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Am J Physiol Lung Cell Mol Physiol 290: L1010-L1017, 2006. First published December 16, 2005; doi:10.1152/ajplung.00487.2005
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Genetic and environmental influences of surfactant protein D serum levels

Grith L. Sørensen,1 Jacob v. B. Hjelmborg,2 Kirsten O. Kyvik,2 Mogens Fenger,3 Anette Høj,4 Christian Bendixen,4 Thorkild I. A. Sørensen,5 and Uffe Holmskov1

1Medical Biotechnology Center, Institute for Medical Biology, and 2The Danish Twin Registry, Epidemiology, Institute of Public Health, University of Southern Denmark, Odense; 3Department of Clinical Biochemistry, University Hospital of Copenhagen, Hvidovre; 4Department of Animal Breeding and Genetics, Danish Institute of Agricultural Sciences, Tjele; and 5Danish Epidemiology Science Centre, Institute of Preventive Medicine, Copenhagen University Hospital, Copenhagen, Denmark

Submitted 17 November 2005 ; accepted in final form 15 December 2005


   ABSTRACT
TOP
 ABSTRACT
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
The collectin surfactant protein D (SP-D) is an important component of the pulmonary innate immune system, but SP-D is also present on extrapulmonary epithelial surfaces and in serum, where it has been used as a biomarker for pulmonary disease states. In this study, we investigate the mechanisms defining the constitutional serum level of SP-D and determine the magnitude of the genetic contribution to serum SP-D in the adult population. Recent studies have demonstrated that serum SP-D concentrations in children are genetically determined and that a single nucleotide polymorphism (SNP) located in the NH2-terminal region (Met11Thr) of the mature protein is significantly associated with the serum SP-D levels. A classic twin study was performed on a twin population including 1,476 self-reported healthy adults. The serum SP-D levels increased with male sex, age, and smoking status. The intraclass correlation was significantly higher for monozygotic (MZ) twin pairs than for dizygotic (DZ) twin pairs. Serum SP-D variance was influenced by nonshared environmental effects and additive genetic effects. Multivariate analysis of MZ and DZ covariance matrixes showed significant genetic correlation among serum SP-D and metabolic variables. The Met11Thr variant explained a significant part of the heritability indicating that serum SP-D variance could be decomposed into non-shared environmental effects (e2 = 0.19), additive genetic effects (h2 = 0.42), and the effect of the Met11Thr variations (q2 = 0.39).

surfactant protein D polymorphism; serum marker; interaction of gene and environment; innate immunity

SURFACTANT PROTEIN D (SP-D) is a member of the collectin family of defense lectins that also includes SP-A and mannan binding lectin. SP-D is composed of polypeptide chains of 43 kDa that assemble into homotrimeric subunits. The single peptide is composed of an NH2-terminal cross-linking domain, a collagen region, a coiled-coil neck region, and a C-type lectin carbohydrate recognition domain. The homotrimeric subunits of SP-D may further associate at their NH2 termini to form cruciform molecules with four collagenous arms and peripheral, globular sugar-binding domains. However, higher order multimers of dodecamers have also been identified (7, 18, 30, 51).

SP-D participates in the innate immune response by opsonization or lysis of inhaled pulmonary pathogens (52) and modulates lung inflammation by interaction with macrophage cell surface molecules like signal inhibitory regulatory protein-{alpha}, CD91, and CD14 (10, 42, 49). Mice that lack the SP-D gene develop progressive emphysema, characterized by chronic inflammation, accumulation of surfactant phospholipids, and infiltration of lipid-laden or apoptotic alveolar macrophages (3, 6, 25). SP-D synthesis is found in the lung and in mucosal epithelia (29, 33, 44). Furthermore, SP-D is present in vascular endothelial cells (43a) and in serum (35).

The source of serum SP-D is presently unknown. A recent study has demonstrated that genes are responsible for 91% of the variation in serum SP-D in twin children (21). SP-D is produced constitutively in the lungs, but increased gene expression can be induced by disease, microbial challenge, and lung injury. Baseline serum SP-D in allergic patients was significantly elevated (24), and serum SP-D levels have further been shown to be markers of disease severity in a number of different lung diseases, including allergic bronchopulmonary aspergillosis (26), community-acquired pneumonia (31), interstitial lung diseases in patients with polymyositis (22), acute lung injury (34, 48), and idiopathic pulmonary fibrosis (11). Moreover, certain cytokines, keratinocyte growth factor, and glucocorticoid are known to affect the expression (5, 19).

Three coding single nucleotide polymorphism (SNP) of the SP-D gene (SFTPD, chromosome 10q22.2-23.1) have been described previously, and a growing number of noncoding SFTPD SNP are reported in available databases. One of the SNP results in an alteration of the codon corresponding to amino acid 11 in the mature protein (dbSNP rs721917), where a methionine (Met) is exchanged for a threonine (Thr). The Met11Thr variant has proved particularly interesting as studies on patients with tuberculosis have indicated that the Thr variant may increase the susceptibility to tuberculosis (8), whereas the Met variant was associated with increased respiratory syncytial virus infection susceptibility (28). Furthermore, the Thr11 variant has previously been associated to low serum levels of SP-D in two independent studies and has been shown to be a part of a frequent haplotype that is associated with low serum SP-D levels. The Thr11 variant was further demonstrated to prohibit the oligomerized state of SP-D and thus reduce binding of bacterial ligands (15, 30).

The current study is a part of the twin study of the metabolic syndrome and related components (GEMINAKAR). The metabolic syndrome has recently been associated to innate immunity serum markers such as the acute phase proteins and proinflammatory cytokines (39), and several components in the metabolic syndrome appear with significant genetic dependence (38). As we recently have observed a significant negative association between serum SP-D and body mass index (BMI) (Sørensen, unpublished data), we set out to estimate genetic correlation to metabolic variables to investigate whether the SP-D phenotype might be considered as a part of the core syndrome.

The overall objective of the present study was to estimate the magnitude of the genetic effect on serum SP-D in normal adults. The genetic dependence of serum SP-D was determined by a structural equation model approach using twin-twin correlations adjusted for sex, age, and smoking status. Furthermore, multivariate genetic analysis was implemented to investigate genetic correlation among serum SP-D and factors in the metabolic syndrome. Finally, the contribution to the serum SP-D heritability of the Met11Thr variant was estimated.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
Study population. Danish twins from 18 to 67 yr were enrolled in a study of components of the metabolic syndrome (GEMINAKAR), for which subjects were identified through the population-based Danish Twin Registry (27). Serum SP-D was measured in 1,476 twins. Only intact twin pairs of the same sex were used for heritability analyses (Table 1). Exclusion criteria were pregnancy, breastfeeding, and known diabetes or cardiovascular disease. The twins were self-reportedly healthy. The study was conducted according to the Helsinki declaration and was approved by the Danish Scientific-Ethical Committee.


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  		Table 1. Serum surfactant protein D in study population divided by zygosity

 
DNA was extracted using high-salt precipitation of contaminating proteins from 10-ml whole blood samples. The zygosity of the twins was established using nine polymorphic DNA-based microsatellite markers with the PE Applied Biosystems AmpFISTR Profiler Plus kit.

Measurement of serum SP-D concentrations by ELISA technique. The immunoassay was performed as previously described (31). Briefly, microtiter wells were coated with F(ab')2 anti-human SP-D IgG (K477) by 4°C overnight incubation at 1 µg/ml in bicarbonate buffer, pH 9.6. This incubation and all the following steps were carried out in a volume of 100 ml/well. Washes and incubations were carried out with Tris-buffered saline, 0.05% (vol/vol) Tween 20, and 5 mM CaCl2 (assay buffer). The coated plates were washed and incubated with 200 ml of assay buffer for 15 min at room temperature with rotary shaking. Then the plates were incubated overnight at 4°C with dilutions of serum, calibrator, and control samples and were washed. They were then incubated for 1 h with 0.5 µg of biotinylated monoclonal antibody anti-human SP-D (Hyb 246-4) per milliliter of assay buffer. This incubation and all the following steps were carried out at room temperature and with rotary shaking. After being washed, the plates were incubated for 30 min with horseradish peroxidase-labeled streptavidin (43-4323, Zymed) diluted 1:1,000. After a final wash, the bound enzyme was estimated by adding H2O2/orthophenyl diamin (Kem-En-Tec, Copenhagen, Denmark) substrate solution. The color reaction was stopped after 15-min incubation in the dark by the addition of 150 ml of 1 M H2SO4. The absorbance was read at 492 nm using a multichannel spectrophotometer. The ELISA was set up with a serum calibrator and two quality controls. All twin pairs were analyzed within the same run.

Clinical measurement. Blood samples for determining serum SP-D, total plasma cholesterol, plasma high-density lipoprotein cholesterol (HDL-C), and plasma triglyceride were drawn in the morning after a 10- to 12-h fast. Plasma lipids were analyzed by commercial kits from Boehringer Mannheim, Mannheim, Germany.

Height was measured to the nearest centimeter using a vertical scale with a horizontal moving headboard. Weight was measured to the nearest 0.1 kg using a standing beam scale with the subject in lightweight clothes with shoes removed, and the BMI was calculated [weight (kg)/height (m2)]. Waist circumference was measured using a nonstretching tape on standing subjects midway between the lowest rib and the iliac crest. Hip circumference was measured over the widest part of the gluteal region.

Smoking status was defined as current tobacco smoking (259 women + 236 men) and determined by a questionnaire.

Assay-by-design SNP analysis. Primers and probes for the non-synonymous cytosine (C) to thymine (T) substitution in position 95 in the SFTPD exon 1 resulting in the Met11Thr variant were designed by Applied Biosystems (Assay-by-Design).

In the assay, the reaction was carried out in a final volume of 5 µl (to a final concentration of 900 nM primers and 200 nM probe, respectively) added to dry DNA (15–50 ng) in optical 384-well plates sealed with optical covers. The primer/probe combination was designed to work at one universal set of thermal cycler conditions: 50°C for 2 min, 95°C for 10 min, followed by 40 cycles at 95°C for 15 s and 60°C for 60 s. The thermal cyclers used for this reaction were GeneAmp PCR System 9700 (Applied Biosystems) with 384-well thermal blocks. After thermal cycling, the plates were stored at 4°C (never >48 h) until they could be read by the fluorescent reader.

Fluorescent signals were detected in an ABI PRISM 7900HT Sequence Detection System (Applied Biosystems). Results were collected and analyzed by ABI PRISM SDS 2.1 software for allelic discrimination.

Analyses of twin similarity. The similarity in mono- (MZ) and dizygotic (DZ) twins was assessed using intraclass correlations for the traits. The classic twin study methodology is based on the fact that MZ twins have identical genotypes, whereas DZ twins share, on average, one-half of their genes and are no more genetically related than ordinary siblings. A greater phenotypic similarity in MZ than in DZ twins is to be expected if there is a significant genetic component. The analyses were adjusted (by linear regression) for age, sex, and smoking status. To approximate a bivariate normal distribution, the data were transformed to the logarithmic scale, and probit plots showed that the marginal distributions could be assumed to be normal.

Estimation of heritability. According to standard biometric practice, assuming no epistasis (genetic inter-locus interaction), no gene-environment interaction or correlation, and no assortative mating, the phenotypic variance of individuals can be separated into four variance components: variance due to additive genetic effects (VA), genetic dominance (VD), shared (family) environment (VC), and nonshared (individual-specific) environment (VE), i.e., Vtotal = VA + VD + VC + VE.

Only nonshared environments contribute to dissimilarity within MZ twin pairs because of their genetic identity, whereas the effects of additive genetic factors and genetic dominance may also contribute to dissimilarity within DZ pairs, who share, on average, one-half of the additive and one-quarter of the dominant genetic factors. Hence, for MZ pairs, the covariance matrix is given by Cov(twin 1, twin 2) = VA + VD + VC, whereas for DZ pairs it takes the form Cov(twin 1, twin 2) = 1/2VA + 1/4VD + VC. From the three equations, up to three of the terms VA, VD, VC, and VE can be estimated simultaneously. A full variance component model (ACE) incorporates additive genetic (A), shared environmental (C), and nonshared environmental factors (E). Further reduced variance component models include AE, CE, and E models (individual variance components are fixed, i.e., in the AE submodel the C component is fixed to zero). Although genetic variance is usually ascribed to genes acting in an additive fashion, nonadditive genetic effects such as genetic dominance (D) may also be influential, and the ADE model was likewise tested.

Effects of the covariates on each trait are given by the regression coefficients coming from each covariate added linearly in the model. The method for selecting the best model among submodels followed standard procedures (structural-equation analyses) using the Mx statistical program (http://www.vcu.edu/mx) according to the following criteria (36): 1) a nonsignificant P value in the {chi}2 goodness of fit test; and 2) minimizing the Akaike Information Criterion [AIC = {chi}2 – 2 x degrees of freedom (d.f.)].

Heritability of the four traits (SP-D, HDL-C, cholesterol, and BMI), effects of covariates on traits, and the degree of dependence between the traits were determined using multivariate variance components models (multivariate Cholesky models) (37). There were 300 intact MZ pairs and 300 intact same-sex DZ pairs included in the multivariate analysis. For each trait, the heritability of the trait is the ratio of genetic variance to the total variance of the trait. The multivariate model incorporates the four traits [Vtotal is the (4 x 4) variance and covariance matrix of the 4 traits] and associated covariates and allows estimating the degree of dependence between the traits, i.e., the (Pearson product moment) correlations between the traits and the genetic and environmental components of the traits. Furthermore, the extent to which the same genetic factors contribute to the observed phenotypic correlation, that is, the degree of pleiotropy of possible genes influencing the traits, is obtained from the model by estimating the genetic correlations, that is, the mutual correlations between the additive genetic factors A of the traits. The method for selecting the best model followed standard procedures. However, for the multivariate model selection, we considered only submodels for which components are estimated for all traits or neither trait.

Association between genotype and phenotype. Association between the Met11Thr variant and SP-D in the whole population was initially assessed by one-way ANOVA (with robust estimation of variance of phenotypes for individual twins clustered into pairs because of possible within-pair dependence). Association analysis was performed using the variance components models of association implemented in the Quantitative Transmission Disequilibrium Test (QTDT) program (http://www.sph.umich.edu/csg/abecasis/QTDT). This is based on the variance component framework and can test association and population stratification. All analyses were controlled for gender, age, and smoking status effects using residuals from linear regression as described above. We tested for association in QTDT using the model by Fulker et al. (9), allowing for the effects of polygenes, shared family environment, and nonshared environment. The program SimWalk2 (http://genetics/ucla.edu/home/software/simwalk2) was used to calculate identity by descent probabilities. This model allows for the partitioning of observed association into between-pair and within-pair components, thus providing a check on whether results could have arisen because of unsuspected population stratification among the pairs studied. There is no adjustment of the mean levels for zygosity.

Differences in the allelic distribution from those expected by the Hardy-Weinberg equilibrium and the significance of differences in the observed frequencies of the SNP in both groups were assessed by the {chi}2 test. P < 0.05 was considered statistically significant.


   RESULTS
TOP
 ABSTRACT
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 GRANTS
 REFERENCES
 
Table 1 shows the concentrations of serum SP-D in the twin population and in MZ twins and DZ twins separately. SP-D is comparable in MZ and DZ twins. Correlation diagrams for SP-D measured in MZ and DZ twins are given in Fig. 1. Each dot represents the serum SP-D level in a pair of twins with one twin assigned to the abscissa and the other to the ordinate. A clear clustering of logarithmic values of serum SP-D [ln(SP-D)] around the 45° identity line was seen for MZ twins, whereas a scattered or circular pattern was seen for DZ twins, respectively, indicating that genes are important contributors to variance in serum SP-D.


Figure 1
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  		Fig. 1. Correlation diagrams (within-pair resemblance) for ln(SP-D) (no unit) for monozygotic (MZ) and all dizygotic (DZ) twins. Line of identity is indicated for MZ twins. SP-D, surfactant protein D.

 
Moreover, a significant proportion of the variance in SP-D was accounted for by gender, age, and smoking status (Table 2). Figure 2A shows the effect of age and sex on the median serum SP-D measurements in the twin population, and Fig. 2B compares the serum levels of SP-D between the smoking and the nonsmoking twin within MZ pairs. The MZ and DZ intraclass correlations were calculated from residuals from the regression analysis including sex, age, and smoking status and showed that the correlation coefficient was almost twice as large in the MZ twins as in the DZ twins (Table 2).


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  		Table 2. Univariate analysis: heritability model

 

Figure 2
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  		Fig. 2. A: median serum SP-D levels in women ({blacklozenge}) and men ({blacksquare}) according to age group. Vertical lines indicate the 95% confidence interval. B: correlation diagram (within-pair resemblance) for ln(SP-D) in MZ twin pairs where 1 twin is a smoker and the other twin of the pair is a nonsmoker.

 
Five biometric models were fitted to the adjusted SP-D data (Table 2). The AE model gave the best fit by AIC, indicating that additive genetic factors and nonshared environmental factors were important.

Heritability of serum SP-D was estimated using the above univariate AE model to h2 = 0.83. Afterward, we set out to estimate heritability coefficients, effects of covariates, and dependencies among serum SP-D and traits related to the metabolic syndrome (i.e., mutual phenotypic correlation and genetic correlation of the traits in a multivariate analysis). We found no evidence that different genes should affect serum SP-D in men and women. Table 3 shows the plasma levels of HDL-C, cholesterol, and BMI in the twin population. In all the traits, the common environmental effects were small and not significantly different from zero (not shown). The AE model was then used to estimate the heritability coefficients, effects of covariates, and dependencies among the traits. The heritability estimates, when adjusting for effects of gender, age, and smoking status and when allowing for possible dependencies between the traits, varied between 0.66 for HDL-C and 0.83 for SP-D (Table 4). Mutual correlations are given in Table 5, and a small negative phenotypic correlation was found between SP-D and BMI. The genetic correlations between the traits were different from but close to zero (for SP-D vs. BMI, HDL-C vs. cholesterol, and HDL-C vs. BMI), which may indicate that the common genetic contribution to the regulation of the traits, i.e., pleiotropy, is limited.


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  		Table 3. Summaries of traits

 

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  		Table 4. Multivariate analysis: heritability

 

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  		Table 5. Multivariate analysis: dependencies

 
The Met11Thr variant was in Hardy-Weinberg equilibrium, and the frequencies of the genotypes, Thr/Thr = 0.18, Met/Thr = 0.43, and Met/Met = 0.36, were comparable to the frequencies reported in other populations (28, 30). Evidence for an association between the Met11Thr variant and SP-D was found by ANOVA (P = 0.0004; Table 6). This association was confirmed using twin analysis [QTDT, {chi}2 = 11.06 (414 d.f.) P = 0.0009] performed using the genetic model by Fulker et al. (9) (Table 7). The model takes possible population stratification into account, and we did not find any evidence of population stratification. The QTDT program estimate of heritability according to an AE model was similar to the one obtained with the Mx program (h2 = 0.83). According to the QTDT association analysis including the Met11Thr variant (AEQ model), the serum SP-D variance can be decomposed into environmental effects (e2 = 0.19), polygene effects (h2 = 0.42), and the presence of Met11Thr variants (q2 = 0.39), indicating that the genetic variant accounts for 39% of the phenotypic variance.


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  		Table 6. Relationship between the Met11 Thr variant and serum SP-D

 

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  		Table 7. Association: variance components

 

   DISCUSSION
TOP
 ABSTRACT
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
GRANTS
 REFERENCES
 
The current study investigated heritability of serum SP-D. The study showed that the serum SP-D level was significantly increased by male sex, increasing age, and current smoking. Serum SP-D variation was largely determined by additive genetic factors, but individual environment also contributes to variation. Furthermore, a large proportion (approximately one-half) of the genetic variation could be explained by a single genetic variant (Met11Thr) or the haplotype it may represent. The study also found evidence that serum SP-D to a small but significant degree is determined by genes also affecting BMI.

Clinically, the serum SP-D level has been used as biomarker for interstitial lung disease (1, 45), and we suggest that stratification may add prognostic information in addition to the SP-D measurement in patients with pulmonary disease. The study indicates that the selection of an appropriate control sample for use in case-control studies of association requires serious deliberation. Unrelated controls with same sex, age, and smoking status may render the resulting analysis less susceptible to spurious association. Although not investigated in this study, history of smoking status may likewise be of importance for the potential use of serum SP-D as disease marker, especially in patients with pulmonary disease, which is related to smoking-induced pathology.

Regulation of the serum SP-D concentration is largely unknown. SP-D is synthesized by endothelial cells (43a), yet it is unknown if endothelial cells secrete SP-D into the circulation. In addition, SP-D is expressed by a series of epithelial tissues and by pulmonary Clara cells and type II cells (33, 50). Because SP-D is mainly synthesized within the respiratory tract, the occurrence in the vascular compartment has so far been explained by leakage from the lung into the bloodstream and the constitutional serum level of SP-D may represent constitutive lung leakage. SP-D further shows variations in the serum of patients with different lung diseases and subjects exposed to lung toxicants. There is evidence for relationships between changes in levels of lung secretory proteins in blood and abnormalities in various diagnostic tests. Such correlation may exist due to loss of integrity of the air-blood barrier typical of acute respiratory distress syndrome. The loss of integrity is responsible for the outward intravascular leakage of lung secretory proteins and the inward edematous flooding of the interstitium and air spaces. The advantages of measuring serum SP-D instead of lung lavage SP-D are that the measurement of lung-specific secretory proteins in serum avoids the intrinsic danger and artifacts associated with the instillation of fluid into the airways and that the measurements are far more easily obtained. If the air-blood barrier is damaged, the levels of lung secretory proteins in serum most likely reflect changes in the permeability of the air-blood barrier to macromolecules. These subjects are thoroughly reviewed by Hermans and Bernard (16) in relation to the use of lung epithelial proteins as serum biomarkers for pulmonary disease. In addition, it was previously published that bronchoalveolar SP-D was significantly decreased in smokers (2). In contrast, we observed a significant increase in serum SP-D in smokers. This could imply either that SP-D is differently regulated in the two compartments or that retrograde flooding of SP-D into the lung is somehow inhibited as a consequence of smoking.

We further aimed at the assessment of genetic, shared, and nonshared environmental determinants of serum SP-D levels. The results of the study are subject to various limitations. First, the study population was based on voluntary participation and may not be representative of the whole population. Second, the relationship between variables may be moderated by factors not accounted for in this study. Third, genetics of serum SP-D were characterized in a self-reported healthy cohort. It is known that serum SP-D is upregulated by pulmonary disease (20, 45), and alternative genetics could be speculated to influence the induced expression. Incorrect classification of health status, therefore, may reduce the estimate of the genetic contribution to basal variation, which would be most accurate in the uninduced state. However, genes involved in monogenic diseases were previously shown to act as quantitative trait loci in the general population, which support the close relationship between physiological and pathological processes (4, 23). Thus the genetic effect on the constitutional levels of SP-D may be important in the pathogenesis of infectious disease or other SP-D-associated conditions because of its importance for activating an adequate immune response.

Measured serum SP-D levels were in accordance with the serum levels of healthy Danish populations in previously published studies using the same ELISA assay (21, 29–31). Assay measurements correlate (r = 0.88) to measurements obtained using the commercially available SP-D assay used in the above-mentioned clinical studies, although that assay measures lower levels. Moreover, serum SP-D appeared with levels and variance comparable to the well-described collectin mannan binding lectin, where low levels have been associated with infectious disease as well as autoimmune disease (46). The main finding is that serum SP-D in the normal adult human is strongly influenced by genetic variance (h2 = 0.83). The contribution of genetic variation to levels of SP-D in the adult twins in our study was comparable yet somewhat smaller than the genetic contributions published for the children (h2 = 0.91) (21). Moreover, mean serum SP-D levels were raised from 741 ng/ml in the children to 1,105 ng/ml in the adults. It was expected that the effect of genetic factors could differ in the adult twins because of different environmental exposures. The result of our study support this hypothesis, reducing the relative impact of genetic influence of the trait, but it remains unclear how much of the difference in heritability that can be attributed to age vs. other population characteristics. The AE variance component model gave the best statistical fit for both sets of data, supporting that inter-locus interaction or family-specific environment do not affect the variance in serum SP-D from childhood to adult life.

Multivariate analysis yielded a similar pattern of results. Like SP-D, some of the metabolic variables (BMI, cholesterol, and HDL-C) have a large genetic component. There is increasing evidence in support of genetic effects underlying the clustering of the factors. The innate immune factor C-reactive protein and candidate genes and gene polymorphisms, encoding proteins involved in glucose and lipid metabolism, hemostasis, blood pressure, and endocrine metabolism, including alleles of the glucocorticoid receptor gene, have been associated with the metabolic disorders, although the functional significance of the associations remains to be established (12, 32, 40, 47). Heritabilities of BMI have previously been determined in this sample of Danish twins. The reported heritability for women and men, respectively, was 0.58/0.63 (43). The observed phenotypic correlation between serum SP-D and BMI suggest that the two variables could be genetically correlated, i.e., that they are subject to the same gene regulatory mechanisms. In this regard, the multivariate analysis showed that pleiotropy between SP-D and BMI was rather limited in this cohort but significantly different from zero and indicated that genes negatively affecting serum SP-D are involved in the positive regulation of BMI. The nature of the association and the biological effect of SP-D in relation to BMI is unknown. Nevertheless, the small genetic correlation may reflect the modest contribution to the pathophysiology of a single factor participating in a multifactorial disorder.

The known promoter sequence in the SFTPD gene indicates that SP-D synthesis contains various gene regulatory sequences including AP-1, E-box, and sequences implicated in modulation of the acute phase response, including the NF-IL-6 consensus sequence (13, 14, 41). Three biallelic polymorphisms, which alter a single amino acid, have been localized in the SP-D gene (Met11Thr, Ala160Thr, and Ser270Thr). The allelic frequencies of Met11 and Thr11 homozygotes and different disease associations indicate diverse pattern recognition specificities and thus immunological function of the two coexisting structural variants. It is currently not known whether the available techniques for measuring SP-D concentrations detect the SP-D variants with equal efficacy.

Finally, using the homogenous Danish twin sample and the QTDT approach, this study confirmed that the Met11Thr variant is associated with the SP-D serum level in adults and it explained 39% of the phenotype variation. The novelty of the study relates to our ability to examine the relationship in a twin-based study of normal adults. The exact "causal alleles" within SFTPD that influence serum SP-D are still unknown, and Met11Thr variation may reflect an underlying haplotype variation. Therefore, it is necessary to perform further statistical and molecular genetic studies (including functional studies) to better understand the role of genetic variation in determination of the phenotype. The genetic effects determining the variance in serum SP-D in healthy persons may ultimately provide an understanding of the function of SP-D in both resistance toward and susceptibility for pulmonary infections and inflammatory disorders.


   GRANTS
TOP
 ABSTRACT
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
REFERENCES
 
This work was supported by grants from the Danish Medical Research Council, the Novo-Nordic Foundation, Fonden til Lægevidenskabens Fremme, the Danish Heart Association, the Benzon Foundation, the Augustinus Foundation, and the Becket Foundation.


   FOOTNOTES
 

Address for reprint requests and other correspondence: G. L. Sørensen, Medical Biotechnology Center, Institute for Medical Biology, Univ. of Southern Denmark, Winsloewparken 25.3, DK-5000 Odense, Denmark (e-mail: glsorensen{at}health.sdu.dk)

The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.


   REFERENCES
TOP
 ABSTRACT
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 

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