Searching for Atherosclerosis Biomarkers by Proteomics

Searching for Atherosclerosis Biomarkers by Proteomics: Comparison

Please note this is a comparison between Version 2 by Catherine Yang and Version 1 by Antonio Junior Lepedda.

Plaque rupture and thrombosis are the most important clinical complications in the pathogenesis of stroke, coronary arteries, and peripheral vascular diseases. The identification of early biomarkers of plaque presence and susceptibility to ulceration could be of primary importance in preventing such life-threatening events. With the improvement of proteomic tools, large-scale technologies have been proven valuable in attempting to unravel pathways of atherosclerotic degeneration and identifying new circulating markers to be utilized either as early diagnostic traits or as targets for new drug therapies. To address these issues, different matrices of human origin, such as vascular cells, arterial tissues, plasma, and urine, have been investigated. Besides, proteomics was also applied to experimental atherosclerosis, to unveil significant insights into the mechanisms influencing atherogenesis. This narrative reviewesearch provides an overview of the last twenty-year -omics applications to the study of atherogenesis and lesion vulnerability, with particular emphasis on lipoproteomics and vascular tissue proteomics. Major issues of tissue analyses such as plaque complexity, sampling, availability, choice of proper controls, and lipoproteins purification will be raised, and future directions will be addressed.

proteomics of the atherosclerotic plaque
lipoproteomics
plaque vulnerability
atherogenesis

1. Application of MS-based Technologies to the Study of Lipoproteins Involvement in Atherogenesis

Lipoproteins are supramolecular complexes that deliver insoluble lipids from the tissues where they are synthesized to those that metabolize or store them. They consist of a hydrophobic core, mainly composed by triacylglycerol and cholesteryl esters, stabilized by a coat of amphipathic compounds, namely, phospholipids, unesterified cholesterol, and proteins, with the latter referred to as apolipoproteins (apo) [44]^[1]. Lipoproteins, especially low-density and high-density lipoproteins (LDL and HDL), have attracted a great deal of interest because of their implication in the development of cardiovascular diseases. LDL is the main carrier of cholesterol to the peripheral tissues, and a well-established major risk factor for atherosclerosis and cardiovascular disease [47]^[2], whereas HDL exerts significant vascular protective effects by facilitating the elimination of cholesterol excess from cells and its transport to the liver (reverse cholesterol transport) [49]^[3], besides performing antioxidant, anti-inflammatory, and anti-thrombotic activities [50]^[4].

In recent years, it has become more evident that the protein composition of each lipoprotein class is largely responsible for its various functions, particularly in relation to pathological conditions, including atherosclerosis. Consequently, acquiring detailed information about the composition and structure of their apolipoproteins cargo could potentially shed light on their involvement in atherogenesis and on the progression of atherosclerotic lesions, ultimately leading to the formation of vulnerable plaques. An updated list of all identified HDL (last update 20 April 2023) and LDL (last update 18 February 2015) proteins, ranked according to the frequency of identification in MS studies, can be downloaded at the “The Davidson/Shah lab” website (www.DavidsonLab.com). According to “The HDL Proteome Watch Database” by the Davidson Laboratory, which has included 51 proteomics studies on HDL, published up to 2022, 1030 proteins have been identified, of which 285 (defined as “likely” HDL proteins) have been reported by at least three different laboratories. Gene ontology analyses on the “likely” HDL proteins revealed that they are implicated in several biological processes including lipid transport, hemostasis/protease inhibition, inflammation/acute phase, immunity/anti-microbial, cell/heparin binding [67]^[5]. With regard to LDL, the Davidson database lists 60 proteins from 4 proteomics studies up to 2015; amidst these, 22 (defined as “likely” LDL proteins) were identified independently by at least two studies (apolipoproteins A-I, A-II, A-IV, B, C-I, C-II, C-III, C-IV, D, E, F, J, L1, M, (a), serum amyloid A1, A2, A4, albumin, alpha-1-antitrypsin, cathelicidin antimicrobial peptide, dermcidin, fibrinogen alpha chain).

Over the past two decades, numerous proteomic studies have been conducted on purified lipoprotein fractions, investigating both physiological and pathological conditions, the latter including coronary artery disease, acute myocardial infarction, chronic kidney disease, end-stage renal disease, type 1 and 2 diabetes mellitus, and experimental atherosclerosis (Table 1).

Table 1. Proteomic studies performed on purified lipoprotein fractions, investigating pathological conditions including coronary artery disease, acute myocardial infarction (), chronic kidney disease, end-stage renal disease (#), type 1 and 2 diabetes mellitus (§), and experimental atherosclerosis (ǂ). Reduced (↓) or increased (↑) levels of protein concentrations are indicated.

	Lipoprotein Fractions	Purification	Proteomics	Main Findings	References
⁕	Group 1: HDL from 20 healthy volunteers; Group 2: HDL3 from 6 controls and 7 CAD patients; Group 3: HDL3 from 32 controls and 32 CAD; HDL from atherosclerotic tissue	Ultracentrifugation/immunoaffinity chromatography	LC-ESI-MS/MS analysis	48 proteins identified in HDL involved in lipid metabolism, complement regulation, proteinase inhibition, acute-phase response. Apo C-IV, paraoxonase-1, Complement C3, apo A-IV, apo E (confirmed by WB on HDL3 fraction from 64 subjects) enriched in HDL3 from CAD. More than 100 proteins identified in HDL from atherosclerotic plaque	[51]^[6]
⁕	Group 1: HDL3 from 6 CAD, 6 CAD + Statin/Niacin, 6 healthy controls; Group 2: HDL3 from 18 CAD, 18 CAD + Statin/Niacin. 12 months therapy	Sequential density ultracentrifugation	LC-FTICR MS	After 12 months of therapy, ↓ apo E, ↑ apo F and PLTP; combination therapy may revert CAD-associated changes in HDL3 protein composition	[77]^[7]
⁕	HDL from 7 hypercholesterolemia subjects and 9 normolipidemic subjects	Salt Gradient Ultracentrifugation	LC-MS/MS analysis	The quantitative HDL protein pattern correlates with the corresponding concentration and distribution of cholesterol from serum lipid measurements; hypercholesterolemia in unrelated individuals is the result of different deficiencies	[78]^[8]
⁕	HDL2 from 18 CAD and 20 controls	Sequential density ultracentrifugation	MALDI-TOF-TOF MS and pattern recognition analysis; LC-MALDI-TOF/TOF MS	HDL2 from CAD contains methionine sulfoxide residues in apolipoprotein A-I and elevated levels of apolipoprotein C-III; specific proteomic signatures of HDL2 accurately classify CAD and control subjects	[79]^[9]
⁕	HDL from 10 healthy men with low HDL cholesterol and 10 men with high HDL cholesterol levels challenged with endotoxin	Immunoaffinity chromatography (anti-apo A-I antibodies); density gradient ultracentrifugation	PS20 protein-chips (anti-apo A-I antibodies) coupled with SELDI-TOF MS analysis/2DE analysis	Profound changes in 21 markers (including SAA-1/2 and paraoxonase-1) were observed in the proteome in both groups; no relationship between baseline HDL cholesterol levels and HDL protein dynamics after endotoxin challenge	[80]^[10]
⁕	HDL from 39 new-onset AMI-patients vs 60 healthy individuals	Salt Gradient Ultracentrifugation	2DE coupled with MALDI-TOF MS analysis	Altered glycosylation pattern in in AMI-patients within the first 6 h after the onset of the event	[81]^[11]
⁕	HDL from 10 healthy controls, 10 CAD and 10 ACS	Sequential ultracentrifugation	1DE coupled with LC-ESI-MS/MS analysis	67 HDL-associated proteins identified; ↓ apo A-IV, ↑ SAA, ↑ Complement C3 in ACS vs. both CAD and controls	[82]^[12]
⁕	HDL from CAD, ACS, and healthy controls	Sequential ultracentrifugation or gel filtration chromatography	LC-ESI-MS/MS analysis	clusterin, ↑ apolipoprotein C-III in both CAD and ACS; HDL-proteome remodeling plays an important role for these altered functional properties of HDL (stimulation of proapoptotic pathways)	[83]^[13]
⁕	VLDL, LDL and HDL from four pooled plasma samples from 79 patients undergoing carotid endarterectomy and 57 healthy normolipidemic volunteers	Density gradient ultracentrifugation	2DE coupled with MALDI-TOF-MS	↑ acute-phase serum amyloid A protein (AP SAA) in all lipoprotein fractions, especially in LDL from atherosclerotic patients	[84]^[14]
⁕	HDL3 from 3 low HDL-c and 3 high HDL-c subjects	Density gradient ultracentrifugation	Top-Down differential Mass Spectrometry: ETD LC-ESI-MS/MS	Proof-of-concept study; higher abundances of three apo C-III glycoforms in HDL3 from donors with low HDL-c	[85]^[15]
⁕	HDL from 10 CHD patients vs. 10 controls	Sequential ultracentrifugation	iTRAQ technology coupled with nanoLC-MS/MS	196 proteins identified, 5 up-regulated proteins (inflammatory reactions) and 7 down-regulated (lipid metabolism) proteins; HDL proteome changes to a pro-atherogenic profile in CHD patients	[86]^[16]
⁕	HDL₂ and HDL₃ from 40 ACS vs. 40 controls	Two-step discontinuous density-gradient ultracentrifugation	2DE and 2DIGE analysis coupled with MALDI-TOF/TOF MS	17 differentially expressed HDL-associated proteins identified, shifting to a dysfunctional HDL subfractions	[87]^[17]
⁕	HDL from diabetes and CVD	Sequential ultracentrifugation	Multi-Analyte Profiling (MAP)/LC-MRM/MS	69 and 32 HDL proteins quantified respectively with MAP and MRM; high-throughput approach to examine changes in HDL proteins in diabetes and CVD	[88]^[18]
⁕	HDL from 21 CAD pre- and post- percutaneous transluminal coronary angioplasty (PTCA)	Immunoaffinity chromatography (anti-apo A-I antibodies)	Quantitative ¹⁶O/¹⁸O analysis/iTRAQ technology coupled with LC–MS/MS/system biology analysis	225 identified proteins; high protein variability in HDL composition between individuals; post-PTCA increase in two protein clusters that included several apolipoproteins, fibrinogen-like protein 1 and other intracellular proteins, and a decrease in antithrombin-III, annexin A1 and several immunoglobulins	[89]^[19]
⁕	HDL from 20 subjects at risk for CAD: 10 patients had CAD and 10 did not	Sequential ultracentrifugation	Shotgun proteomic, glycomic, and ganglioside analyses using LC-MS	combined HDL proteomic and glycomic profiles distinguished at-risk subjects with atherosclerosis from those without; CAD patients had ↓ apo A-I, , ↓ SAA2, ↓ SAA4 (p = 0.007), ↑ sialylated glycans	[90]^[20]
⁕	HDL from 33 hypercholesterolemic subjects included in a clinical trial evaluating effects of virgin olive oil (VOO) and phenol- enriched VOO	Sequential density ultracentrifugation	nano LC-MALDI MS/MS and nano LC-ORBITRAP-ESI MS/MS	127 HDL-associated proteins identified; 15 differentially expressed proteins involved in LXR/RXR activation, acute phase response, and atherosclerosis; Consumption of VOO or phenol-enriched VOOs, has an impact on the HDL proteome in a cardioprotective mode by up-regulating proteins related to cholesterol homeostasis, protection against oxidation and blood coagulation while down-regulating proteins implicated in acute-phase response, lipid transport, and immune response	[91]^[21]
⁕	HDL from 54 SLE patients (with and without atherosclerotic plaque), 25 controls, patients with type 1 diabetes with or without coronary artery calcification	Sequential density gradient ultracentrifugation	Targeted proteomics (18 proteins): LC-ESI-MS/MS analysis	↓ PON3 in HDL of both SLE and T1DM patients with subclinical atherosclerosis	[92]^[22]
⁕	LDL and HDL from 10 healthy individuals with normal LDL-C treated with rosuvastatin for 28 days	Size-exclusion chromatography	LC-ESI-MS/MS analysis	Among the differentially expressed proteins, α-1-antirypsin increased dramatically in HDL; enhanced HDL anti-inflammatory activity, contributing to the non-lipid lowering beneficial effects of statins	[93]^[23]
⁕	HDL from 5 chronic heart failure (CHF) patients vs. 5 controls	Sequential ultracentrifugation	SCX/RP LC–MS/MS	494 proteins identified; 23 newly identified HDL-associated proteins; 223 bacterial peptides were found in both CHF and controls	[94]^[24]
⁕	HDL from 14 abdominal aortic aneurism (AAA) patients vs. 7 controls	Sequential ultracentrifugation	iTRAQ technology coupled with nanoLC-MS/MS	↑ peroxiredoxin-6 (PRDX6), ↑ HLA class I histocompatibility antigen, ↑ retinol-binding protein 4, ↑ paraoxonase/arylesterase 1, ↓ α-2 macroglobulin, ↓ C4b-binding protein	[95]^[25]
⁕	HDL from 10 CVD vs. 7 controls	Two-step discontinuous density-gradient ultracentrifugation	nLC-MS/MS analysis	118 proteins identified; 10 proteins positively associated with the combined level of persistent organic pollutants (POPs) or with highly chlorinated polychlorinated biphenyls (PCB) congeners. Among these, cholesteryl ester transfer protein and phospholipid transfer protein, as well as the inflammatory marker serum amyloid A, were found. The serum paraoxonase/arylesterase 1 activity was inversely associated with POPs. Pathway analysis demonstrated that up-regulated proteins were associated with biological processes involving lipoprotein metabolism, while down-regulated proteins were associated with processes such as negative regulation of proteinases, acute phase response, platelet degranulation, and complement activation.	[96]^[26]
⁕	HDL from 126 subjects with clinical indication for a coronary CT angiography	High-resolution size exclusion chromatography followed by phospholipid-associated proteins capture (Calcium Silicate Hydrate)	LC-ESI-MS/MS	72 HDL-associated proteins detected in at least 75% of subjects; 13 proteins significantly associated with calcified plaque burden including cathelicidin antimicrobial peptide, gelsolin (GELS), kininogen-1 (KNG1), and paraoxonase-1 (inverse relationships), apo A-IV, vitamin D binding protein, alpha-2- macroglobulin, and apo C-II (positive relationships); 15 proteins significantly associated with non-calcified plaque burden including apo A-I, apo F, antithrombin III, and apo C-I (inverse relationships), serum amyloid A1, immunoglobulin heavy constant alpha 1, complement factor B, complement C2, complement C3, complementbC1s subcomponent (positive relationships); among the evaluated risk factors, BMI has the greatest overall impact on the protein composition of HDL	[97]^[27]
⁕	HDL from heart failure patients: cardiovascular deaths vs. survivors (1:1)	Calcium silicate matrix	nLC-MS/MS analysis	647 proteins identified; 49 HDL proteins were significantly different; a set of 12 selected proteins predicted death with 76% accuracy	[98]^[28]
⁕	HDL from 943 participants without prevalent myocardial infarction referred for coronary angiography in the CASABLANCA study	¹⁵NHis₆Apo A-I was added to human serum, incubated, diluted, and then purified using PhyTips (Phynexus, San Jose, CA, USA), packed with Ni-NTA HisBind Superflow stationary phase	Targeted proteomics (apolipoprotein A-I, C-1, C-2, C-3, and C-4): LC-ESI-MS/MS analysis	An HDL apolipoproteomic score is associated with the presence of CAD, independent of circulating apo A-I and apo B concentrations and other conventional cardiovascular risk factors. Among individuals with CAD, this score may be independently associated cardiovascular death	[99]^[29]
⁕	Apolipoprotein AI-Associated Lipoproteins from 231 healthy individuals and patients with coronary artery disease	Metal chelate affinity chromatography	Targeted proteomics (21 proteins): LC-MS/MS analysis	A multiplexed proteomic assay useful for the estimation of cholesterol efflux and CAD risk in the clinical laboratory	[100]^[30]
⁕	HDL from 8 patients with complete deficiency of CETP vs. 8 normolipidemic healthy subjects	Sequential ultracentrifugation	LC-MS/MS analysis	79 HDL-associated proteins identified, involved in lipid metabolism, protease inhibition, complement regulation, and acute-phase response, including 5 potential newly identified HDL-associated proteins; ↑ apo E, ↑ Complement C3, C4a, C4b, and C9, ↑ apo C-III	[101]^[31]
⁕	HDL from patients after acute ischemic stroke at 2 time points (24 h, 35 patients; 96 h, 20 patients) and from 35 control subjects	Sequential density ultracentrifugation	Data-dependent acquisition (DDA) mass spectrometry and parallel reaction monitoring (PRM) mass spectrometry	Some proteins involved in acute phase response and platelet activation were significantly altered in stroke HDL at 24 and 96 h (p < 0.05). Accordingly, cholesterol efflux capacity was reduced by 32% (p < 0.001) at both time points	[102]^[32]
⁕	HDL from 46 incident new CVD and 46 one-to-one matched controls, at various stages of CKD	Sequential ultracentrifugation	Targeted proteomics (31 proteins): LC-MS/MS analysis	PON1, PON3, LCAT, and apolipoprotein A-IV levels inversely associated with incident CVD events in CKD patients	[103]^[33]
⁕	HDL and LDL from pooled plasma samples from 75 patients undergoing carotid endarterectomy and 50 healthy normolipidemic volunteers	Density gradient ultracentrifugation	nanoLC-MS/MS	Protein signatures specific for patients with “hard” or “soft” carotid plaques	[56]^[34]
#	HDL from 27 ESRD vs. 19 healthy subjects	Salt Gradient Ultracentrifugation	LC-MS/MS Analysis	35 HDL-associated proteins identified; antitrypsin, retinol-binding protein 4 (RBP4), transthyretin, apo A-VI, and further minor proteins were exclusively detected in uremic HDL; ↑ SAA1, ↑albumin, ↑lipoprotein-associated phospholipase A2, ↑ apo C-III, ↓ apo A-I, ↓ apo A-II	[104]^[35]
#	HDL from 7 chronic hemodialysis patients vs. 7 healthy controls	Sequential density ultracentrifugation	iTRAQ technology coupled with 2D nano-LC-MALDI-TOF/TOF MS	122 proteins identified, 40 proteins differentially expressed	[105]^[36]
#	HDL from 34 ESRD vs. 17 healthy controls	Sequential density ultracentrifugation	HPLC coupled with MALDI-TOF-TOF MS	SAA is enriched in HDL from ESRD patients correlating with its reduced anti-inflammatory capacity	[106]^[37]
#	HDL from 10 ESRD vs. 10 healthy controls	Sequential ultracentrifugation	1DE coupled with LC-ESI-MS/MS analysis	49 HDL-associated proteins identified; ↑ surfactant protein B (SP-B), ↑ apolipoprotein C-II, ↑ serum amyloid A (SAA), ↑ α-1-microglobulin/bikunin precursor; SAA promotes inflammatory cytokine production	[107]^[38]
#	HDL from 40 ESRD vs. 20 controls	Sequential ultracentrifugation	LC-ESI-MS/MS analysis	63 identified proteins; ↑ 22 proteins, ↓ 6 proteins; HDL proteome is extensively remodeled in uremic subjects	[108]^[39]
#	HDL from 509 CKD; eGFR > 60 mL/min/1.73 m² vs. eGFR < 15 mL/min/1.73 m²	Two-step density gradient ultracentrifugation	nLC-MS/MS analysis (targeted proteomics: quantification of 38 HDL-proteins)	↑ retinol binding protein 4, ↑ apo C-III, ↑ apo L1, ↓ vitronectin	[109]^[40]
#	HDL from 143 patients starting hemodialysis vs. 110 patients with advanced CKD	Two-step density gradient ultracentrifugation	nLC-MS/MS analysis (targeted proteomics: quantification of 38 HDL-proteins)	↑ serum amyloid A1, A2, and A4, ↑ hemoglobin-b, ↑ haptoglobin-related protein, ↑ cholesteryl ester transfer protein, ↑ phospholipid transfer protein, ↑ apo E; hemodialysis initiation is associated with higher concentrations of HDL-proteins related to inflammation and lipid metabolism	[110]^[41]
#	HDL from 9 non-diabetic hemodialysis patients vs. 8 control patients	Sequential ultracentrifugation	nLC-Quadrupole-Orbitrap-MS	326 proteins identified; ↑ 10 proteins (UDP-glucose: glycoprotein glucosyltransferase 1, Beta-2-microglobulin, Pulmonary surfactant-associated protein B, Protein AMBP, Insulin-like growth factor II, Immunoglobulin heavy constant alpha 2, Immunoglobulin lambda constant 2, HLA class I histocompatibility antigen B-58 alpha chain, Complement factor D, Inter-alpha-trypsin inhibitor heavy chain H1), ↓ 9 proteins (Guanylin, Calpain-1 catalytic subunit, Keratin, type I cytoskeletal, Ras-related protein Rab-6B, Ganglioside GM2 activator, Prostaglandin-H2 D-isomerase, Secretoglobin family 3A member 2, Thioredoxin-dependent peroxide reductase mitochondrial, Solute carrier family 2 facilitated glucose transporter member 2) involved in lipid metabolism, hemostasis, wound healing, oxidative stress, and apoptosis pathways.	[111]^[42]
§	HDL from 30 T1DM vs. 30 controls	Single Vertical Spin Density Gradient Ultracentrifugation	LC-ESI-MS/MS analysis	Compromised HDL anti-oxidant functions due to higher abundance of irreversible PTMs of proteins in T1DM	[112]^[43]
§	HDL from 191 T1DM subjects	Sequential ultracentrifugation	Targeted proteomics (46 proteins): LC-ESI-MS/MS analysis	8 proteins associated with albuminuria including AMBP (α1-microglobulin/bikunin precursor) and PTGDS (prostaglandin-H2 D-isomerase) that strongly and positively associated with the albumin excretion rate. PON1 and PON3 levels in HDL strongly and negatively associated with the presence of coronary artery calcium. Only PON1, associated with both albumin excretion rate and coronary artery calcification. The HDL proteome is remodeled in type 1 diabetes mellitus subjects with albuminuria.	[113]^[44]
§	HDL from 26 patients with T1DM vs. 13 healthy controls	High-resolution size exclusion chromatography followed by phospholipid-associated proteins capture (Calcium Silicate Hydrate)	nLC-TripleTOF-MS	78 HDL-bound proteins were measured; Youth with T1DM have proteomic alterations of their HDL compared to HC, despite similar concentration of HDL cholesterol. The influence of these compositional changes on HDL function are not yet known	[114]^[45]
§	HDL from two cohorts of T1DM patients (n = 47, n = 100). T1D without complications vs. T1D with complications	Sequential density ultracentrifugation	Targeted proteomics (35 proteins): LC-MS/MS analysis	Elevated concentrations of M-HDL particles and elevated levels of HDL-associated PON1 may contribute to long-term protection from the vascular complications of diabetes by pathways that are independent of total cholesterol and HDL cholesterol. ↑ apo C-I, apo E, complement C3, apo C-II, apo M, and PON1, ↓ apo A-IV and retinol-binding protein 4 (RBP4). In the female subgroup analysis: ↑ apo C1 and PON1, ↓ apo A-IV. Targeted proteomics in the replication cohort: ↑ PON1	[115]^[46]
§	HDL from 9 newly diagnosed T2D patients and 8 healthy controls	Immunoaffinity chromatography	LC-MS/MS	Plasma adiponectin levels were reduced in subjects with T2D, which was directly associated with suppressed ABCA1-dependent cholesterol efflux capacity of HDL. The fractional catabolic rates of HDL cholesterol, apo A-II, apo J, apo A-IV, transthyretin, complement C3, and vitamin D-binding protein (all p < 0.05) were increased in subjects with T2D. Despite increased HDL flux of acute-phase HDL proteins, there was no change in the proinflammatory index of HDL. Although LCAT and CETP activities were not affected in subjects with T2D, LCAT was inversely associated with blood glucose and CETP was inversely associated with plasma adiponectin. The degradation rates of apo A-II and apo A-IV were correlated with hemoglobin A1c. In conclusion, there were in vivo impairments in HDL proteome dynamics and HDL metabolism in diet-controlled patients with T2D.	[116]^[47]
§	HDL from obese adolescents with T1D (25 treated with metformin as adjunct therapy and 10 with placebo): double-blind, placebo-controlled clinical trial	Size-exclusion chromatography followed by lipophilic absorption	Data-independent acquisition (DIA) mass spectrometry	Two proteins out of eighty-four were significantly affected by metformin treatment, peptidoglycan recognition protein 2 and alpha-2-macroglobulin. Metformin did not significantly affect cholesterol efflux capacity (CEC). Changes in affected HDL proteins did not correlate with CEC	[117]^[48]
§	HDL2 and HDL3 from case–control study that enrolled 50 T1D and 30 non-diabetes control individuals	Discontinuous density ultracentrifugation	45 proteins quantified by parallel reaction monitoring	13 proteins in HDL2 and 33 in HDL3 were differentially expressed in T1D. Six proteins related to lipid metabolism, one to inflammatory acute phase, one to complement system and one to antioxidant response were more abundant in HDL2, while 14 lipid metabolism, three acute-phase, three antioxidants and one transport in HDL3 of T1D subjects. Three proteins (lipid metabolism, transport, and unknown function) were more abundant in HDL2; and ten (lipid metabolism, transport, protease inhibition), more abundant in HDL3 of controls.	[118]^[49]
ǂ	HDL from C57BL/6 mice challenged with intraperitoneal endotoxin vs. controls injected with saline	Sequential ultracentrifugation	Two-dimensional gel electrophoresis (2DE) coupled with LC-MS/MS analysis	↑ SAA, apo E, apo A-IV, apo A-V; ↓ apo A-I, apo A-II	[119]^[50]
ǂ	HDL from C57BL/6j mice following 24 weeks on SFA- or MUFA-enriched high-fat diets (HFDs) or low-fat diet	Fast protein liquid chromatography (FPLC)	nLC-ESI-MS/MS analysis	HDL particles were enriched with acute-phase proteins (serum amyloid A, haptoglobin, and hemopexin) and depleted of paraoxonase-1 after SFA-HFD in comparison with MUFA-HFD.	[120]^[51]
ǂ	HDL from knock out (for apo A-I, apo A-II or apo A-IV) and wild type C57BL/6J mice	High-resolution size exclusion chromatography followed by phospholipid-associated proteins capture (Calcium Silicate Hydrate)	LC-ESI-MS/MS analysis	Loss of apo A-I or apo A-II massively reduced HDL lipids and changed the plasma size pattern and/or abundance of several plasma proteins. Surprisingly though, many HDL proteins were not affected, suggesting they assemble on lipid particles in the absence of apo A-I or apo A-II. In contrast, apo A-IV ablation had minor effects on plasma lipids and proteins, suggesting that it forms particles that largely exclude other apolipoproteins. Overall, the data indicate that distinct HDL subpopulations exist that do not contain, nor depend on, apo A-I, apo A-II or apo A-IV and these contribute substantially to the proteomic diversity of HDL.	[93]^[23]
ǂ	HDL from Scavenger receptor class B type I −/− mice vs. WT mice	Apo B containing lipoproteins precipitation followed by ultracentrifugation	LC–MS/MS analysis/2DE analysis	↓ apo A-I, ↓ PON1, ↑ SAA, ↑ apo A-IV, ↑ α-1-antitrypsin; impaired cholesterol homeostasis in macrophages, and reduced anti-oxidative and anti-inflammatory effects	[121]^[52]

Despite providing valuable insights into the various functions of each lipoprotein class in relation to cardiovascular disease, there is currently a lack of additional information necessary to assess the risk of acute clinical event onset. Indeed, the multifaceted biological functions of lipoproteins, especially HDL, arise from the combined protein and lipid components, and any disruptions or modifications of these components can lead to dysfunctional particles [122]^[53]. In recent years, there has been a growing interest in plasma lipidomics due to compelling evidence linking specific plasma lipid species to the development of atherosclerosis [38^{[54][55][56][57][58][59][60][61]}, 123-129], and the onset of adverse clinical events [39, 130-134]^{[62][63][64][65][66][67]}. However, to date, only a limited number of studies have explored the association between biologically active lipids, particularly those associated with their lipoprotein carriers, and cardiovascular disease (CVD), as also recently reviewed by Ding and Rexrode [135]^[68].

2. Atherosclerotic Plaque Dissection through Proteomics

In the last years, different proteomic technologies have been applied to human diseased tissues to provide further insights on the molecular mechanisms of advanced atherosclerotic plaque development, as well as to identify diagnostic traits of plaque instability useful as therapeutic targets or as markers for patient’s follow-up. With this aim, both plaque extracts and secretomes, obtained by culturing different typologies of plaque segments, have been the topic of these studies. Besides, to delve deeper into the mechanisms underlying the early stages of lesion formation, some animal models, mainly rodents, have been investigated.

Although tissue analyses frequently provide useful information, there are major issues in analyzing human atheromas specimens. In fact, the atherosclerotic plaque environment is a very complex tissue in terms of cell types involved, as well as inflammatory, proteolytic, and oxidative mechanisms, which ultimately reflects a systemic condition resulting from the long-term persistence of multiple environmental and genetic risk factors. In this respect, besides vascular smooth muscle cells and endothelial cells, plaque contains many types of inflammatory cells, filtered plasma proteins, newly formed extracellular matrix, cellular debris and end-products of lipid and protein oxidation . This issue could be partially overcome by selecting specific cells or plaque areas using LCM, a path explored only to a limited extent by proteomics, which holds significant promises. Another critical point of the in situ analyses is the choice of the appropriate control. To minimize inherent tissue differences, it would be desirable to use control specimens from the same vascular district of the same patient. Furthermore, specimens should be from surgical endarterectomy rather than from post-mortem material, to avoid tissue degradation before the analysis. The availability of a poor number of human specimens could be a limitation, as well. Because of the heterogeneity of the different types of advanced lesions in terms of fibrous cap thickness, inflammatory and proteolytic components, calcifications, surface erosion, thrombosis, and intraplaque hemorrhage, careful histochemical classification prior to biochemical analyses is desirable [154, 155]^[69][70]. Theoretically, the secretome should reflect the tissue-specific metabolic activities in both physiological and pathological conditions. With respect to plasma, it is also characterized by a lower number of protein species as well as a narrower dynamic range of concentrations. Therefore, it may represent a rich source of biomarkers with potential implications in clinical practice. Proteomics has been also applied to widely used animal models of atherosclerosis to unveil significant insights into the molecular mechanisms influencing atherogenesis. In this respect, apolipoprotein E-deficient mouse is the most widely used murine model in cardiovascular research.

3. Conclusions

In the last years, proteomics has emerged as a powerful tool in the search for novel cardiovascular biomarkers with diagnostic/prognostic value, offering an unparalleled opportunity to capture the multifaceted aspects of atherosclerosis and its progression, and bridging the gap between fundamental research and practical clinical applications. Both lipoproteins and atherosclerotic tissues, particularly plaque extracts and secretomes, represent a rich source of information with regards to both early events of atherogenesis and predictors of acute clinical events. Furthermore, the analysis of LCM by proteomics, although in its infancy, could reveal valuable topological differences between specific areas of such a heterogeneous environment. However, several issues hinder the step towards the translational medicine: in primis, the intrinsic complexity of the atherosclerotic tissue, its availability, as well as the choice of the proper controls, which could hinder the interpretation of the results. Besides, large-scale studies are required to validate the usefulness of the newly identified biomarkers. Finally, although several database enclosing results from genome-wide association studies or gene expression profiling exist, as far as we know, no no proteomics dataset focused on atherosclerosis are available. Therefore, in the next future, it will be essential to dedicate efforts in conducting a thorough investigation of the vast amount of data generated so far by proteomics and to create shared datasets to collect all the identified markers. In this respect, artificial intelligence tools could represent a profound change in data analysis and interpretation, being able to perform both fast and iterative processing on a large amount of information, such as those obtained by means of all abovementioned technologies.

References

Jonas, A.; Phillips, M.C. Chapter 17—Lipoprotein structure. In Biochemistry of Lipids, Lipoproteins and Membranes, 5th ed.; Vance, D.E., Vance, J.E., Eds.; Elsevier: Amsterdam, The Netherlands, 2008; pp. 485–506.
Ferhatbegovic, L.; Mrsic, D.; Kusljugic, S.; Pojskic, B. LDL-c: The only causal risk factor for ascvd. Why is it still overlooked and underestimated? Curr. Atheroscler. Rep. 2022, 24, 635–642.
Ouimet, M.; Barrett, T.J.; Fisher, E.A. HDL and reverse cholesterol transport. Circ. Res. 2019, 124, 1505–1518.
Kajani, S.; Curley, S.; McGillicuddy, F.C. Unravelling HDL-looking beyond the cholesterol surface to the quality within. Int. J. Mol. Sci. 2018, 19, 1971.
Davidson, W.S.; Shah, A.S.; Sexmith, H.; Gordon, S.M. The HDL proteome watch: Compilation of studies leads to new insights on HDL function. Biochim. Biophys. Acta Mol. Cell Biol. Lipids 2022, 1867, 159072.
Vaisar, T.; Pennathur, S.; Green, P.S.; Gharib, S.A.; Hoofnagle, A.N.; Cheung, M.C.; Byun, J.; Vuletic, S.; Kassim, S.; Singh, P.; et al. Shotgun proteomics implicates protease inhibition and complement activation in the antiinflammatory properties of HDL. J. Clin. Investig. 2007, 117, 746–756.
Green, P.S.; Vaisar, T.; Pennathur, S.; Kulstad, J.J.; Moore, A.B.; Marcovina, S.; Brunzell, J.; Knopp, R.H.; Zhao, X.Q.; Heinecke, J.W. Combined statin and niacin therapy remodels the high-density lipoprotein proteome. Circulation 2008, 118, 1259–1267.
Heller, M.; Schlappritzi, E.; Stalder, D.; Nuoffer, J.M.; Haeberli, A. Compositional protein analysis of high density lipoproteins in hypercholesterolemia by shotgun lc-ms/ms and probabilistic peptide scoring. Mol. Cell. Proteom. 2007, 6, 1059–1072.
Vaisar, T.; Mayer, P.; Nilsson, E.; Zhao, X.Q.; Knopp, R.; Prazen, B.J. HDL in humans with cardiovascular disease exhibits a proteomic signature. Clin. Chim. Acta Int. J. Clin. Chem. 2010, 411, 972–979.
Levels, J.H.; Geurts, P.; Karlsson, H.; Maree, R.; Ljunggren, S.; Fornander, L.; Wehenkel, L.; Lindahl, M.; Stroes, E.S.; Kuivenhoven, J.A.; et al. High-density lipoprotein proteome dynamics in human endotoxemia. Proteome Sci. 2011, 9, 34.
Cubedo, J.; Padro, T.; Garcia-Moll, X.; Pinto, X.; Cinca, J.; Badimon, L. Proteomic signature of apolipoprotein j in the early phase of new-onset myocardial infarction. J. Proteome Res. 2011, 10, 211–220.
Alwaili, K.; Bailey, D.; Awan, Z.; Bailey, S.D.; Ruel, I.; Hafiane, A.; Krimbou, L.; Laboissiere, S.; Genest, J. The HDL proteome in acute coronary syndromes shifts to an inflammatory profile. Biochim. Biophys. Acta (BBA) Mol. Cell Biol. Lipids 2012, 1821, 405–415.
Riwanto, M.; Rohrer, L.; Roschitzki, B.; Besler, C.; Mocharla, P.; Mueller, M.; Perisa, D.; Heinrich, K.; Altwegg, L.; von Eckardstein, A.; et al. Altered activation of endothelial anti- and proapoptotic pathways by high-density lipoprotein from patients with coronary artery disease: Role of high-density lipoprotein-proteome remodeling. Circulation 2013, 127, 891–904.
Lepedda, A.J.; Nieddu, G.; Zinellu, E.; De Muro, P.; Piredda, F.; Guarino, A.; Spirito, R.; Carta, F.; Turrini, F.; Formato, M. Proteomic analysis of plasma-purified VLDL, LDL, and HDL fractions from atherosclerotic patients undergoing carotid endarterectomy: Identification of serum amyloid a as a potential marker. Oxidative Med. Cell. Longev. 2013, 2013, 385214.
Mazur, M.T.; Cardasis, H.L. Quantitative analysis of apolipoproteins in human HDL by top-down differential mass spectrometry. Methods Mol. Biol. 2013, 1000, 115–137.
Yan, L.R.; Wang, D.X.; Liu, H.; Zhang, X.X.; Zhao, H.; Hua, L.; Xu, P.; Li, Y.S. A pro-atherogenic HDL profile in coronary heart disease patients: An itraq labelling-based proteomic approach. PLoS ONE 2014, 9, e98368.
Tan, Y.; Liu, T.R.; Hu, S.W.; Tian, D.; Li, C.; Zhong, J.K.; Sun, H.G.; Luo, T.T.; Lai, W.Y.; Guo, Z.G. Acute coronary syndrome remodels the protein cargo and functions of high-density lipoprotein subfractions. PLoS ONE 2014, 9, e94264.
Yassine, H.N.; Jackson, A.M.; Borges, C.R.; Billheimer, D.; Koh, H.; Smith, D.; Reaven, P.; Lau, S.S.; Borchers, C.H. The application of multiple reaction monitoring and multi-analyte profiling to HDL proteins. Lipids Health Dis. 2014, 13, 8.
Jorge, I.; Burillo, E.; Mesa, R.; Baila-Rueda, L.; Moreno, M.; Trevisan-Herraz, M.; Silla-Castro, J.C.; Camafeita, E.; Ortega-Munoz, M.; Bonzon-Kulichenko, E.; et al. The human HDL proteome displays high inter-individual variability and is altered dynamically in response to angioplasty-induced atheroma plaque rupture. J. Proteom. 2014, 106, 61–73.
Krishnan, S.; Huang, J.; Lee, H.; Guerrero, A.; Berglund, L.; Anuurad, E.; Lebrilla, C.B.; Zivkovic, A.M. Combined high-density lipoprotein proteomic and glycomic profiles in patients at risk for coronary artery disease. J. Proteome Res. 2015, 14, 5109–5118.
Pedret, A.; Catalan, U.; Fernandez-Castillejo, S.; Farras, M.; Valls, R.M.; Rubio, L.; Canela, N.; Aragones, G.; Romeu, M.; Castaner, O.; et al. Impact of virgin olive oil and phenol-enriched virgin olive oils on the HDL proteome in hypercholesterolemic subjects: A double blind, randomized, controlled, cross-over clinical trial (VOHF study). PLoS ONE 2015, 10, e0129160.
Marsillach, J.; Becker, J.O.; Vaisar, T.; Hahn, B.H.; Brunzell, J.D.; Furlong, C.E.; de Boer, I.H.; McMahon, M.A.; Hoofnagle, A.N.; Group, D.E.R. Paraoxonase-3 is depleted from the high-density lipoproteins of autoimmune disease patients with subclinical atherosclerosis. J. Proteome Res. 2015, 14, 2046–2054.
Gordon, S.M.; Li, H.; Zhu, X.; Tso, P.; Reardon, C.A.; Shah, A.S.; Lu, L.J.; Davidson, W.S. Impact of genetic deletion of platform apolipoproteins on the size distribution of the murine lipoproteome. J. Proteom. 2016, 146, 184–194.
Oberbach, A.; Adams, V.; Schlichting, N.; Heinrich, M.; Kullnick, Y.; Lehmann, S.; Lehmann, S.; Feder, S.; Correia, J.C.; Mohr, F.W.; et al. Proteome profiles of HDL particles of patients with chronic heart failure are associated with immune response and also include bacteria proteins. Clin. Chim. Acta Int. J. Clin. Chem. 2016, 453, 114–122.
Burillo, E.; Jorge, I.; Martinez-Lopez, D.; Camafeita, E.; Blanco-Colio, L.M.; Trevisan-Herraz, M.; Ezkurdia, I.; Egido, J.; Michel, J.B.; Meilhac, O.; et al. Quantitative HDL proteomics identifies peroxiredoxin-6 as a biomarker of human abdominal aortic aneurysm. Sci. Rep. 2016, 6, 38477.
Ljunggren, S.A.; Helmfrid, I.; Norinder, U.; Fredriksson, M.; Wingren, G.; Karlsson, H.; Lindahl, M. Alterations in high-density lipoprotein proteome and function associated with persistent organic pollutants. Environ. Int. 2017, 98, 204–211.
Gordon, S.M.; Chung, J.H.; Playford, M.P.; Dey, A.K.; Sviridov, D.; Seifuddin, F.; Chen, Y.C.; Pirooznia, M.; Chen, M.Y.; Mehta, N.N.; et al. High density lipoprotein proteome is associated with cardiovascular risk factors and atherosclerosis burden as evaluated by coronary ct angiography. Atherosclerosis 2018, 278, 278–285.
Emmens, J.E.; Jones, D.J.L.; Cao, T.H.; Chan, D.C.S.; Romaine, S.P.R.; Quinn, P.A.; Anker, S.D.; Cleland, J.G.; Dickstein, K.; Filippatos, G.; et al. Proteomic diversity of high-density lipoprotein explains its association with clinical outcome in patients with heart failure. Eur. J. Heart Fail. 2018, 20, 260–267.
Natarajan, P.; Collier, T.S.; Jin, Z.; Lyass, A.; Li, Y.; Ibrahim, N.E.; Mukai, R.; McCarthy, C.P.; Massaro, J.M.; D’Agostino, R.B., Sr.; et al. Association of an HDL apolipoproteomic score with coronary atherosclerosis and cardiovascular death. J. Am. Coll. Cardiol. 2019, 73, 2135–2145.
Jin, Z.; Collier, T.S.; Dai, D.L.Y.; Chen, V.; Hollander, Z.; Ng, R.T.; McManus, B.M.; Balshaw, R.; Apostolidou, S.; Penn, M.S.; et al. Development and validation of apolipoprotein ai-associated lipoprotein proteome panel for the prediction of cholesterol efflux capacity and coronary artery disease. Clin. Chem. 2019, 65, 282–290.
Okada, T.; Ohama, T.; Takafuji, K.; Kanno, K.; Matsuda, H.; Sairyo, M.; Zhu, Y.; Saga, A.; Kobayashi, T.; Masuda, D.; et al. Shotgun proteomic analysis reveals proteome alterations in HDL of patients with cholesteryl ester transfer protein deficiency. J. Clin. Lipidol. 2019, 13, 317–325.
Plubell, D.L.; Fenton, A.M.; Rosario, S.; Bergstrom, P.; Wilmarth, P.A.; Clark, W.M.; Zakai, N.A.; Quinn, J.F.; Minnier, J.; Alkayed, N.J.; et al. High-density lipoprotein carries markers that track with recovery from stroke. Circ. Res. 2020, 127, 1274–1287.
Shao, B.; Mathew, A.V.; Thornock, C.; Pennathur, S.; Michigan Kidney Translational Core, C.I.G. Altered HDL proteome predicts incident cvd in chronic kidney disease patients. J. Lipid Res. 2021, 62, 100135.
Finamore, F.; Nieddu, G.; Rocchiccioli, S.; Spirito, R.; Guarino, A.; Formato, M.; Lepedda, A.J. Apolipoprotein signature of HDL and LDL from atherosclerotic patients in relation with carotid plaque typology: A preliminary report. Biomedicines 2021, 9, 1156.
Holzer, M.; Birner-Gruenberger, R.; Stojakovic, T.; El-Gamal, D.; Binder, V.; Wadsack, C.; Heinemann, A.; Marsche, G. Uremia alters HDL composition and function. J. Am. Soc. Nephrol. JASN 2011, 22, 1631–1641.
Mange, A.; Goux, A.; Badiou, S.; Patrier, L.; Canaud, B.; Maudelonde, T.; Cristol, J.P.; Solassol, J. HDL proteome in hemodialysis patients: A quantitative nanoflow liquid chromatography-tandem mass spectrometry approach. PLoS ONE 2012, 7, e34107.
Tolle, M.; Huang, T.; Schuchardt, M.; Jankowski, V.; Prufer, N.; Jankowski, J.; Tietge, U.J.; Zidek, W.; van der Giet, M. High-density lipoprotein loses its anti-inflammatory capacity by accumulation of pro-inflammatory-serum amyloid a. Cardiovasc. Res. 2012, 94, 154–162.
Weichhart, T.; Kopecky, C.; Kubicek, M.; Haidinger, M.; Doller, D.; Katholnig, K.; Suarna, C.; Eller, P.; Tolle, M.; Gerner, C.; et al. Serum amyloid a in uremic HDL promotes inflammation. J. Am. Soc. Nephrol. JASN 2012, 23, 934–947.
Shao, B.; de Boer, I.; Tang, C.; Mayer, P.S.; Zelnick, L.; Afkarian, M.; Heinecke, J.W.; Himmelfarb, J. A cluster of proteins implicated in kidney disease is increased in high-density lipoprotein isolated from hemodialysis subjects. J. Proteome Res. 2015, 14, 2792–2806.
Rubinow, K.B.; Henderson, C.M.; Robinson-Cohen, C.; Himmelfarb, J.; de Boer, I.H.; Vaisar, T.; Kestenbaum, B.; Hoofnagle, A.N. Kidney function is associated with an altered protein composition of high-density lipoprotein. Kidney Int. 2017, 92, 1526–1535.
Wang, K.; Zelnick, L.R.; Hoofnagle, A.N.; Vaisar, T.; Henderson, C.M.; Imrey, P.B.; Robinson-Cohen, C.; de Boer, I.H.; Shiu, Y.T.; Himmelfarb, J.; et al. Alteration of HDL protein composition with hemodialysis initiation. Clin. J. Am. Soc. Nephrol. CJASN 2018, 13, 1225–1233.
Florens, N.; Calzada, C.; Delolme, F.; Page, A.; Guebre Egziabher, F.; Juillard, L.; Soulage, A.C.O. Proteomic characterization of high-density lipoprotein particles from non-diabetic hemodialysis patients. Toxins 2019, 11, 671.
Manjunatha, S.; Distelmaier, K.; Dasari, S.; Carter, R.E.; Kudva, Y.C.; Nair, K.S. Functional and proteomic alterations of plasma high density lipoproteins in type 1 diabetes mellitus. Metab. Clin. Exp. 2016, 65, 1421–1431.
Shao, B.; Zelnick, L.R.; Wimberger, J.; Himmelfarb, J.; Brunzell, J.; Davidson, W.S.; Snell-Bergeon, J.K.; Bornfeldt, K.E.; de Boer, I.H.; Heinecke, J.W. Albuminuria, the high-density lipoprotein proteome, and coronary artery calcification in type 1 diabetes mellitus. Arterioscler. Thromb. Vasc. Biol. 2019, 39, 1483–1491.
Gourgari, E.; Ma, J.; Playford, M.P.; Mehta, N.N.; Goldman, R.; Remaley, A.T.; Gordon, S.M. Proteomic alterations of HDL in youth with type 1 diabetes and their associations with glycemic control: A case-control study. Cardiovasc. Diabetol. 2019, 18, 43.
Vaisar, T.; Kanter, J.E.; Wimberger, J.; Irwin, A.D.; Gauthier, J.; Wolfson, E.; Bahnam, V.; Wu, I.H.; Shah, H.; Keenan, H.A.; et al. High concentration of medium-sized HDL particles and enrichment in HDL paraoxonase 1 associate with protection from vascular complications in people with long-standing type 1 diabetes. Diabetes Care 2020, 43, 178–186.
Kheniser, K.G.; Osme, A.; Kim, C.; Ilchenko, S.; Kasumov, T.; Kashyap, S.R. Temporal dynamics of high-density lipoprotein proteome in diet-controlled subjects with type 2 diabetes. Biomolecules 2020, 10, 520.
Gourgari, E.; Nadeau, K.J.; Pyle, L.; Playford, M.P.; Ma, J.; Mehta, N.N.; Remaley, A.T.; Gordon, S.M. Effect of metformin on the high-density lipoprotein proteome in youth with type 1 diabetes. Endocrinol. Diabetes Metab. 2021, 4, e00261.
Toyoshima, M.T.K.; Santana, M.F.M.; Silva, A.R.M.; Mello, G.B.; Santos-Bezerra, D.P.; Goes, M.F.S.; Bosco, A.A.; Caramelli, B.; Ronsein, G.E.; Correa-Giannella, M.L.; et al. Proteomics of high-density lipoprotein subfractions and subclinical atherosclerosis in type 1 diabetes mellitus: A case-control study. Diabetol. Metab. Syndr. 2023, 15, 42.
Khovidhunkit, W.; Duchateau, P.N.; Medzihradszky, K.F.; Moser, A.H.; Naya-Vigne, J.; Shigenaga, J.K.; Kane, J.P.; Grunfeld, C.; Feingold, K.R. Apolipoproteins a-iv and a-v are acute-phase proteins in mouse HDL. Atherosclerosis 2004, 176, 37–44.
O’Reilly, M.; Dillon, E.; Guo, W.; Finucane, O.; McMorrow, A.; Murphy, A.; Lyons, C.; Jones, D.; Ryan, M.; Gibney, M.; et al. High-density lipoprotein proteomic composition, and not efflux capacity, reflects differential modulation of reverse cholesterol transport by saturated and monounsaturated fat diets. Circulation 2016, 133, 1838–1850.
Cao, J.; Xu, Y.; Li, F.; Shang, L.; Fan, D.; Yu, H. Protein markers of dysfunctional HDL in scavenger receptor class b type i deficient mice. J. Transl. Med. 2018, 16, 155.
Camont, L.; Lhomme, M.; Rached, F.; Le Goff, W.; Negre-Salvayre, A.; Salvayre, R.; Calzada, C.; Lagarde, M.; Chapman, M.J.; Kontush, A. Small, dense high-density lipoprotein-3 particles are enriched in negatively charged phospholipids: Relevance to cellular cholesterol efflux, antioxidative, antithrombotic, anti-inflammatory, and antiapoptotic functionalities. Arterioscler. Thromb. Vasc. Biol. 2013, 33, 2715–2723.
Ekroos, K.; Janis, M.; Tarasov, K.; Hurme, R.; Laaksonen, R. Lipidomics: A tool for studies of atherosclerosis. Curr. Atheroscler. Rep. 2010, 12, 273–281.
Borodzicz, S.; Czarzasta, K.; Kuch, M.; Cudnoch-Jedrzejewska, A. Sphingolipids in cardiovascular diseases and metabolic disorders. Lipids Health Dis. 2015, 14, 55.
Dang, V.T.; Huang, A.; Zhong, L.H.; Shi, Y.; Werstuck, G.H. Comprehensive plasma metabolomic analyses of atherosclerotic progression reveal alterations in glycerophospholipid and sphingolipid metabolism in apolipoprotein e-deficient mice. Sci. Rep. 2016, 6, 35037.
Mantovani, A.; Bonapace, S.; Lunardi, G.; Canali, G.; Dugo, C.; Vinco, G.; Calabria, S.; Barbieri, E.; Laaksonen, R.; Bonnet, F.; et al. Associations between specific plasma ceramides and severity of coronary-artery stenosis assessed by coronary angiography. Diabetes Metab. 2020, 46, 150–157.
Hilvo, M.; Meikle, P.J.; Pedersen, E.R.; Tell, G.S.; Dhar, I.; Brenner, H.; Schottker, B.; Laaperi, M.; Kauhanen, D.; Koistinen, K.M.; et al. Development and validation of a ceramide- and phospholipid-based cardiovascular risk estimation score for coronary artery disease patients. Eur. Heart J. 2020, 41, 371–380.
Poss, A.M.; Maschek, J.A.; Cox, J.E.; Hauner, B.J.; Hopkins, P.N.; Hunt, S.C.; Holland, W.L.; Summers, S.A.; Playdon, M.C. Machine learning reveals serum sphingolipids as cholesterol-independent biomarkers of coronary artery disease. J. Clin. Investig. 2020, 130, 1363–1376.
Michelucci, E.; Giorgi, N.D.; Finamore, F.; Smit, J.M.; Scholte, A.; Signore, G.; Rocchiccioli, S. Lipid biomarkers in statin users with coronary artery disease annotated by coronary computed tomography angiography. Sci. Rep. 2021, 11, 12899.
Di Giorgi, N.; Michelucci, E.; Smit, J.M.; Scholte, A.; El Mahdiui, M.; Knuuti, J.; Buechel, R.R.; Teresinska, A.; Pizzi, M.N.; Roque, A.; et al. A specific plasma lipid signature associated with high triglycerides and low HDL cholesterol identifies residual cad risk in patients with chronic coronary syndrome. Atherosclerosis 2021, 339, 1–11.
Stegemann, C.; Pechlaner, R.; Willeit, P.; Langley, S.R.; Mangino, M.; Mayr, U.; Menni, C.; Moayyeri, A.; Santer, P.; Rungger, G.; et al. Lipidomics profiling and risk of cardiovascular disease in the prospective population-based bruneck study. Circulation 2014, 129, 1821–1831.
Meikle, P.J.; Wong, G.; Tsorotes, D.; Barlow, C.K.; Weir, J.M.; Christopher, M.J.; MacIntosh, G.L.; Goudey, B.; Stern, L.; Kowalczyk, A.; et al. Plasma lipidomic analysis of stable and unstable coronary artery disease. Arterioscler. Thromb. Vasc. Biol. 2011, 31, 2723–2732.
Ellims, A.H.; Wong, G.; Weir, J.M.; Lew, P.; Meikle, P.J.; Taylor, A.J. Plasma lipidomic analysis predicts non-calcified coronary artery plaque in asymptomatic patients at intermediate risk of coronary artery disease. Eur. Heart J. Cardiovasc. Imaging 2014, 15, 908–916.
Cheng, J.M.; Suoniemi, M.; Kardys, I.; Vihervaara, T.; de Boer, S.P.; Akkerhuis, K.M.; Sysi-Aho, M.; Ekroos, K.; Garcia-Garcia, H.M.; Oemrawsingh, R.M.; et al. Plasma concentrations of molecular lipid species in relation to coronary plaque characteristics and cardiovascular outcome: Results of the atheroremo-ivus study. Atherosclerosis 2015, 243, 560–566.
Meikle, P.J.; Formosa, M.F.; Mellett, N.A.; Jayawardana, K.S.; Giles, C.; Bertovic, D.A.; Jennings, G.L.; Childs, W.; Reddy, M.; Carey, A.L.; et al. HDL phospholipids, but not cholesterol distinguish acute coronary syndrome from stable coronary artery disease. J. Am. Heart Assoc. 2019, 8, e011792.
Karjalainen, J.P.; Mononen, N.; Hutri-Kahonen, N.; Lehtimaki, M.; Hilvo, M.; Kauhanen, D.; Juonala, M.; Viikari, J.; Kahonen, M.; Raitakari, O.; et al. New evidence from plasma ceramides links apoe polymorphism to greater risk of coronary artery disease in finnish adults. J. Lipid Res. 2019, 60, 1622–1629.
Ding, M.; Rexrode, K.M. A review of lipidomics of cardiovascular disease highlights the importance of isolating lipoproteins. Metabolites 2020, 10, 163.
Stary, H.C. Natural history and histological classification of atherosclerotic lesions: An update. Arterioscler. Thromb. Vasc. Biol. 2000, 20, 1177–1178.
Virmani, R.; Kolodgie, F.D.; Burke, A.P.; Farb, A.; Schwartz, S.M. Lessons from sudden coronary death: A comprehensive morphological classification scheme for atherosclerotic lesions. Arterioscler. Thromb. Vasc. Biol. 2000, 20, 1262–1275.