A variant in MCF2L is associated with osteoarthritis

The Genetic Markers of Knee Osteoarthritis in Women from Russia

Osteoarthritis is a chronic progressive joint disease that clinically debuts at the stage of pronounced morphologic changes, which makes treatment difficult. In this regard, an important task is the study of genetic markers of the disease, which have not been definitively established, due to the clinical and ethnic heterogeneity of the studied populations. To find the genetic markers for the development of knee osteoarthritis (OA) in women from the Volga-Ural region of Russia, we conducted research in two stages using different genotyping methods, such as the restriction fragment length polymorphism (RFLP) measurement, TaqMan technology and competitive allele-specific PCR-KASPTM. In the first stage, we studied polymorphic variants of candidate genes (ACAN, ADAMTS5, CHST11, SOX9, COL1A1) for OA development. The association of the *27 allele of the VNTR locus of the ACAN gene was identified (OR = 1.6). In the second stage, we replicated the GWAS results (ASTN2, ALDH1A2, DVWA, CHST11, GNL3, NCOA3, FILIP/SENP1, MCF2L, GLT8D, DOT1L) for knee OA studies. The association of the *T allele of the rs7639618 locus of the DVWA gene was detected (OR = 1.54). Thus, the VNTR locus of ACAN and the rs7639618 locus of DVWA are risk factors for knee OA in women from the Volga-Ural region of Russia.

Improved genetic prediction of the risk of knee osteoarthritis using the risk factor-based polygenic score

BACKGROUND

Polygenic risk score (PRS) analysis is used to predict disease risk. Although PRS has been shown to have great potential in improving clinical care, PRS accuracy assessment has been mainly focused on European ancestry. This study aimed to develop an accurate genetic risk score for knee osteoarthritis (OA) using a multi-population PRS and leveraging a multi-trait PRS in the Japanese population.

METHODS

We calculated PRS using PRS-CS-auto, derived from genome-wide association study (GWAS) summary statistics for knee OA in the Japanese population (same ancestry) and multi-population. We further identified risk factor traits for which PRS could predict knee OA and subsequently developed an integrated PRS based on multi-trait analysis of GWAS (MTAG), including genetically correlated risk traits. PRS performance was evaluated in participants of the Nagahama cohort study who underwent radiographic evaluation of the knees (n = 3,279). PRSs were incorporated into knee OA integrated risk models along with clinical risk factors.

RESULTS

A total of 2,852 genotyped individuals were included in the PRS analysis. The PRS based on Japanese knee OA GWAS was not associated with knee OA (p = 0.228). In contrast, PRS based on multi-population knee OA GWAS showed a significant association with knee OA (p = 6.7 × 10^-5, odds ratio (OR) per standard deviation = 1.19), whereas PRS based on MTAG of multi-population knee OA, along with risk factor traits such as body mass index GWAS, displayed an even stronger association with knee OA (p = 5.4 × 10^-7, OR = 1.24). Incorporating this PRS into traditional risk factors improved the predictive ability of knee OA (area under the curve, 74.4% to 74.7%; p = 0.029).

CONCLUSIONS

This study showed that multi-trait PRS based on MTAG, combined with traditional risk factors, and using large sample size multi-population GWAS, significantly improved predictive accuracy for knee OA in the Japanese population, even when the sample size of GWAS of the same ancestry was small. To the best of our knowledge, this is the first study to show a statistically significant association between the PRS and knee OA in a non-European population.

TRIAL REGISTRATION

No. C278.

Integrin Subunit Alpha M, ITGAM Nonsynonymous SNP Is Associated with Knee Osteoarthritis among Thais: A Case-Control Study

Knee osteoarthritis (OA), which is one of the most common degenerative joint diseases, presents a multifactorial etiology, involving multiple causative factors including genetic and environmental determinants. Four human neutrophil antigen (HNA) systems can be determined using each HNA allele by single-nucleotide polymorphisms (SNPs). However, there are no data on HNA polymorphisms and knee OA in Thailand, so we investigated the association of HNA SNPs and knee OA in the Thai population. In a case-control study, detection of HNA-1, -3, -4, and -5 alleles by polymerase chain reaction with sequence-specific priming (PCR-SSP) was performed in participants with and without symptomatic knee OA. Logistic regression models were used to estimate the odds ratio (OR) and 95% confidence interval (CI) between cases and controls. Among 200 participants, 117 (58.5%) had knee OA; 83 (41.5%) did not and were included as controls in this study. An integrin subunit alpha M (ITGAM) nonsynonymous SNP, rs1143679, was markedly associated with symptomatic knee OA. The ITGAM*01*01 genotype was identified as an important increased risk factor for knee OA (adjusted OR = 5.645, 95% CI = 1.799-17.711, p = 0.003). These findings may contribute to our understanding of the application prospects for therapeutic approaches to knee OA.

Single nucleotide polymorphism genes and mitochondrial DNA haplogroups as biomarkers for early prediction of knee osteoarthritis structural progressors: use of supervised machine learning classifiers

BACKGROUND

Knee osteoarthritis is the most prevalent chronic musculoskeletal debilitating disease. Current treatments are only symptomatic, and to improve this, we need a robust prediction model to stratify patients at an early stage according to the risk of joint structure disease progression. Some genetic factors, including single nucleotide polymorphism (SNP) genes and mitochondrial (mt)DNA haplogroups/clusters, have been linked to this disease. For the first time, we aim to determine, by using machine learning, whether some SNP genes and mtDNA haplogroups/clusters alone or combined could predict early knee osteoarthritis structural progressors.

METHODS

Participants (901) were first classified for the probability of being structural progressors. Genotyping included SNP genes TP63, FTO, GNL3, DUS4L, GDF5, SUPT3H, MCF2L, and TGFA; mtDNA haplogroups H, J, T, Uk, and others; and clusters HV, TJ, KU, and C-others. They were considered for prediction with major risk factors of osteoarthritis, namely, age and body mass index (BMI). Seven supervised machine learning methodologies were evaluated. The support vector machine was used to generate gender-based models. The best input combination was assessed using sensitivity and synergy analyses. Validation was performed using tenfold cross-validation and an external cohort (TASOAC).

RESULTS

From 277 models, two were defined. Both used age and BMI in addition for the first one of the SNP genes TP63, DUS4L, GDF5, and FTO with an accuracy of 85.0%; the second profits from the association of mtDNA haplogroups and SNP genes FTO and SUPT3H with 82.5% accuracy. The highest impact was associated with the haplogroup H, the presence of CT alleles for rs8044769 at FTO, and the absence of AA for rs10948172 at SUPT3H. Validation accuracy with the cross-validation (about 95%) and the external cohort (90.5%, 85.7%, respectively) was excellent for both models.

CONCLUSIONS

This study introduces a novel source of decision support in precision medicine in which, for the first time, two models were developed consisting of (i) age, BMI, TP63, DUS4L, GDF5, and FTO and (ii) the optimum one as it has one less variable: age, BMI, mtDNA haplogroup, FTO, and SUPT3H. Such a framework is translational and would benefit patients at risk of structural progressive knee osteoarthritis.

Multi-omics molecular biomarkers and database of osteoarthritis

Osteoarthritis (OA) is the most common form of arthritis in the adult population and is a leading cause of disability. OA-related genetic loci may play an important role in clinical diagnosis and disease progression. With the rapid development of diverse technologies and omics methods, many OA-related public data sets have been accumulated. Here, we retrieved a diverse set of omics experimental results from 159 publications, including genome-wide association study, differentially expressed genes and differential methylation regions, and 2405 classified OA-related gene markers. Meanwhile, based on recent single-cell RNA-seq data from different joints, 5459 cell-type gene markers of joints were collected. The information has been integrated into an online database named OAomics and molecular biomarkers (OAOB). The database (http://ibi.zju.edu.cn/oaobdb/) provides a web server for OA marker genes, omics features and so on. To our knowledge, this is the first database of molecular biomarkers for OA.

Genetics of osteoarthritis

Osteoarthritis genetics has been transformed in the past decade through the application of large-scale genome-wide association scans. So far, over 100 polymorphic DNA variants have been associated with this common and complex disease. These genetic risk variants account for over 20% of osteoarthritis heritability and the vast majority map to non-protein coding regions of the genome where they are presumed to act by regulating the expression of target genes. Statistical fine mapping, in silico analyses of genomics data, and laboratory-based functional studies have enabled the identification of some of these targets, which encode proteins with diverse roles, including extracellular signaling molecules, intracellular enzymes, transcription factors, and cytoskeletal proteins. A large number of the risk variants correlate with epigenetic factors, in particular cartilage DNA methylation changes in cis, implying that epigenetics may be a conduit through which genetic effects on gene expression are mediated. Some of the variants also appear to have been selected as humans adapted to bipedalism, suggesting that a proportion of osteoarthritis genetic susceptibility results from antagonistic pleiotropy, with risk variants having a positive role in joint formation but a negative role in the long-term health of the joint. Although data from an osteoarthritis genetic study has not yet directly led to a novel treatment, some of the osteoarthritis associated genes code for proteins that have available therapeutics. Genetic investigations are therefore revealing fascinating fundamental insights into osteoarthritis and can expose options for translational intervention.

The Genetic Epidemiology of Joint Shape and the Development of Osteoarthritis

Congruent, low-friction relative movement between the articulating elements of a synovial joint is an essential pre-requisite for sustained, efficient, function. Where disorders of joint formation or maintenance exist, mechanical overloading and osteoarthritis (OA) follow. The heritable component of OA accounts for ~ 50% of susceptible risk. Although almost 100 genetic risk loci for OA have now been identified, and the epidemiological relationship between joint development, joint shape and osteoarthritis is well established, we still have only a limited understanding of the contribution that genetic variation makes to joint shape and how this modulates OA risk. In this article, a brief overview of synovial joint development and its genetic regulation is followed by a review of current knowledge on the genetic epidemiology of established joint shape disorders and common shape variation. A summary of current genetic epidemiology of OA is also given, together with current evidence on the genetic overlap between shape variation and OA. Finally, the established genetic risk loci for both joint shape and osteoarthritis are discussed.

Sources of Individual Differences in Pain

Pain is an immense clinical and societal challenge, and the key to understanding and treating it is variability. Robust interindividual differences are consistently observed in pain sensitivity, susceptibility to developing painful disorders, and response to analgesic manipulations. This review examines the causes of this variability, including both organismic and environmental sources. Chronic pain development is a textbook example of a gene-environment interaction, requiring both chance initiating events (e.g., trauma, infection) and more immutable risk factors. The focus is on genetic factors, since twin studies have determined that a plurality of the variance likely derives from inherited genetic variants, but sex, age, ethnicity, personality variables, and environmental factors are also considered.

Identification and Functional Annotation of Genes Related to Bone Stability in Laying Hens Using Random Forests

Skeletal disorders, including fractures and osteoporosis, in laying hens cause major welfare and economic problems. Although genetics have been shown to play a key role in bone integrity, little is yet known about the underlying genetic architecture of the traits. This study aimed to identify genes associated with bone breaking strength and bone mineral density of the tibiotarsus and the humerus in laying hens. Potentially informative single nucleotide polymorphisms (SNP) were identified using Random Forests classification. We then searched for genes known to be related to bone stability in close proximity to the SNPs and identified 16 potential candidates. Some of them had human orthologues. Based on our findings, we can support the assumption that multiple genes determine bone strength, with each of them having a rather small effect, as illustrated by our SNP effect estimates. Furthermore, the enrichment analysis showed that some of these candidates are involved in metabolic pathways critical for bone integrity. In conclusion, the identified candidates represent genes that may play a role in the bone integrity of chickens. Although further studies are needed to determine causality, the genes reported here are promising in terms of alleviating bone disorders in laying hens.

Constitutional morphological features and risk of hip osteoarthritis: a case-control study using standard radiographs

OBJECTIVES

To evaluate the risk of association with hip osteoarthritis (OA) of 14 morphological features measured on standard antero-posterior pelvis radiographs.

METHODS

A case-control study of 566 symptomatic unilateral hip OA cases and 1108 controls without hip OA, using the Genetics of OA and Lifestyle database. Unaffected hips of cases were assumed to reflect pre-OA morphology of the contralateral affected hip. ORs with 95% CI adjusted for confounding factors were calculated using logistic regression. Hierarchical clustering on principal component method was used to identify clusters of morphological features. Proportional risk contribution (PRC) of these morphological features in the context of other risk factors of hip OA was estimated using receiver operating characteristic analysis.

RESULTS

All morphological features showed right-left symmetry in controls. Each feature was associated with hip OA after adjusting for age, gender and body mass index. Increased sourcil angle had the strongest association (OR: 6.93, 95% CI 5.16 to 9.32). Three clusters were identified. The PRC varied between individual features, as well as between clusters. It was 35% (95% CI 31% to 40%) for all 14 morphological features, compared to 21% (95% CI 19% to 24%) for all other well-established risk factors.

CONCLUSIONS

Constitutional morphological variation strongly associates with hip OA development and may explain much of its heritability. Relevant morphological measures can be assessed readily on standard radiographs to help predict risk of hip OA. Prospective studies are required to provide further support for causality.

Identification of the key gene and pathways associated with osteoarthritis via single-cell RNA sequencing on synovial fibroblasts

Osteoarthritis (OA) is a chronic degenerative joint disease with its onset closely related to the growth of synovial fibroblasts (SFs), yet the genes involved in are few reported. In our study, we aimed to identify the OA-associated key gene and pathways via the single-cell RNA sequencing (scRNA-seq) analysis on SFs.scRNA-seq data of SFs from OA sufferers were accessed from GEO database, then the genes involved in were subjected to principal component analysis (PCA) and T-Stochastic Neighbor Embedding (TSNE) Analysis. GO and KEGG enrichment analyses were performed to find the most enriched functions and pathways associated with marker genes and a PPI network was constructed to identify the key gene associated with OA occurrence.Findings revealed that marker genes in three cell types identified by TSNE were mainly activated in pathways firmly related to fibroblasts growth, such as extracellular matrix, immune and cell adhesion molecule binding-associated functions and pathways. Moreover, fibronectin1 (FN1) was validated as the key gene that was tightly related to the growth of SFs, as well as had the potential to play a key role in OA occurrence.Our study explored the key gene and pathways associated with OA occurrence, which were of great value in further investigation of OA diagnosis as well as pathogenesis.

Genetics in Cartilage Lesions: Basic Science and Therapy Approaches

Cartilage lesions have a multifactorial nature, and genetic factors are their strongest determinants. As biochemical and genetic studies have dramatically progressed over the past decade, the molecular basis of cartilage pathologies has become clearer. Several homeostasis abnormalities within cartilaginous tissue have been found, including various structural changes, differential gene expression patterns, as well as altered epigenetic regulation. However, the efficient treatment of cartilage pathologies represents a substantial challenge. Understanding the complex genetic background pertaining to cartilage pathologies is useful primarily in the context of seeking new pathways leading to disease progression as well as in developing new targeted therapies. A technology utilizing gene transfer to deliver therapeutic genes to the site of injury is quickly becoming an emerging approach in cartilage renewal. The goal of this work is to provide an overview of the genetic basis of chondral lesions and the different approaches of the most recent systems exploiting therapeutic gene transfer in cartilage repair. The integration of tissue engineering with viral gene vectors is a novel and active area of research. However, despite promising preclinical data, this therapeutic concept needs to be supported by the growing body of clinical trials.

Evolutionary Selection and Constraint on Human Knee Chondrocyte Regulation Impacts Osteoarthritis Risk

During human evolution, the knee adapted to the biomechanical demands of bipedalism by altering chondrocyte developmental programs. This adaptive process was likely not without deleterious consequences to health. Today, osteoarthritis occurs in 250 million people, with risk variants enriched in non-coding sequences near chondrocyte genes, loci that likely became optimized during knee evolution. We explore this relationship by epigenetically profiling joint chondrocytes, revealing ancient selection and recent constraint and drift on knee regulatory elements, which also overlap osteoarthritis variants that contribute to disease heritability by tending to modify constrained functional sequence. We propose a model whereby genetic violations to regulatory constraint, tolerated during knee development, lead to adult pathology. In support, we discover a causal enhancer variant (rs6060369) present in billions of people at a risk locus (GDF5-UQCC1), showing how it impacts mouse knee-shape and osteoarthritis. Overall, our methods link an evolutionarily novel aspect of human anatomy to its pathogenesis.

Systemic Analysis of the Prognosis-Related RNA Alternative Splicing Signals in Melanoma

BACKGROUND Alternative splicing (AS), the mechanism underlying the occurrence of protein diversity, may result in cancer genesis and development when it becomes out of control, as suggested by a growing number of studies. However, systemically analyze of AS events at the genome-wide level for skin cutaneous melanoma (SKCM) is still in a preliminary phase. This study aimed to systemically analyze the bioinformatics of the AS events at a genome-wide level using The Cancer Genome Atlas (TCGA) SKCM data. MATERIAL AND METHODS The SpliceSeq tool was used to analyze the AS profiles for SKCM clinical specimens from the TCGA database. The association between AS events and overall survival was analyzed by Cox regression analysis. AS event intersections and a gene interaction network were established by UpSet plot. A multivariate survival model was used to establish a feature genes prognosis model. RESULTS A total of 103 SKCM patients with full clinical parameters available were included in this study. We established an AS network that investigated the relationship between AS events and clinical prognosis information. Furthermore, 4 underlying feature genes of SKCM (MCF2L, HARS, TFR2, and RALGPS1) were found in the AS network. We performed function analysis as well as correlation analysis of AS events with gene expression. Using the multivariate survival model, we further confirmed the 4 genes that impacted the classifying SKCM prognosis at the level of AS events as well as gene expression, especially in wild-type SKCM. CONCLUSIONS AS events could be ideal indicators for SKCM prognosis. The key feature gene MCF2L played an important role in wild-type SKCM.

Osteoarthritis year in review 2019: genetics, genomics and epigenetics

Although osteoarthritis (OA) aetiology is complex, genetic, genomic and epigenetic studies published within the last decade have advanced our understanding of the molecular processes underlying this common musculoskeletal disease. The purpose of this narrative review is to highlight the key research articles within the OA genetics, genomics and epigenetics fields that were published between April 2018 and April 2019. The review focuses on the identification of new OA genetic risk loci, genomics techniques that have been used for the first time in human cartilage and new publicly available databases, and datasets that will aid OA functional studies. Fifty-six new OA susceptibility loci were identified by two large scale genome wide association study meta-analyses, increasing the number of genome-wide significant risk loci to 90. OA risk variants are enriched near genes involved in skeletal development and morphology, and show genetic overlap with height, hip shape, bone area and developmental dysplasia of the hip. Several functional studies of OA loci were published, including a genome-wide analysis of genetic variation on cartilage gene expression. A specialised data portal for exploring cross-species skeletal transcriptomic datasets has been developed, and the first use of cartilage single cell RNAseq analysis reported. This year also saw the systematic identification of all microRNAs, long non-coding RNAs and circular RNAs expressed in human OA cartilage. Putative transcriptional regulatory regions have been mapped in human chondrocytes genome-wide, providing a dataset that will facilitate the prioritisation and characterisation of OA genetic and epigenetic loci.

miR-140-3p exhibits repressive functions on preosteoblast viability and differentiation by downregulating MCF2L in osteoporosis

Previous research manifested that miR-140-3p was a latent biomarker for osteoporosis. Nevertheless, the mechanism of miR-140-3p in osteoporosis is still not clear and needs ulteriorly studying. The purpose of our paper was to ulteriorly probe the underlying mechanism of miR-140-3p on osteoporosis. Firstly, based on the data acquired from GEO database, we found that miR-140-3p was highly expressed; meanwhile, MCF2L was lowly expressed in osteoporosis patients. Upregulation/downregulation of miR-140-3p by miR-140-3p mimic/inhibitor restrained/promoted MC3T3-E1 cell viability and differentiation. However, miR-140-3p over-expression/downregulation accelerated/repressed MC3T3-E1 cell apoptosis. MCF2L was forecasted as a target of miR-140-3p by miRanda, miRWalk, and TargetScan miRNA target gene prediction software. Luciferase reporter assay confirmed that MCF2L could be directly targeted by miR-140-3p. Moreover, we identified that the expression of MCF2L was negatively regulated by miR-140-3p. From rescue assays, we discovered that knockdown of MCF2L weakened the promoting influence of miR-140-3p ablation on MC3T3-E1 cell viability and differentiation, and receded the suppressing impact of miR-140-3p reduction on MC3T3-E1 cell apoptosis. Above all, this research disclosed that miR-140-3p repressed preosteoblast viability and differentiation while promoted preosteoblast apoptosis via targeting MCF2L. Our discoveries might afford a theoretical basis of developing a latent novel target for osteoporosis therapy.

Genome-wide association study of knee pain identifies associations with GDF5 and COL27A1 in UK Biobank

Knee pain is one of the most common musculoskeletal complaints that brings people to medical attention. Approximately 50% of individuals over the age of 50 report an experience of knee pain within the past 12 months. We sought to identify the genetic variants associated with knee pain in 171,516 subjects from the UK Biobank cohort and seek supporting evidence in cohorts from 23andMe, the Osteoarthritis Initiative, and the Johnston County Osteoarthritis Project. We identified two loci that reached genome-wide significance in the UK Biobank: rs143384, located in GDF5 (P = 1.32 × 10-12), a gene previously implicated in osteoarthritis; and rs2808772, located near COL27A1 (P = 1.49 × 10-8). These findings were supported in cohorts with self-reported osteoarthritis/radiographic knee osteoarthritis without pain information. In this report on genome-wide association of knee pain, we identified two loci in or near GDF5 and COL27A1 that are associated with knee pain.

Genome Engineering for Osteoarthritis: From Designer Cells to Disease-Modifying Drugs

BACKGROUND

Osteoarthritis (OA) is a highly prevalent degenerative joint disease involving joint cartilage and its surrounding tissues. OA is the leading cause of pain and disability worldwide. At present, there are no disease-modifying OA drugs, and the primary therapies include exercise and nonsteroidal anti-inflammatory drugs until total joint replacement at the end-stage of the disease.

METHODS

In this review, we summarized the current state of knowledge in genetic and epigenetic associations and risk factors for OA and their potential diagnostic and therapeutic applications.

RESULTS

Genome-wide association studies and analysis of epigenetic modifications (such as miRNA expression, DNA methylation and histone modifications) conducted across various populations support the notion that there is a genetic basis for certain subsets of OA pathogenesis.

CONCLUSION

With recent advances in the development of genome editing technologies such as the CRISPR-Cas9 system, these genetic and epigenetic alternations in OA can be used as platforms from which potential biomarkers for the diagnosis, prognosis, drug response, and development of potential personalized therapeutic targets for OA can be approached. Furthermore, genome editing has allowed the development of "designer" cells, whereby the receptors, gene regulatory networks, or transgenes can be modified as a basis for new cell-based therapies.

Functional testing of thousands of osteoarthritis-associated variants for regulatory activity

To date, genome-wide association studies have implicated at least 35 loci in osteoarthritis but, due to linkage disequilibrium, the specific variants underlying these associations and the mechanisms by which they contribute to disease risk have yet to be pinpointed. Here, we functionally test 1,605 single nucleotide variants associated with osteoarthritis for regulatory activity using a massively parallel reporter assay. We identify six single nucleotide polymorphisms (SNPs) with differential regulatory activity between the major and minor alleles. We show that the most significant SNP, rs4730222, exhibits differential nuclear protein binding in electrophoretic mobility shift assays and drives increased expression of an alternative isoform of HBP1 in a heterozygote chondrosarcoma cell line, in a CRISPR-edited osteosarcoma cell line, and in chondrocytes derived from osteoarthritis patients. This study provides a framework for prioritization of GWAS variants and highlights a role of HBP1 and Wnt signaling in osteoarthritis pathogenesis.

Computational identification of miRNA and their cross kingdom targets from expressed sequence tags of Ocimum basilicum

MicroRNAs (miRNAs) are conserved small non coding RNAs, which are typically 22-24 nucleotides long and play an important role in post transcription regulation andin various biological processes in both animals and plants. Ocimum basilicum is an important medicinal plant having different bioactive compounds eugenol and essential oils that possess numerous therapeutic properties. However, only a few miRNAs of Ocimum basilicum and its function have been studied till date. The present study focusses on the identification of miRNA from expressed sequenced tags by carrying out computational approaches based on the homology search method. A total of 10 potential miRNAs with 8 different families were predicted in O.basilicum. Furthermore, the psRNA target server was used to predict cross kingdom target genes on human transcriptome for identification ofpotential miRNAs. Eight miRNA families were found to modulate the 87 human target genes which were associated with RAS/MAPK signalling cascade, cardiomyopathy, HIV, breast cancer, lung cancer, Alzheimer's diseases and several neurological disorders. Moreover, O.basilicum miRNAs regulate the key human target genes having significance in various diseases and important biological networks with 10 hub nodes interactions. Thus this study gives the pave for further studies to explore the potential of miRNA mediated cross kingdom regulation and treatment of various diseases including cancer.

Update on the epidemiology, risk factors and disease outcomes of osteoarthritis

Osteoarthritis (OA) is the most frequent form of arthritis and a leading cause of pain and disability worldwide. OA can affect any synovial joint, although the hip, knee, hand, foot and spine are the most commonly affected sites. Knowledge about the occurrence and risk factors for OA is important to define the clinical and public health burden of the disease to understand mechanisms of disease occurrence and may also help to inform the development of population-wide prevention strategies. In this article, we review the occurrence and risk factors for OA and also consider patient-reported outcome measures that have been used for the assessment of the disease.

Lin28a overexpression reveals the role of Erk signaling in articular cartilage development

Adult articular cartilage shows limited tissue turnover, and therefore development of the proper structure of articular cartilage is crucial for life-long joint function. However, the mechanism by which the articular cartilage structure is developmentally regulated is poorly understood. In this study, we show evidence that activation of extracellular signal-regulated kinases (Erk1/2) in articular chondrocyte progenitors during developmental stages control articular cartilage thickness. We found that overexpression of Lin28a, an RNA-binding protein that regulates organismal growth and metabolism, in articular chondrocyte progenitor cells upregulated Erk signaling and increased articular cartilage thickness. Overexpression of a constitutively active Kras mimicked Lin28a overexpression, and inhibition of Erk signaling during embryonic stages normalized the cartilage phenotype of both Kras- and Lin28a-overexpressing mice. These results suggest that articular cartilage thickness is mainly determined during the process of embryonic synovial joint development, which is positively regulated by Erk signaling.

The Involvement of MicroRNAs in Osteoarthritis and Recent Developments: A Narrative Review

Background:

Osteoarthritis (OA) is the most common chronic joint disease and it may progressively cause disability and compromise quality of life. Lately, the role of miRNAs in the pathogenesis of OA has drawn a lot of attention. miRNAs are small, single-stranded, non-coding molecules of RNA which regulate gene expression at post-transcriptional level. The dysregulation of the expression of several miRNAs affects pathways involved in OA pathogenesis.

Objective:

The purpose of this article is to review the literature on the involvement of miRNAs in the pathogenesis of OA and the implications on its diagnosis and treatment.

Materials and Methods:

An extensive electronic literature search was conducted by two researchers from January 2008 to August 2017. Titles and abstracts of papers were screened by the authors for further inclusion in the present work. Finally, full texts of the selected articles were retrieved.

Results:

Abnormally expressed miRNAs enhance the production of cartilage degrading enzymes, inhibit the expression of cartilage matrix components, increase the production of proinflammatory cytokines, facilitate chondrocyte apoptosis, suppress autophagy in chondrocytes and are involved in pain-related pathways. miRNAs are also incorporated in extra-cellular membranous vesicles such as exosomes and participate in the intercellular communication in osteoarthritic joints.

Conclusion:

Ongoing research on miRNAs has potential implications in the diagnosis and treatment of OA. Their different levels in peripheral blood and synovial fluid between OA patients and healthy population makes them candidates for being used as biomarkers of the disease, while targeting miRNAs may be a novel therapeutic strategy in OA.

Osteoarthritis: Trauma vs Disease

Osteoarthritis (OA) is the most prevalent joint disease characterized by pain and degenerative lesions of the cartilage, subchondral bone, and other joint tissues. The causes of OA remain incompletely understood. Over the years, it has become recognized that OA is a multifactorial disease. In particular, aging and trauma are the main risk factors identified for the development of OA; however, other factors such as genetic predisposition, obesity, inflammation, gender and hormones, or metabolic syndrome contribute to OA development and lead to a more severe outcome. While this disease mainly affects people older than 60 years, OA developed after joint trauma affects all range ages and has a particular impact on young individuals and people who have highest levels of physical activity such as athletes. Traumatic injury to the joint often results in joint instability or intra-articular fractures which lead to posttraumatic osteoarthritis (PTOA). In response to injury, several molecular mechanisms are activated, increasing the production and activation of different factors that contribute to the progression of OA.In this chapter, we have focused on the interactions and contribution of the multiple factors involved in joint destruction and progression of OA. In addition, we overview the main changes and molecular mechanisms related to OA pathogenesis.

Genome-wide association and functional studies identify a role for matrix Gla protein in osteoarthritis of the hand

OBJECTIVE

Osteoarthritis (OA) is the most common form of arthritis and the leading cause of disability in the elderly. Of all the joints, genetic predisposition is strongest for OA of the hand; however, only few genetic risk loci for hand OA have been identified. Our aim was to identify novel genes associated with hand OA and examine the underlying mechanism.

METHODS

We performed a genome-wide association study of a quantitative measure of hand OA in 12 784 individuals (discovery: 8743, replication: 4011). Genome-wide significant signals were followed up by analysing gene and allele-specific expression in a RNA sequencing dataset (n=96) of human articular cartilage.

RESULTS

We found two significantly associated loci in the discovery set: at chr12 (p=3.5 × 10-10) near the matrix Gla protein (MGP) gene and at chr12 (p=6.1×10-9) near the CCDC91 gene. The DNA variant near the MGP gene was validated in three additional studies, which resulted in a highly significant association between the MGP variant and hand OA (rs4764133, Betameta=0.83, Pmeta=1.8*10-15). This variant is high linkage disequilibrium with a coding variant in MGP, a vitamin K-dependent inhibitor of cartilage calcification. Using RNA sequencing data from human primary cartilage tissue (n=96), we observed that the MGP RNA expression of the hand OA risk allele was significantly lowercompared with the MGP RNA expression of the reference allele (40.7%, p<5*10-16).

CONCLUSIONS

Our results indicate that the association between the MGP variant and increased risk for hand OA is caused by a lower expression of MGP, which may increase the burden of hand OA by decreased inhibition of cartilage calcification.

Genetic Determinants of Radiographic Knee Osteoarthritis in African Americans

OBJECTIVE

The etiology of knee osteoarthritis (OA), the most common form of arthritis, is complex and may differ by race or ethnicity. In recent years, genetic studies have identified many genetic variants associated with OA, but nearly all the studies were conducted in European whites and Asian Americans. Few studies have focused on the genetics of knee OA in African Americans.

METHODS

We performed a genome-wide association study of radiographic knee OA in 1217 African Americans from 2 North American cohort studies: 590 subjects from the Johnston County Osteoarthritis Project and 627 subjects from the Osteoarthritis Initiative. Analyses were conducted in each cohort separately and combined in an inverse variance fixed effects metaanalysis, which were then included in pathway analyses. We additionally tested 12 single-nucleotide polymorphisms robustly associated with OA in European white populations for association in African Americans.

RESULTS

We identified a genome-wide significant variant in LINC01006 (minor allele frequency 12%; p = 4.11 × 10-9) that is less common in European white populations (minor allele frequency < 3%). Five other independent loci reached suggestive significance (p < 1 × 10-6). In pathway analyses, dorsal/ventral neural tube patterning and iron ion transport pathways were significantly associated with knee OA in African Americans (false discovery rate < 0.05). We found no evidence that previously reported OA susceptibility variants in European whites were associated with knee OA in African Americans.

CONCLUSION

These results highlight differences in the genetic architecture of knee OA between African American and European whites. This finding underscores the need to include more diverse populations in OA genetics studies.

Genome-Wide Association Study of Radiographic Knee Osteoarthritis in North American Caucasians

OBJECTIVE

A major barrier to genetic studies of osteoarthritis (OA) is the need to obtain large numbers of individuals with standardized radiographic evaluations for OA. To address this gap, we performed a genome-wide association study (GWAS) of radiographically defined tibiofemoral knee OA in 3,898 cases and 3,168 controls from 4 well-characterized North American cohorts, and we performed replication analysis of previously reported OA loci.

METHODS

We performed meta-analysis using a 2-stage design. Stage 1 (discovery) consisted of a GWAS meta-analysis of radiographic knee OA carried out in the Osteoarthritis Initiative and the Johnston County Osteoarthritis Project. Knee OA was defined as definite osteophytes and possible joint space narrowing or total joint replacement in one or both knees. Stage 2 (validation) was performed in the Multicenter Osteoarthritis Study and the Genetics of Osteoarthritis study. We genotyped lead meta-analysis variants (P ≤ 1 × 10^-4 ) from stage 1 and tested the association between these variants and knee OA. We then combined results from all cohorts in a meta-analysis.

RESULTS

Lead variants from stage 1, representing 49 unique loci, were analyzed in stage 2; none met genome-wide significance in the combined analysis of stage 1 and stage 2. We validated 1 locus (rs4867568 near LSP1P3) with nominal significance (P < 0.05), which was also our top finding in the combined meta-analysis (odds ratio [OR] 0.84 [95% confidence interval (95% CI) 0.79-0.91], P = 3.02 × 10^-6 ). We observed nominally significant associations (P < 0.05) with 3 previously reported OA loci: rs143383 in GDF5 (OR 1.12 [95% CI 1.04-1.21], P = 2.13 × 10^-3 ), rs835487 in CHST11 (OR 0.93 [95% CI 0.85-0.99], P = 0.03), and rs8044769 in FTO (OR 1.10 [95% CI 1.03-1.19], P = 6.13 × 10^-3 ).

CONCLUSION

These findings provide suggestive evidence of a novel knee OA locus and confirm previously reported associations in GDF5, CHST11, and FTO.

Radiographic endophenotyping in hip osteoarthritis improves the precision of genetic association analysis

OBJECTIVE

Osteoarthritis (OA) has a strong genetic component but the success of previous genome-wide association studies (GWAS) has been restricted due to insufficient sample sizes and phenotype heterogeneity. Our aim was to examine the effect of clinically relevant endophenotyping according to site of maximal joint space narrowing (maxJSN) and bone remodelling response on GWAS signal detection in hip OA.

METHODS

A stratified GWAS meta-analysis was conducted in 2118 radiographically defined hip OA cases and 6500 population-based controls. Signals were followed up by analysing differential expression of proximal genes for bone remodelling endophenotypes in 33 pairs of macroscopically intact and OA-affected cartilage.

RESULTS

We report suggestive evidence (p<5×10-6) of association at 6 variants with OA endophenotypes that would have been missed by using presence of hip OA as the disease end point. For example, in the analysis of hip OA cases with superior maxJSN versus cases with non-superior maxJSN we detected association with a variant in the LRCH1 gene (rs754106, p=1.49×10-7, OR (95% CIs) 0.70 (0.61 to 0.80)). In the comparison of hypertrophic with non-hypertrophic OA the most significant variant was located between STT3B and GADL1 (rs6766414, p=3.13×10-6, OR (95% CIs) 1.45 (1.24 to 1.69)). Both of these associations were fully attenuated in non-stratified analyses of all hip OA cases versus population controls (p>0.05). STT3B was significantly upregulated in OA-affected versus intact cartilage, particularly in the analysis of hypertrophic and normotrophic compared with atrophic bone remodelling pattern (p=4.2×10-4).

CONCLUSIONS

Our findings demonstrate that stratification of OA cases into more homogeneous endophenotypes can identify genes of potential functional importance otherwise obscured by disease heterogeneity.

Osteoarthritis year in review 2016: genetics, genomics and epigenetics

The purpose of this narrative review is to provide an overview of last year's publications in the field of genetics, genomics and epigenetics in the osteoarthritis (OA) field. Major themes arising from a Pubmed search on (epi)genetics in OA were identified. In addition, general developments in the fast evolving field of (epi)genetics are reviewed and relevance for the OA field is summarized. In the last 5 years, a number of genome-wide association studies have identified a modest number of genetic loci associated to OA. Continued functional research into these DNA variants is showing putative biological mechanisms underlying these associations. Over the last year, no additional large genome-wide association studies were published, but there clearly remains much to be discovered in the OA genetic field. A lot of research has been done into the epigenetics of OA over the last year. Several genome-wide screens examining the methylome of osteoarthritic cartilage were done. Pathway analysis confirmed deregulation of developmental and extracellular pathways in OA cartilage. Over the last year many microRNAs (miRNAs) have been identified that potentially play important roles in cartilage homeostasis and/or OA process. Continued research will learn whether these identified miRNAs are truly causal and can be used in clinical applications. Many of the epigenetic findings need further confirmation, but they highlight potential novel pathways involved in cartilage biology and OA.

Identification of novel genetic variations affecting osteoarthritis patients

Background

Osteoarthritis (OA) is a progressive joint disease characterized by gradual degradation of extracellular matrix (ECM) components in the cartilage and bone. The ECM of cartilage is a highly specified structure that is mainly composed of type II collagen and provides tensile strength to the tissue via aggrecan and proteoglycans. However, changes in the ECM composition and structure can lead to loss of collagen type II and network integrity. Several risk factors have been correlated with OA including age, genetic predisposition, hereditary factors, obesity, mechanical injuries, and joint trauma. Certain genetic association studies have identified several genes associated with OA using genome-wide association studies (GWASs).

Results

We identified several novel genetic variants affecting genes that function in several candidate causative pathways including immune responses, inflammatory and cartilage degradation such as SELP, SPN, and COL6A6.

Conclusions

The approach of whole-exome sequencing can be a promising method to identify genetic mutations that can influence the OA disease.

Analysis of genetics and DNA methylation in osteoarthritis: What have we learnt about the disease?

Osteoarthritis (OA) is a chronic musculoskeletal disease characterised by the destruction of articular cartilage, synovial inflammation and bone remodelling. Disease aetiology is complex and highly heritable, with genetic variation estimated to contribute to 50% of OA occurrence. Epigenetic alterations, including DNA methylation changes, have also been implicated in OA pathophysiology. This review examines what genetic and DNA methylation studies have taught us about the genes and pathways involved in OA pathology. The influence of DNA methylation on the molecular mechanisms underlying OA genetic risk and the consequence of this interaction on disease susceptibility and penetrance are also discussed.

Transcriptomic analysis of stage 1 versus advanced adult granulosa cell tumors

Ovarian granulosa cell tumors (GCT) are hormonally-active neoplasms characterized, in the adult-subtype, by a mutation in the FOXL2 gene (C134W). They exhibit an indolent course with an unexplained propensity for late recurrence; ~80% of patients with aggressive, advanced stage tumors die from their disease; aside from surgery, therapeutic options are limited. To identify the molecular basis of advanced stage disease we have used whole transcriptome analysis of FOXL2 C134W mutation positive adult (a)GCT to identify genes that are differentially expressed between early (stage 1) and advanced (stage 3) aGCT. Transcriptome profiles for early (n = 6) and stage 3 (n = 6) aGCT, and for the aGCT-derived KGN, cell line identified 24 genes whose expression significantly differs between the early and stage 3 aGCT. Of these, 16 were more abundantly expressed in the stage 3 aGCT and 8 were higher in the stage 1 tumors. These changes were further examined for the genes which showed the greatest fold change: the cytokine CXCL14, microfibrillar-associated protein 5, insulin-like 3 and desmin. Gene Set Enrichment Analysis identified overexpression of genes on chromosome 7p15 which includes the homeobox A gene locus. The analysis therefore identifies a small number of genes with clearly discriminate patterns of expression arguing that the clinicopathological-derived distinction of the tumor stage is robust, whilst confirming the relative homogeneity of expression for many genes across the cohort and hence of aGCT. The expression profiles do however identify several overexpressed genes in both stage 1 and/or stage 3 aGCT which warrant further study as possible therapeutic targets.

Identification of a novel susceptibility locus at 13q34 and refinement of the 20p12.2 region as a multi-signal locus associated with bladder cancer risk in individuals of European ancestry

Candidate gene and genome-wide association studies (GWAS) have identified 15 independent genomic regions associated with bladder cancer risk. In search for additional susceptibility variants, we followed up on four promising single-nucleotide polymorphisms (SNPs) that had not achieved genome-wide significance in 6911 cases and 11 814 controls (rs6104690, rs4510656, rs5003154 and rs4907479, P < 1 × 10(-6)), using additional data from existing GWAS datasets and targeted genotyping for studies that did not have GWAS data. In a combined analysis, which included data on up to 15 058 cases and 286 270 controls, two SNPs achieved genome-wide statistical significance: rs6104690 in a gene desert at 20p12.2 (P = 2.19 × 10(-11)) and rs4907479 within the MCF2L gene at 13q34 (P = 3.3 × 10(-10)). Imputation and fine-mapping analyses were performed in these two regions for a subset of 5551 bladder cancer cases and 10 242 controls. Analyses at the 13q34 region suggest a single signal marked by rs4907479. In contrast, we detected two signals in the 20p12.2 region-the first signal is marked by rs6104690, and the second signal is marked by two moderately correlated SNPs (r(2) = 0.53), rs6108803 and the previously reported rs62185668. The second 20p12.2 signal is more strongly associated with the risk of muscle-invasive (T2-T4 stage) compared with non-muscle-invasive (Ta, T1 stage) bladder cancer (case-case P ≤ 0.02 for both rs62185668 and rs6108803). Functional analyses are needed to explore the biological mechanisms underlying these novel genetic associations with risk for bladder cancer.

The Genetic Epidemiological Landscape of Hip and Knee Osteoarthritis: Where Are We Now and Where Are We Going?

Osteoarthritis (OA) is a complex disease that affects the whole joint, with multiple biological and environmental factors contributing to its development. The heritable component for primary OA accounts for ∼50% of susceptibility. So far, candidate gene studies and genome-wide association scans have established 18 OA-associated loci. These findings account for 11% of the heritability, explaining a rather small fraction of the genetic component. To further unravel the genetic architecture of OA, the field needs to facilitate more precise phenotypic definitions, high genome coverage, and large sample metaanalyses, expecting the identification of rare and low frequency variants with potentially higher penetrance, and more accurate methods for calculating phenotype-genotype correlation. Expression analysis, epigenetics, and investigation of interactions can also help clarify the implicated transcriptional regulatory pathways and provide insights into further novel pathogenic OA mechanisms leading to diagnostic biomarker identification and new, more focused therapeutic disease approaches.

Expression analysis of the osteoarthritis genetic susceptibility locus mapping to an intron of the MCF2L gene and marked by the polymorphism rs11842874

Background

Osteoarthritis (OA) is a painful, debilitating disease characterised by loss of articular cartilage with concurrent changes in other tissues of the synovial joint. Genetic association studies have shown that a number of common variants increase the risk of developing OA. Investigating their activity can uncover novel causal pathways and potentially highlight new treatment targets. One of the reported OA association signals is marked by the single nucleotide polymorphism (SNP) rs11842874 at chromosome 13q34. rs11842874 is positioned within a small linkage disequilibrium (LD) block within intron 4 of MCF2L, a gene encoding guanine-nucleotide exchange factor DBS. There are no non-synonymous SNPs that correlate with this association signal and we therefore set out to assess whether its effect on OA susceptibility is mediated by alteration of MCF2L expression.

Methods

Nucleic acid was extracted from cartilage, synovial membrane or infrapatellar fat pad tissues from OA patients. Expression of MCF2L was measured by quantitative PCR and RNA-sequencing whilst the presence of DBS was studied using immunohistochemistry. The functional effect of SNPs within the 13q34 locus was assessed using public databases and in vitro using luciferase reporter analysis.

Results

MCF2L gene and protein expression are detectable in joint tissues, with quantitative differences in the expression of the gene and in the transcript isoforms expressed between the tissues tested. There is an expression quantitative trait locus (eQTL) operating within synovial membrane tissue, with possession of the risk-conferring A allele of rs11842874 correlating with increased MCF2L expression. SNPs within the rs11842874 LD block reside within transcriptional regulatory elements and their direct analysis reveals that several show quantitative differences in regulatory activity at the allelic level.

Conclusions

MCF2L is subject to a cis-acting eQTL in synovial membrane that correlates with the OA association signal. This signal contains several functional SNPs that could account for the susceptibility and which therefore merit further investigation. As far as we are aware, this is the first example of an OA susceptibility locus operating as an eQTL in synovial membrane tissue but not in cartilage.

Electronic supplementary material

The online version of this article (doi:10.1186/s12881-015-0254-2) contains supplementary material, which is available to authorized users.

Association study of MMP8 gene in osteoarthritis

OBJECTIVES

Osteoarthritis (OA) is a joint disease common in the elderly. There is a prior functional evidence for different matrix metalloproteinases (MMPs), such as MMP8 and MMP9, having a role in the breakdown of cartilage extracellular matrix in OA. Thus, we analyzed whether the common genetic variants of MMP8 and MMP9 contribute to the risk of OA.

MATERIALS AND METHODS

In total, 13 common tagging single-nucleotide polymorphisms (SNPs) were studied in a discovery knee OA cohort of 185 cases and 895 controls. For validation, two knee OA replication cohorts and two hand OA replication cohorts were studied (altogether 1369 OA cases, 4445 controls in the five cohorts). The χ(2) test for individual study cohorts and Cochran-Mantel-Haenszel test for combined meta-analysis were calculated using Plink.

RESULTS

The rs1940475 SNP in MMP8 showed suggestive association in the discovery cohort (OR = 0.721, 95% CI 0.575-0.906; p = 0.005). Other knee and hand OA replication study cohorts showed similar trend for the predisposing allele without reaching statistical significance in independent replication cohorts nor in their meta-analysis (p > 0.05). Meta-analysis of all five hand and knee OA study cohorts yielded a p-value of 0.027 (OR = 0.904, 95% CI 0.826-0.989).

CONCLUSIONS

Initial analysis of the MMP8 gene showed suggestive association between rs1940475 and knee OA, but the finding did not replicate in other study cohorts, even though the trend for predisposing allele was similar in all five cohorts. MMP-8 is a good biological candidate for OA, but our study did not find common variants with significant association in the gene.

Cartilage stem/progenitor cells are activated in osteoarthritis via interleukin-1β/nerve growth factor signaling

INTRODUCTION

Interleukin-1β (IL-1β) and nerve growth factor (NGF) are key regulators in the pathogenesis of inflammatory arthritis; specifically, IL-1β is involved in tissue degeneration and NGF is involved in joint pain. However, the cellular and molecular interactions between IL-1β and NGF in articular cartilage are not known. Cartilage stem/progenitor cells (CSPCs) have recently been identified in osteoarthritic (OA) cartilage on the basis of their migratory properties. Here we hypothesize that IL-1β/NGF signaling is involved in OA cartilage degeneration by targeting CSPCs.

METHOD

NGF and NGF receptor (NGFR: TrkA and p75NTR) expression in healthy and OA human articular cartilage and isolated chondrocytes was determined by immunostaining, qRT-PCR, flow cytometry and western blot. Articular cartilage derived stem/progenitor cells were collected and identified by stem/progenitor cell characteristics. 3D-cultured CSPC pellets and cartilage explants were treated with NGF and NGF neutralizing antibody, and extracellular matrix changes were examined by sulfated glycosaminoglycan (GAG) release and MMP expression and activity.

RESULTS

Expression of NGF, TrkA and p75NTR was found to be elevated in human OA cartilage. Cellular changes upon IL-1β and/or NGF treatment were then examined. NGF mRNA and NGFR proteins levels were upregulated in cultured chondrocytes exposed to IL-1β. NGF was chemotactic for cells isolated from OA cartilage. Cells isolated on the basis of their chemotactic migration towards NGF demonstrated stem/progenitor cell characteristics, including colony-forming ability, multi-lineage differentiation potential, and stem cell surface markers. The effects of NGF perturbation in cartilage explants and 3D-cultured CSPCs were next analyzed. NGF treatment resulted in extracellular matrix catabolism indicated by increased sGAG release and MMP expression and activity; conversely, treatment with NGF neutralizing antibody inhibited increased MMP levels, and enhanced tissue inhibitor of matrix metalloprotease-1 (TIMP1) expression in OA cartilage explants. NGF blockade with neutralizing antibody also affected cartilage matrix remodeling in 3D-CSPC pellet cultures.

CONCLUSION

Our results strongly suggest that NGF signaling is a contributing factor in articular cartilage degeneration in OA, which likely targets a specific subpopulation of progenitor cells, the CSPCs, affecting their migratory and matrix remodeling activities. These findings provide novel cellular/signaling therapeutic targets in osteoarthritic cartilage.

The role of inflammation-related genes in osteoarthritis

In this review article we examine the role of inflammation-related genes in osteoarthritis (OA) from the perspective of genetics, epigenetics and gene expression. There have been great strides in such genomic analyses of OA in recent years thanks to the study of adequately powered patient cohorts, the detailed analysis of candidate genes, and the application of genome-wide approaches. These have led to some unexpected and therefore exciting discoveries, implicating pathways that would not necessarily have been predicted to have a role in this common arthritis. Inflammatory-related genes sit firmly in the candidate camp based on prior observations that the OA disease process can have an inflammatory component. What is clear from the genetic studies published to date is that there is no compelling evidence that DNA variation in inflammatory genes is an OA risk factor. This conclusion may of course change as ever more powerful association studies are conducted. There is, however, compelling evidence that epigenetic effects involving inflammatory genes are a component of OA and that alteration in the expression of these genes is also highly relevant to the disease process. We may in fact be close to demonstrating, at the genomic level, a clear separation of OA patients into those in whom inflammation is a key driver of the disease and those in whom it is not. This has obvious implications for the design of trials of novel OA interventions and may also guide the intelligent re-purposing of anti-inflammatory therapies.

Methylation quantitative trait locus analysis of osteoarthritis links epigenetics with genetic risk

Osteoarthritis (OA) is a common, painful and debilitating disease of articulating joints resulting from the age-associated loss of cartilage. Well-powered genetic studies have identified a number of DNA polymorphisms that are associated with OA susceptibility. Like most complex trait loci, these OA loci are thought to influence disease susceptibility through the regulation of gene expression, so-called expression quantitative loci, or eQTLs. One mechanism through which eQTLs act is epigenetic, by modulating DNA methylation. In such cases, there are quantitative differences in DNA methylation between the two alleles of the causal polymorphism, with the association signal referred to as a methylation quantitative trait locus, or meQTL. In this study, we aimed to investigate whether the OA susceptibility loci identified to date are functioning as meQTLs by integrating genotype data with whole genome methylation data of cartilage DNA. We investigated potential genotype-methylation correlations within a 1.0-1.5 Mb region surrounding each of 16 OA-associated single-nucleotide polymorphisms (SNPs) in 99 cartilage samples and identified four that function as meQTLs. Three of these replicated in an additional cohort of up to 62 OA patients. These observations suggest that OA susceptibility loci regulate the level of DNA methylation in cis and provide a mechanistic explanation as to how these loci impact upon OA susceptibility, further increasing our understanding of the role of genetics and epigenetics in this common disease.

Regulation of vesicle transport and cell motility by Golgi-localized Dbs

DBS/MCF2L has been recently identified as a risk locus for osteoarthritis. It encodes a guanine nucleotide exchange factor (Dbs) that has been shown to regulate both normal and tumor cell motility. In the current study, we have determined that endogenous Dbs is predominantly expressed as 2 isoforms, a 130 kDa form (Dbs-130) that is localized to the Golgi complex, and an 80 kDa form (Dbs-80) that is localized to the endoplasmic reticulum (ER). We have previously described an inhibitor that binds to the RhoGEF domain of Dbs and blocks its transforming activity. Here we show that the inhibitor localizes to the Golgi, where it specifically interacts with Dbs-130. Inhibition of endogenous Dbs-130 activity is associated with reduced levels of activated Cdc42, enlarged Golgi, and resistance to Brefeldin A-mediated Golgi dispersal, suggesting a role for Dbs in vesicle transport. Cells treated with the inhibitor exhibit normal protein transport from the ER to the Golgi, but are defective in transport from the Golgi to the plasma membrane. Inhibition of Dbs-130 in MDA-MB-231 human breast tumor cells limits motility in both transwell and wound healing assays, but appears to have no effect on the organization of the microtubule cytoskeleton. The reduced motility is associated with a failure to reorient the Golgi toward the leading edge. This is consistent with the Golgi localization, and suggests that the Dbs-130 regulates aspects of the secretory pathway that are required to support cell polarization during directed migration.

Genetic polymorphisms of interleukin-16 and risk of knee osteoarthritis

BACKGROUND

Interleukin-16 (IL-16), a pleiotropic cytokine, plays a fundamental role in inflammatory diseases. This study investigates the association between IL-16 polymorphisms and the risk of knee osteoarthritis (OA) in a Chinese population.

METHODS

The IL-16 rs11556218, rs4072111, and rs4778889 polymorphisms were determined in 150 knee OA cases and 147 healthy controls through polymerase chain reaction-restriction fragment length polymorphism.

RESULTS

The results suggested that the variants in IL-16 gene rs11556218 site were associated with a decreased knee OA risk after adjusting for age, sex, BMI, and smoking and drinking status (TG vs. TT: OR, 0.69; 95% CI, 0.53-0.89; P = 0.006; GG vs. TT: OR, 0.64; 95% CI, 0.45-0.90; P = 0.042; dominant model: OR, 0.68; 95% CI, 0.29-0.87; P = 0.002; G vs. T allele: OR, 0.77; 95% CI, 0.66-0.90; P = 0.003). Similarly, subjects bearing the rs4072111 variant genotypes and alleles also had a lower susceptibility to knee OA compared with those bearing the wild-type (CT vs. CC: OR, 0.66; 95% CI, 0.53-0.83; P = 0.002; TT vs. CC: OR, 0.57; 95% CI, 0.40-0.82; P = 0.027; dominant model: OR, 0.65; 95%, CI 0.52-0.80; P <0.001; T vs. C allele: OR, 0.69; 95% CI, 0.58-0.81; P <0.001). Further, the C allele and the combined genotype (CC+CT) of rs4778889 were associated with a slightly decreased risk of knee OA. In addition, we found two high-risk haplotypes: TTT (OR, 3.70) and GCC (OR, 6.22). Finally, serum IL-16 levels of knee OA patients were significantly higher than those of controls (P = 0.001).

CONCLUSIONS

Despite the small sample size, this is the first study suggesting IL-16 gene polymorphisms to be associated with the risk of knee OA.

A genome-wide association study of copy-number variation identifies putative loci associated with osteoarthritis in Koreans

Background

OA is a complex disease caused by environmental and genetic risk factors. The purpose of this study is to identify candidate copy number variations (CNVs) associated with OA.

Methods

We performed a genome-wide association study of CNV to identify potential loci that confer susceptibility to or protection from OA. CNV genotyping was conducted using NimbleGen HD2 3 × 720K comparative hybridization array and included samples from 371 OA patients and 467 healthy controls. The putative CNV regions identified were confirmed with a TaqMan assay.

Results

We identified six genomic regions associated with OA encompassing CNV loci. None of six loci had previously been reported in genome-wide association studies with OA, although a genetic analysis suggested that they have functional effects. The protein product of a candidate risk gene for obesity, TNKS, targets Wnt inhibition, and this gene was significantly associated with hand and knee OA. Copy number deletion on TNKS was associated with a 1.37-fold decreased risk for OA. In addition, CA10, which shows a strong association with osteoporosis, was also significant in our study. Copy number deletion on this gene was associated with a 1.69-fold decreased risk for OA.

Conclusion

We identified several CNV loci that may contribute to OA susceptibility in Koreans. Further functional investigations of these genes are warranted to fully characterize their putative association.

Electronic supplementary material

The online version of this article (doi:10.1186/s12891-015-0531-4) contains supplementary material, which is available to authorized users.