Bulk and single-cell characterisation of the immune heterogeneity of atherosclerosis identifies novel targets for immunotherapy.

BACKGROUND: Immune cells that infiltrate lesions are important for atherosclerosis progression and immunotherapies. This study was aimed at gaining important new insights into the heterogeneity of these cells by integrating the sequencing results of multiple samples and using an enhanced single-cell sequencing workflow to overcome the limitations of a single study. RESULTS: Integrative analyses identified 28 distinct subpopulations based on gene expression profiles. Further analysis demonstrated that these cells manifested high heterogeneity at the levels of tissue preferences, genetic perturbations, functional variations, immune dynamics, transcriptional regulators, metabolic changes, and communication patterns. Of the T cells, interferon-induced CD8+ T cells were involved in the progression of atherosclerosis. In contrast, proinflammatory CD4+ CD28null T cells predicted a poor outcome in atherosclerosis. Notably, we identified two subpopulations of foamy macrophages that exhibit contrasting phenotypes. Among them, TREM2- SPP1+ foamy macrophages were preferentially distributed in the hypoxic core of plaques. These glycolytic metabolism-enriched cells, with impaired cholesterol metabolism and robust pro-angiogenic capacity, were phenotypically regulated by CSF1 secreted by co-localised mast cells. Moreover, combined with deconvolution of the bulk datasets, we revealed that these dysfunctional cells had a higher proportion of ruptured and haemorrhagic lesions and were significantly associated with poor atherosclerosis prognoses. CONCLUSIONS: We systematically explored atherosclerotic immune heterogeneity and identified cell populations underlying atherosclerosis progression and poor prognosis, which may be valuable for developing new and precise immunotherapies.

Coronary artery calcification and cardiovascular outcome as assessed by intravascular OCT and artificial intelligence.

Coronary artery calcification (CAC) is a marker of atherosclerosis and is thought to be associated with worse clinical outcomes. However, evidence from large-scale high-resolution imaging data is lacking. We proposed a novel deep learning method that can automatically identify and quantify CAC in massive intravascular OCT data trained using efficiently generated sparse labels. 1,106,291 OCT images from 1,048 patients were collected and utilized to train and evaluate the method. The Dice similarity coefficient for CAC segmentation and the accuracy for CAC classification are 0.693 and 0.932, respectively, close to human-level performance. Applying the method to 1259 ST-segment elevated myocardial infarction patients imaged with OCT, we found that patients with a greater extent and more severe calcification in the culprit vessels were significantly more likely to have major adverse cardiovascular and cerebrovascular events (MACCE) (p < 0.05), while the CAC in non-culprit vessels did not differ significantly between MACCE and non-MACCE groups.

Tyrosine kinase inhibitors and atherosclerosis: A close but complicated relationship.

Targeted cancer therapies have revolutionized the treatment of the disease in the past decade. The tyrosine kinase inhibitor (TKI) class of drugs is a widely used option for treating various cancers. Despite numerous advances, clinical and experimental studies have demonstrated the atherosclerosis-inducing properties of these drugs that can cause adverse cardiovascular events. TKIs also have an atherosclerosis-preventing role in patients with cancer through different mechanisms under various conditions, suggesting that specific drugs play different roles in atherosclerosis regulation. Given these contradictory properties, this review summarizes the outcomes of previously performed clinical and basic experiments and shows how the targeted effects of novel TKIs affect atherosclerosis. Future collaborative efforts are warranted to enhance our understanding of the association between TKIs and atherosclerosis.

AgingReG: a curated database of aging regulatory relationships in humans.

Aging and cellular senescence are characterized by a progressive loss of physiological integrity, which could be triggered by aging factors such as physiological, pathological and external factors. Numerous studies have shown that gene regulatory events play crucial roles in aging, increasing the need for a comprehensive repository of regulatory relationships during aging. Here, we established a manually curated database of aging factors (AgingReG, https://bio.liclab.net/Aging-ReG/), focusing on the regulatory relationships during aging with experimental evidence in humans. By curating thousands of published literature, 2157 aging factor entries (1345 aging gene entries, 804 external factor entries and eight aging-related pathway entries) and related regulatory information were manually curated. The regulatory relationships were classified into four types according to their functions: (i) upregulation, which indicates that aging factors upregulate the expression of target genes during aging; (ii) downregulation, which indicates that aging factors downregulate the expression of target genes during aging; (iii) activation, which indicates that aging factors influence the activity of target genes during aging and (iv) inhibition, which indicates that aging factors inhibit the activation of target molecule activity, leading to declined or lost target activity. AgingReG involves 651 upregulating pairs, 632 downregulating pairs, 330 activation-regulating pairs and 34 inhibition-regulating pairs, covering 195 disease types and more than 800 kinds of cells and tissues from 1784 published literature studies. AgingReG provides a user-friendly interface to query, browse and visualize detailed information about the regulatory relationships during aging. We believe that AgingReG will serve as a valuable resource database in the field of aging research. Database URL: https://bio.liclab.net/Aging-ReG/.

Advanced imaging modalities provide new insights into coronary artery calcification.

Coronary calcification plays a major role as a key surrogate measure of plaque burden, providing powerful risk stratification and influencing preventive therapy. Depending on its location and density, microcalcifications may directly result in plaque rupture and adverse clinical events. Although macroscopic calcifications are frequently linked to advanced and stable plaques, the fact that a small number of thrombotic events are caused by plaques that possess a substantial amount of calcification should not be overlooked. Early and accurate assessment of calcium content in atherosclerotic plaques potentially enhances the identification of high-risk patients requiring preventive treatments. Non-invasive imaging allows for the visualization, detection, and quantification of calcific lesions, whereas intravascular imaging has the unique advantage of providing real-time and accurate information during calcium modification interventions. Simultaneously, emerging molecular imaging modalities aid in the investigation of calcification activity. This review summarizes advanced techniques for coronary artery calcification imaging, including their merits and limitations, in addition to their potential applications in both experimental and clinical settings.

Differences in Culprit Lesions Between Premenopausal and Postmenopausal Women With Acute Coronary Syndrome: An Optical Coherence Tomography Study.

BACKGROUND: Differences in culprit lesion characteristics remain unclear between premenopausal and postmenopausal women with acute coronary syndrome (ACS). Optical coherence tomography (OCT) enables high-resolution in vivo identification of plaques. We investigated potential differences in culprit lesions between premenopausal and postmenopausal women with ACS by means of OCT. METHODS: We included 191 ACS patients who had undergone preinterventional OCT and stratified them into 2 groups according to their menopausal status: premenopausal (n = 97) and postmenopausal (n = 94). The characteristics of culprit lesions were compared between the 2 groups. RESULTS: Multivessel lesions were more commonly noted on angiography in the postmenopausal group than in the premenopausal group (40.21% vs 72.34%; P < 0.0001). On OCT, the most common type of culprit plaque was the fibrous plaque in the premenopausal group and the lipid plaque in the postmenopausal group. Compared with the premenopausal group, plaque rupture was more common in the postmenopausal group (39.18% vs 55.32%; P = 0.0254); culprit lesions had more vulnerable features, including macrophage accumulation (58.76% vs 87.23%; P < 0.0001), microchannel (38.14% vs 84.04%; P < 0.0001), cholesterol crystals (30.93% vs 62.77%; P < 0.0001), lipid-rich plaque (32.99% vs 58.51%; P < 0.0001), thin-cap fibroatheroma (3.09% vs 21.28%; P = 0.0001), and calcium (20.62% vs 44.68%; P = 0.0004); maximum lipid arc was larger (121.06 ± 110.99° vs 220.12 ± 115.47°, P < 0.0001); and lipid length was longer (5.78 ± 5.29 mm vs 12.90 ± 8.97 mm; P < 0.0001). CONCLUSIONS: Compared with premenopausal women with ACS, postmenopausal women with ACS had more vulnerable culprit lesions. These finding suggest potential optimised lipid-lowering therapy for postmenopausal women with ACS.