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(The FASEB Journal. 2001;15:978-987.)
© 2001 FASEB

Genome-wide search for loci controlling serum IGF binding protein levels of mice

GUDRUN A. BROCKMANN*1, CHRIS S. HALEY{dagger}, ECKHARD WOLF{ddagger}, STEFFANIE KARLE*, JUERGEN KRATZSCH§, ULLA RENNE*, MANFRED SCHWERIN* and ANDREAS HOEFLICH{ddagger}

* Research Institute for the Biology of Farm Animals, 18196 Dummerstorf, Germany;
{dagger} Roslin Institute (Edinburgh), Roslin, Midlothian EH25 9PS, U. K.;
{ddagger} Department of Molecular Animal Breeding, Ludwig-Maximilian University, 81377 Munich, Germany; and
§ Departments of Clinical Chemistry and Pathobiochemistry, University of Leipzig, 04103 Leipzig, Germany

1Correspondence: Department of Molecular Biology, Research Institute for the Biology of Farm Animals, Wilhelm-Stahl-Allee 2, 18196 Dummerstorf, Germany. E-mail: Gudrun.Brockmann{at}fbn-dummerstorf.de


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
A segregating F2 pedigree based on two mouse lines (DU6i and DBA/2) with extremely different growth characteristics was generated to search for loci affecting serum levels of insulin-like growth factor (IGF) binding proteins (IGFBPs) and to estimate their effects on growth and body composition. DU6i is characterized by high body mass and obesity associated with hyperinsulinemia, hyperleptinemia, and elevated serum IGF-I concentrations. Furthermore, significantly elevated serum levels of IGFBP-2, IGFBP-3, and IGFBP-4 were found in DU6i vs. DBA/2 mice. Linkage analysis identified loci with major effects on the serum level of IGFBP-3 on Chromosome 5 at 58 cM (Igfbp3q1; F = 9.9) and on Chromosome 10 at 46 cM (Igfbp3q2; F = 33.8). A locus significantly influencing serum IGFBP-2 levels in males was found on Chromosome 7. Additional linkage was detected in males and females for IGFBP-2 on Chromosomes 8, 11, 14, 17, and X, and for IGFBP-4 on Chromosome 4. Additional loci affecting IGFBPs acted in a sex-specific manner. The identified loci coincide in part with chromosomal regions controlling growth and obesity. Thus, multiple genes or pleiotropic gene effects may be assumed for these chromosomal regions. The identification of quantitative trait loci for IGFBPs as subcomponents of growth regulation and differentiation will further improve the understanding of complex trait regulation.—Brockmann, G. A., Haley, C. S., Wolf, E., Karle, S., Kratzsch, J., Renne, U., Schwerin, M., Hoeflich, A. Genome-wide search for loci controlling serum IGF binding protein levels of mice.


Key Words: IGFBP-2 • IGFBP-3 • IGFBP-4 • linkage


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
THE MOUSE LINE DU6 SELECTED for extremely high body weight and its inbred line DU6i are models for the analysis of polygenic growth and obesity. The animals in line DU6 had been selected for 78 generations for high body weight at the age of 6 wk (1) (see www.ed.ac.uk/~eang17/mice.html). The age of selection decision corresponds to the end of the juvenile phase, when animals become fertile. At this age, the selected animals of DU6 are more than two times as heavy and three times as fat as nonselected controls. The extreme phenotype of DU6 mice is associated with hyperleptinemia, hyperinsulinemia, significantly elevated serum IGF-I concentrations, and low serum growth hormone levels (2) .

As a result of selection, we expected the fixation of a high number of alleles contributing to the unique phenotype. For the analysis of genetic factors underlying these phenotypic differences, we carried out linkage analyses for body weight, fat accumulation (3) , muscle weight, and serum concentrations of insulin-like growth factor I (IGF-I), insulin, and leptin (4) . The complex linkage analysis revealed a major effect on the serum concentration of IGF-I on Chromosome 10 (Igf1q1), a region harboring the gene for IGF-I (Igf1), and a second highly significant locus on Chromosome 18 (Igf1q2), where no strong candidate gene is known that might cause this effect (4) . IGF-I represents both a fetal (5 , 6) and a postnatal growth factor in mice (7) and is known to mediate some of the growth hormone effects in an autocrine/paracrine or endocrine fashion (8) . However, both identified loci, Igf1q1 and Igf1q2, did not contribute to the variance of body weight, muscle weight, or abdominal fat weight. Thus, we concluded that specific modulators of IGF-I actions might contribute to the variance of growth and obesity. The IGF binding proteins (IGFBPs) that bind IGFs with affinities similar to those of the IGF receptors (9) were pivotal candidates as modulators of IGF effects.

In mouse serum, IGFBP-2, -3, and -4 are the most abundant IGFBPs, and so far mainly inhibitory effects have been described as their biological functions (reviewed in ref 10 ). IGFBPs, especially IGFBP-3, may also have IGF-independent effects on cell growth (11) . IGFBP-2 has recently been identified as an important growth inhibitory IGFBP in IGFBP-2 transgenic mice (12) . The finding of elevated serum IGF-I levels in association with prostate cancer, colorectal cancer, and lung cancer has increased the interest in the role of the IGFs and their binding proteins in growth control (13) . Because little is known about the genetic factors underlying the serum levels of IGFBPs, we analyzed cosegregation of different growth measures and serum levels of IGFBPs in segregating pedigrees, mapped quantitative trait loci (QTLs) contributing to the genetic control of serum IGFBP levels, and compared identified QTL positions for IGFBP levels with recently discovered QTLs affecting body weight, obesity, and serum concentrations of leptin, insulin, and IGF-I. The potential roles of candidate genes within these regions are discussed.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Mouse lines
The study was carried out with the mouse line DU6i, which has been inbred for four generations from the line DU6 selected for high body weight, and the commercial inbred strain DBA/2 (DBA/2OlaHsd) as contrast line (Harlan Winkelmann, Borchen, Germany). The outbred line DU6 had been selected for 78 generations for high body weight at the age of 42 days (1) . Line DU6 descends from original crosses of four outbred (NMRI orig., Han: NMRI, CFW, CF1) and four inbred (CBA/Bln, AB/Bln, C57BL/Bln, XVII/Bln) populations in the Research Institute for the Biology of Farm Animals, Dummerstorf, Germany (14) . Animals were fed ad libitum with a breeding diet containing 12.5 MJ/kg metabolic energy with an average content of 22.5% crude protein, 5.0% crude fat, 4.5% crude fiber, 6.5% crude ash, 13.5% water, 48.0% N-free extract, vitamins, trace elements, amino acids, and minerals (Diet 1314; Altromin, Lage, Germany). Nonfasted males from the DU6i (n = 17) and DBA/2 (n = 20) lines were analyzed for growth and physiological traits at the age of 42 days. This age corresponds to the end of the juvenile phase of ontogenesis, and animals of both DU6i and DBA/2 lines have finished the period of fast growth and are postpubertal. The age of 42 days was the age of selection in all generations.

Pedigree design
QTL analysis was performed with offspring from an intercoss of F1 mice originating from repeated matings of one DU6i female and one DBA/2 male. A total of 411 F2 offspring originated from 12 F1 mating pairs. Mating was initially at the age of 10 wk and was repeated after 6 wk. Recently, the same cross has been used to map QTLs influencing body weight and obesity (4) .

Analysis of serum IGFBP levels
Nonfasted DU6i and DBA/2 mice and all F2 hybrids were killed by decapitation at the age of 42 days in the morning between 9:00 and 12:00 AM. Blood was collected, and serum was recovered by centrifugation and stored at -20°C until analysis. Serum IGFBPs of 208 males and 161 females were analyzed by Western ligand blot analysis (15) . Briefly, serum samples were diluted 1:5 with sample buffer [50 mM Na2HPO4, pH 7.0; 1% (w/v) sodium dodecyl sulfate (SDS); 50% (w/v) glycerin], boiled for 5 min, and electrophoresed on a 5% stacking/12% separating SDS-polyacrylamide gel using the Mini Protean II system (Bio-Rad, Munich, Germany). Separated proteins were transferred to a nitrocellulose membrane (Millipore, Eschborn, Germany). The blots were blocked with 1% fish gelatin and incubated with [125I]IGF-II (106 cpm per blot). All incubation and washing steps were performed at 4°C. Binding proteins were visualized on Phosphor-Imager Storm (Molecular Dynamics, Krefeld, Germany) and quantified by using ImageQuaNT software (Molecular Dynamics). Signal intensities were corrected for background and were normalized by using identical standards on the different blots (Fig. 1 ). The serum levels of IGFBPs are given as relative densitometric values (RDVs) to the standard. The sum of all IGFBPs was quantified and defined as total IGF binding capacity. Because IGFBP-2 is differently regulated in mice selected for body weight (16) and inhibits body growth of transgenic mice (12) , we calculated the amount of IGFBP-2 relative to the total IGF binding capacity in serum (relIGFBP-2), thus taking into account variation in total serum IGFBP levels between different mouse strains.



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  		Figure 1. Exemplary profile of IGFBPs in serum samples from selected F2 offspring (lanes 1–13) from the linkage analysis shown by Western ligand blot analysis. The example shows the great difference in IGFBP levels among F2 animals. Bands were visualized by phosphoimaging and quantified by using ImageQuaNT software as described in Materials and Methods. Serum levels of distinct IGFBPs were measured semiquantitatively (square 1: IGFBP-3; square 2: IGFBP-2; square 3: IGFBP-4; square 4: IGF binding affinity between 28 and 32 kDa; S: standard serum included in each run for normalization of the different blots).

Quantification of IGF-I serum concentration
Serum IGF-I was determined by use of ELISA after acid ethanol extraction as described previously (4) .

Marker analysis
Markers were chosen from the mouse genome database (MGD) for informative parental alleles. Mouse MapPair primers were purchased from Research Genetics (Huntsville, Ala.). Parents and F2 animals were genotyped for all 93 selected loci covering all chromosomes at an average spacing of 14.1 cM.

DNA was extracted from mouse tail clips by using the QIAamp Tissue Kit (Qiagen, Hilden, Germany). DNA was amplified with Taq polymerase (Promega, Mannheim, Germany) with a modified standard polymerase chain reaction protocol (17) . Polymerase chain reaction products were separated on 6% polyacrylamide gels, 40 cm in length, under denaturating conditions. The gels were stained with silver nitrate (18) and dried on Filtrak paper (Filtrak, Bärenstein, Germany). All genotyping results were scored twice, and runs were repeated when there were discrepancies.

Test statistics
For linkage analysis, we initially generated a pedigree-specific marker map with the program CRIMAP (19) . Inasmuch as this map was consistent with the published map, we used the marker distances of the consensus map of the mouse genome (20) for linkage analysis in our pedigree.

For the analysis of the pedigree, we initially estimated the influences of sex, parity, subfamily (i.e., F2 animals from the same pair of F1 parents), and litter size for every trait via analysis of variance (SAS Institute Inc., Cary, N.C.). All factors were found to be significant and were therefore included as fixed effects in the linkage analysis.

Data were analyzed by multiple regression (21) . Once a significant QTL on a chromosome had been identified, the presence of a second QTL was investigated by performing a grid search at 2 cM intervals as described in detail previously (4) . The sex chromosome was analyzed as a pseudoautosomal chromosome, as all markers were located in that chromosomal part. The estimated QTL positions are given as cM distance from the centromere. The joint effect of all significant QTLs for a trait (i.e., proportion of F2 variance explained) was estimated as reduction of the residual mean square in the one QTL analysis fitting all QTL positions as cofactors in comparison with no QTL fitted. When a QTL was identified, the interactions of the QTL effects with intrapedigree subfamily and sex were tested and were accepted as significant at P < 0.05. Inasmuch as we found many significant differences between males and females, we analyzed both sexes together and, in addition, males and females separately.

The experiment-specific empirical threshold values were estimated with the permutation test proposed by Churchill and Doerge (22) . Thresholds showed little variation between the analyzed traits and between the sex-specific analyses. We therefore used a common set of thresholds derived from 1000 replicates of the permutation analysis that was performed for IGFBP-2. Levels for significant ({alpha} = 0.05), and highly significant ({alpha} = 0.01) linkage were used (23) .

The chromosome-wise 0.05 significance levels were taken as genome-wide thresholds for suggestive linkage. We used the 1 logarithm of odds (LOD) drop to provide an estimate of the confidence interval for loci at the chromosome-wise 5% level of significance. Gene symbols were assigned to QTLs exceeding the genome-wide highly significant threshold of {alpha} < 0.01 at F > 9.86.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
Body weight, body composition, and serum levels of IGF-I and IGFBPs
Data on body weight and composition characteristics and serum concentrations of IGF-I and IGFBPs of DU6i and DBA/2 males are presented in Table 1 . The extremely high body weight as well as fat and muscle weights in line DU6i were associated with elevated serum levels of IGF-I and IGFBPs. The serum concentration of IGF-I was 3.2-fold and the total IGF binding capacity was 4.1-fold higher in DU6i than in DBA/2 animals (IGFBP-2: 2-fold; IGFBP-3: 11-fold; IGFBP-4: 1.8-fold, IGFBP 28–30 kDa: 2-fold). The relative amount of IGFBP-2 (relIGFBP-2) was significantly reduced in DU6i animals compared with DBA/2 mice. The F2 population had a mean serum IGFBP-2 activity of 0.89 RDV (Table 1) with significantly (P = 0.007) higher levels in females (0.95 ± 0.03 RDV) than in males (0.85 ± 0.03 RDV). The mean IGFBP-2 level was very close to the average of the two parental lines, with mean values of 1.16 RDV (DU6i) and 0.57 (DBA/2). For IGFBP-3 and -4, the means for the F2 population were shifted toward DBA/2 and DU6i, respectively. Total IGF binding capacity was 7.32 RDV, 1.80 RDV, and 3.03 RDV in the DU6i, DBA/2, and F2 collectives, respectively.


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  		Table 1. Characteristics of the parental mouse lines and the F2 populationa

Correlation analyses of data for different parameters measured in the F2 population reflect the strength of coincidence between measures of body composition and serum parameters. Pearson’s correlation coefficients (r) are given in Table 2 . The regression analysis revealed a negative correlation between IGFBP-2 and body weight (r = -0.16; P < 0.01), abdominal fat weight (r = -0.10; P < 0.05), and muscle weight (r = -0.20; P < 0.0001). This finding was confirmed by the negative correlation between relIGFBP-2 and body weight/composition data. There was also a low negative correlation between serum leptin and IGFBP-2 levels (r = -0.13; P < 0.05) and relIGFBP-2 (r = -0.23; P < 0.001), as well as between serum insulin and relIGFBP-2 (r = -0.18; P < 0.001) (individual data of leptin and insulin are not shown, for details see ref 4 ). For most parameter pairs, different correlation coefficients were calculated for males and females. The negative correlation between body composition parameters and IGFBP-2 was stronger in males than in females. The correlation coefficients between IGFBP-3 as well as IGFBP-4 and body composition data were positive in females, whereas there was no correlation in males. The highest positive correlation (r = 0.36; P < 0.0001) was found between serum IGFBP-3 and insulin levels, which was specific for females.


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  		Table 2. Pearson’s correlation coefficients between body composition and serum parametersa

Genome-wide QTL mapping
The linkage analysis revealed evidence for loci affecting the serum levels of IGFBPs on 15 autosomes and on the X chromosome. Among the QTLs for serum levels of IGFBPs were loci that had similar effects in both sexes, loci that affected males and females in different ways, and loci that acted specifically in males or females only. Additive genetic and dominance effects of the identified QTLs at peak F value position are shown in Table 3 . Positive estimates of genetic effects indicate that alleles from the selected line DU6i increased the trait. The results of linkage analysis were classified as highly significant at F > 9.86 (genome-wide error rate of P < 0.01), as significant at F > 7.07 (genome-wide error rate of P < 0.05), and as suggestive if F > chromosome-specific 5% level.


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  		Table 3. Most likely positions and effects of QTLs influencing IGFBPs

The serum level of IGFBP-2 in males was significantly influenced by a QTL on Chromosome 7 at 16 cM with a peak F value of 7.86. The DU6i allele had a negative additive genetic effect. This locus contributed 9.7% to the phenotypic variance in IGFBP-2 levels of F2 males. A suggestive locus was found on Chromosome 8 that had an estimated negative overdominant effect on serum IGFBP-2 activity in both sexes. In addition, loci on Chromosomes 11, 14, and 17 had similar effects on IGFBP-2 levels in both sexes. Loci on Chromosomes 4, 10, and 18 affected serum IGFBP-2 levels in males only. An X chromosomal influence on serum IGFBP-2 activity was negative additive in males but positive in females. The net effect of all these QTLs accounted for 25.3% and 12.0% of the variance of serum IGFBP-2 levels in F2 males and females, respectively.

The highest effect on IGFBPs was estimated for IGFBP-3 at a peak F value of 33.8 on Chromosome 10 at 46 cM. This locus (Igfbp3q2) acted independently of sex and had a strong additive genetic effect accounting for 16.7% of the variance of IGFBP-3 levels in F2 mice. The DU6i allele increased serum IGFBP-3 levels. The estimated location at 46 cM is 8 cM distal of the Igf1q1 locus, which had been previously identified as affecting the serum IGF-I concentration (4) . The inclusion of IGF-I serum concentration as a covariate in the analysis reduced the F value for Igfbp3q2 from 33.8 to 18.1, indicating an interdependence between the two growth-mediating factors. In addition, a second highly significant QTL (Igfbp3q1) affecting serum IGFBP-3 levels in males and females was mapped on Chromosome 5 with a peak F value of 9.92 at 58 cM. The estimated effect showed dominance for the increasing allele (DU6i) and contributed 5.6% of the phenotypic F2 variance. The F value curves for the probability of linkage between genotype and serum IGFBP levels as a function of chromosomal location are displayed for Chromosomes 5 and 10 in Fig. 2 . Figure 3 shows the most likely chromosomal position of Igfbp3q1 and Igfbp3q2 relative to map positions of known genes in the estimated confidence intervals and the homologous regions of the human chromosomes. The statistical tests for two QTLs in the linkage groups of the significant effects on Chromosomes 5 and 10 did not show evidence for multiple QTLs in the identified chromosomal regions.



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  		Figure 2. F value curves for the probability of linkage between genotype and phenotype as a function of chromosomal location for Chromosomes 5 and 10, for which genome-wide highly significant effects on IGFBP-3 were detected. The F value curves are presented for IGFBPs as well as for body weight (BW), abdominal fat weight (AFW), muscle weight (MW), and IGF-I concentration when they were relevant. The horizontal lines indicate the highly significant (1%) and significant (5%) threshold values for QTL detection. The most likely chromosomal positions of the QTL are located at the peak F value position of the curve.



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  		Figure 3. Linkage maps of the highly significant chromosomal regions harboring Igfbp3q1 (Chromosome 5) and Igfbp3q2 (Chromosome 10) and the confidence intervals were constructed by using the Mouse Genome Database (MGD www.informatics.jax.org). All genes reflecting biological roles were included on the right-hand side of the chromosome, and homologous human chromosomal parts are given on the left-hand side. Genes that are discussed are underlined.

QTLs for serum IGFBP-3 activity at the suggestive level were found on Chromosomes 6 and 8 (independent of sex) and on Chromosome 2 (in females only). The effects of the DU6i alleles of these QTLs were overdominant. The net effect of all identified QTLs for IGFBP-3 contributed 23.5% and 35.6% of the phenotypic F2 variance in males and females, respectively.

For the IGFBP-4 serum level, we detected one locus on Chromosome 4 at 43 cM that acted independent of sex. Although of chromosome-wise suggestive significance only, the estimate for the most likely position of the QTL coincided within the 1 LOD support interval of the chromosomal region for the identified IGFBP-2 QTL in males. The DU6i allele effects of this chromosomal region on both IGFBP-2 and -4 were increasing. In males, we detected suggestive QTLs for the serum level of IGFBP-4 on Chromosomes 18 and 19. The male-specific effect on Chromosome 18 at 50 cM coincided with a male-specific effect of the same chromosomal region on IGFBP-2 and had a negative overdominance effect on both IGFBPs. The joint effect of the QTLs responsible for IGFBP-4 explained 12.8% and 3.8% of the phenotypic F2 variance of IGFBP-4 in males and females, respectively.

The bands below IGFBP-2 in the Western ligand blot represent a fraction of IGFBPs between 28 and 30 kDa. This 28–30 kDa IGFBP fraction was significantly influenced by QTLs on Chromosomes 2, 6, and 15 in females, and by a QTL on Chromosome 7 in males. For the locus on Chromosome 2 at 94 cM, a strong overdominance effect was observed, with decreasing influence of the DU6i allele compared with the DBA/2 allele. The male-specific effect on Chromosome 7 at 16 cM coincides with the male-specific effect of the same chromosomal region on IGFBP-2. This might be caused by a residual IGFBP-2 portion in the analyzed 28–30 kDa fraction of IGF binding capacity (Fig. 1) . The joint effect of all QTLs for the 28–30 kDa IGFBP fraction contributed 7.1% and 23% of the corresponding phenotypic variance in F2 males and females, respectively.


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
The question of what makes a mouse big, small, fat, or lean is normally addressed by overexpression models or by functional inactivation of distinct gene products. Whereas these approaches are important for clarifying the specific functions of a particular gene, the present approach makes use of mice selected for high body weight and mice used as controls and represents a genome-wide search of loci potentially involved in the as yet incompletely defined regulation of growth and obesity. We have analyzed DU6i x DBA/2 F2 mice for genetic factors responsible for differences in serum levels of IGFBP-2, IGFBP-3, and IGFBP-4, and the IGFBP fraction of 28 to 30 kDa. The original populations DU6i and DBA/2 have extremely different body weight and composition as well as serum levels of IGF-I and IGFBPs. The body weight in the selected line is 3.7-fold and the relative fat content is 2-fold increased compared with DBA/2 mice. In contrast, the relative muscle content is 0.7-fold lower in DU6i mice compared with DBA/2 mice. The levels of all components in the IGF system measured were increased several times in the selected line compared with the DBA/2 inbred strain. IGFBP-2 was the only IGFBP that correlated negatively with various parameters of growth and, although absolute IGFBP-2 serum levels were increased in the high-growth DU6i mice compared with DBA/2 mice, this increase was markedly less pronounced than that for serum IGFBP-3 levels. Inasmuch as IGFBP-2 does not form ternary complexes in the circulation, it is capable of passing the capillary barrier easily (10) . IGFBP-2 is the second most abundant IGFBP in the circulation and is present in many tissues, suggesting that IGFBP-2 modulates local IGF actions. Indeed, in IGFBP-2 transgenic mice a significant reduction of body weight gain was found (12) . Because IGFBP-2 binding to the IGFs competes with binding of the other IGFBPs, we have calculated the amount of IGFBP-2 relative to the other IGFBPs. Interestingly, the relative amount of IGFBP-2 was reduced (~40% of DBA/2 mice) in the heavy mouse line. Despite low and partly divergent correlation with parameters of growth, we observed significant positive correlation between all serum IGFBPs. These findings suggest common regulatory mechanisms for IGFBP-2, -3, and -4. Although only a low correlation was found between IGF-I and IGFBP-3 in our study, it cannot be excluded that IGF-I represents a common regulator of IGFBP expression because IGFBP-2 and IGFBP-3 expression has been demonstrated to be regulated by IGF-I (24) . However, in the present study the chromosomal region harboring the Igfbp3q2 QTL had a direct effect on only IGFBP-3. Our linkage analysis found QTLs for IGFBP-2 and IGFBP-3 on Chromosomes 4 and 18 in very narrow chromosomal regions of 3 and <1 cM, which may indicate the presence of one or more common regulators of both binding proteins in these regions.

Different correlation coefficients for males and females and sex-specific QTL effects gave evidence for differential regulation of serum levels of IGFBPs in males and females. This result may indicate direct or indirect sex hormone-dependent regulation of the genes underlying the observed QTL effects. Mutual interactions between sex hormones and IGFBPs have been described before (25 , 26) .

Most obviously, IGFBP-3 was 11-fold increased in DU6i mice, revealing IGFBP-3 as a very strong candidate for the control of growth in vivo. Systemic overexpression of human IGFBP-3 in transgenic mice resulted in selective organomegaly but not in an alteration of body weight (27) . However, this model may be artificial, because the transgene-encoded IGFBP-3 in the serum was not associated with the acid-labile subunit, which is also known to be regulated by growth hormone (28) . In vitro, IGFBP-3 is known to exert IGF-independent inhibitory actions (11) . However, positive effects of IGFBP-3 on DNA synthesis have also been demonstrated in prostate cancer cells (29) . The QTL mapping analysis identified two chromosomal regions with highly significant effects on IGFBP-3. The highly positive effects of the DU6i alleles of Igfbp3q1 and Igfbp3q2 were independent of sex. However, neither QTL exerted significant effects on growth or body composition. The estimated position of Igfbp3q2 at 46 cM on Chromosome 10 coincided with a highly significant effect on IGF-I at 38 cM (4) . The analysis of IGFBP-3 with IGF-I as covariate showed a drop in the F value but did not remove the significant effect on IGFBP-3. This corresponds to the observation that the estimate of the phenotypic correlation between IGF-I and IGFBP-3 serum levels was 0.0 in animals of the F2 population. Thus, the IGF-I and IGFBP-3 serum levels may be controlled by different genes. Although no statistical significance was found for two QTLs in the linkage group of Igfbp3q2, it may well be possible that two or more quantitative trait genes underlie the major effect of this QTL (e.g., see ref 30 ). In the following, we focus the discussion on the genes of the identified chromosomal regions that are reported to play a role for IGF-I or IGFBP action.

The identified region on Chromosome 10 harbors the Igf1 gene as a candidate underlying the observed effects, inasmuch as IGF-I has been demonstrated to control IGFBP-3 expression in various systems (31 32 33) . Another interesting candidate is the Socs2 (suppressor of cytokine signaling 2) gene. Recently, gigantism in mice lacking SOCS-2 has been shown (34) . The same gene underlies the hg (high growth) mutation (Simon Horvat, personal communication), which causes the high-growth phenotype in the HG mouse line (35) . In both, the HG mouse line and the SOCS-2-deficient mouse line, body weight was increased by ~40%, and local IGF-I expression (34) as well as serum IGF-I concentration (36) was enhanced. As no effect on body weight could be found for Chromosome 10 in our analysis, potential variation in the Socs2 gene is not sufficient to explain the F2 phenotypes in our cross. Furthermore, the hg locus at 52 cM is slightly outside the most likely QTL support interval. Other candidate genes resident on chromosomal regions closely distal to Igfbp3q2 include Cdc2a (cell division cycle control protein 2a) at 38 cM, Prkmk2 (mitogen-activated protein kinase 2, p45) at 43 cM, and others that to our knowledge have not been described in a functional context with the IGF system. Therefore, as yet unknown gene or genes are likely to cause the observed effects on Chromosome 11.

As a second chromosomal region with a strong effect on IGFBP-3 expression, Chromosome 5 (58 cM) was identified. It is known that Fgf5 (fibroblast growth factor 5) at 55 cM and Pxn (paxillin) at 60 cM reside in this region. Coordinate expression of Fgf5 and Igf1 has been reported (37) . Interestingly, a functional relationship between paxillin and IGF-I has been described in two recent publications (38 , 39) . Paxillin is a downstream substrate of IGF-I signaling and is involved in IGF-I-stimulated lamellipodial motility (40 , 41) . Further specific studies are necessary to analyze a potential mutual relationship between IGF-I and the candidates on Chromosome 5 around 58 cM. Genes encoding proteins that are known to interact with IGFBP-3, such as p53 (42) , RXR (retinoid x receptor) (43) , ADAM12 (disintegrin and metalloproteinase domain 12) (44) , TGFB1 (transforming growth factor ß1) (45) , and CSNK2 (casein kinase II, ß subunit) (46) , do not map within the identified chromosomal regions in mice. The known genes that are located in the chromosomal sections harboring the QTLs for IGFBP-3 and the corresponding human homologue regions are shown in Fig. 3 .

Some of the QTLs responsible for differences in serum levels of IGFBPs cosegregated with QTLs that have been identified for growth and obesity parameters (4) . The genome-wide significant and male-specific QTL influencing the serum level of IGFBP-2 on Chromosome 7 mapped to a 13 cM interval between 16 and 29 cM, which had the biggest effects on body weight (Bw14) and the weights of muscle (Mwq1) and abdominal fat (Afw9). This QTL effect coincided with the location of the IGF-I receptor gene (Igf1r) as major candidate having an effect on the IGFBP-2 level in serum. It is commonly accepted that both genes represent antagonists in terms of their biological functions. In contrast, coordinate expression of IGFBP-2 and IGF-I receptors has been observed during renal injury and hypertrophy (47) . To our knowledge, direct control of serum IGFBP-2 concentration by IGF-I receptors remains to be demonstrated. The QTL controlling IGFBP-2 on the X chromosome mapped together with a QTL influencing abdominal fat weight (Afw11). The DU6i allele had a smaller effect than the DBA/2 allele and was associated with higher fat weight. A suggestive effect on fat was also found for the IGFBP-2 QTLs on Chromosomes 4 and 14, which also affected the serum leptin concentration. Most interestingly, the leptin receptor gene (Lepr) resides close to the mapped QTL for IGFBP-2 on Chromosome 4. It is well known that increased leptin concentrations can be due to mutant leptin receptors or impaired leptin signaling (48) . The negative coefficients of correlation between IGFBP-2 and leptin serum levels suggest a regulatory system including leptin, its receptor, and IGFBP-2. A functional relationship between IGFBP-2 and leptin has previously been demonstrated, because preadipocyte differentiation is controlled by IGF-I and IGFBP-2 (49) . Thus, an involvement of IGFBP-2 in fat metabolism is suggested. A QTL was also mapped on Chromosome 8 in the direct neighborhood of the insulin receptor gene (Insr). Interactions between glucose homeostasis and IGFBP-2 have also been reported in several studies (50 , 51) , and slightly increased fasting glucose and fasting insulin concentrations in serum have been reported in IGFBP-2 transgenic mice (12) . The IGFBP-2 regulating loci on Chromosomes X and 14 might contribute preferentially to increased fat accumulation. The locus on Chromosome 14 influencing IGFBP-2, which also had an effect on serum leptin levels, coincided with the insulin-dependent diabetes susceptibility locus (Idd12) and the growth differentiation factor 10 gene (Gdf10). For the X chromosomal effect on serum IGFBP-2 levels, no candidate gene has yet been identified.

Candidate genes responsible for the extremely high levels of IGFBPs in DU6i mice include the IGFBP-encoding genes themselves and genes regulating IGF-I. Linkage analyses did not reveal significant effects of chromosomal regions harboring genes encoding IGFBP-2 and -3 on Chromosome 1 at 36 cM. The gene encoding IGFBP-4 has been localized in humans at 17q12-q21. According to synteny between human and mouse chromosomal regions, the mouse IGFBP-4 gene is expected to reside on Chromosome 11 at 57–58 cM. However, no effect on IGFBP-4 levels could be attributed to this chromosomal region.

In conclusion, our study provides further evidence for a role of IGFBPs in growth regulation of mice selected for body weight. Serum levels of IGFBPs are controlled by a number of loci on different chromosomes, indicating that the regulation of IGFBP expression is more complex than assumed by current concepts. Complementary mapping studies using other constellations of selected mice or the search for candidate genes in large-scale phenotype-based mouse mutagenesis screens (e.g., ref 52 ) will facilitate further characterization and molecular identification of the QTLs provisionally identified in the present study.


   ACKNOWLEDGMENTS
 
Excellent technical assistance was provided by Hannelore Tychsen and Petra Demleitner. This work was supported by the German Research Foundation, grant Br 1285/4, and the H. Wilhelm Schaumann Stiftung. C.S.H. acknowledges support from the BBSRC.

Received for publication August 1, 2000. Revision received November 16, 2000.
   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
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