Similar results were found for the potential causal relationship between hand grip strength and fracture risk, but could not be replicated with a multiple testing significance threshold in the study by Trajanoska et al. A minimum sample-size threshold needs to be reached in GWAS, from where the number of discovered loci increases along with growing sample sizes as study power improves Mega-sized biobanks, such as 23andMe and UK Biobank, including hundreds of thousands of participants with GWAS are increasingly becoming available 64 , A drawback from such Mega-GWAS is that phenotype data tends to be of variable quality and less accurate.
However, there is a trade-off where the huge numbers may boost study power tremendously and overcome measurement error to a certain extent. In addition, the success rate of unraveling underlying genetic mechanisms may be influenced by the complexity of the genetic architecture of the trait of interest, including imperfect penetrance, allelic heterogeneity, and gene-environment and epigenetic effects 42 , The discovery of rare variants is hindered by the large sample sizes required to attain sufficient study power, where research consortia and Mega-GWAS with even larger sample sizes prove their worth through ever-increasing sized meta-analyses.
Larger imputation reference panels and sequencing-based genotyping are becoming progressively available, facilitating more accurate examination of lower-frequency SNPs and other type of genetic variants such as indels and larger deletions Furthermore, it has been proposed that the missing heritability for human height and body mass index is likely to be small after estimating the genetic variance from all imputed variants 67 ; this will likely be the case for a quantitative trait such as BMD as well.
Until now, rare variant association studies have found variants with larger effects where each explains only a tiny proportion of the phenotypic variance, because the heritability explained is dependent on the effect size and allele frequency Therefore, arguments can be found to study both common and rare variants in the occurrence of common diseases 68 , as also confirmed by our experiences in the bone field.
More detailed phenotyping is believed to be of value for scrutinizing skeletal-site specific effects for fracture risk, for example cortical vs. This thinking comes from the observations that heritability of BMD varies across skeletal sites due to a mixture of shared and specific genetic and environmental influences as quantified by the genetic correlations 69 , which supports the findings that some genetic loci display skeletal-site specific effects Furthermore, it has been hypothesized that using stricter phenotype definitions and taking into account fracture mechanisms may increase study power.
Yet, a major drawback is the decreasing sample size. Results for radiographic 59 and clinical vertebral fractures 51 have been published, as described above, efforts for hip and wrist fractures are underway, but struggle with attaining sufficient study samples to enable discoveries. Therefore, the all-type of fracture GWAS approach seems the starting point to attain maximum sample size for power to perform the first screening for genetic variants that contribute to osteoporotic fracture risk in general.
Other even more specific subjects of clinical studies could be atypical femoral fractures or fracture healing, which could yield insight into differences in natural healing mechanisms and efficacy of medical treatment between patients. The tough start of the fracture GWAS may be rooted in the complex phenotype definition and heterogeneity of the trait and its underlying genetics. A better understanding of the genetic architecture seems necessary.
More clarity is needed which fracture phenotypes should be studied together because they have a joint genetic etiology, and which do not and thus should be analyzed separately; for example vertebral vs. Then robust selection criteria should be defined for an optimal fracture phenotype definition of interest. Research ideas include data enrichment for cases that have a known family history for osteoporosis, having fractured at relatively young age or having sustained multiple fractures.
This because the heritability of osteoporotic fractures at younger age is higher 4. Nonetheless, the osteoporotic fracture incidence at young age is lower, which may limit study sample sizes. Theoretically, it has been speculated that perhaps further exclusion criteria need to be established for cases that are thought to be caused by arguably non-genetic mechanisms e.
However, until now in practice, bigger seems better to efficiently identify genes; then one should take these discoveries and bring them in a candidate-gene context and look across rich sets of detailed phenotypes that help understand the underlying biology. Combination into multivariate GWAS of multiple disease-related traits could further exploit the detection of pleiotropic effects 70 and novel statistical methods may be able to better utilize the richer phenotype information that will become available 71 , Additionally, richer phenotyping of endophenotypes may yield more insight.
One of the underlying reasons is that it generates two-dimensional scans and does not sufficiently appreciate bone microarchitecture, an important determinant of bone strength Areal BMD does appreciate bone size and in part the internal architecture; the trabecular bone score TBS which can also be derived from DXA data will be worth further investigations Further improvements require more advanced imaging than dual energy X-ray absorptiometry, principally by direct three-dimensional radiological imaging investigations, such as computed tomography or magnetic resonance imaging, to directly visualize microstructure, differentiate cortical and trabecular bone, and model bone strength biomechanically Novel imaging techniques that can quantify this bone composition are coming up 78 , and genetic studies into these endophenotypes are yet to come.
Finally, it could be argued that bone geometry and its genetics should be studied. Intriguingly, taller persons are at increased risk of fractures in spite of having larger bones with more mass 79 , This may be caused by a different distribution of bone mass by periosteal apposition Further, loci implicated in the GWAS of human stature are enriched for genes important for skeletal growth And more specifically, a GWAS meta-analysis for hip shape was published very recently and found 17q However, some of the measurement methods with respect to both genotyping and phenotyping currently available are simply too expensive or invasive to apply on a population level at present.
Yet, current limits are being challenged, with the very first successful large-scale applications of whole-genome sequencing and deep imputation using sequencing-based reference panels in the osteoporosis research field Further studies of copy number and structural variations should be performed. However, the genome may be too distant in the cascade from the disease of interest to detect clinically relevant patterns, therefore, screening the transcriptome, epigenome, metabolome, proteome and even microbiome at perhaps multiple time points may prove necessary.
This may be applied to clinical fracture patient studies as well as population-based cohorts, where subgroups could be studied including for example individuals with multiple fractures, persons with fractures at young age, and elderly individuals free of fractures. The osteoporosis field has started to explore epigenetic regulation for instance: microRNA 84 , 85 , long non-coding RNA 86 , gene expression 87 , and DNA methylation Oftentimes the function of genes contained in the associated loci are not completely known. Functional follow-up studies are needed, yet, the development of animal knock-out-models may take years.
Establishment of multi-disciplinary research consortia worldwide may be beneficial to efficiently take GWAS discoveries to functional follow-up in a harmonized research pipeline. Also, publicly available databases are being launched to enhance interpretation of genomic sequence information, promoting mutual data sharing between expert consortia, professional organizations, health care providers, and patients.
The Encyclopedia of DNA Elements ENCODE project, aiming to identify all functional elements in the human genome, has drastically enriched our comprehension about regions outside of the exome and showed that many GWAS SNPs overlap transcription-factor-occupied regions or DNase I hypersensitive sites and are particularly enriched in the segmentation classes associated with enhancers and transcription start sites A striking finding is that obesity-associated noncoding sequences within the FTO locus are associated with expression of the homeobox gene IRX3 at megabase distances, but not with expression of FTO itself; 91 this association seems to be driven by a topologically associated domain TAD structure encompassing the FTO and IRXB genes cluster Such genomic explorations remain to be performed for osteoporosis-related traits.
So far, therapies used to increase bone strength in individuals with osteoporosis are mainly based on antiresorptives Bisphosphonates are the most widely used first-line because of their effectiveness, reasonable safety, and a low cost price However, in practice, no single antiresorptive therapy is currently appropriate for all patients, as a subgroup of patients on anti-fracture medication responds suboptimally, e. To our knowledge no large-scale pharmacogenetic GWAS studies examining these phenomena in osteoporosis have been published to date, though initial case studies on the genetics of AFF and an accompanying systematic review have been published In the future, results from pharmacogenomic studies may aid in assigning the most effective therapy to specific patient groups and it has been hypothesized that genetic biomarkers can be identified to pinpoint those patients most vulnerable to side-effects of certain agents.
Until now in genetic osteoporosis research, solely candidate gene studies have been performed investigating genetically-based variation in treatment response to raloxifene, teriparatide, and bisphosphonates One of the reasons for this is that the coverage of pharmacogenomics variants was limited on GWAS genotyping platforms , , but this is improving with novel microarrays becoming available.
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GWAS is the study design necessary to further investigate the complex phenotypic and genetic architecture of osteoporotic fracture risk. Although fractures can be considered a complex trait, so far, the majority of susceptibility loci for fractures are also associated with bone mineral density. Hopefully, novel discoveries in the genetics of fracture risk will increasingly be translated clinical practice, with genotyping increasingly being successfully applied providing access to previously unknown information that may change the diagnostics and treatment of patients with bone diseases including osteoporosis with increased fracture risk in the future.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer RP declared a past co-authorship with the authors to the handling editor. Fall risk: the clinical relevance of falls and how to integrate fall risk with fracture risk. Best Pract Res Clin Rheumatol. Kanis JA.
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