Defining atherosclerotic plaque biology by mass spectrometry-based omics approaches

Abstract

Atherosclerosis is the principal cause of vascular diseases and one of the leading causes of worldwide death. Even though several insights into its natural course, risk factors and interventions have been identified, it is still an ongoing global pandemic. Since the structure and biochemical composition of the plaques show high heterogeneity, a comprehensive understanding of the intraplaque composition, its microenvironment, and the mechanisms of the progression and instability across different vascular beds at their progression stages is crucial for better risk stratification and treatment modalities. Even though several cell-based studies, animal studies, and extensive multicentric population studies have been conducted concerning cardiovascular diseases for assessing the risk factors and plaque biology, the studies on human clinical samples are very limited. New novel approaches utilize samples from percutaneous coronary interventions, which could possibly gain more access to clinical samples at different stages of the diseases without complex invasive resections. As an emerging technological platform in disease discovery research, mass spectrometry-based omics technologies offer capabilities for a comprehensive understanding of the mechanisms linked to several vascular diseases. Here, we discuss the cellular and molecular processes of atherosclerosis, different mass spectrometry-based omics approaches, and the studies mostly done on clinical samples of atheroma plaque using mass spectrometry-based proteomics, metabolomics and lipidomics approaches.

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Mahesh Chandran

Mahesh Chandran V. R. completed his master's degree in Biotechnology from Bangalore University, India, in 2009. After that he joined as technical personnel at Mass Spectrometry and Proteomics Core Facility of Rajiv Gandhi Centre for Biotechnology (RGCB), a National Institute under the Dept. of Biotechnology, Govt. of India. His core work includes performing proteomics and metabolomics experiments in the Mass Spectrometry and Proteomics Core Facility of RGCB. He is currently a PhD candidate of Biotechnology at the University of Kerala, India.

Sudhina S.

Sudhina S. received her master's degree in Biochemistry (2010) from Mahatma Gandhi University, Kerala, India. She joined the Department of Biochemistry, University of Kerala, as a junior research fellow in 2021. She is an ICMR senior research fellow and currently pursuing her doctoral degree. Her area of research interest includes cancer biology and nanomedicine.

Abhirami

Abhirami is currently pursuing her doctoral degree as INSPIRE JRF in the area of cardiovascular disease in the Department of Biochemistry, University of Kerala. She received her bachelor's degree in Biochemistry and Industrial Microbiology and master's degree in Biochemistry from the Department of Biochemistry, University of Kerala, Kerala, India. The goal of her research is to explore nanomaterial based therapeutics in myocardial infarction.

Akash Chandran

Akash Chandran is currently a doctoral student in the Department of Nanoscience and Nanotechnology at University of Kerala, Trivandrum, India. He received his bachelor's degree in Chemistry and post-graduation in Analytical Chemistry from the University of Kerala, and completed M. Phil in Inorganic Chemistry from Mahatma Gandhi University, Kerala, India. The goal of his research is to design and fabricate porous nanomaterials as carrier molecules for targeted drug delivery and detection of cancer. In addition, he aims to develop bio-sensors for the early detection of various cancers.

Abdul Jaleel

Dr Abdul Jaleel K. A. is currently serving as a staff scientist at the Diabetes Biology lab of Rajiv Gandhi Centre for Biotechnology, a National Institute under the Dept. of Biotechnology, Govt. of India. He is also heading the Mass Spectrometry facility of the institute. His laboratory investigates the use of MS-based metabolomics and how independent risk factors for type 2 diabetes evolve over time in developing insulin resistance. He received his PhD in life sciences from AIIMS, India (1988), and served as an Assistant Professor of Medicine at Mayo Clinic College of Medicine, Rochester, MN, USA.

Janeesh Plakkal Ayyappan

Dr Janeesh P. A. is an Assistant professor of Department of Biochemistry, University of Kerala, Kerala, India. He received his PhD from the University of Kerala in 2015. He then joined as a Post-Doctoral Fellow in the Centre of Cardiovascular Sciences, Albany Medical College (2015–2016) and PHRI, International Centre for Public Health, New Jersey Medical school, USA (2016–2020). He then joined as a Research Associate Scientist in PHRI, International Centre for Public Health, New Jersey Medical School, USA, in 2020. His research area includes life style disease, translational nano-medicine and molecular biology.

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1. Introduction

Atherosclerosis is a chronic progressive pathosis characterized by the inflammation and proliferation of fibrous tissues in the vascular vessel lumens. These changes initially restrict blood flow and lead to vascular diseases like peripheral vascular diseases (PVD), cerebrovascular diseases, and coronary artery diseases (CAD) in later stages. These non-communicable diseases are a leading cause of death worldwide. They pose significant challenges for sustainable development in the 21st century by increasing the burden in low and middle-income countries.¹ PVD is one of the most common vascular diseases marked by an increasing prevalence worldwide with high mortality and morbidity rate. It has increased by 23% in one decade, with the most significant increase in low-income countries and is very common among elderly individuals. It is estimated to affect 20% of individuals over 60 years old.² PVD is brought about by atherosclerotic plaque buildup, vessel stiffness and stenosis in the peripheral arteries, which reduce blood flow to the limb and lower extremities. It usually exhibits no symptoms or mild to severe symptoms and is typically present with claudication. In some cases, it progresses to chronic limb-threatening ischemia (CLTI) and acute limb ischemia (ALI) conditions.

CAD is a common cardiac condition that involves atherosclerotic plaque formation and thrombosis in the blood vessel lumen and leads to impaired blood flow and oxygen delivery to the myocardium. It mainly includes chronic coronary artery disease (stable angina) and acute coronary syndrome (ACS). The clinical manifestations of ACS include ST-elevation myocardial infarction (STEMI), non-ST elevated myocardial infarction (NSTEMI) or unstable angina. It is one of the significant causes of death, disability, and human suffering globally. It affects around 1.72% of the world's population, and was responsible for nine million deaths globally in 2016. Men are more prone to CAD than women; the incidence typically starts in the fourth decade and increases with age.³ Cerebrovascular diseases refer to a group of conditions and diseases that affect cerebral circulation. This cerebrovascular insult occurs mainly because of the atherosclerotic disease of the carotid arteries, the major artery which supplies blood to the brain. It is the third most common cause of death in industrialized countries and the leading cause of long-term disability. The primary incidence of cerebral diseases is associated with carotid artery stenosis in older adults, and the risk increases with age. The most common presentation of cerebrovascular disease is an ischemic stroke, a hemorrhagic stroke and sometimes a transient ischemic attack. Ischemic stroke constitutes an estimated 80 per cent of all stroke cases.⁴ Several risk factors contribute to atherosclerosis-induced vascular diseases, including increased body mass index, hypertension, dyslipidemia, type 2 diabetes mellitus, etc. Dyslipidemia plays a major role in developing atherosclerotic plaque among the risk factors. And also, several genome-wide association studies (GWAS) show a strong relationship between many gene loci and these conditions. But these genetic changes are relevant to only a very small portion of the population. The environmental exposures can modify the gene expression levels through epigenetic mechanisms, and this modification can be inherited across cell generations to exert a long-term impact on the development of CVD.⁵

Atherogenesis is a prolonged multistep process that involves endothelial dysfunction and lipoprotein retention on the arterial walls, followed by lymphocyte infiltration, inflammation, foam cell formation, plaque buildup and thrombosis. The fibrous cap which forms around the plaque acts as a protective barrier between the prothrombic atheroma and the platelets in the bloodstream. Gradually an outward remodeling of the arterial wall and collateral vessel formation prevents most of the lesions from progressing to any acute vascular diseases.⁶ The vulnerable plaques are marked with an intimal necrotic core, a thin fibrous cap and an increased number of inflammatory cells and are more prone to rupture. The rupture of plaques will lead to thrombotic events, which can be non-obstructive or obstructive. The latter will lead to end-organ ischemic conditions and failure. Despite the recent advancements in the diagnosis, interventions, preventive measurements and management, vascular diseases, especially CAD, are the primary reason for mortality and morbidity worldwide.⁷ A deeper understanding of atherosclerotic plaque biology is essential for finding new efficient strategies for addressing the issue.

The effectiveness of the risk stratification strategies currently employed using traditional risk factor assessment shows a significantly less predictive value with limited capabilities. The sudden occlusion of vessels is always preceded by a varying period of plaque instability and thrombus formation. It manifests only in middle age; the process begins very early in life, even from childhood.⁸ The atheroma of specific histopathological characteristics is more prone to rupture and shows no relation concerning its degree of stenosis.⁹ And also, a significant percentage of patients presented with acute coronary syndromes are not on preventive measures because of the inaccuracy of the traditional cardiovascular risk assessment.¹⁰ The animal models currently being employed for atherosclerotic plaque studies generally develop plaque within a short period, contrary to the real scenario in humans, where it develops over a very long period of time. In spite of enormous studies being conducted to date, the studies on human clinical samples are very much limited.^11,12 Many treatments have been shown to be successful in mice over the past few decades but never made it to the clinical stage due to their unsuccessful translation to the human condition. This situation warrants the need for studies on human clinical samples with an integrated approach for elucidating the information from a whole system view.

The post-genomic era was marked by the introduction of new omics technologies like proteomics, metabolomics and lipidomics which provided good insights and bridged the gap between genotype and phenotype with a systems biology approach to defining the phenotype (Fig. 1).¹³ Proteomics is one of the indispensable tools in the emerging field of systems biology, which emerged in the 90s. It aims for large-scale identification and precise quantification of entire proteins, their proteoforms, their post-translational modifications, and their protein–protein interactions in biological systems. The proteome refers to the protein complement of a given cell at a specified time, including all protein isoforms and modifications.¹⁴

Fig. 1 The omics cascade in systems biology. It shows the unidirectional flow and interrelations between genomics, transcriptomics, proteomics and metabolomics. The DNA level determines what can happen; mRNA, what appears to happen; protein, what makes it happen; and metabolites, what has happened. The complexity dramatically increases as the flow of information moves from genomics to metabolomics. Metabolomics is the final step in the cascade and since the environmental factors are also influencing it, the studies on metabolites provide a much closer detail of the organism^’s phenotype than the preceding omics.

Metabolomics is a newly emerging omics technology that involves the high throughput identification and quantification of the total complement of all low molecular weight molecules, i.e., metabolites, which vary according to the physiological, developmental and disease conditions represented in biological systems such as cell, tissue, organism or bodily fluids. The metabolome, the complete set of small molecules, can be either endogenous (carbohydrates, amino acids, fatty acids, vitamins, nucleic acids, organic acids, etc.) or exogenous (environmental pollutants, drugs, food additives, xenobiotics) in origin.¹⁵ With the advances in metabolomics, it has become an important tool to understand and evaluate the chemical intermediates in varying disease conditions. This lead information can be translated for better CVD diagnosis, new therapeutic strategies, and risk biomarker identification.

Lipidomics involves the high throughput profiling, quantification and study of pathways associated with the lipidome, the total lipid composition of the cell, and its physiological functions and the significance.¹⁶ Since the metabolites are the intermediates and products of cellular metabolism, they represent the immediate readout of cellular metabolism. The genome, transcriptome and proteome represent the gene expression flow, while the metabolome represents the phenotype and functions. The investigation of the expression state of metabolites will give valuable information on the homeostatic mechanisms that govern the responses to different stimuli.¹⁷ The set of data generated from these state-of-the-art multi-omics technologies has the potential to create a comprehensive atlas of several disease conditions. This facilitates the knowledge of the cellular and molecular mechanisms and pathophysiological processes related to the disease state. The metabolic fingerprint can serve as a diagnostic or prognostic tool for biomarker detection for early intervention and drug efficacy studies in atherosclerotic vascular diseases. The complex nature of the biological system and disease conditions can only be captured by combining different omics approaches rather than focusing on single omics studies, which provide only partial information. Only limited studies were conducted on human plaques due to the unavailability of clinical samples, which limits the crucial clinical translation of the disease pathogenesis and mechanism. There is a need to also consider studies on clinical samples of different populations to check for the possible mechanistic changes in plaque biology and its progression. This article captures a comprehensive insight into the molecular and the pathophysiological basis of atherosclerosis, the concept, new advancements in MS-based proteomics and metabolomics workflow and the key findings from mass spectrometry-based omics technologies in atherosclerosis.

2. Cellular mechanism of atherogenesis

The arterial wall consists of an innermost layer, tunica intima, a middle layer, tunica media, and an outermost layer, tunica adventitia. The atherogenic development takes place in the intimal layer of the arterial wall. The intima is a thick region with a complex architecture and heterogeneous cellular composition. The endothelial cells that line the inner luminal wall act as a selectively permeable region for blood and tissues and separate the intima from the vessel's lumen. Endothelial cells have an ellipsoid shape in the tubular luminal wall and a polygonal shape in arterial branching bends or curvature or bifurcation regions. These stress zones, having polygonal-shaped giant endothelial cells, where the uniform laminar flow is disturbed, are the preferential sites for lesion initiation. The disturbed laminar flow induces shear stress on the artery wall. These lesion-prone areas exhibit a dysfunctional endothelial phenotype like pro-inflammatory condition and impaired endothelial permeability.¹⁸ Several studies have shown the role of increased plasma cholesterol levels, reactive oxygen species, and plasma homocysteine levels in triggering atherosclerosis by increasing vascular permeability and reducing nitric oxide production.^19,20 The subendothelial intimal region shows heterogeneous cell populations with several morphotypes. The major cell population includes well-defined vascular smooth muscle cells (VSMCs), macrophages, lymphocytes, dendritic cells, mast cells, pericytes and pericyte-like cells.²¹ Along with the classical cells for phagocytosis, the pericytes can also trap LDL by phagocytosis, produce pro- and anti-inflammatory cytokines, can act as antigen-presenting cells, and can participate in extracellular matrix synthesis and arterial wall thickening.²² The atheroprotective regions show an enhanced expression of the transcriptional integrators Kruppel-like factor 2 and Kruppel-like factor 4. The atheroprone regions show an activation of the NF-kappa signaling pathway in endothelial cells²³ leading to the expression of several pro-inflammatory cytokines: tumor necrosis factor α (TNF-α), interleukin-1 (IL-1), interleukin-6 (IL-6), interleukin-12 (IL-12), chemokines, extracellular matrix proteins, and growth factors which may create a niche for atherogenesis.²⁴

Atherogenesis initiates with the retention of LDL and lipoprotein (a) particles at the tight junctions of endothelial cells with the help of their constituent protein content, apolipoprotein B.²⁵ The latter is more atherogenic than LDL, which exerts its action by enhancing the expression of ICAM (intercellular adhesion molecule) in the endothelium and 6-phophofructo-2-kinase/fructose-2,6-biphosphatase (PFKFB)-3 mediated glycolysis.²⁶ The retention of these particles occurs mainly by interacting with proteoglycans. Later they are migrated by diapedesis through intercellular junctions and transcytosis by vesicular bodies to the subendothelial space. It has been noticed that out of the three main groups of proteoglycans, the relative increase in heparin sulfate molecules in comparison with keratin sulfate and chondroitin sulfate may cause the adhesion of lipoproteins. All the circulating LDL is not atherogenic, and native LDL cholesterol does not cause lipid accumulation in the arterial wall. It has been established from the study of the blood of patients with atherosclerosis that the early modification occurring in the blood LDL subfraction is desialylation.²⁷ LDL oxidation occurs in the vascular wall, not in the peripheral blood circulation. In contrast, other forms of atherogenic LDL modifications like small dense LDL, desialylated LDL, and glycated LDL can be identified in atherosclerotic patients. These circulating LDL particles are smaller, denser, desialylated, more electronegative in nature and are more prone to glycation leading to the formation of glycated LDL and have increased lipid peroxidation and contain more triglycerides and fatty acids.²⁸ Once in the vascular wall, the migrated lipoprotein will undergo multiple atherogenic modifications, including acylation, lipolysis, proteolysis, aggregation, fusion and oxidation by the action of ROS, myeloperoxidase, lipoperoxidase and (NADH/NADPH) oxidases. Out of the all modifications, the significant one is oxidation, which generates minimally oxidized pro-inflammatory LDL species. The sites of LDL oxidation are the unsaturated fatty acids in phosphatidylcholine (PC) and cholesterol ester (CE), thus forming CE hydroperoxide and PC hydro peroxide.²⁹

7-Hydroperoxycholesterol (7-hpCh) and 24-hydroperoxycholesterol, oxidized sterol moieties of cholesterol, are found in very high concentrations in the foam cells and fatty streaks.³⁰ The protein component of LDL, ApoB-100, also undergoes modifications mainly in the tryptophan and histidine residues resulting in the alterations of the secondary structure, which causes the loss of its ability to be recognized by LDL receptors. These modifications lead to lipoprotein aggregation and lipoprotein retention. Cysteine protease cathepsins play a role in the pathogenesis of atherosclerosis by mediating the aggregation of LDL cholesterol, foam cell formation, recruitment of immune cells and degradation of the extracellular matrix.³¹

This change in lipid species mocks damage-associated molecular patterns (DAMPs), activating endothelial cells and smooth muscle cells of the luminal wall. Lipid molecules like lysophoshatidylcholine play a significant role in endothelial cell activation and thereby promote monocyte adhesion in the luminal wall by mitochondrial reactive oxygen species.³² The smooth muscle cells, in turn, gain myofibroblast characteristics. These changes result in the initiation of low-grade inflammation, starting with the release of several pro-inflammatory molecules, including adhesion molecules and growth factors like macrophage colony-stimulating factors (M-CSF), monocyte chemoattractant protein 1 (MCP-1), GRO, and CCL5 by the endothelial cells. These factors interact with the cytokine receptors and result in the recruitment of monocytes, T-lymphocytes, B-lymphocytes, dendritic cells, and mast cells. The tethering, slow-rolling, firm adhesion and transmigration of these leukocytes through extravasation are mediated by P-selectins, E-selectins, L-selectins, several selectin ligands, members of immunoglobulin family-like vascular cell adhesion molecules (VCAM 1), intercellular adhesion molecules (ICAM 1, 2 and 3), platelet endothelial cell adhesion molecule-1 (PECAM1) and transmembrane receptor protein, integrins. The cytokine M-CSF stimulates the proliferation and differentiation of monocytes into macrophages.³³

In the foam cell formation phase, along with the LDL oxidation, the LDL protein component also undergoes modification leading to an unregulated cellular uptake of lipid particles by scavenger receptors, which are not regulated by the cholesterol content of the cells. Once inside the subendothelial space, monocytes acquire macrophage-like characteristics and express the scavenger receptor TLR-4, which recognizes oxidized cholesteryl esters of LDL, the receptors SR-A1, SR-A2 and LOX-1, which recognize modification of apoB-100 of LDL, the cluster of differentiation 36 (CD36) receptor, which recognizes oxidized phospholipids of LDL, and the FcγRII-R2 receptor, which recognizes oxidized LDL. This results in an uncontrolled heavy uptake of the LDL particles by the macrophages converting them into lipid-filled foam cells, thereby creating early fatty streaks on the tunica intima of arteries.³⁴ The macrophages also release inflammatory mediators, such as interleukin-1 β (IL-1β), TNF-α and IL-6, potent regulators involved in atherosclerotic plaque formation. IL-6 is a critical cytokine in the pathogenesis of atherosclerotic plaque development and progression. The lipid oxidation and its byproducts upregulate the secretion of IL-1, IL-6, VCAM-1 and ICAM-1.

The fibroatheroma formation phase is characterized by the elaborate release of pro-inflammatory cytokines by the macrophages. Vascular smooth muscle cells on the tunica media are specialized cells that demonstrate the blood vessel's phenotypic and functional plasticity, mainly by expressing several markers, including α-smooth muscle actin, smooth muscle-myosin, smoothelin-A/B, SMemb/non-muscle MHC isoform-B and cellular retinol-binding protein. The shear stress induced by the disturbed laminar flow and the accumulated modified lipids causes the expression of pro-inflammatory mediators rather than smooth muscle cell markers. This triggers an increased formation of collagen, elastin, and proteoglycans, as well as VSMC dedifferentiation, proliferation, and migration—a primary process in vascular wall repair.³⁵ Further, the increased expression of smooth muscle cell growth factor and platelet-derived growth factor (PDGF) by the monocyte-derived macrophages initiates the migration, mitogenesis and proliferation of smooth muscle cells from the tunica media to the tunica intima of the arterial wall to form a growing mass of fibrous plaque.³⁶ The oxidized LDL also increases the synthesis of asymmetric dimethylarginine (ADMA), an endogenous inhibitor of endothelium nitric oxide synthase (NOS). The enzyme NOS is responsible for the biosynthesis of NO, which has a significant role in maintaining vascular tone and dilation and an inhibitory role in inflammation, VSMC proliferation and migration, and platelet and leukocyte aggregation and adhesion.³⁷ All these events lead to the progression of the lesion. The regression of plaques is hindered by Semaphorin 3E, which facilitates the retention of the macrophages within the growing plaques and maintains the inflammatory condition.³⁸

The major cellular component of atherosclerotic plaque is a heterogeneous population of macrophages and monocytes. Based on the expression of cell surface markers on monocytes, they are classified into three subsets: classical/Mon1, intermediate/Mon2, and non-classical/Mon3. The proportion of intermediate or non-classical monocytes is reported to be elevated in conditions like unstable angina, coronary artery diseases, stroke and peripheral artery diseases with increased severity. Patients with atherosclerosis in multiple vessels have significantly more intermediate and non-classical monocytes than those with single-vessel disease. Several studies have shown the direct association of change of monocyte proportion from classical to non-classical or intermediate with the instability of plaque.³⁹ The intermediate and non-classical subsets show high inflammatory cytokine levels compared with the classical subset in individuals with or without perturbed lipid profiles. The differentiation from classical to non-classical happens through the intermediate subset. An increased monocyte inflammatory state could be a key factor that promotes plaque formation, and it shows an association with HDL and its protein component Apo A1 rather than low density lipoprotein cholesterol (LDL-C). These reports suggest that lowering LDL-C alone without improving functional HDL levels is not likely to reverse monocyte inflammation altogether.⁴⁰

Of the two forms of macrophages in plaque, M1 and M2, M1 is pro-inflammatory and atherogenic, whereas M2 is anti-inflammatory which prevents atherogenesis. Pro-inflammatory macrophages show increased glycolysis, pentose phosphate pathway and impaired TCA cycle, and anti-inflammatory macrophages show an increased fatty acid oxidation.⁴¹ And also, the M1 subset produces higher levels of inflammatory mediators and matrix metalloproteinases which facilitate the degradation of the thin fibrous cap of the atheroma and destabilize the plaque structure. The M2 subset of macrophages shows an increased secretion of anti-inflammatory cytokines and collagen production supporting plaque stabilization.⁴² It also clears apoptotic cells to prevent necrotic core formation. Out of the four major G protein-coupled free fatty acid-binding receptors FFAR1, FFAR2, FFAR3 and FFAR4 present in the macrophages, the last one is most involved and characterized by inflammation. The stable expression of FFAR4 using agonists showed reduced plaque formation and the presence of a high amount of M2 rather than M1.⁴³

The increase in the inflammatory process results in the apoptosis of the foam cells, which releases oil droplets that are further engulfed by smooth muscle cells to form smooth muscle cell foam cells. The arterial wall lesion mainly comprises a lipid core surrounded by smooth muscle cells and the fibrous component of the connective tissue fibers and inflammatory cells. The thick fibrous cap around the plaque forms a protective barrier between the prothrombic atheroma and the platelets in the bloodstream. All the lesions initially migrate towards the tunica adventitia until they can’t expand outward and then proliferate and migrate towards the lumen. The lesion further develops by adding more leucocytes, monocyte-derived macrophages, smooth muscle cells, extracellular matrix and necrotic lipid core.³⁴ The proliferation of smooth muscle cells gives rise to the neointima stage, characterized by fused intima and media.

The apoptotic macrophages show an impaired efferocytosis process, which increases the severity and vulnerability of the plaque to rupture.⁴⁴ The vulnerable plaques are marked with a thin cap fibroatheroma, increased inflammatory cytokines, and ER stress which initiates apoptosis and leads to the intimal necrotic core. In the final phase, these features contribute to the rupture of plaques and proceed to thrombotic events (Fig. 2). The reduced expression of adiponectin receptors, AdipoR1 and AdipoR2, in the unstable plaques impairs the secretion of anti-inflammatory adipokines and may contribute to the vulnerability of plaques.⁴⁵ The activation of ATP citrate lyase in the inflammatory macrophages and plaques also plays a significant role in the destabilization process.⁴⁶

Fig. 2 Atherosclerosis progression: the process starts at the atheroprone regions of the vasculature, where it exhibits dysfunctional endothelial properties marked with impaired permeability and pro-inflammatory conditions. This condition favors the initiation of lipid retention, activation of endothelial cells and progression to inflammatory and foam cell formation phases. The migration and proliferation of smooth muscle cells lead to the plaque formation phase which proceeds to the advanced lesion phase upon the further buildup of fibrotic and calcific layers and a large lipid core. The vulnerable plaques end with thromboembolic events.

The oxidized LDL induces the expression of high levels of plasminogen activator inhibitor and tissue factor, a potent coagulant, in the endothelial cells and monocytes. The oxidized LDL can also induce the expression of metalloproteinase-1 (MMP-1) and metalloproteinase-9 (MMP-9) in the vascular wall via a prostaglandin E₂-dependent mechanism modulated by cyclooxygenase-2 and prostaglandin E synthase causing degradation of extracellular collagen which leads to unstable atherosclerotic plaque.⁴⁷ It also inhibits the expression of nitric oxide synthase, thus affecting vasodilation. Further, the microcalcification within the plaque by extracellular components due to the dysregulated deposition elevates the stress accumulation and favors the rupture progression where the macrocalcification stabilizes it.⁴⁸ The rupture of the atheroma causes thrombus formation, which can be non-occlusive or occlusive. The latter will lead to thromboembolism, end-organ ischemic conditions and failure. Along with plaque rupture, plaque erosion also contributes to the thrombotic complications of atherosclerosiss.⁴⁹

Along with the monocytes, lymphocytes are also recently reported to play a significant role in atherosclerotic lesion development and progression. The expression of CD36, an oxidized LDL receptor, in the peripheral T lymphocytes shows a regulatory action and prevents atherosclerosis development. It is downregulated in subjects with subclinical atherosclerosis compared to healthy subjects. The binding of oxidized LDL to the cluster of differentiation 69 (CD69) receptor initiates the expression of the NR4A nuclear receptor subfamily (NR4A1 [Nur77], NR4A2 [Nurr1] and NR4A3 [NOR-1]) in endothelial and smooth muscle cells, which downregulates the expression of pro-inflammatory cytokines like IL-1β, IL-8, and MCP-1.⁵⁰ The plaques with predominant T helper type 1 cells, which express pro-inflammatory cytokine interferon-γ (IFN-γ), impair the collagen production by the smooth muscle cells and result in rupture-prone plaques with thinner fibrous caps. On the other hand, the plaques with a bulk of T regulatory cells, which express cytokines and transforming growth factor-β (TGF-β), promote collagen synthesis and stabilize plaques.

3. Mass spectrometry-based proteomics and its recent advancements

High-throughput technologies allow us to investigate several disease conditions and integrate their data to identify causal genes and molecular mechanisms involved in those perturbed conditions. These techniques can be easily applied to different sample sources like cell lines, tissues, animal models, human clinical samples, autopsy samples and large population cohorts, enhancing our understanding of the differential cell function across tissues.⁵¹ Proteomics-based approaches are mainly accomplished by liquid chromatography-mass spectrometry analytical platforms (Fig. 3). Proteomics technologies have been rapidly evolving with new technological advancements in the last two decades, and several studies have shed new light on several pathological conditions, including atherosclerosis. Mass spectrometry-based proteomics is generally classified into targeted and untargeted. In targeted proteomics, proteins of interest can be specifically quantify by employing multiple/selected reaction monitoring (MRM) and parallel reaction monitoring (PRM) approaches and are more sensitive and specific.⁵² There are mainly three approaches in the untargeted mass spectrometry-based proteomics: bottom-up, middle-down and top-down proteomics. The commonly used approach is bottom-up proteomics, a peptide-centric approach, which relies on the enzymatic digestion of proteins before liquid chromatography-coupled mass spectrometry analysis.⁵³ The protein samples will be digested into peptides with the help of sequence-specific mass spectrometry grade proteases like trypsin, Glu-C, chymotrypsin, Asp-N, pepsin, etc., alone or in combination based on the application. The most commonly used enzyme is trypsin, a serine protease that cleaves only at the carboxyl side of lysine and arginine and creates distinct peptide fragments and helps in peptide mapping and sequencing. Endoproteinases like Lys-C can specifically cleave proteins at the carboxyl side of lysine even after being followed by proline residues and reduce the missed cleavages. Lys-C creates larger peptide fragments that get multiply charged upon ionization and is ideal for phosphopeptide enrichment workflows using electron transfer dissociation ionization techniques. Top-down proteomics, a protein-centric approach, is mainly employed for identifying and characterizing proteoforms and their post-translational modifications. Middle-down proteomics explores the medium-sized peptides by performing a size-dependent fractionation or cation exchange separation of complex proteomes followed by a restricted proteolysis method along with the electron transfer high energy collisional dissociation (EThcD) mode of dissociation for better sequence coverage.⁵⁴

Fig. 3 Overall scheme of the liquid chromatography mass spectrometry-based proteomics: the proteins from the carotid endarterectomy plaque samples, abdominal aortic surgical specimens, atherosclerotic plaques obtained from autopsies and the plaque debris from the percutaneous coronary angioplasty balloons can be subjected to either peptide-centric approaches, bottom-up proteomics and middle-down proteomics, or the protein-centric approach, top-down proteomics. The peptides or proteins are then separated by using microflow liquid chromatography systems and can be analyzed using mass spectrometry by either data-dependent acquisition (DDA), data independent acquisition (DIA), or targeted acquisition. In DIA, all the peptides within a defined mass-to-charge window are subjected to fragmentation resulting in more complex fragmentation spectra. In DDA, high abundant peptides are selected individually during ion accumulation and fragmented separately. In the targeted approach, the protein of interest can be quantified from a complex mixture of protein samples. The computational analysis of mass spectral data using different software platforms can perform chromatographic peak picking, protein identification, identification of post-translational modifications (PTM), protein structure elucidation, and protein quantification, either by label-free relative protein quantification (LFQ), or by methods employing tandem mass tags (TMT) and stable isotope labels (SILAC).

Various techniques like two-dimensional difference gel electrophoresis (2D-DIGE), 2D gel electrophoresis, and chromatographic separations can be combined with advanced mass spectrometry to decrease the complexity of the samples and increase the proteome coverage. The online separation and quantification of complex mixtures of samples can be achieved by melding the mass spectrometer with a chromatographic system, 1D nano-LC system or 2D nano-LC system, preferably capable of using sub-2-micron sized particle filled reverse-phase columns. This approach helps to physically separate a complex mixture of peptide samples with high resolution and superior chromatographic performance according to their hydrophobicity. Reproducible peptide separation and identification of low abundant species is crucial in proteomics research which can be achieved by exceptional particle innovations and new innovative chip-based microfluidic columns. The commercially available mass spectrometry compatible detergents like RapiGest SF surfactant, Azo and PPS Silent Surfactants provide efficient sample lysis and protein extraction from biological samples without causing detrimental effects on the LC-MS systems and show better sequence coverage than the non-conventional detergents.⁵⁵ The innovations in different fragmentation techniques like high energy collisional dissociation (HCD), electron transfer high energy collisional dissociation (EThcD), electron transfer collisional induced dissociation (ETciD), UV photodissociation (UVPD), electron detachment dissociation (EDD), metastable atom-activated dissociation (MAD) and MALDI post-source decay (PSD) generate informative fragmentation spectra for discerning sequence information, biological diversity and post-translational modifications like glycosylation, phosphorylation, etc.⁵⁶ The data can be acquired by either data dependent acquisition or data independent acquisition utilizing either stable isotope labeling (SIL) like ICAT, ITRAQ, etc. or label-free quantification methods.⁵⁷

The new instruments equipped with multiple analyzers in tandem and ion mobility-enabled separation provide unprecedented proteomics research capabilities. The instruments are now equipped with very high ion transmission capability, scan rates, accuracy and sensitivity, and ultra-high vacuum technologies, which offer a multitude of capabilities like protein structural characterization, mapping protein interactions, crosslinking studies, antibody characterization, interactome studies, post-translational modifications of proteins, immunopeptidome analysis, etc. New interfaces help to achieve the gas-phase fractionation of ions based on differential ion mobility, decreasing the product ion complexity by removing cluster and neutral ions. The PASEF technology allows parallel accumulation of ions and trapped ion mobility-based separations, which offer a four-dimensional approach to discerning the retention time, ion intensity, mass to charge ratio and ion mobility for reducing the complexity of the samples.

3.1. Single cell proteomics

The different types of cells, which are isogenic, vary significantly in their gene expression, proteome levels and functional properties. Such heterogeneity will always be lost when we perform a global proteomics experiment. While the single cell genomics and transcriptomics stand for all the genes and the expressed gene products in a cell, the single cell proteomics and metabolomics address the dynamics in the proteoforms and enable a closer look into the functional proteins and phenotype (Fig. 4). The advancements in the next generation sequencing techniques, cloning technologies and reliable amplification capabilities for nucleic acids provide a strong base for understanding and identifying different cell types and genomic heterogeneity using single cell genomics and transcriptomics studies. The valuable information from multiple levels of omics data from genomics, transcriptomics, single cell RNA technologies, single cell genomics, etc. can serve as a foundation, and an integrative approach with the other omics techniques further facilitates and improves the deep understanding of the biological information.

Fig. 4 Single cell omics: traditional proteomics and metabolomics experiments need large quantities of the analyte, which is being accomplished by averaging the proteome or metabolome of heterogeneous cell types. The recent developments in the sample preparation methodologies and robust computational algorithms can outperform the scenario and help in better stratification by cell type and different cell state resolved analysis for deciphering the molecular characterization of the cell heterogeneity.

Even though antibodies and fluorescent proteins are being used for analyzing single-cell proteomes, they fail to give more information in disease conditions where heterogeneous cell types and thousands of proteins come into action. Due to the fluorophore overlap, quantification of proteins for single-cell kinds is always limited to a few numbers in the case of using fluorescent proteins. Several techniques are used for single-cell analysis, like microscopy, flow cytometry, CyTOF, single-cell Western blotting, proximity extension assay (PEA), multiplexed imaging, etc., with several limitations.⁵⁸ Studying proteomes at a single cell resolution requires a very high analytical capability, as a single cell harbors only a few picograms of proteins. The technological and computational advancements in mass spectrometry utilizing the tandem mass tags help in analyzing the ultra-low level of samples from very few numbers of single-cell types with high sensitivity and quantitative accuracy.⁵⁹ Although MALDI TOF has been used for single-cell analysis initially for two decades, there has been a limitation in the quantification accuracy. The workflow developed by Slavov et al., Single Cell ProtEomics by Mass Spectrometry (SCoPE-MS), could quantify thousands of proteins from single cells using mass tags.⁶⁰ Recently Mathias Mann and the group came up with a new workflow for the label-free quantification of single-cell proteomes using the data dependent and data-independent PASEF technology with high coverage and sensitivity. With the help of the high field asymmetric ion mobility spectrometry (FAIMS), an interface that helps in the gas-phase dispersion and fractionation of ions based on charge, and the nanodroplet sample preparation (nanoPOTS), thousands of proteins can be quantified by using data-dependent acquisition using the latest generation Orbitrap Eclipse mass spectrometry.⁶¹ Senavirathna L. et al. recently reported an integrated spectral library-based single-cell proteomics (SLB-SCP) platform with a direct sample extraction method utilizing the physicochemical characteristics of the peptides, extraction of precursor peptide ions and spectral library for protein profiling at single-cell levels.⁶² Mass spectrometry-based proteomics approaches can identify and quantify differentially expressed proteins in biological systems with the help of available well-annotated protein databases. The integration of information available from multiple omics technologies can then be able to determine the biochemical pathways and biological functional significance in connection with disease pathogenesis.⁶³

3.2. Mass spectrometry-based proteomics in atherosclerosis

Quiles-Jiménez A. et al. used early and advanced carotid plaques to investigate the relationship between aberrant post-translational modifications and atherosclerosis and found decreased levels of N6-methyladenosine rRNA and mRNA and their modulatory enzymes like N6-adenosine-methyltransferase ZCCHC4, methyltransferase like 5 (METTL5), and the rRNA 20-O-methyltransferase fibrillarin (FBRL) in atherosclerotic plaques compared to the control groups.⁶⁴ Hanssen et al. first reported the elevated presence of advanced glycation end products (AGEs) in the rupture-prone atherosclerotic plaques through mass spectrometry studies.⁶⁵ The comparative proteomics analysis of the extracellular matrix of the human carotid endarterectomy specimens from symptomatic and asymptomatic patients revealed the composition of advanced lesions, such as MMP9, calprotectin, cathepsin D, and galectin-3-binding proteins, which can be used for improved risk stratifications.⁶⁶ The proteomics analysis of different regions of human carotid plaque identified several proteins implicated in the plaque progression. Notably, proteins involved in the extracellular matrix remodeling and those in the smooth muscle cells like biglycan, mimecans and myosin RLC-9 were significantly reduced and proteins like Apo A-IV and transthyretin were overexpressed considerably in the plaque core.⁶⁷ The proteomics analysis of coronary artery plaques by You et al. first reported the link between increased ferritin levels and disease severity.⁶⁸ A proteomic investigation of the stable and unstable atherosclerotic plaques by Bao M. H. et al. showed 293 differentially expressed proteins between the groups, and their functional enrichment and pathway analysis indicated the role of metabolism, immune response and endocrine system in defining plaque stability.⁶⁹ Immunoprecipitation followed by GeLCMS on human endarterectomy samples showed the utilization of galectin-3 for developing improved imaging-based diagnostics and biotherapeutics.⁷⁰ The proteomic and peptidome analysis of atherosclerotic lesions from carotid endarterectomy by Jin H. et al. stratified the plaques with different phenotypes like stable, vulnerable and hemorrhage with high predictive power. Also, it revealed the association of a transcription factor, serum response factor (SRF), with the plaque phase transition.⁷¹ A study conducted on the atherosclerotic lesion and normal areas of human aortic tissue first showed the role of complement C3 in disease pathogenesis and progression. The study also showed the differential abundance of the regulators of the C3 complement system in the extracellular matrix (ECM) layer of intimal layer lesion and normal aorta segments and the role of the C3 complement system in the cellular repair mechanisms of VSMCs beyond its role in immunity.⁷² Lorenzo C. delineated the presence of a mitochondrial dehydrogenase, ALDH4A1, in the atherosclerotic plaque, which acts as a target antigen for the elicitation of the autoantibody A12, and its increased presence under the disease condition supports its use as a biomarker and therapeutic.⁷³ Parallel and comparative proteomics studies on the human and murine plaques revealed the primary role of basement membrane proteins in the vascular proteolysis and rupture of plaques.⁷⁴ Proteomic analysis showed the accumulation and activation of the complement C5 in the intima of early atherosclerotic plaques and the same exhibits on the plasma level of patients. Thus, it can be a future biomarker candidate for identifying subclinical atherosclerosis.⁷⁵ Rykaczewska U. et al. established the role of proprotein convertase subtilisin/kexins (PCSKs) in vascular remodeling via smooth muscle cell migration in response to platelet-derived growth factor subunit B and matrix metalloproteases.⁷⁶ The proteomics analysis of the smooth muscle cells derived from the atherosclerotic plaque showed the role of Jagged1/Notch2 signaling in the disease condition and its effects on the proliferation of smooth muscle cells, which in turn affect plaque stability.⁷⁷ Langley et al. profiled the extracellular matrix proteins of the patients with stable and vulnerable plaques and defined the molecular signature between the conditions with potential clinical implications.⁶⁶

One of the extensive studies conducted by Herrington D M. et al. on the human coronary artery and aorta generated very comprehensive information on the proteome and the difference in the mitochondrial protein abundance in normal and disease conditions, which can become a strong indicator for subclinical atherosclerosis and can be used for early prediction.⁷⁸ A comparative proteomics analysis of the atherosclerotic lesion of men and women revealed gender-based alterations in the iron metabolism, which is corroborated by the significant changes in the levels of Hb, ferritin, serotransferrin and hemopexin, which are dependent on the lesion stage in male subjects.⁷⁹ A data independent profiling of the carotid plaque by Hansmeier N. et al. revealed the central role of smooth muscle cells in advancing atherosclerotic plaques.⁸⁰ Dutta B. et al. identified deamidated NGR motifs, i.e., isoDGR, on several extracellular matrix proteins of plaques, which enhance monocyte recruitment and aid the progression of the disease conditions.⁸¹

Proteomic studies on the secretomes of high and partial stenotic plaque reaffirm the role of vascular smooth muscle cell activation in early plaque development stages and the role of extracellular matrix proteins and their substrates in unstable atheromatous lesions.⁸² Viiri L. E. et al. first characterized the smooth muscle cells of the plaques of patients with or without acute cerebrovascular symptoms. They showed the differential expression levels of annexin A1 and its role in eliciting inflammation or inflammatory mediators in smooth muscle cells.⁸³ Olson FJ reported the role of cell-surface plasminogen receptor, S100A10, in extracellular matrix degradation in advanced atherosclerotic plaques by investigating the complicated and stable carotid arteries.⁸⁴ A comparative quantitative proteomics analysis of the apoA-I lysine carbamylation in the complex necrotic plaques from human aortic tissues and the in vitro carbamylation system revealed the presence of significantly higher levels of lysine carbamylation in plaques. It occurs mainly via the nonenzymatic pathway, the urea-decomposed cyanate ion pathway, which converts the cardioprotective lipoproteins into proapoptotic and proatherogenic ones. The study provides insights into the chemical environment within the artery wall.⁸⁵ A study on the specimen from abdominal aortic aneurysm (AAA) patients identified the presence of autoantigen CA1 and its possible role in the pathogenesis of the disease.⁸⁶ Kim E. N. et al. investigated the atherosclerotic plaque collected from the AAA patients and showed a high level of monomeric C reactive protein (mCRP), which correlates with the serum CRP levels and is shown to be associated with various signaling pathways related to complement activation, atherosclerosis, and thrombogenesis.⁸⁷ Lorentzen L. G. et al. used a novel method to demonstrate the differences in the protein signatures of coronary artery lesion of STEMI and stable angina pectoris subjects.⁸⁸ A comprehensive targeted and untargeted proteomics by K. Theofilatoson et al. on the core and periphery of plaques from 219 carotid endarterectomy samples revealed distinct signature proteins involved in plaque calcification and inflammation. The study also showed the proteins Calponin1, Protein C, Serpin H1, and Versican core protein as independent predictors for the progression of atherosclerosis.⁸⁹

4. Mass spectrometry-based metabolomics, and its recent advancements

The emerging field of metabolomics and lipidomics aims to identify and characterize small molecules and their interactions and mechanisms concerning the biology of complex heterogeneous systems. Generally, liquid chromatography or gas chromatography will be hyphenated with MS for the pre-separation of complex samples to generate high-quality spectra. Direct infusion of the metabolite samples can also be considered depending upon the type of analysis. Besides MS, one most widely used technique for metabolomics studies is nuclear magnetic resonance (NMR) spectroscopy. Gas chromatography-mass spectrometry (GC-MS) has been one of the preferred choices since the 1960s for the qualitative and quantitative analysis of small molecules.⁹⁰ In recent years, the technological advances in liquid chromatography coupled with tandem mass spectrometers equipped with high-resolution analyzers such as time-of-flight, quadrupole coupled to time-of-flight (TOF, QTOF), orbitraps and computational power enable us to measure even very low abundance species. Different fragmentation techniques like CID (collision-induced dissociation) and EI-SID (electron impact-source induced dissociation) can be used to generate fragmentation spectra of analytes and elucidate their chemical structure. When considering the inter instrumental variability, EI-MS SID shows more reproducibility than CID.⁹¹ Either untargeted or targeted metabolomics approaches can accomplish MS-based metabolomics investigations. One of the significant hurdles this area faces is the accurate identification of compounds, like structural isomers and positional isomers, in the case of lipids, where they differ only in double bond positions.⁹² High-resolution instruments with ion mobility and trapped ion mobility separation (TIMS) capabilities can identify the collisional cross-section values of the compounds with more unique isotopic patterns and can be determined based on isotopic mass similarity and drift time along with retention time, neutral mass and fragmentation score. This technology gives an extra dimension to the high-confidence molecular characterization.⁹³

The gold standard for metabolite identification compares experimental fragmentation spectra with the database reference spectra. Mass Bank,⁹⁴ MoNA, METLIN⁹⁵ mzCloud, HMDB,⁹⁶ KEGG, LIPID MAPS, NIST, and PubChem are important publicly available compound libraries. These have a limited number of metabolites and their corresponding MS/MS spectra. The unavailability of fragmentation spectra for most compounds constantly challenges accurate identification. The new advancements in the in silico fragmentation and spectral prediction put up by several approaches like quantum chemistry, machine learning, mapping bond dissociation energy, and heuristic models⁹¹ create open MS/MS databases like LipidBlast,⁹⁷ LipidFrag,⁹⁸ ChemFrag,⁹⁹ MetFrag,¹⁰⁰etc. for reliable identification.

The quality of high throughput data generated by global metabolomics or lipidomics is of great importance in systems biology studies for biomarker discovery, precision medicine approach, pathways associated with disease conditions, etc. For generating reproducible results with correct assessments of metabolites, care should be taken to prepare all the samples in such a way as to prevent or reduce the degradation and oxidation of metabolites. Various samples like cell extracts, tissue extracts, biological fluids like plasma, serum, urine, saliva, and cerebrospinal fluid, gastric lavage, lung lavage, etc. can be used in metabolomics studies.¹⁰¹ A suitable extraction method should be selected such that both polar and non-polar compounds should get extracted for a comprehensive analysis of the metabolome or lipidome. Commonly used metabolite extraction techniques are protein precipitation, liquid–liquid extraction, solid-phase extraction, one-phase extraction and two-phase extraction.^102,103

Several open source, instrument-specific and platform-independent software solutions are available for handling the multidimensional complex metabolomics data, such as Progenesis QI, Profinder,¹⁰⁴ Lipid Data Analyzer,¹⁰⁵ LipidXplorer,¹⁰⁶ MetaboAnalyst,¹⁰⁷ XCMS,¹⁰⁸ MZmine,¹⁰⁹ MetaboScape,¹¹⁰etc. These software programs’ enhanced algorithms can preprocess the raw data by performing chromatographic peak alignment of multiple runs, missing value imputation, chromatographic peak picking, adduct deconvolution, normalization and identification of metabolites by searching against databases (Fig. 5).

Fig. 5 Overall scheme of liquid chromatography mass spectrometry-based metabolomics: the metabolites from the carotid endarterectomy plaque samples, abdominal aortic surgical specimens, atherosclerotic plaques obtained from autopsies and the plaque debris from the percutaneous coronary angioplasty balloons are quenched, extracted, separated by using microflow liquid chromatography systems, and analyzed using mass spectrometry. The data acquisition can be either targeted or untargeted, in the targeted approach, the metabolite of interest can be quantified from a complex mixture of metabolite samples, and in the untargeted approach, complete profiling of the metabolites can be achieved depending on the capabilities of the analytical platforms employed. The raw mass spectral data are then analyzed using different software platforms which can perform adduct deconvolution, chromatographic peak picking, feature identification, and quantification. This is followed by several statistical analyses, pathway analyses, data mining and metabolic network reconstructions to identify significant metabolites in disease conditions.

4.1. Single-cell metabolomics

A single cell is the smallest functional biological unit, and its metabolic signatures provide insights into its biological processes. Even within the isogenic cells, different chemical phenotypes can be seen as a result of different cellular dynamics and microenvironments.¹¹¹ Single-cell metabolomics is the youngest of omics technologies that provides an immediate readout of the phenotype of cells, which is generally difficult to measure as it is always very dynamic because of its continuous interaction with the environment. The structural diversity, the vast range of metabolites, and the inability to amplify the metabolites and tagging further increase the challenges.¹¹² Metabolites play a very diverse role in inflammatory diseases, cell signaling cascades, immune responses and epigenetic regulation besides as a metabolic building block.¹¹³ In the case of malignant tumors, delineating the metabolomic imprint of multiple sub-cell populations and the high metabolic rate of cancer cells will give valuable information about the role and phenotype of each cell type.

Sample preparation is key for an accurate readout of the metabolome. The quenching of the metabolic reactions is generally performed by snap-freezing or by adding organic solvents, acids or bases without causing intracellular metabolite leakage.¹¹⁴ Several microfluidic platforms¹¹⁵ and microarray chips for mass spectrometry¹¹⁶ are available, which can effectively trap the selected individual cells, culture them under preferred conditions, quench by the snap freeze method and lyse cells for single-cell analysis using mass spectrometers. Metal-coated microcapillary sampling tips,^117,118 capillary electrophoresis,¹¹⁹ flow cytometry, and laser capture microdissection¹²⁰ are also used for preparing single cells for analysis with their limitations and advantages. SpaceM is a method that integrates light microscopy and MALDI-imaging MS to provide a metabolic profile for each cell.¹²¹ Laser ablation electrospray ionization (LAESI), droplet-based microextraction combined with electro spray ionization (ESI),¹²² non-matrix using MALDI desorption ionization from porous silicon (DIOS),¹²³ silicon nano post arrays (NAPAs),¹²⁴ secondary ion mass spectrometry (SIMS),¹²⁵ and laser desorption/ionization droplet delivery (LDIDD)¹¹⁹ are the ionization methods used for single-cell analysis.

Since most single-cell experiments are performed by direct infusion, the analysis often faces ion suppression and quantitation difficulty because of low analyte concentration and background matrix effects. A few methods have been developed by coupling MS with UHPLC,¹²⁶ capillary electrophoresis (CE)¹²⁷ or nano-LC,¹²⁸ which may circumvent the reproducibility problems, improve quantitative ability and nullify technical variability in the near future. With the help of new advanced mass spectrometers with very high sensitivity, resolution, accuracy and analytical capabilities, colossal information can be extracted from the single-cell levels, yielding a wealth of new biological insights into different disease conditions. Despite this, the field still needs further development, primarily in reproducible single-cell isolation techniques and efficient ionization techniques for the metabolites with low ionization efficiencies and sensitivity to identify from low analyte concentration.

4.2. Mass spectrometry-based metabolomics in atherosclerosis

Metabolomics can be exploited to comprehensively analyze the composition of metabolites in atherosclerotic lesions. Although tissue metabolomics offers promising leads to metabolomic insights and pathogenesis in detail, there are few studies conducted so far exploiting the clinical samples. Studies by Moerman et al. defined the spatial lipid distribution of the human carotid artery plaques employing the matrix-assisted laser desorption ionization mass spectrometry imaging technique. The study showed a high abundance of oxidized cholesteryl esters and sphingomyelin, specifically in the plaque necrotic core, proportional to its lesion complexity. It was established to correlate with the thrombus fragments like coagulation protein fibrin, diacylglycerols and triacylglycerols.¹²⁹ The targeted mass spectrometric analysis first reported the presence of oxidized phosphatidylinositol species in human atherosclerotic plaques and oxidized human LDL.¹³⁰ Surendran et al. identified deferred concentration and distribution of oxylipins in the LDL, depending on the varying degree of oxidative stress.¹³¹ The plasma lipidomics of patients presenting with ACS and stable coronary artery disease revealed low levels of lysophospholipids in ACS, which may be linked to the disruption of the coronary plaque through modulating the function of HDL.¹³² The comprehensive MS analysis of the lipid content in human atherosclerotic plaques of carotid or femoral endarterectomies and radial arteries by Stegemann et al. showed an apparent difference in the relative abundance of cholesteryl esters with linoleic acids, polyunsaturated fatty acids like eicosapentaenoic acid and arachidonic acid compared to their controls. The study also showed a reduced abundance of sphingomyelins with long-chain fatty acids in plaques compared to the plasma levels and certain sphingomyelin species like (d18:1/16:0) and (d18:1/14:0) were enriched. The authors also showed high expression of several genes involved in glycolysis and the pentose phosphate pathway in the high-risk groups and in symptomatic patients.¹³³ The untargeted lipidomics analysis of the serum samples of 109 subjects with or without CAD revealed a positive correlation of sphingomyelins with serum lipoprotein levels highlighting the importance of targeting sphingolipid metabolic pathways as therapeutic agents.¹³⁴ Auguet et al. reported high levels of circulating 20-HETE in patients with unstable carotid plaque compared with the normal healthy subjects.¹³⁵ A metabolomic investigation of the intimal thickened areas and stenosis regions of 78 human carotid and femoral endarterectomy plaques showed higher acylcarnitine levels, which corresponds to dysregulated beta-oxidation and positive correlation of phosphatidylethanolamine-ceramide concerning the progression of atherosclerotic stenosis and can be considered as a potential biomarker.¹³⁶ Jung et al.'s targeted and untargeted analysis of plaque-containing and plaque-free human aortic tissues showed significantly higher levels of glucosylceramide, tryptophan, kynurenine and quinic acid in aortic plaques. The action of later on plaques was further investigated and shown to have an inhibitory effect on the inflammatory activation of macrophages. The plaque containing aortic tissues also showed dysregulation of purine pathway metabolites.¹³⁷ The targeted metabolomics analysis and the gene expression studies on high-risk human plaques revealed and supported the altered expression levels of anabolic and catabolic pathways, which gave evidence for the role of altered cellular metabolism and inflammation and phenotype of plaques.¹³⁸ Untargeted lipidomics analysis of the carotid plaques of symptomatic and asymptomatic cerebrovascular disease patients first reported very high concentrations of acylcarnitine in the symptomatic plaques and its possible role in plaque rupture risk.¹³⁹ Saito et al. first reported the comparative lipid signatures of the aortic media tissue of nonatherosclerotic and atherosclerotic aortic aneurysm patients to define the pathophysiology better.¹⁴⁰ Targeted lipidomics analysis of carotid atheroma plaques reported, for the first time, the significant presence of 2-arachidonoyllysophosphatidylcholine in diabetic subjects.¹⁴¹ One of the most extensive metabolomics studies on human calcific aortic valves revealed lysophosphatidic acid as an independent risk factor for disease severity. Its high levels are associated with a faster progression rate of calcific aortic valve stenosis.¹⁴²

5. Conclusion

Atherosclerosis is the leading cause of death worldwide. In most cases, the early stages of atherosclerosis development are clinically silent, and the disease manifests only during the final phase with a fatal outcome. Several studies have shown a high rate of subclinical atherosclerosis in middle-aged and young populations with different stages of lesion progression.¹⁴³ Identifying and validating several risk factors like hypercholesterolemia, hypertension, diabetes mellitus, and smoking have led to the development of a few risk prediction scoring models, like the Framingham risk score, for assessing CVD, but with several limitations. Only 40% of patients display one risk factor, and 20% won’t show any risk factors.¹⁴⁴ It is, therefore, essential to improve our understanding of the pathological mechanisms that trigger atherosclerotic lesion development in the arterial wall. Although a few biomarkers like C-reactive protein, growth-differentiation factor-15, fibrinogen, and uric acid for assessing systemic inflammation are being used, and markers like myeloperoxidase and matrix metalloproteinases for plaque stability, and cardiac troponin and phospholipase A2 for myocardial infarction have been identified, the exact detailed biochemical roles are not yet understood.¹⁴⁵ The multifactorial nature of atherosclerosis challenges the precise risk prediction and a considerable void exists in understanding the disease pathogenesis. This scenario necessitates further research to comprehensively understand several factors involved, biochemical mechanism, the proteins and metabolites involved in the initiation, progression and vulnerability of atherosclerotic plaques, and the role of the microenvironment in the disease pathogenesis. Since the structure and biochemical composition of the plaques show a high heterogeneity, an integrated approach is necessary for elucidating the information from a whole system view. This approach can facilitate improved cardiovascular disease risk stratification.

Even though animal models can be used for omics studies, atherosclerosis in humans usually develops over a very long period compared to animal models, which we induce in a short time span. There will indeed be some ambiguity in the results. And also, unlike animal models, humans are characterized by the diversity in their genetic makeup and acquire risk factors from the environment during the disease stages, which impacts the lesion phenotype. So, studies on human clinical samples can provide valuable information on the molecular mechanism of the pathogenesis of the disease. A new novel approach utilizes the inflated balloons from the percutaneous coronary intervention for studying the atheroma proteome, which could possibly help overcome the difficulties in getting clinical samples at different progression stages. A combination of various mass spectrometry-based omics technologies will provide unprecedented coverage of biological information related to disease pathogenesis. The advances in instrumentation, the capability of generating MSn spectra, powerful bioinformatics tools for data analysis and improved well comprehensive databases enable reliable identification and characterization of the metabolites and proteins. Although a promising field, the true biological differences, most of the times, get concealed because of the sample sizes. Most of the studies conducted so far were confined to small sample sizes. The heterogeneity in the food habits, genetic makeup and other environmental factors may significantly distort the accurate picture of the conditions. Even though stupendous progress is being achieved to date in identifying the molecular features of atherosclerosis, further research is needed to achieve the aspirational level in the prevention and better management of the condition. A trans omics approach integrating genomics, epigenomics, proteomics and metabolomics information supported by the recent advancements in the extensive data analysis platforms provides more insights into the pathological conditions.

Abbreviation

PVD	Peripheral vascular diseases
CAD	Coronary artery diseases
STEMI	ST-Elevation myocardial infarction
IL-1	Interleukin-1
IL-6	Interleukin-6
TNF α	Tumor necrosis factor-alpha
IL-1 β	Interleukin-1beta
MALDI	Matrix-assisted laser desorption/ionization
HDL	High density lipoprotein
LDL	Low density lipoprotein
HETE	Hydroxyeicosatetranoic acid
SR-A1	Class A1 scavenger receptor
SR-A2	Class A2 scavenger receptor
LOX-1	Lectin-like oxidized LDL receptor-1

Author contributions

Conceptualization: J. P. A. and M. C.; literature collection: S. S., A., and A. C.; data curation and original draft writing: M. C.; and reviewing, editing, and finalizing the manuscript: J. P. A., A. J. and M. C. All authors have read and agreed to the published version of the manuscript.

Conflicts of interest

There are no conflicts to declare.

Acknowledgements

The figures in the article are created with http://BioRender.com.

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