Osteoporosis: A Silent Disease with Complex Genetic

Available online at www.sciencedirect.com

ScienceDirect Journal of Genetics and Genomics 43 (2016) 49e61

JGG REVIEW

Osteoporosis: A Silent Disease with Complex Genetic Contribution Maryam Mafi Golchin a, Laleh Heidari b, Seyyed Mohammad Hossein Ghaderian b, Haleh Akhavan-Niaki a,* b

a Department of Genetics, Faculty of Medicine, Babol University of Medical Sciences, Babol 4717647745, Iran Department of Medical Genetics, Faculty of Medicine, Shahid Beheshti University of Medical Sciences & Health Services, Tehran 1985717443, Iran

Received 13 July 2015; revised 30 October 2015; accepted 26 December 2015 Available online 2 January 2016

ABSTRACT Osteoporosis is the most common multifactorial metabolic bone disorder worldwide with a strong genetic component. In this review, the evidence for a genetic contribution to osteoporosis and related phenotypes is summarized alongside with methods used to identify osteoporosis susceptibility genes. The key biological pathways involved in the skeleton and bone development are discussed with a particular focus on master genes clustered in these pathways and their mode of action. Furthermore, the most studied single nucleotide polymorphisms (SNPs) analyzed for their importance as genetic markers of the disease are presented. New data generated by nextgeneration sequencing in conjunction with extensive meta-analyses should contribute to a better understanding of the genetic basis of osteoporosis and related phenotype variability. These data could be ultimately used for identifying at-risk patients for disease prevention by both controlling environmental factors and providing possible therapeutic targets. KEYWORDS: Osteoporosis; Bone mineral density; Regulatory pathways; Single nucleotide polymorphisms

INTRODUCTION Abbreviations: ALDH, aldehyde dehydrogenase; APC, adenomatous polyposis coli; APOE, apolipoprotein E; BMD, bone mineral density; CBFA1, core-binding factor A1; CGAS, candidate gene association study; COL1A1, collagen type I a1; CRFs, clinical risk factors; CTNNB1, catenin b1; CYP, cytochrome P450; DBP, vitamin D binding protein; DKK1, Dickkopf1; DMP1, dentin matrix acidic phosphoprotein 1; ER, estrogen receptor; GRP177, G-protein-coupled receptor 177; GWAS, genome-wide association study; HDAC, histone deacetylase; hMSC, human mesenchymal stem cells; IBSP, Integrin-binding sialoprotein; IGF, insulin-like growth factor; IL, interleukin; LRP, low-density lipoprotein receptor-related protein; LS, linkage study; MEF2C, myocyte enhancer factor 2C; OPG, osteoprotegerin; RSPO, Rspondin; PTH, parathyroid hormone; RANKL, receptor activator of NF-kB ligand; RUNX2, runt-related transcription factor 2; SNP, single nucleotide polymorphism; SOST, sclerostin; SOX, sex-determining region Y-box; Sp1, specificity protein 1; TCF/LEF, T cell factor/lymphoid enhancer factor; TGF b, transforming growth factor b; TNFRS11B, tumor necrosis factor receptor superfamily, member 11B; UGT2B17, UDP-glucuronosyl transferase 2B17; VDR, vitamin D receptor. * Corresponding author. Tel/fax: þ98 11 3234 5874. E-mail address: [email protected] (H. Akhavan-Niaki).

Osteoporosis is a common metabolic bone disorder with a strong genetic influence. It is characterized by decrease in bone mass and defects in bone tissue, which weaken bone strength and lead to increased risk of fragility fractures (Kanis et al., 1994; Kamel, 2006). Osteoporosis affects one third of women and one out of eight men over the age of 50 (Li et al., 2010). As bone mass decreases with age during adulthood, osteoporosis is considered as a common disease of the elderly people, also known as a silent disease due to the absence of significant signs before the occurrence of fractures. Conclusively, spinal fractures cause pain and most commonly, deformity, loss of height and disability with an increased risk of future fractures (Nevitt et al., 1998), while hip fractures are more painful and often require hospitalization. Susceptibility to osteoporosis results from many different genetic variations and their interaction with environmental factors (Ralston and Uitterlinden, 2010). Correspondingly, up to 60%e80% of

http://dx.doi.org/10.1016/j.jgg.2015.12.001 1673-8527/Copyright Ó 2015, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, and Genetics Society of China. Published by Elsevier Limited and Science Press. All rights reserved.

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M. Mafi Golchin et al. / Journal of Genetics and Genomics 43 (2016) 49e61

bone loss acceleration is due to genetic factors (Ralston and de Crombrugghe, 2006). More than 66 bone mineral density (BMD) loci have been studied in genome wide association studies (GWASs), confirming the highly polygenic nature of BMD variation. Although there has been significant progress in identifying genes and loci involved in BMD, fracture and other related phenotypes over the past two to three decades, most of the genetic variants remain to be uncovered. In this review, we first describe evidences for a genetic contribution to osteoporosis and related phenotypes, then discuss about the methods used to identify osteoporosis susceptibility genes, and present the key biological pathways involved in skeleton and bone development alongside with genes clustered in each pathway.

assess fracture risk (Fini et al., 2010). However, further calibration studies are still necessary to prove the robustness of those tools (Aspray, 2015). BMD is still considered as an effective way of osteoporosis diagnosis by many researchers. Considerably, as the age at menopause is determined by multiple genes, and estrogen deficiency after menopause is an important determinant of bone loss, it seems to be logical that bone loss might be determined at least partially by genetic factors (Snieder et al., 1998). The heritability of fracture is 25%e48% (Deng et al., 2000). A family history of fracture is suggested to be a risk factor for fracture occurrence independent of BMD (Cummings et al., 1995; Torgerson et al., 1996). To date, only one GWAS of fracture performed in elderly Chinese subjects has been published (Guo et al., 2010).

PHENOTYPE AND HERITABILITY

METHODS FOR IDENTIFYING OSTEOPOROSIS SUSCEPTIBILITY GENES

The recent WHO and European guidelines for the management of osteoporosis contributed to identifying clinical risk factors (CRFs) and the use of BMD determination in order to estimate the individual probability of a fragility fracture. Remarkably, among those CRFs, the maternal history of fracture seems to be important (Kanis and Reginster, 2008). BMD is highly correlated between mothers and daughters. It is obvious that this fact is mostly due to the inheritance of bone phenotypes that determine osteoporosis (NIH Consensus Development Panel on Osteoporosis Prevention, Diagnosis, and Therapy, 2001). Twin and family studies have shown that 50%e85% of inter-individual variation in BMD is genetically determined (Krall and Dawsonhughes, 1993; Gueguen et al., 1995). Recent studies performed on twins or multigenerational families also confirmed that differences in bone microarchitecture and remodeling markers are mainly due to genetic factors rather than environmental factors (Liu et al., 2012; Stone et al., 2015; Bjørnerem et al., 2015). Several studies conducted mainly on women in the Middle Eastern countries like Lebanon (Maalouf et al., 2000; El-Hajj Fuleihan et al., 2002), Saudi Arabia (El-Desouki, 2003; Ardawi et al., 2005), Kuwait (Dougherty and Al-Marzouk, 2001) and Qatar (Hammoudeh et al., 2005) showed BMDs lower than the Western population standard. However, lower BMD values in women from Middle Eastern countries could be mainly due to the dressing style imposing reduced exposition to sunlight and subsequent reduced vitamin D activation rather than genetic factors alone. Despite these differences among populations, it is of great importance to investigate the relationship between BMD and fracture risk in order to establish local standards in populations. Although there is a high risk of fracture and low BMD in the offspring of parents with fracture (Soroko et al., 1994), as osteoporosis fractures are mainly fragility fractures principally not depending on falling but caused by low-level or even no trauma, BMD appears an appropriate marker for genetic analyses of osteoporosis. Moreover, as BMD alone appears to be a poor predictor of fragility fractures in some patients, during the last decade a range of skeletal and non-skeletal factors affecting bone regeneration and osteointegration are used to

Linkage and association genetic mapping studies are generally performed for analyzing complex traits and disease. Linkage analysis is the classical approach for gene discovery in an inherited monogenic Mendelian human disease. There are two main subtypes of linkage analysis: parametric (specifying a model of inheritance in a family) and nonparametric (no inheritance model) (Ralston and Uitterlinden, 2010). The latter method has been more widely used for analysis of complex traits. Linkage studies in animal models provide another possible way of identifying genes that regulate BMD and other relevant phenotypes. Noticeably, this approach relies on the assumption that there are at least some orthologous genes with homologous nucleotide sequences and/or biological functions in animals and humans. More than a dozen genome-wide linkage scans have been performed on BMD and other related phenotypes of osteoporosis (Wilson et al., 2004), but even in very large meta-analyses, linkage studies did not yield any genomewide significant loci for BMD (Ioannidis et al., 2007), possibly because common variants regulating BMD have modest effects which are difficult to be detected reproducibly by conventional linkage analysis (Zheng et al., 2011). Given the failure of linkage studies, researchers turned their focus to candidate gene studies. However, results often appeared to be non-replicative, probably due to the statistical power, sample size, lack of standardized phenotype and genotype, limited number of gene variants assessed and difficulties in matching cases and controls. An example of such limitations is a large-scale collaborative meta-analysis performed in 2009 (Richards et al., 2009). This study, which assessed all common SNPs in 150 candidate genes for osteoporosis, found only nine genes associated with BMD regulation. Significantly, GWAS has identified many genome-wide significant loci. GWAS is a powerful tool allowing the investigation of genetic contribution to complex diseases in a specific population composed of unrelated subjects through the analysis of a panel of SNPs surrounding a limited number of candidate genes (Hardy and Singleton, 2009; Manolio et al., 2009). The major benefit of GWASs over candidate gene


studies for common diseases is that they may lead to the identification of new susceptibility genes and pathways. However, there are numerous association studies that cannot be replicated. The first GWAS of osteoporosis was published by Kiel et al. in 2007. From 2008 to 2009, three GWASs (Richards et al., 2008; Styrkarsdottir et al., 2008, 2009) reported 18 genome-wide significant hits for BMD, and, as a consequence, GWASs on osteoporosis were greatly accelerated during the following years. Skeletal phenotypes were predominantly determined by measuring BMD values at femoral neck and/or lumbar spine (Hsu and Kiel, 2012). However, the main disadvantage of GWAS is that most available marker sets are designed to identify common alleles but not rare polymorphisms (1%e5% population frequency). Thus, many polymorphisms contributing really to a trait but with a small effect, may be missed, particularly with a limited sample size. In this way, other methods such as genome-wide sequencing and meta-analysis have also helped to identify susceptibility loci/alleles. Sequencing techniques are currently used for analyzing selected areas such as candidate loci discovered by GWAS. The technique of meta-analysis which can be performed either retrospectively or prospectively is increasingly being used in the field of osteoporosis genetics (Ioannidis et al., 2007; Rivadeneira et al., 2009). Conspicuously, by combining relevant evidence from many studies, statistical power is increased and more precise estimates of effect size can be obtained than with isolated studies. Table S1 represents different genes and loci associated with osteoporosis which were identified using above mentioned methods. KEY BIOLOGICAL PATHWAYS More than 66 loci influencing BMD have been reported after GWASs, confirming the highly polygenic nature of BMD variation. Although many of these loci are involved in key biological pathways during skeleton development, such as mesenchymal stem cell (MSC) differentiation, ossification, osteoclast differentiation, Wnt signaling and TGF-b signaling, others, such as lipid and neural pathways, have no apparently known biological function related to skeletal health. In this section, we discuss these key biological pathways influencing the skeleton and bone development along with genes clustered in these pathways. Table S2 summarizes the biological effects and important polymorphisms of genes involved in signaling pathways leading to skeleton and bone development. Vitamin D endocrine pathway Vitamin D is a steroid hormone that plays a crucial and impressive role in calcium homeostasis and skeletal metabolism. The vitamin D receptor (VDR) mediates the action of its ligand and results in normal bone mineralization and remodeling (Kochupillai, 2008). Interestingly, it was the first gene considered in the study of the genetic basis of osteoporosis. Later on, the role of Vitamin D binding protein (DBP) was also investigated in disease induction. Relatively, DBP

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plays an important role in the maintenance of calcium homeostasis and can be converted to DBP-macrophage activating factor by directly activating osteoclasts which mediate bone resorption (Fang et al., 2009). Estrogen endocrine pathway This pathway exerts a significant role in bone mass regulation and the incidence of osteoporosis. Estrogens have beneficial effects on bone development and maintenance specially through cortical and bone metabolism regulation and bone loss prevention. The association between genetic variation of genes in the estrogen pathway and osteoporosis was reported through candidate gene association study (CGAS) and GWAS (Uitterlinden et al., 2006). Population-based studies indicated the necessity of estrogens in bone homeostasis regulation in both sexes (Khosla et al., 2002; Gennari et al., 2003). This was also demonstrated by bone loss prevention and osteoporotic fracture risk reduction in estrogen-treated postmenopausal women (Cauley et al., 1995; Gu et al., 2001). Estrogen exerts its effects on skeleton by binding to specific estrogen receptors (ERs) present in the cytosol and nucleus. Two functional ERs, ERa and ERb (also named ESR1 and ESR2), encoded by distinct loci, are expressed in bone-related cells such as osteoblasts, osteoclasts and bone marrow stromal cells. There is evidence of age- and gender-specific expression of ERb protein which is involved in this pathway (Batra et al., 2003). CYP17 and CYP19 are also important genes involved in estrogen biosynthesis and are highly suggestive for BMD at various skeletal sites. The CYP17 gene encodes cytochrome P450c17a crucial for the biosynthesis of gonadal hormones, which have profitable effects on bone remodeling. Mutations in CYP17 may cause skeletal growth lag and diffuse osteoporosis (Yanase et al., 1991). The CYP19 gene encodes the aromatase enzyme that transforms androgen to estrogen and is essential for bone development. UDP-glucuronosyl transferase 2B17 (UGT2B17) is another important gene involved in this pathway. This enzyme catalyzes the conjugation of glucuronic acid to a variety of substrates, including steroid hormones, leading to their detoxification. Wnt signaling The Wnt signaling pathway is one of the most important signaling pathways in bone cells. Conclusively, it is crucial in differentiation and proliferation of bone cells. Wnts are secreted glycoproteins that bind to Frizzled receptors or complex receptors including low-density lipoprotein receptor-related protein 5/6 (LRP5/6), leading to a cascade of events within the cell allowing b-catenin stabilization and its transfer to the nucleus, where the association of T cell factor/lymphoid enhancer factor (TCF/LEF) with b-catenin leads to transcription activation (Angers and Moon, 2009). The most important genes of Wnt pathway which may be involved in osteoporosis are reviewed in detail in this section. The Wnt signaling components involved in bone tissue metabolism are shown in Fig. 1.

52 M. Mafi Golchin et al. / Journal of Genetics and Genomics 43 (2016) 49e61 Fig. 1. Wnt signaling components involved in bone formation and resorption. The binding of wingless-type MMTV integration site family members (WNTs) to transmembrane Frizzeld or lipoprotein receptor-related proteins (LRP5/6) receptors, promotes b-catenin transfer to the nucleus, where the association of T cell factor/lymphoid enhancer factor (TCF/LEF) with b-catenin leads to transcriptional activation of WNT responsive genes such as osteoprotegerin (OPG), an osteoclastogenesis inhibitory factor, in osteoblasts and osteocytes. Secreted OPG inhibits the binding of receptor activator of nuclear factor k B (RANK) to its ligand (RANKL) on the surface of osteoclasts, thereby arresting the bone resorption. Sclerostin (SOST) is an antagonist of bone morphogenetic protein 2 (BMP2). The transforming growth factor b receptor (TGFbR) also participates in osteogenesis by modulating the biological function of BMP2. Both SOST and Dickkopf (DKK) inhibit bone formation by binding LRP5/6 receptors and blocking Wnt signaling pathway in osteoblasts. Runt-related transcription factor 2 (RUNX2) is another transcription factor essential for osteoblastic differentiation. Bone tissue metabolism is also modulated by estrogen through binding estrogen receptors (ESR) in osteoblasts and osteoclasts, increasing bone formation and reducing bone resorption, respectively. Estrogen can cause a reduction of production of proinflammatory cytokines such as interleukin-1 (IL1), IL6 and tumor necrosis factor a (TNFa) by peripheral macrophages, which is another mechanism for decreasing bone resorption. Furthermore, estrogen may exert its effect by enhancing functions of regulatory T (T-reg) cells that inhibit osteoclasts differentiation and bone resorption.


Low-density lipoprotein receptor-related protein 5 (LRP5) is a transmembrane receptor which allows exogenous chemical signal transmission to the nucleus and participates in augmenting bone formation. LRP5 inactivation caused by mutation is responsible for osteoporosis-pseudoglioma syndrome, in which low bone mass and fractures occur (Gong et al., 1996). In contrast, high-bone-mass syndromes may be caused by activating mutations of LRP5 (Ralston and de Crombrugghe, 2006), or inactivating mutations of sclerostin (SOST ) (Balemans et al., 2001). SOST prevents bone formation by acting as an antagonist of LRP5/6 receptor. LRP4, also known as MEGF7 (multiple epidermal growth factor-like domains 7), shows a notable interaction with LRP5, a key regulator of bone mass (Kumar et al., 2011). This interaction alongside with SOST for femoral shaft geometry demonstrates the role of LRP4 in regulating hip structure (Boudin et al., 2013). Dickkopf1 (DKK1) is another regulatory protein which inhibits Wnt signaling by binding to the LRP5/6 receptors. Mice carrying a mutant Dkk1 gene exhibit bone mass increase (Morvan et al., 2006), while overexpression of Dkk1 in mice leads to severe osteopenia and reduced bone formation (Li et al., 2006). Serum DKK1 levels seem to be inversely associated with lumbar and femoral BMD (Butler et al., 2011). R-spondin 3 (RSPO3), which is a member of the R-spondin family (R spondin-1 to 4), can activate the Wnt pathway, especially through acting on LRP6. The amount of LRP6 at the cell surface is down-regulated by Kremen and DKK1 proteins, which cooperate to induce LRP6 endocytosis. Members of RSPO family disrupt DKK1-dependent association of LRP6 and Kremen, leading to LRP6 release. Myocyte enhancer factor 2C (MEF2C ) gene encodes another important transcription factor involved in bone development control through Wnt signaling (Arnold et al., 2007). MEF2C overexpression induces chondrocyte hypertrophy and dwarfism, while its knockout in mice is lethal (Duncan and Brown, 2010). The balance between the expressions of this gene and histone deacetylase 4 (HDAC4) is critical, as double gene mutants are rescued from the phenotype of either mutation alone (Arnold et al., 2007). Both HDAC4 and HDAC5 interact with MEF2C and activate MEF2C transcription. The MEF2C also plays a key role in regulating SOST gene expression (Leupin et al., 2007). Adenomatous polyposis coli (APC ) is another regulatory gene which encodes a tumor suppressor protein. It is also involved in cell migration and adhesion, transcriptional activation, and apoptosis. Its main role is to bind b-catenin, a key transducer of the Wnt signaling pathway, and negatively regulate the Wnt signaling cascade. Loss-of-function mutation of Apc in mice results in BMD increase of the distal femur (Holmen et al., 2005). Furthermore, familial adenomatous polyposis (FAP) patients carrying one mutation in APC gene displayed higher BMD than age- and sex-matched controls (Miclea et al., 2010). Catenin b1 (CTNNB1) is a subunit of the cadherin protein complex. CTNNB1 has a dual function, regulating both cellecell adhesion and gene transcription. It also plays a key role in Wnt signaling and MSCs differentiation to osteoblast.

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The nuclear accumulation of CTNNB1, in the presence of Wnt ligand, leads to the activation of Wnt-responsive genes. CTNNB1 acts as a coactivator for transcription factors of the TCF/LEF family. Accordingly, CTNNB1 up-regulates the expression of osteoprotegerin (OPG), also called tumor necrosis factor receptor superfamily member 11b (TNFRS11B) in osteoblasts. OPG is a major osteoclastogenesis inhibitory factor and its expression decreases the process of bone resorption. Deletion of CTNNB1 in osteoblasts results in osteopenia, while its stabilization results in high bone mass, demonstrating the pivotal role of this gene in BMD regulation (Glass et al., 2005). G-protein-coupled receptor 177 (GPR177) gene, commonly known as Wntless (WLS), is another member of Wnt signaling required for Wnt protein secretion. GPR177 plays an essential role in cell surface expression of WNT3A in human embryonic kidney (HEK293) cells (Banziger et al., 2006). Finally, parathyroid hormone (PTH) is the main regulator of calcium and phosphate homeostasis and consequently might be considered as the most important hormone regulating bone remodeling. PTH binds to G-protein-coupled receptors, present largely on osteoblast surface. Therefore, PTH administration stimulates bone formation in both experimental animals (Hock and Gera, 1992) and osteoporotic subjects (Neer et al., 2001). RANK/RANKL/OPG The receptor activator of NF-kB ligand (RANKL), a soluble factor secreted by osteoblasts and osteocytes, is critical for adequate bone metabolism as osteoclastic activity is triggered via the RANKL interaction with the RANK (TNFRSF11A) receptor, present on the osteoclast precursor cell, leading to the migration and differentiation of osteoclastic lineage cells. However, for regulation of this process, a decoy receptor for RANKL called OPG (TNFRSF11B) is produced by osteoblasts and osteocytes and prevents the binding of RANK to RANKL, thereby arresting the bone resorption cycle (Simonet et al., 1997). GWAS and meta-analysis demonstrated an association between RANK polymorphisms and fracture (Styrkarsdottir et al., 2008) as well as BMD (Styrkarsdottir et al., 2009). Moreover, the observation of significant association of several SNPs at OPG locus with BMD in several GWASs and twin studies confirmed that TNFRSF11B (OPG) is also a susceptibility gene for osteoporosis (Styrkarsdottir et al., 2008, 2009). Interleukin 6 (IL6), which acts as both pro-inflammatory and anti-inflammatory cytokine to stimulate immune response, plays a prominent role in postmenopausal bone loss (Murray et al., 1997; McLean, 2009). The RANK/RANKL/ OPG system has been shown to interact with IL6 and play important roles in the occurrence of postmenopausal osteoporosis (Kwan Tat et al., 2004). In fact, RANKL expression can be up-regulated by IL6 (Bezerra et al., 2005). The fall of estradiol levels after menopause leads to increased proinflammatory cytokines including IL6. The circulating levels of IL6 have proven to be correlated with the extent of bone loss.

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Endochondral ossification pathway Mature bone is formed through the ossification of the cartilaginous skeleton. The sequential changes in chondrocyte are regulated by systemic and secreted factors, which act through activation of chondrocyte-selective transcription factors. Systemic factors that regulate the behavior of chondrocytes in growth cartilage include growth hormone, thyroid and parathyroid hormone-related peptide, fibroblast growth factors and components of the cartilage extracellular matrix. Fig. 2 shows the interaction between different genes involved in this pathway and/or other pathways to induce bone formation. Most of the presented genes were also identified by GWASs. Many transcription factors are involved in regulation of chondrocyte gene expression upon extracellular factors stimulation. The SOX (SRY-related HMG box) gene family which encodes a group of transcription factors, plays an essential role in chondrocyte differentiation and endochondral ossification. Remarkably, defective chondrogenesis in patients presenting campomelic dysplasia is caused by heterozygous mutation in and around SOX9 gene (Foster et al. 1994). Moreover, heterozygous Sox6 mutants in mice present mild skeletal abnormalities and homozygous mutant mouse fetuses die from generalized chondrodysplasia (Smits et al. 2001).

Collagen type I, a 1 (COL1A1), which is the major protein of bone, is a heterotrimer consisting of a 1 (two chains) and a 2 (one chain) proteins which are encoded by the COL1A1 and COL1A2 genes, respectively. Although polymorphisms of COL1A1 have been studied extensively, most researches focused on one polymorphism (rs1800012) located within intron 1, affecting the binding site for the transcription factor Sp1 (specificity protein 1) (Grant et al., 1996) and showing association with BMD or osteoporotic fractures (Urano et al., 2009; Judson et al., 2011; Utennam et al., 2012), while there are some contradictory reports (Berg et al., 2000; Ashford et al., 2001). COL1A1 Sp1 polymorphism is common in Caucasians, but is rare in the African subcontinent population and seems to be virtually absent from Asian populations (Nakajima et al., 1999; Lau et al., 2004). Runt-related transcription factor 2 (RUNX2), also known as core-binding factor A1 (CBFA1), is an osteoblast-specific transcription factor. Correspondingly, homozygous Cbfa1 mutants in mice show complete absence of bone (Komori et al., 1997) and heterozygous mutants show skeletal abnormalities similar to cleidocranial dysplasia (Otto et al., 1997). Integrin-binding sialoprotein (IBSP) is expressed in all major bone cells including osteoblasts, osteocytes and osteoclasts, and its expression is up-regulated in osteoporotic bone. IBSP

Fig. 2. Interaction among key genetic components of signaling pathways involved in bone formation. The insulin-like growth factor 1 (IGF1) is an autocrine regulator which activates osteoblastic cell growth and proliferation after binding to insulin-like growth factor receptor (IGFR). TGF-b1 as well as the bone morphogenetic proteins (BMP1/6) is the members of the TGF-b superfamily of ligands, which is involved in a multitude of cellular functions including osteogenesis. Runt-related transcription factor 2 (RUNX2) participates in osteoblastic differentiation from mesenchymal progenitor cells. Type X collagen a 1 (COL10A1) is a direct transcriptional target of RUNX2. Sex-determining region Y-boxes (SOX9 and SOX5/6) cooperate in a genome-wide manner to implement chondrocyte differentiation. SOX9 also activates type II collagen a 1 (COL2A1) transcription. The discoidin domain receptor 2 (DDR2) is a receptor for type X collagen. Binding of DDR2 to collagen results in activation of different signal transducing pathways during endochondral ossification. The parathyroid hormone 1 receptor (PTH1R) functions as a receptor of parathyroid hormone (PTH) and of parathyroid hormone-like hormone (PTHLH). PTH1R is expressed on the surface of osteoblasts. When PTH1R is activated through PTH binding, osteoblasts express the receptor activator of nuclear factor k B ligand (RANKL) which binds to the receptor activator of nuclear factor k B (RANK) on osteoclasts, activating bone resorption. TGF-b activates PTHLH expression. PTHLH stimulates the proliferation of chondrocytes and suppresses their terminal differentiation. NK3 homeobox 2 (NKX3-2) acts as a transcriptional repressor of RUNX2, while MADS box transcription enhancer factor 2, polypeptide C (MEF2C) acts as a transcriptional activator of RUNX2 during chondrogenic differentiation. Postnatal bone homeostasis is regulated by Hedgehog (HH)-Patched1 (PTCH1) signaling. HH-PTCH1 signaling prevents the processing of zinc finger protein GLI3 into transcriptional repressor form.


is located near three other genes called dentin matrix acidic phosphoprotein 1 (DMP1), matrix extracellular phosphoglycoprotein (MEPE ) and secreted phosphoprotein 1 (SPP1) on chromosome 4q21-25. All these four genes (IBSP, DMP1, MEPE and SPP1) show association with BMD. The MEPE, SPP1 and IBSP are expressed in osteocytes. MEPE plays an inhibitory role in bone formation. Mepe knockout in mice causes bone mass increase and inhibition of age-related bone loss (Gowen et al., 2003), while Ibsp knockout results in high bone density.

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the molecular level, SMAD specific E3 ubiquitin-protein ligase (SMURF1) binds to RUNX2 and inhibits SMAD6 gene transcription, although SMAD1 exerts a positive effect by preventing SMURF1 interaction with RUNX2 (Wang et al. 2007). Impressively, mutations in TGF-b receptors and their cytoplasmic elements involved in transduction signals commonly lead to various cancers. Transgenic mice overexpressing Runx2 showed small stature with osteopenia (Geoffroy et al., 2002). Focal adhesion signaling pathway

MSC osteogenic differentiation Human mesenchymal stem cells (hMSC) can differentiate into osteoblasts. An important step of bone formation is osteoblastic differentiation from mesenchymal progenitor cells. During osteogenic differentiation, MSCs generate osteoprecursors, which then generate osteoprogenitors, preosteoblasts, osteoblasts and osteocytes. Many transcription factors such as CBFA1/RUNX2, msh homeobox 2 (MSX2), distal-less homeobox 5 (DLX5) and specificity protein 7 (SP7), and bone marker genes like SPP1, COLIA1, osteonectin (also known as secreted protein acidic and rich in cysteine (SPARC )) and osteocalcin (also known as bone g-carboxyglutamic acidcontaining protein (BGLAP)) are expressed during this process. Some genes involved in MSC differentiation into osteoblast such as FAM3C, SOX4/9, MEF2C and RUNX2 were discussed in the context of different pathways. Another key regulator is doublecortin domain containing 5 (DCDC5). Doublecortin domains are highly conserved and serve as platforms for protein interaction. Although expressed normally in the central nervous system and having no high expression in bone (Ralston and Uitterlinden, 2010), a large meta-analysis showed that DCDC5 gene is a possible candidate for regulation of lumbar spine BMD (Rivadeneira et al., 2009). TGF-b signaling pathway TGF-b and bone morphogenetic proteins (BMPs) belong to the TGF-b superfamily, a group of multifunctional peptides that control proliferation, differentiation and other functions in many cell types. A strong association between the immune and skeletal systems, called osteoimmunology, has been demonstrated. In this context, TGF-b1 plays a critical role in the development and maintenance of the skeletal tissue. TGF-b1 is thought to act as a coupling factor between bone resorption and bone formation and is also one of the most common studied candidate genes for osteoporosis (Bonewald and Mundy, 1990). TGF-b1 knockout mice showed reduced bone mass and bone elasticity (Geiser et al., 1998). Mutations in TGF-b1 result in Camurati-Engelmann disease which shows autosomal dominant pattern of inheritance. Affected subjects have increased BMD predominantly in the long bones of the arms and legs (Janssens et al., 2000). TGF-b receptor III (TGFbR3) appears to modulate the biological function of BMP2. The SMAD family member 6 (SMAD6) and SMAD7 genes are also implicated in the TGF-b signaling pathway. At

Focal adhesion family members are present at the junction of the cellular extracellular matrix and facilitate the link between membrane receptors and actin filaments. COL1A1 is the most studied gene of this family and its implication in osteoporosis was discussed above (Mann et al., 2001). Another key component of this pathway is the insulin-like growth factor (IGF) regulatory system which is a major growth-promoting signaling network composed of two ligands, IGF-I and IGFII, and their specific receptors. IGFs are believed to play important roles in bone acquisition and maintenance and several previous studies have examined the relationship between circulating IGFs and human bone metabolism (Johansson et al., 1992; Ljunghall et al., 1992). IGF-I is expressed at low levels prenatally in contrast to IGF-II. Also, the role of IGF-II in human bone tissue is clearly distinct from that of IGF-I. IGF-I and IGF-II are the most prevalent growth factors secreted by skeletal cells and act as autocrine regulators of osteoblastic cell function (Giustina et al., 2008). Lipid and neural pathway Observational studies suggested that the lipid levels are associated with BMD (Solomon et al., 2005; Sivas et al., 2009). Lipid oxidization inhibits bone mineralization and induces osteoblastic differentiation, while in mice, hyperlipidemia reduces bone density (Parhami, 2003). However, few genes involved in this pathway are discussed. Three common isoforms of apolipoprotein E (APOE ) in human have been identified: APOE2, APOE3 and APOE4. Several studies have focused on the association of APOE4 with BMD and fracture risk (Peter et al., 2011). APOE modulates BMD through lipoproteins and vitamin K transport. Some findings propose that APOE may contribute to the cholesterol increase in menopausal women (Hak et al. 2004). Receptor transporting protein 3 (RTP3) is a newly identified gene harboring SNPs significantly associated with femoral neck bone geometry or hip fracture (Xiong et al. 2006). Catsper channel auxiliary subunit b (CATSPERB) is another gene suspected to have a role in calcium signaling. The study of BMD in premenopausal European-American and African-American women showed the association of CATSPERB gene with femoral neck BMD in premenopausal women only (Koller et al., 2010). Ras and Rab interactor 3 (RIN3) which was found to be a genetic risk factor for late-onset Alzheimer’s disease (Karch

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and Goate, 2015) plays a role in endocytosis, vesicular trafficking and signal transduction by acting as a guanine exchange factor for small GTPases, in particular for the Rab5 family of proteins. Rab proteins play a role in regulating osteoclast function through effects on vesicular trafficking. Nucleoporin 205 kDa (NUP205) encodes a soluble component of the nuclear pore complex and functions in active transport of molecules between the nucleus and cytoplasm. NUP205 disruption was found in the patient with unclear neurodevelopmental disease (Blake et al., 2014). Both NUP205 and RIN3 were also found to be associated with Paget disease of bone which is driven by osteoclast dysfunction (Albagha et al., 2011; Vallet et al., 2015). Spalt-like transcription factor 1 (SALL1) encodes a zinc finger transcriptional repressor. A critical role in normal central nervous system development was proposed for SALL1 due to the presence of multiple congenital anomaly-mental retardation in two siblings homozygous for an autosomal recessive mutation in SALL1 (Vodopiutz et al., 2013). Dominant mutations in this gene can cause Townes-Brocks syndrome in which limb anomalies including absent bones, and supernumerary thumbs as well as mild sensorineural deafness are present (Botzenhart et al., 2005).

STARD3 N-terminal like protein (STARD3NL) gene encodes a cholesterol endosomal transporter. This gene was suspected as a candidate for BMD regulation after rs1524058 located 81 kb upstream of STARD3NL was found to be associated with spine BMD in the meta-analysis. Another polymorphism rs1721400, which is 75 kb apart from rs1524058 and is located on chromosome 7p14, was reported to be highly associated with BMD in Asian individuals (Cho et al., 2009). TBC (Tre-2/Bub2/Cdc16) domain family, member 8 (TBC1D8), also known as vascular Rab GAP/TBCcontaining protein (VRP), is thought to function as a GTPaseactivator for Rab proteins. It contains one GRAM domain and one Rab-GAP TBC domain. rs2278729, an intronic polymorphism of this gene, is significantly associated with narrow neck width in men (Hsu et al., 2010). Zinc finger and BTB domain containing 40 (ZBTB40) is expressed in bone but the function of this gene is as yet unknown. Due to the presence of a zinc finger and a BTB domain, this protein is suspected to act as a transcription factor. Its association with BMD regulation was confirmed by the GWAS and metaanalysis (Rivadeneira et al., 2009; Estrada et al., 2012) where rs7524102 and rs6696981 were found to be associated with hip and spine BMD.

OTHER SUSCEPTIBILITY GENES

CONCLUSION

Some genes involved in osteoporosis have not yet been assigned to a particular biological pathway. For example, aldehyde dehydrogenase 7 family, member A1 (ALDH7A1) is a member of acetaldehyde dehydrogenase superfamily. Acetaldehyde has been shown to inhibit osteoblast proliferation and decrease bone formation (Giuliani et al., 1999). ALDH2 is another member of this family which has also been found to show the significant association with osteoporosis. Corticotropin releasing hormone receptor 1 (CRHR1) is also the candidate gene for BMD regulation. The SNP rs9303521 located in CRHR1 gene is significantly associated with spine BMD (Rivadeneira et al., 2009). The FLJ42280 gene encodes a hypothetical protein of unknown function and several SNPs within or near this gene are significantly associated with both spine and hip BMD (Batra et al., 2003). Polypeptide N-acetylgalactosaminyltransferase 3 (GALNT3) is involved in glycosylation of serine and threonine. Mutations of GALNT3 gene cause familial tumoral calcinosis with deposition of calcium phosphate crystals in extra-skeletal tissues and hyperostosis-hyperphosphatemia syndrome (Frishberg et al., 2005). The MAP/microtubule affinity-regulating kinase 3 is an enzyme encoded by human MARK3 gene. MARK3 is a member of the adenosine monophosphate activated protein kinase (AMPK) superfamily and might be involved in cell cycle regulation. MARK3 was first identified as a locus associated with osteoporosis at a genome-wide significant level (Rivadeneira et al., 2009). The effect of MARK3 rs11623869 on BMD, especially in the presence of high serum levels of alkaline phosphatase, was further demonstrated in a Chinese population cohort (Xiao et al., 2013).

Considering that osteoporosis is becoming clinical and public health problem, many researches have been performed over the past three decades to understand the genetic contribution to osteoporosis and related phenotypes. Many results from candidate gene association studies are contradictory due to different biases such as population stratification, genotyping errors, relatedness, imputations, modeling haplotype variation, dealing with HardyeWeinberg (dis)equilibrium, selection of participants, effects of treatment, lack of up-to-date statistical methods and low probability of the involvement of the studied genes in the overall risk of osteoporosis, leading to the nonreplicability of the candidate associations. In this regard, the validation of associations of multiple candidate genes among the same or different ethnic groups and age category group is dearly needed. Moreover, genes such as FONG, KIT, VDR and many others (Table S1, CGAS as the genetic mapping method) are not replicated in different populations, and therefore one might suspect that those are false-positive (or populationspecific) signals. Hence, a meta-analysis of studies of the same polymorphisms and the same phenotypes should be performed for a better determination of the impact of a particular locus or polymorphism on disease occurrence. In addition, this controversy might also be due to specific geneegene or geneeenvironment associations or falsenegative results caused by stringent significant cutoffs in GWAS. Another limitation of most GWAS studies is the wide range of subjects’ age and hence the mixture of their physiological conditions such as menopausal status. Thus, focusing on narrower age variation, by studying different age groups specially through cohorts of children, teenagers or premenopausal women, can lead to more precise indications


concerning genetic influence on skeletal phenotypes. Furthermore, a particular gene might slightly contribute to the disease and consequently its polymorphisms might have only a weak predictive value. But as many gene products interact together with each other, a systematic investigation of genes involved in a candidate pathway might be more informative for disease risk assessment. It is also valuable to investigate haplotypes rather than isolated SNPs. In fact, one SNP which is present in different haplotypes may not show a particular association with the disease, but a particular haplotype containing that SNP might have a stronger effect on disease occurrence. Progresses in whole-genome/whole-exome sequencing may accelerate to test associations of a higher number of sequence variants throughout the genome with osteoporosis. Another field, which is yet poorly investigated and should provide better understanding of genetic signals and more comprehensible views of pathways involved in this agerelated disease susceptibility, is gene expression profiling as well as epigenetic and proteomic studies in tissues from both normal and affected individuals/animal models. Finally, as many complex traits are multifactorial, the combination of genetic susceptibility and environmental factors (e.g., age, obesity, smoking, dietary calcium or vitamin D) is also likely to be important and vital in determining variable phenotypes related to osteoporosis. Life style modifications might also lead to the occurrence of this disorder in younger subjects in the future. Thus, controlling environmental factors could be important for preventing the development of osteoporosis in subjects with high genetic risk. Taken together, it is of most importance to intensify the investigations elucidating the physiopathology of this disorder and the most relevant pathways and genes involved in bone metabolism and corresponding haplotypes. Moreover, genes regulating BMD might be valuable targets for designing new efficient drugs treating bone diseases. ACKNOWLEDGMENTS We would like to thank Ali Akbar Samadani (Cellular and Molecular Biology Research Center, Babol University of Medical Sciences, Babol, Iran) for his help in English editing of the manuscript.

SUPPLEMENTARY DATA Table S1. Different genes and loci associated with osteoporosis. Table S2. Biological effects and important polymorphisms of genes involved in signaling pathways leading to skeleton and bone development. Supplementary data related to this article can be found at http://dx.doi.org/10.1016/j.jgg.2015.12.001. REFERENCES Albagha, O.M., Wani, S.E., Visconti, M.R., Alonso, N., Goodman, K., Brandi, M.L., Cundy, T., Chung, P.Y., Dargie, R., Devogelaer, J.P.,

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