Single-cell RNA-seq analysis reveals the progression of human osteoarthritis

ObjectivesUnderstanding the molecular mechanisms underlying human cartilage degeneration and regeneration is helpful for improving therapeutic strategies for treating osteoarthritis (OA). Here, we report the molecular programmes and lineage progression patterns controlling human OA pathogenesis usin...

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Published inAnnals of the rheumatic diseases Vol. 78; no. 1; pp. 100 - 110
Main Authors Ji, Quanbo, Zheng, Yuxuan, Zhang, Guoqiang, Hu, Yuqiong, Fan, Xiaoying, Hou, Yu, Wen, Lu, Li, Li, Xu, Yameng, Wang, Yan, Tang, Fuchou
Format Journal Article
LanguageEnglish
Published England Elsevier Limited 01.01.2019
BMJ Publishing Group
SeriesTranslational science
Subjects
Arthritis
Arthroplasty (knee)
Cartilage diseases
Cartilage, Articular - cytology
Cell cycle
Chondrocytes
Chondrocytes - metabolism
Chondrogenesis - genetics
Computational Biology
Computer applications
Degeneration
Disease Progression
Gene expression
Gene Expression Profiling
Homeostasis
Humans
Joint surgery
Kinases
Knee
Molecular modelling
Osteoarthritis
Osteoarthritis, Knee - genetics
Pathogenesis
Phenotype
Phenotypes
Progenitor cells
Ribonucleic acid
RNA
Sequence Analysis, RNA
Stem cells
Stem Cells - metabolism
Surgery
Taxonomy
Transcription
Transcriptome
Beijing China
China
knee osteoarthritis
osteoarthritis
chondrocytes
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Abstract ObjectivesUnderstanding the molecular mechanisms underlying human cartilage degeneration and regeneration is helpful for improving therapeutic strategies for treating osteoarthritis (OA). Here, we report the molecular programmes and lineage progression patterns controlling human OA pathogenesis using single-cell RNA sequencing (scRNA-seq).MethodsWe performed unbiased transcriptome-wide scRNA-seq analysis, computational analysis and histological assays on 1464 chondrocytes from 10 patients with OA undergoing knee arthroplasty surgery. We investigated the relationship between transcriptional programmes of the OA landscape and clinical outcome using severity index and correspondence analysis.ResultsWe identified seven molecularly defined populations of chondrocytes in the human OA cartilage, including three novel phenotypes with distinct functions. We presented gene expression profiles at different OA stages at single-cell resolution. We found a potential transition among proliferative chondrocytes, prehypertrophic chondrocytes and hypertrophic chondrocytes (HTCs) and defined a new subdivision within HTCs. We revealed novel markers for cartilage progenitor cells (CPCs) and demonstrated a relationship between CPCs and fibrocartilage chondrocytes using computational analysis. Notably, we derived predictive targets with respect to clinical outcomes and clarified the role of different cell types for the early diagnosis and treatment of OA.ConclusionsOur results provide new insights into chondrocyte taxonomy and present potential clues for effective and functional manipulation of human OA cartilage regeneration that could lead to improved health.
AbstractList Understanding the molecular mechanisms underlying human cartilage degeneration and regeneration is helpful for improving therapeutic strategies for treating osteoarthritis (OA). Here, we report the molecular programmes and lineage progression patterns controlling human OA pathogenesis using single-cell RNA sequencing (scRNA-seq).OBJECTIVESUnderstanding the molecular mechanisms underlying human cartilage degeneration and regeneration is helpful for improving therapeutic strategies for treating osteoarthritis (OA). Here, we report the molecular programmes and lineage progression patterns controlling human OA pathogenesis using single-cell RNA sequencing (scRNA-seq).We performed unbiased transcriptome-wide scRNA-seq analysis, computational analysis and histological assays on 1464 chondrocytes from 10 patients with OA undergoing knee arthroplasty surgery. We investigated the relationship between transcriptional programmes of the OA landscape and clinical outcome using severity index and correspondence analysis.METHODSWe performed unbiased transcriptome-wide scRNA-seq analysis, computational analysis and histological assays on 1464 chondrocytes from 10 patients with OA undergoing knee arthroplasty surgery. We investigated the relationship between transcriptional programmes of the OA landscape and clinical outcome using severity index and correspondence analysis.We identified seven molecularly defined populations of chondrocytes in the human OA cartilage, including three novel phenotypes with distinct functions. We presented gene expression profiles at different OA stages at single-cell resolution. We found a potential transition among proliferative chondrocytes, prehypertrophic chondrocytes and hypertrophic chondrocytes (HTCs) and defined a new subdivision within HTCs. We revealed novel markers for cartilage progenitor cells (CPCs) and demonstrated a relationship between CPCs and fibrocartilage chondrocytes using computational analysis. Notably, we derived predictive targets with respect to clinical outcomes and clarified the role of different cell types for the early diagnosis and treatment of OA.RESULTSWe identified seven molecularly defined populations of chondrocytes in the human OA cartilage, including three novel phenotypes with distinct functions. We presented gene expression profiles at different OA stages at single-cell resolution. We found a potential transition among proliferative chondrocytes, prehypertrophic chondrocytes and hypertrophic chondrocytes (HTCs) and defined a new subdivision within HTCs. We revealed novel markers for cartilage progenitor cells (CPCs) and demonstrated a relationship between CPCs and fibrocartilage chondrocytes using computational analysis. Notably, we derived predictive targets with respect to clinical outcomes and clarified the role of different cell types for the early diagnosis and treatment of OA.Our results provide new insights into chondrocyte taxonomy and present potential clues for effective and functional manipulation of human OA cartilage regeneration that could lead to improved health.CONCLUSIONSOur results provide new insights into chondrocyte taxonomy and present potential clues for effective and functional manipulation of human OA cartilage regeneration that could lead to improved health.
ObjectivesUnderstanding the molecular mechanisms underlying human cartilage degeneration and regeneration is helpful for improving therapeutic strategies for treating osteoarthritis (OA). Here, we report the molecular programmes and lineage progression patterns controlling human OA pathogenesis using single-cell RNA sequencing (scRNA-seq).MethodsWe performed unbiased transcriptome-wide scRNA-seq analysis, computational analysis and histological assays on 1464 chondrocytes from 10 patients with OA undergoing knee arthroplasty surgery. We investigated the relationship between transcriptional programmes of the OA landscape and clinical outcome using severity index and correspondence analysis.ResultsWe identified seven molecularly defined populations of chondrocytes in the human OA cartilage, including three novel phenotypes with distinct functions. We presented gene expression profiles at different OA stages at single-cell resolution. We found a potential transition among proliferative chondrocytes, prehypertrophic chondrocytes and hypertrophic chondrocytes (HTCs) and defined a new subdivision within HTCs. We revealed novel markers for cartilage progenitor cells (CPCs) and demonstrated a relationship between CPCs and fibrocartilage chondrocytes using computational analysis. Notably, we derived predictive targets with respect to clinical outcomes and clarified the role of different cell types for the early diagnosis and treatment of OA.ConclusionsOur results provide new insights into chondrocyte taxonomy and present potential clues for effective and functional manipulation of human OA cartilage regeneration that could lead to improved health.
Understanding the molecular mechanisms underlying human cartilage degeneration and regeneration is helpful for improving therapeutic strategies for treating osteoarthritis (OA). Here, we report the molecular programmes and lineage progression patterns controlling human OA pathogenesis using single-cell RNA sequencing (scRNA-seq). We performed unbiased transcriptome-wide scRNA-seq analysis, computational analysis and histological assays on 1464 chondrocytes from 10 patients with OA undergoing knee arthroplasty surgery. We investigated the relationship between transcriptional programmes of the OA landscape and clinical outcome using severity index and correspondence analysis. We identified seven molecularly defined populations of chondrocytes in the human OA cartilage, including three novel phenotypes with distinct functions. We presented gene expression profiles at different OA stages at single-cell resolution. We found a potential transition among proliferative chondrocytes, prehypertrophic chondrocytes and hypertrophic chondrocytes (HTCs) and defined a new subdivision within HTCs. We revealed novel markers for cartilage progenitor cells (CPCs) and demonstrated a relationship between CPCs and fibrocartilage chondrocytes using computational analysis. Notably, we derived predictive targets with respect to clinical outcomes and clarified the role of different cell types for the early diagnosis and treatment of OA. Our results provide new insights into chondrocyte taxonomy and present potential clues for effective and functional manipulation of human OA cartilage regeneration that could lead to improved health.
Author Xu, Yameng
Hou, Yu
Li, Li
Tang, Fuchou
Hu, Yuqiong
Wen, Lu
Zhang, Guoqiang
Fan, Xiaoying
Zheng, Yuxuan
Ji, Quanbo
Wang, Yan
AuthorAffiliation 4 Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies , Peking University , Beijing , China
3 Beijing Advanced Innovation Center for Genomics (ICG), College of Life Science, Peking University , Beijing , China
5 Department of Traditional Chinese Medicine , Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine , Shanghai , China
1 Department of Orthopaedics , General Hospital of Chinese People’s Liberation Army , Beijing , China
2 Biomedical Institute for Pioneering Investigation via Convergence and Ministry of Education Key Laboratory of Cell Proliferation and Differentiation , Beijing , China
AuthorAffiliation_xml – name: 3 Beijing Advanced Innovation Center for Genomics (ICG), College of Life Science, Peking University , Beijing , China
– name: 5 Department of Traditional Chinese Medicine , Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine , Shanghai , China
– name: 2 Biomedical Institute for Pioneering Investigation via Convergence and Ministry of Education Key Laboratory of Cell Proliferation and Differentiation , Beijing , China
– name: 4 Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies , Peking University , Beijing , China
– name: 1 Department of Orthopaedics , General Hospital of Chinese People’s Liberation Army , Beijing , China
Author_xml – sequence: 1
  givenname: Quanbo
  surname: Ji
  fullname: Ji, Quanbo
  email: yanwang301@126.com, tangfuchou@pku.edu.cn
  organization: Biomedical Institute for Pioneering Investigation via Convergence and Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China
– sequence: 2
  givenname: Yuxuan
  surname: Zheng
  fullname: Zheng, Yuxuan
  email: yanwang301@126.com, tangfuchou@pku.edu.cn
  organization: Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
– sequence: 3
  givenname: Guoqiang
  surname: Zhang
  fullname: Zhang, Guoqiang
  email: yanwang301@126.com, tangfuchou@pku.edu.cn
  organization: Department of Orthopaedics, General Hospital of Chinese People’s Liberation Army, Beijing, China
– sequence: 4
  givenname: Yuqiong
  surname: Hu
  fullname: Hu, Yuqiong
  email: yanwang301@126.com, tangfuchou@pku.edu.cn
  organization: Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
– sequence: 5
  givenname: Xiaoying
  surname: Fan
  fullname: Fan, Xiaoying
  email: yanwang301@126.com, tangfuchou@pku.edu.cn
  organization: Beijing Advanced Innovation Center for Genomics (ICG), College of Life Science, Peking University, Beijing, China
– sequence: 6
  givenname: Yu
  surname: Hou
  fullname: Hou, Yu
  email: yanwang301@126.com, tangfuchou@pku.edu.cn
  organization: Beijing Advanced Innovation Center for Genomics (ICG), College of Life Science, Peking University, Beijing, China
– sequence: 7
  givenname: Lu
  surname: Wen
  fullname: Wen, Lu
  email: yanwang301@126.com, tangfuchou@pku.edu.cn
  organization: Beijing Advanced Innovation Center for Genomics (ICG), College of Life Science, Peking University, Beijing, China
– sequence: 8
  givenname: Li
  surname: Li
  fullname: Li, Li
  email: yanwang301@126.com, tangfuchou@pku.edu.cn
  organization: Beijing Advanced Innovation Center for Genomics (ICG), College of Life Science, Peking University, Beijing, China
– sequence: 9
  givenname: Yameng
  surname: Xu
  fullname: Xu, Yameng
  email: yanwang301@126.com, tangfuchou@pku.edu.cn
  organization: Department of Traditional Chinese Medicine, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
– sequence: 10
  givenname: Yan
  surname: Wang
  fullname: Wang, Yan
  email: yanwang301@126.com, tangfuchou@pku.edu.cn
  organization: Department of Orthopaedics, General Hospital of Chinese People’s Liberation Army, Beijing, China
– sequence: 11
  givenname: Fuchou
  surname: Tang
  fullname: Tang, Fuchou
  email: yanwang301@126.com, tangfuchou@pku.edu.cn
  organization: Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
BackLink https://www.ncbi.nlm.nih.gov/pubmed/30026257$$D View this record in MEDLINE/PubMed
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Issue 1
Keywords knee osteoarthritis
osteoarthritis
chondrocytes
Language English
License This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0
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Snippet ObjectivesUnderstanding the molecular mechanisms underlying human cartilage degeneration and regeneration is helpful for improving therapeutic strategies for...
Understanding the molecular mechanisms underlying human cartilage degeneration and regeneration is helpful for improving therapeutic strategies for treating...
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StartPage 100
SubjectTerms Arthritis
Arthroplasty (knee)
Cartilage diseases
Cartilage, Articular - cytology
Cell cycle
Chondrocytes
Chondrocytes - metabolism
Chondrogenesis - genetics
Computational Biology
Computer applications
Degeneration
Disease Progression
Gene expression
Gene Expression Profiling
Homeostasis
Humans
Joint surgery
Kinases
Knee
Molecular modelling
Osteoarthritis
Osteoarthritis, Knee - genetics
Pathogenesis
Phenotype
Phenotypes
Progenitor cells
Ribonucleic acid
RNA
Sequence Analysis, RNA
Stem cells
Stem Cells - metabolism
Surgery
Taxonomy
Transcription
Transcriptome
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Title Single-cell RNA-seq analysis reveals the progression of human osteoarthritis
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