Common variants in OSMR contribute to carotid plaque vulnerability Short Title Common variants in OSMR and plaque vulnerability AUTHORS

BackgroundOncostatin M (OSM) signaling is implicated in atherosclerosis, however the mechanism remains unclear. We investigated the impact of common genetic variants in OSM and its receptors, OSMR and LIFR, on overall plaque vulnerability (based on macrophage, collagen, smooth muscle cell and fat content) and on seven individual atherosclerotic plaque phenotypes (calcification, collagen, atheroma size, macrophages, smooth muscle cells, vessel density and intraplaque hemorrhage).nnMethods and resultsWe queried Genotype-Tissue Expression (GTEx) data and selected one variant, rs13168867 (C allele), that associated with decreased OSMR expression and one variant, rs10491509 (A allele), that associated with increased LIFR expression in arterial tissue. No variant was associated to significantly altered OSM expression.nnWe associated these two variants with plaque characteristics from 1,443 genotyped carotid endarterectomy patients in the Athero-Express Biobank Study. The rs13168867 variant in OSMR was significantly associated with an increased overall plaque vulnerability ({beta} = 0.118 {+/-} s.e. = 0.040, p = 3.00x2-3, C allele). With respect to different plaque phenotypes, this variant showed strongest associations with intraplaque fat ({beta} = 0.248 {+/-} s.e. = 0.088, p = 4.66x2-3, C allele) and collagen content ({beta} = -0.259 {+/-} s.e. = 0.095, p = 6.22x2-3, C allele). No associations were found for rs10491509 in the LIFR locus.nnConclusionOur study suggests that genetically decreased arterial OSMR expression, possibly resulting in decreased OSM signaling, contributes to increased carotid plaque vulnerability.


Introduction
Oncostatin M (OSM) is an inflammatory cytokine 1 that is released by activated monocytes 2 , macrophages 2 , T-lymphocytes 3 and neutrophils 4 , and mediates its effects through binding to either the glycoprotein (gp) 130/ oncostatin M receptor (OSMR) heterodimer or the gp130/ leukemia inhibitory factor receptor (LIFR) heterodimer [5][6][7] . Binding of OSM to either of the receptor heterodimers can activate multiple pathways, including the janus kinase (JAK)/ signal transduction and activator of transcription (STAT), the mitogen-activated protein kinase (MAPK), and the Phosphoinositide 3-kinase (PI3K)/AKT pathway 6 . It is suggested that the ratio of the two receptor types expressed on the cell membrane is a potential regulatory mechanism for the multiple and sometimes opposing effects that are exerted by OSM 8 . The cytokine is associated to multiple inflammatory diseases, including chronic periodontitis 5,9 , rheumatoid arthritis 10 and inflammatory bowel disease 11 .
There are multiple indications, that OSM is involved in atherosclerosis. OSM is present in both murine and human atherosclerotic plaques 12 and OSMR -/-ApoE -/mice show reduced plaque size and improved plaque stability compared to their OSMR expressing littermates 13 , indicating that OSM drives atherosclerosis development. To our knowledge, no studies have been performed to investigate the involvement of LIFR in OSM driven atherosclerosis development. However, we previously showed that OSM signals through both receptors simultaneously to induce activation in human endothelial cells, suggesting that also LIFR is involved in atherosclerosis development 14 .
Little is known about the effect of OSM on plaque composition. Since OSM affects multiple cell types and processes, it is difficult to predict how OSM contributes to atherosclerotic plaque formation. As OSM promotes angiogenesis 15 , endothelial activation 14 , vessel permeability 16 and osteoblastic differentiation 17 , it hypothetically results in a higher intraplaque microvessel density and intraplaque hemorrhages and plaque calcification, thereby contributing to the formation of a vulnerable plaque 18,19 . On the other hand, OSM also promotes fibroblast proliferation 20 , collagen formation 20 , smooth muscle cell proliferation 12 and M2 macrophage polarization 21 , hypothetically resulting in enhanced fibrosis and attenuates inflammation, thereby contributing to plaque stabilization [22][23][24] .
We aimed to investigate these theorized opposing effects of OSM signaling on the atherosclerotic plaque using data from the Athero-Express Biobank Study, which comprises a large collection of human plaque specimens obtained through carotid endarterectomy 25 . Common genetic variation in gene expression is key to disease susceptibility, and cis-acting genetic variants, single-nucleotide polymorphisms (SNPs), have been mapped to expression quantitative trait loci (eQTLs) 26 . Likewise, eQTLs modulate transcriptional regulation of OSM, OSMR, and LIFR in arterial tissues. We hypothesized that eQTLs for these genes, can be used as proxies of gene expression to examine the effect on overall plaque vulnerability 27 and individual plaque characteristics, including collagen, lipid, macrophage and smooth muscle cell content, calcification, and intraplaque microvessel density and hemorrhage.

Sample collection
The Athero-Express Biobank Study (https://www.atheroexpress.nl) contains plaque material of patients that underwent carotid endarterectomy (CEA) or femoral endarterectomy at two Dutch tertiary referral centers 25 . Details of the study design were described before. Briefly, blood and plaque material were obtained during endarterectomy and stored at -80℃. Only CEA patients were included in the present study. All patients provided informed consent and the study was approved by the medical ethics committee.

Athero-Express genotyping, quality control, and imputation
Details of genotyping have been previously described 28

Variant selection
We queried data from the Genotype-Tissue Expression (GTEx) Portal (https://gtexportal.org) 26 for variants that alter OSM expression in the blood, and OSMR or LIFR expression in arterial tissue. We selected common variants with a MAF >3%, which yielded 2 variants in total. We harmonized the effect alleles and effect sizes from these eQTLs to the Athero-Express Biobank Study data.

Plaque phenotyping
The (immuno)histochemical analyses of plaque phenotypes have been described previously 25,28,32 . Briefly, the culprit lesion was identified directly after dissection, fixed in 4% formaldehyde and embedded in paraffin. The tissue was cut in 5µm sections on a cryotome for (immuno)histochemical analysis by pathology experts. Calcification (hematoxylin & eosin, H&E) and collagen content (picrosirius red) were semi-quantitatively scored and defined as no/minor or moderate/heavy. Atheroma size (H&E and picrosirius red) was defined as <10% or ≥10% fat content. The amount of macrophages (CD68) and smooth muscle cells (ACTA2) were quantitatively scored and classified as percentage of plaque area. The presence of intraplaque hemorrhage (H&E and fibrin) was defined as absent or present, and vessel density was classified as the number of intraplaque vessels (CD34)/ hotspot.

Plaque vulnerability
Assessment of overall plaque vulnerability was performed as previously described 27 . In short, the amount of macrophages and smooth muscle cells were also semi-quantitatively defined as no/minor or moderate/heavy. Each plaque characteristic that defines a stable plaque (i.e. no/minor macrophages, moderate/heavy collagen, moderate/heavy smooth muscle cells and <10% fat) was given a score of 0, while each plaque characteristic that defines a vulnerable plaque (i.e. moderate/heavy macrophages, no/minor collagen, no/minor smooth muscle cells and ≥10% fat) was given a score of 1. The score of each plaque characteristic was summed resulting in a final plaque score ranging from 0 (most stable plaque) to 4 (most vulnerable plaque). Intraobserver and interobserver variability were examined previously and showed good concordance (κ 0.6-0.9) 33 .

Statistical analyses
Quantitatively scored characteristics (macrophages, smooth muscle cells, and the vessel density) were Box-Cox transformed 34 to obtain a normal distribution. Association of the common variants with continuous parameters were statistically tested with linear regression and the categorical parameters with logistic regression. Data was corrected for age, sex, genotyping chip, and genetic ancestry using principal components 1 through 4.

Baseline characteristics
A total of 1,443 patients that underwent carotid endarterectomy were genotyped and included in this study. The genotyped groups (AEGS1 and AEGS2) are not overlapping. As we previously showed that the baseline characteristics of both groups are comparable 28 , the groups were combined for overall plaque vulnerability and phenotype analyses.
Baseline characteristics of the combined groups are shown in Table 1.

Common variants altering OSM, OSMR and LIFR expression
OSM is secreted by neutrophils 4 , monocytes 2 , macrophages 2 and T-cells 3 , and acts through binding to OSMR and LIFR [5][6][7] in the arterial wall 13,35 . Thus we queried data from the Genotype-Tissue Expression project (GTEx) 26 for SNPs that alter OSM expression in whole blood and LIFR and OSMR expression in arterial tissue. There were no significant eQTLs for OSM, but there were two eQTLs that associated with either altered OSMR (rs13168867) or LIFR (rs10491509) expression in arterial tissue. The C allele of rs13168867 showed the strongest association with decreased OSMR expression in the tibial artery ( Figure 1A), and the A allele of rs10491509 showed the strongest association with increased LIFR expression in the aortic artery ( Figure 1B). Cross-tissue meta-analysis showed that these variants have > 0.9 m-values in both tibial and aortic artery tissue, indicating a high probability that they are single cis-eQTLs in both tissues (Supplemental Figure 2 and 3).

Genetic association with plaque vulnerability
To determine the effect of OSM signaling on the overall plaque vulnerability, we correlated the rs13168867 and rs10491509 genotypes to the overall plaque vulnerability, which was given a score ranging from 0 (least vulnerable plaque) to 4 (most vulnerable plaque). The effect allele of variant rs13168867 in the OSMR locus was significantly correlated with an increased overall plaque vulnerability (β = 0.118 ± s.e. = 0.040 (C allele), p = 3.00x10 -3 , Table 2), which is visualized in Figure 2. No association was observed with rs10491509 and overall plaque vulnerability.

Genetic association with plaque phenotypes
To determine the effect of OSM signaling on the plaque phenotype, we assessed the association between rs13168867 and rs10491509 and seven plaque phenotypes in the Athero-Express Biobank Study. The strongest associations were observed between the effect allele of variant rs13168867 in the OSMR locus and intraplaque fat (β = 0.248 ± s.e. = 0.088 (C allele), p = 4.66x10 -3 ), and collagen content (β = -0.259 ± s.e. = 0.095 (C allele), p = 6.22x10 -3 , Table 3). No associations were observed between rs10491509 and any of the plaque phenotypes.

Discussion
We investigated whether common variants associated to arterial gene expression, eQTLs, near OSM, OSMR and LIFR affect overall plaque vulnerability and phenotype. We showed that one cis-acting eQTL (rs13168867), associated with reduced OSMR expression arterial tissue, is associated with increased plaque vulnerability. This suggests that a decrease in OSMR expression and therefore possibly a decrease in OSM signaling, increases the chance on a vulnerable plaque. To gain further insight into the role of genetically decreased OSMR expression on plaque vulnerability, we examined the effect of rs13168867 on individual plaque characteristics in more detail. The strongest associations were found for rs13168867 with increased intraplaque fat and decreased collagen content, suggesting that reduced OSM signaling results in a larger lipid core and less fibrosis -in line with a more vulnerable plaque phenotype. None of the other plaque characteristics were associated with rs13168867.
The increase in intraplaque fat content that is associated with genetically decreased arterial OSMR expression can be related to the effect of OSM signaling on endothelial cells. OSM enhances ICAM-1 expression, but not VCAM-1 expression on endothelial cells 36,37 , suggesting that OSM enhances recruitment of the non-classical monocyte subset 38,39 has a protective effect on the endothelium 38,39 Furthermore, this monocyte subset is biased to turn into the M2 macrophage subset 40 , which is associated with plaque regression [41][42][43] .
OSM could even accelerate this process as OSM induces M2 macrophage polarization 21 .
Yet, this hypothesis remains to be investigated and future studies should explore whether genetically reduced OSM signaling indeed increases intraplaque lipid content by reduced recruitment of non-classical monocytes and impaired M2 macrophage polarization.
The decrease in collagen content associated to genetically decreased OSM signaling could be attributed to the increase in fibroblast proliferation and enhancement of collagen formation that is induced by OSM 20 . Moreover, OSM enhances liver fibrosis in mice 44  Interestingly, a previous study showed that OSMR deficient mice have more stable plaques 13 , which runs counter to our findings. This controversy could be explained by the differences in human and murine OSM signaling. In humans OSM binds to OSMR and LIFR with the same affinity, while murine OSM has a much stronger affinity for OSMR 46 In point of fact, while homologous, the sequence similarity of human OSM, OSMR, LIFR with murine is moderate at best (64.75%, 70.79%, 78.51%, respectively based on data from GeneCards 47 ) and might directly impact receptor affinity 48 .
Based on our data we can conclude that the variant rs13168867 in the OSMR locus is associated with increased plaque vulnerability. Given the multiple testing burden for individual plaque characteristics, it remains unclear through which precise biological mechanisms OSM signaling exerts its effects on plaque morphology, although our data point towards lipid metabolism and extracellular matrix remodeling. Compared to genomewide association studies that include thousands of individuals, the Athero-Express Biobank Study is relatively small (n = 1,443), and given its design finite in size. However it is well suited to examine the effect of common disease associated genetic variation on plaque morphology and characteristics. Indeed, we estimated the power at ±75% given a MAF = 0.40 (approximately the frequency of rs13168867) and relative risk = 1.28 49 .

Conclusion
We associated one eQTL in the OSMR locus, which associates with decreased arterial OSMR