Risk Assessment for Hip and Knee Osteoarthritis Using Polygenic Risk Scores

Sedaghati-Khayat, Bahareh; Boer, Cindy G.; Runhaar, Jos; Bierma-Zeinstra, Sita M A; Broer, Linda; Ikram, M. Arfan; Zeggini, Eleftheria; Uitterlinden, André G.; Rooij, Jeroen G.J. van; Meurs, Joyce B. J. van

doi:10.1002/art.42246

Cited by 16 publications

(10 citation statements)

References 37 publications

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“…This is the first study to identify the presence of mQTLs in human fetal cartilage and limb tissues, and our report demonstrates that the functional genetic risk of OA can be laid down during human skeletogenesis. Strides are being made within the field, with the first recent reports of polygenic risk scores (PRS) for the disease ( 52 , 53 ), yet the clinical utility of such systems is still lacking ( 54 ). We would encourage the integration of epigenetic data at the loci, along with clinical and biochemical parameters to further advance these tools for the patient benefit.…”

Section: Discussionmentioning

confidence: 99%

Genetic risk of osteoarthritis operates during human skeletogenesis

Rice

Brumwell

Falk

et al. 2022

Human Molecular Genetics

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Osteoarthritis (OA) is a polygenic disease of older people resulting in the breakdown of cartilage within articular joints. Although a leading cause of disability, there are no disease-modifying therapies. Evidence is emerging to support the origins of OA in skeletogenesis. Whilst methylation QTLs (mQTLs) co-localizing with OA GWAS signals have been identified in aged human cartilage and used to identify effector genes and variants, such analyses have never been conducted during human development. Here, for the first time, we have investigated the developmental origins of OA genetic risk at seven well-characterized OA risk loci, comprising 39 OA-mQTL CpGs, in human foetal limb (FL) and cartilage (FC) tissues using a range of molecular genetic techniques. We compared our results to aged cartilage samples (AC) and identified significant OA-mQTLs at 14 CpGs and 29 CpGs in FL and FC tissues, respectively. Differential methylation was observed at 26 sites between foetal and aged cartilage, with the majority becoming actively hypermethylated in old age. Notably, 6/9 OA effector genes showed allelic expression imbalances during foetal development. Finally, we conducted ATAC-sequencing in cartilage from the developing and aged hip and knee to identify accessible chromatin regions, and found enrichment for transcription factor binding motifs including SOX9 and FOS/JUN. For the first time, we have demonstrated the activity of OA-mQTLs and expression imbalance of OA effector genes during skeletogenesis. We show striking differences in the spatiotemporal function of these loci, contributing to our understanding of OA aetiology, with implications for the timing and strategy of pharmacological interventions.

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Section: Discussionmentioning

confidence: 99%

Genetic risk of osteoarthritis operates during human skeletogenesis

Rice

Brumwell

Falk

et al. 2022

Human Molecular Genetics

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“…That said, it is known that variations in hip shape exist between European and East Asian populations (17). Future work, harnessing the resources of these large population studies with genetic data, could explore the incorporation of polygenic risk scores to assess whether their inclusion can enhance the performance of disease prediction models (39). In addition, if more cohorts become available then superior trans-ancestry GWAS techniques become possible such as meta-regression of multi-ancestry genetic association (MR-MEGA) (40).…”

Section: Discussionmentioning

confidence: 99%

Hip shape shows a causal effect on hip fracture but not hip osteoarthritis: findings from a GWAS meta-analysis and causal analyses

Faber,

Frysz,

Zheng

et al. 2024

Preprint

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Objectives Hip shape is thought to be an important causal risk factor for hip osteoarthritis and fracture. We aimed to identify genetic determinants of hip shape and use these to assess causal relationships with hip osteoarthritis. Methods Statistical hip shape modelling was used to derive 10 hip shape modes (HSMs) from DXA images in UK Biobank and Shanghai Changfeng cohorts (ntotal=43,485). Genome-wide association study meta-analyses were conducted for each HSM. Two-sample Mendelian randomisation (MR) was used to estimate causal effects between HSM and hip osteoarthritis using hip fracture as a positive control. Results Analysis of the first 10 HSMs identified 290 independent association signals (P<5×10-8). Hip shape SNPs were also associated (P<1.7×10-4) with hip osteoarthritis (n=29) and hip fracture (n=4). Fine mapping implicated SMAD3 and PLEC as candidate genes that may be involved in the development of hip shape and hip osteoarthritis. MR analyses suggested there was no causal effect between any HSM and hip osteoarthritis, however there was evidence that HSM2 (higher neck-shaft angle) and HSM4 (wider femoral neck) have a causal effect on hip fracture (ORIVW1.27 [95% CI 1.12-1.44], P=1.79×10-4and ORIVW0.74 [0.65-0.84], P=7.60×10-6respectively) Conclusions We report the largest hip shape GWAS meta-analysis that identifies hundreds of novel loci, some of which are also associated with hip osteoarthritis and hip fracture. MR analyses suggest hip shape may not cause hip osteoarthritis but is implicated in hip fractures. Consequently, interventions aimed at modifying hip shape in older adults to prevent hip osteoarthritis may prove ineffective.

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“…However, some of these data sets might be used much earlier as prognostic tools, to determine patient risk and to direct prevention. For example, two recent studies used the loci identified in GWAS studies to determine the 'Polygenic Risk Score' (PRS) for OA patients, with encouraging results ( [30,31], discussed in [32]). Steinbeck et al [33] provide another example of using multiomics approaches to stratify patients and potentially direct more personalized treatments in the future.…”

Section: Outlook and Conclusionmentioning

confidence: 99%

The impact of omics research on our understanding of osteoarthritis and future treatments

Beier¹

2022

Current Opinion in Rheumatology

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Purpose of reviewTo review recent studies using Omics approaches (genomics, proteomics, metabolomics, single cell analyses) in patient populations and animal models of osteoarthritis (OA), with the goal of identifying disease-modifying mechanisms that could serve as therapeutic and diagnostic targets. Recent findingsThe number of genes, pathways and molecules with potential roles in OA pathogenesis has grown substantially over the last 18 months. Studies have expanded from their traditional focus on cartilage and gene expression to other joint tissues, proteins and metabolites. Single cell approaches provide unprecedented resolution and exciting insights into the heterogeneity of cellular activities in OA. Functional validation and investigation of underlying mechanisms in animal models of OA, in particular genetically engineered mice, link Omics findings to pathophysiology and potential therapeutic applications.

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Risk Assessment for Hip and Knee Osteoarthritis Using Polygenic Risk Scores

Cited by 16 publications

References 37 publications

Genetic risk of osteoarthritis operates during human skeletogenesis

Genetic risk of osteoarthritis operates during human skeletogenesis

Hip shape shows a causal effect on hip fracture but not hip osteoarthritis: findings from a GWAS meta-analysis and causal analyses

The impact of omics research on our understanding of osteoarthritis and future treatments

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