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Department of Stroke Center, Central Hospital Affiliated to Shandong First Medical University, ChinaDepartment of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
BaoFeng Key Laboratory of Genetics and Metabolism, Beijing, ChinaZhongyuanborui Key Laborotory of Genetics and Metabolism, Guangdong-Macao In-depth Cooperation Zone in Hengqin, China
Corresponding author. Department of Neurology, Xuanwu Hospital of Capital Medical University, National Clinical Research Center for Geriatric Diseases, 45 Changchun Street, Beijing, China.
Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, ChinaNational Clinical Research Center for Geriatric Diseases, Beijing, China
Corresponding author. Department of Neurosurgery and Department of Interventional Neuroradiology, Xuanwu Hospital of Capital Medical University, 45 Changchun Street, Beijing, China.
Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, 100053, ChinaChina International Neuroscience Institute (China-INI), Beijing, 100053, ChinaDepartment of Interventional Neuroradiology, Xuanwu Hospital, Capital Medical University, Beijing, China
Specific lipids located in lipid-rich regions and collagen-rich regions were identified.
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The spatial dynamic lipid metabolism footprint of atherosclerosis was delineated.
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Different metabolic pathways between lipid-rich regions and collagen-rich regions with atherosclerosis progression were found.
Abstract
Background and aims
Carotid atherosclerosis is an important cause of ischemic stroke. Lipids play a key role in the progression of atherosclerosis. To date, the spatial lipid profile of carotid atherosclerotic plaques related to histology has not been systematically investigated.
Methods
Carotid atherosclerosis samples from 12 patients were obtained and classified into four classical pathological stages (preatheroma, atheroma, fibroatheroma and complicated lesion) by histological staining. Desorption electrospray ionization-mass spectrometry imaging (DESI-MSI) was used to investigate the lipid profile of carotid atherosclerosis, and correlated it with histological information. Bioinformatics technology was used to process MSI data among different pathological stages of atherosclerosis lesions.
Results
A total of 55 lipids (26 throughout cross-section regions [TCSRs], 13 in lipid-rich regions [LRRs], and 16 in collagen-rich regions [CRRs]) were initially identified in carotid plaque from one patient. Subsequently, 32 of 55 lipids (12 in TCSRs, eight in LRRs, and 12 in CRRs) were further screened in 11 patients. Pathway enrichment analysis showed that multiple metabolic pathways, such as fat digestion and absorption, cholesterol metabolism, lipid and atherosclerosis, were enriched in TCSRs; sphingolipid signaling pathway, necroptosis pathway were enriched in LRRs; and glycerophospholipid metabolism, ether lipid metabolism pathway were mainly enriched in CRRs.
Conclusions
This study comprehensively showed the spatial lipid metabolism footprint in human carotid atherosclerotic plaques. The lipid profiles and related metabolism pathways in three regions of plaque with disease progression were different markedly, suggesting that the different metabolic mechanisms in these regions of carotid plaque may be critical in atherosclerosis progression.
], which is a progressive process. Lipids play a key role in the progression of atherosclerosis. They accumulate at sites of impaired endothelium in arterial walls, and subsequently activate inflammatory reactions and macrophages transformed from recruited monocytes in the intima and subintima. Foam cells are then formed through increased uptake of oxidized low-density lipoprotein and cause the initiation of atherosclerosis (fatty streaks) [
A definition of initial, fatty streak, and intermediate lesions of atherosclerosis. A report from the Committee on Vascular Lesions of the Council on Arteriosclerosis, American Heart Association.
]. With continued accumulation of lipids and inflammatory cells, fatty streaks grow into atherosclerotic plaques characterized by lipid core surrounded by fibrous cap [
]. Atherosclerosis plaque continuously progresses into heterogeneous and complex structures (calcification, plaque fissures, hematoma and thrombus), and stroke events may eventually occur [
A definition of advanced types of atherosclerotic lesions and a histological classification of atherosclerosis. A report from the Committee on Vascular Lesions of the Council on Arteriosclerosis, American Heart Association.
]. Uncontrolled uptake of LDL and impaired cholesterol efflux lead to the death of foam cells and accumulation of extracellular lipid droplets, causing the formation of lipid-rich regions (LRRs) [
]. Vascular smooth muscle cells (VSMCs) in the media layer can migrate to the sub-endothelial space and produce extracellular matrix proteins such as collagen and elastin forming collagen-rich regions (CRRs) [
], the spatial distribution information was unavailable due to limited technology. Data on lipid profiles and spatial lipid patterns contextualized in terms of LRRs and CRRs, and their association with plaque progression remains unknown.
Spatial metabolomics is an emerging omics that can map the spatial distribution of small molecules, such as lipids, and correlate with pathological findings in situ without chemical labels or antibodies. Different spatial metabolomics technologies exist, such as time-of-flight secondary ion mass spectrometry (TOF-SIMS) and matrix-assisted laser desorption/ionization MSI (MALDI-MSI). In recent years, significant progress in this field has been achieved by desorption electrospray ionization MSI (DESI-MSI), which has the advantages of not destroying tissue sections, no matrix deposition, and to be performed under ambient conditions [
Investigation of lipid metabolism in dynamic progression of coronary artery atherosclerosis of humans by time-of-flight secondary ion mass spectrometry.
] along various dimensions. However, only one study has reported on the spatial distribution of lipid in coronary artery atherosclerosis in a single patient by TOF-SIMS [
Investigation of lipid metabolism in dynamic progression of coronary artery atherosclerosis of humans by time-of-flight secondary ion mass spectrometry.
In this study, we employed DESI-MSI to investigate the spatial lipid profile distribution in human carotid plaques at different stages of atherosclerosis, and correlate MSI data with histological information, aiming to delineate metabolic profiles and provide deep insights into spatial metabolic mechanism of human carotid atherosclerosis.
2. Materials and methods
2.1 Chemicals and reagents
Acetonitrile, methanol, isopropanol, ammonium formate and formic acid were of LC-MS grade and purchased from Fisher Scientific (Waltham, MA, USA). Oil Red O solution and Masson's trichrome reagents were purchased from ZSGB-BIO (Beijing, China).
2.2 Patients and study design
This study was approved by the institutional review boards of our hospital (KS2021124-1). The human research in this study conformed to the principles of the Declaration of Helsinki (revision 6, 2008) and was conducted in accordance with the institutional guidelines. All patients provided informed consent to use their samples in this study.
In total, 12 patients with symptomatic carotid stenosis of 50–99% or asymptomatic carotid stenosis of 70–99%, who underwent carotid endarterectomy between February 1, 2021, and June 30, 2021, in our hospital, were included in the study. Carotid atherosclerosis plaque samples were collected. Baseline characteristics (including age, sex, smoking, drinking, diabetes, hypertension, hyperlipidemia, coronary heart disease, peripheral vascular diseases, atrial fibrillation, previous cerebral infarction, symptoms of ischemic stroke and degree of stenosis) of the 12 patients are presented in Supplementary Table 1.
2.3 Sample preparation
Human carotid plaque specimens removed by carotid endarterectomy were immediately washed in ice-cold saline, frozen in liquid nitrogen for 1 min, and stored at −80 °C. Samples were cut into fragments of approximately 5 mm in size and embedded in 2% sodium carboxymethyl cellulose. Frozen sections (10 μm-thick) were cut using a cryotome, mounted on glass slides, and stored at −80 °C for DESI-MSI and histochemical staining.
2.4 DESI-MSI
All MSI experiments were performed using a SYNAPT G2-Si HDMS Q-TOF instrument (Waters, Milford, MA, USA). The glass slides containing 10 μm sample were subjected to DESI-MSI in positive and negative ion modes over mass range m/z 50 to 1200. We used a spray solvent, methanol:water (95:5, v:v), containing 400 pg/μL leucine enkephalin, at a flow rate of 2 μL/min assisted by a nebulizing gas (N2) at a pressure of 0.45 Mpa. The sprayer tip-to-surface distance was 1 mm, the sprayer-to-inlet distance was 5 mm, and the spray incident angle was 70°. The source parameters were: 4.5 kV capillary voltage and 150 °C source temperature. To acquire DESI-MS images, tissues were raster-scanned at a velocity of 200 μm/s, with a spatial resolution of 80 μm.
A high definition imaging platform version 1.5 (Waters) was used to process the mass spectral data and to generate two-dimensional spatially resolved ion images. The top 1000 intensity peaks were extracted. Spectra were recalibrated for high mass accuracy using the accurate mass of leucine enkephalin (positive, m/z 556.2771; negative, m/z 554.2615) presented in the solvent spray. The mass spectra were normalized to the total ion currents. An m/z tolerance of ±0.02 was assigned to account for slight variations in the measured m/z values. Each mono-isotopic peak was mass lock corrected to yield accurate mass measurements on MassLynx. Isotope peaks were excluded. Regions of interest (ROIs) (5 pixel2) were randomly chosen in areas of four pathological stages.
2.5 Ion identification
To further identify lipids and metabolites, tissue lysates were prepared from the samples remaining after sectioning, and subjected to ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC/Q-TOF-MS) (Xevo G2-XS QTof, Waters). A simple methanol extraction method [
Objective set of criteria for optimization of sample preparation procedures for ultra-high throughput untargeted blood plasma lipid profiling by ultra performance liquid chromatography-mass spectrometry.
] was used for lipid extraction. The protocols for sample preparation, chromatographic gradient, and MS parameters are provided in Supplementary Materials.
Ion identification was assigned to accurate DESI-MSI m/z in comparison to UPLC/Q-TOF-MS-based fragmentation patterns. Accurate m/z values were searched against the Human Metabolome Database and Lipid Maps Database with a tolerance of 20 ppm and considering H+, H−, Na+, K+, Cl+, H–H2O+, and NH4+ as adducts or referring to relevant publications [
] for compound identification. Indistinguishable isomers of lipid species of the same mass were excluded.
2.6 Immunostaining and immunohistochemistry
Oil Red O and Masson's trichrome staining was performed according to the manufacturer's protocol for staining neutral lipids and collagen fibers. Oil Red O staining was used to classify the atherosclerotic lesions into four pathological stages (preatheroma, atheroma, fibroatheroma and complicated lesion) according to the American Heart Association classification of atherosclerosis [
A definition of initial, fatty streak, and intermediate lesions of atherosclerosis. A report from the Committee on Vascular Lesions of the Council on Arteriosclerosis, American Heart Association.
]. The following primary antibodies for immunohistochemistry were used: mouse anti-human CD68 (1:300) to visualize macrophages, rat anti-human glycophorin A (1:500) to detect intraplaque haemorrhage, mouse anti-human α-smooth muscle actin (α-SMA) (1:300) to visualize vascular smooth muscle cells (VSMCs). The protocol of immunohistochemistry is shown in the Supplementary Materials.
2.7 Statistical analysis
To have a broad perspective of the datasets from the 14 sample sections of first plaque, t-stochastic neighbor embedding (t-SNE) was used. DESI-MSI data were processed and subjected to multivariate statistical data analysis. An orthogonal partial least squares discriminant analysis (OPLS-DA) was applied to identify potential discrimination among the four pathological stages. The quality of the model was monitored via a permutation test (seven times), and the parameters R2 and Q2 were calculated to test the robustness and predictability of the model. Differential lipid profiles were selected based on variable importance in the projection (VIP) values (VIP >1) and, p-value (p < 0.05). Metabolic pathways involving differential lipid profiles were identified using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. All statistical analyses and graph design were performed using R (version 3.6.3, Foundation for Statistical Computing, Vienna, Austria),Python (version 3.6.3), Prism 8.0.2 (GraphPad Software, San Diego, CA, USA) and Adobe Illustrator CC 2019 (Adobe Systems Incorporated, San Jose, CA, USA). Statistical significance was defined at p < 0.05.
3. Results
3.1 Preliminary assessment of lipid abundance from one patient by DESI-MSI
To investigate the spatial lipid profiles correlated with histology of carotid atherosclerosis, an exploratory experiment was performed using DESI-MSI on 14 frozen, consecutive 10 μm-thick sections every 100 μm of carotid plaque from one patient. The ion at m/z 671.576 (assigned as cholesterol ester [CE] 18:2) was distributed throughout cross-section regions (TCSRs) in positive ion mode, and the ion intensity was elevated in 14 consecutive sections (from the edge to the core of plaque) (Fig. 1A). The t-SNE projection was used to visualize the distribution differences of total lipid profiles among the 14 sections. Clusters of lipid signatures of the 14 consecutive sections were separated from each other, and with atherosclerosis progression the clusters were much closer in positive (Fig. 1B) and negative ion modes (Fig. 1C).
Fig. 1DESI-MSI of 14 frozen 10 μm-thick consecutive sections of the carotid plaque from one patient, and ion intensity and regional distribution corresponding to the four pathological stages.
Distribution and ion intensity of m/z 671.576, assigned as cholesterol ester (CE) 18:2 among 14 frozen consecutive sections from one carotid plaque (A). The t-SNE projection in (B) positive and (C) negative ion modes. Sections were stained with Oil red O after DESI-MSI and the adjacent sections stained with Masson's trichrome (D). Distribution of the selected ion of m/z 671.576 (CE 18:2), m/z 703.577 (assigned as sphingomyelin [SM] 34:1), and m/z 772.528 (assigned as phosphatidylcholine [PC] 32:0), and the overlay images of ions m/z 703.577 and 772.528 (D). DESI-MSI: desorption electrospray ionization mass spectrometry imaging; t-SNE: t-stochastic neighbor embedding. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
3.2 Distinct lipids are spatially distributed in different regions of plaque
After DESI scanning, the samples were stained with Oil red O reagent and the adjacent slices were stained with Masson's trichrome reagent. We classified the atherosclerotic lesions into the four pathological stages (preatheroma, atheroma, fibroatheroma and complicated lesion) (Fig. 1D). The abundance of different lipids was observed to be different in the four pathological stages (Fig. 1D). The ion m/z 671.576 (CE 18:2) was observed predominantly in the TCSRs, where the lipid-rich regions (LRRs) and collagen-rich regions (CRRs) were located with the ion m/z 703.577 (assigned as sphingomyelin [SM] 34:1) and m/z 772.528 (assigned as phosphatidylcholine [PC] 32:0) respectively. Overlay images of ions m/z 703.577 and 772.528 exhibited the same area of TCSRs. The ion intensities of these three lipids were increased with pathological progression. VSMCs (Supplementary Fig. 1C) were mainly in the smooth muscle layer in the preatheroma, atheroma, and fibroatheroma stages and migrated into the region of the fibrous cap in the complicated lesion stage. The macrophage (Supplementary Fig. 1D) and intraplaque haemorrhage (Supplementary Fig. 1E) were restricted under the fibrous cap and overlapped. All these components were in the CRRs. No lipids were found to be correlated with these components.
3.3 Screening spatial lipid profiles related to histology by OPLS-DA
A total of 6149 and 7275 metabolites were obtained in positive and negative modes, respectively. To further study the spatial changes in lipid profiles with atherosclerosis progression, the precise regions of the four pathological stages, especially regions of LRRs and CRRs in stages of fibroatheroma and complicated lesion, were delineated (Fig. 2A). Ten ROIs were randomly chosen in preatheroma and atheroma pathological stages, and 10 ROIs were randomly chosen in LRRs and CRRs of fibroatheroma and complicated lesion. Data from these ROIs were exported for multivariate analysis. The OPLS-DA model was introduced to screen lipid profiles to identify the four pathological stages in regions of LRRs and CRRs. The permutation test showed that the slopes of R2 were all greater than 0 and those of Q2 were all less than 0 in both positive and negative ion modes (Supplementary Figs. 2A–D), indicating that the OPLS-DA models were not overfitting.
Fig. 2Screening of lipid profile related to histology from the first patient.
Delineation areas of four pathological structures stained with Oil red O from the first patient (A). The black dashed lines represent regions of preatheroma and atheroma, respectively. The blue and green dashed lines represent regions of LRRs and CRRs in fibroathroma and complicated lesion, respectively. OPLS-DA modeling was conducted for positive and negative ions in LRRs and CRRs, respectively. OPLS-DA score scatter plot of LRRs in (B) positive and (C) negative modes and of CRRs in (D) positive and (E) negative modes. The blue, red, green and black dots represent data from preatheroma, atheroma, fibroatheroma and complicated lesions, respectively. Venn diagram shows the identified lipids in LRRs, CRRs and TCSRs (F). Heatmaps show ions intensity changes of screened lipid profiles among four pathological stages in different regions: TCSRs (G), LRRs (H) and CRRs (I). CE: cholesterolester; Cer: ceramide; CRRs: collagen-rich regions; DG: diacylglycerol; GPC: glycerylphosphorylcholine; LRRs: lipid-rich regions; LysoPC: lysophosphatidylcholine; LysoPI: Lysophosphatidylinositol; OPLS-DA, orthogonal partial least squares discriminant analysis; PC: phosphatidylcholine; PE: phosphatidylethanolamine; SM: sphingomyelin; TCSRs: throughout cross-section regions; TG: triacylglycerol. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
The lipid profiles of the four stages in both positive and negative ion modes in LRRs and CRRs differed significantly in the OPLS-DA models (Fig. 2B–E). Based on the screening conditions (VIP >1, p < 0.05), ion identification and images manually viewed, 55 lipid profiles were screened (Supplementary Table 2). The Venn diagram showed that 13 lipids were distributed exclusively in LRRs, 16 were exclusively in CRRs, and 26 lipids were distributed in the intersection of LRRs and CRRs (representing the TCSRs) (Fig. 2F). Heatmaps showed that these lipid profiles varied significantly among the four stages in TCSRs (Fig. 2G), LRRs (Fig. 2H) and CRRs (Fig. 2I). The spatial distribution of 10 lipids correlated with histology selected randomly (three in TCSRs, three in LRRs and four in CRRs) in four pathological stages, as shown in Fig. 3.
Fig. 3The spatial distribution of 10 lipids selected randomly (three in TCSRs, three in LRRs and four in CRRs) in four pathological stages.
3.4 Confirmation of the spatial lipid profile by OPLS-DA
To eliminate the effect of heterogeneity, 10 μm-thick frozen carotid plaque sections from 11 additional patients were stained with Oil Red O to identify the four pathological stages. Sections including preatheroma (n = 7), atheroma (n = 8), fibroatheroma (n = 5) and complicated lesion (n = 8) were identified, and adjacent slides were scanned by DESI-MSI. The selection of ROIs was the same as the first plaque. Data from these ROIs were also exported for multivariate analysis. All OPLS-DA models did not overfit (Supplementary Figs. 3A–D). The lipid profiles of four groups in both positive and negative ion modes in LRRs and CRRs also differed significantly in the OPLS-DA models (Fig. 4A–D). Using the screening conditions described above, 32 lipid profiles were screened (Supplementary Table 3). The Venn diagram showed that eight lipids were exclusively distributed in LRRs, 12 in CRRs, and 12 were distributed at the intersection of LRRs and CRRs (representing TCSRs) (Fig. 4E). The main lipids in TCSRs were CEs, triacylglycerols (TGs) and SMs; in LRRs were SMs, Cer 34:1, PE 34:2, glycerylphosphorylcholine (GPC), 7β-hydroxycholesterol and α-tocopherolquinone; and in CRRs were PCs, PEs, and LysoPC 20:3. Heatmaps showed that these lipid profiles also varied significantly among the four groups in TCSRs (Fig. 4F), LRRs (Fig. 4G) and CRRs (Fig. 4H). The spatial distribution of 10 lipids correlated with histology selected randomly (three in TCSRs, three in LRRs and four in CRRs) in four pathological stages from 11 patients, as shown in Supplementary Fig. 4.
Fig. 4Screening of lipid profile related to histology from additional 11 patients.
OPLS-DA modeling was conducted for positive and negative ions in LRRs and CRRs, respectively. The OPLS-DA score scatter plot of LRRs in (A) positive and (B) negative modes, and of CRRs in (C) positive and (D) negative modes. The blue, red, green and black dots represent data from preatheroma, atheroma, fibroatheroma and complicated lesions, respectively. Venn diagram showed the identified lipids in LRRs, CRRs and TCSRs (E). Heatmaps showed ions intensity changes of screened lipid profiles among four pathological stages in different regions: TCSRs (F), LRRs (G) and CRRs (H). CE: cholesterolester; Cer: ceramide; CRRs: collagen-rich regions; DG: diacylglycerol; GPC: glycerylphosphorylcholine; LRRs: lipid-rich regions; LysoPC: lysophosphatidylcholine; OPLS-DA, orthogonal partial least squares discriminant analysis; PC: phosphatidylcholine; PE: phosphatidylethanolamine; SM: sphingomyelin; TCSRs: throughout cross-section regions; TG: triacylglycerol. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
3.5 Lipid-related pathways predicted to distinguish pathological stages in different regions
Next, KEGG pathway enrichment analysis was conducted to predict metabolic pathways involved in the atherosclerotic process based on the 32 identified lipids. Among 88 pathways detected, the top 10 (sphingolipid signaling pathway, fat digestion and absorption, glycerophospholipid metabolism, adipocytokine signaling pathway, Necroptosis, etc.) were determined to be the most overrepresented (Fig. 5A and Supplementary Table 4). Moreover, the top 10 of 86 pathways (fat digestion and absorption, cholesterol metabolism, regulation of lipolysis in adipocytes, lipid and atherosclerosis, etc.) enriched by 12 lipids were distributed in TCSRs (Fig. 5B and Supplementary Table 5), the top 10 of 11 pathways (neurotrophin signaling pathway, sphingolipid signaling pathway, necroptosis, insulin resistance, etc.) enriched by eight lipids were in LRRs (Fig. 5C, Supplementary Table 6), and three pathways (glycerophospholipid metabolism, ether lipid metabolism and choline metabolism in cancer) enriched by 12 lipids were distributed in CRRs (Fig. 5D, Supplementary Table 7). These data demonstrate that metabolic pathways among three regions, especially in LRRs and CRRs, are largely different as atherosclerosis progresses.
Fig. 5KEGG pathway enrichment analysis of identified lipids from 11 additional patients.
The top 10 pathways among 88 pathways enriched by total 32 lipids (A), the top 10 of 86 pathways enriched by 12 lipids distributed in TCSRs (B), the top 10 of 11 pathways enriched by eight lipids distributed in LRRs (C) and the three pathways enriched by 12 lipids distributed in CRRs (D). TCSRs: throughout cross-section regions; LRRs: lipid-rich regions; CRRs: collagen-rich regions.
To date, the spatial lipid profile of carotid atherosclerotic plaques related to histology has not been systematically investigated. Herein, the cross-sectional lipid profiles of human carotid atherosclerotic plaques correlated with histology were investigated by DESI-MSI. Overall, 55 lipids (26 in TCSRs, 13 in LRRs, and 16 in CRRs) were found to be differently present in the four pathological stages of atherosclerotic lesions based on samples from a single patient. Next, plaque samples from 11 additional patients were processed in the same way to exclude heterogeneity, and 32 of 55 lipids (12 in TCSRs, eight in LRRs, and 12 in CRRs) were identified. Pathway enrichment analysis further showed metabolic pathways were different in three regions with atherosclerosis progression.
The TCSRs of atherosclerosis plaques were found to be enriched in CEs, TGs and SMs. CEs are the main components of atherosclerotic plaques [
], we confirmed this result and observed this lipid distributed in TCSRs. The mechanisms of CE in atherosclerosis include stimulating generation of inflammasome, promoting inflammation and accelerating atherogenoesis, destabilizing atherosclerotic palques [
]. TG 52:1 and TG 52:4 distributed in TCSRs were found increased with atherosclerosis progression in this study. Inflammation triggered by high levels of low-density lipoprotein enriched in TGs is closely associated with atherosclerosis progression [
The LRRs of atherosclerosis plaques were found to be enriched in SMs, Cer 34:1, PE 34:2, GPC, 7β-hydroxycholesterol and α-tocopherolquinone. GPC is the catabolite of PCs and PEs. 7β-hydroxycholesterol (a form of oxidized cholesterol) promotes atherogenesis by triggering endoplasmic reticulum stress, inflammation and cell death [
Susceptibility of low-density lipoprotein particles to aggregate depends on particle lipidome, is modifiable, and associates with future cardiovascular deaths.
]. The pathways of these lipids and metabolites distributed in LRRs were found to be mainly enriched in necroptosis, sphingolipid signaling pathway and glycerophospholipid metabolism, which indicates that metabolites associated with damaged organelles and cell death are directly related to pathological progression.
The vast majority of lipids located in CRRs associated with pathological progression were PCs, along with other lipids such as PEs, lysoPC 20:3. All PEs, lysoPC 20:3 are related to PCs and are involved in glycerophospholipid metabolism, as shown by KEGG pathway analysis. PCs constitutes the backbone of cellular membrane. Zaima et al. [
] reported that PCs were mainly distributed in regions of vascular smooth muscle cells (VSMCs) of human plaques and mouse model, which were located in collagen regions. Moreover, PCs metabolism-mediated macrophage receptors upregulation and enhanced formation of foam cells from macrophages were described in atherosclerosis [
]. The PCs distributed in CRRs that were associated with plaque progression suggest an increase in recruited monocytes that differentiate into macrophages, as well as VSMCs proliferation, migration and phenotype transformation.
In vivo isotopically labeled atherosclerotic aorta plaques in ApoE KO mice and molecular profiling by matrix-assisted laser desorption/ionization mass spectrometric imaging.
] have focused on exploring lipid profiles and plaque stability in specific sites, such as the necrotic core, smooth muscle cells, macrophages and calcium-rich regions, while other studies [
] have investigated the lipid profiles and vascular structure in the intima and media regions in human samples or animal models. However, the data obtained are inconsistent, complex, and scattered. Based on the dynamic latitudinal perspective of the lipid core covered with fibrous cap and surrounded collagen tissue, this study comprehensively demonstrated the lipid metabolism footprint in atherosclerosis. The CRRs and LRRs harbor different lipids with disease progression, suggesting that these lipids (SM, Cer, PC and LysoPC) may be potential targets for new lipid-lowering medications besides CE and TG.
The study had some limitations. The transitions from the relatively normal edge to the core of plaques may not completely reflect the disease progression of plaques, as the edge of plaques may be influenced by adjacent complicated lesions. Obtaining samples of pathological type not influenced by other pathological types is ideal but not practical. We did not analyze plaques from the perspective of plaque stability because some plaques may contain a large amount of calcium, and the plaque shape can be changed, leading to manual damage to the integrity of the fibrous cap during frozen sectioning. In addition, the sample size in this study for spatial metabolomics was relatively small. A larger sample size should be further analyzed to verify our observations.
In this study, we comprehensively demonstrated the spatial lipid metabolism footprint of human carotid atherosclerosis plaques. Special lipids located in three regions and related metabolic pathways were different as atherosclerosis progresses, suggesting that the different metabolic mechanisms in these regions of carotid plaque may be critical in atherosclerosis progression.
Financial support
This work was supported by the National Natural Science Foundation (82171303, 82171412).
A definition of initial, fatty streak, and intermediate lesions of atherosclerosis. A report from the Committee on Vascular Lesions of the Council on Arteriosclerosis, American Heart Association.
A definition of advanced types of atherosclerotic lesions and a histological classification of atherosclerosis. A report from the Committee on Vascular Lesions of the Council on Arteriosclerosis, American Heart Association.
Investigation of lipid metabolism in dynamic progression of coronary artery atherosclerosis of humans by time-of-flight secondary ion mass spectrometry.
Objective set of criteria for optimization of sample preparation procedures for ultra-high throughput untargeted blood plasma lipid profiling by ultra performance liquid chromatography-mass spectrometry.
Susceptibility of low-density lipoprotein particles to aggregate depends on particle lipidome, is modifiable, and associates with future cardiovascular deaths.
In vivo isotopically labeled atherosclerotic aorta plaques in ApoE KO mice and molecular profiling by matrix-assisted laser desorption/ionization mass spectrometric imaging.
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