Genetic studies of osteoporosis: A rethink required

It has been 10 years since the seminal paper by Morrison and colleagues reporting the association of alleles of the vitamin D receptor and bone density [1], a paper which arguably kick-started the study of osteoporosis genetics. Since that report there have been literally thousands of osteoporosis genetic studies published, and large numbers of genes have been reported to be associated with the condition [2]. Although some of these reported associations are undoubtedly true, this snow-storm of papers and abstracts has clouded the field to such a great extent that it is very difficult to be certain of the veracity of most genetic associations reported hereto. The field needs to take stock and reconsider the best way forward, taking into account the biology of skeletal development and technological and statistical advances in human genetics, before more effort and money is wasted on continuing a process in which the primary achievement could be said to be a massive paper mountain. I propose in this review that the primary reasons for the paucity of success in osteoporosis genetics has been: •the absence of a major gene effect on bone mineral density (BMD), the most commonly studied bone phenotype; •failure to consider issues such as genetic heterogeneity, gene–environment interaction, and gene–gene interaction; •small sample sizes and over-optimistic data interpretation; and •incomplete assessment of the genetic variation in candidate genes studied.

Genetic susceptibility to ankylosing spondylitis

Ankylosing spondylitis is a highly heritable, common rheumatic condition, primarily affecting the axial skeleton. The association with HLA-B27 has been demonstrated worldwide, and evidence for a role of HLA-B27 in disease comes from linkage and association studies in humans, and transgenic animal models. However, twin studies indicate that HLA-B27 contributes only 16% of the total genetic risk for disease. Furthermore, there is compelling evidence that non-B27 genes, both within and outwith the major histocompatability complex, are involved in disease aetiology. In this post-genomic era we have the tools to help elicit the genetic basis of disease. This review describes methods for genetic investigation of ankylosing spondylitis, and summarises the status of current research in this exciting area.

Genetic aspects of susceptibility, severity, and clinical expression in ankylosing spondylitis

While twin studies have previously demonstrated high heritability of susceptibility to ankylosing spondylitis (AS), it is only recently that the involvement of genetic factors in determining the severity of the disease has been demonstrated. The genes involved in determining the rate of ankylosis in AS are likely to be different from those involved in the underlying immunologic events, and represent important potential targets for treatment of AS. This article will describe the progress that has been made in the genetic epidemiology of AS, and in identifying the genes involved.

Genetic studies of chondrocalcinosis

Purpose of review Our understanding of the causation of the chondrocalcinosis and other disorders characterized by ectopic mineralization is rapidly increasing, and genetic studies have contributed substantially to recent major advances in the field. This review will discuss what is known about the genetics of chondrocalcinosis and what we have learned from genetic studies to date. Recent findings: Chondrocalcinosis is one of a family of conditions associated with ectopic mineralization. This family also includes disorders of mineralization of bone and spinal and other ligaments, and vascular calcification. There has been increasing evidence of the key role of transport and metabolism of inorganic pyrophosphate (PPi) in control of mineralization, and as the likely explanation for the association of a variety of genetic variants with chondrocalcinosis and ectopic mineralization elsewhere. This may be an overly simplistic view of this family of conditions, with recent evidence suggesting that, for example, ANKH variants may not all predispose to chondrocalcinosis by effects on PPi transport, but may also influence chondrocyte maturation. Summary: Understanding the control of the process of mineralization and its tissue specificity are important steps in the search for rational therapies for these conditions.

Genetic determinants of heel bone properties: Genome-wide association meta-analysis and replication in the GEFOS/GENOMOS consortium

Quantitative ultrasound of the heel captures heel bone properties that independently predict fracture risk and, with bone mineral density (BMD) assessed by X-ray (DXA), may be convenient alternatives for evaluating osteoporosis and fracture risk. We performed a meta-analysis of genome-wide association (GWA) studies to assess the genetic determinants of heel broadband ultrasound attenuation (BUA; n 5 14 260), velocity of sound (VOS; n 5 15 514) and BMD (n 5 4566) in 13 discovery cohorts. Independent replication involved seven cohorts with GWA data (in silico n 5 11 452) and new genotyping in 15 cohorts (de novo n 5 24 902). In combined random effects, meta-analysis of the discovery and replication cohorts, nine single nucleotide polymorphisms (SNPs) had genome-wide significant (P < 5 3 108) associations with heel bone properties. Alongside SNPs within or near previously identified osteoporosis susceptibility genes including ESR1 (6q25.1: rs4869739, rs3020331, rs2982552), SPTBN1 (2p16.2: rs11898505), RSPO3 (6q22.33: rs7741021), WNT16 (7q31.31: rs2908007), DKK1 (10q21.1: rs7902708) and GPATCH1 (19q13.11: rs10416265), we identified a new locus on chromosome 11q14.2 (rs597319 close to TMEM135, a gene recently linked to osteoblastogenesis and longevity) significantly associated with both BUA and VOS (P < 8.23 3 1014). In meta-analyses involving 25 cohorts with up to 14 985 fracture cases, six of 10 SNPs associated with heel bone properties at P < 5 3 106 also had the expected direction of association with any fracture (P < 0.05), including threeSNPswithP < 0.005: 6q22.33 (rs7741021), 7q31.31 (rs2908007) and 10q21.1 (rs7902708). In conclusion, thisGWAstudy reveals the effect of several genescommon to central DXA-derivedBMDand heel ultrasound/DXAmeasures and points to anewgenetic locus with potential implications for better understanding of osteoporosis pathophysiology.

Genetic determinants of bone density and fracture risk: State of the art and future directions

Context: Osteoporosis is a common, highly heritable condition that causes substantial morbidity and mortality, the etiopathogenesis of which is poorly understood. Genetic studies are making increasingly rapid progress in identifying the genes involved. Evidence Acquisition and Synthesis: In this review, we will summarize the current understanding of the genetics of osteoporosis based on publications from PubMed from the year 1987 onward. Conclusions: Most genes involved in osteoporosis identified to date encode components of known pathways involved in bone synthesis or resorption, but as the field progresses, new pathways are being identified. Only a small proportion of the total genetic variation involved in osteoporosis has been identified, and new approaches will be required to identify most of the remaining genes.

Breakthroughs in genetic studies of ankylosing spondylitis

Ankylosing spondylitis (AS), the prototypic seronegative arthropathy, is known to be highly heritable, with >90% of the risk of developing the disease determined genetically. As with most common heritable diseases, progress in identifying the genes involved using family-based or candidate gene approaches has been slow. The recent development of the genome-wide association study approach has revolutionized genetic studies of such diseases. Early studies in ankylosing spondylitis have produced two major breakthroughs in the identification of genes contributing roughly one third of the population attributable risk of the disease, and pointing directly to a potential therapy. These exciting findings highlight the potential of future more comprehensive genetic studies of determinants of disease risk and clinical manifestations, and are the biggest advance in our understanding of the causation of the disease since the discovery of the association with HLA-B27.

The v-MFG test: Investigating maternal, offspring and maternal-fetal genetic incompatibility effects on disease and viability

The MFG test is a family-based association test that detects genetic effects contributing to disease in offspring, including offspring allelic effects, maternal allelic effects and MFG incompatibility effects. Like many other family-based association tests, it assumes that the offspring survival and the offspring-parent genotypes are conditionally independent provided the offspring is affected. However, when the putative disease-increasing locus can affect another competing phenotype, for example, offspring viability, the conditional independence assumption fails and these tests could lead to incorrect conclusions regarding the role of the gene in disease. We propose the v-MFG test to adjust for the genetic effects on one phenotype, e.g., viability, when testing the effects of that locus on another phenotype, e.g., disease. Using genotype data from nuclear families containing parents and at least one affected offspring, the v-MFG test models the distribution of family genotypes conditional on offspring phenotypes. It simultaneously estimates genetic effects on two phenotypes, viability and disease. Simulations show that the v-MFG test produces accurate genetic effect estimates on disease as well as on viability under several different scenarios. It generates accurate type-I error rates and provides adequate power with moderate sample sizes to detect genetic effects on disease risk when viability is reduced. We demonstrate the v-MFG test with HLA-DRB1 data from study participants with rheumatoid arthritis (RA) and their parents, we show that the v-MFG test successfully detects an MFG incompatibility effect on RA while simultaneously adjusting for a possible viability loss.

Common genetic influences underlie comorbidity of migraine and endometriosis

We examined the co-occurrence of migraine and endometriosis within the largest known collection of families containing multiple women with surgically confirmed endometriosis and in an independent sample of 815 monozygotic and 457 dizygotic female twin pairs. Within the endometriosis families, a significantly increased risk of migrainous headache was observed in women with endometriosis compared to women without endometriosis (odds ratio [OR] 1.57, 95% confidence interval [CI]: 1.12-2.21, P=0.009). Bivariate heritability analyses indicated no evidence for common environmental factors influencing either migraine or endometriosis but significant genetic components for both traits, with heritability estimates of 69 and 49%, respectively. Importantly, a significant additive genetic correlation (r(G) = 0.27, 95% CI: 0.06-0.47) and bivariate heritability (h(2)=0.17, 95% CI: 0.08-0.27) was observed between migraine and endometriosis. Controlling for the personality trait neuroticism made little impact on this association. These results confirm the previously reported comorbidity between migraine and endometriosis and indicate common genetic influences completely explain their co-occurrence within individuals. Given pharmacological treatments for endometriosis typically target hormonal pathways and a number of findings provide support for a relationship between hormonal variations and migraine, hormone-related genes and pathways are highly plausible candidates for both migraine and endometriosis. Therefore, taking into account the status of both migraine and endometriosis may provide a novel opportunity to identify the genes underlying them. Finally, we propose that the analysis of such genetically correlated comorbid traits can increase power to detect genetic risk loci through the use of more specific, homogenous and heritable phenotypes.

Latent class and genetic analysis does not support migraine with aura and migraine without aura as separate entities

Latent class and genetic analyses were used to identify subgroups of migraine sufferers in a community sample of 6,265 Australian twins (55% female) aged 25-36 who had completed an interview based on International Headache Society (IHS) criteria. Consistent with prevalence rates from other population-based studies, 703 (20%) female and 250 (9%) male twins satisfied the IHS criteria for migraine without aura (MO), and of these, 432 (13%) female and 166 (6%) male twins satisfied the criteria for migraine with aura (MA) as indicated by visual symptoms. Latent class analysis (LCA) of IHS symptoms identified three major symptomatic classes, representing 1) a mild form of recurrent nonmigrainous headache, 2) a moderately severe form of migraine, typically without visual aura symptoms (although 40% of individuals in this class were positive for aura), and 3) a severe form of migraine typically with visual aura symptoms (although 24% of individuals were negative for aura). Using the LCA classification, many more individuals were considered affected to some degree than when using IHS criteria (35% vs. 13%). Furthermore, genetic model fitting indicated a greater genetic contribution to migraine using the LCA classification (heritability, h(2)=0.40; 95% CI, 0.29-0.46) compared with the IHS classification (h(2)=0.36; 95% CI, 0.22-0.42). Exploratory latent class modeling, fitting up to 10 classes, did not identify classes corresponding to either the IHS MO or MA classification. Our data indicate the existence of a continuum of severity, with MA more severe but not etiologically distinct from MO. In searching for predisposing genes, we should therefore expect to find some genes that may underlie all major recurrent headache subtypes, with modifying genetic or environmental factors that may lead to differential expression of the liability for migraine.

Latent variable models in statistical genetics

Understanding the complexities that are involved in the genetics of multifactorial diseases is still a monumental task. In addition to environmental factors that can influence the risk of disease, there is also a number of other complicating factors. Genetic variants associated with age of disease onset may be different from those variants associated with overall risk of disease, and variants may be located in positions that are not consistent with the traditional protein coding genetic paradigm. Latent Variable Models are well suited for the analysis of genetic data. A latent variable is one that we do not directly observe, but which is believed to exist or is included for computational or analytic convenience in a model. This thesis presents a mixture of methodological developments utilising latent variables, and results from case studies in genetic epidemiology and comparative genomics. Epidemiological studies have identified a number of environmental risk factors for appendicitis, but the disease aetiology of this oft thought useless vestige remains largely a mystery. The effects of smoking on other gastrointestinal disorders are well documented, and in light of this, the thesis investigates the association between smoking and appendicitis through the use of latent variables. By utilising data from a large Australian twin study questionnaire as both cohort and case-control, evidence is found for the association between tobacco smoking and appendicitis. Twin and family studies have also found evidence for the role of heredity in the risk of appendicitis. Results from previous studies are extended here to estimate the heritability of age-at-onset and account for the eect of smoking. This thesis presents a novel approach for performing a genome-wide variance components linkage analysis on transformed residuals from a Cox regression. This method finds evidence for a dierent subset of genes responsible for variation in age at onset than those associated with overall risk of appendicitis. Motivated by increasing evidence of functional activity in regions of the genome once thought of as evolutionary graveyards, this thesis develops a generalisation to the Bayesian multiple changepoint model on aligned DNA sequences for more than two species. This sensitive technique is applied to evaluating the distributions of evolutionary rates, with the finding that they are much more complex than previously apparent. We show strong evidence for at least 9 well-resolved evolutionary rate classes in an alignment of four Drosophila species and at least 7 classes in an alignment of four mammals, including human. A pattern of enrichment and depletion of genic regions in the profiled segments suggests they are functionally significant, and most likely consist of various functional classes. Furthermore, a method of incorporating alignment characteristics representative of function such as GC content and type of mutation into the segmentation model is developed within this thesis. Evidence of fine-structured segmental variation is presented.

Candidate gene association studies : a comprehensive guide to useful in silico tools

The candidate gene approach has been a pioneer in the field of genetic epidemiology, identifying risk alleles and their association with clinical traits. With the advent of rapidly changing technology, there has been an explosion of in silico tools available to researchers, giving them fast, efficient resources and reliable strategies important to find casual gene variants for candidate or genome wide association studies (GWAS). In this review, following a description of candidate gene prioritisation, we summarise the approaches to single nucleotide polymorphism (SNP) prioritisation and discuss the tools available to assess functional relevance of the risk variant with consideration to its genomic location. The strategy and the tools discussed are applicable to any study investigating genetic risk factors associated with a particular disease. Some of the tools are also applicable for the functional validation of variants relevant to the era of GWAS and next generation sequencing (NGS).

Rapid analysis of GSTM1, GSTT1 and GSTP1 polymorphisms using real-time polymerase chain reaction

Polymorphisms of glutathione transferases (GST) are important genetic determinants of susceptibility to environmental carcinogens (Rebbeck, 1997). The GSTs are a multigene family of dimeric enzymes involved in detoxification, and, in a few cases, the bioactivation of a variety of xenobiotics (Hayes et al., 1995). The cytosolic GST enzyme family consists of four major classes of enzymes, referred to as alpha, mu, pi and theta. Several members of this family (for example, GSTM1, GSTT1 and GSTP1) are polymorphic in human populations (Wormhoudt et al., 1999). Molecular epidemiology studies have examined the role of GST polymorphisms as susceptibility factors for environmentally and/or occupationally induced cancers (Wormhoudt et al., 1999). In particular, case-control studies showed a relationship between the GSTM1 null genotype and the development of cancer in association with smoking habits, which has been shown for cancers of the respiratory and gastrointestinal tracts as well as other cancer types (Miller et al., 1997). Only a few molecular epidemiological studies addressed the role of GSTT1 and GSTP1 polymorphisms in cancer susceptibility. Since GSTP1 is a key player in biotransformation/bioactivation of benzo(a)pyrene, GSTP1 may be even more important than GSTM1 in the prevention of tobacco-induced cancers (Harries et al., 1997; Harris et al., 1998). To date, this relationship has not been sufficiently addressed in humans. Comprehensive molecular epidemiological studies may add to the current knowledge of the role of GST polymorphisms in cancer susceptibility and extent of the knowledge gained from approaches that used phenotyping, such as GSTM1 activity as it relates to trans-stilbene oxide, or polymerase chain reaction (PCR) based genotyping of polymorphic isoenzymes (Bell et al., 1993; Pemble et al., 1994; Harries et al., 1997).