S A Ali1, R Gandhi2, P Potla3, S Keshavarzi4, O Espin-Garcia5, K Shestopaloff6, C Pastrello7, D Bethune-Waddell8, S Lively9, A V Perruccio10, Y R Rampersaud11, C Veillette12, J S Rockel13, I Jurisica14, C T Appleton15, M Kapoor16. 1. Arthritis Program, Krembil Research Institute, University Health Network, Toronto, ON, Canada; Bone & Joint Center, Department of Orthopaedic Surgery, Henry Ford Health System, Detroit, MI, USA. Electronic address: s.amanda.ali@gmail.com. 2. Arthritis Program, Krembil Research Institute, University Health Network, Toronto, ON, Canada; Department of Surgery, Faculty of Medicine, University of Toronto, ON, Canada. Electronic address: Rajiv.Gandhi@uhn.ca. 3. Arthritis Program, Krembil Research Institute, University Health Network, Toronto, ON, Canada. Electronic address: Pratibha.Potla@uhnresearch.ca. 4. Arthritis Program, Krembil Research Institute, University Health Network, Toronto, ON, Canada. Electronic address: sareh.keshavarzi@uhnresearch.ca. 5. Arthritis Program, Krembil Research Institute, University Health Network, Toronto, ON, Canada. Electronic address: Osvaldo.Espin-Garcia@uhnresearch.ca. 6. Arthritis Program, Krembil Research Institute, University Health Network, Toronto, ON, Canada. Electronic address: konstantin.shestopaloff@utoronto.ca. 7. Arthritis Program, Krembil Research Institute, University Health Network, Toronto, ON, Canada. Electronic address: chiara.pastre@gmail.com. 8. Arthritis Program, Krembil Research Institute, University Health Network, Toronto, ON, Canada. Electronic address: dylan.bethune.waddell@gmail.com. 9. Arthritis Program, Krembil Research Institute, University Health Network, Toronto, ON, Canada. Electronic address: Starlee.Lively@uhnresearch.ca. 10. Arthritis Program, Krembil Research Institute, University Health Network, Toronto, ON, Canada; Department of Surgery, Faculty of Medicine, University of Toronto, ON, Canada; Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, ON, Canada. Electronic address: Anthony.Perruccio@uhnresearch.ca. 11. Arthritis Program, Krembil Research Institute, University Health Network, Toronto, ON, Canada; Department of Surgery, Faculty of Medicine, University of Toronto, ON, Canada. Electronic address: raja.rampersaud@uhn.ca. 12. Arthritis Program, Krembil Research Institute, University Health Network, Toronto, ON, Canada; Department of Surgery, Faculty of Medicine, University of Toronto, ON, Canada. Electronic address: christian.veillette@uhn.ca. 13. Arthritis Program, Krembil Research Institute, University Health Network, Toronto, ON, Canada. Electronic address: jason.rockel@utoronto.ca. 14. Arthritis Program, Krembil Research Institute, University Health Network, Toronto, ON, Canada; Departments of Medical Biophysics and Computer Science, University of Toronto, Toronto, ON, Canada. Electronic address: juris@ai.utoronto.ca. 15. Department of Medicine and Department of Physiology and Pharmacology, Western Bone and Joint Institute, The University of Western Ontario, London, ON, Canada(a). Electronic address: Tom.Appleton@sjhc.london.on.ca. 16. Arthritis Program, Krembil Research Institute, University Health Network, Toronto, ON, Canada; Department of Surgery, Faculty of Medicine, University of Toronto, ON, Canada; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada. Electronic address: mkapoor@uhnresearch.ca.
Abstract
OBJECTIVE: MicroRNAs act locally and systemically to impact osteoarthritis (OA) pathophysiology, but comprehensive profiling of the circulating miRNome in early vs late stages of OA has yet to be conducted. Sequencing has emerged as the preferred method for microRNA profiling since it offers high sensitivity and specificity. Our objective was to sequence the miRNome in plasma from 91 patients with early [Kellgren-Lawrence (KL) grade 0 or 1 (n = 41)] or late [KL grade 3 or 4 (n = 50)] symptomatic radiographic knee OA to identify unique microRNA signatures in each disease state. DESIGN: MicroRNA libraries were prepared using the QIAseq miRNA Library Kit and sequenced on the Illumina NextSeq 550. Counts were produced for microRNAs captured in miRBase and for novel microRNAs. Statistical, bioinformatics, and computational biology approaches were used to refine and interpret the final list of microRNAs. RESULTS: From 215 differentially expressed microRNAs (FDR < 0.01), 97 microRNAs showed an increase or decrease in expression in ≥85% of samples in the early OA group as compared to the median expression in the late OA group. Increasing this threshold to ≥95%, seven microRNAs were identified: hsa-miR-335-3p, hsa-miR-199a-5p, hsa-miR-671-3p, hsa-miR-1260b, hsa-miR-191-3p, hsa-miR-335-5p, and hsa-miR-543. Four novel microRNAs were present in ≥50% of early OA samples and had 27 predicted gene targets in common with the prioritized set of predicted gene targets from the 97 microRNAs, suggesting common underlying mechanisms. CONCLUSION: Sequencing of well-characterized patient cohorts produced unbiased profiling of the circulating miRNome and identified a unique panel of 11 microRNAs in early radiographic knee OA.
OBJECTIVE: MicroRNAs act locally and systemically to impact osteoarthritis (OA) pathophysiology, but comprehensive profiling of the circulating miRNome in early vs late stages of OA has yet to be conducted. Sequencing has emerged as the preferred method for microRNA profiling since it offers high sensitivity and specificity. Our objective was to sequence the miRNome in plasma from 91 patients with early [Kellgren-Lawrence (KL) grade 0 or 1 (n = 41)] or late [KL grade 3 or 4 (n = 50)] symptomatic radiographic knee OA to identify unique microRNA signatures in each disease state. DESIGN: MicroRNA libraries were prepared using the QIAseq miRNA Library Kit and sequenced on the Illumina NextSeq 550. Counts were produced for microRNAs captured in miRBase and for novel microRNAs. Statistical, bioinformatics, and computational biology approaches were used to refine and interpret the final list of microRNAs. RESULTS: From 215 differentially expressed microRNAs (FDR < 0.01), 97 microRNAs showed an increase or decrease in expression in ≥85% of samples in the early OA group as compared to the median expression in the late OA group. Increasing this threshold to ≥95%, seven microRNAs were identified: hsa-miR-335-3p, hsa-miR-199a-5p, hsa-miR-671-3p, hsa-miR-1260b, hsa-miR-191-3p, hsa-miR-335-5p, and hsa-miR-543. Four novel microRNAs were present in ≥50% of early OA samples and had 27 predicted gene targets in common with the prioritized set of predicted gene targets from the 97 microRNAs, suggesting common underlying mechanisms. CONCLUSION: Sequencing of well-characterized patient cohorts produced unbiased profiling of the circulating miRNome and identified a unique panel of 11 microRNAs in early radiographic knee OA.
Authors: Clara Sanjurjo-Rodríguez; Rachel E Crossland; Monica Reis; Hemant Pandit; Xiao-Nong Wang; Elena Jones Journal: Stem Cells Int Date: 2021-10-09 Impact factor: 5.443
Authors: Yolande F M Ramos; Rodrigo Coutinho de Almeida; Nico Lakenberg; Eka Suchiman; Hailiang Mei; Margreet Kloppenburg; Rob G H H Nelissen; Ingrid Meulenbelt Journal: Biomolecules Date: 2021-09-13