Throughout human history, cardiovascular illness has been responsible for a disproportionately high number of fatalities and impairments. According to statistics provided by the World Health Organization (WHO), cardiovascular diseases (CVDs) are responsible for the deaths of 17.9 million people each year. This figure represents 31% of the total death toll that can be ascribed to all causes throughout the globe (1,2). A "biomarker" is an indication capable of being analysed objectively and may be used to ascertain normal biological or pathological processes and pharmacological responses to treatments. A growing body of research is pointing to biomarkers as a viable tool for detecting risk factors for cardiovascular disease and monitoring the progression of the illness. Such an instrument might be used to monitor the progression of the ailment (3). Certain biomarkers found relatively recently and have shown their potential in recent years may make it possible to identify cardiac illness at an earlier stage and classify individuals according to the likelihood that they will acquire the condition within the next few years (4). A biomarker that is deployed on a large scale will possess high levels of sensitivity and specificity, in addition to detection methods that are repeatable, standardized, and cost-effective.

Much research has been carried out to investigate, pinpoint, validate, and use biomarkers for cardiovascular disease in genomics, proteomics, and metabolomics. Researchers who have been performing genome-wide association studies (GWAS) have discovered significant loci that are related to cardiovascular disease. These loci are highly beneficial for predicting and avoiding the risk of sickness among potential patients (5). According to the findings of a genome-wide association study (GWAS), a single nucleotide polymorphism located at chromosome is responsible for the connection between atherosclerotic stroke in major arteries. Magnetic resonance imaging (MRI) was utilized to conduct a meta-analysis that focused on individuals who had been diagnosed with a lacunar stroke. The results of this research revealed genetic loci. These results were helpful to screen individuals at high risk for cardiovascular disease (6). The proteomics-based search for biomarkers of cardiovascular disease is one use of this technique. Growth differentiation factor 15, renal damage molecule, and WAP 4-disulfide core domain protein 215 are some of the biomarkers that fall under this category. These genes and proteins related to cardiovascular disease led to a better knowledge of the pathophysiology and provide major diagnostic targets (7).

The role of anomalies in lipid metabolism, including lipid synthesis, breakdown, and regulation in the beginning stages of atherosclerosis, inflammation, and other disorders connected to the cardiovascular system, is becoming more recognized. New biomarkers, like oxidized lipoproteins, lipid ratios, and certain lipid species (like ceramides, phospholipids, and sphingolipids), have made it much easier to predict and understand cardiovascular disease (CVD) risk beyond the classic signs (8). This study tends to explore these novel biomarkers offers the potential to enhance risk stratification, enable earlier detection, and support the development of personalized therapeutic strategies for individuals at risk.

Aim of the study

To evaluate the significance of new lipid biomarkers in lipid metabolism and their relationship to cardiovascular disease risk, to improve CVD risk assessment, early detection, and preventative measures.

Objective of the Study

To identify and analyse novel lipid biomarkers associated with lipid metabolism that are linked to cardiovascular disease risk.

The study was planned to be a cross-sectional longitudinal observational study. Using established and emerging lipid biomarkers, the lipid profiles of a group of 200 people with varying degrees of cardiovascular disease risk characteristics were analysed. Participants were recruited from various sources, including general population screenings and outpatient cardiology clinics. This study's primary purpose was to assess the risk of cardiovascular disease by comparing the predictive value of new lipid biomarkers to that of classic lipid indicators.

Inclusion Criteria

200 participants in this research aged 35 to 70 years were selected. Within this age range, there is a greater incidence of variables that are associated with cardiovascular risk. People were eligible to take part in the study if they fulfilled one of two criteria concerning cardiovascular disease (CVD): either they had a confirmed diagnosis of CVD (such as a heart attack, stroke, or coronary artery disease), or they had two risk factors for CVD (such as diabetes, high cholesterol, or a hereditary predisposition for CVD). The participants' health had to be stable, meaning they couldn't have been hospitalized or diagnosed with a major disease during the last three months. Before being included in the research, each participant was required to provide their written approval as part of the protocol for obtaining informed consent.

Exclusion Criteria

The following criteria were used to exclude patients from the study:

• Patients with chronic inflammatory diseases (e.g., rheumatoid arthritis, lupus) or other systemic diseases that may affect lipid metabolism.
• Individuals on lipid-lowering medications such as statins or fibrates, unless the medication has been taken for at least 6 months prior to the study and lipid levels have stabilized.
• Pregnant or lactating women due to potential alterations in lipid metabolism during pregnancy and lactation.
• Participants with severe renal or hepatic dysfunction as these conditions may impact lipid profiles.
• Participants with a history of cancer or undergoing active cancer treatment, as cancer and chemotherapy can significantly affect lipid metabolism.

Data Collection

Clinical examination and laboratory analysis are essential components of the data collection approach. The participants' demographic information, medical history, and lifestyle information (including whether they smoked, what they ate, and how much physical exercise they did) were collected using structured questionnaires. Traditional lipid indicators, such as total cholesterol, low-density lipoprotein (LDL), high-density lipoprotein (HDL), and triglycerides, as well as new lipid biomarkers, such as ceramides, phospholipids, sphingolipids, and oxidized lipoproteins, were evaluated in blood samples that were collected after a fast of twelve hours. Processing and analysis of the blood samples were carried out with high-performance liquid chromatography and mass spectrometry to guarantee accurate quantification of lipid species.

Data Collection

Statistical software such as SPSS and R to analyse the data to determine the relationship between lipid biomarkers and the risk of cardiovascular disease were used. Descriptive statistics were used to offer a concise summary of the demographic and clinical features of the people. The mean, the standard deviation, and the frequencies are all things that are included in this data collection. Univariate and multivariate modelling techniques were used in this study to determine the predictive utility of new lipid biomarkers. The predictive ability of these investigations was compared to that of more conventional lipid markers, and the results were presented. To determine the degree of sensitivity and specificity of these biomarkers in terms of their ability to predict the likelihood of cardiovascular disease, we developed receiver operating characteristic (ROC) curves. Based on a p-value that was lower than 0.05, statistical significance was evaluated for every analysis.

Table 1: Demographic and Clinical Characteristics of the Study Population

The demographic and clinical features of the study cohort are summarized in Table 1 in a manner that is both short and comprehensive. Older individuals who had a higher body mass index (BMI) and had a higher incidence of hypertension, diabetes, and smoking were found to be in the high cardiovascular disease risk group. This group was distinguished from the low cardiovascular disease risk group. It was shown that each of the parameters differed from the others in a substantial way, which indicates that these characteristics are associated with an elevated risk of cardiovascular disease.

Table 2: Lipid Biomarkers in Low and High Cardiovascular Risk Groups

A comparison of the lipid biomarkers presented in the groups at low risk and those at high risk for cardiovascular disease is shown in Table 2, which can be seen below. Even though HDL cholesterol was lower, the high-risk group had considerably higher total cholesterol levels, LDL cholesterol, triglycerides, ceramides, and sphingolipids. Additionally, oxidized LDL cholesterol was much higher. Because every comparison exhibited a statistically significant difference (p < 0.05), these biomarkers might be used to differentiate between persons at a low risk of cardiovascular disease and those at a high risk of developing cardiovascular disease.

Table 3: Multivariate Regression Analysis of Lipid Biomarkers for Predicting CVD Risk

Table 3 shows the findings of a multivariate regression analysis are shown. According to these findings, there is a correlation between certain lipid markers and an elevated risk of cardiovascular disease. On the other hand, a negative beta coefficient for HDL cholesterol indicates that greater HDL levels are associated with a lower risk of cardiovascular disease (CVD). As a result of positive beta coefficients for total cholesterol, low-density lipoprotein (LDL), ceramides, and oxidized LDL, it may be inferred that greater levels of these biomarkers are linked to an increased risk of cardiovascular disease (CVD). The study's results demonstrated that every single biomarker had a substantial impact on predicting the risk of cardiovascular disease (p < 0.05). Among these biomarkers, ceramides and oxidized LDL came up as having the greatest odds ratios, which indicates that they are highly connected with cardiovascular risk.

Table 4: Receiver Operating Characteristic (ROC) Curve Analysis of Biomarkers

Table 4 presents the findings of the research conducted on the ROC curve. Within the scope of this study, several biomarkers associated with predicting cardiovascular disease (CVD) risk were examined. Compared to more traditional biomarkers such as total cholesterol and LDL, the area under the curve (AUC) values for ceramides and oxidized LDL were the greatest. This indicates that these biomarkers are more predictive in general. The oxidized LDL and ceramides have shown good sensitivity and specificity, which raises the possibility that these chemicals might be useful new biomarkers for evaluating the risk of cardiovascular disease.

According to this study's findings, novel lipid biomarkers may play a significant role in the development of cardiovascular disease (CVD). These biomarkers include ceramides and oxidize bad cholesterol, among others.  Total cholesterol, triglycerides, and very low-density lipoprotein (HDL) and very low-density lipoprotein (LDL) cholesterol are the fundamental lipid indicators that are used to assess the likelihood of developing cardiovascular disease (CVD). The findings of this study lend credence to the substantial prognostic significance of ceramides and provide more data about the association between ceramides and the early stages of the evolution of atherosclerosis. According to ROC statistics, ceramides have a bigger area under the curve (AUC), indicating they are more predictive than other substances. The following illustration shows that ceramides are superior to other substances in their predictive capabilities. Oxidative stress and lipid peroxidation are two crucial factors that play a significant role in the development of early atherosclerosis. The oxidized low-density lipoprotein (LDL) marker offers significant data regarding these processes. The presence of lipid peroxidation characterizes every one of these processes. For this reason, the hypothesis that lipoprotein oxidative alteration plays a role in the development of cardiovascular disease is gaining significant support.

Research conducted in recent years has shown that ceramides and sphingolipids play a significant part in determining the likelihood of developing cardiovascular disease. As proven by Hilvo et al., who established that ceramides may independently predict cardiovascular events and mortality (9), clinical risk stratification may benefit from ceramides. This is shown by the study that will be presented in the next sentence. The findings of this research provide credence to the hypothesis that ceramides are associated with a larger odds ratio and a greater degree of predictive power than traditional lipid markers. The hypothesis that oxidized LDL acts as a marker of cardiovascular risk is supported by the findings of research conducted by Holvoet et al., for instance, which discovered a high connection between oxidized LDL levels and coronary artery disease (10). This research adds to the growing body of data that oxidized LDL is associated with an elevated risk of cardiovascular disease. It does so by building on the work that has been done in the past.

According to the regression analysis presented in this study, novel biomarkers such as oxidized LDL and ceramides continue to operate as powerful predictors of the risk of cardiovascular disease. This is the case even after considering any factors that may cause confusion. The findings of this research provide more evidence that these markers have the potential to provide additional information that helps supplement standard lipid profiles. This research discovered that there is a negative correlation between high-density lipoprotein (HDL) cholesterol and the risk of cardiovascular disease. This finding aligns with earlier studies showing that greater HDL levels protect against cardiovascular events (11).

This research contributed to existing knowledge of lipid metabolism's function in cardiovascular disease. This by comprehensively analysed new lipid markers and comparing them to established techniques for examining lipid profiles. The cross-sectional form of the study made it difficult to conclude their causal relationships. The fact that the study sample was selected based on a particular geographical and clinical environment is another factor that makes it difficult to generalize the findings. The influence of these biomarkers on long-term cardiovascular disease outcomes should be investigated in further research, and these results should be validated using cohorts that are both bigger and more varied.

The findings of this research provide credence to the use of oxidized LDL, ceramides, and sphingolipids as instruments for evaluating the risk of cardiovascular disease. These lipid indicators are superior to more traditional lipid markers in sensitivity and specificity, which is the major cause of occurrence. The rising body of research supporting this concept lends credence to the notion that new biomarkers can enhance early identification and risk stratification, which might ultimately result in the development of individualized treatment strategies that minimize the morbidity and mortality associated with cardiovascular disease

1.      Forouzanfar MH, Alexander L, Anderson HR, et al. Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990–2013: a systematic analysis for the global burden of disease study 2013. Lancet 2015; 386: 2287–2323.

2.      Hozawa A, Folsom AR, Sharrett AR, et al. Absolute and attributable risks of cardiovascular disease incidence in relation to optimal and borderline risk factors: comparison of African American with white subjects––atherosclerosis risk in communities study. Arch Intern Med 2007; 167: 573–579.

3.      Biomarkers Definitions Working G. Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin Pharmacol Ther 2001; 69: 89–95.

4.      Cullen L, Mueller C, Parsonage WA, et al. Validation of high-sensitivity troponin I in a 2-hour diagnostic strategy to assess 30-day outcomes in emergency department patients with possible acute coronary syndrome. J Am Coll Cardiol 2013; 62: 1242–1249.

5.      Haaf P, Drexler B, Reichlin T, et al. High-sensitivity cardiac troponin in the distinction of acute myocardial infarction from acute cardiac noncoronary artery disease. Circulation 2012; 126: 31–40.

6.      Everett BM, Brooks MM, Vlachos HE, et al. Troponin and cardiac events in stable ischemic heart disease and diabetes. N Engl J Med 2015; 373: 610–620.

7.      Pelsers MM, Hermens WT, Glatz JF. Fatty acid-binding proteins as plasma markers of tissue injury. Clin Chim Acta 2005; 352: 15–35.

8.      McMahon CG, Lamont JV, Curtin E, et al. Diagnostic accuracy of heart-type fatty acid-binding protein for the early diagnosis of acute myocardial infarction. TAm J Emerg Med 2012; 30: 267–274.

9.      Gami BN, Patel DS, Haridas N, et al. Utility of heart-type fatty acid binding protein as a new biochemical marker for the early diagnosis of acute coronary syndrome. J Clin Diagn Res 2015; 9: Bc22–Bc24.

10.   Kabekkodu SP, Mananje SR, Saya RP. A study on the role of heart type fatty acid binding protein in the diagnosis of acute myocardial infarction. J Clin Diagn Res 2016; 10: Oc07– Oc10.

11.   Otaki Y, Watanabe T, Takahashi H, et al. Association of heart-type fatty acid-binding protein with cardiovascular risk factors and all-cause mortality in the general population: the Takahata study. PLoS One 2014; 9: e94834.