Using multivariable Mendelian randomization to estimate the causal effect of bone mineral density on osteoarthritis risk, independently of body mass index

Causal effects of inflammatory bowel disease on risk of type 2 diabetes: a two-sample multivariable Mendelian randomization study

AIM

This study aimed to explore the causal association between inflammatory bowel disease (IBD) and the risk of type 2 diabetes (T2D) based on a two-sample Mendelian randomization (MR) study.

METHODS

Summary single nucleotide polymorphism (SNP)-phenotype association data were obtained from published two genome-wide association studies (GWAS) including SNPs related to IBD, UC, or CD in European participants (n = 71,997) and East Asian participants (n = 16,805). Two GWAS including SNPs associated with T2D included 655,666 Europeans and 433,540 East Asians. A series of screening processes were performed to select qualified instrumental SNPs strongly related to exposure. We applied the inverse variance weighted (IVW), the MR-Egger regression, and the weighted median to estimate the causal effects of IBD, ulcerative colitis (UC) or Crohn' disease (CD) on T2D. Cochran's Q test was conducted to evaluate the statistical heterogeneity between SNPs in the IVW method. The leave-one-out analysis was employed to assess whether the results were caused by any single SNP associated with IBD, UC, or CD. Odds ratio (OR) and 95% confidence interval (CI) were calculated.

RESULTS

The IVW results demonstrated that IBD could increase the risk of T2D in the European population (OR = 1.0230, 95%CI: 1.0073-1.0390). UC was positively associated with the risk of T2D according to the weighted median (OR = 1.0274, 95%CI: 1.0009-1.0546) and IVW (OR = 1.0244, 95%CI: 1.0071-1.0421) results in the European population. The IVW results indicated that the CD was positively associated with the risk of T2D in the European population (OR = 1.0187, 95%CI: 1.0045-1.0330). In the East Asian population, there are no associations between the IBD, UC, or CD and the risk of T2D (all P > 0.05). MVMR results revealed that the causal effect UC on T2D was still statistically significant after including body mass index (BMI) or low-density lipoprotein (LDL).

CONCLUSION

IBD, UC, or CD had causal effects on the risk of T2D in the European population, which might provide evidence for the prevention of T2D in patients with IBD, UC, or CD.

Causal relationships between anthropometric traits, bone mineral density, osteoarthritis and spinal stenosis: A Mendelian randomisation investigation

OBJECTIVE

Spinal stenosis is a common condition among older individuals, with significant morbidity attached. Little is known about its risk factors but degenerative conditions, such as osteoarthritis (OA) have been identified for their mechanistic role. This study aims to explore causal relationships between anthropometric risk factors, OA, and spinal stenosis using Mendelian randomisation (MR) techniques.

DESIGN

We applied two-sample MR to investigate the causal relationships between genetic liability for select risk factors and spinal stenosis. Next, we examined the genetic relationship between OA and spinal stenosis with linkage disequilibrium score regression and Causal Analysis Using Summary Effect estimates MR method. Finally, we used multivariable MR (MVMR) to explore whether OA and body mass index (BMI) mediate the causal pathways identified.

RESULTS

Our analysis revealed strong evidence for the effect of higher BMI (odds ratio [OR] = 1.54, 95%CI: 1.41-1.69, p-value = 2.7 × 10-21), waist (OR = 1.43, 95%CI: 1.15-1.79, p-value = 1.5 × 10-3) and hip (OR = 1.50, 95%CI: 1.27-1.78, p-value = 3.3 × 10-6) circumference on spinal stenosis. Strong evidence of causality was also observed for higher bone mineral density (BMD): total body (OR = 1.21, 95%CI: 1.12-1.29, p-value = 1.6 × 10-7), femoral neck (OR = 1.35, 95%CI: 1.09-1.37, p-value = 7.5×10-7), and lumbar spine (OR = 1.38, 95%CI: 1.25-1.52, p-value = 4.4 × 10-11). We detected high genetic correlations between spinal stenosis and OA (rg range: 0.47-0.66), with Causal Analysis Using Summary Effect estimates results supporting a causal effect of OA on spinal stenosis (ORallOA = 1.6, 95%CI: 1.41-1.79). Direct effects of BMI, BMD on spinal stenosis remained after adjusting for OA in the MVMR.

CONCLUSIONS

Genetic susceptibility to anthropometric risk factors, particularly higher BMI and BMD can increase the risk of spinal stenosis, independent of OA status. These results may inform preventative strategies and treatments.

No genetic causal association between iron status and pulmonary artery hypertension: Insights from a two-sample Mendelian randomization

To explore the genetic causal association between pulmonary artery hypertension (PAH) and iron status through Mendelian randomization (MR), we conducted MR analysis using publicly available genome-wide association study (GWAS) summary data. Five indicators related to iron status (serum iron, ferritin, total iron binding capacity (TIBC), soluble transferrin receptor (sTfR), and transferrin saturation) served as exposures, while PAH was the outcome. The genetic causal association between these iron status indicators and PAH was assessed using the inverse variance weighted (IVW) method. Cochran's Q statistic was employed to evaluate heterogeneity. We assessed pleiotropy using MR-Egger regression and MR-Presso test. Additionally, we validated our results using the Weighted median, Simple mode, and Weighted mode methods. Based on the IVW method, we found no causal association between iron status (serum iron, ferritin, TIBC, sTfR, and transferrin saturation) and PAH (p β > 0.05). The Weighted median, Simple mode, and Weighted mode methods showed no potential genetic causal association (p β > 0.05 in the three analyses). Additionally, no heterogeneity or horizontal pleiotropy was detected in any of the analyses. Our results show that there are no genetic causal association between iron status and PAH.

Phenome-wide causal associations between osteoarthritis and other complex traits through the latent causal variable analysis

BACKGROUND

Individuals with osteoarthritis present with comorbidities, and the potential causal associations remain incompletely elucidated. The present study undertook a large-scale investigation about the causality between osteoarthritis and variable traits, using the summary-level data of genome-wide association studies (GWAS).

METHODS

The present study included the summary-level GWS data of knee osteoarthritis, hip osteoarthritis, hip or knee osteoarthritis, hand osteoarthritis, and other 1355 traits. Genetic correlation analysis was conducted between osteoarthritis and other traits through cross-trait bivariate linkage disequilibrium score regression. Subsequently, latent causal variable analysis was performed to explore the causal association when there was a significant genetic correlation. Genetic correlation and latent causal variable analysis were conducted on the Complex Traits Genomics Virtual Lab platform ( https://vl.genoma.io/ ).

RESULTS

We found 133 unique phenotypes showing causal relationships with osteoarthritis. Our results confirmed several well-established risk factors of osteoarthritis, such as obesity, weight, BMI, and meniscus derangement. Additionally, our findings suggested putative causal links between osteoarthritis and multiple factors. Socioeconomic determinants such as occupational exposure to dust and diesel exhaust, extended work hours exceeding 40 per week, and unemployment status were implicated. Furthermore, our analysis revealed causal associations with cardiovascular and metabolic disorders, including heart failure, deep venous thrombosis, type 2 diabetes mellitus, and elevated cholesterol levels. Soft tissue and musculoskeletal disorders, such as hallux valgus, internal derangement of the knee, and spondylitis, were also identified to be causally related to osteoarthritis. The study also identified the putative causal associations of osteoarthritis with digestive and respiratory diseases, such as Barrett's esophagus, esophagitis, and asthma, as well as psychiatric conditions including panic attacks and manic or hyperactive episodes. Additionally, we observed osteoarthritis causally related to pharmacological treatments, such as the use of antihypertensive medications, anti-asthmatic drugs, and antidepressants.

CONCLUSION

Our study uncovered a wide range of traits causally associated with osteoarthritis. Further studies are needed to validate and illustrate the detailed mechanism of those causal associations.

Causal Factors for Osteoarthritis: A Scoping Review of Mendelian Randomization Studies

OBJECTIVE

Mendelian randomization (MR) has increasingly been utilized as a tool for establishing causal relations between modifiable exposures and osteoarthritis (OA). The goal of this review was to summarize available MR studies of OA that evaluate the causal role of modifiable risk factors on OA.

METHODS

This review was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) Extension for Scoping Reviews model. We performed a literature search for relevant studies published before December 2021 across multiple databases using the search terms "osteoarthritis" and ("Mendelian randomization" or "polygenic risk score"). We reported the MR estimates of causal associations between exposures and OA and then assessed methodologic quality of abstracted studies according to their efforts to validate the three key MR assumptions.

RESULTS

Our search identified 45 studies reporting on 141 exposure-association analyses. All studies performed a formal instrumental variable analysis to estimate the causal effect of exposure on OA. Causal associations (P < 0.05) were reported in 60 of these analyses representing 36 unique publications, and MR-Egger sensitivity analyses were performed in 45 of these analyses. MR studies provided support for causal associations of OA with increased levels of adiposity, coffee consumption, bone mineral density, and sleep disturbance, and decreased levels of serum calcium and low-density lipoprotein cholesterol.

CONCLUSION

These results highlight the potential benefits of weight reduction and improvement of sleep quality to reduce the risk of OA and call for a better understanding of the relations of coffee consumption and serum calcium to OA risk.

Coffee and the risk of osteoarthritis: a two-sample, two-step multivariable Mendelian randomization study

Purpose: To investigate the potential causal relationship between coffee consumption and osteoarthritis (OA), and to disentangle whether body mass index (BMI) and Bone mineral density (BMD) mediate this relationship. Methods: We performed two-sample and two-step Mendelian randomization (MR) analyses utilizing publicly available genome-wide association studies (GWAS) summary statistics to estimate the association between coffee intake and OA risk (including knee OA, hip OA, knee or hip OA, and total OA), as well as the possible mediating effects of BMI and BMD. In addition, data of different coffee types (decaffeinated coffee, instant coffee, ground coffee-including espresso, filter, etc., and other coffee types) were used to explore the effect of coffee type on the risk of OA. Results: In two-sample MR, coffee intake increased the risk of OA in various sites, with the most significant impact observed in knee osteoarthritis (KOA) (odds ratio [OR] 2.03, 95% confidence interval [CI] 1.57-2.61, p < 0.001). The effect on self-reported OA was minimal (OR 1.03, 95% CI 1.01-1.05, p = 0.006). Further analysis of different types of coffee revealed that only decaffeinated coffee was causally associated with both KOA (OR 4.40, 95% CI 1.71-11.33, p = 0.002) and self-reported OA (OR 1.13, 95% CI 1.02-1.26, p = 0.022). In two-step MR, BMI explained over half of the coffee intake-all OA risk association, while BMD accounted for less than 5% of the mediation effect. Conclusion: Our study suggests that coffee intake increase the risk of OA, with BMI playing a significant mediating role. Decaffeinated coffee appears to have the greatest impact on OA risk compared to other types of coffee. Therefore, managing BMI and selecting appropriate types of coffee should be included in the health management of individuals who frequently consume coffee.

Osteoarthriris year in review 2023: genetics, genomics, and epigenetics

OBJECTIVE

To elucidate the scientific advances made in the last 12 months within the realm of osteoarthritis genetics, genomics, and epigenetics. This review paper highlights major research publications that enhance our current understanding of the role of genetics, genomics, and epigenetics in osteoarthritis.

METHODS

A systematic literature search was conducted on pubmed.ncbi.nlm.nih.gov on "March 17, 2023", using the following keywords: "osteoarthritis" in combination with any of these terms: "genetic(s)", "mutation(s)", "genomic(s)", "epigenetic(s)", "DNA methylation", "noncoding RNA", "lncRNA", "circular RNA", "microRNA", "transcriptomic(s)", "RNA sequencing", "single cell RNA sequencing", or "single nucleus RNA sequencing". The selection comprised original research articles published in the English language between the OARSI congresses of 2022 and 2023.

RESULTS

A total of 2178 research articles were identified, which subsequently reduced to 67 unique articles relevant to the field. Current trends in osteoarthritis genetics research involve meta-analyses of various cohorts to explore the impact of gene variants on osteoarthritis-related outcomes, such as pain. Early developmental changes within the joint were also found to influence osteoarthritis through genetic variations. Researchers also prioritize testing the mechanisms and functions of miRNAs, circRNAs, and lncRNAs. Potential drug targets began to emerge; however, independent validation studies are lacking. Single cell RNA sequencing studies revealed unique immune cell populations in the knee; however, no study reported single nucleus RNA sequencing analysis.

CONCLUSIONS

This review focused on recent advances in the above-mentioned themes within the field of osteoarthritis. These advances improve our understanding of the disease's complexity and guide us toward functional assessments of genetic/epigenetic outcomes and toward their translational and clinical applications.

Osteoporosis and osteoarthritis: a bi-directional Mendelian randomization study

OBJECTIVE

To investigate the causal relationship between low bone mineral density (BMD) and osteoarthritis (OA) using Mendelian randomization (MR) design.

METHODS

Two-sample bi-directional MR analyses were performed using summary-level information on OA traits from UK Biobank and arcOGEN. Sensitivity analyses including MR-Egger, simple median, weighted median, MR pleiotropy residual sum, and outlier approaches were utilized in conjunction with inverse variance weighting (IVW). Gene ontology (GO) enrichment analyses and expression quantitative trait locus (eQTL) colocalization analyses were used to investigate the potential mechanism and shared genes between osteoporosis (OP) and OA.

RESULTS

The IVW method revealed that genetically predicted low femoral neck BMD was significantly linked with hip (β = 0.105, 95% CI: 0.023-0.188) and knee OA (β = 0.117, 95% CI: 0.049-0.184), but not with other site-specific OA. Genetically predicted low lumber spine BMD was significantly associated with OA at any sites (β = 0.048, 95% CI: 0.011-0.085), knee OA (β = 0.101, 95% CI: 0.045-0.156), and hip OA (β = 0.150, 95% CI: 0.077-0.224). Only hip OA was significantly linked with genetically predicted reduced total bone BMD (β = 0.092, 95% CI: 0.010-0.174). In the reverse MR analyses, no evidence for a causal effect of OA on BMD was found. GO enrichment analysis and eQTL analysis illustrated that DDN and SMAD-3 were the most prominent co-located genes.

CONCLUSIONS

These findings suggested that OP may be causally linked to an increased risk of OA, indicating that measures to raise BMD may be effective in preventing OA. More research is required to determine the underlying processes via which OP causes OA.

Causal effect of physical activity and sedentary behaviors on the risk of osteoarthritis: a univariate and multivariate Mendelian randomization study

There is still a lot of ambiguity about the link between physical activity (PA), sedentary behaviors (SBs) and osteoarthritis (OA). This study aimed to investigate the causal relationship of PA/SBs on the risk of OA. A univariate and multivariate Mendelian randomization (MR) analysis was conducted to investigate the causal effect of five PA phenotypes and three SB phenotypes on overall OA, knee OA, hip OA, total hip arthroplasty, and total knee arthroplasty (TKA). MR methods used were inverse-variance weighting, MR-Egger regressions, and weighted median. Sensitivity analysis examined horizontal pleiotropy and heterogeneity, and confirmed the reliability of the results. After false discovery rate, light do-it-yourself (DIY) activities decreased the risk for overall OA (OR: 0.32, 95% CI 0.16-0.65), and knee OA (OR: 0.26, 95% CI 0.12-0.51). Resulting in a decreased risk of walking for pleasure on overall OA (OR: 0.87, 95% CI 0.70-1.04) and knee OA (OR: 0.14, 95% CI 0.06-0.32) was also observed. Television viewing, however, significantly increased the risk of OA, knee OA, hip OA, and TKA. MVMR findings revealed independent causal impacts of walking for pleasure and watching television on overall and knee OA, taking into account BMI, smoking, and education. This study suggested that light DIY and walking for pleasure were beneficial for preventing OA, and the risk of OA and TKA increased with prolonged television watching.

The causal relationship between gut microbiota and bone mineral density: a Mendelian randomization study

Background

The gut microbiota has emerged as an intriguing and potentially influential factor in regulating bone health. However, the causal effect of the gut microbiota on bone mineral density (BMD) appears to differ throughout various life stages.

Methods

We conducted a Mendelian randomization (MR) analysis to investigate the potential causal relationship between gut microbiota and BMD in five distinct age groups: 0-15, 15-30, 30-45, 45-60, and 60 years and older. The analysis employed three different methods, namely MR-Egger, weighted median, and Inverse-variance weighting, to ensure the robustness of our findings, a series of sensitivity analyses were also conducted, such as horizontal pleiotropy tests, heterogeneity tests, and leave-one-out sensitivity tests.

Results

In the age group of 0-15 years, Eubacterium_fissicatena_group and Eubacterium_hallii_group were identified as risk factors for BMD. During the 15-30 age group, Phascolarctobacterium, Roseburia, and Ruminococcaceae_UCG_003 were found to be protective factors for BMD. In the 30-45 age group, Lachnospira genus demonstrated a protective effect on BMD, while Barnesiella and Lactococcus were identified as risk factors for BMD. Moving on to the 45-60 age group, Eubacterium_ventriosum_group, Lachnospiraceae_UCG_004, and Subdoligranulum were observed to be protective factors for BMD, while Eubacterium_coprostanoligenes_group, Fusicatenibacter, and Lactococcus were associated with an increased risk of BMD. In individuals aged 60 years and older, Fusicatenibacter and Ruminococcaceae_UCG_002 were also noted as risk factors for BMD. Conversely, Eubacterium_ruminantium_group, Ruminococcus_gauvreauii_group, Alistipes, and Coprococcus_3 were found to be protective factors for BMD, whereas Barnesiella and Sellimonas were identified as risk factors for BMD.

Conclusion

A robust causal relationship between gut microbiota and bone mineral density (BMD) exists throughout all stages of life, with Firmicutes phylum being the primary group associated with BMD across age groups. Gut microbiota linked with BMD primarily belong to the Firmicutes phylum across age groups. The diversity of gut microbiota phyla associated with BMD depicts relatively stable patterns during the ages of 0-45 years. However, for individuals aged 45 years and above, there is an observed increase in the number of gut microbiota species linked with BMD, and by the age of 60 years, a trend toward an increase in the Bacteroidetes phylum categories is proposed.

Stem Design in Total Hip Arthroplasty Influences Ipsilateral Knee Valgus: A Retrospective Comparative Analysis of 2953 Cases

BACKGROUND

Total hip arthroplasty (THA) affects the biomechanics of the hip and the patient gait. The stem design influences femoral lever ratios and tissue trauma. Biomechanical changes such as these have the potential to induce knee arthritis. A varus or valgus configuration of knee arthritis is formed by asymmetric loadings. The aim of this study was to evaluate the impact of stem design in THA on knee valgus by comparing a standard implant with an implant with a short stem.

METHODS

A total of 2953 patients who underwent primary total knee arthroplasty for end-stage osteoarthritis between 2015 and 2021 were included in this retrospective data analysis. Patients were divided into three groups, depending on hip status (straight stem, short stem, and native joint). Leg alignment was distinguished as varus or valgus, and the degree of axial deviation was measured. Descriptive and explorative statistical analyses were performed, with a p value < 0.05 set as significant.

RESULTS

Ipsilateral knee valgus occurred significantly more often in patients with straight stems (57.2%) than in those with short stems (29%) and native joints (25.8%) (p < 0.001). Additionally, mean valgus deviation was significantly increased in patients with straight stems (8.9°) compared to those with short stems (6.4°) or native hip joints (6.7°). Both findings were accentuated in women.

CONCLUSIONS

Previous ipsilateral straight-stem THA is associated with knee valgus deformity, especially in women. Short-stem THA seems to be better suited to restoring physiological biomechanics and preventing the development of valgus osteoarthritis of the ipsilateral knee.

Genetic underpinning of the comorbidity between type 2 diabetes and osteoarthritis

Multimorbidity is a rising public health challenge with important implications for health management and policy. The most common multimorbidity pattern is the combination of cardiometabolic and osteoarticular diseases. Here, we study the genetic underpinning of the comorbidity between type 2 diabetes and osteoarthritis. We find genome-wide genetic correlation between the two diseases and robust evidence for association-signal colocalization at 18 genomic regions. We integrate multi-omics and functional information to resolve the colocalizing signals and identify high-confidence effector genes, including FTO and IRX3, which provide proof-of-concept insights into the epidemiologic link between obesity and both diseases. We find enrichment for lipid metabolism and skeletal formation pathways for signals underpinning the knee and hip osteoarthritis comorbidities with type 2 diabetes, respectively. Causal inference analysis identifies complex effects of tissue-specific gene expression on comorbidity outcomes. Our findings provide insights into the biological basis for the type 2 diabetes-osteoarthritis disease co-occurrence.

Causal Effect of Higher Glycated Hemoglobin (HbA1c) Levels on Knee Osteoarthritis Risk: A Mendelian Randomization Study

INTRODUCTION

The association between diabetes mellitus (DM) and risk of osteoarthritis (OA) is inconsistent based on published observational studies. This study aimed to conduct a two-sample Mendelian randomization (MR) analysis to explore the causal link between glycated hemoglobin (HbA1c) level and OA risk.

METHODS

Genome-wide association studies (GWAS) summary statistics were obtained from the publicly available Integrative Epidemiology Unit (IEU) OpenGWAS database. A series of screening processes were performed to select qualified instrumental single-nucleotide polymorphisms (SNPs) strongly related to exposure. The inverse-variance-weighted method, weighted-median method, and MR-Egger method were performed to ensure robust and reliable results. The MR-Egger intercept test, Cochran's Q test, and the leave-one-out sensitivity analysis were utilized to assess the horizontal pleiotropy, heterogeneities, and stability of these genetic variants for OA. Odds ratio (OR) and 95% confidence interval (CI) were calculated.

RESULTS

MR analyses found a robust causal association of genetically determined HbA1c with knee OA (OR = 1.561; 95% CI 1.110-2.197; P = 0.011), but not with hip OA (OR = 1.073; 95% CI 0.674-1.710; P = 0.766) or overall OA (OR = 1.141; 95% CI 0.904-1.441; P = 0.804). Sensitivity analyses showed that there was a strong association between SNPs and HbA1c (F = 21.138), no evidence of heterogeneity (Q = 150.625, P = 0.402), and no potential SNPs affecting the causal link.

CONCLUSION

Our MR study supported a causal effect of genetically increased HbA1c on knee OA risk.

Novel genetic loci associated with osteoarthritis in multi-ancestry analyses in the Million Veteran Program and UK Biobank

Osteoarthritis is a common progressive joint disease. As no effective medical interventions are available, osteoarthritis often progresses to the end stage, in which only surgical options such as total joint replacement are available. A more thorough understanding of genetic influences of osteoarthritis is essential to develop targeted personalized approaches to treatment, ideally long before the end stage is reached. To date, there have been no large multiancestry genetic studies of osteoarthritis. Here, we leveraged the unique resources of 484,374 participants in the Million Veteran Program and UK Biobank to address this gap. Analyses included participants of European, African, Asian and Hispanic descent. We discovered osteoarthritis-associated genetic variation at 10 loci and replicated findings from previous osteoarthritis studies. We also present evidence that some osteoarthritis-associated regions are robust to population ancestry. Drug repurposing analyses revealed enrichment of targets of several medication classes and provide potential insight into the etiology of beneficial effects of antiepileptics on osteoarthritis pain.

A Guide for Understanding and Designing Mendelian Randomization Studies in the Musculoskeletal Field

Mendelian randomization (MR) is an increasingly popular component of an epidemiologist's toolkit, used to provide evidence of a causal effect of one trait (an exposure, eg, body mass index [BMI]) on an outcome trait or disease (eg, osteoarthritis). Identifying these effects is important for understanding disease etiology and potentially identifying targets for therapeutic intervention. MR uses genetic variants as instrumental variables for the exposure, which should not be influenced by the outcome or confounding variables, overcoming key limitations of traditional epidemiological analyses. For MR to generate a valid estimate of effect, key assumptions must be met. In recent years, there has been a rapid rise in MR methods that aim to test, or are robust to violations of, these assumptions. In this review, we provide an overview of MR for a non-expert audience, including an explanation of these key assumptions and how they are often tested, to aid a better reading and understanding of the MR literature. We highlight some of these new methods and how they can be useful for specific methodological challenges in the musculoskeletal field, including for conditions or traits that share underlying biological pathways, such as bone and joint disease. © 2022 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

High bone mass and cam morphology are independently related to hip osteoarthritis: findings from the High Bone Mass cohort

BACKGROUND

High bone mass (HBM, BMD Z-score ≥  + 3.2) and cam morphology (bulging of lateral femoral head) are associated with greater odds of prevalent radiographic hip osteoarthritis (rHOA). As cam morphology is itself a manifestation of increased bone deposition around the femoral head, it is conceivable that cam morphology may mediate the relationship between HBM and rHOA. We therefore aimed to determine if individuals with HBM have increased odds of prevalent cam morphology. In addition, we investigated whether the relationship between cam and prevalent and incident osteoarthritis was preserved in a HBM population.

METHODS

In the HBM study, a UK based cohort of adults with unexplained HBM and their relatives and spouses (controls), we determined the presence of cam morphology using semi-automatic methods of alpha angle derivation from pelvic radiographs. Associations between HBM status and presence of cam morphology, and between cam morphology and presence of rHOA (or its subphenotypes: osteophytes, joint space narrowing, cysts, and subchondral sclerosis) were determined using multivariable logistic regression, adjusting for age, sex, height, weight, and adolescent physical activity levels. The association between cam at baseline and incidence of rHOA after an average of 8 years was determined. Generalised estimating equations accounted for individual-level clustering.

RESULTS

The study included 352 individuals, of whom 235 (66.7%) were female and 234 (66.5%) had HBM. Included individuals contributed 694 hips, of which 143 had a cam deformity (20.6%). There was no evidence of an association between HBM and cam morphology (OR = 0.97 [95% CI: 0.63-1.51], p = 0.90) but a strong relationship was observed between cam morphology and rHOA (OR = 3.96 [2.63-5.98], p = 5.46 × 10-11) and rHOA subphenotypes joint space narrowing (OR = 3.70 [2.48-5.54], p = 1.76 × 10-10), subchondral sclerosis (OR = 3.28 [1.60-6.60], p = 9.57 × 10-4) and osteophytes (OR = 3.01 [1.87-4.87], p = 6.37 × 10-6). Cam morphology was not associated with incident osteoarthritis (OR = 0.76 [0.16-3.49], p = 0.72).

CONCLUSIONS

The relationship between cam morphology and rHOA seen in other studies is preserved in a HBM population. This study suggests that the risk of OA conferred by high BMD and by cam morphology are mediated via distinct pathways.