Mass spectrometry-based proteomics identify novel serum osteoarthritis biomarkers
Abstract Background Osteoarthritis (OA) is a slowly developing and debilitating disease, and there are no validated specific biomarkers for its early detection. To improve therapeutic approaches, identification of specific molecules/biomarkers enabling early determination of this disease is needed....
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ftdoajarticles:oai:doaj.org/article:cedea55d8a3f4c18b61c342dfbb76726 2023-05-15T17:22:53+02:00 Mass spectrometry-based proteomics identify novel serum osteoarthritis biomarkers Ginette Tardif Frédéric Paré Clarisse Gotti Florence Roux-Dalvai Arnaud Droit Guangju Zhai Guang Sun Hassan Fahmi Jean-Pierre Pelletier Johanne Martel-Pelletier 2022-05-01T00:00:00Z https://doi.org/10.1186/s13075-022-02801-1 https://doaj.org/article/cedea55d8a3f4c18b61c342dfbb76726 EN eng BMC https://doi.org/10.1186/s13075-022-02801-1 https://doaj.org/toc/1478-6362 doi:10.1186/s13075-022-02801-1 1478-6362 https://doaj.org/article/cedea55d8a3f4c18b61c342dfbb76726 Arthritis Research & Therapy, Vol 24, Iss 1, Pp 1-16 (2022) Serum biomarkers Proteomics Osteoarthritis Mass spectrometry Diseases of the musculoskeletal system RC925-935 article 2022 ftdoajarticles https://doi.org/10.1186/s13075-022-02801-1 2022-12-31T02:31:52Z Abstract Background Osteoarthritis (OA) is a slowly developing and debilitating disease, and there are no validated specific biomarkers for its early detection. To improve therapeutic approaches, identification of specific molecules/biomarkers enabling early determination of this disease is needed. This study aimed at identifying, with the use of proteomics/mass spectrometry, novel OA-specific serum biomarkers. As obesity is a major risk factor for OA, we discriminated obesity-regulated proteins to target only OA-specific proteins as biomarkers. Methods Serum from the Osteoarthritis Initiative cohort was used and divided into 3 groups: controls (n=8), OA-obese (n=10) and OA-non-obese (n=10). Proteins were identified and quantified from the liquid chromatography–tandem mass spectrometry analyses using MaxQuant software. Statistical analysis used the Limma test followed by the Benjamini-Hochberg method. To compare the proteomic profiles, the multivariate unsupervised principal component analysis (PCA) followed by the pairwise comparison was used. To select the most predictive/discriminative features, the supervised linear classification model sparse partial least squares regression discriminant analysis (sPLS-DA) was employed. Validation of three differential proteins was performed with protein-specific assays using plasma from a cohort derived from the Newfoundland Osteoarthritis. Results In total, 509 proteins were identified, and 279 proteins were quantified. PCA-pairwise differential comparisons between the 3 groups revealed that 8 proteins were differentially regulated between the OA-obese and/or OA-non-obese with controls. Further experiments using the sPLS-DA revealed two components discriminating OA from controls (component 1, 9 proteins), and OA-obese from OA-non-obese (component 2, 23 proteins). Proteins from component 2 were considered related to obesity. In component 1, compared to controls, 7 proteins were significantly upregulated by both OA groups and 2 by the OA-obese. Among upregulated proteins ... Article in Journal/Newspaper Newfoundland Directory of Open Access Journals: DOAJ Articles Arthritis Research & Therapy 24 1 |
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Open Polar |
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Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Serum biomarkers Proteomics Osteoarthritis Mass spectrometry Diseases of the musculoskeletal system RC925-935 |
spellingShingle |
Serum biomarkers Proteomics Osteoarthritis Mass spectrometry Diseases of the musculoskeletal system RC925-935 Ginette Tardif Frédéric Paré Clarisse Gotti Florence Roux-Dalvai Arnaud Droit Guangju Zhai Guang Sun Hassan Fahmi Jean-Pierre Pelletier Johanne Martel-Pelletier Mass spectrometry-based proteomics identify novel serum osteoarthritis biomarkers |
topic_facet |
Serum biomarkers Proteomics Osteoarthritis Mass spectrometry Diseases of the musculoskeletal system RC925-935 |
description |
Abstract Background Osteoarthritis (OA) is a slowly developing and debilitating disease, and there are no validated specific biomarkers for its early detection. To improve therapeutic approaches, identification of specific molecules/biomarkers enabling early determination of this disease is needed. This study aimed at identifying, with the use of proteomics/mass spectrometry, novel OA-specific serum biomarkers. As obesity is a major risk factor for OA, we discriminated obesity-regulated proteins to target only OA-specific proteins as biomarkers. Methods Serum from the Osteoarthritis Initiative cohort was used and divided into 3 groups: controls (n=8), OA-obese (n=10) and OA-non-obese (n=10). Proteins were identified and quantified from the liquid chromatography–tandem mass spectrometry analyses using MaxQuant software. Statistical analysis used the Limma test followed by the Benjamini-Hochberg method. To compare the proteomic profiles, the multivariate unsupervised principal component analysis (PCA) followed by the pairwise comparison was used. To select the most predictive/discriminative features, the supervised linear classification model sparse partial least squares regression discriminant analysis (sPLS-DA) was employed. Validation of three differential proteins was performed with protein-specific assays using plasma from a cohort derived from the Newfoundland Osteoarthritis. Results In total, 509 proteins were identified, and 279 proteins were quantified. PCA-pairwise differential comparisons between the 3 groups revealed that 8 proteins were differentially regulated between the OA-obese and/or OA-non-obese with controls. Further experiments using the sPLS-DA revealed two components discriminating OA from controls (component 1, 9 proteins), and OA-obese from OA-non-obese (component 2, 23 proteins). Proteins from component 2 were considered related to obesity. In component 1, compared to controls, 7 proteins were significantly upregulated by both OA groups and 2 by the OA-obese. Among upregulated proteins ... |
format |
Article in Journal/Newspaper |
author |
Ginette Tardif Frédéric Paré Clarisse Gotti Florence Roux-Dalvai Arnaud Droit Guangju Zhai Guang Sun Hassan Fahmi Jean-Pierre Pelletier Johanne Martel-Pelletier |
author_facet |
Ginette Tardif Frédéric Paré Clarisse Gotti Florence Roux-Dalvai Arnaud Droit Guangju Zhai Guang Sun Hassan Fahmi Jean-Pierre Pelletier Johanne Martel-Pelletier |
author_sort |
Ginette Tardif |
title |
Mass spectrometry-based proteomics identify novel serum osteoarthritis biomarkers |
title_short |
Mass spectrometry-based proteomics identify novel serum osteoarthritis biomarkers |
title_full |
Mass spectrometry-based proteomics identify novel serum osteoarthritis biomarkers |
title_fullStr |
Mass spectrometry-based proteomics identify novel serum osteoarthritis biomarkers |
title_full_unstemmed |
Mass spectrometry-based proteomics identify novel serum osteoarthritis biomarkers |
title_sort |
mass spectrometry-based proteomics identify novel serum osteoarthritis biomarkers |
publisher |
BMC |
publishDate |
2022 |
url |
https://doi.org/10.1186/s13075-022-02801-1 https://doaj.org/article/cedea55d8a3f4c18b61c342dfbb76726 |
genre |
Newfoundland |
genre_facet |
Newfoundland |
op_source |
Arthritis Research & Therapy, Vol 24, Iss 1, Pp 1-16 (2022) |
op_relation |
https://doi.org/10.1186/s13075-022-02801-1 https://doaj.org/toc/1478-6362 doi:10.1186/s13075-022-02801-1 1478-6362 https://doaj.org/article/cedea55d8a3f4c18b61c342dfbb76726 |
op_doi |
https://doi.org/10.1186/s13075-022-02801-1 |
container_title |
Arthritis Research & Therapy |
container_volume |
24 |
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1 |
_version_ |
1766109800222949376 |