AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
Powered by AMiner. Clicking this button will take you away from SciOpen.
Home Bone Research Article
PDF (3.9 MB)
Cite
EndNote(RIS) BibTeX
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Original Article | Open Access

Combining single-cell RNA sequencing and population-based studies reveals hand osteoarthritis-associated chondrocyte subpopulations and pathways

Hui Li1,2,3,, Xiaofeng Jiang1,2,3,, Yongbing Xiao1,2,3,, Yuqing Zhang4,5, Weiya Zhang6,7, Michael Doherty6,7, Jacquelyn Nestor4, Changjun Li2,3,8,9, Jing Ye1,2,3, Tingting Sha2,3, Houchen Lyu1, Jie Wei1,3,10,11 ( ), Chao Zeng1,2,3,9( ), Guanghua Lei1,2,3,9 ( )
Department of Orthopaedics, Xiangya Hospital, Central South University, Changsha 410008, Hunan, China
Hunan Key Laboratory of Joint Degeneration and Injury, Changsha 410008 Hunan, China
Key Laboratory of Aging-related Bone and Joint Diseases Prevention and Treatment, Ministry of Education, Xiangya Hospital, Central South University, Changsha, China
Division of Rheumatology, Allergy, and Immunology, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02115, USA
The Mongan Institute, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02115, USA
Academic Rheumatology, School of Medicine, University ofNottingham, Nottingham NG5 1PB, UK
Pain Centre Versus Arthritis UK, Nottingham NG5 1PB, UK
Department of Endocrinology, Endocrinology Research Center, Xiangya Hospital, Central South University, Changsha 410008 Hunan, China
National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410008 Hunan, China
Health Management Center, Xiangya Hospital, Central South University, Changsha 410008 Hunan, China
Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410008 Hunan, China

These authors contributed equally: Hui Li, Xiaofeng Jiang, Yongbing Xiao

Show Author Information

Abstract

Hand osteoarthritis is a common heterogeneous joint disorder with unclear molecular mechanisms and no disease-modifying drugs. In this study, we performed single-cell RNA sequencing analysis to compare the cellular composition and subpopulation-specific gene expression between cartilage with macroscopically confirmed osteoarthritis (n = 5) and cartilage without osteoarthritis (n = 5) from the interphalangeal joints of five donors. Of 105 142 cells, we identified 13 subpopulations, including a novel subpopulation with inflammation-modulating potential annotated as inflammatory chondrocytes. Fibrocartilage chondrocytes exhibited extensive alteration of gene expression patterns in osteoarthritic cartilage compared with nonosteoarthritic cartilage. Both inflammatory chondrocytes and fibrocartilage chondrocytes showed a trend toward increased numbers in osteoarthritic cartilage. In these two subpopulations from osteoarthritic cartilage, the ferroptosis pathway was enriched, and expression of iron overload-related genes, e.g., FTH1, was elevated. To verify these findings, we conducted a Mendelian randomization study using UK Biobank and a population-based cross-sectional study using data collected from Xiangya Osteoarthritis Study. Genetic predisposition toward higher expression of FTH1 mRNA significantly increased the risk of hand osteoarthritis (odds ratio = 1.07, 95% confidence interval: 1.02–1.11) among participants (n = 332 668) in UK Biobank. High levels of serum ferritin (encoded by FTH1), a biomarker of body iron overload, were significantly associated with a high prevalence of hand osteoarthritis among participants (n = 1 241) of Xiangya Osteoarthritis Study (P-for-trend = 0.037). In conclusion, our findings indicate that inflammatory and fibrocartilage chondrocytes are key subpopulations and that ferroptosis may be a key pathway in hand osteoarthritis, providing new insights into the pathophysiology and potential therapeutic targets of hand osteoarthritis.

References

1

Kloppenburg, M. & Kwok, W. Y. Hand osteoarthritis-a heterogeneous disorder. Nat. Rev. Rheumatol. 8, 22–31 (2011).
Crossref Google Scholar
2

Marshall, M., Watt, F. E., Vincent, T. L. & Dziedzic, K. Hand osteoarthritis: clinical phenotypes, molecular mechanisms and disease management. Nat. Rev. Rheumatol. 14, 641–656 (2018).
Crossref Google Scholar
3

Haugen, I. K. et al. Prevalence, incidence and progression of hand osteoarthritis in the general population: the Framingham Osteoarthritis Study. Ann. Rheum. Dis. 70, 1581–1586 (2011).
Crossref Google Scholar
4

Bijlsma, J. W., Berenbaum, F. & Lafeber, F. P. Osteoarthritis: an update with relevance for clinical practice. Lancet 377, 2115–2126 (2011).
Crossref Google Scholar
5

Funck-Brentano, T. et al. Causal factors for knee, hip, and hand osteoarthritis: a mendelian randomization study in the UK biobank. Arthritis Rheumatol. 71, 1634–1641 (2019).
Crossref Google Scholar
6

Kjeken, I. et al. Activity limitations and participation restrictions in women with hand osteoarthritis: patients’ descriptions and associations between dimensions of functioning. Ann. Rheum. Dis. 64, 1633–1638 (2005).
Crossref Google Scholar
7

Kwok, W. Y. et al. Limitations in daily activities are the major determinant of reduced health-related quality of life in patients with hand osteoarthritis. Ann. Rheum. Dis. 70, 334–336 (2011).
Crossref Google Scholar
8

Michon, M., Maheu, E. & Berenbaum, F. Assessing health-related quality of life in hand osteoarthritis: a literature review. Ann. Rheum. Dis. 70, 921–928 (2011).
Crossref Google Scholar
9

Haugen, I. K. et al. Hand osteoarthritis in relation to mortality and incidence of cardiovascular disease: data from the Framingham heart study. Ann. Rheum. Dis. 74, 74–81 (2015).
Crossref Google Scholar
10

Kloppenburg, M. et al. Etanercept in patients with inflammatory hand osteoarthritis (EHOA): a multicentre, randomised, double-blind, placebo-controlled trial. Ann. Rheum. Dis. 77, 1757–1764 (2018).
Crossref Google Scholar
11

Chevalier, X. et al. Adalimumab in patients with hand osteoarthritis refractory to analgesics and NSAIDs: a randomised, multicentre, double-blind, placebo-controlled trial. Ann. Rheum. Dis. 74, 1697–1705 (2015).
Crossref Google Scholar
12

Kingsbury, S. R. et al. Hydroxychloroquine effectiveness in reducing symptoms of hand osteoarthritis: a randomized trial. Ann. Intern. Med. 168, 385–395, (2018).
Crossref Google Scholar
13

Kroon, F. P. B. et al. Results of a 6-week treatment with 10 mg prednisolone in patients with hand osteoarthritis (HOPE): a double-blind, randomised, placebo-controlled trial. Lancet 394, 1993–2001 (2019).
Crossref Google Scholar
14

Kolasinski, S. L. et al. 2019 American college of rheumatology/arthritis foundation guideline for the management of osteoarthritis of the hand, hip, and knee. Arthritis Rheumatol. 72, 220–233 (2020).
Crossref Google Scholar
15

Zhang, W. et al. EULAR evidence based recommendations for the management of hand osteoarthritis: report of a Task Force of the EULAR Standing Committee for International Clinical Studies Including Therapeutics (ESCISIT). Ann. Rheum. Dis. 66, 377–388 (2007).
Crossref Google Scholar
16

Grun, D. & van Oudenaarden, A. Design and analysis of single-cell sequencing experiments. Cell 163, 799–810 (2015).
Crossref Google Scholar
17

Emdin, C. A., Khera, A. V. & Kathiresan, S. Mendelian randomization. Jama 318, 1925–1926, (2017).
Crossref Google Scholar
18

Wei, J. et al. Association between gut microbiota and symptomatic hand osteoarthritis: data from the Xiangya Osteoarthritis Study. Arthritis Rheumatol. 73, 1656–1662 (2021).
Crossref Google Scholar
19

Wei, J. et al. Association between gut microbiota and elevated serum urate in two independent cohorts. Arthritis Rheumatol. 74, 682–691 (2022).
Crossref Google Scholar
20

Ji, Q. et al. Single-cell RNA-seq analysis reveals the progression of human osteoarthritis. Ann. Rheum. Dis. 78, 100–110 (2019).
Crossref Google Scholar
21

Gan, Y. et al. Spatially defined single-cell transcriptional profiling characterizes diverse chondrocyte subtypes and nucleus pulposus progenitors in human intervertebral discs. Bone Res. 9, 37 (2021).
Crossref Google Scholar
22

Sun, H. et al. Single-cell RNA-seq analysis identifies meniscus progenitors and reveals the progression of meniscus degeneration. Ann. Rheum. Dis. 79, 408–417 (2020).
Crossref Google Scholar
23

Wang, X. et al. Comparison of the major cell populations among osteoarthritis, Kashin-Beck disease and healthy chondrocytes by single-cell RNA-seq analysis. Cell Death Dis. 12, 551 (2021).
Crossref Google Scholar
24

Chou, C. H. et al. Synovial cell cross-talk with cartilage plays a major role in the pathogenesis of osteoarthritis. Sci. Rep. 10, 10868 (2020).
Crossref Google Scholar
25

Dixon, S. J. et al. Ferroptosis: an iron-dependent form of nonapoptotic cell death. Cell 149, 1060–1072 (2012).
Crossref Google Scholar
26

Arosio, P., Ingrassia, R. & Cavadini, P. Ferritins: a family of molecules for iron storage, antioxidation and more. Biochim. Biophys. Acta 1790, 589–599 (2009).
Crossref Google Scholar
27

Robinson, W. H. et al. Low-grade inflammation as a key mediator of the pathogenesis of osteoarthritis. Nat. Rev. Rheumatol. 12, 580–592 (2016).
Crossref Google Scholar
28

Pap, T. & Korb-Pap, A. Cartilage damage in osteoarthritis and rheumatoid arthritis-two unequal siblings. Nat. Rev. Rheumatol. 11, 606–615 (2015).
Crossref Google Scholar
29

Jiang, Y. & Tuan, R. S. Origin and function of cartilage stem/progenitor cells in osteoarthritis. Nat. Rev. Rheumatol. 11, 206–212 (2015).
Crossref Google Scholar
30

Walsh, D. A. et al. Angiogenesis and nerve growth factor at the osteochondral junction in rheumatoid arthritis and osteoarthritis. Rheumatology (Oxford) 49, 1852–1861 (2010).
Crossref Google Scholar
31

Mapp, P. I. & Walsh, D. A. Mechanisms and targets of angiogenesis and nerve growth in osteoarthritis. Nat. Rev. Rheumatol. 8, 390–398 (2012).
Crossref Google Scholar
32

Suri, S. et al. Neurovascular invasion at the osteochondral junction and in osteophytes in osteoarthritis. Ann. Rheum. Dis. 66, 1423–1428 (2007).
Crossref Google Scholar
33

Zhou, J. et al. Single-cell transcriptome analysis profile of meniscal tissue macrophages in human osteoarthritis. J. Immunol. Res. 2020, 8127281 (2020).
Crossref Google Scholar
34

Cui, Z. et al. Halofuginone attenuates osteoarthritis by inhibition of TGF-beta activity and H-type vessel formation in subchondral bone. Ann. Rheum. Dis. 75, 1714–1721 (2016).
Crossref Google Scholar
35

Jiang, X., Stockwell, B. R. & Conrad, M. Ferroptosis: mechanisms, biology and role in disease. Nat. Rev. Mol. Cell Biol. 22, 266–282 (2021).
Crossref Google Scholar
36

Simão, M. et al. Intracellular iron uptake is favored in Hfe-KO mouse primary chondrocytes mimicking an osteoarthritis-related phenotype. Biofactors 45, 583–597 (2019).
Crossref Google Scholar
37

Ryder, J. J. et al. Genetic associations in peripheral joint osteoarthritis and spinal degenerative disease: a systematic review. Ann. Rheum. Dis. 67, 584–591 (2008).
Crossref Google Scholar
38

Yamada, N. et al. Iron overload as a risk factor for hepatic ischemia-reperfusion injury in liver transplantation: potential role of ferroptosis. Am. J. Transplant. 20, 1606–1618 (2020).
Crossref Google Scholar
39

Goozee, K. et al. Elevated plasma ferritin in elderly individuals with high neocortical amyloid-β load. Mol. Psychiatry 23, 1807–1812 (2018).
Crossref Google Scholar
40

Zilka, O. et al. On the mechanism of cytoprotection by Ferrostatin-1 and Liproxstatin-1 and the role of lipid peroxidation in ferroptotic cell death. ACS Cent. Sci. 3, 232–243 (2017).
Crossref Google Scholar
41

Pei, Z. et al. Inhibition of ferroptosis and iron accumulation alleviates pulmonary fibrosis in a bleomycin model. Redox. Biol. 57, 102509 (2022).
Crossref Google Scholar
42

Wright, R. W. & Group, M. Osteoarthritis classification scales: interobserver reliability and arthroscopic correlation. J. Bone Joint Surg. Am. 96, 1145–1151 (2014).
Crossref Google Scholar
43

Hwang, J. et al. Increased hydraulic conductance of human articular cartilage and subchondral bone plate with progression of osteoarthritis. Arthritis Rheum. 58, 3831–3842 (2008).
Crossref Google Scholar
44

Alexa, A. & Rahnenfürer, J. J. B. I. Gene set enrichment analysis with topGO. Bioconductor lImprov. 27, 1–26 (2009).
Google Scholar
45

Liberzon, A. et al. The molecular signatures database (MSigDB) hallmark gene set collection. Cell Syst. 1, 417–425 (2015).
Crossref Google Scholar
46

Naba, A. et al. The extracellular matrix: tools and insights for the “omics” era. Matrix Biol. 49, 10–24 (2016).
Crossref Google Scholar
47

Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl. Acad. Sci. USA 102, 15545–15550 (2005).
Crossref Google Scholar
48

Jin, S. et al. Inference and analysis of cell-cell communication using CellChat. Nat. Commun. 12, 1088 (2021).
Crossref Google Scholar
49

Ostergaard, K. et al. Expression of alpha and beta subunits of the integrin superfamily in articular cartilage from macroscopically normal and osteoarthritic human femoral heads. Ann. Rheum. Dis. 57, 303–308 (1998).
Crossref Google Scholar
50

Võsa, U. et al. Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression. Nat. Genet. 53, 1300–1310 (2021).
Crossref Google Scholar
51

Sudlow, C. et al. UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 12, e1001779 (2015).
Crossref Google Scholar
52

Burgess, S. et al. Sensitivity analyses for robust causal inference from mendelian randomization analyses with multiple genetic variants. Epidemiology 28, 30–42 (2017).
Crossref Google Scholar
53

Verbanck, M., Chen, C. Y., Neale, B. & Do, R. Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases. Nat. Genet. 50, 693–698 (2018).
Crossref Google Scholar
54

Bowden, J. et al. Improving the accuracy of two-sample summary-data Mendelian randomization: moving beyond the NOME assumption. Int. J. Epidemiol. 48, 728–742 (2019).
Crossref Google Scholar
55

Zhang, Y., Glynn, R. J. & Felson, D. T. Musculoskeletal disease research: should we analyze the joint or the person? J. Rheumatol. 23, 1130–1134 (1996).
Google Scholar
Bone Research
Volume 11,
December 2023
Article number: 58
DOI: 10.1038/s41413-023-00292-7
Cite this article:
Li H, Jiang X, Xiao Y, et al. Combining single-cell RNA sequencing and population-based studies reveals hand osteoarthritis-associated chondrocyte subpopulations and pathways. Bone Research, 2023, 11: 58. https://doi.org/10.1038/s41413-023-00292-7

99

Views

2

Downloads

8

Crossref

7

Web of Science

7

Scopus

Altmetrics
Received: 03 March 2023
Revised: 17 July 2023
Accepted: 07 September 2023
Published: 02 November 2023
© The Author(s) 2023

This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
Return