Martin Dichgans

Atherosclerotic plaque vulnerability drives ischemic cardiovascular events, yet the cellular and molecular signatures distinguishing symptomatic from asymptomatic human plaques remain poorly defined. Here, we compared 53 symptomatic and asymptomatic human carotid plaques using single-nucleus (snRNA-seq; 17 samples, 19,100 nuclei; AtherOMICS biobank) and single-cell RNA sequencing (scRNA-seq; 36 samples, 68,983 cells; four public datasets), analyzed independently and combined by meta-analysis. Across sequencing approaches, symptomatic plaques showed cell-state shifts toward later or terminal states in osteochondrogenic smooth muscle cells (SMCs) and CD4⁺ T cells, as well as transcriptional changes toward inflammatory and epithelial-to-mesenchymal transition (EMT) in endothelial cells (ECs), T cells, and fibroblasts. Nuclear profiling uncovered a depletion of fibroblasts in symptomatic plaques, marked by downregulation of RGS5. Integrating these transcriptomic signatures with genome-wide association data for coronary, cerebrovascular, and peripheral atherosclerotic disease, we found that genetic risk was enriched primarily in vascular wall cells (SMCs, fibroblasts, ECs), rather than immune cell types. The analyses further nominated higher TWIST1 expression in ECs (colocalized with risk across four atherosclerotic phenotypes), lower GUCY1A1 expression in fibroblasts and macrophages, and higher MRAS expression in T cells as candidate driver mechanisms linking genetic risk to symptomatic plaque transition. These findings provide novel insights into cellular and molecular phenotypes associated with plaque vulnerability and identify potential driver mechanisms of symptomatic plaque transformation that could inform therapeutic development.

Omics technologies enable deep profiling of human atherosclerosis but have mostly been applied in small studies lacking integration with other data modalities. AtherOMICS is a biobanking project linking multiomic atherosclerotic plaque phenotyping with blood biobanking, in vivo imaging, and clinical data. Here, we present the study protocol and show pilot results that demonstrate technical feasibility. Since August 2022, 246 patients scheduled to undergo carotid or femoral endarterectomy at Ludwig-Maximilians-Universität Klinikum (Munich, Germany), have been enrolled (median age, 73 years; 32% female), with recruitment ongoing. Plaques undergo systematic histological characterization of lipid core, calcification, intraplaque hemorrhage, fibrous cap, macrophages, and smooth muscle cells. Single-nucleus RNA sequencing ( n = 17) has confirmed macrophages as the dominant intraplaque cell type, whereas paired plaque and plasma affinity–based proteomics ( n = 88) quantified 2841 shared proteins showing low plaque-plasma correlation (median ρ = 0.10). Cross-modality image integration [histology, ex vivo magnetic resonance imaging (MRI), in vivo MRI, and computed tomography angiography] proved feasible. Together, AtherOMICS enables multimodal characterization of human atherosclerosis aiming for the discovery of athero-specific drug targets, molecular signatures of atheroprogression, and noninvasive biomarkers of plaque vulnerability.

Aims: Atherosclerosis is currently evaluated by imaging, but scalable circulating biomarkers to detect its presence and quantify overall burden are lacking. We sought to define plasma proteomic signatures that reflect the systemic burden of atherosclerosis. Methods and Results: In UK Biobank, we trained machine-learning models on plasma proteomics in a nested, propensity-score-matched case-control sample (1,666 cases; 1,666 controls; Olink Explore 3072, 2,920 proteins) to derive four AtheroBurden signatures: one based on the entire proteome (all 2,920 proteins) and three biologically informed subsets—genetically anchored (n = 402), atherogenesis-related (n = 680), and artery-enriched (n = 248). We then computed individual-level signatures in 41,200 disease-free participants and validated their performance through 1) correlation with carotid plaque burden via ultrasound (n = 1,712); 2) prospective major adverse cardiovascular events (MACE) prediction over 13.7-year follow-up using multivariable Cox models and incremental prediction over Systematic COronary Risk Evaluation version 2 (SCORE2) (ΔC-index; net reclassification improvement [NRI]); as well as in the external Cooperative Health Research in the Region of Augsburg (KORA) S4 (n = 1,361) and Age1 (n = 796) cohorts; and 3) longitudinal trajectories analysis in 1,210 participants with three serial proteomic measurements. All four AtheroBurden signatures robustly discriminated prevalent atherosclerotic disease (ROC-AUC up to 0.91, 95% CI: 0.89–0.93) with their levels significantly increasing with the number of clinically affected vascular beds. We found significant correlations with carotid ultrasound–measured plaque burden. In prospective analysis, each signature exhibited strong associations with incident MACE (HR per SD increase in whole proteome signature: 1.75, 95% CI: 1.68–1.83; HR for Q4 vs. Q1: 3.18, 95% CI: 2.8–3.61), providing significant improvements in risk discrimination (ΔC-index: +0.044; p < 0.0001) and reclassification (NRI: 0.12 (95% CI: 0.09-0.15) at a 10% risk threshold) beyond SCORE2. These results were replicated in the KORA S4 and KORA-Age1 cohorts, where the signatures were associated with risk of future myocardial infarction and stroke. Furthermore, longitudinal analyses demonstrated steeper annual increases in proteomic signature among individuals with higher burden of vascular risk factors and individuals who experienced MACE over follow-up. Conclusions: Plasma proteomic signatures effectively capture atherosclerotic burden and improve cardiovascular risk prediction in asymptomatic individuals. They may complement existing risk stratification by serving as a scalable and accessible blood-based screening tool to identify individuals more likely to have subclinical atherosclerosis and may benefit from confirmatory imaging and earlier prevention strategies.

Aims: In patients with atherosclerotic internal carotid artery stenosis, the risk of subsequent ischaemic stroke is higher in those presenting with a cerebral transient ischaemic attack (TIA) than in those with amaurosis fugax (AFX; transient monocular blindness). While AFX is associated with more stable histological characteristics, the underlying molecular mechanisms remain unclear. We hypothesized that biological processes and gene expression profiles in carotid plaques of patients with AFX differ from those with cerebral TIA and stroke. Methods and results: We analysed carotid plaques from 2508 patients undergoing endarterectomy between 2002 and 2022. Bulk RNA sequencing (RNA-seq) was performed on 1088 plaques (136 asymptomatic, 179 AFX, 481 TIA, 292 stroke). Single-cell RNA-seq from 46 previously profiled plaques was used to identify cell-specific transcriptomic signatures. Mass spectrometry-based proteomics (n = 189) and targeted plasma proteomics (n = 1291) were used to validate the molecular differences. AFX plaques showed fewer lipid-rich cores than those from cerebral TIA [odds ratio (95% CI): 1.41 (1.03–1.94)] or stroke [1.42 (1.01–1.99)]. RNA-seq identified 408 differentially expressed genes (DEGs) between AFX and TIA and 463 between AFX and stroke (FDR < 0.1), while AFX and asymptomatic plaques showed only 10 DEGs. AFX plaques were enriched for vascular smooth muscle cell signatures and extracellular matrix remodelling, while cerebral TIA and stroke plaques exhibited macrophage-driven inflammatory molecular signatures. These transcriptomic differences were confirmed by plaque proteomic analyses. In parallel, circulating proteomic profiling revealed higher levels of inflammatory and thrombo-inflammatory markers in cerebral TIA and stroke compared with AFX. Conclusion: AFX plaques exhibit stable, SMC-dominant molecular signatures that differ markedly from the macrophage-driven inflammatory profiles of cerebral TIA and stroke plaques. These findings support AFX as a biologically distinct entity with potential implications for risk stratification and personalized treatment.

Cerebrovascular dysfunction emerges early in neurodegeneration, yet how vascular structure, blood–brain barrier (BBB) failure, and cognition are linked remains undefined. Using VesselPro, a whole-brain pipeline integrating perfusion-resolved 3D imaging with spatial proteomics, we mapped vascular aging across the mouse lifespan. We identify two discrete trajectories: a hypovascular state and a previously unrecognized hyper-vascular, BBB-compromised state, defined relative to a young-adult vascular baseline. The hyper-vascular trajectory, concentrated in the cortex and hippocampus, was associated with marked spatial memory impairment and pervasive BBB leakage. Spatial proteomics revealed a coordinated program involving angiogenic activation, endothelial stress, cytoskeletal remodeling, and inflammatory signaling. Cross-species comparison with human proteomic biomarkers from the UK Biobank showed strong alignment between the mouse hypervascular signature and vascular dementia risk, but minimal concordance with Alzheimer’s disease, defining a vascular-specific dementia endotype. Transient Tie2 activation with AKB-9778 attenuated this trajectory, improving vessel organization, BBB integrity, and memory performance. Our findings show that endothelial instability is a key mechanistic driver of this heterogeneous vascular aging state. Graphical Highlights: VesselPro : we developed a pipeline for capturing perfused blood vessels in the brain: unexpected bifurcation in vascular aging: traditional hypovascular state and a novel, hypervascular, BBB-compromised state . Hypervascular pathology : Linked the hypervascular profile in the cortex and hippocampus to spatial memory impairment, pervasive BBB leakage , and angiogenic inflammatory signaling . Clinical endotype : Cross-species analysis via the UK Biobank confirms this hypervascular signature aligns with vascular dementia risk rather than Alzheimer’s disease. Pharmacological stabilization : Demonstrated that Tie2 signaling activation (AKB-9778) improves the vessel organization, BBB integrity, and memory performance.

BACKGROUND: Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is the most common hereditary cerebral small-vessel disease. The CADASIL MRI Inventory Tool summarizes individual MRI findings as simple, type-specific lesion levels. We assessed the predictive value of these levels beyond clinical information. METHODS: At baseline, CADASIL MRI Inventory Tool levels were assigned for periventricular, deep, and superficial white matter hyperintensities, lacunes, cerebral microbleeds, perivascular spaces in the centrum semiovale and basal ganglia, superficial and deep atrophy, large infarcts, and macrobleeds. Outcomes included stroke, migraine with aura (MA), moderate or severe cognitive impairment, and disability, which were assessed at baseline and during 2-year follow-up. Multivariable logistic regression was performed, with adjustment for age, sex, vascular risk factors, mutation location, and education level. RESULTS: We analyzed 743 patients from France, Germany, and Taiwan (mean age, 53±12; 55% with prior stroke; 35% with MA; 15% with disability; 18% with cognitive impairment). At baseline, higher deep white matter hyperintensities and lacune levels were associated with stroke, whereas cerebral microbleeds and superficial atrophy were inversely associated with MA. Superficial atrophy and periventricular white matter hyperintensities were higher, and superficial white matter hyperintensities were lower, among those with cognitive impairment, whereas deep atrophy and lacunes were linked to disability. Over 2 years (n=547), 11.7% experienced ischemic stroke events, 22.2% MA attacks, 6.5% developed disability, and 6.9% moderate or severe cognitive impairment. After adjustment, lacune levels independently predicted ischemic stroke events (odds ratio, 6.10 [95% CI, 2.09–26.02] for all levels combined). Superficial atrophy and higher superficial white matter hyperintensities predicted a lower risk of MA (odds ratio, 0.29 and 0.21 [95% CI, 0.12–0.68] and [0.06–0.77]). Lacunes and deep atrophy predicted disability, and lacunes with superficial atrophy predicted cognitive impairment. CONCLUSIONS: CADASIL MRI Inventory Tool lesion levels are differentially associated with CADASIL manifestations and provide independent 2-year prognostic information beyond clinical covariates. These simple measures may supplement clinical evaluation to improve short-term risk stratification and support patient selection in clinical trials.

Introduction: Inequity in stroke care in Europe has previously been reported despite the existence of evidence-based cost-effective interventions for both prevention and treatment. This report aims to provide comprehensive data on stroke care in Europe in 2023 and explore associations to European regions, organisational and economic factors. Patients and methods: The Stroke Service Tracker, an annually collected survey-based dataset of aggregate summary data from participating European nations, was used with key performance indicators (KPIs) from the Stroke Action Plan for Europe (SAP-E). European regions were defined based on United Nations Geoscheme regions. Gross domestic product (GDP) per capita and healthcare spending per capita were collected based on World Bank data. Results: A total of 1,460,630 stroke events were reported in 2023 from 52 nations. Significant inequity was present in all data points and data quality varied significantly. Twenty (43.5%) nations have a national stroke plan in place, and in 19 (41.3%) work is ongoing. Quality programmes have been implemented in 20 (43.5%) nations. Implementation of a national stroke plan or a quality programme was associated with achieving more SAP-E KPIs (P < .001). There were regional differences in the number of met KPIs (P < .001). Both GDP and healthcare spending per capita were strongly correlated to meeting KPIs. Conclusion: The inequity in stroke care persists in Europe. Implementation of a national stroke plan and a quality programme is associated with meeting more KPIs; however, economic factors may pose limitations. Access to high-quality data will support decision-making towards evidence-based and cost-effective care.