Is population bone mineral density variation linked to the marker D11S987 on chromosome 11q12-13?

Molecular genetic studies of gene identification for osteoporosis: a 2004 update

This review summarizes comprehensively the most important and representative molecular genetics studies of gene identification for osteoporosis published up to the end of December 2004. It is intended to constitute a sequential update of our previously published review covering the available data up to the end of 2002. Evidence from candidate gene association studies and genome-wide linkage studies in humans, as well as quantitative trait locus mapping animal models are reviewed separately. Studies of transgenic and knockout mice models relevant to osteoporosis are summarized. An important extension of this update is incorporation of functional genomic studies (including DNA microarrays and proteomics) on osteogenesis and osteoporosis, in light of the rapid advances and the promising prospects of the field. Comments are made on the most notable findings and representative studies for their potential influence and implications on our present understanding of genetics of osteoporosis. The format adopted by this review should be ideal for accommodating future new advances and studies.

Assessment of linkage and association of 13 genetic loci with bone mineral density

Bone mineral density (BMD), an important risk factor for osteoporosis, is a complex trait likely affected by multiple genes. The linkage and/or association of 13 polymorphic loci of seven candidate genes (estrogen receptor alpha [ERalpha] and beta [ERbeta], calcium-sensing receptor, vitamin D receptor, collagen type 1alpha1, low-density lipoprotein [LDL] receptor-related protein 5 [LRPS], and transforming growth factor beta1) were evaluated in 177 southern Chinese pedigrees of 674 subjects, with each pedigree identified through a proband having a BMD Z score of -1.28 or less at the hip or spine. A suggestive linkage was detected between the IVS1-351A/G polymorphism of ERalpha and spine BMD, and between the 1082G/A, 1730G/A, and D14S1026 polymorphisms of ERbeta and BMD at both spine and hip. The quantitative transmission disequilibrium test (QTDT) detected total family association between 1730G/A of ERbeta and BMD at spine and hip; between D14S1026 of ERbeta and hip BMD; and between the 266A/G and 2220C/T polymorphisms of LRP5 and hip BMD. Similar total family associations were detected when only the females were analyzed. In addition, the IVS1-397T/C polymorphism of ERalpha was associated with spine BMD, and the 266A/G and 2220C/T polymorphisms of LRP5 were associated with femoral neck BMD in the females. A within-family association was detected with the IVS1-397T/C polymorphism of ERalpha, and the 266A/G and 2220C/T polymorphisms of LRP5 in the females. The effect of each polymorphism on BMD variance ranged from 1% to 4%. In conclusion, ERalpha, ERbeta and LRP5 are important candidate genes determining BMD variation, especially in females.

A genome-wide linkage scan for bone mineral density in an extended sample: evidence for linkage on 11q23 and Xq27

BACKGROUND

Osteoporosis is a major public health problem, mainly quantified by low bone mineral density (BMD). The majority of BMD variation is determined by genetic effects. A pilot whole genome linkage scan (WGS) was previously reported in 53 white pedigrees with 630 subjects. Several genomic regions were suggested to be linked to BMD variation.

OBJECTIVE

To substantiate these previous findings and detect new genomic regions.

METHODS

A WGS was conducted on an extended sample where the size was almost tripled (1816 subjects from 79 pedigrees). All the subjects were genotyped with 451 microsatellite markers spaced approximately 8.1 cM apart across the human genome. Two point and multipoint linkage analyses were carried out using the variance component method.

RESULTS

The strongest linkage signal was obtained on Xq27 with two point LOD scores of 4.30 for wrist BMD, and 2.57 for hip BMD, respectively. Another important region was 11q23, which achieved a maximum LOD score of 3.13 for spine BMD in multipoint analyses, confirming the results on this region in two earlier independent studies. Suggestive linkage evidence was also found on 7p14 and 20p12.

CONCLUSIONS

Together with the findings from other studies, the current study has further delineated the genetic basis of bone mass and highlights the importance of increasing sample size to confirm linkage findings and to identify new regions of linkage.

A genomewide linkage scan for quantitative-trait loci for obesity phenotypes

Obesity is an increasingly serious health problem in the world. Body mass index (BMI), percentage fat mass, and body fat mass are important indices of obesity. For a sample of pedigrees that contains >10,000 relative pairs (including 1,249 sib pairs) that are useful for linkage analyses, we performed a whole-genome linkage scan, using 380 microsatellite markers to identify genomic regions that may contain quantitative-trait loci (QTLs) for obesity. Each pedigree was ascertained through a proband who has extremely low bone mass, which translates into a low BMI. A major QTL for BMI was identified on 2q14 near the marker D2S347 with a LOD score of 4.04 in two-point analysis and a maximum LOD score (MLS) of 4.44 in multipoint analysis. The genomic region near 2q14 also achieved an MLS >2.0 for percentage of fat mass and body fat mass. For the putative QTL on 2q14, as much as 28.2% of BMI variation (after adjustment for age and sex) may be attributable to this locus. In addition, several other genomic regions that may contain obesity-related QTLs are suggested. For example, 1p36 near the marker D1S468 may contain a QTL for BMI variation, with a LOD score of 2.75 in two-point analysis and an MLS of 2.09 in multipoint analysis. The genomic regions identified in this and earlier reports are compared for further exploration in extension studies that use larger samples and/or denser markers for confirmation and fine-mapping studies, to eventually identify major functional genes involved in obesity.

Mutation patterns at dinucleotide microsatellite loci in humans

Microsatellites are a major type of molecular markers in genetics studies. Their mutational dynamics are not clear. We investigated the patterns and characteristics of 97 mutation events unambiguously identified, from 53 multigenerational pedigrees with 630 subjects, at 362 autosomal dinucleotide microsatellite loci. A size-dependent mutation bias (in which long alleles are biased toward contraction, whereas short alleles are biased toward expansion) is observed. There is a statistically significant negative relationship between the magnitude (repeat numbers changed during mutation) and direction (contraction or expansion) of mutations and standardized allele size. Contrasting with earlier findings in humans, most mutation events (63%) in our study are multistep events that involve changes of more than one repeat unit. There was no correlation between mutation rate and recombination rate. Our data indicate that mutational dynamics at microsatellite loci are more complicated than the generalized stepwise mutation models.

Role of genetics in osteoporosis

Osteoporosis is a disease characterized by fragile bones and high susceptibility to low-trauma fractures. It is a serious health problem, especially in elderly women. Bone mineral density (BMD) has been employed most commonly as the index for defining and studying osteoporosis. BMD has high genetic determination, with heritability ranging from 50 to 90%. Various gene-mapping approaches have been applied to identify specific genes underlying osteoporosis, largely using BMD as the study phenotype. We review here the genetic determination of osteoporosis as defined by BMD and discuss a fundamental issue we encounter in genetic research in osteoporosis: the choice of phenotype(s) to study. We briefly summarize and discuss advantages and disadvantages of various approaches used in genetic studies of osteoporosis. Finally, we review and discuss the current status for mapping and identification of genes for osteoporosis. We focus on linkage studies in humans and quantitative trait loci mapping in mice to supplement the already extensive reviews of association studies made by many investigators for candidate genes.

Toward high-throughput genotyping: dynamic and automatic software for manipulating large-scale genotype data using fluorescently labeled dinucleotide markers

To efficiently manipulate large amounts of genotype data generated with fluorescently labeled dinucleotide markers, we developed a Microsoft database management system, named. offers several advantages. First, it accommodates the dynamic nature of the accumulations of genotype data during the genotyping process; some data need to be confirmed or replaced by repeat lab procedures. By using, the raw genotype data can be imported easily and continuously and incorporated into the database during the genotyping process that may continue over an extended period of time in large projects. Second, almost all of the procedures are automatic, including autocomparison of the raw data read by different technicians from the same gel, autoadjustment among the allele fragment-size data from cross-runs or cross-platforms, autobinning of alleles, and autocompilation of genotype data for suitable programs to perform inheritance check in pedigrees. Third, provides functions to track electrophoresis gel files to locate gel or sample sources for any resultant genotype data, which is extremely helpful for double-checking consistency of raw and final data and for directing repeat experiments. In addition, the user-friendly graphic interface of renders processing of large amounts of data much less labor-intensive. Furthermore, has built-in mechanisms to detect some genotyping errors and to assess the quality of genotype data that then are summarized in the statistic reports automatically generated by. The can easily handle >500,000 genotype data entries, a number more than sufficient for typical whole-genome linkage studies. The modules and programs we developed for the can be extended to other database platforms, such as Microsoft SQL server, if the capability to handle still greater quantities of genotype data simultaneously is desired.

Characterization of genetic and lifestyle factors for determining variation in body mass index, fat mass, percentage of fat mass, and lean mass

In this study, we simultaneously characterized genetic and lifestyle factors (exercise, smoking, and alcohol consumption) in determining variation in body mass index (BMI), fat mass, percentage of fat mass (PFM), and lean mass while adjusting for the effects of age and sex. Six hundred fifty-eight Caucasian individuals from 48 pedigrees were studied for BMI. Among these individuals, 289 from 38 pedigrees were studied for fat mass, PFM, and lean mass measured by dual X-ray absorptiometry (DXA). After adjusting for age, sex, and lifestyle factors, the heritabilities (h(2)) of BMI, fat mass, PFM, and lean mass ranged from 0.52 to 0.57 with associated standard errors ranging from 0.09 to 0.14. After accounting for significant sex and age effects, exercise had significant effects for all the phenotypes studied, and the effects of smoking and alcohol consumption were not significant. Therefore, significant proportions of variation in BMI, fat mass, PFM, and lean mass were under genetic control, and exercise had a significant effect in reducing BMI, fat mass, and PFM and in increasing lean mass. This study warrants further genetic linkage analyses to search for genes for the obesity-related phenotypes measured by DXA in our population.