Additive Effects of Genetic Interleukin-6 Signaling Downregulation and Low-Density Lipoprotein Cholesterol Lowering on Cardiovascular Disease: A 2×2 Factorial Mendelian Randomization Analysis.

Background Although trials suggest that anti-inflammatory approaches targeting interleukin (IL)-6 signaling can reduce cardiovascular risk, it remains unknown whether targeting IL-6 signaling could reduce risk additively to low-density lipoprotein cholesterol (LDL-C) lowering. Here, we assess interactions in associations of genetic downregulation of IL-6 signaling and LDL-C lowering with lifetime cardiovascular disease risk. Methods and Results Genetic scores for IL-6 signaling downregulation and LDL-C lowering were used to divide 408 225 White British individuals in UK Biobank into groups of lifelong exposure to downregulated IL-6 signaling, lower LDL-C, or both. Associations with risk of cardiovascular disease (coronary artery disease, ischemic stroke, peripheral artery disease, aortic aneurysm, vascular death) were explored in factorial Mendelian randomization. Compared with individuals with genetic IL-6 and LDL-C scores above the median, individuals with LDL-C scores lower than the median but IL-6 scores above the median had an odds ratio (OR) of 0.96 (95% CI, 0.93-0.98) for cardiovascular disease. A similar OR (0.96; 95% CI, 0.93-0.98) was estimated for individuals with genetic IL-6 scores below the median but LDL-C scores above the median. Individuals with both genetic scores lower than the median were at lower odds of cardiovascular disease (OR, 0.92; 95% CI, 0.90-0.95). There was no interaction between the 2 scores (relative excess risk attributed to interaction index, 0; synergy index, 1; P for multiplicative interaction=0.51). Genetic IL-6 score below the median was associated with lower cardiovascular disease risk across measured LDL-C strata (<100 or ≥100 mg/dL). Conclusions Genetically downregulated IL-6 signaling and genetically lowered LDL-C are associated with additively lower lifetime risk of cardiovascular disease. Future trials should explore combined IL-6 inhibition and LDL-C lowering treatments for cardiovascular prevention.

Accumulating evidence supports the fact that targeting inflammation can offer benefits in atherosclerosis independently of lipid‐lowering approaches. First, the Canakinumab Anti‐Inflammatory Thrombosis Outcome Study (CANTOS), Colchicine Cardiovascular Outcomes Trial (COLCOT), and Low‐Dose Colchicine 2 (LoDoCo2) trials showed that anti‐inflammatory approaches directly or indirectly targeting upstream regulators of interleukin (IL)‐6 signaling can lower cardiovascular risk without affecting low‐density lipoprotein cholesterol (LDL‐C) levels. Second, Mendelian randomization analyses showed genetic downregulation of IL‐6 signaling to be associated with a lower risk of vascular events , and a more favorable cardiometabolic profile, but not LDL‐C levels. Third, even at very low LDL‐C, high CRP (C‐reactive protein) levels—a marker of IL‐6 signaling activation—predict vascular events, thus suggesting the presence of residual inflammatory risk beyond cholesterol lowering. These results have motivated efforts aiming to directly interfere with the IL‐6 signaling cascade in patients with cardiovascular disease, which are already at the phase of clinical testing with promising results.

Yet, it remains unknown whether there would be any interaction between lipid‐lowering and anti‐inflammatory strategies regarding the effects of IL‐6‐targeting and LDL‐C‐lowering approaches on cardiovascular risk. The Pravastatin Inflammation/CRP Evaluation (PRINCE) and Justification for the Use of Statin in Prevention: An Intervention Trial Evaluating Rosuvastatin (JUPITER) trials have shown that statins also reduce CRP levels beyond the expected reductions in LDL‐C levels and this effect has been associated with additional reductions in vascular event rates. Conversely, tocilizumab, a monoclonal antibody targeting the IL‐6 receptor (IL‐6R), has been shown to elevate circulating cholesterol levels. Thus, it is not clear whether aggressive targeting of both lipid accumulation and inflammation to minimize residual risk would offer additive benefits in patients with atherosclerosis. To test such a hypothesis, a 2×2 factorial trial design has been proposed that would test the efficacy of a combination therapy of IL‐6 signaling inhibition and LDL‐C lowering.

Here, we use large‐scale data to test whether there is genetic support for this hypothesis before investing in a clinical trial. Specifically, we used a 2×2 factorial Mendelian randomization study design to compare the associations of (1) downregulated IL‐6 signaling attributed to variation in the gene‐encoding IL‐6R, (2) lower LDL‐C levels as a result of variation in genes encoding lipid‐lowering drug targets (PCSK9 [proprotein convertase subtilisin/kexin type 9] inhibitors, statins, ezetimibe), or (3) both with the lifetime risk of cardiovascular disease. Evidence of an interaction between genetically predicted LDL‐C levels and genetically predicted IL‐6 signaling activity, and specifically an attenuation of the effect of the latter in genetically lowered LDL‐C levels, would indicate a relevance of the IL‐6 signaling pathway only under high LDL‐C levels. We hypothesized that genetically regulated IL‐6 signaling and genetically predicted LDL‐C levels are additively associated with the lifetime risk of cardiovascular disease and as such might represent independent targets for lowering residual cardiovascular risk.

METHODS

The data used in these analyses are available from the UK Biobank (UKB) upon approval of a submitted research proposal. The UKB has institutional review board approval from the Northwest Multi‐Center Research Ethics Committee. All participants provided written informed consent. We accessed the data following approval of an application by the UKB Ethics and Governance Council (Application No. 2532). The genetic variants used to generate the genetic risk scores for the presented analyses are available in Data S1. A detailed description of the methods is provided in Data S1.

We performed this analysis in 408 225 unrelated White British individuals from the UKB, a population‐based study of individuals aged 40 to 69 years. To construct a score for IL6 signaling downregulation (IL‐6 score), we selected variants within 300 kB of the IL6R gene that were associated at P<5×10−8 (r 2<0.1) with CRP, a downstream biomarker of IL6 signaling, in a meta‐analysis of 522 681 European individuals from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium and UKB. To avoid bias due to winner’s curse, we weighed the score solely on the basis of the effects of the identified genetic variants on CRP levels in the CHARGE Consortium (and not in the meta‐analysis with UKB). Also, in sensitivity analyses, we restricted our selection to variants strictly selected on the basis of the CHARGE data, as previously described. For validation, we explored associations with IL6, soluble IL6R, and fibrinogen levels (please see Data S1 for a description of the sample). To construct a genetic score for LDL‐C lowering through currently used drug targets (LDL‐C score), we selected genetic variants associated with LDL‐C at P<5×10−8 (clumped at r 2<0.1) and located within 300 kB of the genes encoding the drug targets for PCSK9 inhibitors, statins, and ezetimibe (PCSK9, HMGCR, NPC1L1) in a meta‐analysis of 504 943 European individuals from the Global Lipids Genetics Consortium (GLGC) Consortium and UKB. To avoid bias attributed to winner’s curse, we weighed the score solely on the basis of the effects of the identified genetic variants on LDL‐C levels in the GLGC Consortium (and not in the meta‐analysis with UKB). Also, in sensitivity analyses, we restricted our selection to variants strictly selected on the basis of the GLGC data, as previously described. For validation, we explored associations with apolipoprotein B levels and cholesterol levels across LDL particles (please see Data S1 for a description of the sample).

The primary combined outcome included coronary artery disease, ischemic stroke, peripheral artery disease, aortic aneurysm, and cardiovascular death (Table S1). Secondary outcomes included the 5 individual outcomes. In the primary analysis, we combined prevalent and incident cases, whereas in sensitivity analyses, we explored associations with time‐to‐incident events among individuals free of cardiovascular disease at baseline. We performed 2×2 factorial Mendelian randomization analysis, splitting our sample to 4 groups based on the IL6 and LDL‐C scores, as depicted in Figure 1. Although this 2×2 method based on dichotomization might arbitrarily group participants across different levels of IL6 and LDL‐C genetic scores, it provides sufficient power to meaningfully test interactions and is also offering estimates that are easier to interpret in the clinical setting. To avoid biased estimates attributed to arbitrary dichotomization and to maximize power, we also analyzed the 2 scores as quantitative traits, also exploring their interaction. Furthermore, we explored the associations of the each score as a quantitative continuous variable with cardiovascular outcomes across deciles of the other. We explored associations with the primary and secondary outcomes in logistic regression models. Our models were adjusted for age, sex, the first 10 principal components of population structure, and the array used for genotyping (UK Biobank Lung Exome Variant Evaluation Axiom array or UKB Axiom array).

Figure 1

Study design of the 2×2 Mendelian randomization analysis in the UK Biobank (UKB).

Participants were divided into 4 groups according to their genetic risk scores for interleukin (IL)‐6 signaling and low‐density lipoprotein cholesterol (LDL‐C). CRP indicates C‐reactive protein.

RESULTS

We identified 26 variants in the IL6R gene as genetic proxies for IL‐6 signaling downregulation (Table S2) and 36 variants as proxies for LDL‐C lowering (17 in the PCSK9, 15 in the HMGCR, 4 in the NPC1L1 locus; Table S3). The genetic IL‐6 score was associated with lower levels of fibrinogen and higher levels of IL‐6 and soluble IL‐6R (Figure S1), whereas the genetic LDL‐C score was associated with lower apolipoprotein B and lower levels of cholesterol in all LDL particles (Figure S2). In the UKB, the genetic IL‐6 score was strongly associated with CRP levels, but not LDL‐C levels, and the genetic LDL‐C score was strongly associated with LDL‐C, but not CRP levels (Figure S3). There was no correlation between the 2 scores (Spearman ρ=0.0016).

The baseline characteristics of the 4 groups are presented in Table S4. There was no statistically significant difference with regard to age, sex, body mass index, blood pressure, or smoking status between the 4 groups. CRP levels were significantly lower in individuals with a mean genetic IL‐6 score lower than the median (mean 2.75±4.54 versus 2.47±4.23 mg/L), whereas LDL‐C levels were lower among individuals with a median genetic LDL‐C score below the median (mean 139.5±34.4 versus 136.0±33.4 mg/L; Figure 1). Furthermore, individuals with median genetic LDL‐C score below the median had lower apolipoprotein B levels, whereas individuals with median genetic IL‐6 scores below the median had slightly higher HDL‐C and apolipoprotein A1 levels, as well as lower hemoglobin A1c, as has been previously described.

In the 2×2 factorial Mendelian randomization analysis, both a lower genetic IL‐6 score and a lower genetic LDL‐C score were associated with a lower risk of cardiovascular disease, whereas scoring less than the median in both scores showed an approximately log‐additive lower risk (Figure 2). Specifically, when scaled to 50% decrement in CRP levels (0.5 log‐decrement in log‐transformed CRP levels), a lower genetic IL‐6 score was associated with 33% lower odds for cardiovascular disease (odds ratio [OR], 0.67; 95% CI, 0.50–0.90), whereas a lower genetic LDL‐C score scaled to a 38.67 mg/dL decrement in LDL‐C levels was associated with 45% lower odds for cardiovascular disease (OR, 0.55; 95% CI, 0.40–0.77); a combined exposure showed an OR of 0.43 (95% CI, 0.31–0.59; Figure 2). This corresponded to a relative excess risk attributed to interaction index of 0 and a synergy index of 1 indicating an absolute lack of additive interaction. In the continuous analysis, both scores were also independently associated with a lower risk of cardiovascular disease, with no evidence of multiplicative interaction between the 2 scores (Figure 2), and the results were consistent when splitting the sample in deciles of the genetic LDL‐C and IL‐6 scores (Figure S4). Furthermore, to avoid bias attributed to arbitrary dichotomization of the genetic scores and to explore the impact of potentially hidden nonlinear effects on the examined interaction, we then tested in spline models the association between the 2 genetic scores with the risk of cardiovascular disease. There was no evidence for nonlinear effects (Figure S5). Introducing an interaction term between the 2 spline factors to the model (4×4 equally split splines of each genetic score) to explore if potential nonlinearities in the associations of the 2 variables with cardiovascular outcome cloud any interaction, we again found no significant interaction across any of the 16 interaction terms.

Figure 2

Independent associations between genetic scores for IL‐6 signaling and LDL‐C with risk of cardiovascular disease.

A, Nonscaled associations. B, Associations scaled to 38.67 mg/dL (1 mmol/L) decrement in LDL‐C levels and 0.50 log(mg/L) decrement in log‐transformed C‐reactive protein levels. The upper panels of (A and B) represent associations from the 2×2 analysis dividing participants into 4 groups according to the median genetic IL‐6 and LDL‐C scores. The lower panels of (A and B) represent associations from an analysis where the 2 genetic scores were included on a continuous scale as well as the interaction between the 2 scores. The results are derived from logistic regression models adjusted for age, sex, the first 10 principal components of population structure, and the genotyping array. IL6 indicates interleukin‐6; LDL‐C, low‐density lipoprotein cholesterol; and OR, odds ratio.

In sensitivity analyses restricted to incident cardiovascular events, as well as when excluding individuals on lipid‐lowering treatments at baseline, the results were stable (Table S5). Furthermore, the results were similar in sensitivity analyses of genetic scores from variants strictly selected on the basis of the CHARGE and GLGC Consortium data (Table S6). Directionally consistent and significant results were similarly obtained for the individual end points including coronary artery disease, peripheral artery disease, aortic aneurysm, and vascular death, but not ischemic stroke (Figure 3).

Figure 3

Independent associations between genetic scores for IL‐6 signaling and LDL‐cholesterol with risk of individual cardiovascular outcomes.

The results represent associations from the 2×2 analysis dividing participants into 4 groups according to the median genetic IL‐6 and LDL‐C scores. The results are derived from logistic regression models adjusted for age, sex, the first 10 principal components of population structure, and the genotyping array. *ORs are scaled to 38.67 mg/dL (1 mmol/L) decrement in LDL‐C levels and 0.5 log(mg/L) decrement in log‐transformed C‐reactive protein levels. IL6 indicates interleukin‐6; LDL‐C, low‐density lipoprotein cholesterol; and OR, odds ratio.

To explore whether the effects of the IL‐6 score were also independent of measured LDL‐C levels, we examined associations with incident cardiovascular events among individuals with baseline LDL‐C levels <100 and ≥100 mg/dL stratified by the intake of lipid‐lowering medications at baseline. Interestingly, there was no evidence of differential effects by LDL‐C levels or use of lipid‐lowering treatment at baseline (Figure S6).

DISCUSSION

Among 408 225 community‐based individuals, genetically downregulated IL‐6 signaling was associated with a lower risk of cardiovascular events additively to genetically lowered and measured LDL‐C levels. Although several trials support the fact that targeting IL‐6 signaling could reduce vascular risk, it remains unknown whether a combined treatment of LDL‐C‐lowering and IL‐6‐signaling inhibition would offer additive reductions in risk. Our results provide genetic support that targeting residual inflammatory risk and residual cholesterol risk could indeed offer additive benefits in patients with atherosclerosis.

Although several trials now support the fact that targeting the inflammasome–IL‐1β–IL‐6 axis could lower vascular risk among patients with myocardial infarction, post hoc analyses from the CANTOS trial support the concept that there remains substantial residual inflammatory risk related to IL‐6 after interventions targeting upstream regulators of IL‐6, thus indicating that targeting IL‐6 signaling directly could be a more effective approach than targeting upstream molecules in the pathway. Our results support this notion and further expand these findings by showing that targeting IL‐6 signaling by blocking IL‐6R could reduce cardiovascular risk additively to current lipid‐lowering approaches. Beyond genetically determined lipid levels, in an analysis of actually measured LDL‐C levels, we were able to show that even among individuals with relatively low LDL‐C levels (<100 mg/dL) either on or off lipid‐lowering treatments, genetically downregulated IL‐6 signaling is still associated with a lower risk of vascular events. Cumulatively, these results provide support that a combined strategy of lowering LDL‐C and inflammation could offer additive benefits in lowering cardiovascular risk and as such should be tested in the future in a 2×2 factorial clinical trial.

We found that genetically downregulated IL‐6 signaling is consistently associated with lower risk beyond lipid lowering for a number of vascular end points including coronary artery disease, peripheral artery disease, aortic aneurysm, and vascular death, thus supporting the utility of the approach for lowering vascular events in general. Still, there were differences in the effect sizes across different end points. For example, we found a particularly strong association between the genetic IL‐6 score and aortic aneurysm in accord with previous reports. IL‐6 signaling might contribute to the formation of aortic aneurysms through mechanisms aside from atherosclerosis, thus explaining the large effect. For instance, IL‐6 signaling is a key pathway in the pathogenesis of giant cell arteritis, which are strongly associated with the formation of aortic aneurysms. In contrast, and in opposition to our previous findings, we found no significant association of genetic IL‐6 signaling downregulation with ischemic stroke. Although the direction of the association was consistent with other end points, the lack of a significant effect might relate to limited power or to the heterogeneous nature of ischemic stroke. Atherosclerosis accounts for only about 30% of the cases, and because the UKB does not have data on stroke subtypes, we could not perform analyses by stroke etiology.

Our study has limitations. First, we did not explore the effects of medications but, rather, the effects of the lifetime changes as a result of genetic variation in the targets of IL‐6R inhibitors and lipid‐lowering treatments, which might differ from those of a short‐acting treatment on vascular events. Second, the results from the current analysis reflect the effects of IL‐6 signaling on incident vascular events and might thus not be applicable for secondary prevention. Third, our results reflect the effects of genetic downregulation of IL‐6 signaling attributed to variations in the IL6R gene and may thus differ from other approaches targeting other molecules upstream to IL‐6. Still, post hoc analyses from the CANTOS and Cardiovascular Inflammation Reduction Trial (CIRT) support the fact that there is residual inflammatory risk that is explained by posttreatment IL‐6 levels, thus providing indirect evidence that targeting IL‐6 directly might be the optimal strategy. Fourth, as we selected variants on genes encoding the primary targets of available lipid‐lowering drugs, our results cannot inform on potential off‐target pleiotropic effects of statins, other lipid‐lowering medications, or IL‐6R‐targeting monoclonal antibodies.

In conclusion, lifelong genetic exposure to IL‐6 signaling downregulation is associated with lower cardiovascular risk additively to the genetic lowering of LDL‐C levels through variation in genes encoding standard LDL‐C‐lowering treatments. These results suggest that inhibition of IL‐6 signaling on top of LDL lowering could lead to further reductions in vascular risk and should be tested in clinical trials of patients with atherosclerosis.

Sources of Funding

Dr Georgakis is supported by a Walter Benjamin Fellowship by the German Research Foundation (Deutsche Forschungsgemeinschaft [DFG], GE 3461/1‐1). This project has received funding from the European Union’s Horizon 2020 research and innovation program (666881), SVDs@target (to Dr Dichgans; 667375), Common mechanisms and pathways in stroke and Alzheimer's disease (CoSTREAM) (to Dr Dichgans), the DFG as part of the Munich Cluster for Systems Neurology (EXC 2145 SyNergy—ID 390857198) and the Collaborative Research Centre (CRC) 1123 (B3; to Dr Dichgans), the Corona Foundation (to Dr Dichgans), the Fondation Leducq (Transatlantic Network of Excellence on the Pathogenesis of Small Vessel Disease of the Brain; to Dr Dichgans), the e:Med Program (e:AtheroSysMed; to Dr Dichgans), and the FP7/2007‐2103 European Union Project CVgenes@target (Grant No. Health‐F2‐2013‐601456; to Dr Dichgans). Dr Burgess is supported by a Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (Grant No. 204623/Z/16/Z).

Disclosures

None.

Data S1

Tables S1–S6

Figures S1–S6

References 4, 5, 11, 12, 13, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26

Click here for additional data file.