Allelic expression imbalance in articular cartilage and subchondral bone refined genome-wide association signals in osteoarthritis

OBJECTIVES

To present an unbiased approach to identify positional transcript single nucleotide polymorphisms (SNPs) of osteoarthritis (OA) risk loci by allelic expression imbalance (AEI) analyses using RNA sequencing of articular cartilage and subchondral bone from OA patients.

METHODS

RNA sequencing from 65 articular cartilage and 24 subchondral bone from OA patients was used for AEI analysis. AEI was determined for all genes present in the 100 regions reported by the GWAS catalog that were also expressed in cartilage or bone. The count fraction of the alternative allele (φ) was calculated for each heterozygous individual with the risk-SNP or with the SNP in linkage disequilibrium (LD) with it (r2 > 0.6). Furthermore, a meta-analysis was performed to generate a meta-φ (null hypothesis median φ = 0.49) and P-value for each SNP.

RESULTS

We identified 30 transcript SNPs (28 in cartilage and 2 in subchondral bone) subject to AEI in 29 genes. Notably, 10 transcript SNPs were located in genes not previously reported in the GWAS catalog, including two long intergenic non-coding RNAs (lincRNAs), MALAT1 (meta-φ = 0.54, FDR = 1.7x10-4) and ILF3-DT (meta-φ = 0.6, FDR = 1.75x10-5). Moreover, 12 drugs were interacting with 7 genes displaying AEI, of which 7 drugs have been already approved.

CONCLUSIONS

By prioritizing proxy transcript SNPs that mark AEI in cartilage and/or subchondral bone at loci harboring GWAS signals, we present an unbiased approach to identify the most likely functional OA risk-SNP and gene. We identified 10 new potential OA risk genes ready for further, translation towards underlying biological mechanisms.

Inhibiting thyroid activation in aged human explants prevents mechanical induced detrimental signalling by mitigating metabolic processes

OBJECTIVES

To investigate whether the deiodinase inhibitor iopanoic acid (IOP) has chondroprotective properties, a mechanical stress induced model of human aged explants was used to test both repeated dosing and slow release of IOP.

METHODS

Human osteochondral explants subjected to injurious mechanical stress (65%MS) were treated with IOP or IOP encapsulated in poly lactic-co-glycolic acid-polyethylene glycol nanoparticles (NP-IOP). Changes to cartilage integrity and signalling were determined by Mankin scoring of histology, sulphated glycosaminoglycan (sGAG) release and expression levels of catabolic, anabolic and hypertrophic markers. Subsequently, on a subgroup of samples, RNA sequencing was performed on 65%MS (n = 14) and 65%MS+IOP (n = 7) treated cartilage to identify IOP's mode of action.

RESULTS

Damage from injurious mechanical stress was confirmed by increased cartilage surface damage in the Mankin score, increased sGAG release, and consistent upregulation of catabolic markers and downregulation of anabolic markers. IOP and, though less effective, NP-IOP treatment, reduced MMP13 and increased COL2A1 expression. In line with this, IOP and NP-IOP reduced cartilage surface damage induced by 65%MS, while only IOP reduced sGAG release from explants subjected to 65%MS. Lastly, differential expression analysis identified 12 genes in IOP's mode of action to be mainly involved in reducing metabolic processes (INSIG1, DHCR7, FADS1 and ACAT2) and proliferation and differentiation (CTGF, BMP5 and FOXM1).

CONCLUSION

Treatment with the deiodinase inhibitor IOP reduced detrimental changes of injurious mechanical stress. In addition, we identified that its mode of action was likely on metabolic processes, cell proliferation and differentiation.

Long non-coding RNA expression profiling of subchondral bone reveals AC005165.1 modifying FRZB expression during osteoarthritis

Objective

To gain insight in the expression profile of long non-coding RNAs (lncRNAs) in OA subchondral bone.

Methods

RNA sequencing data of macroscopically preserved and lesioned OA subchondral bone of patients that underwent joint replacement surgery due to OA (N = 22 pairs; 5 hips, 17 knees, Research osteoArthrits Articular Tissue (RAAK study) was run through an in-house pipeline to detect expression of lncRNAs. Differential expression analysis between preserved and lesioned bone was performed. Spearman correlations were calculated between differentially expressed lncRNAs and differentially expressed mRNAs identified previously in the same samples. Primary osteogenic cells were transfected with locked nucleic acid (LNA) GapmeRs targeting AC005165.1 lncRNA, to functionally investigate its potential mRNA targets.

Results

In total, 2816 lncRNAs were well-expressed in subchondral bone and we identified 233 lncRNAs exclusively expressed in knee and 307 lncRNAs exclusively in hip. Differential expression analysis, using all samples (N = 22 pairs; 5 hips, 17 knees), resulted in 21 differentially expressed lncRNAs [false discovery rate (FDR) < 0.05, fold change (FC) range 1.19–7.39], including long intergenic non-protein coding RNA (LINC) 1411 (LINC01411, FC = 7.39, FDR = 2.20 × 10⁻⁸), AC005165.1 (FC = 0.44, FDR = 2.37 × 10⁻⁶) and empty spiracles homeobox 2 opposite strand RNA (EMX2OS, FC = 0.41, FDR = 7.64 × 10⁻³). Among the differentially expressed lncRNAs, five were also differentially expressed in articular cartilage, including AC005165.1, showing similar direction of effect. Downregulation of AC005165.1 in primary osteogenic cells resulted in consistent downregulation of highly correlated frizzled related protein (FRZB).

Conclusion

The current study identified a novel lncRNA, AC005165.1, being dysregulated in OA articular cartilage and subchondral bone. Downregulation of AC005165.1 caused a decreased expression of OA risk gene FRZB, an important member of the wnt pathway, suggesting that AC005165.1 could be an attractive potential therapeutic target with effects in articular cartilage and subchondral bone.

Identification and characterization of two consistent osteoarthritis subtypes by transcriptome and clinical data integration

OBJECTIVE

To identify OA subtypes based on cartilage transcriptomic data in cartilage tissue and characterize their underlying pathophysiological processes and/or clinically relevant characteristics.

METHODS

This study includes n = 66 primary OA patients (41 knees and 25 hips), who underwent a joint replacement surgery, from which macroscopically unaffected (preserved, n = 56) and lesioned (n = 45) OA articular cartilage were collected [Research Arthritis and Articular Cartilage (RAAK) study]. Unsupervised hierarchical clustering analysis on preserved cartilage transcriptome followed by clinical data integration was performed. Protein-protein interaction (PPI) followed by pathway enrichment analysis were done for genes significant differentially expressed between subgroups with interactions in the PPI network.

RESULTS

Analysis of preserved samples (n = 56) resulted in two OA subtypes with n = 41 (cluster A) and n = 15 (cluster B) patients. The transcriptomic profile of cluster B cartilage, relative to cluster A (DE-AB genes) showed among others a pronounced upregulation of multiple genes involved in chemokine pathways. Nevertheless, upon investigating the OA pathophysiology in cluster B patients as reflected by differentially expressed genes between preserved and lesioned OA cartilage (DE-OA-B genes), the chemokine genes were significantly downregulated with OA pathophysiology. Upon integrating radiographic OA data, we showed that the OA phenotype among cluster B patients, relative to cluster A, may be characterized by higher joint space narrowing (JSN) scores and low osteophyte (OP) scores.

CONCLUSION

Based on whole-transcriptome profiling, we identified two robust OA subtypes characterized by unique OA, pathophysiological processes in cartilage as well as a clinical phenotype. We advocate that further characterization, confirmation and clinical data integration is a prerequisite to allow for development of treatments towards personalized care with concurrently more effective treatment response.

RNA Sequencing Reveals Interacting Key Determinants of Osteoarthritis Acting in Subchondral Bone and Articular Cartilage: Identification of IL11 and CHADL as Attractive Treatment Targets

OBJECTIVE

To identify key determinants of the interactive pathophysiologic processes in subchondral bone and cartilage in osteoarthritis (OA).

METHODS

We performed RNA sequencing on macroscopically preserved and lesional OA subchondral bone from patients in the Research Arthritis and Articular Cartilage study who underwent joint replacement surgery due to OA (n = 24 sample pairs: 6 hips and 18 knees). Unsupervised hierarchical clustering and differential expression analyses were conducted. Results were combined with data on previously identified differentially expressed genes in cartilage (partly overlapping samples) as well as data on recently identified OA risk genes.

RESULTS

We identified 1,569 genes that were significantly differentially expressed between lesional and preserved subchondral bone, including CNTNAP2 (fold change [FC] 2.4, false discovery rate [FDR] 3.36 × 10^-5 ) and STMN2 (FC 9.6, FDR 2.36 × 10^-3 ). Among these 1,569 genes, 305 were also differentially expressed, and with the same direction of effect, in cartilage, including the recently recognized OA susceptibility genes IL11 and CHADL. Upon differential expression analysis with stratification for joint site, we identified 509 genes that were exclusively differentially expressed in subchondral bone of the knee, including KLF11 and WNT4. These genes that were differentially expressed exclusively in the knee were enriched for involvement in epigenetic processes, characterized by, e.g., HIST1H3J and HIST1H3H.

CONCLUSION

IL11 and CHADL were among the most consistently differentially expressed genes OA pathophysiology-related genes in both bone and cartilage. As these genes were recently also identified as robust OA risk genes, they classify as attractive therapeutic targets acting on 2 OA-relevant tissues.

Human Osteochondral Explants: Reliable Biomimetic Models to Investigate Disease Mechanisms and Develop Personalized Treatments for Osteoarthritis

Introduction

Likely due to ignored heterogeneity in disease pathophysiology, osteoarthritis (OA) has become the most common disabling joint disease, without effective disease-modifying treatment causing a large social and economic burden. In this study we set out to explore responses of aged human osteochondral explants upon different OA-related perturbing triggers (inflammation, hypertrophy and mechanical stress) for future tailored biomimetic human models.

Methods

Human osteochondral explants were treated with IL-1β (10 ng/ml) or triiodothyronine (T3; 10 nM) or received 65% strains of mechanical stress (65% MS). Changes in chondrocyte signalling were determined by expression levels of nine genes involved in catabolism, anabolism and hypertrophy. Breakdown of cartilage was measured by sulphated glycosaminoglycans (sGAGs) release, scoring histological changes (Mankin score) and mechanical properties of cartilage.

Results

All three perturbations (IL-1β, T3 and 65% MS) resulted in upregulation of the catabolic genes MMP13 and EPAS1. IL-1β abolished COL2A1 and ACAN gene expression and increased cartilage degeneration, reflected by increased Mankin scores and sGAGs released. Treatment with T3 resulted in a high and significant upregulation of the hypertrophic markers COL1A1, COL10A1 and ALPL. However, 65% MS increased sGAG release and detrimentally altered mechanical properties of cartilage.

Conclusion

We present consistent and specific output on three different triggers of OA. Perturbation with the pro-inflammatory IL-1β mainly induced catabolic chondrocyte signalling and cartilage breakdown, while T3 initiated expression of hypertrophic and mineralization markers. Mechanical stress at a strain of 65% induced catabolic chondrocyte signalling and changed cartilage matrix integrity. The major strength of our ex vivo models was that they considered aged, preserved, human cartilage of a heterogeneous OA patient population. As a result, the explants may reflect a reliable biomimetic model prone to OA onset allowing for development of different treatment modalities.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40744-021-00287-y.

Elucidating Epigenetic Regulation by Identifying Functional cis-Acting Long Noncoding RNAs and Their Targets in Osteoarthritic Articular Cartilage

Objective

To identify robustly differentially expressed long noncoding RNAs (lncRNAs) with osteoarthritis (OA) pathophysiology in cartilage and to explore potential target messenger RNA (mRNA) by establishing coexpression networks, followed by functional validation.

Methods

RNA sequencing was performed on macroscopically lesioned and preserved OA cartilage from patients who underwent joint replacement surgery due to OA (n = 98). Differential expression analysis was performed on lncRNAs that were annotated in GENCODE and Ensembl databases. To identify potential interactions, correlations were calculated between the identified differentially expressed lncRNAs and the previously reported differentially expressed protein‐coding genes in the same samples. Modulation of chondrocyte lncRNA expression was achieved using locked nucleic acid GapmeRs.

Results

By applying our in‐house pipeline, we identified 5,053 lncRNAs that were robustly expressed, of which 191 were significantly differentially expressed (according to false discovery rate) between lesioned and preserved OA cartilage. Upon integrating mRNA sequencing data, we showed that intergenic and antisense differentially expressed lncRNAs demonstrate high, positive correlations with their respective flanking sense genes. To functionally validate this observation, we selected P3H2‐AS1, which was down‐regulated in primary chondrocytes, resulting in the down‐regulation of P3H2 gene expression levels. As such, we can confirm that P3H2‐AS1 regulates its sense gene P3H2.

Conclusion

By applying an improved detection strategy, robustly differentially expressed lncRNAs in OA cartilage were detected. Integration of these lncRNAs with differential mRNA expression levels in the same samples provided insight into their regulatory networks. Our data indicate that intergenic and antisense lncRNAs play an important role in regulating the pathophysiology of OA.

Annotating Transcriptional Effects of Genetic Variants in Disease-Relevant Tissue: Transcriptome-Wide Allelic Imbalance in Osteoarthritic Cartilage

OBJECTIVE

Multiple single-nucleotide polymorphisms (SNPs) conferring susceptibility to osteoarthritis (OA) mark imbalanced expression of positional genes in articular cartilage, reflected by unequally expressed alleles among heterozygotes (allelic imbalance [AI]). We undertook this study to explore the articular cartilage transcriptome from OA patients for AI events to identify putative disease-driving genetic variation.

METHODS

AI was assessed in 42 preserved and 5 lesioned OA cartilage samples (from the Research Arthritis and Articular Cartilage study) for which RNA sequencing data were available. The count fraction of the alternative alleles among the alternative and reference alleles together (φ) was determined for heterozygous individuals. A meta-analysis was performed to generate a meta-φ and P value for each SNP with a false discovery rate (FDR) correction for multiple comparisons. To further validate AI events, we explored them as a function of multiple additional OA features.

RESULTS

We observed a total of 2,070 SNPs that consistently marked AI of 1,031 unique genes in articular cartilage. Of these genes, 49 were found to be significantly differentially expressed (fold change <0.5 or >2, FDR <0.05) between preserved and paired lesioned cartilage, and 18 had previously been reported to confer susceptibility to OA and/or related phenotypes. Moreover, we identified notable highly significant AI SNPs in the CRLF1, WWP2, and RPS3 genes that were related to multiple OA features.

CONCLUSION

We present a framework and resulting data set for researchers in the OA research field to probe for disease-relevant genetic variation that affects gene expression in pivotal disease-affected tissue. This likely includes putative novel compelling OA risk genes such as CRLF1, WWP2, and RPS3.

RNA sequencing data integration reveals an miRNA interactome of osteoarthritis cartilage

Objective

To uncover the microRNA (miRNA) interactome of the osteoarthritis (OA) pathophysiological process in the cartilage.

Methods

We performed RNA sequencing in 130 samples (n=35 and n=30 pairs for messenger RNA (mRNA) and miRNA, respectively) on macroscopically preserved and lesioned OA cartilage from the same patient and performed differential expression (DE) analysis of miRNA and mRNAs. To build an OA-specific miRNA interactome, a prioritisation scheme was applied based on inverse Pearson’s correlations and inverse DE of miRNAs and mRNAs. Subsequently, these were filtered by those present in predicted (TargetScan/microT-CDS) and/or experimentally validated (miRTarBase/TarBase) public databases. Pathway enrichment analysis was applied to elucidate OA-related pathways likely mediated by miRNA regulatory mechanisms.

Results

We found 142 miRNAs and 2387 mRNAs to be differentially expressed between lesioned and preserved OA articular cartilage. After applying prioritisation towards likely miRNA-mRNA targets, a regulatory network of 62 miRNAs targeting 238 mRNAs was created. Subsequent pathway enrichment analysis of these mRNAs (or genes) elucidated that genes within the ‘nervous system development’ are likely mediated by miRNA regulatory mechanisms (familywise error=8.4×10⁻⁵). Herein NTF3 encodes neurotrophin-3, which controls survival and differentiation of neurons and which is closely related to the nerve growth factor.

Conclusions

By an integrated approach of miRNA and mRNA sequencing data of OA cartilage, an OA miRNA interactome and related pathways were elucidated. Our functional data demonstrated interacting levels at which miRNA affects expression of genes in the cartilage and exemplified the complexity of functionally validating a network of genes that may be targeted by multiple miRNAs.

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.

Aberrant Calreticulin Expression in Articular Cartilage of Dio2 Deficient Mice

OBJECTIVE

To identify intrinsic differences in cartilage gene expression profiles between wild-type- and Dio2-/--mice, as a mechanism to investigate factors that contribute to prolonged healthy tissue homeostasis.

METHODS

Previously generated microarray-data (Illumina MouseWG-6 v2) of knee cartilage of wild-type and Dio2 -/- -mice were re-analyzed to identify differential expressed genes independent of mechanical loading conditions by forced treadmill-running. RT-qPCR and western blot analyses of overexpression and knockdown of Calr in mouse chondro-progenitor cells (ATDC5) were applied to assess the direct effect of differential Calr expression on cartilage deposition.

RESULTS

Differential expression analyses of articular cartilage of Dio2-/- (N = 9) and wild-type-mice (N = 11) while applying a cutoff threshold (P < 0.05 (FDR) and FC > |1,5|) resulted in 1 probe located in Calreticulin (Calr) that was found significantly downregulated in Dio2-/- mice (FC = -1.731; P = 0.044). Furthermore, overexpression of Calr during early chondrogenesis in ATDC5 cells leads to decreased proteoglycan deposition and corresponding lower Aggrecan expression, whereas knocking down Calr expression does not lead to histological differences of matrix composition.

CONCLUSION

We here demonstrate that the beneficial homeostatic state of articular cartilage in Dio2-/- mice is accompanied with significant lower expression of Calr. Functional analyses further showed that upregulation of Calr expression could act as an initiator of cartilage destruction. The consistent association between Calr and Dio2 expression suggests that enhanced expression of these genes facilitate detrimental effects on cartilage integrity.

The effect of forced exercise on knee joints in Dio2(-/-) mice: type II iodothyronine deiodinase-deficient mice are less prone to develop OA-like cartilage damage upon excessive mechanical stress

OBJECTIVE

To further explore deiodinase iodothyronine type 2 (DIO2) as a therapeutic target in osteoarthritis (OA) by studying the effects of forced mechanical loading on in vivo joint cartilage tissue homeostasis and the modulating effect herein of Dio2 deficiency.

METHODS

Wild-type and C57BL/6-Dio2(-/-) -mice were subjected to a forced running regime for 1 h per day for 3 weeks. Severity of OA was assessed by histological scoring for cartilage damage and synovitis. Genome-wide gene expression was determined in knee cartilage by microarray analysis (Illumina MouseWG-6 v2). STRING-db analyses were applied to determine enrichment for specific pathways and to visualise protein-protein interactions.

RESULTS

In total, 158 probes representing 147 unique genes showed significantly differential expression with a fold-change ≥1.5 upon forced exercise. Among these are genes known for their association with OA (eg, Mef2c, Egfr, Ctgf, Prg4 and Ctnnb1), supporting the use of forced running as an OA model in mice. Dio2-deficient mice showed significantly less cartilage damage and signs of synovitis. Gene expression response upon exercise between wild-type and knockout mice was significantly different for 29 genes.

CONCLUSIONS

Mice subjected to a running regime have significant increased cartilage damage and synovitis scores. Lack of Dio2 protected against cartilage damage in this model and was reflected in a specific gene expression profile, and either mark a favourable effect in the Dio2 knockout (eg, Gnas) or an unfavourable effect in wild-type cartilage homeostasis (eg, Hmbg2 and Calr). These data further support DIO2 activity as a therapeutic target in OA.

Detecting dispersed duplications in high-throughput sequencing data using a database-free approach

MOTIVATION

Dispersed duplications (DDs) such as transposon element insertions and copy number variations are ubiquitous in the human genome. They have attracted the interest of biologists as well as medical researchers due to their role in both evolution and disease. The efforts of discovering DDs in high-throughput sequencing data are currently dominated by database-oriented approaches that require pre-existing knowledge of the DD elements to be detected.

RESULTS

We present DD_DETECTION, a database-free approach to finding DD events in high-throughput sequencing data. DD_DETECTION is able to detect DDs purely from paired-end read alignments. We show in a comparative study that this method is able to compete with database-oriented approaches in recovering validated transposon insertion events. We also experimentally validate the predictions of DD_DETECTION on a human DNA sample, showing that it can find not only duplicated elements present in common databases but also DDs of novel type.

AVAILABILITY AND IMPLEMENTATION

The software presented in this article is open source and available from https://bitbucket.org/mkroon/dd_detection.

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.

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.

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.

High Microsatellite and SNP Genotyping Success Rates Established in a Large Number of Genomic DNA Samples Extracted From Mouth Swabs and Genotypes

In this article, we present the genomic DNA yield and the microsatellite and single nucleotide polymorphism (SNP) genotyping success rates of genomic DNA extracted from a large number of mouth swab samples. In total, the median yield and quality was determined in 714 individuals and the success rates in 378,480 genotypings of 915 individuals. The median yield of genomic DNA per mouth swab was 4.1 μg (range 0.1–42.2 μg) and was not reduced when mouth swabs were stored for at least 21 months prior to extraction. A maximum of 20 mouth swabs is collected per participant. Mouth swab samples showed in, respectively, 89% for 390 microsatellites and 99% for 24 SNPs a genotyping success rate higher than 75%. A very low success rate of genotyping (0%–10%) was obtained for 3.2% of the 915 mouth swab samples using microsatellite markers. Only 0.005% of the mouth swab samples showed a geno-typing success rate lower than 75% (range 58%–71%) using SNPs. Our results show that mouth swabs can be easily collected, stored by our conditions for months prior to DNA extraction and result in high yield and high-quality DNA appropriate for genotyping with high success rate including whole genome searches using microsatellites or SNPs.

Genome-wide association study identifies a single major locus contributing to survival into old age; the APOE locus revisited

By studying the loci that contribute to human longevity, we aim to identify mechanisms that contribute to healthy aging. To identify such loci, we performed a genome-wide association study (GWAS) comparing 403 unrelated nonagenarians from long-living families included in the Leiden Longevity Study (LLS) and 1670 younger population controls. The strongest candidate SNPs from this GWAS have been analyzed in a meta-analysis of nonagenarian cases from the Rotterdam Study, Leiden 85-plus study, and Danish 1905 cohort. Only one of the 62 prioritized SNPs from the GWAS analysis (P < 1 × 10⁻⁴) showed genome-wide significance with survival into old age in the meta-analysis of 4149 nonagenarian cases and 7582 younger controls [OR = 0.71 (95% CI 0.65–0.77), P = 3.39 × 10⁻¹⁷]. This SNP, rs2075650, is located in TOMM40 at chromosome 19q13.32 close to the apolipoprotein E (APOE) gene. Although there was only moderate linkage disequilibrium between rs2075650 and the ApoE ε4 defining SNP rs429358, we could not find an APOE-independent effect of rs2075650 on longevity, either in cross-sectional or in longitudinal analyses. As expected, rs429358 associated with metabolic phenotypes in the offspring of the nonagenarian cases from the LLS and their partners. In addition, we observed a novel association between this locus and serum levels of IGF-1 in women (P = 0.005). In conclusion, the major locus determining familial longevity up to high age as detected by GWAS was marked by rs2075650, which tags the deleterious effects of the ApoE ε4 allele. No other major longevity locus was found.

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.

Interleukin-1 gene cluster variants with innate cytokine production profiles and osteoarthritis in subjects from the Genetics, Osteoarthritis and Progression Study

OBJECTIVE

To assess whether genetic variation in the interleukin-1 (IL-1) gene cluster contributes to familial osteoarthritis (OA) by influencing innate ex vivo production of IL-1beta or IL-1 receptor antagonist (IL-1Ra).

METHODS

Innate ex vivo IL-1beta and IL-1Ra production upon lipopolysaccharide (LPS) stimulation of whole blood cells was measured in subjects from the Genetics, Osteoarthritis and Progression (GARP) Study, which includes sibling pairs in which at least one sibling has symptomatic OA at multiple sites. Radiographic OA (ROA) was assessed by Kellgren/Lawrence score. Subjects from the GARP Study and controls from the Rotterdam Study were genotyped for 7 single-nucleotide polymorphisms (SNPs) encompassing the IL-1 gene cluster on chromosome 2q13. Linkage disequilibrium analysis and genotype and haplotype association analysis were performed to assess the relationship between the IL-1 gene cluster SNPs, innate ex vivo cytokine production, and OA.

RESULTS

Among subjects in the GARP Study, the haplotype variable-number tandem repeat in intron 2/T+8006C/T+11100C 2/2/1 of the IL1RN gene was significantly associated with reduced innate ex vivo bioavailability of IL-1beta upon LPS stimulation (P = 0.026) and with ROA at the highest number of joint locations.

CONCLUSION

These results show that genetic variation at the IL-1 gene cluster is associated with lower IL-1beta bioavailability and with OA at a large number of joint locations. The data further indicate that, among subjects with OA affecting the highest number of joints, the innate immune system may be activated, thereby obscuring possible underlying mechanisms.

Identification of DIO2 as a new susceptibility locus for symptomatic osteoarthritis

Osteoarthritis [MIM 165720] is a common late-onset articular joint disease for which no pharmaceutical intervention is available to attenuate the cartilage degeneration. To identify a new osteoarthritis susceptibility locus, a genome-wide linkage scan and combined linkage association analysis were applied to 179 affected siblings and four trios with generalized osteoarthritis (The GARP study). We tested, for confirmation by association, 1478 subjects who required joint replacement and 734 controls in a UK population. Additional replication was tested in 1582 population-based females from the Rotterdam study that contained 94 cases with defined hip osteoarthritis and in 267 Japanese females with symptomatic hip osteoarthritis and 465 controls. Suggested evidence for linkage in the GARP study was observed on chromosome 14q32.11 (log of odds = 3.03, P = 1.9 x 10(-4)). Genotyping tagging single-nucleotide polymorphisms covering three important candidate genes revealed a common coding variant (rs225014; Thr92Ala) in the iodothyronine-deiodinase enzyme type 2 (D2) gene (DIO2 [MIM 601413]) which significantly explained the linkage signal (P = 0.006). Confirmation and replication by association in the additional osteoarthritis studies indicated a common DIO2 haplotype, exclusively containing the minor allele of rs225014 and common allele of rs12885300, with a combined recessive odds ratio of 1.79, 95% confidence interval (CI) 1.37-2.34 with P = 2.02 x 10(-5) in female cases with advanced/symptomatic hip osteoarthritis. The gene product of this DIO2 converts intracellular pro-hormone-3,3',5,5'-tetraiodothyronine (T4) into the active thyroid hormone 3,3',5-triiodothyronine (T3) thereby regulating intracellular levels of active T3 in target tissues such as the growth plate. Our results indicate a new susceptibility gene (DIO2) conferring risk to osteoarthritis.

Family Based Association Analyses between the Serotonin Transporter Gene Polymorphism (5-HTTLPR) and Neuroticism, Anxiety and Depression

We studied the association between the short/long promotor-based length polymorphism of the serotonin transporter gene (5-HTTLPR) and neuroticism, anxiety and depression. Subjects included twins, their siblings and parents from the Netherlands Twin Register (559 parents and 1,245 offspring). Subjects had participated between one and five times in a survey study measuring neuroticism, anxiety and depression. Offspring of these families were also approached to participate in a psychiatric interview diagnosing DSM-IV major depression. Within-family and total association between 5-HTTLPR and these traits were tested. Only three of the 36 tests showed a significant effect of 5-HTTLPR (P<0.05). These effects were in opposite directions, i.e. both negative and positive regression coefficients were found for the s allele. No additive effect of the s allele was found for DSM-IV depression. Our results strongly suggest that there is no straightforward association between 5-HTTLPR and neuroticism, anxiety and depression.

High microsatellite and SNP genotyping success rates established in a large number of genomic DNA samples extracted from mouth swabs and genotypes

In this article, we present the genomic DNA yield and the microsatellite and single nucleotide polymorphism (SNP) genotyping success rates of genomic DNA extracted from a large number of mouth swab samples. In total, the median yield and quality was determined in 714 individuals and the success rates in 378,480 genotypings of 915 individuals. The median yield of genomic DNA per mouth swab was 4.1 microg (range 0.1-42.2 microg) and was not reduced when mouth swabs were stored for at least 21 months prior to extraction. A maximum of 20 mouth swabs is collected per participant. Mouth swab samples showed in, respectively, 89% for 390 microsatellites and 99% for 24 SNPs a genotyping success rate higher than 75%. A very low success rate of genotyping (0%-10%) was obtained for 3.2% of the 915 mouth swab samples using microsatellite markers. Only 0.005% of the mouth swab samples showed a genotyping success rate lower than 75% (range 58%-71%) using SNPs. Our results show that mouth swabs can be easily collected, stored by our conditions for months prior to DNA extraction and result in high yield and high-quality DNA appropriate for genotyping with high success rate including whole genome searches using microsatellites or SNPs.

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.

Combined association and linkage analysis applied to the APOE locus

Combined association and linkage analysis is a powerful tool for pinpointing functional quantitative traits (QTLs) responsible for regions of significant linkage identified in genome-wide scans. We applied this technique to apoE plasma levels and the APOEepsilon2/epsilon3/epsilon4 polymorphism in two Dutch twin cohorts of different age ranges. Across chromosome 19, short tandem repeats and the APOEepsilon2/epsilon3/epsilon4 polymorphism were genotyped in adolescent (aged 13-22 years) and adult (aged 34-62 years) Dutch twins. In both samples, evidence for indicative linkage with plasma apoE levels was found (maximum LOD score (MLS)=0.8, MLS=2.5, respectively) at 19q13.32. These linkage regions included the APOE locus. As expected, the APOEepsilon2/epsilon3/epsilon4 polymorphism was strongly associated with apoE plasma levels in both samples. An extension of the between/within families association test developed by Fulker et al. ([1999] Am. J. Hum. Genet. 64:259-267) showed that these associations were not due to population stratification. The combined association and linkage analyses revealed that the association of the APOEepsilon2/epsilon3/epsilon4 polymorphism with apoE plasma levels completely explained the linkage in the adolescent twins and partly in the adult twins.

Evidence for a QTL on chromosome 19 influencing LDL cholesterol levels in the general population

The genetic basis of cardiovascular disease (CVD) with its complex etiology is still largely elusive. Plasma levels of lipids and apolipoproteins are among the major quantitative risk factors for CVD and are well-established intermediate traits that may be more accessible to genetic dissection than clinical CVD end points. Chromosome 19 harbors multiple genes that have been suggested to play a role in lipid metabolism and previous studies indicated the presence of a quantitative trait locus (QTL) for cholesterol levels in genetic isolates. To establish the relevance of genetic variation at chromosome 19 for plasma levels of lipids and apolipoproteins in the general, out-bred Caucasian population, we performed a linkage study in four independent samples, including adolescent Dutch twins and adult Dutch, Swedish and Australian twins totaling 493 dizygotic twin pairs. The average spacing of short-tandem-repeat markers was 6-8 cM. In the three adult twin samples, we found consistent evidence for linkage of chromosome 19 with LDL cholesterol levels (maximum LOD scores of 4.5, 1.7 and 2.1 in the Dutch, Swedish and Australian sample, respectively); no indication for linkage was observed in the adolescent Dutch twin sample. The QTL effects in the three adult samples were not significantly different and a simultaneous analysis of the samples increased the maximum LOD score to 5.7 at 60 cM pter. Bivariate analyses indicated that the putative LDL-C QTL also contributed to the variance in ApoB levels, consistent with the high genetic correlation between these phenotypes. Our study provides strong evidence for the presence of a QTL on chromosome 19 with a major effect on LDL-C plasma levels in outbred Caucasian populations.

Two-locus Linkage Analysis Applied to Putative Quantitative Trait Loci for Lipoprotein(a) Levels

Plasma levels of lipoprotein(a) - Lp(a) - are associated with cardiovascular risk (Danesh et al., 2000) and were long believed to be influenced by the LPA locus on chromosome 6q27 only. However, a recent report of Broeckel et al. (2002) suggested the presence of a second quantitative trait locus on chromosome 1 influencing Lp(a) levels. Using a two-locus model, we found no evidence for an additional Lp(a) locus on chromosome 1 in a linkage study among 483 dizygotic twin pairs.

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 inter-marker 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 μg of genomic DNA per individual, isolated from either blood or from mouth swabs.