The search for human osteoporosis genes

Osteoporosis is the most prevalent metabolic bone disease and a major clinical and public health problem. Heredity plays an important and well-established role in determining the lifetime risk of this disease. Major efforts are currently underway to identify the specific genes and their allelic variations that contribute to the heritable component to osteoporosis. A number of laboratories are using quantitative trait locus (QTL) methods of genome scanning in families and animal models to identify candidate genomic regions and, ultimately, the genes and genetic variations that lead to osteoporosis. Several chromosomal regions of the human genome have now been linked to osteoporosis-related phenotypes. Although the specific genes contributing to the majority of these linkage signals have not been identified, two positional candidate genes have now been identified: low density lipoprotein receptor-related protein 5 (LRP5) and bone morphogenetic protein 2 (BMP2). A number of QTL has also been identified by cross-breeding strains of mice with variable bone density and several of these QTL have been fine mapped, providing a rich new base for understanding osteoporosis. Genetic association analyses have also provided evidence for a modest relationship between allelic variants in several biological candidate genes and bone mass and the risk of fracture. These ongoing animal and human studies will provide a continuing source of new insight into the genetic regulation of bone and mineral metabolism and the molecular etiology of osteoporosis. The new insight that will emerge from this ongoing research should lead to new ways of diagnosing, preventing and treating the growing clinical and public health problem of osteoporosis.     

Gene variants for osteoporosis and their pleiotropic effects in aging

The prevalence of osteoporosis is raising worldwide as improving conditions of living and treatment of other common diseases continuously increases life expectancy. Thus, osteoporosis affects most women above 80 years of age and, at the age of 50, the lifetime risk of suffering an osteoporosis-related fracture approaches 50% in women and 20% in men. Numerous genetic, hormonal, nutritional and life-style factors contribute to the acquisition and maintenance of bone mass. Among them, genetic variations explain as much as 70% of the variance for bone mineral density (BMD) in the population. Dozens of quantitative trait loci (QTLs) for BMD have been identified by genome screening and linkage approaches in humans and mice, and more than 100 candidate gene polymorphisms tested for association with BMD and/or fracture. Sequence variants in the vitamin D receptor (VDR), collagen 1 alpha 1 chain (Col1A1), estrogen receptor alpha (ESR1), interleukin-6 (IL-6) and LDL receptor-related protein 5 (LRP5) genes were all found to be significantly associated with differences in BMD and/or fracture risk in multiple replication studies. Moreover, some genes, such as VDR and IL-6, were shown to interact with non-genetic factors, i.e. calcium intake and estrogens, to modulate BMD. Since these gene variants have also been associated with other complex disorders, including cancer and coronary heart disease, they may represent common genetic susceptibility factors exerting pleiotropic effects during the aging process.     

Genetic Regulation of Bone Metabolism in the Chicken: Similarities and Differences to Mammalian Systems

Birds have a unique bone physiology, due to the demands placed on them through egg production. In particular their medullary bone serves as a source of calcium for eggshell production during lay and undergoes continuous and rapid remodelling. We take advantage of the fact that bone traits have diverged massively during chicken domestication to map the genetic basis of bone metabolism in the chicken. We performed a quantitative trait locus (QTL) and expression QTL (eQTL) mapping study in an advanced intercross based on Red Junglefowl (the wild progenitor of the modern domestic chicken) and White Leghorn chickens. We measured femoral bone traits in 456 chickens by peripheral computerised tomography and femoral gene expression in a subset of 125 females from the cross with microarrays. This resulted in 25 loci for female bone traits, 26 loci for male bone traits and 6318 local eQTL loci. We then overlapped bone and gene expression loci, before checking for an association between gene expression and trait values to identify candidate quantitative trait genes for bone traits. A handful of our candidates have been previously associated with bone traits in mice, but our results also implicate unexpected and largely unknown genes in bone metabolism. In summary, by utilising the unique bone metabolism of an avian species, we have identified a number of candidate genes affecting bone allocation and metabolism. These findings can have ramifications not only for the understanding of bone metabolism genetics in general, but could also be used as a potential model for osteoporosis as well as revealing new aspects of vertebrate bone regulation or features that distinguish avian and mammalian bone.     

Confirmation of linkage to chromosome 1q for peak vertebral bone mineral density in premenopausal white women

Peak bone mineral density (BMD) is a highly heritable trait and is a good predictor of the risk of osteoporosis and fracture in later life. Recent studies have sought to identify the genes underlying peak BMD. Linkage analysis in a sample of 464 premenopausal white sister pairs detected linkage of spine BMD to chromosome 1q (LOD 3.6). An independent sample of 254 white sister pairs has now been genotyped, and it also provides evidence of linkage to chromosome 1q (LOD 2.5) for spine BMD. Microsatellite markers were subsequently genotyped for a 4-cM map in the chromosome 1q region in all available white sister pairs (n=938), and a LOD score of 4.3 was obtained near the marker D1S445. Studies in the mouse have also detected evidence of linkage to BMD phenotypes in the region syntenic to our linkage finding on chromosome 1q. Thus, we have replicated a locus on 1q contributing to BMD at the spine and have found further support for the region in analyses employing an enlarged sample. Studies are now ongoing to identify the gene(s) contributing to peak spine BMD in women.     

Genetic dissection of femur breaking strength in a large population (MRL/MpJ x SJL/J) of F2 Mice: single QTL effects, epistasis, and pleiotropy

Bone breaking strength is an ultimate measurement of the risk of fracture. For a practical reason, bone mineral density (BMD) has been commonly used for predicting the risk instead. To identify genetic loci influencing femur-breaking strength (FBS), which was measured by three-point bending using an Instron DynaMight Low-Force Testing System, the whole-genome scan was carried out using 119 polymorphic markers in 633 (MRLxSJL) F2 female mice. We identified six significant quantitative trait loci (QTL) affecting bone breaking strength on chromosomes 1, 2, 8, 9, 10, and 17, which together explained 23% of F2 variance. Of those, the QTL on chromosomes 2, 8, and 10 seem to be unique to bone breaking strength, whereas the remaining three QTL are concordant with femur BMD QTL. Genetic analysis suggests that, of these six FBS QTL, three influence BMD, two influence bone quality, and one influences bone size. We detected multiple significant epistatic interactions for FBS, which accounts for half (14.6%) of F2 variance compared with significant single QTL effects. We found evidence that pleiotropic effect might represent a common genetic mechanism to coordinately regulate bone-related phenotypes. Pleiotropic analysis also suggests that our current threshold level for significant QTL may be too high to detect biologically significant QTL with small effect. Together with epistatic interactions, these undetected small QTL could explain 30% of genetic variance that remains unaccounted for in this study (heritability estimate for FBS is 68%). Our findings in single QTL effects, epistasis, and pleiotropy demonstrate that partially overlapped but distinct combinations of genetic loci in MRL/MpJ and SJL/J inbred strains of mice regulate bone strength and bone density. Identification of the genes unique to FBS may have an impact on prediction of osteoporosis in human.     

Genetics of osteoporosis

Osteoporosis is a skeletal disease characterized by low bone mineral density (BMD) and microarchitectural deterioration of bone tissue, which increases susceptibility to fractures. BMD is a complex quantitative trait with normal distribution and seems to be genetically controlled (in 50–90% of the cases), according to studies on twins and families. Over the last 20 years, candidate gene approach and genome-wide association studies (GWAS) have identified single-nucleotide polymorphisms (SNPs) that are associated with low BMD, osteoporosis, and osteoporotic fractures. These SNPs have been mapped close to or within genes including those encoding nuclear receptors and WNT-β-catenin signaling proteins. Understanding the genetics of osteoporosis will help identify novel candidates for diagnostic and therapeutic targets.     

Genetic determinants of bone mass.

A genetic contribution to bone mass determination was first described in the early 70s. Elucidation of gene contribution to this has since been attempted through studies analyzing associations between bone mass acquisition and/or maintenance and polymorphic variations of several genes. The first to be described was the vitamin D receptor gene (VDR), initially claimed to contribute to almost 75% of the genetic variation in bone mineral density (BMD) in twin and general population studies. Not all of the studies published to date conclude that a clear relationship exists between polymorphic VDR alleles and BMD, and the molecular basis for the VDR gene polymorphisms influence on bone mineralization has not yet been clarified. Since then, other genes with a significant role in bone metabolism such as estradiol receptor, collagen type 1alpha1, TGF-beta1, interleukin-6, calcitonin receptor, alpha2-HS-glycoprotein, osteocalcin, calcium-sensing receptor, interleukin-1 receptor antagonist, beta3-adrenergic receptor, apolipoprotein E, PTH, IGF-I and glucocorticoid receptor have been analyzed. Some polymorphic variations in these genes have been associated in some works with significant differences in BMD, with even more significant contributions when associations of different gene polymorphisms were analyzed. Again, the molecular basis for the contribution of these alleles to bone mass determination has not yet been described. A different approach has been attempted by linkage analysis of loci involved in bone density in pedigrees with low BMD using BMD as a quantitative trait. Recent results do not confirm, in these families, any association with any of the previously reported genes, but rather with other as yet unidentified genes. The genetic contribution to mild variations in the general population, as a result of environmental and endogenous individual influences, probably differs completely from that providing a pathologic BMD.     

Genetic research in osteoporosis: Where are we? Where should we go next?

Fractures resulting from low bone mass and excessive skeletal fragility (osteoporosis) are common worldwide both in males and females, particularly in later years of life. Both fractures, and the most important predictor of fractures, bone mass, are now known to be strongly heritable. This fact, plus the current growth in genetic science, has led to a surge of genetic research in osteoporosis, mostly in the search for genes and their polymorphisms that are responsible for variation in bone mass. Finding the genetic basis underlying variation in bone mass will lead us to deeper understanding of the biology of bone mass accumulation, maintenance and adaptation to load. This, plus finding the genetic basis for overall variation in fracture risk per se, will facilitate the development of interventions, both pharmaceutical and non-pharmaceutical, to prevent and/or treat osteoporosis successfully. This research has produced a rather large number of gene loci that seem to influence bone mass. The challenge now is to refine the statistical genetics and the phenotypes involved so that we can confidently identify those gene loci that truly influence bone mass, and to find ways to study the genetic basis for the most direct disease outcome of interest, fracture.     

Codon 325 sequence polymorphism of the estrogen receptor alpha gene and bone mineral density in postmenopausal women

Estrogen receptor alpha (ER alpha) encoding gene is one of the candidate genes to be involved in the development of osteoporosis. Until now correlation between three ER gene polymorphisms (identified with PvuII, XbaI and BstUI) and bone mineral density (BMD) have been investigated. The results of these studies are contradictory. Thus the aim of our work was to search for new, yet unknown, and probably more informative polymorphism(s) of the ER alpha gene. For detection of mutations the whole coding region of the ER alpha gene was screened systematically. In a group of 85 late postmenopausal women all of the eight exons were amplified by polymerase chain reaction (PCR) and fragments were further analyzed by single-stranded conformation polymorphism (SSCP) analysis. Mutations were confirmed by direct DNA sequencing. In the whole coding region of the ER alpha gene two silent mutations in codon 87 and 325, respectively, were found. The silent mutation in codon 85 of exon 1 (GCG-->GCC; A87A) was described previously, as BstUI polymorphism. On the other side, the silent mutation in codon 325 (CCC-->CCG; P325P), located in exon 4, has not been analyzed so far in correlation with BMD. According to the distribution of genotypes CC:CG:GG=49.4:41.2:9.4, we can affirm the existence of genetic polymorphism in codon 325 in our population of late postmenopausal women. The mean femoral neck BMD, but not the lumbar spine BMD, was significantly lower (P=0.029) in the homozygous GG-women with CCG/CCG codon 325 as compared to the homozygous CC-women with the normal codon CCC/CCC. Our results suggest that codon 325 sequence polymorphism of the ER alpha gene might be one of the factors associated with low femoral neck BMD.     

Functional genomics complements quantitative genetics in identifying disease-gene associations

An ultimate goal of genetic research is to understand the connection between genotype and phenotype in order to improve the diagnosis and treatment of diseases. The quantitative genetics field has developed a suite of statistical methods to associate genetic loci with diseases and phenotypes, including quantitative trait loci (QTL) linkage mapping and genome-wide association studies (GWAS). However, each of these approaches have technical and biological shortcomings. For example, the amount of heritable variation explained by GWAS is often surprisingly small and the resolution of many QTL linkage mapping studies is poor. The predictive power and interpretation of QTL and GWAS results are consequently limited. In this study, we propose a complementary approach to quantitative genetics by interrogating the vast amount of high-throughput genomic data in model organisms to functionally associate genes with phenotypes and diseases. Our algorithm combines the genome-wide functional relationship network for the laboratory mouse and a state-of-the-art machine learning method. We demonstrate the superior accuracy of this algorithm through predicting genes associated with each of 1157 diverse phenotype ontology terms. Comparison between our prediction results and a meta-analysis of quantitative genetic studies reveals both overlapping candidates and distinct, accurate predictions uniquely identified by our approach. Focusing on bone mineral density (BMD), a phenotype related to osteoporotic fracture, we experimentally validated two of our novel predictions (not observed in any previous GWAS/QTL studies) and found significant bone density defects for both Timp2 and Abcg8 deficient mice. Our results suggest that the integration of functional genomics data into networks, which itself is informative of protein function and interactions, can successfully be utilized as a complementary approach to quantitative genetics to predict disease risks. All supplementary material is available at http://cbfg.jax.org/phenotype.     

Genetic and Molecular Basis of QTL of Diabetes in Mouse: Genes and Polymorphisms

A systematic study has been conducted of all available reports in PubMed and OMIM (Online Mendelian Inheritance in Man) to examine the genetic and molecular basis of quantitative genetic loci (QTL) of diabetes with the main focus on genes and polymorphisms. The major question is, What can the QTL tell us? Specifically, we want to know whether those genome regions differ from other regions in terms of genes relevant to diabetes. Which genes are within those QTL regions, and, among them, which genes have already been linked to diabetes? whether more polymorphisms have been associated with diabetes in the QTL regions than in the non-QTL regions.Our search revealed a total of 9038 genes from 26 type 1 diabetes QTL, which cover 667,096,006 bp of the mouse genomic sequence. On one hand, a large number of candidate genes are in each of these QTL; on the other hand, we found that some obvious candidate genes of QTL have not yet been investigated. Thus, the comprehensive search of candidate genes for known QTL may provide unexpected benefit for identifying QTL genes for diabetes. Key Words: Quantitative trait loci, type 1 diabetes, insulin-dependent diabetes mellitus (IDDM), candidate gene, polymorphism, mouse.     

LOD Score Exclusion Analyses for Candidate QTLs using Random Population Samples

While extensive analyses have been conducted to test for, no formal analyses have been conducted to test against, the importance of candidate genes as putative QTLs using random population samples. Previously, we developed an LOD score exclusion mapping approach for candidate genes for complex diseases. Here, we extend this LOD score approach for exclusion analyses of candidate genes for quantitative traits. Under this approach, specific genetic effects (as reflected by heritability) and inheritance models at candidate QTLs can be analyzed and if an LOD score is < or = -2.0, the locus can be excluded from having a heritability larger than that specified. Simulations show that this approach has high power to exclude a candidate gene from having moderate genetic effects if it is not a QTL and is robust to population admixture. Our exclusion analysis complements association analysis for candidate genes as putative QTLs in random population samples. The approach is applied to test the importance of Vitamin D receptor (VDR) gene as a potential QTL underlying the variation of bone mass, an important determinant of osteoporosis.     

Epistasis between QTLs for bone density variation in Copenhagen × dark agouti F2 rats

The variation in several of the risk factors for osteoporotic fracture, including bone mineral density (BMD), has been shown to be strongly influenced by genetic differences. However, the genetic architecture of BMD is complex in both humans and in model organisms. We previously reported quantitative trait locus (QTL) results for BMD from a genome screen of 828 F2 progeny of Copenhagen and dark agouti rats. These progeny also provide an excellent opportunity to search for epistatic effects, or interaction between genetic loci, that contribute to fracture risk. Microsatellite marker data from a 20-cM genome screen was analyzed along with weight-adjusted bone density (DXA and pQCT) phenotypic data using the R/qtl software package. Genotype and phenotype data were permuted to determine genome-wide significance thresholds for the full model and epistasis (interaction) LOD scores corresponding to an alpha level of 0.01. A novel locus on chromosome 15 and a previously reported chromosome 14 QTL demonstrated a strong epistatic effect on BMD at the femur by DXA (LOD = 5.4). Two novel QTLs on chromosomes 2 and 12 were found to interact to affect total BMD at the femur midshaft by pQCT (LOD = 5.0). These results provide new information regarding the mode of action of previously identified QTL in the rat, as well as identifying novel loci that act in combination with known QTL or with other novel loci to contribute to BMD variation.     

Parathyroid hormone gene with bone phenotypes in Chinese

Osteoporosis is a common disorder afflicting old people. The parathyroid hormone (PTH) gene is involved in bone remodeling and calcium homeostasis, and has been considered as an important candidate gene for osteoporosis. In this study, we simultaneously tested linkage and/or association of PTH gene with bone mineral density (BMD) and bone mineral content (BMC), two important risk factors for osteoporosis. A sample of 1263 subjects from 402 Chinese nuclear families was used. The families are composed of both parents and at least one healthy daughter aged from 20 to 45 years. All the subjects were genotyped at the polymorphic BstBI site inside the intron 2 of the PTH gene (a nucleotide substitution of G to A at the position +3244). BMD and BMC were measured at the lumbar spine and the hip region via dual-energy X-ray absorptiometry (DXA). Using QTDT (quantitative trait transmission disequilibrium test), we did not find significant results for association or linkage between the PTH gene and BMD or BMC variation at the spine or hip. Our data do not support the PTH gene as a quantitative trait locus (QTL) underlying the bone phenotypic variation in the Chinese population.     

遗传基因组学(Genetical genomics)的研究进展

遗传基因组学(geneticalgenomics)是将微阵列技术和数量性状座位(QTL)分析结合起来,全基因组水平上定位基因表达的QTL(eQTL).它为研究复杂性状的分子机理和调控网络提供全新的手段.遗传基因组这个概念和研究策略在2001年由Janson和Nap首先提出,到目前为止,遗传基因组学已应用于酵母、老鼠、人以及玉米等植物.研究结果表明:基因表达水平的差异是可遗传的复杂性状;eQTL可以分为顺式作用eQTL和反式作用eQTL,顺式作用eQTL就是某个基因的eQTL定位到该基因所在的基因组区域,表明可能是该基因本身的差别引起mRNA水平的差别,反式作用就是eQTL定位到其他基因组区域,表明其他基因的差别控制该基因mRNA水平的差异.将eQTL结果、基因功能注解以及多种统计分析方法相结合,不仅能更准确地鉴别控制复杂性状及其相关基因表达的候选基因,而且能构建相应的基因调控网络.     

Advances in QTL mapping in pigs

Over the past 15 years advances in the porcine genetic linkage map and discovery of useful candidate genes have led to valuable gene and trait information being discovered. Early use of exotic breed crosses and now commercial breed crosses for quantitative trait loci (QTL) scans and candidate gene analyses have led to 110 publications which have identified 1,675 QTL. Additionally, these studies continue to identify genes associated with economically important traits such as growth rate, leanness, feed intake, meat quality, litter size, and disease resistance. A well developed QTL database called PigQTLdb is now as a valuable tool for summarizing and pinpointing in silico regions of interest to researchers. The commercial pig industry is actively incorporating these markers in marker-assisted selection along with traditional performance information to improve traits of economic performance. The long awaited sequencing efforts are also now beginning to provide sequence available for both comparative genomics and large scale single nucleotide polymorphism (SNP) association studies. While these advances are all positive, development of useful new trait families and measurement of new or underlying traits still limits future discoveries. A review of these developments is presented.     

Mapping of the chromosome 17 BMD QTL in the F<Subscript>2</Subscript> male mice of MRL/MpJ × SJL/J

Developing treatment strategies for osteoporosis would be facilitated by identifying genes regulating bone mineral density (BMD). One way to do so is through quantitative trait locus (QTL) mapping. However, there are sex differences in terms of the presence/absence and locations of BMD QTLs. In a previous study, our group identified a BMD QTL on chromosome 17 in the F₂ female mice of the MRL/MpJ × SJL/J cross. Here, we determined whether it was also present in the male mice of the same cross. Furthermore, we also intended to reduce the QTL region by increasing marker density. Interval mapping showed that the same QTL based on chromosomal positions was present in the male mice, with logarithmic odds (LOD) scores of 4.0 for femur BMD and 5.2 for total body BMD. Although there was a body weight QTL at the same location, the BMD QTL was not affected by the adjustment for body weight. Mapping with increased marker density indicated a most likely region of 35–55 Mb for this QTL. There were also co-localized QTLs for femur length, femur periosteal circumference (PC) and total body bone area, suggesting possibility of pleiotropy. Runx2 and VEGFA are strong candidate genes located within this QTL region.     

Chasing the genes that control resistance to gastrointestinal nematodes

The host-protective immune response to infection with gastrointestinal (GI) nematodes involves a range of interacting processes that begin with recognition of the parasite's antigens and culminate in an inflammatory reaction in the intestinal mucosa. Precisely which immune effectors are responsible for the loss of specific worms is still not known although many candidate effectors have been proposed. However, it is now clear that many different genes regulate the response and that differences between hosts (fast or strong versus slow or weak responses) can be explained by allelic variation in crucial genes associated with the gene cascade that accompanies the immune response and/or genes encoding constitutively expressed receptor/signalling molecules. Major histocompatibility complex (MHC) genes have been recognized for some time as decisive in controlling immunity, and evidence that non-MHC genes are equally, if not more important in this respect has also been available for two decades. Nevertheless, whilst the former have been mapped in mice, only two candidate loci have been proposed for non-MHC genes and relatively little is known about their roles. Now, with the availability of microsatellite markers, it is possible to exploit linkage mapping techniques to identify quantitative trait loci (QTL) responsible for resistance to GI nematodes. Four QTL for resistance to Heligmosomoides polygyrus, and additional QTL affecting faecal egg production by the worms and the accompanying immune responses, have been identified. Fine mapping and eventually the identification of the genes (and their alleles) underlying QTL for resistance/susceptibility will permit informed searches for homologues in domestic animals, and human beings, through comparative genomic maps. This information in turn will facilitate targeted breeding to improve resistance in domestic animals and, in human beings, focused application of treatment and control strategies for GI nematodes.     

Mouse mutant phenotyping at scale reveals novel genes controlling bone mineral density

The genetic landscape of diseases associated with changes in bone mineral density (BMD), such as osteoporosis, is only partially understood. Here, we explored data from 3,823 mutant mouse strains for BMD, a measure that is frequently altered in a range of bone pathologies, including osteoporosis. A total of 200 genes were found to significantly affect BMD. This pool of BMD genes comprised 141 genes with previously unknown functions in bone biology and was complementary to pools derived from recent human studies. Nineteen of the 141 genes also caused skeletal abnormalities. Examination of the BMD genes in osteoclasts and osteoblasts underscored BMD pathways, including vesicle transport, in these cells and together with in silico bone turnover studies resulted in the prioritization of candidate genes for further investigation. Overall, the results add novel pathophysiological and molecular insight into bone health and disease.     

Confirmation of linkage to chromosome 1q for spine bone mineral density in southern Chinese

Chromosome 1q has previously been linked to bone mineral density (BMD) variation in the general population in several genome-wide linkage studies in both humans and mouse model. The aim of present study is to replicate and fine map the QTL influencing BMD in chromosome 1q in southern Chinese. Twelve microsatellite markers were genotyped for a 57 cΜ region in the chromosome 1q in 306 southern Chinese families with 1,459 subjects. Each of these families was ascertained through a proband with BMD Z-scores less than −1.3 at the hip or spine. BMD (g/cm²) at the L1-4 lumbar spine, femoral neck (FN), trochanter and total hip was measured by dual-energy X-ray absortiometry. Linkage analyses were performed using the variance component linkage analysis method implemented in Merlin software. Four markers (D1S2878, D1S196, D1S452, and D1S218) achieved a LOD score greater than 1.0 with spine BMD, with the maximum multipoint LOD score of 2.36 at the marker D1S196. We did not detect a LOD score greater than 1.0 for BMD at the FN, trochanter, or total hip in multipoint linkage analyses. Our results present the first evidence for the presence of an osteoporosis susceptibility gene on chromosome 1q in non-Caucasian subjects. Further analyses of candidate genes are warranted to identify QTL genes and variants underlying the variations of BMD in this region.