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首页医源资料库在线期刊动脉硬化血栓血管生物学杂志2007年第27卷第12期

Free Interleukin (IL)-18 Levels, and the Impact of IL18 and IL18BP Genetic Variation, in CHD Patients and Healthy Men

来源:《动脉硬化血栓血管生物学杂志》
摘要:Toinvestigatefreeinterleukin-18(fIL-18)levels,andvariationwithintheIL-18systemgenes,inheartsurgerypatients,andhealthymen。fIL-18wascalculatedfromIL-18andIL-18bindingprotein(BP)levels,in421healthymenand196post&ndash。Aftersurgery,fIL-18peakedat6hours(fr......

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【摘要】  Objective— To investigate free interleukin-18 (fIL-18) levels, and variation within the IL-18 system genes, in heart surgery patients, and healthy men.

Methods and Results— fIL-18 was calculated from IL-18 and IL-18 binding protein (BP) levels, in 421 healthy men and 196 post–coronary artery bypass graft (CABG) patients. After surgery, fIL-18 peaked at 6 hours (from 117 to 331 pg/mL) but fell to below presurgery levels at 24 hours (99 pg/mL), because of changes in total IL-18 and IL-18BP. fIL-18 24 hours postsurgery was significantly higher in those who suffered a major complication after surgery (125 versus 80 pg/mL, P <0.01). Baseline total IL-18 was also higher in healthy men who went on to suffer an MI over 17 years of prospective study (276 versus 240 pg/mL, P =0.01). Tagging SNPs for IL18 (n=5) and IL18BP (n=3) were determined, in both studies the IL18 Hap III haplotype (frequency 30%) was associated with 36% lower baseline fIL-18 levels before surgery ( P <0.01), and 7% lower in healthy men ( P =0.04). The frequency of Hap III was lower in CABG patients than in healthy men (20.7 versus 29.8%, P <0.01).

Conclusions— IL-18 levels, which are determined in part by variation in IL18, play a role in CHD development and postsurgery outcome.

The affect of elevated IL-18 levels and the implications of variation within the IL-18 system genes was investigated. In both healthy and diseased individuals, IL-18, determined in part by common variation within IL18, was predictive of adverse outcomes, suggesting IL-18 may play a role in CHD development and postsurgery outcome.

【关键词】  IL ILBP polymorphism surgery atherosclerosis


Introduction


Interleukin (IL)-18 is a pleiotropic cytokine involved in both innate and adaptive immune response, 1 and is widely expressed in monocytes/macrophages, adipocytes, keratinocytes, Kupffer cells, and osteoblasts. 2,3 Originally identified as an interferon (INF)- –inducing factor, 4 it stimulates IFN production in T lymphocytes and natural killer (NK) cells in synergy with IL-12. 5 This induction does not require prior activation of either CD4+ or CD8+ T cells 5 and produces significant quantities of IFN; a protein believed to have an affect on around 25% of the macrophage transcriptome. 6 Both T lymphocytes and NK cells are key in atherosclerotic plaque progression and stability. 7,8 Il-18 activity is determined in part by the action of an intrinsic inhibitor, IL-18 binding protein (IL-18BP). 9 IL-18BP is reactive to inflammatory stress 10 and modulates atherosclerotic lesion development in apoE –/– mice. 11


Increased IL-18 expression is seen in atherosclerotic plaques and is associated with plaque instability. 12,13 In healthy middle-aged European men total plasma IL-18 levels were an independent predictor of coronary events, 14 and variation within IL18 has been shown to influence circulating levels of IL-18 and clinical outcome in patients with cardiovascular disease (CVD). 15 However, the MONICA/KORA Ausburg Case-Cohort Study showed no association between IL-18 and risk of future CVD in apparently healthy subjects. 16 Several groups have also sought to clarify the role of IL-18 and IL-18BP in the development of plaque instability in cross-sectional studies, 17–20 but with inconsistent results.


All studies to date investigating the impact of IL-18 on CHD risk have not taken into account IL-18BP levels. In the present study, we investigated variation in IL-18 and IL-18BP levels, and were therefore able to calculate levels of free IL-18 (fIL-18), in a surgical model of postevent immunoactivation. We have also determined levels of fIL-18 in a prospective study of healthy European men, and assessed their association with future CHD events. The impact of genetic variation within IL18 and IL18BP on protein levels were also examined.


Methods


Study Groups


The Coronary Artery Bypass Graft (CABG) study is described in more detail elsewhere. 21 Briefly, 439 patients were recruited prospectively from those undergoing first time elective CABG surgery. Venous blood samples (nonfasting) were initially drawn before surgery and then again at 6 and 24 hours postoperatively. Those with sufficient plasma still available at all 3 time points were selected (n=196) and this cohort forms the basis of this 98% of participants. Patients were defined as having suffered a major complication after surgery for a number of reasons, with major causes being continued inotrope administration, increased 12 hours), or extended intensive care 2 days).


The second Northwick Park Heart Study (NPHSII) 22 consists of 3012 healthy European, Caucasian men, aged 51 to 60 years, recruited from 9 general medical practices, and free from cardiovascular disease at recruitment. Over 17 years of follow-up (median 14 years), 294 (9.8%) participants have developed definite CHD (definite MI, surgical intervention, or silent MI) over this period. Blood samples were taken after a light breakfast.


In both studies ethical approval was granted by the institutional ethical committee and all subjects gave written informed consent before recruitment.


Measurement of Total IL-18 and IL-18BP


IL-18 and IL-18BP protein levels were measured in the CABG cohort and in an age-matched nested case:control cohort from NPHSII (185 cases, 236 controls) that form the basis for this article. Total IL-18 was measured by a commercially available ELISA-kit (MBL, Naka-Ku), according to manufacturer?s instructions. The ELISA method used for the IL-18BP measurement is described in detail elsewhere. 10 Because antibodies for the IL-18 ELISA detect both fIL-18 and IL-18:IL-18BP complexes, levels of fIL-18 were calculated based on known stoichiometry and dissociation rates, as described elsewhere. 10


tSNP Selection and Genotyping


IL18 resequencing and haplotype data from Innate Immunity Programmes for Genomic Applications (IIPGA, http://innateimmunity. net) was used in conjunction with a haplotype-tagging SNP program—tagSNPs.exe 23 —to select IL18 haplotype-tagging polymorphisms with a minimum R 2 of 0.9. For IL18BP, genotyping data for all the SNPs within the candidate region (in total 10 kb) were obtained for the European population (CEU) from the International HapMap project (www.hapmap.org, HapMap data release #18/phaseII) and PGA, and Tagger 24 used to select tSNPs. For further information and genotyping details, see supplemental materials at http://atvb.ahajournals.org.


Statistical Analysis


Standard statistical tools were used to analyze all data (for further details see supplemental materials). Haplotype association analysis was carried out using Thesias, 25 and was limited to the four most common haplotypes.


Results


Baseline Characteristics


As can be seen from the baseline characteristics (see Table 1 ), the CABG patients are a largely Caucasian male cohort, with around a third having suffered 1 or more myocardial infarctions (MIs) previously. There were no significant differences in those who suffered a postoperative complication (43%) and those who did not. In NPHSII, those who went on to develop CHD during follow-up were more likely to smoke, be hypertensive, have elevated cholesterol, or have low HDL levels. Compared with CABG, NPHSII was a younger cohort with lower BMI yet higher lipid levels, probably attributable to the common use of statins in CABG patients. Levels of fIL-18 were 21% lower in CABG participants than NPHSII participants ( P =0.02), attributable to significant differences in total IL-18 levels ( P =0.01), but not IL-18BP ( P =0.14). Most likely this difference is attributable to statin use within CABG, because levels of total IL-18, IL-18BP, or fIL-18 in CABG patients not taking statins did not differ significantly compared with NPHSII (data not shown).


Table 1. Baseline Characteristics of Study Groups


Table 1. Continued


Profile of IL-18 and IL-18BP After Surgery


After surgery, the levels of total IL-18 peaked at 6 hours (see Table 1 ), showing a 2.3-fold elevation from baseline ( P <0.01), 24 hours after surgery levels of fIL-18 had decreased to below baseline levels ( P =0.04) attributable to significant changes in both total IL-18 and IL-18BP levels (see Figure 1 ).


Figure 1. Fold-changes (95% CI) from baseline in total IL-18, fIL-18, and IL-18BP at 6 hours and 24 hours.


IL-18 Level and Postoperative Recovery and CVD Risk


In CABG, plasma levels of total IL-18 24 hours after surgery in those who had suffered a major complication after surgery (n=84), were significantly higher (1.6-fold) than those who did not ( P <0.01). The association remained when fIL-18 was analyzed (1.6-fold higher, P <0.01), equating to a relative risk (RR) (95% CI) of 1.64 (1.06 to 2.53, P =0.02) for those in the top tertile of fIL-18 versus the lowest tertile. The predictive effect of total IL-18 ( P <0.01) and fIL-18 ( P <0.01) were independent of statin use and IL-18BP (a covariate in total IL-18 analysis only). We have previously reported (Sanders, Brull, and Humphries, 2007, unpublished data) that levels of IL-6 at 24 hours were also significantly higher in those with a major postoperative complication; both total and fIL-18 at 24 hours remained predictive in multivariate analysis with IL-6 levels at 24 hours added as a covariate ( P <0.01 and P <0.01, respectively), suggesting that this predictive effect of IL-18 was independent of IL-6 also.


NPHSII participants in the top tertile of total IL-18 levels at baseline had an RR (95% CI) for an MI during follow-up of 1.6 (1.0 to 2.6, P =0.03, see supplemental Table II). Those who suffered an MI during follow-up had significantly higher total and fIL-18 levels at baseline than those who did not (total IL-18, 1.2-fold higher, P =0.01; fIL-18, 1.1-fold higher, P =0.04). This effect was not seen when men with any CHD event were analyzed and was no longer statistically significant after adjustment for traditional risk factors.


Impact of Genetic Variation on Protein Levels


Single SNP Analysis


An IL18 tSNP set comprising 5 SNPs was selected and comprised A and +11015 T), and C). 26 LD between the SNPs ranged from D'=0.52 to 0.96, all were found to be in HWE in the original study groups. Only IL18 C was associated with differences in total IL-18 levels in CABG (see Figure 2, panel A and supplemental Table III), at both baseline ( P <0.01) and 6 hours postoperative ( P <0.01), but not 24 hours ( P =0.65). Those carrying 2 copies of the rare allele had total IL-18 levels 1.9-fold higher at baseline and 1.3-fold higher at 6 hours than those carrying no copies, and of all the variants, this SNP explained the largest amount of the variation in IL-18 levels ( R 2 =6.3% at baseline, 5.5% at 6 hours, 0.5% at 24 hours). These associations remained significant after adjustment for statin use, and were also seen, in a similar pattern, with fIL-18 levels (see supplemental Table IV).


Figure 2. A, Total IL-18 plasma levels (pg/mL) in CABG by IL18 C genotype at baseline and 6 hours. B, Total IL-18 plasma levels (pg/mL) in NPHSII by IL18 C genotype, by event status; TT: no CHD event n=87, CHD event n=82; TC: no CHD event n=96, CHD event n=64; CC: no CHD event n=28, CHD event n=64. Line indicates Median; Box, 75 th to 25 th 3 box lengths above box); whisker, last value not an outlier.


C was also associated with significant differences in plasma IL-18 levels in NPHSII ( P <0.01, R 2 =3.9%), with those carrying 2 copies of the rare allele having levels 1.3-fold higher than those carrying no copies (see supplemental Table III). This effect was unchanged after adjustment for IL-18BP levels ( P C SNP was also associated with fIL-18 levels in univariate ( P =0.03) and multivariate analysis ( P =0.02, see supplemental Table IV). When analysis was stratified C was associated with total IL-18 levels in both groups (see Figure 2, panel B), although the association was more prominent in those who went on to develop CHD (CHD event, P <0.01; no CHD event, P =0.05; interaction P =0.01).


None of the IL18BP tSNPs were consistently associated with significant differences in IL-18BP or fIL-18 levels in either study (see supplemental Table IV).


Haplotype Analysis


To avoid any problems attributable to genetic heterogeneity, analysis in the CABG group was limited to those of Caucasian T; C) were globally associated with total IL-18 levels at baseline ( P <0.01), and borderline significantly associated at 6 hours ( P =0.06, see Table 2 ), explaining 5.2% and 5.1% of the variation in IL-18 levels, respectively. A common haplotype, Hap III (frequency 21% in CABG), was associated with a lower haplotypic mean IL-18 level at baseline and 6 hours (both P <0.01) than Hap I, but not 24 hours ( P =0.08). Those homozygous for Hap I were estimated to have IL-18 levels 2.7-fold higher at baseline, and 1.7-fold higher at 6 hours, than those homozygous for Hap III (see Figure 3 ). These associations remained significant after adjustment for statin use and IL-18BP levels, and when fIL-18 was analyzed (see supplemental Table V).


Table 2. Estimated Haplotypic Mean (95% CI) lnIL-18 Levels by IL18 Haplotypes in Both CABG and NPHSII (Total, no CHD Event, and CHD Event), Using Univariate Analysis ( P *) and Multivariate Analysis With Either Statin Use and IL-18BP Levels ( P ) or GP Practice and IL-18BP Levels ( P ) as Covariates


Table 2. Continued


Figure 3. Estimated total IL-18 plasma levels (box, mean; whisker, 95% CI) for homozygotes of each haplotype, in CABG and NPHSII. Data presented are the haplotypic mean and confidence intervals estimated by Thesias, multiplied by 2.


In NPHSII, univariate ( P <0.01) and multivariate ( P <0.01) analysis showed haplotypes were globally associated with total IL-18 levels (see Table 2 ) and explained 3.2% of the variation in IL-18 levels. Two common haplotypes, Hap II (25%, P =0.01) and Hap III (30%, P <0.01), had significantly lower total IL-18 levels when compared with Hap I. Those homozygous for Hap I were estimated to have IL-18 levels 1.3-fold higher than those homozygous for Hap II or Hap III (see Figure 3 ). These associations were attenuated, but remained significant, after adjustment for IL-18BP levels and platelet glycoprotein practice, and when fIL-18 was analyzed (see Table 2, and supplemental Table V).


No consistent, significant associations were observed between IL18BP haplotypes and IL-18BP or fIL-18 levels in either study (see supplemental Table VI). There was no significant associations between IL18 or IL18BP genotypes or haplotypes, and postoperative risk in CABG or with CHD risk in NPHSII (see supplemental Table VII). However, Hap III was found at a lower frequency in CABG than NPHSII (20.7% versus 29.8%, P <0.01).


Discussion


The major findings of this study are that levels of fIL-18 undergo transient dynamic changes after a significant inflammatory activation, through variation in both IL-18 and IL-18BP, and that its levels influence postoperative outcome. Both at its peak and at baseline, common genetic variation within IL18 was significantly associated with levels of fIL-18 in both healthy individuals and those with advanced disease.


Within the CABG group those who suffered complications after surgery did not differ significantly in their baseline characteristics from the other study participants. At 24 hours after surgery, levels of both total and fIL-18 were significantly higher in those who suffered a later postoperative complication than those who did not. This association remained significant in subset 12 hours) 2 days) as outcomes (data not shown), demonstrating the long-standing effects of early IL-18 activation and the key initiating role of IL-18 in immunoactivation. Adjusting for levels of IL-6 did not reduce this effect, suggesting that the effect was independent of other inflammatory pathways.


How the surgical model of postevent immunoactivation used here equates to processes leading up to, and immediately after, plaque rupture is unclear; however, there are animal models that suggest IL-18 levels may influence post-MI survival. In caspase-1 knockout (KO) mice, no bioactive IL-18 is present in the plasma due to the requirement of IL-18 for caspase-1 processing. When these animals undergo left coronary artery ligation to induce MI, they have significantly greater postevent survival than WT animals. 27 Although caspase-1 has a number of effects other than IL-18 processing, IL-18 has been shown to predict long-term survival in patients with advanced disease. 17,28,29


A similarly predictive effect was also seen in the prospective NPHSII study; levels of IL-18 were significantly higher in those who went on to suffer, specifically, an MI than those who did not. IL-18 is known to play an active role in determining plaque stability, with overexpression in apoE -deficient mice causing decreased intimal collagen content, 30 and higher IL-18 expression seen in unstable over stable human plaques. 13 That higher levels were observed only in those whose first indication of disease, during follow-up, was an MI, and not when other CHD end points were included, suggests that IL-18 may have a key role in dictating the stability or instability of the plaque, rather than other processes involved in plaque development. However, because of the small number of cases within NPHSII, the power to truly identify and characterize this association is low. Furthermore, given that there was no significant difference in fIL-18 levels in those who went on to develop disease, cautious interpretation of these results is required. At present there is no other suitable method for measuring fIL-18 in the plasma other than the calculation used here. Exactly how well this reflects the true concentration across individuals is not presently clear.


In this study we show that IL-18 levels in both healthy and diseased individuals are determined in part by variation within IL18. Both in CABG and NPHSII, haplotypic variation in IL18, but not IL18BP, was significantly associated with total and fIL-18 levels, explaining 3% to 5% of the variation in levels. Consistently, Hap III was associated with significantly lower IL-18 levels in both studies. This finding was supported by C, the SNP that differentiates Hap III and the reference haplotype ( Hap I), was associated with significant differences in total and free IL-18 levels. Furthermore, there was evidence that the influence of genetic variation was exacerbated by underlying disease, with the effect seen to be significantly stronger in those in NPHSII men who went on to develop CHD than those who did not.


Few studies have investigated the effect of genetic variation on IL-18 and IL-18BP protein levels, and we are unaware of any where analysis has been extended to fIL-18. Tiret et al 15 found a 5-SNP haplotype (HapGCAGT) to be associated with lower IL-18 levels and a protective effect on risk, and in further studies, to be associated with lower IL18 mRNA levels. 31 The IL18 SNPs studied here are not those used by Tiret et al, however when those SNPs are aligned on to the IIPGA gene-wide haplotypes, both HapGCAGT, and Hap III represent the same gene-wide haplotype. Furthermore, Frayling et al 32 studied the effect of a single SNP, rs5744256, on IL-18 levels and found the rare allele, only found on Hap III, to be associated with lower IL-18 levels. We have already shown that Hap III is associated with differences in BMI, 26 and so, taken together, the data confirm that this IL18 haplotype is functionally distinct from others and affects individual disease risk through differences in total and fIL-18 levels. None of the SNPs studied here have a strong likelihood of being themselves functional, and it is probable that the SNP, or SNPs, ultimately responsible for this effect are present elsewhere on Hap III. Therefore further genotyping and extended sequencing will be required to characterize Hap III in more detail, in tandem with in vitro studies of isolated SNPs to assess their functionality.


The lack of measures beyond 24 hours is a limitation of the CABG study, with it representing a brief, but critical, window in a patient?s postoperative recovery. With further measures beyond and within this period it would be possible to better characterize the profile of IL-18. However, beyond 24 hours the patient group becomes more heterogenous as each adopts differing treatment regimen, which may begin to confound IL-18 levels. In support of this data, a recent study investigating the differing profile of IL18 and IL18BP transcription in isolated PBMCs from diseased and healthy patients, found the peak of IL-18 production after in vitro activation was 8 hours, 33 confirming that the period studied here represents the most important time for IL-18 activation.


This study also lacks the power to truly test whether IL-18 levels immediately before and after surgery have an effect on postoperative mortality. IL-18 has been shown to predict in-hospital adverse events (death, recurrent ischemia, reinfarction) in patients with acute coronary syndrome, 17 and there is some evidence here to suggest that IL-18 levels may differ depending on recovery; however, the statistical power to study postoperative mortality is low with only 2 patients dying in hospital after surgery. A larger group would allow us to study this association with greater certainty and may also allow us to study the effect of genetic variation within IL18.


Acknowledgments


Sources of Funding


S.R.T. is supported by a British Heart Foundation studentship FS/04/039; C.J.S. is supported by an Oliver Bird Rheumatism Programme studentship; M.R. is the Edna and Maurice Weiss Professor of Cytokine Research, and is supported in part by Merck Serono; S.E.H. is supported by a BHF program grant 2000/015.


Disclosures


None.

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作者单位:From Cardiovascular Genetics (S.R.T., J.C., S.E.H.), Rayne Institute, University College London, UK.; the Department of Molecular Genetics (D.N., M.R.), The Weizmann Institute of Science, Rehovot, Israel; the Department of Immunology and Molecular Pathology (C.J.S., P.W.), University College London,

作者: Simon R. Thompson; Daniela Novick; Carmel J. Stock
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