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

Osmolarity-Induced Altered Intracellular Molecular Crowding Drives Osteoarthritis Pathology

Osteoarthritis (OA) is a multifactorial degenerative joint disease of which the underlying mechanisms are yet to be fully understood. At the molecular level, multiple factors including altered signaling pathways, epigenetics, metabolic imbalance, extracellular matrix degradation, production of matrix metalloproteinases, and inflammatory cytokines, are known to play a detrimental role in OA. However, these factors do not initiate OA, but are mediators or consequences of the disease, while many other factors causing the etiology of OA are still unknown. Here, it is revealed that microenvironmental osmolarity can induce and reverse osteoarthritis-related behavior of chondrocytes via altered intracellular molecular crowding, which represents a previously unknown mechanism underlying OA pathophysiology. Decreased intracellular crowding is associated with increased sensitivity to proinflammatory triggers and decreased responsiveness to anabolic stimuli. OA-induced lowered intracellular molecular crowding could be renormalized via exposure to higher extracellular osmolarity such as those found in healthy joints, which reverse OA chondrocyte's sensitivity to catabolic stimuli as well as its glycolytic metabolism.</p