Journal of Thrombosis and Haemostasis

BackgroundPlatelet morphological indices, such as mean platelet volume and distribution width, reflect platelet turnover and thrombo-inflammatory activity relevant to acute coronary syndrome (ACS), but their individual prognostic value remains inconsistent. This study aimed to derive an Integrated Platelet Index (IPI) using principal component analysis (PCA) to capture a multidimensional platelet morphological phenotype influenced by cardiometabolic and inflammatory stress and to examine its association with long-term major adverse cardiovascular and cerebrovascular events (MACCE) in ACS. MethodsThis prospective observational study included 1,467 ACS patients from the Beijing Hospital Atherosclerosis Study. Five routinely measured platelet indices--platelet count, mean platelet volume, platelet distribution width, plateletcrit, and platelet large-cell ratio--were integrated via PCA to construct the IPI. The primary endpoint was MACCE. Cox models, restricted cubic splines, Kaplan-Meier curves, and prespecified subgroup analyses assessed the prognostic relevance of the IPI and its consistency across metabolic and clinical strata. ResultsOver a median follow-up of 55.0 months, 141 patients (9.6%) experienced MACCE. Lower IPI values were associated with higher risk. Each unit increase in IPI was independently associated with a 27% lower MACCE risk after full adjustment (HR 0.73; 95% CI: 0.59-0.90). A significant L-shaped nonlinear relationship was observed, with steep risk reduction at lower IPI values. Event-free survival increased progressively across IPI tertiles. Associations remained consistent across cardiometabolic subgroups, with no significant interactions. ConclusionsThe PCA-derived IPI represents an integrated platelet morphological phenotype associated with long-term atherothrombotic risk in ACS. Its nonlinear behavior and robust performance across metabolic backgrounds support its potential as an accessible, phenotype-based marker for refining secondary prevention risk stratification. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/25342328v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@7a6e84org.highwire.dtl.DTLVardef@1eda7a3org.highwire.dtl.DTLVardef@198df1forg.highwire.dtl.DTLVardef@160722b_HPS_FORMAT_FIGEXP M_FIG C_FIG What Are the Clinical Implications?Platelet morphology and turnover are influenced by cardiometabolic and inflammatory stress, yet routine platelet indices are rarely incorporated into ACS risk assessment because each parameter reflects only a single dimension of platelet biology. By integrating five commonly available platelet indices into a single PCA-derived morphological phenotype, the Integrated Platelet Index (IPI) provides a multidimensional representation of platelet alterations relevant to atherothrombotic risk. In this study, lower IPI values consistently identified patients at higher long-term risk of MACCE, and the L-shaped nonlinear association suggests that relatively small reductions in this phenotype may reflect disproportionately adverse platelet remodeling. Because the IPI relies solely on automated complete blood count parameters, it is low-cost, universally available, and feasible for implementation in secondary prevention pathways, including in resource-limited settings. Clinically, the IPI may improve risk stratification in ACS by capturing thrombo-inflammatory and metabolic influences not detected by traditional predictors. Its stability across cardiometabolic subgroups supports broad applicability. Future studies should determine whether serial IPI monitoring can identify patients with persistent thrombotic risk and whether incorporating the IPI into validated ACS risk models enhances individualized management. HighlightsO_LIWe derived an Integrated Platelet Index (IPI) representing a PCA-based morphological phenotype from five routine platelet indices. C_LIO_LILower IPI values identified patients with heightened long-term atherothrombotic risk after acute coronary syndrome. C_LIO_LIThe IPI captures multidimensional platelet alterations shaped by thrombo-inflammatory and cardiometabolic stress. C_LIO_LIThe association between IPI and adverse outcomes remained consistent across major cardiometabolic subgroups. C_LIO_LIThe IPI provides an accessible, low-cost phenotype with potential utility for risk stratification in secondary prevention. C_LI

BackgroundScreening criteria for abdominal aortic aneurysm (AAA) are based on clinical factors, such as age and smoking history, but do not include biological factors that may better reflect disease pathogenesis. ObjectivesWe sought to determine whether a proteomic risk score (ProRS) incorporating plasma protein abundance could improve prediction of AAA. MethodsWe performed a cross-sectional analysis of nearly 37,000 participants in the UK Biobank Pharma Proteomics Project with plasma protein abundance data for 274 cardiometabolic proteins. ProRS models were developed using regularized regression. ResultsThe generated sparse ProRS contained well-established clinical risk factors as well as a single protein - matrix metalloproteinase 12 (MMP12). Overall performance and discriminatory utility of this model was higher than an identical model without MMP12 (difference in Brier score 2.1 x 10-4, 95% CrI 2.0-2.3 x 10-4; difference in AUROC 0.021, 95% CrI 0.020 - 0.022). Within the cohort, current AAA screening recommendations applied to 4.6% of the population and captured 30% of cases, whereas screening 4.6% of the population at highest risk by ProRS captured 52% of cases. Among individuals with incident AAA, MMP12 abundance was independently associated with time to rupture or repair (HR 1.86, 95% CI 1.39-2.50, p < 0.001). Additionally, MMP12 level improved discrimination of AAA in an external cohort (SIMPLER; difference in AUROC 0.084, 95% CrI 0.081 - 0.087). ConclusionsA biologically-plausible ProRS incorporating a single matrix metalloproteinase improved prediction of AAA over clinical factors alone. These results may be used to enhance screening strategies for AAA.

Anti-{beta}2-glycoprotein I (anti-{beta}2GPI) antibodies are central to the pathogenesis of antiphospholipid syndrome (APS), an autoimmune disease characterized by a strong predisposition to venous thromboembolism (VTE). In this study, we conducted a multi-ancestry genome-wide association study (GWAS) of quantitative total anti-{beta}2GPI levels in 5,969 participants enrolled in the Multi-Ethnic Study of Atherosclerosis (MESA) and identified a genome-wide significant association at the APOH locus. Paradoxically, genetically determined increases in anti-{beta}2GPI levels at this locus were associated with lower VTE risk. Fine-mapping and functional genomics prioritized the missense variant rs1801690 (W335S) in {beta}2GPI (apolipoprotein H, [APOH]) as the most likely causal variant. This variant has an allele frequency of 5-6% in European and East Asian ancestries but only 1% in African ancestries. Integrating prior experimental studies, molecular dynamics simulations and structure-based epitope prediction, we propose a dual-effect mechanism whereby W335S reduces thrombotic risk by disrupting phospholipid binding in Domain V, yet increases autoantibody production through conformational changes that enhance epitope exposure in Domains I and II. These findings mechanistically uncouple autoantibody formation from thrombotic risk in carriers of the W335S variant, and suggest that APOH genotype may represent a clinically relevant genetic biomarker with potential utility for thrombotic risk stratification in anti-{beta}2GPI-positive individuals.

BackgroundEmbolic stroke of undetermined source (ESUS) is associated with a high risk of recurrence. However, randomized trials have not shown superiority of anticoagulation over aspirin in unselected patients. Atrial cardiomyopathy (AtCM) may identify a high-risk ESUS phenotype. We investigated whether multimodal AtCM markers distinguish ESUS from controls and predict adverse clinical outcomes. MethodsIn this prospective single-center study, consecutive ESUS patients and age- and sex-matched controls without known cardiac disease were enrolled and followed for [&ge;]12 months. All participants underwent clinical assessment, measurement of NT-proBNP, 12-lead ECG, and transthoracic echocardiography. The primary endpoint was a composite of all-cause death, recurrent stroke, transient ischemic attack, myocardial infarction, or newly detected atrial fibrillation. Cox regression analyses identified independent predictors and optimal cutoff values. ResultsThe study included 103 ESUS patients (mean age 70.6{+/-}13.3 years) and 123 controls. Compared with controls, ESUS patients had higher NT-proBNP levels, more frequent advanced interatrial block (IAB), and impaired left atrial function. Over a mean follow-up of 470{+/-}205 days, 29 ESUS patients experienced the primary endpoint. Independent predictors were NT-proBNP >420 pg/mL, advanced IAB, E' [&le;]9 cm/s, left atrial volume index [&ge;]29 mL/m{superscript 2}, and left atrial ejection fraction <50%. A risk score incorporating these variables identified a high-risk ESUS subgroup ([&ge;]3 factors) in which >50% experienced a cardiovascular event within 1 year. ConclusionsAtCM features are common in ESUS and strongly associated with adverse outcomes. A multimodal assessment incorporating NT-proBNP, ECG, and echocardiography identifies a high-risk ESUS subgroup that merits targeted evaluation in future anticoagulation trials.

ObjectiveRotational percutaneous mechanical thrombectomy with adjunctive angioplasty, stenting or limited thrombolysis (rPMT+) has become commonplace in the treatment of acute and subacute limb ischaemia. This systematic review and proportional meta-analysis synthesises the available evidence on its safety and efficacy. Data SourcesMEDLINE, Embase and the Cochrane Library. [&ge;] Review MethodsWe searched for studies ([&ge;]10 patients) published since 1 January 2012 (PROSPERO protocol CRD420251015846). Risk of bias was assessed using RoBANS 2. Proportional meta-analysis maximised representative sample sizes by incorporating both single-arm and comparative studies. GRADE evidence profiles were developed for each outcome of interest. ResultsTwenty-four studies - seven comparative and 17 single arm - containing 2,954 procedures (2,697 rPMT+, 257 controls) met eligibility criteria. There were no randomised controlled trials. The pooled technical success (TS) rate for rPMT+ was 98% (95% CI: 97-100%, p<0.001). Amputation-free survival (AFS) was 96% (95% CI: 93-98%, p<0.001). Twelve-month primary patency (PP) was 68% (95% CI: 55-79%, p<0.001). The pooled rate of freedom from clinically-driven target lesion revascularisation (fCDTLR) was 85% (95% CI: 80-90%, p<0.001). No significant differences existed between acute, subacute and mixed subgroups. Procedure-related mortality was 0.5% (11 deaths in 2,086 procedures from 17 studies) with most deaths occurring after adjunctive catheter-directed thrombolysis. Major adverse events occurred in 4% of procedures (95% CI: 1-8%, p<0.001) and distal embolization in 8% (95% CI: 5-11%, p<0.001). rPMT+ reduced length of stay by 1.7 days versus alternatives (95% CI: 3.3-0.1 days, p<0.05). All outcomes demonstrated heterogeneity. GRADE assessment rated evidence certainty as low to very low. ConclusionrPMT+ delivers consistently high TS and AFS rates, promising 12-month fCDTLR, acceptable PP, low procedural risk and shorter hospital stays than comparators. The consistency of favourable outcomes supports its use as a safe and effective treatment in appropriately selected ALI and SLI patients. WHAT THIS PAPER ADDSThis systematic review and proportional meta-analysis synthesises 24 single-arm and comparative non randomised studies encompassing nearly 3,000 procedures to provide a comprehensive assessment of the safety and efficacy of rotational percutaneous mechanical thrombectomy in patients with acute and subacute lower limb ischaemia. It demonstrates that, when used for initial revascularisation prior to adjunctive angioplasty, stenting or limited thrombolysis, this endovascular approach delivers consistently high rates of technical success and amputation-free survival with notably high rates of freedom from clinically-driven target lesion revascularisation, acceptable primary patency, low procedural risk and significantly shorter hospital stays.

ObjectivePost-thrombotic syndrome (PTS), a common complication of deep vein thrombosis, lacks objective diagnostic biomarkers and its molecular mechanisms remain poorly understood. This study aimed to identify plasma biomarkers and clarify pathways using integrated multi-omics and machine learning. MethodsProteomic and metabolomic profiling of 75 PTS patients and 75 controls was performed. Differential expression analysis, pathway enrichment, and protein-metabolite network analysis were conducted. A multi-algorithm machine learning with 8 feature selection methods prioritized biomarkers. Validations and 14 models were assessed. Results1,104 proteins and 1,891 metabolites were differentially expressed. Citrate cycle and unsaturated fatty acid biosynthesis were enriched. Three proteins, namely DIP2B, KNG1, and SUCLG2, were consistently selected as core biomarkers. All of these proteins were significantly downregulated in PTS and externally validated. A random forest model utilizing these proteins achieved an accuracy of 97.7% in independent testing, with SUCLG2 being the most influential predictor. ConclusionThis study identifies a novel three - protein biomarker panel for the diagnosis of PTS and reveals an immunometabolic axis in the pathogenesis of PTS, which links inflammatory regulation with mitochondrial energy metabolism. These findings provide valuable insights into the development of diagnostic tools and targeted therapeutic approaches.

BackgroundAnthracyclines are central to childhood cancer therapy but predispose patients to cardiotoxicity leading to long-term cardiovascular risk. Endothelial injury and impaired repair contribute to this, yet pediatric data remain limited. ObjectiveTo longitudinally assess endothelial injury and repair in childhood cancer patients treated with anthracyclines by quantifying circulating endothelial cells (CECs) and endothelial progenitor cells (EPCs). MethodsIn a single-centre retrospective cohort, children (<18 years) diagnosed with leukemia (n=35) or lymphoma (n=13) were studied at four timepoints: pre-treatment ("Pre"), [~]1-month- ("End"), 3 months- (3M), and 1 year- (1Y) post-treatment. Peripheral blood mononuclear cells were analyzed by flow cytometry to quantify CECs and EPCs, and EPC fate was assessed by p16 (senescence) and Annexin V (apoptosis). Cardiac injury biomarkers and left ventricular function were assessed at each timepoint. ResultsLongitudinal trends of CEC and EPC counts were similar between leukemia and lymphoma participants. CECs were highest at pre-treatment and declined significantly thereafter, though they remained marginally elevated during remission compared with healthy controls, indicating that endothelial damage had largely subsided following treatment. EPCs were also highest at pre-treatment and decreased to levels below healthy controls during remission, suggesting impaired baseline endothelial maintenance and repair. Furthermore, EPCs were predominantly senescent up to 1-year post-treatment. ConclusionsEndothelial injury resolves by treatment completion, but repair remains impaired during remission with EPC pools dominated by senescent cells. This suggests defective endothelial regeneration, rather than persistent injury, drives long-term cardiovascular complications and underscores the need to restore EPC viability and function in childhood cancer survivors.

BackgroundThe relationship between COVID-19 hospitalisation and stroke occurrence remains incompletely understood, with reported incidence rates varying significantly across studies. This systematic review and meta-analysis aimed to comprehensively evaluate the association between COVID-19 hospitalisation and stroke occurrence, while examining key subgroup variations and potential risk factors. MethodsA systematic search was conducted across PubMed, Scopus, and Web of Science databases from December 2019 to 2023. Studies reporting stroke occurrence in hospitalised COVID-19 patients were included. The Newcastle-Ottawa Scale was used for quality assessment. Random-effects meta-analysis was performed to calculate pooled odds ratios (OR) and risk ratios (RR) with 95% confidence intervals (CI). ResultsNineteen studies met the inclusion criteria. The primary meta-analysis of 17 studies, comprising 98,297 patients, revealed a pooled stroke occurrence of 1% (95% CI: 1%,2%). A comparative analysis of three studies showed no significant difference in stroke risk between hospitalised COVID-19 patients and non-COVID-19 hospitalised controls (OR: 1.13, 95% CI: 0.49,2.65). However, within the COVID-19 hospitalised population, stroke risk was strongly associated with disease severity, including the need for mechanical ventilation (OR: 3.59, 95% CI: 2.21,5.83) and ICU admission (OR: 6.33, 95% CI: 4.95, 8.09). Significant pre-existing comorbidities included hypertension (OR: 2.35, 95% CI: 1.12,4.92) and atrial fibrillation (OR: 1.98, 95% CI: 1.18,3.31). Ischemic stroke was the predominant subtype, accounting for 81% of cases (95% CI: 73%,90%). Quality assessment of the 19 studies identified 9 as high quality and 10 as moderate quality. ConclusionsThis meta-analysis indicates that while the overall occurrence of stroke in hospitalised COVID-19 patients is approximately 1%, the risk is not significantly elevated compared to non-COVID-19 hospitalised patients. Instead, stroke occurrence is powerfully driven by the severity of the illness and the presence of traditional vascular risk factors. These findings underscore the critical need for vigilant neurological monitoring and targeted stroke prevention strategies, particularly for COVID-19 patients who require intensive care or mechanical ventilation.

BackgroundCardiovascular (CV) disease risk is increased in rheumatoid arthritis (RA) and is the leading cause of mortality. Improved CV risk stratification tools in RA could enhance use of preventative care and improve outcomes. MethodsWe previously studied biomarkers of CV disease - adiponectin, hsCRP, Lp(a), osteoprotegerin (OPG), high-sensitivity cardiac troponin T (hsTnT), serum amyloid A (SAA), YKL-40, soluble TNF receptor1 (sTNFR1) -- that were associated with CV risk. In the current study, these biomarkers were tested in an unrelated external cohort of RA patients followed at a single academic medical center without a history of CV events. CV events were identified through Medicare and Medicaid administrative data or through medical record review of self-reported events. Biomarkers were assessed at cohort entry among a nested cohort of cases and controls, matched 1:1 on sex and age. Analyses were conducted using conditional logistic regression. We examined whether the candidate biomarkers added to clinical CV risk factors improved model prediction, using the area under the curve (AUC) as well as the net reclassification index (NRI). ResultsFrom a cohort of 1,345 eligible patients with RA, we identified 123 patients with confirmed CV events. Cases and matched controls were typical of RA: median age 63 years, 77% women, RA disease duration 11 years, 72% seropositive, 85% used a biologic or conventional disease modifying anti-rheumatic drug, 58% non-steroidal anti-inflammatory drugs, and 30% oral glucocorticoids. From the candidate biomarkers, LASSO regression selected hsTnT and sTNFR1 as associated with CV events. The AUC for models that included only clinical risk factors was 0.758 (95% CI 0.689-0.829); after adding hsTnT and sTNFR1, the AUC increased to 0.802 (95% CI 0.718-0.998). The NRI of the model with biomarkers was 16.3%, with improvement only observed in patients who did not have CV events during follow-up. ConclusionsAdding selected biomarkers to clinical risk factors enhances the discrimination of models predicting CV events among patients with RA. These risk models require prospective testing to see if they have value in clinical practice decision-making regarding preventative care.

BackgroundThe pathways linking lipoprotein(a) (Lp[a]) to atherosclerotic cardiovascular disease (ASCVD) are unclear. This study aimed to discover Lp(a)-associated plasma proteins and estimate their associations with incident ASCVD. MethodsWe analyzed 48,859 UK Biobank participants with measured Lp(a) and proteomic profiles, with replication in 9,416 individuals in the Atherosclerosis Risk in Communities (ARIC) study cohort utilizing a separate proteomic platform. Linear models assessed associations between Lp(a) and protein concentrations adjusted for age, sex, cigarette smoking, diabetes diagnosis, body mass index, systolic blood pressure, hypertension, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol, triglycerides, estimated glomerular filtration rate, statin prescription, and the first 10 components of genetic ancestry. Multiple testing correction was performed using the Benjamini-Hochberg FDR method (P < 0.05). We examined how the protein effect sizes from the primary analysis using the outcome of Lp(a) aligned with those for the outcomes of an LPA genetic risk score (GRS) and LDL-C. Cox proportional hazards models quantified hazard ratios (HRs) for protein associations with incident ASCVD. ResultsParticipants were a mean age of 57 years (SD 8.22), 93.9% European, and 53.8% male, with median follow-up of 8.9 years (IQR 8.3-9.7). Of 1,459 circulating proteins, 164 were significantly associated with Lp(a) after FDR correction, with enrichment for lipid degradation, metabolism, and insulin secretion. In the ARIC study, 10 proteins were replicated with consistent effect estimates. Of these replicated proteins, there were no significant associations observed with an LPA GRS. Only REG4 and VWC2 showed concordant associations with LDL-C (P < 0.001), consistent with their association with Lp(a). Five proteins exhibited concordant associations with Lp(a) and incident ASCVD (ITIH3, DLL1, REG4, VWC2, CBLN4). ITIH3 was positively associated with coronary artery disease (HR 1.13, 95% CI 1.04-1.23), peripheral artery disease (HR 1.42, 95% CI 1.19-1.69), major adverse limb events (HR 1.65, 95% CI 1.14-2.40), carotid stenosis (HR 1.45, 95% CI 1.13-1.85), and ischemic stroke (HR 1.33, 95% CI 1.13-1.55). CBLN4 uniquely showed inverse associations with Lp(a) and disease: higher levels were linked to lower risk of CAD (HR 0.88, 95% CI 0.80-0.96), PAD (HR 0.78, 95% CI 0.64-0.96), and ischemic stroke (HR 0.72, 95% CI 0.60-0.85). ConclusionUsing high-throughput proteomics, we discovered and replicated 10 proteins associated with circulating Lp(a), several of which were independent of genetically-predicted Lp(a). While Lp(a) is highly heritable, these atherogenic proteins represent a non-heritable Lp(a) axis. Clinical PerspectiveO_ST_ABSWhats New?C_ST_ABSO_LITen proteins associated with circulating lipoprotein(a) levels were identified and independently replicated in an external cohort, with associations independent of a genetic risk score. C_LIO_LIFive proteins (ITIH3, CBLN4, FLL1, REG4, VWC2) were concordantly associated with lipoprotein(a) and incident atherosclerotic cardiovascular disease. C_LI Clinical ImplicationsO_LIThese proteins may represent pathways through which lipoprotein(a) drives atherosclerosis beyond traditional lipid mechanisms. C_LIO_LIFuture mechanistic studies should investigate the roles of these proteins to guide the development of targeted strategies for preventing atherosclerotic cardiovascular disease. C_LI

IntroductionPathophysiological distinctions among stroke subtypes--acute ischemic stroke (AIS), subarachnoid hemorrhage (SAH), intracerebral hemorrhage (ICH), and other nontraumatic intracranial hemorrhage (ONIH)--are well described, but their associations with long-term mortality, cognitive outcomes, and dementia risk remain incompletely characterized. We examined whether stroke subtypes differ in post-stroke survival, cognitive performance, dementia risk, and neuroimaging phenotypes. MethodsUsing data from the UK Biobank, we evaluated subtype-specific associations with all-cause mortality, incident all-cause dementia, post-stroke cognitive performance, and white matter hyperintensity (WMH) burden. We assessed time to mortality and all-cause dementia using multivariable Cox proportional hazards models. Cognitive outcomes were compared cross-sectionally between stroke subtypes and stroke-free participants using covariate-adjusted linear models with ANOVA and Tukey post hoc tests. Neuroimaging analyses assessed associations between stroke subtype and WMH volume. ResultsMortality risk varied substantially by stroke subtype. Of UKB participants who had a stroke during surveillance (n=14,806), we found that 69.24% of strokes were ischemic, 9.51% subarachnoid, 9.78% ONIH, and 11.78% ICH. Compared with stroke-free person-time, intracerebral hemorrhage was associated with the highest post-stroke hazard of death (HR 7.62, 95% CI 7.10-8.18), followed by other nontraumatic intracranial hemorrhage (HR 5.41, 95% CI 4.89-5.98), subarachnoid hemorrhage (HR 3.89, 95% CI 3.52-4.31), and ischemic stroke (HR 3.99, 95% CI 3.82-4.16). At 1 year after stroke, absolute mortality risk was highest following ICH (36.4%), followed by ONIH (31.9%) and SAH (26.0%), while ischemic stroke was associated with substantially lower risk (11.7%); by 5 years, corresponding risks increased to 43.5%, 39.8%, 30.0%, and 20.0%, respectively. Dementia risk also differed by subtype, with the highest risk observed following ICH. Post-stroke cognitive performance varied across domains, with slower reaction times observed across multiple stroke subtypes and lower fluid intelligence scores among AIS and ICH patients. Reaction time and fluid intelligence assessments were completed a median of approximately 6-9 years after stroke. WMH burden was higher in ICH and AIS compared with stroke-free participants. ConclusionsStroke subtype is associated with distinct patterns of mortality, dementia risk, cognitive performance, and brain imaging phenotypes. These findings highlight the heterogeneity of long-term outcomes following stroke and support the importance of subtype-aware post-stroke monitoring and prognostication.

BackgroundThe comparative roles of triglyceride-rich lipoproteins (TRLs) and low-density lipoproteins (LDLs) in abdominal aortic aneurysm (AAA) pathogenesis are unclear. ObjectivesTo evaluate the putative causal role of TRLs in AAA, quantify the relative effect on AAA risk ("aneurysmogenicity") of TRL vs LDL particles, and prioritize lipid-lowering drug targets for AAA prevention and treatment. MethodsWe performed summary-level and individual-level Mendelian randomization (MR) analyses. Genetic variants were selected from 383,983 UK Biobank participants and ranked into 10 sets of variants where set 1 predominantly affected LDL cholesterol (LDL-C) and set 10 predominantly affected TRL cholesterol (TRL-C; and with mixed effects for intermediate variant sets). AAA outcome data were obtained from AAAgen (37,214 cases), FinnGen (4,439 cases), and the VA Million Veteran Program (MVP; 23,848 cases). Multivariable MR was used to assess the independent roles of LDL-C and TRL-C in AAA. For each set of variants, MR or logistic regression was used to estimate AAA odds ratios (ORs) per 10 mg/dL higher apolipoprotein B (apoB). Interaction analyses were conducted between a statin-like LDL-C-lowering variant set (set 3) and a TRL-C-lowering variant set (set 10). Drug-target MR was performed to evaluate lipid-lowering targets relevant to LDL-C- and TRL-C-lowering. ResultsGenetically predicted LDL-C and TRL-C concentrations were each associated independently with genetic liability for AAA after mutual adjustment, with 3.0 to 5.5 times stronger associations for TRL-C compared to LDL-C on a per-cholesterol basis. In AAAgen, the AAA OR per 10 mg/dL increased apoB concentrations were 1.10 (95% CI, 1.05-1.14) for variant set 1 (LDL-C-predominant) and 1.89 (95% CI, 1.69-2.11) for variant set 10 (TRL-C-predominant). Using the ratio of log(OR) per 10 mg/dL apoB for set 10 versus set 1 as a conservative estimate of relative aneurysmogenicity, TRLs were approximately 3.2 to 6.9 times more aneurysmogenic than LDLs across the three studies. No evidence of interaction was observed between LDLs and TRLs, indicating additive contribution to AAA risk. Drug-target MR supported strong protective associations for genetically proxied inhibition of TRL-pathway targets, particularly APOC3 and LPL, with AAA risk. ConclusionsTRLs are at least threefold more aneurysmogenic than LDLs on a per-particle basis. Therapeutic strategies targeting TRL-C --especially via APOC3 and LPL--should be prioritized for AAA prevention and treatment.

PurposeSepsis-associated immunothrombosis significantly contributes to high mortality, yet the role of N-glycosylation in this process remains poorly understood. This study aimed to comprehensively profile the plasma N-glycosylation landscape in sepsis and elucidate how its specific reprogramming in the complement and coagulation cascades influences immunothrombotic balance and patient outcomes. MethodsWe performed in-depth 4D-DIA proteomic and N-glycomic analyses on plasma from 43 sepsis patients and 9 healthy controls. Differential expression, weighted gene co-expression network analysis (WGCNA), and protein-glycosylation correlation analyses were used to characterize molecular features. Clinical relevance was assessed via correlation and survival analyses. ResultsExtensive N-glycosylation reprogramming was observed in sepsis plasma,with marked enrichment in complement and coagulation pathways(KEGG p=7.76x10- {superscript 2}{superscript 1}).Pro-coagulant proteins(eg,vWF,fibrinogen)showed increased abundance together with enhanced site-specific glycosylation,potentially amplifying their activity.In contrast,key anticoagulant proteins(eg,SERPINC1)displayed unchanged glycosylation at critical sites despite abundance changes,which may impair function.Survival analysis revealed distinct prognostic values of glycoproteins and specific glycosylation sites.For instance,high vWF protein levels predicted mortality(HR=2.83),whereas elevated glycosylation at vWF N211 was associated with improved survival(HR=0.135),suggesting a negative regulatory role.These glycosylation markers correlated closely with disease severity and prognosis,representing potential early-warning biomarkers independent of current clinical coagulation indicators. ConclusionOur study demonstrates widespread reprogramming of the plasma proteome and N-glycome in sepsis.We propose that decoupling of protein function from abundance through N-glycosylation in the complement-coagulation network contributes to immunothrombotic imbalance.Specific N-glycosylation sites may serve as novel prognostic biomarkers,offering new perspectives for early risk stratification and glycosylation-targeted therapies in sepsis. Key PointsO_LISepsis plasma exhibits specific N-glycosylation reprogramming overwhelmingly focused on the complement and coagulation cascade. C_LIO_LIA dominant "glycosylation-dominated co-upregulation" mode in procoagulant factors, coupled with a "silent" glycosylation state in key anticoagulants, drives prothrombotic imbalance. C_LIO_LISite-specific N-glycosylation levels provide prognostic information distinct from, and often superior to, their carrier protein abundance, offering novel early-risk biomarkers. C_LI

BackgroundPulmonary embolism (PE) is frequently suspected in patients with cancer due to non-specific symptoms suggestive of PE and their inherent risk of venous thromboembolism (VTE). Commonly used clinical decision rules (CDRs) and D-dimer testing may be less reliable in this specific population. Due to the lack of guideline recommendations on the optimal diagnostic approach and the perceived futility of D-dimer in patients with cancer, clinicians often use computed tomography pulmonary angiography (CTPA) as a sole diagnostic test. This practice exposes patients to potentially unnecessary radiation and harm, and contributes to a significant burden on healthcare systems through inefficient resource allocation. The YEARS algorithm is an easy-to-use CDR that has been shown to safely exclude PE without the need for CTPA in a diverse population of patients with suspected PE. ObjectiveTo compare the safety and efficiency of the YEARS algorithm to the safety and efficiency of CTPA only in the diagnostic management of acute PE in cancer patients. Design and interventionsThe Hydra study (ClinicalTrials.gov NCT04657120) is an investigator-initiated, multicentre, multinational open-label, randomised, non-inferiority trial with blinded adjudication of outcome events, comparing the YEARS algorithm with CTPA only in the diagnostic work-up of cancer patients with clinically suspected acute PE. Participants are randomised in a 1:1 ratio to each diagnostic strategy via a web-based system. The trial anticipates to include 1566 patients. ParticipantsConsecutive patients with active cancer who are hospitalized or present to the emergency department, outpatient clinic, or thrombosis clinic with clinically suspected PE and who are not receiving therapeutic anticoagulation or have an indication for anticoagulation therapy other than PE. Study outcomesThe primary safety outcome is the proportion of symptomatic and objectively proven fatal or non-fatal VTE (i.e., PE or deep vein thrombosis in the upper or lower extremities) or death with undetermined cause where acute PE could not be ruled out as contributing factor during three months follow-up in patients in whom PE was ruled out at initial testing. The primary efficiency outcome is the proportion of negative CTPA scans for PE, relative to the total number of CTPA scans performed at initial testing. ImplicationThis trial will provide pivotal data on the optimal diagnostic approach for suspected acute PE in patients with cancer. Strengths and limitations of this studyO_LIThe Hydra study is the first prospective, randomised trial comparing the safety and efficiency of the YEARS algorithm with CTPA only for suspected acute PE in patients with active cancer. C_LIO_LIThe enrolment of a large number of patients from multiple teaching and general hospitals across various clinical settings and countries enhances the generalisability of this study. C_LIO_LIThe randomised design and the vulnerable study population may render the study challenging. C_LI

Deep vein thrombosis is a disease that occurs when a blood clot is formed in a vein and occludes the vessel lumen, blocking the blood flow, causing pain and even disability and possibly leading to complications such as postthrombotic syndrome and pulmonary embolism. Treatments for DVT include mechanical thrombectomy: introducing a device into the vasculature to remove thrombus. Currently used devices either macerate the thrombus to aid removal or pierce the thrombus to reach its distal side. This can pose risk of fragmentation or distal embolization, or in case of fibrous, cohesive thrombi can be hard to achieve due to their resistance to deformation. The following study proposes an alternative approach of bypasing the thrombus via the space between the thrombus and the vessel wall in order to avoid thrombus penetration. The design implements a strategy of simultaneously gripping the clot and expanding the vessel lumen in order to create space between the thrombus and the vessel wall while advancing along the clots length in incremental steps. The prototype has been evaluated in a custom-made experimental setup using phantom vessels and thrombi analogs. The proof-of-concept experiments have shown that the device can successfully bypass and in some cases even remove thrombi. The study shows promising results for this new kind of device and can be a foundation for future research into applying similar removal strategies in thrombectomy.

BackgroundInhaled combusted cannabis and co-use of combusted cannabis and nicotine electronic cigarettes (nECIGs) are on the rise, yet their long-term cardiovascular risk is unclear due to the high prevalence of confounders in observational human studies. Using primary plasma and monocytes and a novel ex vivo mechanistic model of two early steps in atherogenesis, this study examined whether chronic combusted cannabis use is associated with atherogenic changes, as estimated by 1) monocyte transendothelial migration (MTEM), and 2) monocyte-derived foam cell formation (MDFCF), and whether nECIG co-use further amplifies this risk. MethodsA cross-sectional parallel group comparison study was conducted in healthy adults (21-30 years) who chronically 1) used combusted cannabis, 2) co-used both combusted cannabis and nECIGs, and 3) were non-using controls. Using our ex vivo atherogenesis assay, primary outcomes of MTEM, MDFCF, and median fluorescence intensity (MFI) of the lipid-staining fluorochrome BODIPY were determined using primary plasma and autologous primary monocytes from participants. Using flow cytometry and the fluorochrome CELLROX, cellular oxidative stress (COS) in monocytes was determined. ResultsOf the 134 participants, 59 used cannabis, 26 co-used cannabis/nECIG, and 49 were non-using controls. The groups had similar age, sex, and race. Median MTEM was 1.13 fold greater in people who used cannabis compared to non-users 27.8% (IQR 26.1:29.2%) vs 24.5%, (IQR 22.9:27.4%), p<0.0001, and tended to be greater in people who co-used cannabis/nECIG by 1.22-fold 34.1%, (IQR 29.9:38.3%, p=0.17). Median MDFCF and MFI were also increased in people who used cannabis compared to non-users (MDFCF 36.3%, IQR 31.8:35.8%, vs 26.6%, IQR 23.8:25.8%, 1.36-fold and MFI 1163.8, IQR 1042.8:1155.0, vs 940.2 IQR 849.9:1101.4, 1.24-fold) and were further increased in people who co-used cannabis/nECIG (MDFCF 48.7%, IQR 37.3:52.4%, 1.34-fold, MFI 1433.7, IQR 1263.8:1686.4, 1.23-fold; all comparisons p<0.008). Foam cell formation, but not transendothelial migration, was strongly positively correlated with COS. All primary outcomes increased with greater frequency of cannabis and/or nECIG use. ConclusionsIn healthy young adults, exclusive cannabis use is associated with increased atherogenic properties of monocytes and plasma, and this atherogenic effect is further amplified by co-use of nECIGs.

BackgroundCirculating lipoprotein(a) [Lp(a)] levels are highly heritable and linked to atherosclerotic cardiovascular disease, yet clinical measurement rates remain low (<1%) in the United States. The high heritability of Lp(a) across populations makes genetic prediction an attractive approach for closing this testing gap, but existing polygenic scores transfer poorly across populations. Haplotype-based prediction models, which use standard genome-wide genotype data to capture common-, rare-, and structural-variation at the LPA locus, could bridge this gap, enabling opportunistic identification of individuals with elevated Lp(a) levels across diverse populations within existing large, genotyped cohorts. ObjectivesThis study sought to develop and validate a haplotype-based prediction model using genome-wide genotype data to identify individuals with elevated Lp(a) levels across diverse populations. MethodsWe developed an LPA-haplotype model using data from the All of Us Research Program and validated it in the Penn Medicine BioBank (PMBB), Mass General Brigham Biobank (MGBB), and Mount Sinai BioMe cohorts. Primary outcomes included model performance for predicting continuous Lp(a) concentrations (r{superscript 2}) and identifying elevated Lp(a) levels (>125 nmol/L) through positive predictive value (PPV) and number needed to test (NNT). ResultsAmong PMBB (n = 1856), MGBB (n = 1401), and BioMe (n = 1686) participants with available genotype and Lp(a) measurements, average age was 60 years, and 51% were female. Overall r{superscript 2} of the haplotype model was 0.46 (95% Credible Interval [CrI] 0.32 to 0.6), with similar performance across genetically inferred ancestries and cohorts. For identifying elevated Lp(a) levels >125 nmol/L the overall PPV was 0.81 (95% CrI 0.6 to 0.89), corresponding to a NNT of 1.2 (95% CrI 1.1 to 1.7) individuals predicted to have elevated levels needing to undergo clinical testing to identify one true elevation. In the full PMBB cohort (n = 49310), the haplotype model identified elevated Lp(a) at a rate of 128 per 1000 (95% CrI 125 to 130), corresponding to an estimated 14.4-fold improvement (95% CrI 13.1 to 15.9; P(improvement) = 1) in identification rate compared with the existing rate of clinical assessment. ConclusionsA haplotype-based genetic model effectively identified individuals with elevated Lp(a) levels across diverse populations, with potential utility for opportunistic screening among cohorts where genotype data is available, but Lp(a) testing rates are low.

BackgroundClonal hematopoiesis of indeterminate potential (CHIP) is associated with cardiovascular disease (CVD) in the general population and is more common among people with HIV (PWH). The mechanisms by which CHIP contributes to atherosclerosis in PWH are unknown. We hypothesized that CHIP is associated with carotid atherosclerosis, arterial inflammation, and hematopoietic activity among PWH. MethodsIn a cohort study, we studied PWH ages 31-74 years. CHIP mutations were detected with a validated targeted sequencing assay. Carotid intima-media thickness (IMT) was measured longitudinally with ultrasound. Aortic inflammation and lymph node activity were assessed cross-sectionally using 18F-FDG-PET. Inflammatory biomarkers were measured using multiplex electrochemiluminescence assay. Linear regression was employed, with adjustments for traditional and HIV-related factors. ResultsWe included 230 PWH (52{+/-}9 years, 7% female); 32 (14%) had CHIP with median variant allele fraction of 2.8%. Common mutations were in DNM3TA (n=21) and TET2 (n=6). Age was associated with CHIP (OR 2.0 per decade older, 95% CI 1.3-3.01; p=0.002). Among 166 participants with IMT measurements (CHIP=23), CHIP was not associated with IMT (p=0.21; unchanged after adjustment). Among 80 with FDG-PET, CHIP (n=12) was not associated with arterial inflammation (p=0.89), but was associated with higher lymph node metabolic activity (p=0.03) that was attenuated in reference to background activity and adjusted for risk factors. CHIP was not associated with soluble inflammatory markers or viral persistence markers. ConclusionsAmong PWH, CHIP mutations were not associated with subclinical atherosclerosis, arterial inflammation, or soluble inflammatory markers but were related to hematopoietic activity. The mechanism by which CHIP increases HIV-associated atherosclerosis may preferentially involve lymph nodes and merits additional evaluation.

Current clinical risk stratification for thoracic aortic aneurysms (TAA) relies primarily on maximum diameter, which is a poor predictor of rupture. Recent fluid-structure interaction studies have identified a dimensionless "flutter instability parameter" (N{omega} ) that accurately classifies abnormal aortic growth. However, this parameter currently serves as a static diagnostic snapshot. In this work, we propose a proof-of-concept computational framework that links flutter instability to microstructural tissue damage via a coupled system of ordinary differential equations (ODEs). We model a feedback loop where flutter-induced energy dissipation drives elastin degradation and collagen remodeling, which in turn reduces wall stiffness and amplifies the instability. To address the challenge of unobservable tissue properties, we implement a Bayesian inference engine to infer model parameters. We demonstrate feasibility on a synthetic patient cohort calibrated to published clinical growth rates and diameters. Our results show that this approach can infer hidden damage parameters and capture the qualitative bifurcation between stabilizing remodeling and runaway aneurysm expansion. While validation on real patient data remains essential, this work establishes the mathematical foundation for transforming a static physiomarker into a personalized prognostic trajectory.

BackgroundAtrial cardiopathy is an important cause of embolic stroke and a potential cause of cognitive dysfunction. Increased left atrial volume indexed to body surface area (LAVi) has been widely used as marker for atrial cardiopathy. However, since physiological remodeling may also increase LAVi, it lacks specificity. Left atrial to left ventricular volume (LA:LV) ratio was recently suggested as a better marker of atrial cardiopathy allowing a more accurate detection of imbalanced, pathological atrial remodeling. We investigated if LA:LV ratio is associated with different established sequelae of atrial cardiopathy and if it is superior to LAVi for the detection of atrial fibrillation/flutter (AF) as cause of stroke. MethodsWe compared the association of LAVi and LA:LV ratio with risk of ischemic stroke or transient ischemic attack (TIA) in the population-based UK Biobank cohort (n= 38848), using cause specific hazard models. In addition, we tested for an association with cognitive function using multivariate linear regression models. Finally, we investigated the association of LAVi and LA:LV ratio with probability of atrial fibrillation/flutter being identified as stroke etiology in a cohort of ischemic stroke patients (n = 1273). We compared the test performance of LAVi and LA:LV ratio for identifying atrial fibrillation/flutter as stroke etiology. ResultsWhile LAVi was not significantly associated with risk of ischemic stroke/TIA (HR: 1.11, 95% CI 0.97 - 1.26, p = 0.14), LA:LV ratio was (HR: 1.15, 95% CI 1.01-1.30, p = 0.04). Besides, LA:LV ratio was more strongly associated with worse cognitive function in healthy adults [LA:LV ratio: -0.024 (95% CI (- 0.032) - (- 0.015)), LAVi: - 0.010 (95% CI (- 0.019) - (- 0.002))]. In a stroke patient cohort, LA:LV ratio showed a significantly better performance in identifying AF as underlying cause of ischemic stroke compared to LAVi (Receiver Operating Characteristic Area under the Curve 0.856 (0.803- 0.908) vs. 0.808 (0.750 - 0.866) p = 0.03). ConclusionsWe provide evidence that LA:LV ratio is a promising marker of atrial cardiopathy. Hence, LA:LV ratio has the potential to improve diagnosis of atrial cardiopathy, facilitating prevention of ischemic stroke and maintaining of brain health.