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1.  Hip Ontogenesis: How Evolution, Genes, and Load History Shape Hip Morphotype and Cartilotype 
Developmental hip disorders (DHDs), eg, developmental dysplasia of the hip, slipped capitis femoris epiphysis, and femoroacetabular impingement, can be considered morphology variants of the normal hip. The femoroacetabular morphology of DHD is believed to induce osteoarthritis (OA) through local cumulative mechanical overload acting on genetically controlled patterning systems and subsequent damage of joint structures. However, it is unclear why hip morphology differs between individuals with seemingly comparable load histories and why certain hips with DHD progress to symptomatic OA whereas others do not.
We asked (1) which mechanical factors influence growth and development of the proximal femur; and (2) which genes or genetic mechanisms are associated with hip ontogenesis.
We performed a systematic literature review of mechanical and genetic factors of hip ontogeny. We focused on three fields that in recent years have advanced our knowledge of adult hip morphology: imaging, evolution, and genetics.
Where Are We Now?
Mechanical factors can be understood in view of human evolutionary peculiarities and may summate to load histories conducive to DHD. Genetic factors most likely act through multiple genes, each with modest effect sizes. Single genes that explain a DHD are therefore unlikely to be found. Apparently, the interplay between genes and load history not only determines hip morphotype, but also joint cartilage robustness (“cartilotype”) and resistance to symptomatic OA.
Where Do We Need to Go?
We need therapies that can improve both morphotype and cartilotype.
How Do We Get There?
Better phenotyping, improving classification systems of hip morphology, and comparative population studies can be done with existing methods. Quantifying load histories likely requires new tools, but proof of principle of modifying morphotype in treatment of DDH and of cartilotype with exercise is available.
PMCID: PMC3492609  PMID: 22926490
2.  GREM1, FRZB and DKK1 mRNA levels correlate with osteoarthritis and are regulated by osteoarthritis-associated factors 
Arthritis Research & Therapy  2013;15(5):R126.
Osteoarthritis is, at least in a subset of patients, associated with hypertrophic differentiation of articular chondrocytes. Recently, we identified the bone morphogenetic protein (BMP) and wingless-type MMTV integration site (WNT) signaling antagonists Gremlin 1 (GREM1), frizzled-related protein (FRZB) and dickkopf 1 homolog (Xenopus laevis) (DKK1) as articular cartilage’s natural brakes of hypertrophic differentiation. In this study, we investigated whether factors implicated in osteoarthritis or regulation of chondrocyte hypertrophy influence GREM1, FRZB and DKK1 expression levels.
GREM1, FRZB and DKK1 mRNA levels were studied in articular cartilage from healthy preadolescents and healthy adults as well as in preserved and degrading osteoarthritic cartilage from the same osteoarthritic joint by quantitative PCR. Subsequently, we exposed human articular chondrocytes to WNT, BMP, IL-1β, Indian hedgehog, parathyroid hormone-related peptide, mechanical loading, different medium tonicities or distinct oxygen levels and investigated GREM1, FRZB and DKK1 expression levels using a time-course analysis.
GREM1, FRZB and DKK1 mRNA expression were strongly decreased in osteoarthritis. Moreover, this downregulation is stronger in degrading cartilage compared with macroscopically preserved cartilage from the same osteoarthritic joint. WNT, BMP, IL-1β signaling and mechanical loading regulated GREM1, FRZB and DKK1 mRNA levels. Indian hedgehog, parathyroid hormone-related peptide and tonicity influenced the mRNA levels of at least one antagonist, while oxygen levels did not demonstrate any statistically significant effect. Interestingly, BMP and WNT signaling upregulated the expression of each other’s antagonists.
Together, the current study demonstrates an inverse correlation between osteoarthritis and GREM1, FRZB and DKK1 gene expression in cartilage and provides insight into the underlying transcriptional regulation. Furthermore, we show that BMP and WNT signaling are linked in a negative feedback loop, which might prove essential in articular cartilage homeostasis by balancing BMP and WNT activity.
PMCID: PMC3978825  PMID: 24286177
3.  Genome-wide association study meta-analysis of chronic widespread pain: evidence for involvement of the 5p15.2 region 
Annals of the rheumatic diseases  2012;72(3):427-436.
Chronic widespread pain (CWP) is a common disorder affecting ~10% of the general population and has an estimated heritability of 48-52%. In the first large-scale genome-wide association study (GWAS) meta-analysis, we aimed to identify common genetic variants associated with CWP.
We conducted a GWAS meta-analysis in 1,308 female CWP cases and 5,791 controls of European descent, and replicated the effects of the genetic variants with suggestive evidence for association in 1,480 CWP cases and 7,989 controls (P<1×10−5). Subsequently, we studied gene expression levels of the nearest genes in two chronic inflammatory pain mouse models, and examined 92 genetic variants previously described associated with pain.
The minor C-allele of rs13361160 on chromosome 5p15.2, located upstream of CCT5 and downstream of FAM173B, was found to be associated with a 30% higher risk of CWP (MAF=43%; OR=1.30, 95%CI=1.19-1.42, P=1.2×10−8). Combined with the replication, we observed a slightly attenuated OR of 1.17 (95%CI=1.10-1.24, P=4.7×10−7) with moderate heterogeneity (I2=28.4%). However, in a sensitivity analysis that only allowed studies with joint-specific pain, the combined association was genome-wide significant (OR=1.23, 95%CI=1.14-1.32, P=3.4×10−8, I2=0%). Expression levels of Cct5 and Fam173b in mice with inflammatory pain were higher in the lumbar spinal cord, not in the lumbar dorsal root ganglions, compared to mice without pain. None of the 92 genetic variants previously described were significantly associated with pain (P>7.7×10−4).
We identified a common genetic variant on chromosome 5p15.2 associated with joint-specific CWP in humans. This work suggests that CCT5 and FAM173B are promising targets in the regulation of pain.
PMCID: PMC3691951  PMID: 22956598
Gene Polymorphism; Fibromyalgia/Pain Syndromes; Epidemiology
4.  Identification and systematic annotation of tissue-specific differentially methylated regions using the Illumina 450k array 
DNA methylation has been recognized as a key mechanism in cell differentiation. Various studies have compared tissues to characterize epigenetically regulated genomic regions, but due to differences in study design and focus there still is no consensus as to the annotation of genomic regions predominantly involved in tissue-specific methylation. We used a new algorithm to identify and annotate tissue-specific differentially methylated regions (tDMRs) from Illumina 450k chip data for four peripheral tissues (blood, saliva, buccal swabs and hair follicles) and six internal tissues (liver, muscle, pancreas, subcutaneous fat, omentum and spleen with matched blood samples).
The majority of tDMRs, in both relative and absolute terms, occurred in CpG-poor regions. Further analysis revealed that these regions were associated with alternative transcription events (alternative first exons, mutually exclusive exons and cassette exons). Only a minority of tDMRs mapped to gene-body CpG islands (13%) or CpG islands shores (25%) suggesting a less prominent role for these regions than indicated previously. Implementation of ENCODE annotations showed enrichment of tDMRs in DNase hypersensitive sites and transcription factor binding sites. Despite the predominance of tissue differences, inter-individual differences in DNA methylation in internal tissues were correlated with those for blood for a subset of CpG sites in a locus- and tissue-specific manner.
We conclude that tDMRs preferentially occur in CpG-poor regions and are associated with alternative transcription. Furthermore, our data suggest the utility of creating an atlas cataloguing variably methylated regions in internal tissues that correlate to DNA methylation measured in easy accessible peripheral tissues.
PMCID: PMC3750594  PMID: 23919675
Differentially methylated region; Illumina 450k; Annotation; Algorithm; Tissue
5.  Meta-analysis of genome-wide association studies confirms a susceptibility locus for knee osteoarthritis on chromosome 7q22 
Evangelou, Evangelos | Valdes, Ana M. | Kerkhof, Hanneke J.M | Styrkarsdottir, Unnur | Zhu, YanYan | Meulenbelt, Ingrid | Lories, Rik J. | Karassa, Fotini B. | Tylzanowski, Przemko | Bos, Steffan D. | Akune, Toru | Arden, Nigel K. | Carr, Andrew | Chapman, Kay | Cupples, L. Adrienne | Dai, Jin | Deloukas, Panos | Doherty, Michael | Doherty, Sally | Engstrom, Gunnar | Gonzalez, Antonio | Halldorsson, Bjarni V. | Hammond, Christina L. | Hart, Deborah J. | Helgadottir, Hafdis | Hofman, Albert | Ikegawa, Shiro | Ingvarsson, Thorvaldur | Jiang, Qing | Jonsson, Helgi | Kaprio, Jaakko | Kawaguchi, Hiroshi | Kisand, Kalle | Kloppenburg, Margreet | Kujala, Urho M. | Lohmander, L. Stefan | Loughlin, John | Luyten, Frank P. | Mabuchi, Akihiko | McCaskie, Andrew | Nakajima, Masahiro | Nilsson, Peter M. | Nishida, Nao | Ollier, William E.R. | Panoutsopoulou, Kalliope | van de Putte, Tom | Ralston, Stuart H. | Rivadeneira, Fernado | Saarela, Janna | Schulte-Merker, Stefan | Slagboom, P. Eline | Sudo, Akihiro | Tamm, Agu | Tamm, Ann | Thorleifsson, Gudmar | Thorsteinsdottir, Unnur | Tsezou, Aspasia | Wallis, Gillian A. | Wilkinson, J. Mark | Yoshimura, Noriko | Zeggini, Eleftheria | Zhai, Guangju | Zhang, Feng | Jonsdottir, Ingileif | Uitterlinden, Andre G. | Felson, David T | van Meurs, Joyce B. | Stefansson, Kari | Ioannidis, John P.A. | Spector, Timothy D.
Annals of the rheumatic diseases  2010;70(2):349-355.
Osteoarthritis (OA) is the most prevalent form of arthritis and accounts for substantial morbidity and disability, particularly in the elderly. It is characterized by changes in joint structure including degeneration of the articular cartilage and its etiology is multifactorial with a strong postulated genetic component. We performed a meta-analysis of four genome-wide association (GWA) studies of 2,371 knee OA cases and 35,909 controls in Caucasian populations. Replication of the top hits was attempted with data from additional ten replication datasets. With a cumulative sample size of 6,709 cases and 44,439 controls, we identified one genome-wide significant locus on chromosome 7q22 for knee OA (rs4730250, p-value=9.2×10−9), thereby confirming its role as a susceptibility locus for OA. The associated signal is located within a large (500kb) linkage disequilibrium (LD) block that contains six genes; PRKAR2B (protein kinase, cAMP-dependent, regulatory, type II, beta), HPB1 (HMG-box transcription factor 1), COG5 (component of oligomeric golgi complex 5), GPR22 (G protein-coupled receptor 22), DUS4L (dihydrouridine synthase 4-like), and BCAP29 (the B-cell receptor-associated protein 29). Gene expression analyses of the (six) genes in primary cells derived from different joint tissues confirmed expression of all the genes in the joint environment.
PMCID: PMC3615180  PMID: 21068099
6.  A Genome-Wide Association Study identifies a locus on chromosome 7q22 to influence susceptibility for osteoarthritis 
Arthritis and Rheumatism  2010;62(2):499-510.
To identify genes involved in osteoarthritis (OA), the most prevalent form of joint disease, we performed a genome-wide association study (GWAS) in which we tested 500,510 Single Nucelotide Polymorphisms (SNPs) in 1341 OA cases and 3496 Dutch Caucasian controls. SNPs associated with at least two OA-phenotypes were analysed in 14,938 OA cases and approximately 39,000 controls. The C-allele of rs3815148 on chromosome 7q22 (MAF 23%, 172 kb upstream of the GPR22 gene) was consistently associated with a 1.14-fold increased risk (95%CI: 1.09–1.19) for knee- and/or hand-OA (p=8×10−8), and also with a 30% increased risk for knee-OA progression (95%CI: 1.03–1.64, p=0.03). This SNP is in almost complete linkage disequilibrium with rs3757713 (located 68 kb upstream of GPR22) which is associated with GPR22 expression levels in lymphoblast cell lines (p=4×10−12). GPR22 encodes an G-protein coupled receptor with unkown ligand (orphan receptor). Immunohistochemistry experiments showed absence of GPR22 in normal mouse articular cartilage or synovium. However, GPR22 positive chondrocytes were found in the upper layers of the articular cartilage of mouse knee joints that were challenged by in vivo papain treatment or in the presence of interleukin-1 driven inflammation. GRP22 positive chondrocyte-like cells were also found in osteophytes in instability-induced OA. In addition, GPR22 is also present in areas of the brain involved in locomotor function. Our findings reveal a novel common variant on chromosome 7q22 to influence susceptibility for prevalence and progression of OA.
PMCID: PMC3354739  PMID: 20112360
7.  Recommendations for standardization and phenotype definitions in genetic studies of osteoarthritis: the TREAT-OA consortium 
To address the need for standardization of osteoarthritis (OA) phenotypes by examining the effect of heterogeneity among symptomatic (SOA) and radiographic osteoarthritis (ROA) phenotypes.
Descriptions of OA phenotypes of the 28 studies involved in the TREAT-OA consortium were collected. To investigate whether different OA definitions result in different association results, we created hip OA definitions used within the consortium in the Rotterdam Study-I and tested the association of hip OA with gender, age and BMI using one-way ANOVA. For radiographic OA, we standardized the hip, knee and hand ROA definitions and calculated prevalence's of ROA before and after standardization in 9 cohort studies. This procedure could only be performed in cohort studies and standardization of SOA definitions was not feasible at this moment.
In this consortium, all studies with symptomatic OA phenotypes (knee, hip and hand) used a different definition and/or assessment of OA status. For knee, hip and hand radiographic OA 5, 4 and 7 different definitions were used, respectively. Different hip OA definitions do lead to different association results. For example, we showed in the Rotterdam Study-I that hip OA defined as “at least definite JSN and one definite osteophyte” was not associated with gender (p=0.22), but defined as “at least one definite osteophyte” was significantly associated with gender (p=3×10−9). Therefore, a standardization process was undertaken for radiographic OA definitions. Before standardization a wide range of ROA prevalence's was observed in the 9 cohorts studied. After standardization the range in prevalence of knee and hip ROA was small. Standardization of SOA phenotypes was not possible due to the case-control design of the studies.
Phenotype definitions influence the prevalence of OA and association with clinical variables. ROA phenotypes within the TREAT-OA consortium were standardized to reduce heterogeneity and improve power in future genetics studies.
PMCID: PMC3236091  PMID: 21059398
8.  A genome-wide linkage scan reveals CD53 as an important regulator of innate TNF-α levels 
Cytokines are major immune system regulators. Previously, innate cytokine profiles determined by lipopolysaccharide stimulation were shown to be highly heritable. To identify regulating genes in innate immunity, we analyzed data from a genome-wide linkage scan using microsatellites in osteoarthritis (OA) patients (The GARP study) and their innate cytokine data on interleukin (IL)-1β, IL-1Ra, IL-10 and tumor necrosis factor (TNF)α. A confirmation cohort consisted of the Leiden 85-Plus study. In this study, a linkage analysis was followed by manual selection of candidate genes in linkage regions showing LOD scores over 2.5. An single-nucleotide polymorphism (SNP) gene tagging method was applied to select SNPs on the basis of the highest level of gene tagging and possible functional effects. QTDT was used to identify the SNPs associated with innate cytokine production. Initial association signals were modeled by a linear mixed model. Through these analyses, we identified 10 putative genes involved in the regulation of TNFα. SNP rs6679497 in gene CD53 showed significant association with TNFα levels (P=0.001). No association of this SNP was observed with OA. A novel gene involved in the innate immune response of TNFα is identified. Genetic variation in this gene may have a role in diseases and disorders in which TNFα is closely involved.
PMCID: PMC2987381  PMID: 20407468
linkage; osteoarthritis; immunity; TNF; GARP; CD53
9.  Common genetic variation in the Estrogen Receptor Beta (ESR2) gene and osteoarthritis: results of a meta-analysis 
BMC Medical Genetics  2010;11:164.
The objective of this study was to examine the relationship between common genetic variation of the ESR2 gene and osteoarthritis.
In the discovery study, the Rotterdam Study-I, 7 single nucleotide polymorphisms (SNPs) were genotyped and tested for association with hip (284 cases, 2772 controls), knee (665 cases, 2075 controls), and hand OA (874 cases, 2184 controls) using an additive model. In the replication stage one SNP (rs1256031) was tested in an additional 2080 hip, 1318 knee and 557 hand OA cases and 4001, 2631 and 1699 controls respectively. Fixed- and random-effects meta-analyses were performed over the complete dataset including 2364 hip, 1983 knee and 1431 hand OA cases and approximately 6000 controls.
The C allele of rs1256031 was associated with a 36% increased odds of hip OA in women of the Rotterdam Study-I (OR 1.36, 95% CI 1.08-1.70, p = 0.009). Haplotype analysis and analysis of knee- and hand OA did not give additional information. With the replication studies, the meta-analysis did not show a significant effect of this SNP on hip OA in the total population (OR 1.06, 95% CI 0.99-1.15, p = 0.10). Stratification according to gender did not change the results. In this study, we had 80% power to detect an odds ratio of at least 1.14 for hip OA (α = 0.05).
This study showed that common genetic variation in the ESR2 gene is not likely to influence the risk of osteoarthritis with effects smaller than a 13% increase.
PMCID: PMC2997092  PMID: 21080949
10.  Molecular epidemiology, candidate genes versus genome-wide scans 
Genes & Nutrition  2007;2(1):27-29.
PMCID: PMC2474924  PMID: 18850134
Human genetics; Disease; Genetic epidemiology; Population studies; Biomarkers; Human; Genome scans; Complex disease
11.  Novel genetic variants associated with lumbar disc degeneration in northern Europeans: a meta-analysis of 4600 subjects 
Annals of the Rheumatic Diseases  2012;72(7):1141-1148.
Lumbar disc degeneration (LDD) is an important cause of low back pain, which is a common and costly problem. LDD is characterised by disc space narrowing and osteophyte growth at the circumference of the disc. To date, the agnostic search of the genome by genome-wide association (GWA) to identify common variants associated with LDD has not been fruitful. This study is the first GWA meta-analysis of LDD.
We have developed a continuous trait based on disc space narrowing and osteophytes growth which is measurable on all forms of imaging (plain radiograph, CT scan and MRI) and performed a meta-analysis of five cohorts of Northern European extraction each having GWA data imputed to HapMap V.2.
This study of 4600 individuals identified four single nucleotide polymorphisms with p<5×10−8, the threshold set for genome-wide significance. We identified a variant in the PARK2 gene (p=2.8×10−8) associated with LDD. Differential methylation at one CpG island of the PARK2 promoter was observed in a small subset of subjects (β=8.74×10−4, p=0.006).
LDD accounts for a considerable proportion of low back pain and the pathogenesis of LDD is poorly understood. This work provides evidence of association of the PARK2 gene and suggests that methylation of the PARK2 promoter may influence degeneration of the intervertebral disc. This gene has not previously been considered a candidate in LDD and further functional work is needed on this hitherto unsuspected pathway.
PMCID: PMC3686263  PMID: 22993228
Gene Polymorphism; Low Back Pain; Magnetic Resonance Imaging

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