferase(ALT), creatine(CRE), total cholesterol(TC), triglycerides(TG) high and low density lipoprotein cholesterol(HDL-C, LDL-C).

Nontargeted Lipidomics Analysis
Firstly, we employed PLS-DA for profile visualization and differentiation among the multiple groups.
The initial overview of global metabolic profiles as revealed by PLS-DA scores plot indicated that lipids among IHD, ICM and control group were generally correlated but to some extent separable, which is more prominent for lipids in positive ion model (Fig. 1). The heatmap overview for the serum lipids levels were shown in supplemental figure S1 and S2. The variable importance in projection(VIP) for lipids in negative and positive ion mode were shown in Fig. 1C and Fig. 1D, which indicated the importance in projection of listed lipids.
To identify the individual lipids levels, we compared the lipids levels in negative and positive ion modes among IHD, ICM and control patients using one-way ANOVA (Fig. 2). A total of 63 lipids were detected in negative ion mode (Supplementary table S1

Interrelation between lipids and clinical characters
At last, we explored the interrelationship between the significantly altered lipids and the clinical phenotype. Figure 5 showed the heatmap of the Pearson's correlation coefficients between age, HR, blood pressure, EF, hepatic function, renal function, serum lipid levels, thyroid function and lipids profile in negative ion mode (Fig. 5A) and positive ion mode (Fig. 5B). Red blots indicated the highest positive coefficient of 1 and blue blots indicated the lowest negative coefficient of − 1. It was noteworthy that the 16:0 ceramide and 18:0 ceramide were both significantly and negatively correlated to renal function as indicated by serum creatine. It was also quite interesting to notify the prominent negative correlation between systolic blood pressure and nearly all altered lipids in positive ion mode except for 18:0-22:6 PC.

Discussion
In this study, metabolic profile and the network of serum lipids were analyzed in IHD and ICM patients. Lipids metabolic perturbance was observed in both IHD and ICM based on the following results: 1) A number of lipids were altered in IHD and ICH; 2) Lipids metabolic alteration was more significant in ICM and most of altered serum lipids also showed significant predictive value for ICM; 3) Serum lipids profile exhibited interrelation to clinical features to ICM patients. It is also interesting to notify that, based on lipidomics approach in positive ion mode, significantly altered lipids are closely negatively related to systolic blood pressure, although not to cardiac ejection fraction. It is well known that sBP is regulated by cardiac contraction function, cardiac output, and aortic resilience. As cardiac ejection fraction showed no correlation to lipids both in negative and positive ion mode, and most of correlated lipids ascribe to phosphocholine, we suppose that decreased aorta resilience, especially during ICM, is associated with lower phosphocholine. However, the hypothesis from this cross-sectional observative study warrants further validation.
The novelty of the current study is that we have provided new lipidomic alteration evidence as heart undergoes transition from IHD to ICM. The term ICM describes significantly impaired left ventricular function resulting from IHD. Previous analyses of conventional metabolism and circulating metabolites have confirmed metabolic disturbances as heart undergoes structural and functional change from IHD to ICM [29,30]. Cardiac pathological structural remodeling has resulted in reprogramming of cardiac metabolic pathways. The metabolic consequences of ICM have been examined in a wide variety of experimental animal models. Present analysis has indicated that serum lipids have undergone profound alterations as myocardial ischemia progressing to myopathy. The altered lipids could serve as potential biomarkers for predicting progression and prognosis of ICM. Identification for deeper molecular mechanism could be helpful for understanding pathophysiologic alterations.
Recent advances in metabolic profiling technologies have enhanced the feasibility of high-throughput patient screening for the diagnosis of disease states[31]. However, applying global metabolomics approach to explore cardiovascular disease are still lacking, and prior studies have generally assayed relatively limited subsets of metabolites in focused approaches. In the present study, we utilized nontargeted metabolomics analysis to investigate lipidomic alterations in patients with different levels of myocardial ischemia. Circulating lipids are found to participate as regulatory signals and could be potential biomarkers for ICM. The large-scale metabolic profiling approaches have been recognized as a more comprehensive survey to better inform underlying biological processes and identify potential biomarkers for disease progression in the present analysis.
Our study has several limitations. Although we have studied 3 major groups along the myocardial spectrum, the cohort size for each group is relatively limited, and the selection and observation bias could not be easily excluded. In addition, serum lipids alterations are based on non-targeted metabolic approach and warrant further confirmation by targeted metabolomics measurement.
Moreover, the present investigation is agnostic to tissue source of circulating metabolites. Thus, molecular and biochemical confirmation are also required to further explain the exact metabolic pathway alterations. Large-scale studies are also necessary to validate the predictive function of lipids for disease phenotype.

Conclusion
In this study, we have demonstrated the application of lipidomics platform to better understand pathogenic progression from IHD to ICM. Lipidomics profile was more significantly altered as myocardial ischemia progressed to ischemic cardiomyopathy. The lipids metabolic signatures also provide novel biomarkers for preventing and diagnosing IHD and ICM.

Supplementary Files
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