👤 Anders Gummesson

LDL-C and non-HDL-C do not fully capture coronary heart disease (CHD) risk attributed to all apoB-containing lipoproteins. Use of apolipoprotein B (apoB) as a marker of total atherogenic particle number improves risk prediction, but risk may still be underestimated when triglyceride-rich lipoproteins (TRL/remnants) and lipoprotein(a) [Lp(a)] are elevated. The aim was to formulate a new metric-risk-weighted apoB (RW-apoB)-designed to capture risk from LDL, TRL/remnants, and Lp(a) in a single number. Based on previously published estimates of the relative atherogenicity of LDL, TRL/remnant, and Lp(a) particles, RW-apoB was developed (using UK Biobank data) as an atherogenicity-weighted apoB-sum calculated as: RW-apoB = 11.65×TG(mmol/L) + 0.215×lipoprotein(a)(nmol/L) + 0.736×apoB(mg/dL). Assigning RW-apoB to individuals substantially reclassified their risk status. Compared with ranking by measured apoB, 52% of individuals were up- or down-ranked by ≥10 percentiles. About one-third of those in the top RW-apoB quintile-with elevated TRL and Lp(a) and a CHD event rate of 5.4%-were misclassified as lower risk by apoB. Conversely, individuals in the top measured apoB quintile but with low TRL and Lp(a) had a lower event rate (3.9%) and were correctly down-ranked. RW-apoB improved risk prediction, significantly increasing Harrell's C-index relative to apoB (P < .0001). In statin-treated subjects, RW-apoB was potentially a better index of residual risk. RW-apoB consistently outperformed apoB as a risk predictor in Cox models across the UK Biobank and three other large population cohorts. RW-apoB represents not only particle number but also accounts for the higher atherogenicity of TRL and Lp(a). It offers clinically meaningful improvements in CHD risk stratification. Show less

Triglyceride-rich lipoproteins (TRLs) and remnants are established causal risk factors for coronary heart disease (CHD). APOC3 gene-silencing agents reduce TRL/remnant concentrations but the consequent quantitative effect on CHD risk is not yet defined. We used a polygenic score (PGS)-based model to investigate if the degree of TRL/remnant reduction seen on APOC3 silencing would lead to a meaningful reduction in CHD risk. A TRL/remnant-specific PGS was used to select two groups (each >4,150 individuals) from the UK Biobank. CHD event rates were compared between the group with the highest PGS with genetically higher TRL/remnant levels (mimicking placebo) and the group with the lowest PGS with lower levels (mimicking APOC3 silencing). Compared with the high PGS group, the low PGS group had lower plasma triglycerides (-34%), TRL/remnant cholesterol (-22.5%), non-HDL cholesterol (-7.5%) and apolipoprotein B (-6.0%), with a small reduction in LDL cholesterol (-3.9%) and a 15.3% increase in HDL cholesterol. These differences were similar to those seen with APOC3 silencing agents, but with about a third of the absolute effect size. The low PGS group had a 28% lower lifetime CHD event rate (HR = 0.72, 95% CI:0.56-0.91). Extrapolating to a 5-year trial, an APOC3 silencing agent achieving a 16-23 mg/dL decrease in TRL/remnant cholesterol is predicted to reduce CHD risk by approximately 25%. Based on our genetic modelling, the degree of TRL/remnant lowering seen on APOC3 silencing would produce a meaningful CHD risk reduction of around 25 % over a 5-year outcomes trial. Show less

Habitual physical activity (PA) affects metabolism and homeostasis in various tissues and organs. However, detailed knowledge of associations between PA and cardiovascular disease (CVD) risk markers is limited. We sought to identify associations between accelerometer-assessed PA classes and 183 proteomic and 154 metabolomic CVD-related biomarkers. We utilized cross-sectional data from the main SCAPIS cohort (n = 4647, median age: 57.5 yrs, 50.5% female) as a discovery sample and the SCAPIS pilot cohort (n = 910, median age: 57.5 yrs, 50.3% female) as a validation sample. PA was assessed via hip-worn accelerometers, while plasma concentrations of proteomic biomarkers were measured using Olink CVD II and III panels. Metabolomic markers were assessed using the Nightingale NMR platform. We evaluated associations between four PA classes (moderate-to-vigorous PA [MVPA], low-intensity PA [LIPA], sedentary [SED], and prolonged SED [prolSED]) and biomarkers, controlling for potential confounders and applying a false discovery rate of 5% using multiple linear regressions. A total of eighty-five metabolomic markers and forty-three proteomic markers were validated and found to be significantly associated with one or more PA classes. LIPA and SED markers demonstrated significant mirroring or opposing relations to biomarkers, while prolSED mainly shared relations with SED. Notably, HDL species were predominantly negatively associated with SED, whereas LDL species were positively associated with SED and negatively associated with MVPA. Among the proteomic markers, eighteen were uniquely associated with MVPA (among those Interleukin - 6 [IL6] and Growth/differentiation factor 15 [GDF15] both negatively related), seven with SED (among those Metalloproteinase inhibitor 4 [TIMP4] and Tumor necrosis factor receptor 2 [TNFR2], both positively related), and eight were related to both SED/prolSED (among those Lipoprotein lipase [LPL] negatively related to SED and leptin [LEP] positively related to SED) and MVPA (with LPL positively related to MVPA and LEP negatively related to MVPA). Our findings suggest the existence of specific associations between PA classes and metabolomic and cardiovascular protein biomarkers in a middle-aged population. Beyond validation of previous results, we identified new associations. This multitude of connections between PA and CVD-related markers may help elucidate the previously observed relationship between PA and CVD. The identified cross-sectional associations could inform the design of future experimental studies, serving as important outcome measures. Show less

Triglyceride-rich lipoproteins and remnants (TRL/remnants) have a causal, but not yet quantified, relationship with coronary heart disease (CHD): myocardial infarction plus revascularization. The authors sought to estimate TRL/remnant per-particle atherogenicity, investigate causal relationships with inflammation, and determine whether differences in the atherogenicity of TRL/remnants and low-density lipoprotein (LDL) impact the causal association of non-high-density lipoprotein cholesterol (non-HDL-C) with CHD. Single nucleotide polymorphisms (SNPs) (N = 1,357) identified by genome-wide association in the UK Biobank were ranked into 10 clusters according to the effect on TRL/remnant-C vs LDL-C. Mendelian randomization analysis was used to estimate for each SNP cluster CHD ORs per 10 mg/dL apolipoprotein B (apoB) and per 0.33 mmol/L non-HDL-cholesterol, and to evaluate association of TRL/remnants with biomarkers of systemic inflammation. SNPs in cluster 1 predominantly affected LDL-C, whereas SNPs in cluster 10 predominantly affected TRL/remnant-C. CHD risk per genetically predicted increase in apoB and in non-HDL-C rose across clusters. ORs per 10 mg/dL higher apoB was 1.15 (95% CI: 1.11-1.19) in cluster 1 vs 1.70 (95% CI: 1.52-1.90) in cluster 10. Comparing ORs between these TRL/remnant-predominant and LDL-predominant clusters, we estimated that TRL/remnants were at least 3.9 (95% CI: 2.8-5.4) times more atherogenic than LDL on a per-particle basis. For non-HDL-C, CHD ORs per 0.33 mmol/L rose from 1.15 (95% CI: 1.11-1.19) for cluster 1 to 1.40 (95% CI: 1.30-1.50) for cluster 10. TRL/remnants exhibited causal relationships with inflammation, but this did not explain their greater atherogenicity. TRL/remnants are about 4 times more atherogenic than LDL. Variation in the causal association of non-HDL-C with CHD indicates that adjustment for percentage TRL/remnant-C may be needed for accurate risk prediction. Show less