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Mannose-Binding Lectin Gene Polymorphisms Are Associated with Gestational Diabetes Mellitus

Endocrinology and Diabetes Unit (A.M., L.G., J.V., I.S., C.G., C.R.), Research Department, University Hospital of Tarragona "Joan XXIII," School of Medicine, Rovira I Virgili University, Tarragona 43007, Spain; and Endocrinology and Diabetes Unit (J.-M.F.-R.), Department of Internal Medicine, University Hospital of Girona "Dr. Josep Trueta," Girona 17007, Spain

Address all correspondence and requests for reprints to: Anna Megia Colet, Secció d’endocrinología, Hospital Universitari "Joan XXIII" de Tarragona, c/Mallafré Guasch, 4.43007 Tarragona, Spain. E-mail: jvo{at}comt.es.

	Abstract

Top Abstract Introduction Patients and Methods Results Discussion References

 
Insulin resistance is a feature of gestational diabetes mellitus (GDM). Inverse correlations between indexes of insulin sensitivity and serum markers of inflammation have been observed and, particularly, TNF- has been shown to be associated with the appearance of insulin resistance in pregnancy. Mannose-binding lectin (MBL) is a protein member of the collectin family. Its deficiency is genetically determined and predisposes to recurrent infections and chronic inflammatory diseases. To test the hypothesis that a genetic predisposition to a proinflammatory state could favor the appearance of GDM during pregnancy, we studied R52C and G54D polymorphisms of MBL2 gene and plasma MBL levels from 105 consecutive GDM women and 173 healthy pregnant women. An association was found between G54D and GDM [odds ratio, 2.03 (1.18–3.49); P < 0.01], and this association remained significant when the presence of both mutated alleles was considered [odds ratio, 1.76 (1.04–2.96); P < 0.05] but not for the R52C. GDM patients who carried the G54D mutation required insulin therapy more frequently (56.4 vs. 30.4%, ² =5.83; P = 0.027) and had heavier infants (3326.4 ± 546.9 vs. 3087.5 ± 395.5 g; P < 0.05) than GDM women homozygous for the wild-type allele. An inverse correlation in GDM patients between neonatal weight and plasma MBL levels (r = –0.320; P = 0.002) was found, remaining significant after adjustment for confounding variables. In conclusion, pregnant women bearing the G54D MBL allele have a greater risk for developing GDM and having heavier infants.

	Introduction

Top Abstract Introduction Patients and Methods Results Discussion References

 
GESTATIONAL DIABETES MELLITUS (GDM) is a heterogeneous disorder in which several environmental and genetic factors may be implicated. The progressive increase in insulin resistance during the course of normal pregnancy (1, 2), particularly in the second and third trimesters, is well known. This diminished insulin sensitivity is more pronounced in patients with GDM. This situation can lead to an increased risk for fetal macrosomia and may be an increased risk for stillbirth. Although classically maternal and placental diabetogenic hormones (human placental lactogen, progesterone, cortisol, and others) have been ascribed as the principal mediators of these alterations in insulin sensitivity, their effects have not been well demonstrated. Recently, some investigators have focused on other factors such as enhanced levels of free fatty acids, maternal adiposity, and new potential mediators of insulin resistance such as TNF- (3, 4) and hormones such as leptin (5), resistin (6), and adiponectin (7). The fact that leptin and TNF- are good predictors of the insulin resistance of pregnancy (3) in addition to the induction of placental genes for chronic stress and inflammatory pathways in GDM is indicative of a role of inflammation in the pathophysiology of GDM (8). Nevertheless, the search for a relationship between GDM and some nonspecific inflammatory parameters as leukocyte count (9) and C-reactive protein (CRP) (10, 11) has yielded inconsistent results.

Mannose-binding lectin (MBL) is a plasma protein synthesized in the liver and released as a component of the acute-phase response (12). It is a member of the collectin family of proteins and is considered an important component of the innate immune system. MBL binds to an array of specific repetitive carbohydrate structures on microbial surfaces and subsequently exerts an antibacterial effect by the activation of the complement cascade through MBL-associated serine proteases, the so-called MBL pathway, or by promoting phagocytosis. MBL levels are genetically determined, although a large interindividual variability exists, in part due to its behavior as a reactant phase protein. It is for this reason that MBL genetic studies have recently gained interest. Three major mutant alleles in exon 1, as well as mutations in the promoter region of the gene, have been associated with MBL deficiency (13, 14). The presence of MBL deficiency in 10% of the population makes it the most frequent immunodeficiency described. Recurrent infections, recurrent miscarriage, and a greater risk of having autoimmune disorders such as systemic lupus erythematosus, rheumatoid arthritis (14), and perhaps type 1 diabetes mellitus (15) have been related with MBL deficiency.

Little is known about the role of genetic conditions associated with a greater risk of infection, low-grade inflammation, and the development of insulin resistance and cardiovascular disease. There have been some reports linking MBL deficiency and the appearance of atherosclerosis. Madsen et al. (16) found that MBL-deficient patients may have earlier atherosclerosis or a more progressive disease. Moreover, Hegele et al. (17) observed that carotid plaque was associated with MBL2 polymorphisms. These data have been recently confirmed (18), supporting a possible link between MBL deficiency that favors an infection/inflammatory state that in turn activates the complement cascade and the release of TNF- and other proinflammatory cytokines and an accelerated atherogenesis. On the other hand, inverse correlations between indexes of insulin sensitivity and serum markers of inflammation have been found (19, 20). In addition, insulin resistance might be induced by the direct action of inflammatory cytokines on insulin signaling postreceptor molecules (21). We hypothesized that MBL deficiency could be involved in the appearance of some insulin-resistant states. To evaluate this question, we have studied in pregnancy a reversible insulin resistance state, the plasma levels and polymorphisms of MBL2. In our study, we have considered two groups of women, one with normal glucose tolerance and the other with GDM. We hypothesized that women with low plasma MBL levels and carrying a MBL2 mutated allele could be at risk for developing GDM, and this situation could also condition the pregnancy outcome.

	Patients and Methods

Top Abstract Introduction Patients and Methods Results Discussion References

 
Patient population

Between January 1999 and February 2001, 105 consecutive pregnant women with GDM were included in a cross-sectional case-control study. They were compared with 173 consecutive pregnant women matched for geographic origin, parity, and body mass index (BMI), (Table 1). The American Diabetes Association criteria were used to define GDM (22). All women had been followed up at the diabetes clinic and the obstetric service of University Hospital "Joan XXIII" from Tarragona (northeast of Spain). During pregnancy in the GDM group, 57.3% women were treated only with diet, and 42.7% were treated with diet plus insulin. All GDM women entered in the same outpatient diabetes education program, with the same team (physician and nurse practitioner) along the gestation period, programing an individualized dietary planning (calculating a diet with 45% of carbohydrates) and 1 h postprandial blood glucose monitoring. When postprandial glucose response exceeded 2-fold 6.7 mmol/l, insulin therapy was started. The control group included 173 healthy women with normal O’Sullivan test during pregnancy. All women were healthy (except for GDM) and were not taking any medication at the time of the study. Each subject gave informed consent before entering the study. The ethical committee of University Hospital "Joan XXIII" approved the study.

Venous blood sample was drawn after overnight fasting between wk 24 and 28, after an O’Sullivan test was performed.

Plasma glucose was measured with a glucose oxidase method using a Hitachi autoanalyzer (Hitachi 1737, Boehringer Mannheim, Marburg, Germany).

Plasma levels of soluble TNF receptor 1 (sTNFR1) and sTNFR2 were determined by a solid-phase enzyme-amplified sensitivity immunoassay (EASIA) performed on a microtiter plate (Medgenix sTNFR1-EASIA and sTNFR2-EASIA, BioSource Europe, Fleurus, Belgium). Intra- and interassay coefficients of variation (CV) were <7 and <9%, respectively. The sTNFR2 EASIA does not cross-react with sTNFR1 and vice versa. TNF- does not interfere with the assay.

Plasma levels of MBL were determined using commercially available MBL ELISA kits (AntibodyShop, Copenhagen, Denmark). The lower detection limit was 5 ng/ml for undiluted samples.

Plasma leptin concentrations were measured by radio immunoassay (Linco Research Inc., St. Charles, MO). The lower detection limit was 0.5 µg/l. Intra- and interassay CV were less than 7 and less than 8%, respectively. The RIA for leptin did not exhibit cross-reactivity with human proinsulin, insulin, or glucagon.

Plasma CRP was measured by a highly sensitive immunonephelometry kit (Dade Behring, Marburg, Germany) (sensitivity, 0.17 mg/liter; intraassay CV, 4.0%).

DNA and PCR methodology

DNA was extracted from EDTA blood samples using MasterPure Genomic DNA Purification Kit (Epicenter, Madison, WI).

The R52C (GT) and G54D (GA), the two most frequently found MBL2 polymorphisms in the European population (14) located in exon 1 of MBL2, were analyzed by sequence analysis. Codon 57 substitution was not analyzed in this study because it has been found to be very rare in the Caucasian population (14). A total of 100 ng genomic DNA was amplified with specific primers derived from the published sequence (GenBank accession no. NM_000242): 5'-TCACTCCCTCTCCTTCTCCT-3' and 5'-GTTCCCCCTTTTCTCCCTTG-3'. All PCR amplifications were carried out on a final volume of 25 µl containing 1x buffer [10 mM Tris-HCl (pH 8.4) and 50 mM KCl)], 1 mM MgCl₂, 0.2 mM each dNTP, 0.2 µM each primer, and 1 U Taq polymerase (GeneCraft, Lüdinghausen, Germany). Amplification conditions consisted of initial denaturation at 94 C for 3 min, followed by 35 cycles of denaturation at 94 C for 30 sec, annealing at 63.1 C for 30 sec, and extension at 72 C for 30 sec. The PCR profile ended with a final extension at 72 C for 10 min. PCRs were carried out using a GeneAmp PCR system 9700 (Applied Biosystems, Foster City, CA). The resulting 169-bp fragment was purified using the High Pure PCR Product Purification Kit (Roche, Mannheim, Germany). Fluorescent-based automated sequencing of amplified product was performed on an ABI PRISM 310 Genetic Analyzer (Applied Biosystems) using dye-terminator methodology (BigDye Terminator version 3.0; Applied Biosystems) according to the manufacturer’s instructions.

Statistical analysis

All statistical analysis was performed by using the SPSS/PC+ statistical package (version 10.0 for Windows, SPSS Inc., Chicago, IL). Descriptive data are expressed as mean value ± SD. Differences in levels between groups were compared by using a Student’s t test or ANOVA of clinical or laboratory parameters. Nonparametric tests were performed when variables did not have a gaussian distribution. Hardy-Weinberg equilibrium was assessed by the ² goodness-of-fit test. MBL genotypes frequencies were compared by contingency table analysis by the ² test. P < 0.05 was considered to be significant. Logistic regression analysis was used to identify determinants of GDM, and odds ratios (ORs) are presented with 95% confidence interval for significant OR.

Multiple linear regression analysis was also used to analyze the independence of the association between quantitative variables (age, pregravid maternal weight, week of delivery, and plasma MBL levels were included as independent variables and infant weight as dependent variable).

	Results

Top Abstract Introduction Patients and Methods Results Discussion References

 
The clinical and biochemical characteristics of the healthy pregnant (HP) and GDM groups are reported in Table 1. The mean age was higher (P < 0.001), and the systolic and diastolic blood pressure were lower (P < 0.05 and P < 0.001, respectively) in the GDM group, whereas BMI, neonatal weight at delivery, and parity were similar in both groups. The GDM group had a significant smaller increase in body weight at the end of pregnancy than the HP group (P = 0.01). Mean serum sTNFR1, sTNFR2, leptin, and MBL levels were comparable between both groups.

MBL2 polymorphisms and risk of GDM

The genotypic and allelic distributions between HP and GDM were consistent with the Hardy-Weinberg equilibrium.

Fifty-two (49.5%) of the 105 women with GDM in which MBL2 was analyzed and 62 (35.88%) of the 173 HP women carried at least one of the MBL2 polymorphisms studied. One patient was heterozygous for both codon 54 and codon 52 mutations. Genotypes and allele frequencies are listed in Table 2. No linkage disequilibrium was observed between these two allelic variants (² = 0.85; P = 0.65).

An association was found between G54D and GDM. Forty-six of the 105 GDM women (43.8%) carried the A allele (AA or AG genotype) compared with 48 (27.9%) of 173 of the HP group [OR, 2.03 (1.18–3.49); P < 0.01], and this association remained significant when the presence of both mutated alleles was considered [OR, 1.76 (1.04–2.96); P < 0.05] (Table 2).

Due to differences in the basal status of many clinical parameters (age, blood pressure, and weight gain) between HP and GDM groups, we performed a multiple logistic regression analysis considering all the mentioned variables including MBL2 polymorphism and the existence of familial type 2 diabetes as independent variables and the presence of GDM as dependent variable. G54D polymorphism was significantly associated with the presence of GDM [B = 0.62; P = 0.006; OR, 2.45 (1.2–2.9)].

Differences within groups according to the G54D polymorphisms

HP group. Clinical and laboratory variables were also analyzed according to the presence of G54D polymorphism. No differences were found in any of the clinical variables among women in the HP group. The levels of MBL were, as expected, higher in the wild-type group (P < 0.001). The levels of sTNFR1, sTNFR2, and leptin were similar in both groups (Table 3).

G54D polymorphisms and insulinization. Patients who belonged to the GDM group and carried the G54D allele were more frequently insulinized (56.4 vs. 30.4%, ² = 5.83; P = 0.027), although the time of insulinization (29.1 ± 6.2 vs. 29.5 ± 5.8 weeks) was not different (Fig. 1). This association was maintained after adjusting for potential confounding variables: age, BMI, smoking status, weight gain, and familial antecedents of type 2 diabetes (B = 1.23; P = 0.016; OR, 1.26–9.37).

View larger version (14K): [in this window] [in a new window]   FIG. 1. Distribution of GDM women treated with insulin according to the presence of G54D mutant allele for the MBL2 gene.

When HP and GDM women homozygous for the wild-type gene were compared, differences in MBL levels and birth weight that had not been found in the whole-group analysis appeared. Women in the HP group had lower mean MBL levels (3.27 ± 0.52 vs. 3.56 ± 0.53; P < 0.01) and heavier infants than GDM patients (3309.9 ± 506.4 vs. 3087.5 ± 395.5 g, P < 0.05).

Differences in neonatal weight were observed when the group who carried the G54D polymorphism was studied. GDM patients had heavier infants than HP women (3326.4 ± 546.9 vs. 3181.2 ± 595.9 g; P < 0.05, respectively) (Table 3).

Correlations/regressions

Table 4 summarizes the correlations observed. To analyze the independence of the association between plasma MBL levels and neonatal weight, a multiple linear regression model was developed. Age, pregravid maternal weight, week of delivery, and plasma MBL levels were included as independent variables and infant weight as dependent variable. All the independent variables remained significantly associated with infant weight in GDM group, except pregravid maternal weight (Table 5).

	Discussion

Top Abstract Introduction Patients and Methods Results Discussion References

 
The results of our study show that the codon 54 mutation of the MBL2 gene confers a greater susceptibility for developing GDM. G54D is by far the most frequent mutation for MBL2 in the European population, followed by the mutation at codon 52. Both mutations are associated with a profound lowering effect on plasma MBL levels. To our knowledge, this study is the first report of an increased risk for developing GDM associated with a MBL2 coding mutation. The lack of association between R52C and DGM could be due in part to the low frequency of this mutation in our pregnant population, although when we considered the presence of any MBL2 coding mutation, the association persisted. As has been previously stated, GDM is the extreme manifestation of the insulin-resistant state that occurs during the second and third trimesters of pregnancy. It is a heterogeneous disorder in which genetic background and environmental factors, such as age and obesity, contribute to the abnormal glucose metabolism. This situation may lead to fetal macrosomia, an increased likelihood of obstetric complications, and, in some cases, increases the risk of stillbirth. Although cortisol and placental hormones had been classically considered the possible pathogenic mechanism, this hypothesis has been recently challenged (3), and the roles of some new mediators that have been implicated in the pathogenesis of insulin resistance, such as TNF- and other proinflammatory cytokines, have gained importance as the possible explanation of insulin resistance in pregnancy.

Therefore, in the line of evidence that insulin resistance is the result of a low-grade chronic inflammatory state, any situation that maintains or perpetuates an inflammatory response will favor the decrease of insulin sensitivity. A major effector function of MBL is the activation of complement, a factor known to influence the inflammatory response (24). In addition, MBL has the ability to enhance phagocytosis (25) and to inhibit TNF- release (26). This cytokine has been repeatedly strongly associated with the degree of insulin resistance. Regarding these observations, we suggest that women carrying the G54D mutation will be less prone to activate the innate immunity response in front of an aggression and make the mother and fetus more susceptible to a prolonged and sustained inflammatory response. Consequently, there will be a sustained release of inflammatory cytokines known to down-regulate the insulin sensitivity, such as TNF-, and this situation, in part, could contribute to the appearance of GDM.

We expected lower mean MBL plasmatic levels in the group of women with GDM than in the HP group, although circulating MBL concentration is largely genetically determined and the presence of a mutant allele is associated with a partial or complete lack of this protein, but plasma levels were comparable. This finding is not in disagree with the group distribution of the G54D polymorphism because individuals heterozygous for mutant alleles encoding MBL2 have a dominant effect causing functional defects through disrupting interactions with associated serine proteases that lead to the disease phenotype (23). In fact, in our study, the main differences in MBL2 genotypic distribution were due to a major prevalence of heterozygous for G54D mutation. In pregnant women, no association was found between R52C mutation and GDM (Table 2), despite that this mutation causes a similar reduction in MBL functional activity and levels as produced by the G54D mutation. This lack of association could be explained by the low frequency of R52C mutation. In addition, the differences observed in neonatal birth weight and MBL levels when the groups were compared according to the presence of the G54D mutation increased its significance when the R52C was added (data not shown).

If we consider that GDM, as any other insulin-resistant state, is the result of an inflammatory situation associated with acute phase proteins release, therefore it is not strange to find higher MBL levels in this group. In fact, a previous study has shown a significant increase in MBL levels in the third trimester of pregnancy that coincides with the time of lower insulin sensitivity (27). On the other hand, there is controversy about the possible biological disadvantage associated with increased MBL levels, which could lead to an increase inflammatory damage (28). Oxidative stress, a feature of GDM and other hyperglycemic conditions, has been recently shown to activate complement by the lectin pathway. One is tempted to speculate that perhaps the increased levels of protein observed in GDM wild-type carriers with respect to the HP women may also represent a compensatory response, a condition that cannot be produced in the mutant forms, at least in the same proportion.

Experimental evidence suggests that in late gestation, fetal growth is controlled by maternal and placental factors (29). It is difficult to estimate the relative influence of these two parameters in determining the rate of intrauterine growth, but it seems that in GDM, excess fetal growth seems to be due to an increased availability of maternal nutrients. The decrease in maternal insulin sensitivity with advancing gestation leads to an increase in glucose and nutrient supply to the feto-placental unit (30) with insulin sensitivity negatively related to fetal fat-free mass and placental weight (31). Placental weight is significantly increased in pregnancies associated with GDM, even when maternal glycemic control is optimal throughout the third trimester (32). In this situation, strict control of maternal glucose values is associated with average fetal weights within normal ranges, although significantly higher than in nondiabetic population. We also found that our gestational diabetic patients had infants with fetal weights in the normal range but were comparable to the ones born from HP mothers, when they were considered as a whole group. However, when the group of pregnant women who were homozygous for the wild-type gene were excluded, fetal birth weight was found to be significantly higher in the gestational group than in the HP group. This difference in favor of a greater fetal weight in mutant forms of GDM patients was maintained when comparing with the wild-type GDM women (Table 4).

Recent experimental data show that intrauterine injection of lipopolysaccharide causes an increase in fetal weight and amniotic fluid volume in pigs supporting a direct role of inflammatory reaction on final fetal weight (33). In humans, there are little data regarding the association between fetal birth weight and MBL2 haplotype. Kruse et al. (34) observed that in-term infants born from mothers with low MBL levels were smaller compared with infants of women with normal MBL levels, and they ascribe these findings to a possible impair in placental function. Our results in the group of healthy women who carried the G54D mutation seem to support these data. However, when we studied the GDM group, the results were opposed. Infants of diabetic mothers who carried the mutated allele were heavier compared with the ones born from diabetic mothers with wild-type genotype. It is difficult to obtain a satisfactory explanation for this difference between healthy and GDM pregnant women because the study was not designed for it, but if we assume that the placental nutrition supply can strongly influence fetal growth in the last trimester, the greater nutrient availability conditioned by this insulin-resistant state could overcome, in GDM patients, the possible impairment of placental function.

Some anthropometrics and clinical variables have been related with intrauterine growth including maternal pregravid weight, which is considered a strong predictor of birth weight. We found a significant relationship between maternal weight and fetal birth weight, but when other variables such as week of delivery, age, and plasma MBL levels were considered, it lost its significance. Plasma MBL levels, age, and week of delivery were independent factors related with fetal birth weight in the GDM group. The inverse correlation between MBL plasma levels and birth weight in GDM women and the presence of heavier newborns in G54D-mutated GDM carriers suggest a participation of the MBL system in the fetal growth, at least in this population.

Abnormal glucose tolerance and hyperglycemia are the result of the insulin-resistant state associated with pregnancy. Because maternal glucose levels have been directly correlated with the risk of accelerated fetal growth and neonatal morbidity, when glucose levels cannot be controlled by diet, insulin therapy is required. Patients homozygous for the wild-type allele were less frequently insulinized compared with patients with the mutant allele. Despite that we have not measured the insulin resistance in this patients, the major basal glucose levels and the more frequent insulin therapy needed during pregnancy in GDM mutated group support a more severe metabolic disturbance in this patients.

In summary, our results suggest that pregnant women with the G54D mutant allele for MBL2 have a higher risk for developing GDM and having heavier infants. We will be aware of new replication studies necessaries to confirm this association before a definitive implication of MBL in GDM may be concluded.

	Acknowledgments

 
We thank Dr. A. García-España for his helpful suggestions.

	Footnotes

 
This work was supported by Red de Centros de Metabolismo y Nutricion Grant C03/08, Red de Grupos de Diabetes Grant G03/212 from the Instituto de Salud Carlos III, by Fondo de Investigacion Sanitaria Grant PI03/1322, and by Ministerio de Ciencia y Tecnologia (Madrid, Spain) Grant BSA2001-0629.

Abbreviations: BMI, Body mass index; CRP, C-reactive protein; CV, coefficient(s) of variation; EASIA, enzyme-amplified sensitivity immunoassay; GDM, gestational diabetes mellitus; HP, healthy pregnant; MBL, mannose-binding lectin; OR, odds ratio; sTNFR, soluble TNF receptor.

Received February 6, 2004.

Accepted June 28, 2004.

	References

Top Abstract Introduction Patients and Methods Results Discussion References

 

1. Catalano PM, Roman-Drago NM, Amini SB, Sims EA 1998 Longitudinal changes in body composition and energy balanced in lean women with normal and abnormal glucose tolerance during pregnancy. Am J Obstet Gynecol 179:156–165[CrossRef][Medline]
2. Catalano PM, Huston LP, Amini SB 1999 Longitudinal changes in glucose metabolism during pregnancy in obese women with normal glucose tolerance and gestational diabetes mellitus. Am J Obstet Gynecol 180:903–906[CrossRef][Medline]
3. Kirwan JP, Hauguel De Mouzon S, Lepercq J, Challier JC, Huston-Presley L, Friedman JE, Calan SC, Catalano PM 2002 TNF- is a predictor of insulin resistance in human pregnancy. Diabetes 51:2207–2213[Abstract/Free Full Text]
4. Winkler G, Cseh K, Baranyi E, Melczer Z, Speer G, Hajós P, Salamon F, Turi Z, Kovacs M, Vargha P, Karadi I 2002 Tumor necrosis factor system in insulin resistance in gestational diabetes. Diabetes Res Clin Pract 56:93–99[CrossRef][Medline]
5. Melczer Z, Banhidy F, Csomor S, Toth P, Kovacs M, Winkler G, Cseh K 2003 Influence of leptin and the TNF system on insulin resistance in pregnancy and their effect on anthropometric parameters of newborns. Acta Obstet Gynecol Scand 82:432–438[CrossRef][Medline]
6. Sagawa N, Yura S, Itoh H, Mise H, Kakui K, Korita D, Takemura M, Nuamah MA, Ogawa Y, Masuzaki H, Nakao K, Fujii S 2002 Role of leptin in pregnancy: a review. Placenta 23(Suppl A):S80–S86
7. Fernandez-Real JM, Lopez-Bermejo A, Casamitjana R, Ricart W 2003 Novel interactions of adiponectin with the endocrine system and inflammatory parameters. J Clin Endocrinol Metab 88:2714–2718[Abstract/Free Full Text]
8. Radaelli T, Varatehpour A, Catalano P, Hauguel-de Mouzon S 2003 Gestational diabetes induces placental genes for chronic stress and inflammatory pathways. Diabetes 52:2951–2958[Abstract/Free Full Text]
9. Wolf M, Sauk J, Shah A, Smirnakis KV, Jiménez-Kimble R, Ecker JL, Thadhani R 2004 Inflammation and glucose intolerance. Diabetes Care 27:21–27[Abstract/Free Full Text]
10. Wolf M, Sandler L, Hsu K, Vossen-Smirnakis K, Ecker JL, Thadhani R 2003 First-trimester C-reactive protein and subsequent gestational diabetes. Diabetes Care 26:819–824[Abstract/Free Full Text]
11. Retnakaran R, Hangley AJG, Raif N, Connelly PW, Sermer M, Zinman B 2003 C-reactive protein and gestational diabetes: the central role of maternal obesity. J Clin Endocrinol Metab 88:3507–3512[Abstract/Free Full Text]
12. Medzhitov R, Janeway C 2000 Innate inmunity. N Engl J Med 343:338–344[Free Full Text]
13. Madsen HO, Garred P, Thiel S, Kurthalzs JA, Laam LU, Ryder LP, Svejgaard A 1995 Interplay between promotor and structural gene variants control basal serum level of mannan-binding protein. J Inmunol 155:3013–3020
14. Kilpatrick DC 2002 Mannan-binding lectin: clinical significance and applications. Biochim Biophys Acta 1572:401–413[Medline]
15. Tsutsumi A, Ikegami H, Takahashi R, Murata H, Goto D, Matsumoto I, Fujisawa T, Sumida T 2003 Mannose binding lectin gene polymorphism in patients with type 1 diabetes mellitus. Hum Immunol 64:621–624[Medline]
16. Madsen HO, Videm V, Svejgaard A, Svennevig JL, Garred P 1998 Association of mannose binding lectin deficiency with severe atherosclerosis. Lancet 352:959–960[CrossRef][Medline]
17. Hegele RA, Ban MR, Anderson CM, Spence JD 2000 Infection-susceptibility alleles of mannose-binding lectin are associated with increased carotid plaque. J Invest Med 48:198–202[Medline]
18. Rugonfalvi-Kiss S, Endrész V, Madsen HO, Burián K, Duba J, Prohászka Z, Karádi I, Romics L, Gönczöl É, Füst G, Garred P 2002 Association of Chlamydia pneumoniae with coronary artery disease and its progression is dependent on the modifying effect of mannose-binding lectin. Circulation 106:1071–1076[Abstract/Free Full Text]
19. Hak AE, Pols HA, Stehouwer CD, Meijer J, Kilian AJ, Hofman A, Breteler MM, Witteman JC 2001 Markers of inflammation and cellullar adhesion molecules in relation to insulin resistance in nondiabetic elderly: the Rotterdam Study. J Clin Endocrinol Metab 86:4398–4405[Abstract/Free Full Text]
20. Fernández-Real JM, Broch M, Ricart W, Casamitjana R, Gutierrez C, Vendrell J, Richart C 1998 Plasma levels of the soluble fraction of tumor necrosis factor receptor 2 and insulin resistance. Diabetes 47:1757–1762[Abstract]
21. Hotamisligil GS, Peraldi P, Budavari A, Ellis R, White MF, Spiegeleman BM 1996 IRS-1-mediated inhibition of insulin receptor tyrosine kinase activity in TNF--and obesity induced insulin resistance. Science 271:665–668[Abstract]
22. American Diabetes Association 2002 Gestational diabetes (position statement). Diabetes Care:S94–S96
23. Wallis R 2002 Dominant effects of mutations in the collagenous domain of mannose binding protein. J Immunol 168:4553–4558[Abstract/Free Full Text]
24. Lehner PJ, Davies KA, Walport MJ, Cope AP, Wurzner R, Orren A, Morgan BP, Cohen J 1992 Meningoccocal septicaemia in a C6-deficient patient and effects of plasma transfusion on lipopolysacharide release. Lancet 340:1379–1381[CrossRef][Medline]
25. Tenner AJ, Robinson SL, Ezekowitz RA 1995 Mannose binding protein (MBP) enhances mononuclear phagocyte function via a receptor that contains the 126.000 M(r) component of the C1q receptor. Immunity 3:485–493[CrossRef][Medline]
26. Soell M, Lett E, Holveck F, Scholler M, Wachsmann D, Klein JP 1995 Activation of human monocytes by streptoccocal rhamnose glucose polymers is mediated by CD14 antigen, and mannan binding protein inhibits TNF- release. J Immunol 154:851–860[Abstract]
27. Kilpatrick DC 2000 Mannan binding lectin concentration during normal human pregnancy. Hum Reprod 15:941–943[Abstract/Free Full Text]
28. Turner MW, Hamvas RM 2000 Mannose-binding lectin: structure, function, genetics and disease associations. Rev Immunogenet 2:305–322[Medline]
29. Gluckman PD, Breier BH, Oliver M, Harding J, Basset N 1990 Fetal growth in late gestation: a constrained pattern of growth. Acta Paediatr Scand 367:105–110
30. Catalano PM, Tyzbir ED, Wolfe RR, Calles J, Roman NM, Amini SB, Sims EA 1993 Carbohydrate metabolism during pregnancy in control subjects and women with gestational diabetes. Am J Physiol 264:E60–E67
31. Catalano PM, Noreen MD, Amini SB 1995 Maternal carbohydrate metabolism and its relationship to fetal growth and body composition. Am J Obstet Gynecol 172:1464–1470[CrossRef][Medline]
32. Taricco E, Radaelli T, Nobile de Santis MS, Cetin I 2003 Fetal and placental weights in relation to maternal characteristics in gestational diabetes. Placenta 24:343–347[CrossRef][Medline]
33. Tuo W, Ott TL, Liu S, Bazer FW 1999 Intrauterine infusion of bacterial lipopolysaccharide (LPS) prior to mating has no adverse effect on fertility, fetal survival and fetal development. Reprod Immunol 42:31–39[CrossRef]
34. Kruse C, Rosgaard A, Steffensen R, Varming K, Jenseniua JC, Christiansen OB 2002 Low serum level of mannan-binding lectin is a determinant for pregnancy outcome in women with recurrent spontaneous abortion. Am J Obstet Gynecol 187:1313–1320[CrossRef][Medline]

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