Risk Factors and Population-Attributable Fractions for Incident Hip Osteoarthritis

Background: Despite the huge burden of hip osteoarthritis (OA) and the lack of effective treatment, research into the primary prevention of hip OA is in its infancy. Purpose: We sought to evaluate risk factors for incident clinical and incident radiographic hip OA among middle-aged and older adults, to evaluate the importance of risk factors from a preventive perspective, and to estimate the percentage of new cases attributable to these risk factors. Methods: We retrospectively reviewed data from the Rotterdam study, an open-population cohort study of individuals aged 55 years or older. Data including baseline age, sex, body mass index, smoking status, education level, diagnosis of diabetes, C-reactive protein (CRP), cam morphology, acetabular dysplasia, radiographic thumb OA, radiographic hip OA, and hip pain were assessed for their association with incident clinical hip OA and incident radiographic hip OA separately, after 11 years of follow-up. The population-attributable fractions (PAFs) of statistically significant modifiable risk factors were calculated, as well. Results: New onset of clinical hip OA was seen in 19.9% (544 of 2729) and incident radiographic hip OA in 9.9% (329 of 3309). Female sex, education level below average (PAF 21.4%), and radiographic hip OA (PAF 3.4%) were statistically significantly associated with incident clinical hip OA. Female sex, age, overweight (PAF 20.0%), cam morphology (PAF 7.9%), acetabular dysplasia (PAF 3.6%), and radiographic thumb OA (PAF 4.7%) were statistically significantly associated with radiographic hip OA. Conclusions: Our retrospective analysis suggests that, from a primary prevention perspective, the most important modifiable risk factors among middle-aged and older individuals may be low educational level for incident clinical hip OA and overweight for incident radiographic hip OA. Further study is warranted.</p

Multimodal Machine Learning-based Knee Osteoarthritis Progression Prediction from Plain Radiographs and Clinical Data

Knee osteoarthritis (OA) is the most common musculoskeletal disease without a cure, and current treatment options are limited to symptomatic relief. Prediction of OA progression is a very challenging and timely issue, and it could, if resolved, accelerate the disease modifying drug development and ultimately help to prevent millions of total joint replacement surgeries performed annually. Here, we present a multi-modal machine learning-based OA progression prediction model that utilizes raw radiographic data, clinical examination results and previous medical history of the patient. We validated this approach on an independent test set of 3,918 knee images from 2,129 subjects. Our method yielded area under the ROC curve (AUC) of 0.79 (0.78-0.81) and Average Precision (AP) of 0.68 (0.66-0.70). In contrast, a reference approach, based on logistic regression, yielded AUC of 0.75 (0.74-0.77) and AP of 0.62 (0.60-0.64). The proposed method could significantly improve the subject selection process for OA drug-development trials and help the development of personalized therapeutic plans

Genetics and biology of vitamin D receptor polymorphisms

The vitamin D endocrine system is involved in a wide variety of biological processes including bone metabolism, modulation of the immune response, and regulation of cell proliferation and differentiation. Variations in this endocrine system have, thus, been linked to several common diseases, including osteoarthritis (OA), diabetes, cancer, cardiovascular disease, and tuberculosis. Evidence to support this pleiotropic character of vitamin D has included epidemiological studies on circulating vitamin D hormone levels, but also genetic epidemiological studies. Genetic studies provide excellent opportunities to link molecular insights with epidemiological data and have therefore gained much interest. DNA sequence variations, which occur frequently i

Genetic Variants and Anterior Cruciate Ligament Rupture: A Systematic Review

_Background:_ Studies have shown a familial predisposition for anterior cruciate ligament (ACL) rupture and have been followed by genetic-association studies on polymorphisms in candidate genes in recent years. To date, no systematic review with a best-evidence synthesis has evaluated the influence of genetics on this devastating knee injury. _Objective:_ Our objective was to evaluate the association between genetic variants and ACL rupture. _Methods:_ We performed an extensive search in Embase, MEDLINE, Web of Science, Scopus, PubMed Publisher, Cochrane Register of Clinical Trials, and Google scholar up to 24 August 2015. Studies were eligible if they met the following inclusion criteria: (1) design was a case–control study, retrospective or prospective follow-up study, or a randomized controlled trial (RCT); (2) the study examined the association between a genetic variant and ACL rupture in both an ACL and a control group. We determined the risk of bias for all included studies. _Results:_ We included a total of 16 studies (eight at high risk of bias and eight with an unclear risk) that examined 33 different DNA variants. Conflicting evidence was found for the COL1A1 rs1800012 and COL3A1 rs1800255 variants, whereas limited evidence was found for no association of the COL5A1 rs12722 and rs13946 and COL12A1 rs970547 variants (all encoding collagen). Evidence was insufficient to draw conclusions as to whether any other genetic variant identified in this review had any association with ACL rupture. _Conclusions:_ More research is needed to support a clear association between ACL rupture and genetic variants. Genome-wide studies are recommended for exploring more potential genetic variants. Moreover, large prospective studies are needed to draw robust conclusions

Genetic polymorphisms in the locus control region and promoter of GH1 are related to serum IGF-I levels and height in patients with isolated growth hormone deficiency and healthy controls

Background/Aims: Expression of the human growth hormone (GH) gene (GH1) is regulated by a locus contro

Controlling bias and inflation in epigenome- and transcriptome-wide association studies using the empirical null distribution

We show that epigenome- and transcriptome-wide association studies (EWAS and TWAS) are prone to significant inflation and bias of test statistics, an unrecognized phenomenon introducing spurious findings if left unaddressed. Neither GWAS-based methodology nor state-of-the-art confounder adjustment methods completely remove bias and inflation. We propose a Bayesian method to control bias and inflation in EWAS and TWAS based on estimation of the empirical null distribution. Using simulations and real data, we demonstrate that our method maximizes power while properly controlling the false positive rate. We illustrate the utility of our method in large-scale EWAS and TWAS meta-analyses of age and smoking.</p

Interaction between vitamin D receptor genotype and estrogen receptor alpha genotype influences vertebral fracture risk

In view of the interactions of vitamin D and the estrogen endocrine system, we studied the combined influence of polymorphisms in the estrogen receptor (ER) alpha gene and the vitamin D receptor (VDR) gene on the susceptibility to osteoporotic vertebral fractures in 634 women aged 55 yr and older. Three VDR haplotypes (1, 2, and 3) of the BsmI, ApaI, and TaqI restriction fragment length polymorphisms and three ERalpha haplotypes (1, 2, and 3) of the PvuII and XbaI restriction fragment length polymorphisms were identified. We captured 131 nonvertebral and 85 vertebral fracture cases during a mean follow-up period of 7 yr. ERalpha haplotype 1 was dose-dependently associated with increased vertebral fracture risk (P < 0.001) corresponding to an odds ratio of 1.9 [95% confidence interval (CI), 0.9-4.1] per copy of the risk allele. VDR haplotype 1 was overrepresented in vertebral fracture cases. There was a significant interaction (P = 0.01) between ERalpha haplotype 1 and VDR haplotype 1 in determining vertebral fracture risk. The association of ERalpha haplotype 1 with vertebral fracture risk was only present in homozygous carriers of VDR haplotype 1. The risk of fracture was 2.5 (95% CI, 0.6-9.9) for heterozygous and 10.3 (95% CI, 2.7-40) for homozygous carriers of ERalpha haplotype 1. These associations were independent of bone mineral density. In conclusion, interaction between ERalpha and VDR gene polymorphisms leads to increased risk of osteoporotic vertebral fractures in women, largely independent of bone mineral density