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Roberts JB, Rice SJ. Osteoarthritis as an Enhanceropathy: Gene Regulation in Complex Musculoskeletal Disease. Curr Rheumatol Rep 2024; 26:222-234. [PMID: 38430365 PMCID: PMC11116181 DOI: 10.1007/s11926-024-01142-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/07/2024] [Indexed: 03/03/2024]
Abstract
PURPOSE OF REVIEW Osteoarthritis is a complex and highly polygenic disease. Over 100 reported osteoarthritis risk variants fall in non-coding regions of the genome, ostensibly conferring functional effects through the disruption of regulatory elements impacting target gene expression. In this review, we summarise the progress that has advanced our knowledge of gene enhancers both within the field of osteoarthritis and more broadly in complex diseases. RECENT FINDINGS Advances in technologies such as ATAC-seq have facilitated our understanding of chromatin states in specific cell types, bolstering the interpretation of GWAS and the identification of effector genes. Their application to osteoarthritis research has revealed enhancers as the principal regulatory element driving disease-associated changes in gene expression. However, tissue-specific effects in gene regulatory mechanisms can contribute added complexity to biological interpretation. Understanding gene enhancers and their altered activity in specific cell and tissue types is the key to unlocking the genetic complexity of osteoarthritis. The use of single-cell technologies in osteoarthritis research is still in its infancy. However, such tools offer great promise in improving our functional interpretation of osteoarthritis GWAS and the identification of druggable targets. Large-scale collaborative efforts will be imperative to understand tissue and cell-type specific molecular mechanisms underlying enhancer function in disease.
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Affiliation(s)
- Jack B Roberts
- Skeletal Research Group, International Centre for Life, Biosciences Institute, Newcastle University, Newcastle Upon Tyne, NE1 3BZ, UK
| | - Sarah J Rice
- Skeletal Research Group, International Centre for Life, Biosciences Institute, Newcastle University, Newcastle Upon Tyne, NE1 3BZ, UK.
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McKay L, Petrelli B, Pind M, Reynolds JN, Wintle RF, Chudley AE, Drögemöller B, Fainsod A, Scherer SW, Hanlon-Dearman A, Hicks GG. Risk and Resilience Variants in the Retinoic Acid Metabolic and Developmental Pathways Associated with Risk of FASD Outcomes. Biomolecules 2024; 14:569. [PMID: 38785976 PMCID: PMC11117505 DOI: 10.3390/biom14050569] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Revised: 05/01/2024] [Accepted: 05/07/2024] [Indexed: 05/25/2024] Open
Abstract
Fetal Alcohol Spectrum Disorder (FASD) is a common neurodevelopmental disorder that affects an estimated 2-5% of North Americans. FASD is induced by prenatal alcohol exposure (PAE) during pregnancy and while there is a clear genetic contribution, few genetic factors are currently identified or understood. In this study, using a candidate gene approach, we performed a genetic variant analysis of retinoic acid (RA) metabolic and developmental signaling pathway genes on whole exome sequencing data of 23 FASD-diagnosed individuals. We found risk and resilience alleles in ADH and ALDH genes known to normally be involved in alcohol detoxification at the expense of RA production, causing RA deficiency, following PAE. Risk and resilience variants were also identified in RA-regulated developmental pathway genes, especially in SHH and WNT pathways. Notably, we also identified significant variants in the causative genes of rare neurodevelopmental disorders sharing comorbidities with FASD, including STRA6 (Matthew-Wood), SOX9 (Campomelic Dysplasia), FDG1 (Aarskog), and 22q11.2 deletion syndrome (TBX1). Although this is a small exploratory study, the findings support PAE-induced RA deficiency as a major etiology underlying FASD and suggest risk and resilience variants may be suitable biomarkers to determine the risk of FASD outcomes following PAE.
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Affiliation(s)
- Leo McKay
- Department of Biochemistry & Medical Genetics, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB R3E 0J9, Canada
| | - Berardino Petrelli
- Department of Biochemistry & Medical Genetics, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB R3E 0J9, Canada
| | - Molly Pind
- Department of Biochemistry & Medical Genetics, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB R3E 0J9, Canada
| | - James N. Reynolds
- Department of Biomedical and Molecular Sciences, Queen’s University, Kingston, ON K7L 2V7, Canada
| | - Richard F. Wintle
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Albert E. Chudley
- Department of Biochemistry & Medical Genetics, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB R3E 0J9, Canada
- Department of Pediatrics and Child Health, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB R3A 1S1, Canada
| | - Britt Drögemöller
- Department of Biochemistry & Medical Genetics, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB R3E 0J9, Canada
- Paul Albrechtsen Research Institute CancerCare Manitoba, Winnipeg, MB R3E 0V9, Canada
- Children’s Hospital Research Institute of Manitoba, Winnipeg, MB R3E 3P4, Canada
- Centre on Aging, University of Manitoba, Winnipeg, MB R3T 2N2, Canada
| | - Abraham Fainsod
- Department of Developmental Biology and Cancer Research, Institute for Medical Research Israel-Canada, Faculty of Medicine, The Hebrew University of Jerusalem, P.O. Box 12271, Jerusalem 9112102, Israel
| | - Stephen W. Scherer
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
- Department of Molecular Genetics and McLaughlin Centre, University of Toronto, Toronto, ON M5G 1L7, Canada
- Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Ana Hanlon-Dearman
- Department of Pediatrics and Child Health, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB R3A 1S1, Canada
| | - Geoffrey G. Hicks
- Department of Biochemistry & Medical Genetics, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB R3E 0J9, Canada
- Paul Albrechtsen Research Institute CancerCare Manitoba, Winnipeg, MB R3E 0V9, Canada
- Children’s Hospital Research Institute of Manitoba, Winnipeg, MB R3E 3P4, Canada
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Korthagen NM, Houtman E, Boone I, Coutinho de Almeida R, Sivasubramaniyan K, Mahdad R, Nelissen RGHH, Ramos YFM, Tessari MA, Meulenbelt I. Thyroid hormone induces ossification and terminal maturation in a preserved OA cartilage biomimetic model. Arthritis Res Ther 2024; 26:91. [PMID: 38664820 PMCID: PMC11044551 DOI: 10.1186/s13075-024-03326-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2023] [Accepted: 04/21/2024] [Indexed: 04/29/2024] Open
Abstract
OBJECTIVE To characterize aspects of triiodothyronine (T3) induced chondrocyte terminal maturation within the molecular osteoarthritis pathophysiology using the previously established T3 human ex vivo osteochondral explant model. DESIGNS RNA-sequencing was performed on explant cartilage obtained from OA patients (n = 8), that was cultured ex vivo with or without T3 (10 ng/ml), and main findings were validated using RT-qPCR in an independent sample set (n = 22). Enrichment analysis was used for functional clustering and comparisons with available OA patient RNA-sequencing and GWAS datasets were used to establish relevance for OA pathophysiology by linking to OA patient genomic profiles. RESULTS Besides the upregulation of known hypertrophic genes EPAS1 and ANKH, T3 treatment resulted in differential expression of 247 genes with main pathways linked to extracellular matrix and ossification. CCDC80, CDON, ANKH and ATOH8 were among the genes found to consistently mark early, ongoing and terminal maturational OA processes in patients. Furthermore, among the 37 OA risk genes that were significantly affected in cartilage by T3 were COL12A1, TNC, SPARC and PAPPA. CONCLUSIONS RNA-sequencing results show that metabolic activation and recuperation of growth plate morphology are induced by T3 in OA chondrocytes, indicating terminal maturation is accelerated. The molecular mechanisms involved in hypertrophy were linked to all stages of OA pathophysiology and will be used to validate disease models for drug testing.
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Affiliation(s)
- N M Korthagen
- Department Biomedical Data Sciences, Section of Molecular Epidemiology, LUMC, Einthovenweg 20, Postzone S05-P, 2333 ZC, Leiden, The Netherlands
| | - E Houtman
- Department Biomedical Data Sciences, Section of Molecular Epidemiology, LUMC, Einthovenweg 20, Postzone S05-P, 2333 ZC, Leiden, The Netherlands
| | - I Boone
- Department Biomedical Data Sciences, Section of Molecular Epidemiology, LUMC, Einthovenweg 20, Postzone S05-P, 2333 ZC, Leiden, The Netherlands
| | - R Coutinho de Almeida
- Department Biomedical Data Sciences, Section of Molecular Epidemiology, LUMC, Einthovenweg 20, Postzone S05-P, 2333 ZC, Leiden, The Netherlands
| | - K Sivasubramaniyan
- Galapagos BV, Willem Einthovenstraat 13, Oegstgeest, 2342 BH, The Netherlands
| | - R Mahdad
- Alrijne hospital, Simon Smitweg 1, Leiderdorp, 2353 GA, The Netherlands
| | - R G H H Nelissen
- Department Biomedical Data Sciences, Section of Molecular Epidemiology, LUMC, Einthovenweg 20, Postzone S05-P, 2333 ZC, Leiden, The Netherlands
| | - Y F M Ramos
- Department Biomedical Data Sciences, Section of Molecular Epidemiology, LUMC, Einthovenweg 20, Postzone S05-P, 2333 ZC, Leiden, The Netherlands
| | - M A Tessari
- Galapagos BV, Willem Einthovenstraat 13, Oegstgeest, 2342 BH, The Netherlands
| | - I Meulenbelt
- Department Biomedical Data Sciences, Section of Molecular Epidemiology, LUMC, Einthovenweg 20, Postzone S05-P, 2333 ZC, Leiden, The Netherlands.
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Roberts JB, Boldvig OLG, Aubourg G, Kanchenapally ST, Deehan DJ, Rice SJ, Loughlin J. Specific isoforms of the ubiquitin ligase gene WWP2 are targets of osteoarthritis genetic risk via a differentially methylated DNA sequence. Arthritis Res Ther 2024; 26:78. [PMID: 38570801 PMCID: PMC10988806 DOI: 10.1186/s13075-024-03315-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Accepted: 03/21/2024] [Indexed: 04/05/2024] Open
Abstract
BACKGROUND Transitioning from a genetic association signal to an effector gene and a targetable molecular mechanism requires the application of functional fine-mapping tools such as reporter assays and genome editing. In this report, we undertook such studies on the osteoarthritis (OA) risk that is marked by single nucleotide polymorphism (SNP) rs34195470 (A > G). The OA risk-conferring G allele of this SNP associates with increased DNA methylation (DNAm) at two CpG dinucleotides within WWP2. This gene encodes a ubiquitin ligase and is the host gene of microRNA-140 (miR-140). WWP2 and miR-140 are both regulators of TGFβ signaling. METHODS Nucleic acids were extracted from adult OA (arthroplasty) and foetal cartilage. Samples were genotyped and DNAm quantified by pyrosequencing at the two CpGs plus 14 flanking CpGs. CpGs were tested for transcriptional regulatory effects using a chondrocyte cell line and reporter gene assay. DNAm was altered using epigenetic editing, with the impact on gene expression determined using RT-qPCR. In silico analysis complemented laboratory experiments. RESULTS rs34195470 genotype associates with differential methylation at 14 of the 16 CpGs in OA cartilage, forming a methylation quantitative trait locus (mQTL). The mQTL is less pronounced in foetal cartilage (5/16 CpGs). The reporter assay revealed that the CpGs reside within a transcriptional regulator. Epigenetic editing to increase their DNAm resulted in altered expression of the full-length and N-terminal transcript isoforms of WWP2. No changes in expression were observed for the C-terminal isoform of WWP2 or for miR-140. CONCLUSIONS As far as we are aware, this is the first experimental demonstration of an OA association signal targeting specific transcript isoforms of a gene. The WWP2 isoforms encode proteins with varying substrate specificities for the components of the TGFβ signaling pathway. Future analysis should focus on the substrates regulated by the two WWP2 isoforms that are the targets of this genetic risk.
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Affiliation(s)
- Jack B Roberts
- Biosciences Institute, Newcastle University, International Centre for Life, Newcastle upon Tyne, NE1 3BZ, UK.
| | - Olivia L G Boldvig
- Biosciences Institute, Newcastle University, International Centre for Life, Newcastle upon Tyne, NE1 3BZ, UK
| | - Guillaume Aubourg
- Biosciences Institute, Newcastle University, International Centre for Life, Newcastle upon Tyne, NE1 3BZ, UK
| | - S Tanishq Kanchenapally
- Biosciences Institute, Newcastle University, International Centre for Life, Newcastle upon Tyne, NE1 3BZ, UK
| | - David J Deehan
- Freeman Hospital, Newcastle University Teaching Hospitals NHS Trust, Newcastle upon Tyne, UK
| | - Sarah J Rice
- Biosciences Institute, Newcastle University, International Centre for Life, Newcastle upon Tyne, NE1 3BZ, UK
| | - John Loughlin
- Biosciences Institute, Newcastle University, International Centre for Life, Newcastle upon Tyne, NE1 3BZ, UK.
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You S, Xu J, Guo Y, Guo X, Zhang Y, Zhang N, Sun G, Sun Y. E3 ubiquitin ligase WWP2 as a promising therapeutic target for diverse human diseases. Mol Aspects Med 2024; 96:101257. [PMID: 38430667 DOI: 10.1016/j.mam.2024.101257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2023] [Revised: 02/05/2024] [Accepted: 02/13/2024] [Indexed: 03/05/2024]
Abstract
Mammalian E3 ubiquitin ligases have emerged in recent years as critical regulators of cellular homeostasis due to their roles in targeting substrate proteins for ubiquitination and triggering subsequent downstream signals. In this review, we describe the multiple roles of WWP2, an E3 ubiquitin ligase with unique and important functions in regulating a wide range of biological processes, including DNA repair, gene expression, signal transduction, and cell-fate decisions. As such, WWP2 has evolved to play a key role in normal physiology and diseases, such as tumorigenesis, skeletal development and diseases, immune regulation, cardiovascular disease, and others. We attempt to provide an overview of the biochemical, physiological, and pathophysiological roles of WWP2, as well as open questions for future research, particularly in the context of putative therapeutic opportunities.
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Affiliation(s)
- Shilong You
- Department of Cardiology, First Hospital of China Medical University, Shenyang, Liaoning, China
| | - Jiaqi Xu
- Department of Cardiology, First Hospital of China Medical University, Shenyang, Liaoning, China
| | - Yushan Guo
- Department of Cardiology, First Hospital of China Medical University, Shenyang, Liaoning, China
| | - Xiaofan Guo
- Department of Cardiology, First Hospital of China Medical University, Shenyang, Liaoning, China
| | - Ying Zhang
- Department of Cardiology, First Hospital of China Medical University, Shenyang, Liaoning, China; Institute of Health Sciences, China Medical University, Shenyang, Liaoning, China.
| | - Naijin Zhang
- Department of Cardiology, First Hospital of China Medical University, Shenyang, Liaoning, China; Institute of Health Sciences, China Medical University, Shenyang, Liaoning, China; NHC Key Laboratory of Advanced Reproductive Medicine and Fertility, National Health Commission, China Medical University, Shenyang, Liaoning, China.
| | - Guozhe Sun
- Department of Cardiology, First Hospital of China Medical University, Shenyang, Liaoning, China.
| | - Yingxian Sun
- Department of Cardiology, First Hospital of China Medical University, Shenyang, Liaoning, China; Institute of Health Sciences, China Medical University, Shenyang, Liaoning, China.
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Wang Y, Wu Z, Wang C, Wu N, Wang C, Hu S, Shi J. The role of WWP1 and WWP2 in bone/cartilage development and diseases. Mol Cell Biochem 2024:10.1007/s11010-023-04917-7. [PMID: 38252355 DOI: 10.1007/s11010-023-04917-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Accepted: 12/11/2023] [Indexed: 01/23/2024]
Abstract
Bone and cartilage diseases are often associated with trauma and senescence, manifested as pain and limited mobility. The repair of bone and cartilage lesion by mesenchymal stem cells is regulated by various transcription factors. WW domain-containing protein 1 (WWP1) and WW domain-containing protein 2 (WWP2) are named for WW domain which recognizes PPXY (phono Ser Pro and Pro Arg) motifs of substrate. WWP1and WWP2 are prominent components of the homologous to the E6-AP carboxyl terminus (HECT) subfamily, a group of the ubiquitin ligase. Recently, some studies have found that WWP1 and WWP2 play an important role in the pathogenesis of bone and cartilage diseases and regulate the level and the transactivation of various transcription factors through ubiquitination. Therefore, this review summarizes the distribution and effects of WWP1 and WWP2 in the development of bone and cartilage, discusses the potential mechanism and therapeutic drugs in bone and cartilage diseases such as osteoarthritis, fracture, and osteoporosis.
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Affiliation(s)
- Ying Wang
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Clinical Research Center for Oral Diseases of Zhejiang Province, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, 310016, China
| | - Zuping Wu
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Clinical Research Center for Oral Diseases of Zhejiang Province, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, 310016, China
| | - Cunyi Wang
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Clinical Research Center for Oral Diseases of Zhejiang Province, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, 310016, China
| | - Na Wu
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Clinical Research Center for Oral Diseases of Zhejiang Province, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, 310016, China
| | - Chenyu Wang
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Clinical Research Center for Oral Diseases of Zhejiang Province, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, 310016, China
| | - Shiyu Hu
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Clinical Research Center for Oral Diseases of Zhejiang Province, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, 310016, China
| | - Jiejun Shi
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Clinical Research Center for Oral Diseases of Zhejiang Province, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, 310016, China.
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Kehayova YS, Wilkinson JM, Rice SJ, Loughlin J. Mediation of the Same Epigenetic and Transcriptional Effect by Independent Osteoarthritis Risk-Conferring Alleles on a Shared Target Gene, COLGALT2. Arthritis Rheumatol 2023; 75:910-922. [PMID: 36538011 PMCID: PMC10952352 DOI: 10.1002/art.42427] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 11/14/2022] [Accepted: 12/15/2022] [Indexed: 12/24/2022]
Abstract
OBJECTIVE Over 100 DNA variants have been associated with osteoarthritis (OA), including rs1046934, located within a linkage disequilibrium block encompassing part of COLGALT2 and TSEN15. The present study was undertaken to determine the target gene(s) and the mechanism of action of the OA locus using human fetal cartilage, cartilage from OA and femoral neck fracture arthroplasty patients, and a chondrocyte cell model. METHODS Genotyping and methylation array data of DNA from human OA cartilage samples (n = 87) were used to determine whether the rs1046934 genotype is associated with differential DNA methylation at proximal CpGs. Results were replicated in DNA from human arthroplasty (n = 132) and fetal (n = 77) cartilage samples using pyrosequencing. Allelic expression imbalance (AEI) measured the effects of genotype on COLGALT2 and TSEN15 expression. Reporter gene assays and epigenetic editing determined the functional role of regions harboring differentially methylated CpGs. In silico analyses complemented these experiments. RESULTS Three differentially methylated CpGs residing within regulatory regions were detected in the human OA cartilage array data, and 2 of these were replicated in human arthroplasty and fetal cartilage. AEI was detected for COLGALT2 and TSEN15, with associations between expression and methylation for COLGALT2. Reporter gene assays confirmed that the CpGs are in chondrocyte enhancers, with epigenetic editing results directly linking methylation with COLGALT2 expression. CONCLUSION COLGALT2 is a target of this OA locus. We previously characterized another OA locus, marked by rs11583641, that independently targets COLGALT2. The genotype of rs1046934, like rs11583641, mediates its effect by modulating expression of COLGALT2 via methylation changes to CpGs located in enhancers. Although the single-nucleotide polymorphisms, CpGs, and enhancers are distinct between the 2 independent OA risk loci, their effect on COLGALT2 is the same. COLGALT2 is the target of independent OA risk loci sharing a common mechanism of action.
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Affiliation(s)
| | - J. Mark Wilkinson
- Department of Oncology and MetabolismUniversity of SheffieldSheffieldUK
| | - Sarah J. Rice
- Biosciences Institute, Newcastle UniversityNewcastle upon TyneUK
| | - John Loughlin
- Biosciences Institute, Newcastle UniversityNewcastle upon TyneUK
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Tuerlings M, Janssen GMC, Boone I, van Hoolwerff M, Rodriguez Ruiz A, Houtman E, Suchiman HED, van der Wal RJP, Nelissen RGHH, Coutinho de Almeida R, van Veelen PA, Ramos YFM, Meulenbelt I. WWP2 confers risk to osteoarthritis by affecting cartilage matrix deposition via hypoxia associated genes. Osteoarthritis Cartilage 2023; 31:39-48. [PMID: 36208715 DOI: 10.1016/j.joca.2022.09.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 09/12/2022] [Accepted: 09/28/2022] [Indexed: 11/06/2022]
Abstract
OBJECTIVE To explore the co-expression network of the osteoarthritis (OA) risk gene WWP2 in articular cartilage and study cartilage characteristics when mimicking the effect of OA risk allele rs1052429-A on WWP2 expression in a human 3D in vitro model of cartilage. METHOD Co-expression behavior of WWP2 with genes expressed in lesioned OA articular cartilage (N = 35 samples) was explored. By applying lentiviral particle mediated WWP2 upregulation in 3D in vitro pellet cultures of human primary chondrocytes (N = 8 donors) the effects of upregulation on cartilage matrix deposition was evaluated. Finally, we transfected primary chondrocytes with miR-140 mimics to evaluate whether miR-140 and WWP2 are involved in similar pathways. RESULTS Upon performing Spearman correlations in lesioned OA cartilage, 98 highly correlating genes (|ρ| > 0.7) were identified. Among these genes, we identified GJA1, GDF10, STC2, WDR1, and WNK4. Subsequent upregulation of WWP2 on 3D chondrocyte pellet cultures resulted in a decreased expression of COL2A1 and ACAN and an increase in EPAS1 expression. Additionally, we observed a decreased expression of GDF10, STC2, and GJA1. Proteomics analysis identified 42 proteins being differentially expressed with WWP2 upregulation, which were enriched for ubiquitin conjugating enzyme activity. Finally, upregulation of miR-140 in 2D chondrocytes resulted in significant upregulation of WWP2 and WDR1. CONCLUSIONS Mimicking the effect of OA risk allele rs1052429-A on WWP2 expression initiates detrimental processes in the cartilage shown by a response in hypoxia associated genes EPAS1, GDF10, and GJA1 and a decrease in anabolic markers, COL2A1 and ACAN.
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Affiliation(s)
- M Tuerlings
- Dept. of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.
| | - G M C Janssen
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, the Netherlands.
| | - I Boone
- Dept. of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.
| | - M van Hoolwerff
- Dept. of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.
| | - A Rodriguez Ruiz
- Dept. of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.
| | - E Houtman
- Dept. of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.
| | - H E D Suchiman
- Dept. of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.
| | - R J P van der Wal
- Dept. Orthopaedics, Leiden University Medical Center, Leiden, the Netherlands.
| | - R G H H Nelissen
- Dept. Orthopaedics, Leiden University Medical Center, Leiden, the Netherlands.
| | - R Coutinho de Almeida
- Dept. of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.
| | - P A van Veelen
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, the Netherlands.
| | - Y F M Ramos
- Dept. of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.
| | - I Meulenbelt
- Dept. of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.
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9
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Coutinho de Almeida R, Tuerlings M, Ramos Y, Den Hollander W, Suchiman E, Lakenberg N, Nelissen RGHH, Mei H, Meulenbelt I. Allelic expression imbalance in articular cartilage and subchondral bone refined genome-wide association signals in osteoarthritis. Rheumatology (Oxford) 2022; 62:1669-1676. [PMID: 36040165 PMCID: PMC10070069 DOI: 10.1093/rheumatology/keac498] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Revised: 08/12/2022] [Accepted: 08/18/2022] [Indexed: 11/14/2022] Open
Abstract
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.
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Affiliation(s)
- Rodrigo Coutinho de Almeida
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Margo Tuerlings
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Yolande Ramos
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Wouter Den Hollander
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Eka Suchiman
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Nico Lakenberg
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Rob G H H Nelissen
- Department of Orthopaedics, Leiden University Medical Center, Leiden, The Netherlands
| | - Hailiang Mei
- Sequencing Analysis Support Core, Dept. of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - Ingrid Meulenbelt
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
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10
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Humphreys PA, Mancini FE, Ferreira MJS, Woods S, Ogene L, Kimber SJ. Developmental principles informing human pluripotent stem cell differentiation to cartilage and bone. Semin Cell Dev Biol 2022; 127:17-36. [PMID: 34949507 DOI: 10.1016/j.semcdb.2021.11.024] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Revised: 11/23/2021] [Accepted: 11/24/2021] [Indexed: 12/14/2022]
Abstract
Human pluripotent stem cells can differentiate into any cell type given appropriate signals and hence have been used to research early human development of many tissues and diseases. Here, we review the major biological factors that regulate cartilage and bone development through the three main routes of neural crest, lateral plate mesoderm and paraxial mesoderm. We examine how these routes have been used in differentiation protocols that replicate skeletal development using human pluripotent stem cells and how these methods have been refined and improved over time. Finally, we discuss how pluripotent stem cells can be employed to understand human skeletal genetic diseases with a developmental origin and phenotype, and how developmental protocols have been applied to gain a better understanding of these conditions.
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Affiliation(s)
- Paul A Humphreys
- Division of Cell Matrix Biology and Regenerative Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, UK; Department of Mechanical, Aerospace and Civil Engineering, School of Engineering, Faculty of Science and Engineering & Henry Royce Institute, University of Manchester, UK
| | - Fabrizio E Mancini
- Division of Cell Matrix Biology and Regenerative Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, UK
| | - Miguel J S Ferreira
- Division of Cell Matrix Biology and Regenerative Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, UK; Department of Mechanical, Aerospace and Civil Engineering, School of Engineering, Faculty of Science and Engineering & Henry Royce Institute, University of Manchester, UK
| | - Steven Woods
- Division of Cell Matrix Biology and Regenerative Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, UK
| | - Leona Ogene
- Division of Cell Matrix Biology and Regenerative Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, UK
| | - Susan J Kimber
- Division of Cell Matrix Biology and Regenerative Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, UK
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11
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Aubourg G, Rice SJ, Bruce-Wootton P, Loughlin J. Genetics of osteoarthritis. Osteoarthritis Cartilage 2022; 30:636-649. [PMID: 33722698 PMCID: PMC9067452 DOI: 10.1016/j.joca.2021.03.002] [Citation(s) in RCA: 55] [Impact Index Per Article: 27.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Revised: 02/17/2021] [Accepted: 03/06/2021] [Indexed: 02/02/2023]
Abstract
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.
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Affiliation(s)
- G Aubourg
- Biosciences Institute, Newcastle University, Newcastle Upon Tyne, UK
| | - S J Rice
- Biosciences Institute, Newcastle University, Newcastle Upon Tyne, UK
| | - P Bruce-Wootton
- Biosciences Institute, Newcastle University, Newcastle Upon Tyne, UK
| | - J Loughlin
- Biosciences Institute, Newcastle University, Newcastle Upon Tyne, UK.
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12
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Ning Y, Hu M, Diao J, Gong Y, Huang R, Chen S, Zhang F, Liu Y, Chen F, Zhang P, Zhao G, Chang Y, Xu K, Zhou R, Li C, Zhang F, Lammi M, Wang X, Guo X. Genetic Variants and Protein Alterations of Selenium- and T-2 Toxin-Responsive Genes Are Associated With Chondrocytic Damage in Endemic Osteoarthropathy. Front Genet 2022; 12:773534. [PMID: 35087566 PMCID: PMC8787141 DOI: 10.3389/fgene.2021.773534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Accepted: 12/16/2021] [Indexed: 11/13/2022] Open
Abstract
The mechanism of environmental factors in Kashin–Beck disease (KBD) remains unknown. We aimed to identify single nucleotide polymorphisms (SNPs) and protein alterations of selenium- and T-2 toxin–responsive genes to provide new evidence of chondrocytic damage in KBD. This study sampled the cubital venous blood of 258 subjects including 129 sex-matched KBD patients and 129 healthy controls for SNP detection. We applied an additive model, a dominant model, and a recessive model to identify significant SNPs. We then used the Comparative Toxicogenomics Database (CTD) to select selenium- and T-2 toxin–responsive genes with the candidate SNP loci. Finally, immunohistochemistry was applied to verify the protein expression of candidate genes in knee cartilage obtained from 15 subjects including 5 KBD, 5 osteoarthritis (OA), and 5 healthy controls. Forty-nine SNPs were genotyped in the current study. The C allele of rs6494629 was less frequent in KBD than in the controls (OR = 0.63, p = 0.011). Based on the CTD database, PPARG, ADAM12, IL6, SMAD3, and TIMP2 were identified to interact with selenium, sodium selenite, and T-2 toxin. KBD was found to be significantly associated with rs12629751 of PPARG (additive model: OR = 0.46, p = 0.012; dominant model: OR = 0.45, p = 0.049; recessive model: OR = 0.18, p = 0.018), rs1871054 of ADAM12 (dominant model: OR = 2.19, p = 0.022), rs1800796 of IL6 (dominant model: OR = 0.30, p = 0.003), rs6494629 of SMAD3 (additive model: OR = 0.65, p = 0.019; dominant model: OR = 0.52, p = 0.012), and rs4789936 of TIMP2 (recessive model: OR = 5.90, p = 0.024). Immunohistochemistry verified significantly upregulated PPARG, ADAM12, SMAD3, and TIMP2 in KBD compared with OA and normal controls (p < 0.05). Genetic polymorphisms of PPARG, ADAM12, SMAD3, and TIMP2 may contribute to the risk of KBD. These genes could promote the pathogenesis of KBD by disturbing ECM homeostasis.
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Affiliation(s)
- Yujie Ning
- Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, National Health Commission of the People's Republic of China, Xi'an, China
| | - Minhan Hu
- Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, National Health Commission of the People's Republic of China, Xi'an, China
| | - Jiayu Diao
- Shaanxi Provincial People's Hospital, Xi'an, China
| | - Yi Gong
- Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, National Health Commission of the People's Republic of China, Xi'an, China
| | - Ruitian Huang
- Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, National Health Commission of the People's Republic of China, Xi'an, China
| | - Sijie Chen
- Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, National Health Commission of the People's Republic of China, Xi'an, China
| | - Feiyu Zhang
- Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, National Health Commission of the People's Republic of China, Xi'an, China
| | - Yanli Liu
- Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, National Health Commission of the People's Republic of China, Xi'an, China
| | - Feihong Chen
- Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, National Health Commission of the People's Republic of China, Xi'an, China
| | - Pan Zhang
- Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, National Health Commission of the People's Republic of China, Xi'an, China
| | | | - Yanhai Chang
- Shaanxi Provincial People's Hospital, Xi'an, China
| | - Ke Xu
- Xi'an Honghui Hospital, Xi'an, China
| | - Rong Zhou
- Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, National Health Commission of the People's Republic of China, Xi'an, China.,Shaanxi Provincial Institute for Endemic Disease Control, Xi'an, China
| | - Cheng Li
- Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, National Health Commission of the People's Republic of China, Xi'an, China.,Shaanxi Provincial Institute for Endemic Disease Control, Xi'an, China
| | - Feng Zhang
- Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, National Health Commission of the People's Republic of China, Xi'an, China
| | - Mikko Lammi
- Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, National Health Commission of the People's Republic of China, Xi'an, China.,Department of Integrative Medical Biology, University of Umeå, Umeå, Sweden
| | - Xi Wang
- Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, National Health Commission of the People's Republic of China, Xi'an, China
| | - Xiong Guo
- Key Laboratory of Trace Elements and Endemic Diseases, School of Public Health, Health Science Center, Xi'an Jiaotong University, National Health Commission of the People's Republic of China, Xi'an, China
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13
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CRLF1 and CLCF1 in Development, Health and Disease. Int J Mol Sci 2022; 23:ijms23020992. [PMID: 35055176 PMCID: PMC8780587 DOI: 10.3390/ijms23020992] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 01/13/2022] [Accepted: 01/14/2022] [Indexed: 12/12/2022] Open
Abstract
Cytokines and their receptors have a vital function in regulating various processes such as immune function, inflammation, haematopoiesis, cell growth and differentiation. The interaction between a cytokine and its specific receptor triggers intracellular signalling cascades that lead to altered gene expression in the target cell and consequent changes in its proliferation, differentiation, or activation. In this review, we highlight the role of the soluble type I cytokine receptor CRLF1 (cytokine receptor-like factor-1) and the Interleukin (IL)-6 cytokine CLCF1 (cardiotrophin-like cytokine factor 1) during development in physiological and pathological conditions with particular emphasis on Crisponi/cold-induced sweating syndrome (CS/CISS) and discuss new insights, challenges and possibilities arising from recent studies.
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14
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Boer CG, Hatzikotoulas K, Southam L, Stefánsdóttir L, Zhang Y, Coutinho de Almeida R, Wu TT, Zheng J, Hartley A, Teder-Laving M, Skogholt AH, Terao C, Zengini E, Alexiadis G, Barysenka A, Bjornsdottir G, Gabrielsen ME, Gilly A, Ingvarsson T, Johnsen MB, Jonsson H, Kloppenburg M, Luetge A, Lund SH, Mägi R, Mangino M, Nelissen RRGHH, Shivakumar M, Steinberg J, Takuwa H, Thomas LF, Tuerlings M, Babis GC, Cheung JPY, Kang JH, Kraft P, Lietman SA, Samartzis D, Slagboom PE, Stefansson K, Thorsteinsdottir U, Tobias JH, Uitterlinden AG, Winsvold B, Zwart JA, Davey Smith G, Sham PC, Thorleifsson G, Gaunt TR, Morris AP, Valdes AM, Tsezou A, Cheah KSE, Ikegawa S, Hveem K, Esko T, Wilkinson JM, Meulenbelt I, Lee MTM, van Meurs JBJ, Styrkársdóttir U, Zeggini E. Deciphering osteoarthritis genetics across 826,690 individuals from 9 populations. Cell 2021; 184:4784-4818.e17. [PMID: 34450027 PMCID: PMC8459317 DOI: 10.1016/j.cell.2021.07.038] [Citation(s) in RCA: 159] [Impact Index Per Article: 53.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Revised: 03/26/2021] [Accepted: 07/30/2021] [Indexed: 12/19/2022]
Abstract
Osteoarthritis affects over 300 million people worldwide. Here, we conduct a genome-wide association study meta-analysis across 826,690 individuals (177,517 with osteoarthritis) and identify 100 independently associated risk variants across 11 osteoarthritis phenotypes, 52 of which have not been associated with the disease before. We report thumb and spine osteoarthritis risk variants and identify differences in genetic effects between weight-bearing and non-weight-bearing joints. We identify sex-specific and early age-at-onset osteoarthritis risk loci. We integrate functional genomics data from primary patient tissues (including articular cartilage, subchondral bone, and osteophytic cartilage) and identify high-confidence effector genes. We provide evidence for genetic correlation with phenotypes related to pain, the main disease symptom, and identify likely causal genes linked to neuronal processes. Our results provide insights into key molecular players in disease processes and highlight attractive drug targets to accelerate translation.
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Affiliation(s)
- Cindy G Boer
- Department of Internal Medicine, Erasmus MC, Medical Center, 3015CN Rotterdam, the Netherlands
| | - Konstantinos Hatzikotoulas
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - Lorraine Southam
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | | | - Yanfei Zhang
- Genomic Medicine Institute, Geisinger Health System, Danville, PA 17822, USA
| | - Rodrigo Coutinho de Almeida
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Postzone S05-P Leiden University Medical Center, 2333ZC Leiden, the Netherlands
| | - Tian T Wu
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong, China
| | - Jie Zheng
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
| | - April Hartley
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK; Musculoskeletal Research Unit, Translation Health Sciences, Bristol Medical School, University of Bristol, Southmead Hospital, Bristol BS10 5NB, UK
| | - Maris Teder-Laving
- Estonian Genome Center, Institute of Genomics, University of Tartu, 51010 Tartu, Estonia
| | - Anne Heidi Skogholt
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, 7491 Trondheim, Norway
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa 230-0045, Japan
| | - Eleni Zengini
- 4(th) Psychiatric Department, Dromokaiteio Psychiatric Hospital, 12461 Athens, Greece
| | - George Alexiadis
- 1(st) Department of Orthopaedics, KAT General Hospital, 14561 Athens, Greece
| | - Andrei Barysenka
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | | | - Maiken E Gabrielsen
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, 7491 Trondheim, Norway
| | - Arthur Gilly
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - Thorvaldur Ingvarsson
- Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland; Department of Orthopedic Surgery, Akureyri Hospital, 600 Akureyri, Iceland
| | - Marianne B Johnsen
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, 7491 Trondheim, Norway; Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, 0316 Oslo, Norway; Research and Communication Unit for Musculoskeletal Health (FORMI), Department of Research, Innovation and Education, Division of Clinical Neuroscience, Oslo University Hospital, 0424 Oslo, Norway
| | - Helgi Jonsson
- Department of Medicine, Landspitali The National University Hospital of Iceland, 108 Reykjavik, Iceland; Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland
| | - Margreet Kloppenburg
- Departments of Rheumatology and Clinical Epidemiology, Leiden University Medical Center, 9600, 23OORC Leiden, the Netherlands
| | - Almut Luetge
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, 7491 Trondheim, Norway
| | | | - Reedik Mägi
- Estonian Genome Center, Institute of Genomics, University of Tartu, 51010 Tartu, Estonia
| | - Massimo Mangino
- Department of Twin Research and Genetic Epidemiology, Kings College London, London SE1 7EH, UK
| | - Rob R G H H Nelissen
- Department of Orthopaedics, Leiden University Medical Center, 9600, 23OORC Leiden, the Netherlands
| | - Manu Shivakumar
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Julia Steinberg
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany; Daffodil Centre, The University of Sydney, a joint venture with Cancer Council NSW, Sydney, NSW 1340, Australia
| | - Hiroshi Takuwa
- Laboratory for Bone and Joint Diseases, RIKEN Center for Integrative Medical Sciences, Tokyo 108-8639, Japan; Department of Orthopedic Surgery, Shimane University, Shimane 693-8501, Japan
| | - Laurent F Thomas
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, 7491 Trondheim, Norway; Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, 7491 Trondheim, Norway; BioCore-Bioinformatics Core Facility, Norwegian University of Science and Technology, 7491 Trondheim, Norway; Clinic of Laboratory Medicine, St. Olavs Hospital, Trondheim University Hospital, 7030 Trondheim, Norway
| | - Margo Tuerlings
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Postzone S05-P Leiden University Medical Center, 2333ZC Leiden, the Netherlands
| | - George C Babis
- 2(nd) Department of Orthopaedics, National and Kapodistrian University of Athens, Medical School, Nea Ionia General Hospital Konstantopouleio, 14233 Athens, Greece
| | - Jason Pui Yin Cheung
- Department of Orthopaedics and Traumatology, The University of Hong Kong, Pokfulam, Hong Kong, China
| | - Jae Hee Kang
- Department of Medicine, Brigham and Women's Hospital, 181 Longwood Ave, Boston, MA 02115, USA
| | - Peter Kraft
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA 02115, USA
| | - Steven A Lietman
- Musculoskeletal Institute, Geisinger Health System, Danville, PA 17822, USA
| | - Dino Samartzis
- Department of Orthopaedics and Traumatology, The University of Hong Kong, Pokfulam, Hong Kong, China; Department of Orthopaedic Surgery, Rush University Medical Center, Chicago, IL 60612, USA
| | - P Eline Slagboom
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Postzone S05-P Leiden University Medical Center, 2333ZC Leiden, the Netherlands
| | - Kari Stefansson
- deCODE Genetics/Amgen Inc., 102 Reykjavik, Iceland; Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland
| | - Unnur Thorsteinsdottir
- deCODE Genetics/Amgen Inc., 102 Reykjavik, Iceland; Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland
| | - Jonathan H Tobias
- Musculoskeletal Research Unit, Translation Health Sciences, Bristol Medical School, University of Bristol, Southmead Hospital, Bristol BS10 5NB, UK; MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
| | - André G Uitterlinden
- Department of Internal Medicine, Erasmus MC, Medical Center, 3015CN Rotterdam, the Netherlands
| | - Bendik Winsvold
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, 7491 Trondheim, Norway; Department of Research, Innovation and Education, Division of Clinical Neuroscience, Oslo University Hospital and University of Oslo, 0450 Oslo, Norway; Department of Neurology, Oslo University Hospital, 0424 Oslo, Norway
| | - John-Anker Zwart
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, 7491 Trondheim, Norway; Department of Research, Innovation and Education, Division of Clinical Neuroscience, Oslo University Hospital and University of Oslo, 0450 Oslo, Norway
| | - George Davey Smith
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK
| | - Pak Chung Sham
- Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong, China
| | | | - Tom R Gaunt
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
| | - Andrew P Morris
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, University of Manchester, Manchester M13 9LJ, UK
| | - Ana M Valdes
- Faculty of Medicine and Health Sciences, School of Medicine, University of Nottingham, Nottingham, Nottinghamshire NG5 1PB, UK
| | - Aspasia Tsezou
- Laboratory of Cytogenetics and Molecular Genetics, Faculty of Medicine, University of Thessaly, Larissa 411 10, Greece
| | - Kathryn S E Cheah
- School of Biomedical Sciences, The University of Hong Kong, Pokfulam, Hong Kong, China
| | - Shiro Ikegawa
- Laboratory for Bone and Joint Diseases, RIKEN Center for Integrative Medical Sciences, Tokyo 108-8639, Japan
| | - Kristian Hveem
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, 7491 Trondheim, Norway; HUNT Research Center, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, 7600 Levanger, Norway
| | - Tõnu Esko
- Estonian Genome Center, Institute of Genomics, University of Tartu, 51010 Tartu, Estonia
| | - J Mark Wilkinson
- Department of Oncology and Metabolism and Healthy Lifespan Institute, University of Sheffield, Sheffield S10 2RX, UK
| | - Ingrid Meulenbelt
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Postzone S05-P Leiden University Medical Center, 2333ZC Leiden, the Netherlands
| | - Ming Ta Michael Lee
- Genomic Medicine Institute, Geisinger Health System, Danville, PA 17822, USA; Institute of Biomedical Sciences, Academia Sinica, 115 Taipei, Taiwan
| | - Joyce B J van Meurs
- Department of Internal Medicine, Erasmus MC, Medical Center, 3015CN Rotterdam, the Netherlands
| | | | - Eleftheria Zeggini
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany; TUM School of Medicine, Technical University of Munich and Klinikum Rechts der Isar, 81675 Munich, Germany.
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15
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Elucidating mechano-pathology of osteoarthritis: transcriptome-wide differences in mechanically stressed aged human cartilage explants. Arthritis Res Ther 2021; 23:215. [PMID: 34399844 PMCID: PMC8365911 DOI: 10.1186/s13075-021-02595-8] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Accepted: 07/30/2021] [Indexed: 11/25/2022] Open
Abstract
Background Failing of intrinsic chondrocyte repair after mechanical stress is known as one of the most important initiators of osteoarthritis. Nonetheless, insight into these early mechano-pathophysiological processes in age-related human articular cartilage is still lacking. Such insights are needed to advance clinical development. To highlight important molecular processes of osteoarthritis mechano-pathology, the transcriptome-wide changes following injurious mechanical stress on human aged osteochondral explants were characterized. Methods Following mechanical stress at a strain of 65% (65%MS) on human osteochondral explants (n65%MS = 14 versus ncontrol = 14), RNA sequencing was performed. Differential expression analysis between control and 65%MS was performed to determine mechanical stress-specific changes. Enrichment for pathways and protein-protein interactions was analyzed with Enrichr and STRING. Results We identified 156 genes significantly differentially expressed between control and 65%MS human osteochondral explants. Of note, IGFBP5 (FC = 6.01; FDR = 7.81 × 10−3) and MMP13 (FC = 5.19; FDR = 4.84 × 10−2) were the highest upregulated genes, while IGFBP6 (FC = 0.19; FDR = 3.07 × 10−4) was the most downregulated gene. Protein-protein interactions were significantly higher than expected by chance (P = 1.44 × 10−15 with connections between 116 out of 156 genes). Pathway analysis showed, among others, enrichment for cellular senescence, insulin-like growth factor (IGF) I and II binding, and focal adhesion. Conclusions Our results faithfully represent transcriptomic wide consequences of mechanical stress in human aged articular cartilage with MMP13, IGF binding proteins, and cellular senescence as the most notable results. Acquired knowledge on the as such identified initial, osteoarthritis-related, detrimental responses of chondrocytes may eventually contribute to the development of effective disease-modifying osteoarthritis treatments. Supplementary Information The online version contains supplementary material available at 10.1186/s13075-021-02595-8.
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16
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Houtman E, Coutinho de Almeida R, Tuerlings M, Suchiman HED, Broekhuis D, Nelissen RGHH, Ramos YFM, van Meurs JBJ, Meulenbelt I. Characterization of dynamic changes in Matrix Gla Protein (MGP) gene expression as function of genetic risk alleles, osteoarthritis relevant stimuli, and the vitamin K inhibitor warfarin. Osteoarthritis Cartilage 2021; 29:1193-1202. [PMID: 33984465 DOI: 10.1016/j.joca.2021.05.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Revised: 04/28/2021] [Accepted: 05/05/2021] [Indexed: 02/02/2023]
Abstract
OBJECTIVE We here aimed to characterize changes of Matrix Gla Protein (MGP) expression in relation to its recently identified OA risk allele rs1800801-T in OA cartilage, subchondral bone and human ex vivo osteochondral explants subjected to OA related stimuli. Given that MGP function depends on vitamin K bioavailability, we studied the effect of frequently prescribed vitamin K antagonist warfarin. METHODS Differential (allelic) mRNA expression of MGP was analyzed using RNA-sequencing data of human OA cartilage and subchondral bone. Human osteochondral explants were used to study exposures to interleukin one beta (IL-1β; inflammation), triiodothyronine (T3; Hypertrophy), warfarin, or 65% mechanical stress (65%MS) as function of rs1800801 genotypes. RESULTS We confirmed that the MGP risk allele rs1800801-T was associated with lower expression and that MGP was significantly upregulated in lesioned as compared to preserved OA tissues, mainly in risk allele carriers, in both cartilage and subchondral bone. Moreover, MGP expression was downregulated in response to OA like triggers in cartilage and subchondral bone and this effect might be reduced in carriers of the rs1800801-T risk allele. Finally, warfarin treatment in cartilage increased COL10A1 and reduced SOX9 and MMP3 expression and in subchondral bone reduced COL1A1 and POSTN expression. DISCUSSION & CONCLUSIONS Our data highlights that the genetic risk allele lowers MGP expression and upon OA relevant triggers may hamper adequate dynamic changes in MGP expression, mainly in cartilage. The determined direct negative effect of warfarin on human explant cultures functionally underscores the previously found association between vitamin K deficiency and OA.
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Affiliation(s)
- E Houtman
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| | - R Coutinho de Almeida
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| | - M Tuerlings
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| | - H E D Suchiman
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| | - D Broekhuis
- Department of Orthopaedics, Leiden University Medical Center, Leiden, the Netherlands
| | - R G H H Nelissen
- Department of Orthopaedics, Leiden University Medical Center, Leiden, the Netherlands
| | - Y F M Ramos
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| | - J B J van Meurs
- Department of Internal Medicine, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
| | - I Meulenbelt
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands.
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17
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Association between miRNA Target Sites and Incidence of Primary Osteoarthritis in Women from Volga-Ural Region of Russia: A Case-Control Study. Diagnostics (Basel) 2021; 11:diagnostics11071222. [PMID: 34359306 PMCID: PMC8306068 DOI: 10.3390/diagnostics11071222] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2021] [Revised: 06/30/2021] [Accepted: 06/30/2021] [Indexed: 11/30/2022] Open
Abstract
Over the past decades, numerous studies on the genetic markers of osteoarthritis (OA) have been conducted. MiRNA targets sites are a promising new area of research. In this study, we analyzed the polymorphic variants in 3′ UTR regions of COL1A1, COL11A1, ADAMTS5, MMP1, MMP13, SOX9, GDF5, FGF2, FGFR1, and FGFRL1 genes to examine the association between miRNA target site alteration and the incidence of OA in women from the Volga-Ural region of Russia using competitive allele-specific PCR. The T allele of the rs9659030 was associated with generalized OA (OR = 2.0), whereas the C allele of the rs229069 was associated with total OA (OR = 1.43). The T allele of the rs13317 was associated with the total OA (OR = 1.67). After Benjamini-Hochberg correction, only rs13317 remained statistically significant. According to ethnic heterogeneity, associations between the T allele (rs1061237) with OA in women of Russian descent (OR = 1.77), the G allele (rs6854081) in women of Tatar descent (OR = 4.78), the C allele (rs229069) and the T allele (rs73611720) in women of mixed descent and other ethnic groups (OR = 2.25 and OR = 3.02, respectively) were identified. All associations remained statistically significant after Benjamini-Hochberg correction. Together, this study identified miRNA target sites as a genetic marker for the development of OA in various ethnic groups.
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18
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Sorial AK, Hofer IMJ, Tselepi M, Cheung K, Parker E, Deehan DJ, Rice SJ, Loughlin J. Multi-tissue epigenetic analysis of the osteoarthritis susceptibility locus mapping to the plectin gene PLEC. Osteoarthritis Cartilage 2020; 28:1448-1458. [PMID: 32580029 PMCID: PMC7594932 DOI: 10.1016/j.joca.2020.06.001] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Revised: 06/08/2020] [Accepted: 06/09/2020] [Indexed: 02/02/2023]
Abstract
OBJECTIVE In cartilage, the osteoarthritis (OA) associated single nucleotide polymorphism (SNP) rs11780978 correlates with differential expression of PLEC, and with differential methylation of PLEC CpG dinucleotides, forming eQTLs and mQTLs respectively. This implies that methylation links chondrocyte genotype and phenotype, thus driving the functional effect of this genetic risk signal. PLEC encodes plectin, a cytoskeletal protein that enables tissues to respond to mechanical forces. We sought to assess whether these PLEC functional effects were cartilage specific. METHOD Cartilage, fat pad, synovium and peripheral blood were collected from patients undergoing arthroplasty. PLEC CpGs were analysed for mQTLs and allelic expression imbalance (AEI) was performed to test for eQTLs. Plectin was knocked down in a mesenchymal stem cell (MSC) line using CRISPR/Cas9 and cells phenotyped by RNA-sequencing. RESULTS mQTLs were discovered in fat pad, synovium and blood. Their effects were however stronger in the joint tissues and of comparable effect between these tissues. We observed AEI in synovium in the same direction as for cartilage and correlations between methylation and PLEC expression. Knocking-down plectin impacted on pathways reported to have a role in OA, including Wnt signalling, glycosaminoglycan biosynthesis and immune regulation. CONCLUSIONS Synovium is also a target of the rs11780978 OA association functionally operating on PLEC. In fat pad, mQTLs were identified but these did not correlate with PLEC expression, suggesting the functional effect is not joint-wide. Our study highlights interplay between genetic risk, DNA methylation and gene expression in OA, and reveals clear differences between tissues from the same diseased joint.
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MESH Headings
- Adipose Tissue/metabolism
- Adult
- Aged
- Aged, 80 and over
- Arthroplasty, Replacement
- CRISPR-Cas Systems
- Cartilage, Articular/metabolism
- Cell Line
- Chondrocytes/metabolism
- CpG Islands
- DNA Methylation
- Epigenesis, Genetic
- Female
- Gene Expression
- Gene Knockdown Techniques
- Genetic Predisposition to Disease
- Glycosaminoglycans/biosynthesis
- Humans
- Male
- Mesenchymal Stem Cells/metabolism
- Middle Aged
- Osteoarthritis, Hip/blood
- Osteoarthritis, Hip/genetics
- Osteoarthritis, Hip/metabolism
- Osteoarthritis, Hip/surgery
- Osteoarthritis, Knee/blood
- Osteoarthritis, Knee/genetics
- Osteoarthritis, Knee/metabolism
- Osteoarthritis, Knee/surgery
- Plectin/blood
- Plectin/genetics
- Plectin/metabolism
- Quantitative Trait Loci
- Sequence Analysis, RNA
- Synovial Membrane/metabolism
- Wnt Signaling Pathway/genetics
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Affiliation(s)
- A K Sorial
- Newcastle University, Biosciences Institute, Newcastle Upon Tyne, UK.
| | - I M J Hofer
- Newcastle University, Biosciences Institute, Newcastle Upon Tyne, UK.
| | - M Tselepi
- Newcastle University, Biosciences Institute, Newcastle Upon Tyne, UK.
| | - K Cheung
- Newcastle University, Biosciences Institute, Newcastle Upon Tyne, UK.
| | - E Parker
- Newcastle University, Biosciences Institute, Newcastle Upon Tyne, UK.
| | - D J Deehan
- Freeman Hospital, Newcastle Upon Tyne, UK.
| | - S J Rice
- Newcastle University, Biosciences Institute, Newcastle Upon Tyne, UK.
| | - J Loughlin
- Newcastle University, Biosciences Institute, Newcastle Upon Tyne, UK.
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19
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Boer CG, Yau MS, Rice SJ, Coutinho de Almeida R, Cheung K, Styrkarsdottir U, Southam L, Broer L, Wilkinson JM, Uitterlinden AG, Zeggini E, Felson D, Loughlin J, Young M, Capellini TD, Meulenbelt I, van Meurs JB. Genome-wide association of phenotypes based on clustering patterns of hand osteoarthritis identify WNT9A as novel osteoarthritis gene. Ann Rheum Dis 2020; 80:367-375. [PMID: 33055079 PMCID: PMC7892373 DOI: 10.1136/annrheumdis-2020-217834] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Revised: 09/07/2020] [Accepted: 09/08/2020] [Indexed: 12/14/2022]
Abstract
Background Despite recent advances in the understanding of the genetic architecture of osteoarthritis (OA), only two genetic loci have been identified for OA of the hand, in part explained by the complexity of the different hand joints and heterogeneity of OA pathology. Methods We used data from the Rotterdam Study (RSI, RSII and RSIII) to create three hand OA phenotypes based on clustering patterns of radiographic OA severity to increase power in our modest discovery genome-wide association studies in the RS (n=8700), and sought replication in an independent cohort, the Framingham Heart Study (n=1203). We used multiple approaches that leverage different levels of information and functional data to further investigate the underlying biological mechanisms and candidate genes for replicated loci. We also attempted to replicate known OA loci at other joint sites, including the hips and knees. Results We found two novel genome-wide significant loci for OA in the thumb joints. We identified WNT9A as a possible novel causal gene involved in OA pathogenesis. Furthermore, several previously identified genetic loci for OA seem to confer risk for OA across multiple joints: TGFa, RUNX2, COL27A1, ASTN2, IL11 and GDF5 loci. Conclusions We identified a robust novel genetic locus for hand OA on chromosome 1, of which WNT9A is the most likely causal gene. In addition, multiple genetic loci were identified to be associated with OA across multiple joints. Our study confirms the potential for novel insight into the genetic architecture of OA by using biologically meaningful stratified phenotypes.
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Affiliation(s)
- Cindy Germaine Boer
- Department of Internal Medicine, Genetic Laboratories, Erasmus MC, University Medical Center, Rotterdam, The Netherlands
| | - Michelle S Yau
- Hebrew SeniorLife, Beth Israel Deaconess Medical Center. Harvard Medical School, Hinda and Arthur Marcus Institute for Aging Research, Boston, Massachusetts, USA.,Department of Rheumatology, Boston University School of Medicine, Boston, Massachusetts, USA
| | - Sarah J Rice
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Rodrigo Coutinho de Almeida
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Kathleen Cheung
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, UK.,Newcastle University, Bioinformatics Support Unit, Newcastle upon Tyne, UK
| | | | - Lorraine Southam
- Institute of Translational Genomics, Helmholtz Zentrum München Deutsches Forschungszentrum für Gesundheit und Umwelt, Neuherberg, Germany
| | - Linda Broer
- Department of Internal Medicine, Genetic Laboratories, Erasmus MC, University Medical Center, Rotterdam, The Netherlands
| | | | - André G Uitterlinden
- Department of Internal Medicine, Genetic Laboratories, Erasmus MC, University Medical Center, Rotterdam, The Netherlands.,Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands
| | - Eleftheria Zeggini
- Institute of Translational Genomics, Helmholtz Zentrum München Deutsches Forschungszentrum für Gesundheit und Umwelt, Neuherberg, Germany
| | - David Felson
- Arthritis Research UK Epidemiology Unit, The University of Manchester, Manchester, UK
| | - John Loughlin
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Mariel Young
- Human Evolutionary Biology, Harvard University, Cambridge, Massachusetts, USA
| | | | - Ingrid Meulenbelt
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Joyce Bj van Meurs
- Department of Internal Medicine, Genetic Laboratories, Erasmus MC, University Medical Center, Rotterdam, The Netherlands
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20
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Bian Q, Cheng YH, Wilson JP, Su EY, Kim DW, Wang H, Yoo S, Blackshaw S, Cahan P. A single cell transcriptional atlas of early synovial joint development. Development 2020; 147:dev.185777. [PMID: 32580935 DOI: 10.1242/dev.185777] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2019] [Accepted: 06/09/2020] [Indexed: 12/14/2022]
Abstract
Synovial joint development begins with the formation of the interzone, a region of condensed mesenchymal cells at the site of the prospective joint. Recently, lineage-tracing strategies have revealed that Gdf5-lineage cells native to and from outside the interzone contribute to most, if not all, of the major joint components. However, there is limited knowledge of the specific transcriptional and signaling programs that regulate interzone formation and fate diversification of synovial joint constituents. To address this, we have performed single cell RNA-Seq analysis of 7329 synovial joint progenitor cells from the developing murine knee joint from E12.5 to E15.5. By using a combination of computational analytics, in situ hybridization and in vitro characterization of prospectively isolated populations, we have identified the transcriptional profiles of the major developmental paths for joint progenitors. Our freely available single cell transcriptional atlas will serve as a resource for the community to uncover transcriptional programs and cell interactions that regulate synovial joint development.
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Affiliation(s)
- Qin Bian
- Institute for Cell Engineering, Johns Hopkins School of Medicine, Baltimore MD 21205, USA.,Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore MD 21205, USA
| | - Yu-Hao Cheng
- Institute for Cell Engineering, Johns Hopkins School of Medicine, Baltimore MD 21205, USA.,Department of Molecular Biology and Genetics, Johns Hopkins School of Medicine, Baltimore MD 21205, USA
| | - Jordan P Wilson
- Institute for Cell Engineering, Johns Hopkins School of Medicine, Baltimore MD 21205, USA
| | - Emily Y Su
- Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore MD 21205, USA
| | - Dong Won Kim
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore MD 21205, USA
| | - Hong Wang
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore MD 21205, USA
| | - Sooyeon Yoo
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore MD 21205, USA
| | - Seth Blackshaw
- Institute for Cell Engineering, Johns Hopkins School of Medicine, Baltimore MD 21205, USA.,Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore MD 21205, USA
| | - Patrick Cahan
- Institute for Cell Engineering, Johns Hopkins School of Medicine, Baltimore MD 21205, USA .,Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore MD 21205, USA.,Department of Molecular Biology and Genetics, Johns Hopkins School of Medicine, Baltimore MD 21205, USA
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21
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Rice SJ, Beier F, Young DA, Loughlin J. Interplay between genetics and epigenetics in osteoarthritis. Nat Rev Rheumatol 2020; 16:268-281. [PMID: 32273577 DOI: 10.1038/s41584-020-0407-3] [Citation(s) in RCA: 85] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/11/2020] [Indexed: 12/15/2022]
Abstract
Research into the molecular genetics of osteoarthritis (OA) has been substantially bolstered in the past few years by the implementation of powerful genome-wide scans that have revealed a large number of novel risk loci associated with the disease. This refreshing wave of discovery has occurred concurrently with epigenetic studies of joint tissues that have examined DNA methylation, histone modifications and regulatory RNAs. These epigenetic analyses have involved investigations of joint development, homeostasis and disease and have used both human samples and animal models. What has become apparent from a comparison of these two complementary approaches is that many OA genetic risk signals interact with, map to or correlate with epigenetic mediators. This discovery implies that epigenetic mechanisms, and their effect on gene expression, are a major conduit through which OA genetic risk polymorphisms exert their functional effects. This observation is particularly exciting as it provides mechanistic insight into OA susceptibility. Furthermore, this knowledge reveals avenues for attenuating the negative effect of risk-conferring alleles by exposing the epigenome as an exploitable target for therapeutic intervention in OA.
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Affiliation(s)
- Sarah J Rice
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Frank Beier
- Department of Physiology and Pharmacology, The University of Western Ontario, London, ON, Canada.,Western Bone and Joint Institute, The University of Western Ontario, London, ON, Canada
| | - David A Young
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - John Loughlin
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, UK.
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22
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Osteoarthritis year in review 2019: genetics, genomics and epigenetics. Osteoarthritis Cartilage 2020; 28:275-284. [PMID: 31874234 DOI: 10.1016/j.joca.2019.11.010] [Citation(s) in RCA: 58] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/15/2019] [Revised: 10/31/2019] [Accepted: 11/05/2019] [Indexed: 02/02/2023]
Abstract
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.
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23
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Rice SJ, Cheung K, Reynard LN, Loughlin J. Discovery and analysis of methylation quantitative trait loci (mQTLs) mapping to novel osteoarthritis genetic risk signals. Osteoarthritis Cartilage 2019; 27:1545-1556. [PMID: 31173883 DOI: 10.1016/j.joca.2019.05.017] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/05/2019] [Revised: 05/23/2019] [Accepted: 05/24/2019] [Indexed: 02/02/2023]
Abstract
OBJECTIVE Osteoarthritis (OA) is polygenic with over 90 independent genome-wide association loci so far reported. A key next step is the identification of target genes and the molecular mechanisms through which this genetic risk operates. The majority of OA risk-conferring alleles are predicted to act by modulating gene expression. DNA methylation at CpG dinucleotides may be a functional conduit through which this occurs and is detectable by mapping methylation quantitative trait loci, or mQTLs. This approach can therefore provide functional insight into OA risk and will prioritize genes for subsequent investigation. That was our goal, with a focus on the largest set of OA loci yet to be reported. METHOD We investigated DNA methylation, genotype and RNA sequencing data derived from the cartilage of patients who had undergone arthroplasty and combined this with in silico analyses of expression quantitative trait loci, epigenomes and chromatin interactions. RESULTS We investigated 42 OA risk loci and in ten of these we identified 24 CpGs in which methylation correlated with genotype (false discovery rate (FDR) P-values ranging from 0.049 to 1.73x10-25). In silico analyses of these mQTLs prioritised genes and regulatory elements at the majority of the ten loci, with COLGALT2 (encoding a collagen galactosyltransferase), COL11A2 (encoding a polypeptide chain of type XI collagen) and WWP2 (encoding a ubiquitin ligase active during chondrogenesis) emerging as particularly compelling target genes. CONCLUSION We have highlighted the pivotal role of DNA methylation as a link between genetic risk and OA and prioritized genes for further investigation.
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Affiliation(s)
- S J Rice
- Newcastle University, Institute of Genetic Medicine, Newcastle upon Tyne, UK.
| | - K Cheung
- Newcastle University, Institute of Genetic Medicine, Newcastle upon Tyne, UK; Newcastle University, Bioinformatics Support Unit, Newcastle upon Tyne, UK.
| | - L N Reynard
- Newcastle University, Institute of Genetic Medicine, Newcastle upon Tyne, UK.
| | - J Loughlin
- Newcastle University, Institute of Genetic Medicine, Newcastle upon Tyne, UK.
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