| Literature DB >> 30258647 |
Thor Ueland1,2,3, Ola Kleveland4,5, Annika E Michelsen1,2, Rune Wiseth4,5, Jan Kristian Damås6, Pål Aukrust1,2,7, Lars Gullestad2,8,9, Bente Halvorsen1,2, Arne Yndestad1,2,9.
Abstract
Objective: It is unclear if activation of inflammatory pathways regulates proprotein convertase subtilisin-kexin type 9 (PCSK9) levels. Approach: We evaluated (1) the temporal course of serum PCSK9 during hospitalisation following acute coronary syndrome and associations with markers of inflammation (leucocyte counts, interleukin (IL)-6, C-reactive protein) and lipid levels and (2) the effect of inhibition of IL-6 signalling with the IL-6 receptor antibody tocilizumab on PCSK9 levels in a randomised, double-blind, placebo-controlled trial release in patients with non-ST-elevation myocardial infarction.Entities:
Keywords: PCSK9; acute coronary syndrome; anti-IL6 therapy; inflammation
Year: 2018 PMID: 30258647 PMCID: PMC6150185 DOI: 10.1136/openhrt-2017-000765
Source DB: PubMed Journal: Open Heart ISSN: 2053-3624
Figure 1Tukey plot of serum proprotein convertase subtilisin-kexin type 9 (PCSK9) in healthy controls (CTR; n=27) and patients with non-ST-elevation myocardial infarction (NSTEMI; n=117) on admission. P values are adjusted for age and body mass index (BMI).
Baseline characteristics according to treatment group and association with PCSK9
| Placebo | Tocilizumab | Between groups | PCSK9† | PCSK9‡ | |
| Age (years) | 60.1±9.9 | 59.8±7.7 | 0.859 | −0.03 | −0.16 |
| Female gender | 5 (8.5%) | 9 (15.5%) | 0.364 | 0.02 | 0.00 |
| BMI (kg/m2) | 27.4±4.4 | 28.8±3.3 | 0.055 | −0.08 | 0.25* |
| Hypertension | 17 (28.8%) | 26 (44.8%) | 0.109 | −0.09 | 0.07 |
| Hypercholesterolaemia | 13 (22.0%) | 17 (29.3%) | 0.491 | 0.06 | 0.15 |
| Diabetes type 2 | 10 (16.9%) | 10 (17.2%) | 1.0 | −0.06 | 0.01 |
| Smoking (previous or current) | 40 (67.8 %) | 35 (61.4%) | 0.599 | 0.06 | 0.08 |
| Heart rate (beats/min) | 66±13 | 66±10 | 0.770 | −0.08 | 0.02 |
| SBP (mm Hg) | 137±18 | 140±18 | 0.389 | −0.06 | 0.02 |
| DBP (mm Hg) | 81±12 | 83±12 | 0.273 | −0.05 | 0.08 |
| PCI | 47 (79.7%) | 41 (70.7%) | 0.367 | −0.04 | 0.02 |
| CABG | 7 (11.9%) | 6 (10.3%) | 1.0 | 0.00 | 0.12 |
| Medical treatment | 5 (8.5%) | 11 (19.0%) | 0.167 | 0.05 | −0.14 |
| GRACE score | 92 (75, 105) | 86 (72, 97) | 0.168 | 0.00 | −0.16 |
| Biochemistry | |||||
| Creatinine (µmol/L) | 76 (69, 90) | 76 (66, 83) | 0.260 | −0.10 | 0.02 |
| Leucocytes (×109/L) | 7.3 (5.9, 9.2) | 7.9 (5.9, 9.3) | 0.406 | 0.12 | 0.02 |
| Neutrophils (×109/L) | 4.5 (3.4, 6.0) | 5.1 (3.4, 6.3) | 0.471 | 0.08 | 0.04 |
| Interleukin-6 (pg/mL) | 2.2 (1.1, 4.6) | 2.7 (1.2, 8.7) | 0.185 | 0.02 | −0.10 |
| C-reactive protein (mg/L) | 2.5 (1.0, 8.3) | 2.7 (1.5, 4.7) | 0.458 | 0.02 | 0.01 |
| Troponin T (ng/L) | 192 (71, 571) | 128 (53, 749) | 0.965 | 0.05 | 0.05 |
| Total cholesterol (mmol/L) | 5.3 (4.5, 5.9) | 4.9 (4.2, 5.7) | 0.279 | −0.02 | 0.10 |
| LDL cholesterol (mmol/L) | 3.2 (2.8, 3.8) | 3.0 (2.3, 3.6) | 0.149 | −0.09 | 0.09 |
| Medication at baseline | |||||
| Aspirin | 59 (100%) | 57 (98.3%) | 0.496 | 0.04 | 0.06 |
| Clopidogrel | 32 (54.2%) | 32 (55.2%) | 1.0 | −0.02 | −0.06 |
| Ticagrelor | 27 (45.8%) | 26 (44.8%) | 1.0 | 0.02 | 0.06 |
| Low molecular weight heparin | 54 (91.5%) | 51 (89.5%) | 0.952 | 0.01 | −0.03 |
| Beta blocker | 45 (76.3%) | 45 (77.6%) | 1.0 | −0.05 | −0.05 |
| Statin | 53 (89.8%) | 53 (91.4%) | 1.0 | 0.14 | – |
*P<0.01.
†Spearman correlation.
‡Partial correlation adjusting for statin use. Categorical data are given as n (%). Continuous data are expressed as mean±SD or median (25th, 75th percentiles) and were compared with unpaired parametric or non-parametric tests depending on distribution.
BMI, body mass index; CABG, coronary artery bypass grafting; DBP, diastolic blood pressure; GRACE, Global Registry of Acute Coronary Events; LDL, low-density lipoprotein; PCI, percutaneous coronary intervention; PCSK9, proprotein convertase subtilisin-kexin type 9; SBP, systolic blood pressure.
Figure 2Serum PCSK9 in patients with non-ST-elevation myocardial infarction (NSTEMI) receiving placebo (n=59) or tocilizumab (n=58) during hospitalisation and at 3 and 6 months of follow-up. Circles represent geometric back-transformed estimated marginal means and 95% CIs, respectively. *P<0.05; **P<0.01; ***P<0.001 versus baseline (BL). The grey area and line represent the geometric mean and 95% CI for healthy controls. AFN, afternoon; ANOVA, analysis of variance; EVE, evening; MO, morning; PCSK9, proprotein convertase subtilisin-kexin type 9.
Figure 3Serum PCSK9 during hospitalisation in non-ST-elevation myocardial infarction (NSTEMI) stratified by hypercholesterolaemia. (A) Comparison of AUC during hospitalisation for PCSK9 in groups stratified by treatment and presence of hypercholesterolaemia (HC). Boxes represent median and 25th and 75th percentiles. (B) Serum PCSK9 during hospitalisation stratified by treatment and hypercholesterolaemia. The p values in (B) represent the group effects from the repeated measures analysis of variance (ANOVA). Circles represent geometric back-transformed estimated marginal means 95% CIs. AFN, afternoon; AUC, area under the curve; BL, baseline; EVE, evening; MO, morning; PCSK9, proprotein convertase subtilisin-kexin type 9.
Figure 4Correlation between AUC during hospitalisation for neutrophils and PCSK9 stratified by absence (top panel) or presence (bottom panel) of hypercholesterolaemia and treatment (clear circles, placebo; filled circles, tocilizumab). Correlation coefficients within each stratification group are given and p value when significant. The small graph in each panel shows the average white cell count within each stratification group according to treatment during hospitalisation. AUC, area under the curve; BL, baseline; PCSK9, proprotein convertase subtilisin-kexin type 9.