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Human Molecular Genetics Advance Access originally published online on February 14, 2008
Human Molecular Genetics 2008 17(11):1619-1630; doi:10.1093/hmg/ddn049
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© The Author 2008. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Interleukin-6 (IL-6) and receptor (IL6-R) gene haplotypes associate with amniotic fluid protein concentrations in preterm birth

Digna R. Velez1,2,3, Stephen J. Fortunato4,5, Scott M. Williams1,2,3,* and Ramkumar Menon4,6

1 Division of Cardiovascular Medicine 2 Department of Medicine 3 Center for Human Genetics Research, Vanderbilt University, Nashville, TN, USA 4 The Perinatal Research Center, Centennial Women's Hospital, Nashville, TN, USA 5 Department of Obstetrics and Gynecology and Reproductive Sciences, Yale University, New Haven, CT, USA 6 Northern Atlantic Neuro Epidemiologic Alliance, Department of Epidemiology, University of Aarhus, Denmark

* To whom correspondence should be addressed at: Center for Human Genetics Research, 519 Light Hall, Vanderbilt University, Nashville, TN 37232, USA. Tel: +1 6153228036; Fax: +1 6153438619; Email: smwilliams{at}chgr.mc.vanderbilt.edu

Received January 8, 2008; Accepted February 12, 2008


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIAL AND METHODS
 SUPPLEMENTARY MATERIAL
 FUNDING
 REFERENCES
 
Spontaneous preterm birth (PTB—gestational age <37 weeks) occurs in ~450 000 births annually in the United States and is one of the leading causes of neonatal morbidity and mortality. Risk of PTB is affected by complex gene–environment interactions that are not well understood. We examined the PTB candidate gene, Interleukin 6 (IL-6) and its receptor (IL6-R) in both Caucasian (145 PTB and 194 term maternal; 140 PTB and 179 term fetal) and African-American (76 PTB and 191 term maternal; 66 PTB and 183 term fetal) DNA. Eight single nucleotide polymorphisms (SNPs) in IL-6 and 22 SNPs in IL6R were examined for association with IL-6 amniotic fluid (AF) concentrations, as concentration of IL-6 is a hypothesized risk factor. In addition, IL-6 and IL6-R SNPs were analyzed for associations with PTB. Haplotype associations were tested by sliding windows. No strong single marker effects were observed in Caucasians; however, in African-American maternal IL-6R marker rs4553185 associated with PTB (allele P = 4.49 x 10–3 and genotype P = 0.01). The strongest haplotype associations were observed in IL-6R with IL-6 cytokine concentration as outcome: Caucasian fetal (rs4601580–rs4845618) P = 1.6 x 10–3 and African-American maternal (rs4601580–rs4845618–rs6687726–rs7549338) P = 2.30 x 10–3. Significant results converged on three regions in the two genes: in IL-6 markers rs1800797, rs1800796 and rs1800795; in IL-6R markers rs4075015, rs4601580, rs4645618, rs6687726 and rs7549338 and markers rs4845623, rs4537545 and rs4845625. In conclusion, our results suggest that IL-6 AF concentration, in situations of PTB, result from variation in IL-6 and more importantly IL-6R.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
RESULTS
 DISCUSSION
 MATERIAL AND METHODS
 SUPPLEMENTARY MATERIAL
 FUNDING
 REFERENCES
 
Preterm birth (<37 weeks gestation—PTB) occurs in 12.0–13.0% of pregnancies in the United States (1) and is associated with 60–80% of the neonatal morbidity and mortality (2). Our understanding of PTB is further complicated by the observed rate disparity between African-Americans and Caucasians, with rates in Caucasians being ~11–12% and ~17–18% in African-Americans. (3). The causes of PTB and racial disparity are still unclear.

There is accumulating evidence supporting the hypothesis that PTB is influenced by genetic factors (4–6). These include: (i) previous PTB are associated with an increased risk of future PTB; (ii) an association has been seen between ethnicity/race and PTB; (iii) mothers who were born PTB or have sisters who had a PTB have a higher risk of delivering preterm (7–9). In addition, twin studies estimate a heritability between 20 and 40% (5,10). These data, although not conclusive, strongly support a role for genetic variation in the etiology of PTB.

An important etiological factor associated with PTB is inflammatory response. As many as 60% of PTB have demonstrated evidence of inflammation (11–13) and ~40–50% are associated with infection. As a result, it has been hypothesized that host inflammatory response to infection (e.g. cytokine and matrix metalloproteinase activation) in some women increases their risk of PTB compared with others (11,12,14) and that the differential response is due to a different genetic constitution (15,16). Increased interleukin-6 (IL-6) in the cervical and amniotic fluid (AF) is associated with PTB (13,17), regardless of infectious status. Because of this IL-6, is considered to be a marker of ‘high’ risk status for PTB (13). Fetal plasma analyses have shown that elevated IL-6 is associated with fetal inflammatory response syndrome and maternal infection (18). Recent genetic association studies for PTB have found an association with a single nucleotide polymorphism (SNP) in the promoter region of the IL-6 gene (rs1800795; C-174G) (19) that may affect IL-6 concentration in response to stressful stimuli (20). The C-174G polymorphism (G allele) decreases promoter activity and the (G/G) homozygote associates with increased risk of PTB (19). Additional studies have indicated that plasma IL-6 concentrations also associate with SNPs in its receptor gene, IL-6R (21). Therefore, both IL-6 and IL-6R are strong candidates for PTB and as mediators of IL-6 concentrations in pregnancy.

In a previous study, we examined a small subset of SNPs in IL-6 and IL6-R and found an association between AF IL-6, and a marker in the promoter region of IL-6, rs1800797 (A-661G), but only in Caucasian PTB (22) The association between AF IL-6 concentration and genotype at A-661G also differed between PTB with and without microbial invasion of the amniotic cavity (MIAC), providing evidence of a gene–environment interaction. This marker was also in linkage disequilibrium (LD) with the previously described C-174G variant, indicating that a haplotype effect may account for the observed association with AF IL-6 concentrations. Support for this hypothesis was further provided by a report that haplotypes in the promoter region of IL-6, and not individual SNPs, control IL-6 gene expression (23). In the present study we analyze several more markers in the IL-6 and IL-6R genes to better assess the relationship of AF IL-6 concentrations with genetic variation in the context of PTB. We focus on haplotype variation, as haplotype analyses may better detect variants of etiological significance (24). Given the disparity in PTB rates, we analyzed African-American and Caucasian samples separately to provide insight into haplotype diversity and association across different ethnic groups. Specifically, we examined maternal and fetal DNA from PTB (cases) and term deliveries after a normal pregnancy (controls) for single locus and haplotype associations within the IL-6 and IL6-R genes, using both dichotomous (case versus control) and continuous outcome (AF IL-6 concentration).


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
DISCUSSION
 MATERIAL AND METHODS
 SUPPLEMENTARY MATERIAL
 FUNDING
 REFERENCES
 
Baseline characteristics
As expected, significant differences between cases and controls were observed in both Caucasians and African-Americans for gestational age (days) (Caucasian P < 0.001; African-American P < 0.001), birth weight (grams) (Caucasian P < 0.001; African-American P < 0.001). Differences in APGAR 1 (1 min after birth)(Caucasian P < 0.001; African-American P < 0.001) and APGAR 5 (5 min after birth) (Caucasian P < 0.001; African-American P < 0.001) were also noted. (Table 1).


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  		Table 1. Clinical and demographic information

 
Single locus associations
Tests for Hardy–Weinberg equilibrium (HWE) were performed for all SNPs in cases and controls separately, in each population. Among the 120 tests for HWE, seven deviated in cases and 16 in controls but only one had a P < 0.01. It is of note that for most situations where control P < 0.05 for HWE tests there is evidence that the inbreeding coefficients (f) were in opposite directions in cases and controls. For example, the f in Caucasian maternal controls revealed that four of the markers that deviated from HWE in IL-6R showed that the directions of deviations from HWE was opposite to that of cases (rs4845622 – PTB f = –0.07 term f = 0.16; rs4845623 – PTB f = –0.06, term f = 0.18; rs4537545 – PTB f = 0.19, term f = –0.002; rs4329505 – PTB f = 0.04, term f = –0.13). These results suggest that the deviations are not likely due to genotyping error, as cases and controls were mixed in the same plates for genotyping.

In Caucasian maternal samples, four marginally significant allelic associations were observed with PTB in IL6-R at rs7549338 (P = 0.04), rs4845625 (P = 0.04), rs11265618 (P = 0.05), and rs4072391 (P = 0.04) (Table 2C). No statistically significant single locus associations were observed in Caucasian fetal samples (Table 2C). African-American maternal samples had one statistically significant association with PTB in IL-6 (Table 2B) at rs2069840 (allelic association P = 0.03), but in IL-6R there were eight SNPs with significant associations (either for allelic or genotypic association): rs4845618 (allele P = 0.02, genotype P = 0.03), rs6687726 (allele P = 0.04), rs7549338 (allele P = 0.01, genotype P = 0.02), rs4553185 (allele P = 4.49 x 10–3, genotype P = 0.01), rs4845622 (genotype P = 0.02), rs4845623 (allele P = 0.02, genotype P = 0.02), rs4537545 (allele P = 0.05), and rs4845625 (allele P = 0.03) (Table 2D). African-American fetal samples had two associated markers in IL-6: rs1880243 (allele P = 0.01, genotype P = 0.03) and rs12700386 (allele P = 0.03), but none in IL-6R (Table 2B).


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  		Table 2. Minor allele frequencies and association analysis in maternal and fetal samples

 
Linkage disequilibrium (LD) characterization
In Caucasian maternal and fetal DNA there is evidence for substantial LD in IL-6 in both cases and controls (Supplementary Material, Fig. S1A–D). Two IL-6 SNPs in the 5' part of the gene (rs1880243 and rs12700386) had D' values of 1.0 in all Caucasian samples, although the pattern may be slightly different for other variants between cases and controls. As expected African-American maternal and fetal samples showed less evidence of LD (Supplementary Material, Fig. S1E–H) in IL-6. In fact, in the African-American samples there was little evidence of LD in IL-6. Of particular note, the two most 5' markers that demonstrated complete LD in Caucasians showed no sign of LD in African-Americans.

IL-6R had strong regions of LD in Caucasians, however, no blocks were identified according to the Gabriel et al. definition (Supplementary Material, Fig. S2A–D). The strongest regions of LD were in the 3' part of the gene between markers rs4845618 and rs7526293; weaker pairwise LD was observed in the 5' region between markers rs952146 and rs4075015. African-Americans had weaker LD in comparison with Caucasians; however, several blocks were identified (Supplementary Material, Fig. S2E–H). None of the blocks were consistent across status groups.

IL-6 haplotype and case–control status
Sliding window haplotype analyses in Caucasian maternal samples found that IL-6 haplotypes defined by SNPs rs12700386–rs1800797–rs1800796–rs1800795 associated with pregnancy outcome (global P = 0.05). The G–A–G–C haplotype showed the strongest association [OR 2.42 (CI 0.92–6.85), P = 0.06] (Table 3). Caucasian fetal sample sliding window haplotype analyses found association with haplotypes defined by rs2069840–rs1554606–rs11766273 (global P = 0.01) (Table 3), but no single haplotype showed significant association.


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  		Table 3. IL-6 sliding window haplotype analysis results (dichotomous outcome)

 
In African-American maternal samples the sliding window analyses showed an association for a two SNP haplotype defined by rs1800795–rs2069840 (global P = 0.05), but no single haplotype significantly associated with PTB (Table 3). African-American fetal sliding window haplotype analyses found an association with SNPs rs1880243–rs12700386 (global P = 0.02). This result is due to the A–G haplotype that confers a significant protective effect relative to the most common haplotype, C–C [OR = 0.32 (CI 0.12–0.73), P = 4.00 x 10–3].

IL-6 haplotype and IL-6 concentration
In Caucasian maternal samples haplotypes defined by rs12700386–rs1800797 associated with AF log transformed cytokine concentrations in pooled analyses of cases and controls (P = 0.04) but showed no significant association when stratified by status (cases P = 0.36; controls P = 0.34) (Table 4). Of interest is the observation that rs12700386-1800797 haplotypes have apparently different patterns of association depending on clinical status. The G–A haplotype associated with a higher IL-6 concentration in cases [3.47 log (pg/ml) compared with controls 2.90 log (pg/ml)]. These two markers also have different LD structure in cases and controls with D' = 0.36 in cases and D' = 0.75 in controls (Supplementary Material, Fig. S1A and B). Caucasian fetal sample haplotype analyses found that rs1554606–rs11766273 associated with IL-6 concentrations (pooled P = 0.05); however, this is probably due to the fact that the haplotype associations trended in the same direction in cases and controls even though they were not significant (cases P = 0.14; controls P = 0.51); (Table 4).


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  		Table 4. IL-6 sliding window haplotype analysis results (cytokine concentration outcome)

 
Haplotype analyses in African-Americans revealed associations in both maternal and fetal samples with two site haplotypes (Table 4). In maternal samples rs1554606–rs11766273 haplotypes associated with IL-6 concentration in controls (P = 0.03) but not in cases (P = 0.68) Haplotypes for rs1554606–rs11766273 had different trends in IL-6 concentrations in cases and controls, with T–A having the lowest IL-6 concentration in controls [2.91 log (pg/ml)] but T–G having the lowest concentration in cases [3.29 log (pg/ml)]. These two SNPs are in high LD in controls (D' = 1.00), but rs11766273 has low MAF (0.02) in controls in AA. For African-American fetal sample haplotype analyses the rs1800797–rs1800796 haplotype associated with IL-6 concentrations (pooled cases and controls P = 0.02; cases P = 0.58; controls P = 0.02) as did rs1800796–rs1800795 (pooled P = 0.02; cases P = 0.58; controls P = 0.16) (Table 4). Both rs1800797–rs1800796 and rs1800796–rs1800795 IL-6 concentrations trended in opposite directions with respect to case status. For example, for rs1800796–rs1800795 the G–C haplotype has the lowest concentration in cases [2.99 log (pg/ml)] but the highest in term [3.34 log (pg/ml)]. The three marker haplotype including rs1800797–rs1800796–rs1800795 did not associate with AF IL-6. Overall, the IL-6 haplotypes we studied account for from less than 1% to almost 10% of the variation in IL-6 concentrations (Table 4).

IL-6R haplotype analyses and case–control status
In Caucasian maternal samples IL-6R haplotypes rs4845625–rs4845374 showed significant association with PTB (global P = 0.02) (Table 5) with the C–T haplotype showing strongest association (OR = 1.34 (CI = 0.95–1.89), P = 0.08). No fetal haplotype associated with pregnancy outcome.


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  		Table 5. IL-6R sliding window haplotype analysis results (dichotomous outcome)

 
In African-American mothers a three SNP haplotype associated with PTB, rs4075015–rs4601580–rs4845618 (global P = 0.01) (Table 5). In addition to there being global significance, three individual haplotypes associated with PTB: A–A–G (frequency 0.07 in cases, undetected in controls, OR uncalculated, P < 0.001), A–A–T [OR = 0.17 (CI = 0.46–1.25); P = 0.01], and A–T–G [OR = 2.89 (CI = 1.00–9.12), P = 0.05]. These differences appear to be motivated by rs4845618 as indicated in the single SNP association (Table 2D). In African-American fetal samples rs4845625–rs4845374 haplotypes associated with PTB (global P = 0.04), but no haplotype associated individually.

IL-6R haplotype and IL-6 concentration
Haplotype analyses of IL-6R found several haplotypes that associated with IL-6 concentration, although none for Caucasian maternal haplotypes. A two SNP Caucasian fetal haplotype at rs460158–rs4845618 associated significantly with IL-6 concentration in cases (cases P = 0.04) but not in controls (P = 0.63) (Table 6). As in some cases above, trends differed between cases and controls; in cases the A–G haplotype had highest IL-6 concentration [3.67 log (pg/ml)] compared with controls, where this haplotype had the second lowest value [3.22 log (pg/ml)].


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  		Table 6. IL-6R sliding window haplotype analysis results (continuous cytokine concentration outcome)

 
In African-American maternal samples haplotypes defined by rs4601580–rs4845618–rs6687726–rs7549338 significantly associated with IL-6 concentration in both cases (P = 0.03) and controls (P = 0.05). The analysis provided evidence for similar trends in cytokine concentrations in cases and controls (Table 6). In African-American fetal sample haplotypes there was an association with rs4537545–rs4845625 and IL-6 concentration (pooled P = 0.02; case P = 0.33; control P = 0.08). Case and control mean cytokine concentrations trended in a different direction (Table 6). The IL-6R haplotypes studied account for from less than 1% to almost 30% of the variation in IL-6 concentrations, although the 30% is most likely an over-estimate due to small sample size (Table 6).

Haplotype–infection interaction
Cases stratified by MIAC were examined for IL-6 and IL-6R haplotype association (Table 7). Only African-American fetal samples showed evidence for differences in haplotype associations between cases with and without MIAC for IL-6 rs1800797–rs1800796 (MIAC P < 10–3; no MIAC P = 0.72) and rs1800796–rs1800795 (MIAC P < 10–3; no MIAC P = 0.72) and in IL-6R rs4537545–rs4845625 (MIAC P = 0.06; no MIAC P = 0.31).


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  		Table 7. MIAC analyses of haplotypes identified with continuous outcome

 


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  		Table 8. SNP positions and functions

 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
MATERIAL AND METHODS
 SUPPLEMENTARY MATERIAL
 FUNDING
 REFERENCES
 
This study examined 30 polymorphisms in IL-6 and IL-6R for association with PTB as an extension of our previous study of many fewer SNPs in these genes with the intent of assessing haplotype association (25). This analysis was performed with the intention of identifying common regions in both IL-6 and IL-6R across African-Americans and Caucasians that influence risk of PTB. Several statistically significant haplotypes were found in both Caucasian and African-Americans with both dichotomous and IL-6 concentration as outcome; however, three regions in the two genes appear to be shared in several of the comparisons (Fig. 1A and B).


Figure 1
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  		Figure 1. Haplotype summary. Solid lines indicate haplotypes that were associated with dichotomous outcome and dashed lines indicate haplotype that were associated with continuous outcome. Dark bounded lines on the schematic of the genes indicate regions of overlapping haplotype associations. Introns are labeled with light gray, promoter with dashed lines, exons with solid black rectangles, and 3'-UTR with dark gray. (A) Results for haplotype analyses for IL-6; (B) Results for haplotype analyses for IL-6R.

 
In the IL-6 gene one small region in the promoter region that includes markers rs1800797–rs1800796–rs1800795 showed significance in both Caucasian and African-American maternal and African-American fetal samples; two significant associations were observed with IL-6 concentration and two with PTB. In our previous report one SNP in this region showed evidence for association with IL-6 concentration (rs1800796) (25). African-American samples had two independent overlapping haplotypes and Caucasian maternal samples had one overlapping haplotype in this region. In Caucasians this region is in very strong LD, (pairwise D' 0.96–1.00). In African-American maternal and fetal samples only two of these markers have strong pairwise LD (rs1800797–rs1800795, D' = 1.00), with stronger overall LD in this region in controls relative to cases in both maternal and fetal samples. This indicates that there may be an effect caused by either an ungenotyped variants in this region or a haplotype effect.

Our results are in agreement with a previously published reports of IL-6 promoter haplotypes (23). This study examined rs1800797, rs1800796 and rs1800795 in Caucasians in which haplotypes within the IL-6 promoter region (including rs1800797, rs1800796, rs1800795 and -373AnTn) were shown to influence IL-6 transcription. The results demonstrated that upon stimulation with IL-1, IL-6 production is greatest with the G–G–G (rs1800797–rs1800796–rs1800795) haplotype but this same haplotype shows lowest IL-6 concentration in the absence of stimulation. In our study this haplotype did not associate with IL-6 concentration; however, in Caucasian maternal samples markers rs12700386–rs1800797–rs1800796–rs1800795 associated with PTB status with the G–G–G–G haplotype being protective. African-American fetal data also associated two overlapping haplotypes (rs1800797–rs1800795; rs1800795–rs1800796) with IL-6 concentration. The fact that African-American fetal samples have two haplotypes rather than one may suggest a recombination event split a single functional haplotype into two independent functional haplotypes. Across the analyses, three markers in this haplotype (rs1800797–rs1800796–rs1800795) were found to have the most overlapping haplotype associations, suggesting that a variant tagged by this haplotype may be playing an important regulatory in AF IL-6 production in cases, regardless of ethnicity.

In IL-6R, two regions (rs4601580–rs4845618–rs6687726 and rs4537545–rs4845625–rs4845374) associated with a phenotype in more than one analysis. Both regions contain intronic and exonic markers (Fig. 1B). These two regions had the strongest overall haplotype associations and also had more associations in African-Americans than Caucasians, especially with IL-6 concentration as outcome. Of note, two haplotypes in maternal Caucasian samples (rs4845618–rs6687726–rs7549338, P = 0.06 and rs4537545–rs4845625, P = 0.04 both for PTB) and one in fetal Caucasians samples (rs453745–rs4845625, P = 0.02 for IL-6) that are not represented in the figures also had some evidence for association in these two regions. Although these were not the most strongly associating haplotypes, they were significant or of borderline significance, and these data further support the likelihood that these regions of the IL-6R gene affect phenotype.

Comparing the strength of the results in the IL-6 to that of IL-6R, indicates that IL-6R rather than IL-6 has more influence on AF IL-6 concentration. This may be because these SNPs are in close proximity and in LD with functional/coding parts of the gene. For example, markers rs4845618 and rs6687726 are in close proximity to several exons and rs4537545–rs4845625–rs4845374 have exons between them. The CEU LD structure from the HapMap for IL-6R markers shows that both of the interesting regions in IL-6R are all in LD and in close proximity to several coding variants. The part of the IL-6R gene from rs4537545–rs4845625–rs4845374 was also found to associate with increased IL-6 concentration (21). This study found that a variant in IL-6R (rs4537545) associated with both IL-6 and IL-6R serum concentrations. It was also observed that these markers associate with several metabolic traits, e.g, diabetes, and marginally associates with cardio-vascular disease and asthma. Another recent study found that IL-6 concentrations are more associated with IL-6R variants than IL-6 gene variants (26). This study identified a variant (rs8192284 – between markers rs4845374 and rs11265618) that associated in Caucasians and African-American with IL-6 concentrations; this marker is just located downstream of the 3' most region IL-6R that we identified.

At present it is not possible to know precisely why the IL-6R variants have such strong association with IL-6 levels. However, it is possible based on other data to speculate that binding of IL-6 to IL-6R may impact the measurement of IL-6 via failure to detect bound IL-6 or its removal from the AF via binding. This may be through either membrane bound IL-6 or soluble IL-6R (sIL-6R) since both are encoded by the same gene and produced by either alternative splicing or limited proteolysis. sIL-6R can bind IL-6 creating a sIL-6R–IL-6 complex that can bind to membrane bound gp130, the signal transduction component of IL-6 receptor. This process triggers signaling through dimerization of gp 130 and activation of associated tyrosine kinases (27,28). However, since it has been shown that sIL-6R remains unchanged, during pregnancy, at least in serum, the exact mechanisms is unclear (29,30). It can be speculated that the variants we analyzed alter binding affinity thereby affecting the ability to detect IL-6 in the AF. Since our data support the conclusion that genetic variation in the promoter region of the IL-6 gene, the most important regulatory component of this gene, associates with IL-6 levels it is reasonable to hypothesize that the AF IL-6 is affected more by factors that affect how IL-6 interacts with IL-6R than by transcriptional regulation alone.

In our haplotype/AF analyses opposite trends in AF IL-6 concentrations were observed between cases and controls for some of the same haplotypes. This indicates that the same haplotypes can affect IL-6 concentrations as a function of status and ethnicity. Haplotype trend regression analyses within cases and controls for AF concentrations revealed different trends in AF haplotype levels between ethnic groups in cases with MIAC further supporting this conclusion.

We were underpowered to detect an association with our MIAC subset in our samples; however, we observed association between IL-6 haplotypes and IL-6 concentrations in African-American cases with MIAC, but not in those without MIAC. No differences were seen for cases with and without MIAC for any of the other associated haplotypes with cytokine concentration as outcome. This is indicative of an environmental influence (i.e. infection) on IL-6 production with African-American fetal genotype, but not in the others. However, in previous studies we observed that at the single SNP level MIAC plays a strong regulatory role on IL-6 production within Caucasian maternal samples (25) especially at rs1800797. Interestingly, rs1800797 overlaps with the haplotypes found to associate with MIAC in African-American fetal data. These data further support the hypothesis that a gene–environment interaction is occurring in PTB in both African-American fetal and Caucasian maternal genes; the mechanism, however, is unclear but is consistent with a strong regulatory role by the markers within the region, including rs1800796 in the IL-6 gene and this result is consistent across ethnic groups.

Previous results and our present results indicate that both IL-6 and IL-6R haplotype variation contribute to the variations in IL-6 concentrations in both ethnic groups. Different maternal and fetal effects are observed in the two groups. Our dichotomous and continuous analyses were consistent for variants in IL-6 and/or elevated IL-6 concentrations being a risk factor for PTB. Results also suggest that some haplotype effects may be common across African-Americans and Caucasians, although our analyses were designed to increase chances of detecting commonalities. Our data also support the hypothesis that the regulation by genetic variation is dependent on a variety of other factors such as infection, but others may be operating, including patterns of variation at other genes related to inflammatory processes. Demonstrating the role of other factors will, however, require further investigation. Although we identified interesting statistical associations, the interpretation of their biological relevance is currently unclear. Functional studies will need to be performed to assess the biological implications of these associations and these gene regions in IL-6 and IL-6R. In conclusion, haplotype association analyses revealed three regions in IL-6 and IL-6R that associate with AF IL-6 in PTB.


   MATERIAL AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIAL AND METHODS
SUPPLEMENTARY MATERIAL
 FUNDING
 REFERENCES
 
Study population
Caucasian and African-American subjects were recruited at the Centennial Medical Center, Nashville, TN. Institutional Review Boards at TriStar Nashville and Vanderbilt University, Nashville, TN, approved this study. All included pregnancies were singleton live births. Ethnicity was identified by self-report and a questionnaire that traces ethnicity back two generations from the parents. Individuals who had more than one ancestry were excluded from the study. We recruited mothers between the ages of 18 and 40. Gestational age was determined by last menstrual period and corroborated by ultrasound dating. In our study, cases (PTB) were defined as presence of labor (2 contractions/10 min with documented cervical changes) at <360/7 weeks gestation followed by delivery. We excluded subjects with multiple gestations, preeclampsia, preterm premature rupture of the membranes, placental previa, fetal anomalies, gestational diabetes, poly- and oligohydramnios, and other complications such as surgeries during pregnancies. The controls consisted of women having normal labor and delivery at term (≥370/7 weeks) with no medical or obstetrical complications during pregnancy. We used non-contiguous gestational ages to define cases and controls in order to minimize overlap of phenotypes.

MIAC was defined either by presence of microbial 16s ribosomal DNA (TaqMan Assay, CA, USA) detected by polymerase chain reaction (PCR) and/or clinical evidence. Microbial cultures were not attempted since the PCR-based detection of microbes is much more sensitive than traditional cultures (31,32). Cases with clinical evidence of MIAC were those individuals having three or more of the following criteria: abdominal tenderness, temperature>40°C, foul smelling vaginal discharge, an elevated C-reactive protein (CRP) or histologic chorioamnionitis. Another study performed PCR to detect presence of bacteria in a subset of 25 control samples and revealed no evidence of MIAC (33,34).

DNA sampling and genotyping
The total number of DNA samples included Caucasian (maternal samples: 145 cases and 194 controls; fetal samples: 140 cases and 179 controls) and African-American samples (maternal samples: 76 cases and 191 controls; fetal samples: 66 cases and 183 controls). DNA was isolated from maternal and fetal blood samples using the Autopure automated system (Gentra Systems, Minneapolis, MN, USA).

A total of 30 SNPs were screened in IL-6 and IL-6R genes (eight in IL-6 and 22 in IL-6R). We used SNPs from our previous publication (35) and additional SNPs based on their ability to tag surrounding variants from the HapMap (http://www.hapmap.org). The criteria for Caucasian tag SNPs were a minor allele frequency (MAF) of 0.07 and for African-Americans a MAF of 0.20. For both we used an LD cut-off of r2 = 0.8. The rs numbers of SNPs from the NIH database, chromosome, base pair position on chromosome, and SNP function are shown in Table 8. We did not use functional significance of SNPs as selection criteria with the exception of IL-6–237 (rs1800795 also reported as –174) that was previously shown to associate with PTB and IL-6 expression (36). Genotyping was done using the Illumina GoldenGate genotyping system (Illumina, San Diego, CA, USA).

Cytokine measurements
AF samples were collected during labor [either preterm (cases) or term (controls)] by transvaginal amniocentesis before rupture of the membranes and before preterm or term vaginal deliveries by puncture of intact membrane using a 22-gauge needle. A few samples were also collected at the time of cesareans. AF was centrifuged immediately for 10 min at 2500 RPM to remove cellular and particulate matter. Aliquots of AF were stored at –70°C until analysis. AF samples were measured from Caucasian (105 cases and 100 controls) and African-American mothers (41 cases and 91 controls). Among these the following had genetic data: Caucasian (82 maternal cases and 40 maternal controls; 78 fetal PTBs and 36 fetal controls); African-American (33 maternal cases and 57 maternal controls; 33 fetal cases and 57 fetal controls). AF IL-6 was measured by multiplex immunoassay (Biosource International, Camarillo, CA, USA) using LuminexTM (Austin, TX, USA). The assay protocol is described elsewhere in detail (33). The sensitivity of the assay was 1 pg/ml.

Statistical analysis
Shapiro–Wilks tests of normality were performed on gestational age, gestational weight, APGAR 1, APGAR 5, and maternal age. All measurements deviated significantly from normality with the exception of maternal age; as a result Mann–Whitney two-sample rank-sum tests was used to test for statistical differences between medians of cases and controls (37); t-tests were used to test for statistical differences between case and control means for maternal age. STATA 9.0 statistical software (38), College Station, TX, USA, was used for all analyses.

Statistical tests for differences in single locus allele and genotype frequencies between ethnic groups and deviations from Hardy–Weinberg equilibrium (HWE) were performed by the use of Powermarker statistical software (39,40). Statistical significance for these analyses was determined using Fishers Exact tests.

Pairwise LD was characterized and haplotype frequencies were calculated using Powermarker (39,40) and HaploView (41) statistical software. Standard summary statistics D' and r2 were calculated using HaploView (42). Haplotype blocks were assigned, using the D' confidence interval algorithm created by Gabriel et al. (43). Both Powermarker and HaploView use an EM algorithm to determine haplotype frequency distributions when phase is unknown. The Powermarker haplotype trend analysis was performed with outcome as both dichotomous and continuous with 2, 3 and 4 marker sliding windows. This analysis is a regression approach to test haplotype–trait association. The test for association uses an F-test for a specialized additive model. Haplotype trend analyses produce global P-values for tests of haplotype associations and not haplotype specific P-values. Log transformed cytokine concentration was used for these analyses because the untransformed data were not normally distributed according to a Shapiro–Wilks test. We performed analyses for cytokine concentrations initially on pooled case–control samples within Caucasians and within African-Americans in order to narrow down the regions of interest for follow up with haplotype analyses, stratified by status and ethnicity. This was done under the presumption that pooled analysis would reveal most haplotype associations. For continuous outcomes, we calculated P-values within all of the cytokine-genotype data and then within each status group, and within cases with and without MIAC.

For case–control analyses the haplotypes with the most significant global associations were analyzed for haplotype specific effects. This included the calculation of Odds Ratios (OR) for each haplotype, as well as determination of case and control haplotype frequencies. To determine the effect sizes for haplotypes with continuous outcomes, r2 were calculated [log(IL-6)] using regression analyses from STATA 9.0 statistical software (38), College Station, TX, USA. The highest frequency haplotype was used as the reference haplotype for both OR and r2 analyses.


   SUPPLEMENTARY MATERIAL
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIAL AND METHODS
 SUPPLEMENTARY MATERIAL
FUNDING
 REFERENCES
 
Supplementary material is available at HMG Online

Conflict of Interest statement. None declared.


   FUNDING
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIAL AND METHODS
 SUPPLEMENTARY MATERIAL
 FUNDING
REFERENCES
 
This study was supported by a grant from Thrasher Research Funds (to S.J.F), and by the Maternal Fetal Group, Nashville, TN, USA.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIAL AND METHODS
 SUPPLEMENTARY MATERIAL
 FUNDING
 REFERENCES
 

  1. Goldenberg R.L., Jobe A.H. Prospects for research in reproductive health and birth outcomes. JAMA (2001) 285:633–639.[Abstract/Free Full Text]

  2. Goldenberg R.L., Andrews W.W. Intrauterine infection and why preterm prevention programs have failed. Am. J. Public Health (1996) 86:781–783.[Free Full Text]

  3. Martin J.A., Kochanek K.D., Strobino D.M., Guyer B., MacDorman M.F. Annual summary of vital statistics–2003. Pediatrics (2005) 115:619–634.[Abstract/Free Full Text]

  4. Khoury M.J., Calle E.E., Joesoef R.M. Recurrence of low birth weight in siblings. J. Clin. Epidemiol. (1989) 42:1171–1178.[CrossRef][Web of Science][Medline]

  5. Treloar S.A., Macones G.A., Mitchell L.E., Martin N.G. Genetic influences on premature parturition in an Australian twin sample. Twin Res. (2000) 3:80–82.[CrossRef][Medline]

  6. Varner M.W., Esplin M.S. Current understanding of genetic factors in preterm birth. BJOG. (2005) 112(Suppl. 1):28–31.[CrossRef][Web of Science][Medline]

  7. Carr-Hill R.A., Hall M.H. The repetition of spontaneous preterm labour. Br. J. Obstet. Gynaecol. (1985) 92:921–928.[Web of Science][Medline]

  8. Porter T.F., Fraser A.M., Hunter C.Y., Ward R.H., Varner M.W. The risk of preterm birth across generations. Obstet. Gynecol. (1997) 90:63–67.[CrossRef][Web of Science][Medline]

  9. Goldenberg R.L., Andrews W.W. Intrauterine infection and why preterm prevention programs have failed. Am. J. Public Health (1996) 86:781–783.[Free Full Text]

  10. Clausson B., Lichtenstein P., Cnattingius S. Genetic influence on birthweight and gestational length determined by studies in offspring of twins. BJOG. (2000) 107:375–381.[Medline]

  11. Hillier S.L., Martius J., Krohn M., Kiviat N., Holmes K.K., Eschenbach D.A. A case–control study of chorioamnionic infection and histologic chorioamnionitis in prematurity. N. Engl. J. Med. (1988) 319:972–978.[Abstract]

  12. Romero R., Mazor M. Infection and preterm labor. Clin. Obstet. Gynecol. (1988) 31:553–584.[CrossRef][Web of Science][Medline]

  13. Romero R., Avila C., Santhanam U., Sehgal P.B. Amniotic fluid interleukin 6 in preterm labor. Association with infection. J. Clin. Invest (1990) 85:1392–1400.[Web of Science][Medline]

  14. Romero R., Espinoza J., Goncalves L.F., Kusanovic J.P., Friel L.A., Nien J.K. Inflammation in preterm and term labour and delivery. Semin. Fetal Neonatal Med. (2006) 11:317–326.[CrossRef][Web of Science][Medline]

  15. Macones G.A., Parry S., Elkousy M., Clothier B., Ural S.H., Strauss J.F. III. A polymorphism in the promoter region of TNF and bacterial vaginosis: preliminary evidence of gene-environment interaction in the etiology of spontaneous preterm birth. Am. J. Obstet. Gynecol. (2004) 190:1504–1508.[CrossRef][Web of Science][Medline]

  16. Roberts A.K., Monzon-Bordonaba F., Van Deerlin P.G., Holder J., Macones G.A., Morgan M.A., Strauss J.F. III, Parry S. Association of polymorphism within the promoter of the tumor necrosis factor alpha gene with increased risk of preterm premature rupture of the fetal membranes. Am. J. Obstet. Gynecol. (1999) 180:1297–1302.[CrossRef][Web of Science][Medline]

  17. El-Bastawissi A.Y., Williams M.A., Riley D.E., Hitti J., Krieger J.N. Amniotic fluid interleukin-6 and preterm delivery: a review. Obstet. Gynecol. (2000) 95:1056–1064.[CrossRef][Web of Science][Medline]

  18. Yoon B.H., Romero R., Park J.S., Kim M., Oh S.Y., Kim C.J., Jun J.K. The relationship among inflammatory lesions of the umbilical cord (funisitis), umbilical cord plasma interleukin 6 concentration, amniotic fluid infection, and neonatal sepsis. Am. J. Obstet. Gynecol. (2000) 183:1124–1129.[CrossRef][Web of Science][Medline]

  19. Hartel C., Finas D., Ahrens P., Kattner E., Schaible T., Muller D., Segerer H., Albrecht K., Moller J., Diedrich K., Gopel W. Polymorphisms of genes involved in innate immunity: association with preterm delivery. Mol. Hum. Reprod. (2004) 10:911–915.[Abstract/Free Full Text]

  20. Fishman D., Faulds G., Jeffery R., Mohamed-Ali V., Yudkin J.S., Humphries S., Woo P. The effect of novel polymorphisms in the interleukin-6 (IL-6) gene on IL-6 transcription and plasma IL-6 levels, and an association with systemic-onset juvenile chronic arthritis. J. Clin. Invest (1998) 102:1369–1376.[Web of Science][Medline]

  21. Rafiq S., Frayling T.M., Murray A., Hurst A., Stevens K., Weedon M.N., Henley W., Ferrucci L., Bandinelli S., Corsi A.M., et al. A common variant of the interleukin 6 receptor (IL-6r) gene increases IL-6r and IL-6 levels, without other inflammatory effects. Genes Immun (2007) 8:552–559.[CrossRef][Web of Science][Medline]

  22. Velez D.R., Menon R., Thorsen P., Jiang L., Simhan H., Morgan N., Fortunato S.J., Williams S.M. Ethnic differences in interleukin 6 (IL-6) and IL6 receptor genes in spontaneous preterm birth and effects on amniotic fluid protein levels. Ann. Hum. Genet. (2007) 71:586–600.[CrossRef][Web of Science][Medline]

  23. Terry C.F., Loukaci V., Green F.R. Cooperative influence of genetic polymorphisms on interleukin 6 transcriptional regulation. J. Biol. Chem. (2000) 275:18138–18144.[Abstract/Free Full Text]

  24. Johnson G.C., Esposito L., Barratt B.J., Smith A.N., Heward J., Di G.G., Ueda H., Cordell H.J., Eaves I.A., Dudbridge F., et al. Haplotype tagging for the identification of common disease genes. Nat. Genet. (2001) 29:233–237.[CrossRef][Web of Science][Medline]

  25. Velez D.R., Menon R., Thorsen P., Jiang L., Simhan H., Morgan N., Fortunato S.J., Williams S.M. Ethnic differences in interleukin 6 (IL-6) and IL6 receptor genes in spontaneous preterm birth and effects on amniotic fluid protein levels. Ann. Hum. Genet. (2007) 71:586–600.[CrossRef][Web of Science][Medline]

  26. Reich D., Patterson N., Ramesh V., De Jager P.L., McDonald G.J., Tandon A., Choy E., Hu D., Tamraz B., Pawlikowska L., et al. Admixture mapping of an allele affecting interleukin 6 soluble receptor and interleukin 6 levels. Am. J. Hum. Genet. (2007) 80:716–726.[CrossRef][Web of Science][Medline]

  27. Rose-John S., Scheller J., Elson G., Jones S.A. Interleukin-6 biology is coordinated by membrane-bound and soluble receptors: role in inflammation and cancer. J. Leukoc. Biol. (2006) 80:227–236.[Abstract/Free Full Text]

  28. Scheller J., Ohnesorge N., Rose-John S. Interleukin-6 trans-signalling in chronic inflammation and cancer. Scand. J. Immunol. (2006) 63:321–329.[CrossRef][Web of Science][Medline]

  29. Lien E., Liabakk N.B., Austgulen R. Detection of soluble receptors for tumor necrosis factor, interleukin-2 and interleukin-6 in retroplacental serum from normal pregnant women. Gynecol. Obstet. Invest. (1996) 41:1–4.[Web of Science][Medline]

  30. Matsuzaki N., Neki R., Sawai K., Shimoya K., Okada T., Sakata M., Saji F., Koishihara Y., Ida N. Soluble interleukin-6 (IL-6) receptor in the sera of pregnant women forms a complex with IL-6 and augments human chorionic gonadotropin production by normal human trophoblasts through binding to the IL-6 signal transducer. J. Clin. Endocrinol. Metab. (1995) 80:2912–2917.[Abstract/Free Full Text]

  31. Gardella C., Riley D.E., Hitti J., Agnew K., Krieger J.N., Eschenbach D. Identification and sequencing of bacterial rDNAs in culture-negative amniotic fluid from women in premature labor. Am. J. Perinatol. (2004) 21:319–323.[CrossRef][Web of Science][Medline]

  32. Hitti J., Riley D.E., Krohn M.A., Hillier S.L., Agnew K.J., Krieger J.N., Eschenbach D.A. Broad-spectrum bacterial rDNA polymerase chain reaction assay for detecting amniotic fluid infection among women in premature labor. Clin. Infect. Dis. (1997) 24:1228–1232.[Web of Science][Medline]

  33. Menon R., Camargo C., Thorsen P., Fortunator S.J. Amniotic fluid Interleukin-6 increase is an indicator of Preterm Birth in Caucasians but not in blacks. Am. J. Obstet. Gynecol. (2007) 198:77e1–77e7.

  34. Menon R., Jiang L., Morgan N., Lombardi S.J., Williams S.M., Fortunato S.J. Amniotic Fluid Interleukin (IL)-1 and IL-8 Concentrations: Racial Disparity in Spontaneous Preterm Birth. Reprod. Sci (2007) in press.

  35. Velez D.R., Menon R., Thorsen P., Jiang L., Simhan H., Morgan N., Fortunato S.J., Williams S.M. Ethnic differences in interleukin 6 (IL-6) and IL6 receptor genes in spontaneous preterm birth and effects on amniotic fluid protein levels. Ann. Hum. Genet. (2007) 71:586–600.[CrossRef][Web of Science][Medline]

  36. Simhan H.N., Krohn M.A., Roberts J.M., Zeevi A., Caritis S.N. Interleukin-6 promoter -174 polymorphism and spontaneous preterm birth. Am. J. Obstet. Gynecol. (2003) 189:915–918.[CrossRef][Web of Science][Medline]

  37. Hollander M., Wolfe D.A. Nonparametric Statistical Methods (1999) New York: John Wiley & Sons.

  38. StataCorp. (2007) Stata Statistical Software, Reelase 9, College Station, TX.

  39. Zaykin D.V., Westfall P.H., Young S.S., Karnoub M.A., Wagner M.J., Ehm M.G. Testing association of statistically inferred haplotypes with discrete and continuous traits in samples of unrelated individuals. Hum. Hered. (2002) 53:79–91.[Web of Science][Medline]

  40. Liu K., Muse S.V. PowerMarker: an integrated analysis environment for genetic marker analysis. Bioinformatics (2005) 21:2128–2129.[Abstract/Free Full Text]

  41. Barrett J.C., Fry B., Maller J., Daly M.J. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics (2005) 21:263–265.[Abstract/Free Full Text]

  42. Devlin B., Risch N. A comparison of linkage disequilibrium measures for fine-scale mapping. Genomics (1995) 29:311–322.[CrossRef][Web of Science][Medline]

  43. Gabriel S.B., Schaffner S.F., Nguyen H., Moore J.M., Roy J., Blumenstiel B., Higgins J., DeFelice M., Lochner A., Faggart M., et al. The structure of haplotype blocks in the human genome. Science (2002) 296:2225–2229.[Abstract/Free Full Text]


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