Aims Current risk scores do not accurately identify patients at highest risk of recurrent atherosclerotic cardiovascular disease (ASCVD) in need of more intensive therapeutic interventions. Advances in high-throughput plasma proteomics, analysed with machine learning techniques, may offer new opportunities to further improve risk stratification in these patients. Methods and results Targeted plasma proteomics was performed in two secondary prevention cohorts: the Second Manifestations of ARTerial disease (SMART) cohort (n = 870) and the Athero-Express cohort (n = 700). The primary outcome was recurrent ASCVD (acute myocardial infarction, ischaemic stroke, and cardiovascular death). Machine learning techniques with extreme gradient boosting were used to construct a protein model in the derivation cohort (SMART), which was validated in the Athero-Express cohort and compared with a clinical risk model. Pathway analysis was performed to identify specific pathways in high and low C-reactive protein (CRP) patient subsets. The protein model outperformed the clinical model in both the derivation cohort [area under the curve (AUC): 0.810 vs. 0.750; P < 0.001] and validation cohort (AUC: 0.801 vs. 0.765; P < 0.001), provided significant net reclassification improvement (0.173 in validation cohort) and was well calibrated. In contrast to a clear interleukin-6 signal in high CRP patients, neutrophil-signalling-related proteins were associated with recurrent ASCVD in low CRP patients. Conclusion A proteome-based risk model is superior to a clinical risk model in predicting recurrent ASCVD events. Neutrophil-related pathways were found in low CRP patients, implying the presence of a residual inflammatory risk beyond traditional NLRP3 pathways. The observed net reclassification improvement illustrates the potential of proteomics when incorporated in a tailored therapeutic approach in secondary prevention patients. Key question Does targeted plasma proteomics improve cardiovascular risk prediction in secondary prevention patients? Are different pathways contributing to cardiovascular risk in high and low C-reactive protein (CRP) patients? Key finding Cardiovascular risk prediction with targeted plasma proteomics outperformed prediction with clinical risk factors resulting in major net reclassification improvement. Neutrophil-signalling-related proteins were associated with cardiovascular events in low CRP patients. Take-home message Routine implementation of a targeted protein panel in cardiovascular risk prediction holds promise to improve risk stratification in secondary prevention. The involvement of neutrophil-related pathways in low CRP patients indicates residual inflammatory risk beyond NLRP3.

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Purpose of Review Over the past decades, genetic and observational evidence has positioned lipoprotein(a) as novel important and independent risk factor for cardiovascular disease (ASCVD) and aortic valve stenosis. Recent Findings As Lp(a) levels are determined genetically, lifestyle interventions have no effect on Lp(a)-mediated ASCVD risk. While traditional low-density lipoprotein cholesterol (LDL-C) can now be effectively lowered in the vast majority of patients, current lipid lowering therapies have no clinically relevant Lp(a) lowering effect. Summary There are multiple Lp(a)-directed therapies in clinical development targeting LPA mRNA that have shown to lower Lp(a) plasma levels for up to 90%: pelacarsen, olpasiran, and SLN360. Pelacarsen is currently investigated in a phase 3 cardiovascular outcome trial expected to finish in 2024, while olpasiran is about to proceed to phase 3 and SLN360’s phase 1 outcomes were recently published. If proven efficacious, Lp(a) will soon become the next pathway to target in ASCVD risk management.

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Aim To determine the glucose‐independent effect of the dipeptidyl peptidase‐4 (DPP‐4) inhibitor linagliptin versus the sulphonylurea glimepiride on systemic haemodynamics in the fasting and postprandial state in patients with type 2 diabetes (T2D). Materials and Methods In this prespecified secondary analysis of a phase IV, double‐blind trial, 46 metformin‐treated, overweight patients with T2D were included and randomly assigned (1:1) to once‐daily linagliptin (5 mg) or glimepiride (1 mg) for 8 weeks. In a sub‐study involving 26 patients, systemic haemodynamics were also assessed following a standardized liquid meal (Nutridrink Yoghurt style). Systemic haemodynamics (oscillometric device and finger photoplethysmography), arterial stiffness (applanation tonometry) and cardiac sympathovagal balance (heart rate variability [HRV]) were measured in the fasting state and repetitively following the meal. Ewing tests were performed in the fasting state. Results From baseline to week 8, linagliptin compared with glimepiride did not affect systemic haemodynamics, arterial stiffness or HRV in the fasting state. Linagliptin increased parasympathetic nervous activity, as measured by the Valsalva manoeuvre (P = .021) and deep breathing test (P = .027) compared with glimepiride. Postprandially, systolic blood pressure (SBP) dropped an average of 7.6 ± 1.6 mmHg. Linagliptin reduced this decrease to 0.7 ± 2.3 mmHg, which was significant to glimepiride (P = .010). Conclusions When compared with glimepiride, linagliptin does not affect fasting blood pressure. However, linagliptin blunted the postprandial drop in SBP, which could benefit patients with postprandial hypotension.

Purpose of review Lipid-mediated atherogenesis is hallmarked by a chronic inflammatory state. Low-density lipoprotein cholesterol (LDL-C), triglyceride rich lipoproteins (TRLs), and lipoprotein(a) [Lp(a)] are causally related to atherosclerosis. Within the paradigm of endothelial activation and subendothelial lipid deposition, these lipoproteins induce numerous pro-inflammatory pathways. In this review, we will outline the effects of lipoproteins on systemic inflammatory pathways in atherosclerosis. Recent findings Apolipoprotein B-containing lipoproteins exert a variety of pro-inflammatory effects, ranging from the local artery to systemic immune cell activation. LDL-C, TRLs, and Lp(a) induce endothelial dysfunction with concomitant activation of circulating monocytes through enhanced lipid accumulation. The process of trained immunity of the innate immune system, predominantly induced by LDL-C particles, hallmarks the propagation of the low-grade inflammatory response. In concert, bone marrow activation induces myeloid skewing, further contributing to immune cell mobilization and plaque progression. Summary Lipoproteins and inflammation are intertwined in atherogenesis. Elucidating the inflammatory pathways will provide new opportunities for therapeutic agents.

Neurocognitive impairment (NCI) is an increasingly important comorbidity in an ageing HIV+ population. Despite the lack of available treatment modalities, screening for NCI is recommended. In the UMC Utrecht, yearly NCI screening is done using the Montreal Cognitive Assessment (MoCA) tool and the HIV Dementia Scale (HDS). The aim of this study was to evaluate this screening protocol in relation to clinical outcomes and management. A retrospective cohort study was performed in suppressed adult HIV+ patients. Apart from the MoCa and the HDS, the Utrecht Scale for Evaluation of Rehabilitation-Participation (USER-P) and the Hospital Anxiety and Depression Scale (HADS) were performed. Patients scoring below average on cognitive screening tests or with subjective cognitive complaints were further evaluated using a standardized protocol, including optimizing cART and checking for somatic disorders. In patients with cognitive complaints and participation restrictions, cognitive rehabilitation was proposed. Two hundred eighty-six patients were screened. The vast majority were MSM with an average age of 49 years. One hundred forty-four out of 286 patients (50%) had an abnormal test score and/or had subjective cognitive complaints. Restrictions in participation were present in 23% of patients. Six patients on Efavirenz switched their regimes, as this drug is known for its potential central nervous system (CNS) side effects. A depressive component was present in 58 patients (40%). Five patients had a clinical relevant laboratory abnormality. Moreover, six patients were referred for cognitive rehabilitation, which resulted in a 100% success rate in set goals in the five evaluable patients. Although the protocol was not fully adhered to in all patients, it did result in detectable underlying causes of NCI in 59% of patients, and 21% was referred for further treatment. Moreover, cognitive rehabilitation appears to be a very successful intervention for patients with NCI who experience subjective complaints and participation restrictions.

Given the limited accuracy of clinically used risk scores such as the Systematic COronary Risk Evaluation 2 system and the Second Manifestations of ARTerial disease 2 risk scores, novel risk algorithms determining an individual’s susceptibility of future incident or recurrent atherosclerotic cardiovascular disease (ASCVD) risk are urgently needed. Due to major improvements in assay techniques, multimarker proteomic and lipidomic panels hold the promise to be reliably assessed in a high-throughput routine. Novel machine learning-based approaches have facilitated the use of this high-dimensional data resulting from these analyses for ASCVD risk prediction. More than a dozen of large-scale retrospective studies using different sets of biomarkers and different statistical methods have consistently demonstrated the additive prognostic value of these panels over traditionally used clinical risk scores. Prospective studies are needed to determine the clinical utility of a biomarker panel in clinical ASCVD risk stratification. When combined with the genetic predisposition captured with polygenic risk scores and the actual ASCVD phenotype observed with coronary artery imaging, proteomics and lipidomics can advance understanding of the complex multifactorial causes underlying an individual’s ASCVD risk.