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Human Molecular Genetics Advance Access originally published online on September 23, 2005
Human Molecular Genetics 2005 14(21):3141-3148; doi:10.1093/hmg/ddi346
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© The Author 2005. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Interspecies synteny mapping identifies a quantitative trait locus for bone mineral density on human chromosome Xp22

Claire A. Parsons1,{dagger}, H. Joel Mroczkowski2,{dagger}, Fiona E.A. McGuigan1,{dagger}, Omar M.E. Albagha4, Stavros Manolagas3, David M. Reid1, Stuart H. Ralston4,* and Robert J. Shmookler Reis2,3

1Bone Research Group, Institute of Medical Sciences, University of Aberdeen, Aberdeen, UK, 2Department of Geriatrics, and Department of Biochemistry and Molecular Biology, University of Arkansas for Medical Sciences and 3Department of Medicine, University of Arkansas for Medical Sciences and Central Arkansas Veterans Health Care System, Little Rock, AR 72205, USA and 4Rheumatic Diseases Unit, School of Molecular and Clinical Medicine, University of Edinburgh, Western General Hospital, Edinburgh EH4 2XU, UK

* To whom correspondence should be addressed. Tel: +44 131-651-1035; Fax: +44 131-651-1085; Email: stuart.ralston{at}ed.ac.uk

Received June 4, 2005; Accepted September 7, 2005


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
Bone mineral density (BMD) is a complex trait with a strong genetic component and an important predictor of osteoporotic fracture risk. Here we report the use of a cross-species strategy to identify genes that regulate BMD, proceeding from quantitative trait mapping in mice to association mapping of the syntenic region in the human genome. We identified a quantitative trait locus (QTL) on the mouse X-chromosome for post-maturity change in spine BMD in a cross of SAMP6 and AKR/J mice and conducted association mapping of the syntenic region on human chromosome Xp22. We studied 76 single nucleotide polymorphisms (SNP) from the human region in two sets of DNA pools prepared from individuals with lumbar spine-BMD (LS-BMD) values falling into the top and bottom 13th percentiles of a population-based study of 3100 post-menopausal women. This procedure identified a region of significant association for two adjacent SNP (rs234494 and rs234495) within the Xp22 locus (P<0.001). Individual genotyping for rs234494 in the BMD pools confirmed the presence of an association for alleles (P=0.018) and genotypes (P=0.008). Analysis of rs234494 and rs234495 in 1053 women derived from the same population who were not selected for BMD values showed an association with LS-BMD for rs234495 (P=0.01) and for haplotypes defined by both SNP (P=0.002). Our study illustrates that interspecies synteny can be used to identify and refine QTL for complex traits and represents the first example where a human QTL for BMD regulation has been mapped using this approach.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
Osteoporosis is a common disease characterized by reduced bone mass and an increased risk of fractures, which affects up to 30% of women and 12% of men at some point in life. Fractures related to osteoporosis are a major public health problem of global importance (1Go) and bone mineral density (BMD) is one of the most important predictors of osteoporotic fracture risk (2Go). Twin- and family-studies have shown that 60–80% of the population variance in BMD is genetically determined (3Go–5Go) with effects that are sex-specific and site-specific (6Go). Several approaches have been used in efforts to identify the genes that predispose to osteoporosis, including candidate-gene association studies in unrelated subjects, and linkage analyses in sibling pairs and extended families (7Go). These studies have resulted in the identification of some allelic variants that are associated with BMD, but most of the genes that regulate bone mass remains to be discovered. The difficulty of dissecting environmental from genetic regulators of BMD in human studies has led several investigators to propose the use of animal models as an alternative means of identifying QTL that regulate BMD (8Go). Genetic mapping studies in inbred strains of mice have resulted in the identification of several QTL that regulate BMD (9Go–11Go). At least some of these QTL have been replicated (or coincident loci observed) in crosses of distantly related strains, implying that variation in genes that regulate BMD may be favoured by natural selection in mice. Variation in the same genes might also be conserved in humans, where it may underlie observed genetic predispositions to low- or high-BMD. In this study we exploited the extensive, segmental conservation of synteny that exists between the mouse and human genomes, and used the results of mouse QTL mapping to search for human loci involved in the regulation of BMD.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
Characteristics of study population
Table 1 shows relevant characteristics of individuals whose DNA samples were combined to create low-BMD and high-BMD DNA pools for initial mapping by comparing allele proportions at phenotypic extremes. As expected, there were highly significant differences in both LS- and FN-BMD values, between the low- and high-BMD groups, but no significant difference between the groups with respect to age, weight or height. The majority of women included in the DNA pooling studies were post-menopausal at the time of study but none had used HRT for more than 3 months (see Materials and Methods section). Table 2 shows the characteristics of the 1053 women who took part in a second association study, for which subjects were drawn from the whole population without selection for BMD values. The mean BMD values of these subjects lay between those of the high- and low-BMD sub-groups. Most of the women (88%) were post-menopausal; 36.6% were current HRT users at the time of study and 17.5% had previously used HRT. There was some overlap between subjects who participated in the two association studies; 126/349 (36%) of individuals who were included in the low-BMD pools, and 128/346 (37%) of those included in the high-BMD pools, were also included in the random sample association study. In total, 254 of the 1053 women who took part in the association study (24%) had also been included in the pooling study.


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  		Table 1. Characteristics of the extreme-BMD subjects included in the DNA pools
 

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  		Table 2. Characteristics of subjects included in population-based association study
 
Identification of mouse BMD QTL and syntenic human chromosomal region
We identified a quantitative trait locus (QTL) for post-maturity change in vertebral BMD of mice, by linkage analysis in experimental crosses between strains SAMP6 and AKR/J mice, using composite interval mapping as previously described (9Go). This phenotype was defined as the change in vertebral BMD values observed between the age of 4 and 6 months, in F2 progeny from the interstrain cross. Those studies will be described more fully elsewhere (D. Szumska, H. Benes, P. Kang, R. Weinstein, R.L. Jilka, S. Manolagas and R.J. Shmookler Reis, submitted for publication). In brief, two significant QTL were observed for this trait. One of these lay on chromosome 7, with an empirical genome-wide significance of P=0.05 and the second lay on the X-chromosome between 145 and 58 Mb (96% confidence interval, NCBI Build 34) with an empirical genome-wide significance of P=0.01. In this report we focus on association mapping in humans, across the QTL interval corresponding to that identified on the X-chromosome of mice. Details of the mouse QTL region and the corresponding segment of the human X-chromosome are shown in Figure 1. The region of interest encompassed just over 12 Mb in the mouse genome and 10.9 Mb in the human genome. As can be appreciated from the figure, there was absolute conservation of gene order between the mouse and human genomes within this region.



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  		Figure 1. Mouse QTL on chromosome-X for post-maturity change in BMD and syntenic region on human chromosome-X. The approximate position of selected genes is indicated in relation to genetic distance from the telomere as determined by the NCBI database. The genes included in this map are: SAT, spermine N1-acetyltransferase; PHEX, phosphate regulating neutral endopeptidase; SMPX, small muscle protein, x-linked; PDHA1, E1-alpha polypeptide (of the pyruvate dehydrogenase complex); PHKA2, phosphorylase kinase alpha L subunit; RBBP7, retinoblastoma-binding protein 7; CALB3, calbindin 3; CA5B, carbonic anhydrase 5B, mitochondrial; ACE2, angiotensin I converting enzyme 2 presursor; BMX, bone marrow kinase BMX; PIR, pirin; FIGF, c-fos induced growth factor; PIGA, phosphatidylinositol-glycan biosynthesis, class A protein; ASB11, ankyrin repeat and SOCS box-containing 11; GLRA2, glycine receptor alpha-2 chain precursor; TLR7, toll-like receptor 7 precursor; TLR8, toll-like receptor 8 precursor; AMELX, amelogenin, X isoform precursor; MID1, midline 1 (Opitz/BBB syndrome).

 
Identification and analysis of SNP in human syntenic region
We identified 76 SNP that lay within the region of interest from public databases (dbSNP) focussing on those, which lay within or close to known genes. We were unable to amplify 18 of these SNPs and a further nine were not polymorphic in the Aberdeen Prospective Osteoporosis Screening Study (APOSS) population, resulting in a final series of 49 polymorphisms, which were successfully amplified and analysed (Table 3). Of these markers, 25 were concentrated within an initially suggestive 1.1 Mb region extending from GLRA2 to CA5B. Allele frequencies were averaged from at least four repeats for each pair of pooled samples, and corrected for differences in efficiency of allele amplification, determined empirically on individual samples from heterozygotes.


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  		Table 3. Association analysis of SNP within human chromosome Xp22, initial screening of DNA pools
 
Fine mapping of QTL and association studies in DNA pools
On analysis of DNA pool 1, we identified two SNPs (rs234494 and rs234495) within the candidate region, for which the nominal P-value was 0.05 or less in the first-round screen; these are situated 119 bp from each other, within intron 6 of the PIRIN gene. Further analysis focussed primarily on rs234494 as these two SNP were found to be in strong linkage disequilibrium with each other (D'=0.95). Genotyping for the rs234494 SNP in the replication DNA pool (pool 2) also showed a significant difference in allele proportions, in each case with nominally significant over-representation of the ‘A’-allele in the low-BMD subjects (combined P<10–3; Table 4). To confirm the results obtained for the pooled DNA samples, we performed genotyping for rs234494 in the individual samples that comprised the DNA pools. The results of this are shown in Table 5, which confirmed that there was over-representation of the A-allele in low-BMD pool 1, compared with high-BMD pool 1 (19% versus 13%; P=0.04) and a trend towards over-representation of the A-allele in low-BMD pool 2 compared with high-BMD pool 2 (18% versus 14%; P=0.19). The product of these two P-values gives a combined P<0.01, a slightly better significance than that was obtained by comparing allele proportions between high and low pools for both DNA pool sets combined (18% versus 13%; P=0.018). The genotype frequencies also differed significantly between low and high pools for data combined from both pool sets, mainly because of over-representation of the AA genotype in the low-BMD pools (5% versus 1%; P=0.008). This confirmed that there was a difference in allele proportions for both sets of DNA pools, although it should be noted that the association in the individual genotyping was weaker than that predicted by the results of the analysis in the pooled samples.


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  		Table 4. Allele frequencies for SNPs rs234494 and rs234495 in screening and replication DNA pools
 

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  		Table 5. Individual genotyping for rs234494 in subjects utilized for DNA pools
 
Association studies in a population-based cohort
We next evaluated the rs234494 SNP and the neighbouring rs234495 SNP in a group of 1053 individuals from the APOSS population who were not selected with regard to BMD values or genotype. These data are summarized in Table 6. The genotypes were in Hardy–Weinberg Equilibrium (HWE) for rs234494 (P=0.22), but deviated from HWE for rs234495, (P=0.005) owing to an excess of CC homozygotes. In view of this, we reviewed all the sequencing traces for rs234495 but did not identify any errors. We conclude that deviation from HWE may therefore have occurred as the result of over selection for this genotype in the sub-population of women studied, possibly as a result of sampling error.


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  		Table 6. Association between genotypes and haplotypes of PIRIN, BMD and bone loss in a population-based study of 1053 women
 
Analysis of the genotype data by the PHASE program showed that two haplotypes accounted for 98.8% of alleles in the study population, consistent with the strong linkage disequlibrium (D'=0.95) between the two SNP. Haplotype 1 comprised a G-allele at rs234494 and a T-allele at rs234495 (‘G-T’, 82.4% of alleles), whereas haplotype 4 comprised an A-allele at rs234494 and a C-allele at rs234495 (‘A-C’, 16.4% of alleles). Associations between BMD values, bone loss and genotypes plus common haplotypes are shown in Table 6, with adjustment of the BMD values and bone loss data for age, BMI, menopausal status and HRT use by general linear model-analysis of variance (GLM-ANOVA). This showed a trend for association between rs234494 and LS-BMD (P=0.09) and a significant association between rs234495 SNP and LS-BMD (P=0.01). Haplotype analysis showed a highly significant association between both common haplotypes and LS-BMD. Analysis of haplotype 1 data showed higher LS-BMD values in carriers of one or two copies of the rs234494 G–rs234495 T haplotype with a co-dominant (additive) pattern of inheritance (P=0.002). As expected, analysis of haplotype 4 (rs234494 A–rs234495 C) showed the opposite association with lower BMD values at the spine in carriers of one or two copies of the haplotype (P=0.006). There was no significant association with FN-BMD for either SNP (P=0.46 and P=0.88) or either haplotype (P=0.35 and P=0.53). There was no significant association between any of the SNP or haplotypes studied and bone loss at the LS or FN during an average ±SD of 6.6 ±0.6 years follow up between the baseline and second study visit. The major predictors of bone loss identified by the GLM-ANOVA procedure were HRT use/menopausal status and BMI for bone loss at the lumbar (both P<0.001) and HRT use/menopausal status for bone loss at the femoral neck (P<0.0001).


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
MATERIALS AND METHODS
 REFERENCES
 
In this study we exploited chromosomal synteny between the mouse and human genomes to fine-map a QTL for regulation of spine BMD on human chromosome Xp22. A whole-genome scan performed on the F2 generation of a cross between the AKR/J and SAMP6 mouse strains defined a significant QTL on chromosome-X for post-maturity change in spine BMD between the ages of 4 and 6 months. The syntenic region in the human genome on Xp22 was identified and was found to be highly conserved in terms of gene content and order. Association mapping of the human QTL employed preferential selection of markers within or near genes situated in the region of interest, and on a first-round screen, two markers were identified in which allele frequencies differed between the low and high DNA pools. Similar differences were observed on analysis of replication DNA pools and the association was confirmed by genotyping of individual samples. Two of the associated SNP lie within intron 6 of the PIR gene, which is near the centre of the QTL and close to the peak-LOD position based on linkage in the mouse. The PIR gene encodes Pirin—a nuclear protein which has been shown to interact with the transcription factors NFI/CTF1 and Bcl-3 (12Go). The function of Pirin is currently unclear, but its mRNA is widely expressed in human tissues and the N-terminal domain is significantly conserved between mammals, plants, fungi and prokaryotic organisms, implying that it serves an important function.

To assess the contribution of these alleles in regulating the BMD of a population-based setting, the two SNP within PIR that were associated with BMD were analysed in a cohort of 1053 women drawn from the same population as the DNA pools were constructed from. This analysis confirmed that there was an association between the intron 6 polymorphisms of PIR and BMD especially when we conducted haplotype analysis. Although there was some overlap between the subjects who were included in the DNA pools and the population-based cohort, there were similar trends for association with spine BMD when DNA pooling subjects were excluded, indicating that the association was not being driven by a few subjects with extreme BMD values (data not shown).

It is of interest that the association was observed only for spine BMD and not hip BMD, which is in accord with the trait initially mapped in the mouse. Osteoporosis is generally considered a systemic disease, but recent studies in man and experimental animals indicate that the genes and loci which regulate BMD do so in a site-specific manner (13Go). Though we did not observe an association between the human loci studied and rates of bone loss at the spine, the power to do so was extremely limited in view of the short duration of follow up and the very strong effect of menopausal status/HRT use and BMI on this phenotype.

Over recent years, many advances have been made in identifying QTL that regulate BMD and other complex traits by genome-wide scans in experimental crosses of inbred mouse strains (8Go). Indeed, at the current time, QTL for regulation of BMD and other phenotypes relevant to the pathogenesis of osteoporosis have been identified on almost all mouse chromosomes (9Go,10Go,14Go–17Go). At least some of these QTL have been confirmed in multiple crosses, utilizing distantly related mouse strains, implying that the genetic variants responsible may have been evolutionarily conserved and hence might play a role in the regulation of BMD in other species such as humans. Conservation of synteny between humans and rodents has previously been utilized in the mapping and identification of genes that contribute to other complex traits such as hyperlipidaemia (18Go), obesity (19Go), inflammatory arthritis (20Go), warfarin resistance (21Go) and polycystic kidney disease (22Go), but none of these studies used DNA pooling. As far as we are aware this is the first study in which synteny mapping has been successfully combined with DNA pooling to identify a QTL for the osteoporosis-related phenotype of BMD in humans.

Though we identified a fairly robust association between BMD and the two intronic SNP of PIR that were analysed here, it seems likely that the association we observed may have been driven by other functional allelic variants which are in linkage disequilibrium to those studied here. This is because both SNP that were associated with BMD lie deep within intron 6 of PIR and are not in a region or motif known to be involved in gene regulation. Further work is currently in progress to try and identify other polymorphisms within PIR and surrounding genes to address this possibility. We have demonstrated the feasibility of transferring QTL mapping information for genes that regulate BMD between the mouse and human genomes, at a stage well in advance of gene identification. This indicates that association analysis of human chromosomal regions syntenic to other mouse BMD QTL may represent a valuable approach in identifying genes that regulate BMD and other traits relevant to the pathogenesis of osteoporosis.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
REFERENCES
 
Study subjects
The study group was derived from APOSS (23Go). Participants in the study were randomly selected from the community health index, which is a database of all patients registered with general practitioners in Scotland, focussing on those living within a 25 mile radius of Aberdeen. Approximately, 7000 women were originally invited to take part in the study by letter between 1990 and 1994 and 5119 women attended the clinical evaluation and BMD measurements by dual-energy X-ray absorptiometry. All participants were invited to re-attend for further evaluation between 1997 and 1999 when BMD measurements were repeated and blood was obtained for DNA extraction in 3100 women. No specific exclusions were applied with regard to secondary causes of osteoporosis or vitamin D status. Information was collected on height, weight, menopausal status and use of hormone replacement therapy (HRT). Women were classified as pre-menopausal if they were menstruating regularly, as perimenopausal if menstruation was irregular and/or up to 6 months had elapsed since their last period and post-menopausal if menstruation had ceased for 6 months or more. Information gathered on menopausal status and HRT use identified five categories as follows: 1, pre-menopausal, no HRT; 2, perimenopausal, no HRT; 3, post-menopausal, no HRT; 4, post-menopausal, previous HRT user; 5, post-menopausal, current HRT user. All participants gave written informed consent to participating in the study, which also received the approval of the local ethics committee.

BMD measurements
Measurements of BMD at the left proximal femur (the femoral neck; FN) and lumbar spine (LS; L2–L4) were performed by dual energy X-ray absorptiometry using one of two Norland densitometers (models XR26 or XR36; Norland Corp., WI, USA). Calibration of the machines was performed daily, and quality assurance checked by measuring the manufacturer's LS phantom at daily intervals and a Hologic spine phantom at weekly intervals. The in vivo precision for XR26 was 1.95% for LS, and 2.3% for the FN. Corresponding values for the XR36 were 1.2% for LS and 2.3% for FN. Comparison between the XR26 and XR36 was performed using 50 phantom spine measurements for each machine. The XR36 was consistently found to give slightly higher measurements (2.4%) than the XR26. BMD measurements obtained from the XR36 were therefore corrected to correspond with the XR26 by regression analysis.

Construction and validation of DNA pools
We employed a four-stage design to identify markers that were associated with BMD, using a similar strategy to that employed by Fisher and colleagues to identity loci associated with cognitive function (24Go). We performed a first round screen by genotyping a series of markers from the region of interest in DNA pools constructed from individuals with low and high lumbar-BMD (DNA pools 1). Markers that were significantly associated with BMD in the screening pool (pool 1) at a nominal level of P≤0.05 were genotyped in a replication (pool 2) and markers that were positive in both pools were further investigated. The rationale for this approach is that false positive associations which are identified as the result of the low stringency cut-off in the first round screen are removed at the stage of the replication screen (24Go). For markers that remained significantly associated with BMD in both DNA pool pairs, we genotyped the individual samples that had been combined to make the DNA pools. Markers that remained significantly associated with BMD after individual genotyping were analysed in an association study of 1053 women from the APOSS population, who were unselected with regard to BMD values. The screening and replication DNA pools were prepared from individuals with LS-BMD values (adjusted for age, weight and height) lying within the lowest ~13th percentile and the highest 13th percentile of the APOSS study population, after exclusion of participants that had used HRT for more than 3 months.

Individuals were sorted by the adjusted BMD value and numbered 1–400 (low-BMD) and 1–400 (high-BMD). Samples from individuals that had been assigned odd numbers were combined to make DNA pools 1 (the screening pools) and individuals that had been assigned even numbers were combined to form DNA pools 2 (the replication pools).

The samples were quantitated using a DNA binding dye (Hoescht 33258) and aliquots of 0.25 µg from each individual were combined to make each DNA pool. The pools were validated by analysis of two microsatellite markers [D11S4178 and a TA dinucleotide repeat in the promoter of the oestrogen receptor-{alpha} gene (25Go)] in the pooled samples as previously described (26Go,27Go) and the results compared with those of individual genotyping. For D11S4178 the correlation coefficient, r, between predicted and actual allele frequencies all four pools lay between 0.994–0.997 (P<0.001) and for the TA repeat the values lay between 0.970–0.997 (P<0.001). During this validation, we noted that some of the DNA samples that had been combined to make the DNA pools consistently failed to amplify for any markers as the result of sample degradation. In view of this, the actual numbers of evaluable samples included in the DNA pools were: 172 in low pool 1, 169 in high pool 1, 177 in low pool 2 and 177 in high pool 2.

DNA extraction and genotyping
Genomic DNA was extracted from peripheral blood leukocytes using the Nucleon II DNA extraction kit (Scotlab, Coatbridge, UK). Genotyping single nucleotide polymorphisms (SNP) in the DNA pools was performed by single base extension using SNaPshotTM (ABI Biosystems) or SNuPeTM (Pharmacia Amersham Biotech, Buckinghamshire, UK) kits on products generated from the DNA pools by PCR using Qiagen Taq DNA polymerase (Qiagen, Crawley, UK) according to the manufacturer's instructions. The reaction products for SNuPeTM were analysed on a MegaBACETM 1000 capillary DNA sequencer (Amersham Pharmacia Biotech UK Ltd, Buckinghamshire, UK) and those generated by SNaPshotTM on a ABI PRISM® 3100 capillary-based electrophoresis system. Individual genotyping was done by DNA sequencing of PCR-amplified fragments of genomic DNA products. The PCR products were treated with ExoSAP ITTM (USB Corporation, Cleveland, OH, USA) to degrade unincorporated primers and dNTPs and sequenced using the DYEnamic ET dye terminator cycle sequencing kit (Amersham Pharmacia Biotech UK Ltd, Buckinghamshire, UK) according to standard procedures. Reactions were analysed on a MegaBACETM 1000 capillary DNA sequencer.

Statistical analysis
Statistical analyses were carried out using Minitab version 12. Comparison of allele and genotype frequencies in high- and low-BMD groups was performed using the {chi}2 test. Differences in BMD between the genotype and haplotype groups were tested using GLM-ANOVA to adjust for confounding factors such as age, body mass index (BMI), menopausal status and HRT use. Haplotypes were inferred from genotype data using the PHASE software program (28Go). Haplotype data were used only for subjects where the probability of correct assignment was greater than 95% as assessed by PHASE and the study subjects were coded according to whether they had two copies, one copy or no copies of the haplotype under consideration. Power calculations indicated that the association study had approximately 88% power to detect differences in BMD of 0.20 SD units between genotypes for a polymorphism with allele frequency of 0.5.


   ACKNOWLEDGEMENTS
 
We are grateful to S. Main, A. Bassiti, P. Kang and G. Taylor for their technical assistance. This study was supported in part by a REAP grant from the US Department of Veterans Affairs and was based on work supported by NIH grant P01-AG13918. It was also supported by grants from the European Commission to SHR (QRLT-2001-02629); the European Calcified Tissues Society to (FEAM); the Arthritis Research Campaign to SHR (R0592) and the Medical Research Council to SHR and DMR (co-operative group grant G982381). CAP was supported by an MRC-CASE studentship, OMEA by a ARC Non-clinical Lectureship award; and RJSR by a Research Career Scientist award from the Department of Veterans Affairs.

Conflict of Interest statement. None declared.


   FOOTNOTES
 
{dagger} The authors wish it to be known that, in their opinion, the first three authors should be regarded as joint First Authors. Back


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
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S. L. Ferrari, E. Seeman, and G. J. Strewler
Clinical and Basic Research Papers - October 2005 Selections
IBMS BoneKEy, November 1, 2005; 2(11): 1 - 6.
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