N. Lakenberg

Insights into the genetic architecture of osteoarthritis from stage 1 of the arcOGEN study

Objectives The genetic aetiology of osteoarthritis has not yet been elucidated. To enable a well-powered genome-wide association study (GWAS) for osteoarthritis, the authors have formed the arcOGEN Consortium, a UK-wide collaborative effort aiming to scan genome-wide over 7500 osteoarthritis cases in a two-stage genome-wide association scan. Here the authors report the findings of the stage 1 interim analysis. Methods The authors have performed a genome-wide association scan for knee and hip osteoarthritis in 3177 cases and 4894 population-based controls from the UK. Replication of promising signals was carried out in silico in five further scans (44 449 individuals), and de novo in 14 534 independent samples, all of European descent. Results None of the association signals the authors identified reach genome-wide levels of statistical significance, therefore stressing the need for corroboration in sample sets of a larger size. Application of analytical approaches to examine the allelic architecture of disease to the stage 1 genome-wide association scan data suggests that osteoarthritis is a highly polygenic disease with multiple risk variants conferring small effects. Conclusions Identifying loci conferring susceptibility to osteoarthritis will require large-scale sample sizes and well-defined phenotypes to minimise heterogeneity.

Genome-wide association study (GWAS)-identified disease risk alleles do not compromise human longevity

A set of currently known alleles increasing the risk for coronary artery disease, cancer, and type 2 diabetes as identified by genome-wide association studies was tested for compatibility with human longevity. Here, we show that nonagenarian siblings from long-lived families and singletons older than 85 y of age from the general population carry the same number of disease risk alleles as young controls. Longevity in this study population is not compromised by the cumulative effect of this set of risk alleles for common disease.

Disease variants alter transcription factor levels and methylation of their binding sites

Most disease-associated genetic variants are noncoding, making it challenging to design experiments to understand their functional consequences. Identification of expression quantitative trait loci (eQTLs) has been a powerful approach to infer the downstream effects of disease-associated variants, but most of these variants remain unexplained. The analysis of DNA methylation, a key component of the epigenome, offers highly complementary data on the regulatory potential of genomic regions. Here we show that disease-associated variants have widespread effects on DNA methylation in trans that likely reflect differential occupancy of trans binding sites by cis-regulated transcription factors. Using multiple omics data sets from 3,841 Dutch individuals, we identified 1,907 established trait-associated SNPs that affect the methylation levels of 10,141 different CpG sites in trans (false discovery rate (FDR) < 0.05). These included SNPs that affect both the expression of a nearby transcription factor (such as NFKB1, CTCF and NKX2-3) and methylation of its respective binding site across the genome. Trans methylation QTLs effectively expose the downstream effects of disease-associated variants.

Knee and hip articular cartilage have distinct epigenomic landscapes: implications for future cartilage regeneration approaches

Objectives To elucidate the functional epigenomic landscape of articular cartilage in osteoarthritis (OA) affected knee and hip joints in relation to gene expression. Methods Using Illumina Infinium HumanMethylation450 BeadChip arrays, genome-wide DNA methylation was measured in 31 preserved and lesioned cartilage sample pairs (14 knees and 17 hips) from patients who underwent a total joint replacement due to primary OA. Using previously published genome-wide expression data of 33 pairs of cartilage samples, of which 13 pairs were overlapping with the current methylation dataset, we assessed gene expression differences in differentially methylated regions (DMRs). Results Principal component analysis of the methylation data revealed distinct clustering of knee and hip samples, irrespective of OA pathophysiology. A total of 6272 CpG dinucleotides were differentially methylated between the two joints, comprising a total of 357 DMRs containing 1817 CpGs and 245 unique genes. Enrichment analysis of genes proximal of the DMRs revealed significant enrichment for developmental pathways and homeobox (HOX) genes. Subsequent transcriptomic analysis of DMR genes exposed distinct knee and hip expression patterns. Conclusions Our findings reveal consistent DMRs between knee and hip articular cartilage that marked transcriptomic differences among HOX genes, which were not reflecting the temporal sequential HOX expression pattern during development. This implies distinct mechanisms for maintaining cartilage integrity in adulthood, thereby contributing to our understanding of cartilage homeostasis and future tissue regeneration approaches.

Large replication study and meta-analyses of DVWA as an osteoarthritis susceptibility locus in European and Asian populations

Recently, through a genome wide association study in Japanese knee osteoarthritis (OA) cases, a previously unknown gene, DVWA, was identified. The non-synonymous single nucleotide polymorphism (SNP) rs7639618 was subsequently found to be consistent and most significantly associated in Japanese and Han Chinese knee OA studies and functional relevant. Here, the association of the DVWA polymorphisms (rs7639618, rs11718863 and rs9864422) was genotyped in 1120 knee OA cases, 1482 hip OA cases and 2147 controls, all of white European descent from the Netherlands, the UK, Spain and Greece. Random effect DerSimonian and Laird meta-analyses were performed to assess the association in the different strata. To assess a more global effect, the original Japanese and Chinese data were included with the European. The meta-analyses provided evidence for global association of rs7639618 with knee OA with an odds ratio (OR) of 1.29, 95% confidence interval (CI) of 1.15-1.45 and a P-value of 2.70 x 10(-5). This effect, however, showed moderate heterogeneity, and rs7639618 was not independently associated with knee OA in Europeans, with an OR of 1.16, 95% CI of 0.99-1.35 and a P-value of 0.063. Furthermore, no association was observed with hip OA in Europeans, with a P-value of 0.851. Our results suggest that there may be global relevance for the DVWA SNP rs7639618 among knee OA cases, however, the apparent lower effect size in combination with the higher risk allele frequency in the European samples highlights again the ethnic differences in effects of discovered OA susceptibility genes.

Genes involved in the osteoarthritis process identified through genome wide expression analysis in articular cartilage; the RAAK study

Objective Identify gene expression profiles associated with OA processes in articular cartilage and determine pathways changing during the disease process. Methods Genome wide gene expression was determined in paired samples of OA affected and preserved cartilage of the same joint using microarray analysis for 33 patients of the RAAK study. Results were replicated in independent samples by RT-qPCR and immunohistochemistry. Profiles were analyzed with the online analysis tools DAVID and STRING to identify enrichment for specific pathways and protein-protein interactions. Results Among the 1717 genes that were significantly differently expressed between OA affected and preserved cartilage we found significant enrichment for genes involved in skeletal development (e.g. TNFRSF11B and FRZB). Also several inflammatory genes such as CD55, PTGES and TNFAIP6, previously identified in within-joint analyses as well as in analyses comparing preserved cartilage from OA affected joints versus healthy cartilage were among the top genes. Of note was the high up-regulation of NGF in OA cartilage. RT-qPCR confirmed differential expression for 18 out of 19 genes with expression changes of 2-fold or higher, and immunohistochemistry of selected genes showed a concordant change in protein expression. Most of these changes associated with OA severity (Mankin score) but were independent of joint-site or sex. Conclusion We provide further insights into the ongoing OA pathophysiological processes in cartilage, in particular into differences in macroscopically intact cartilage compared to OA affected cartilage, which seem relatively consistent and independent of sex or joint. We advocate that development of treatment could benefit by focusing on these similarities in gene expression changes and/or pathways.

Meta-analysis of four new genome scans for lipid parameters and analysis of positional candidates in positive linkage regions

Lipid levels in plasma strongly influence the risk for coronary heart disease. To localise and subsequently identify genes affecting lipid levels, we performed four genome-wide linkage scans followed by combined linkage/association analysis. Genome-scans were performed in 701 dizygotic twin pairs from four samples with data on plasma levels of HDL- and LDL-cholesterol and their major protein constituents, apolipoprotein AI (ApoAI) and Apolipoprotein B (ApoB). To maximise power, the genome scans were analysed simultaneously using a well-established meta-analysis method that was newly applied to linkage analysis. Overall LOD scores were estimated using the means of the sample-specific quantitative trait locus (QTL) effects inversely weighted by the standard errors obtained using an inverse regression method. Possible heterogeneity was accounted for with a random effects model. Suggestive linkage for HDL-C was observed on 8p23.1 and 12q21.2 and for ApoAI on 1q21.3. For LDL-C and ApoB, linkage regions frequently coincided (2p24.1, 2q32.1, 19p13.2 and 19q13.31). Six of the putative QTLs replicated previous findings. After fine mapping, three maximum LOD scores mapped within 1 cM of major candidate genes, namely APOB (LOD=2.1), LDLR (LOD=1.9) and APOE (LOD=1.7). APOB haplotypes explained 27% of the QTL effect observed for LDL-C on 2p24.1 and reduced the LOD-score by 0.82. Accounting for the effect of the LDLR and APOE haplotypes did not change the LOD score close to the LDLR gene but abolished the linkage signal at the APOE gene. In conclusion, application of a new meta-analysis approach maximised the power to detect QTLs for lipid levels and improved the precision of their location estimate.

Underlying molecular mechanisms of DIO2 susceptibility in symptomatic osteoarthritis.

Objectives To investigate how the genetic susceptibility gene DIO2 confers risk to osteoarthritis (OA) onset in humans and to explore whether counteracting the deleterious effect could contribute to novel therapeutic approaches. Methods Epigenetically regulated expression of DIO2 was explored by assessing methylation of positional CpG-dinucleotides and the respective DIO2 expression in OA-affected and macroscopically preserved articular cartilage from end-stage OA patients. In a human in vitro chondrogenesis model, we measured the effects when thyroid signalling during culturing was either enhanced (excess T3 or lentiviral induced DIO2 overexpression) or decreased (iopanoic acid). Results OA-related changes in methylation at a specific CpG dinucleotide upstream of DIO2 caused significant upregulation of its expression (β=4.96; p=0.0016). This effect was enhanced and appeared driven specifically by DIO2 rs225014 risk allele carriers (β=5.58, p=0.0006). During in vitro chondrogenesis, DIO2 overexpression resulted in a significant reduced capacity of chondrocytes to deposit extracellular matrix (ECM) components, concurrent with significant induction of ECM degrading enzymes (ADAMTS5, MMP13) and markers of mineralisation (ALPL, COL1A1). Given their concurrent and significant upregulation of expression, this process is likely mediated via HIF-2α/RUNX2 signalling. In contrast, we showed that inhibiting deiodinases during in vitro chondrogenesis contributed to prolonged cartilage homeostasis as reflected by significant increased deposition of ECM components and attenuated upregulation of matrix degrading enzymes. Conclusions Our findings show how genetic variation at DIO2 could confer risk to OA and raised the possibility that counteracting thyroid signalling may be a novel therapeutic approach.

A powerful and rapid approach to human genome scanning using small quantities of genomic DNA

Dense maps of short-tandem-repeat polymorphisms (STRPs) have allowed genome-wide searches for genes involved in a great variety of diseases with genetic influences, including common complex diseases. Generally for this purpose, marker sets with a 10 cM spacing are genotyped in hundreds of individuals. We have performed power simulations to estimate the maximum possible intermarker distance that still allows for sufficient power. In this paper we further report on modifications of previously published protocols, resulting in a powerful screening set containing 229 STRPs with an average spacing of 18.3 cM. A complete genome scan using our protocol requires only 80 multiplex PCR reactions which are all carried out using one set of conditions and which do not contain overlapping marker allele sizes. The multiplex PCR reactions are grouped by sets of chromosomes, which enables on-line statistical analysis of a set of chromosomes, as sets of chromosomes are being genotyped. A genome scan following this modified protocol can be performed using a maximum amount of 2.5 micrograms of genomic DNA per individual, isolated from either blood or from mouth swabs.

Genes expressed in blood link osteoarthritis with apoptotic pathways

Objective To identify novel gene expression networks in blood of osteoarthritis patients compared to controls. Methods A comprehensive exploration of gene expression in peripheral blood was performed by microarray analysis for a subset of osteoarthritis patients from the Genetics osteoARthritis and Progression (GARP) study in comparison with sex and age-matched healthy controls. To identify pathways, we performed gene enrichment analyses (database for annotation, visualisation and integrated discovery and search tool for the retrieval of interacting genes). Quantitative PCR analysis in overlapping and in additional osteoarthritis samples was performed for prioritised genes to validate and replicate findings. Classification of cases and controls was explored by applying statistical models. Results 741 probes representing 694 unique genes were differentially expressed between cases and controls, including 86 genes expressed with at least a 1.5-fold difference. ATF4, GPR18 and H3F3B were among the top genes identified (p<4.5 × 10−8). We found that in the blood of osteoarthritis patients the apoptosis pathway, including the well-known gene CASP3, was significantly enriched among the differentially expressed genes. Our findings were validated in independent samples and when using a small subset of the validated genes, we could accurately distinguish patients from controls (area under the curve 98%). Conclusions In the current study, we have identified specific gene expression networks, in the easily accessible tissue blood, which associated consistently with osteoarthritis among GARP study cases. Our data further hint at the relevance of apoptosis as an aetiological factor in osteoarthritis onset, thereby qualifying expression profiling of blood as a useful tool to understand the underlying molecular mechanisms of osteoarthritis.