Serum metabolomic profiling identifies potential biomarkers in arthritis in older adults: an exploratory study
Background Seronegative elderly-onset rheumatoid arthritis (EORA)neg and polymyalgia rheumatica (PMR) have similar clinical characteristics making them difficult to distinguish based on clinical features. We hypothesized that the study of serum metabolome could identify potential biomarkers of PMR vs. $ EORA^{neg} $. Methods Arthritis in older adults (ARTIEL) is an observational prospective cohort with patients older than 60 years of age with newly diagnosed arthritis. Patients’ blood samples were compared at baseline with 18 controls. A thorough clinical examination was conducted. A Bruker Avance 600 MHz spectrometer was used to acquire Nuclear Magnetic Resonance (NMR) spectra of serum samples. Chenomx NMR suite 8.5 was used for metabolite identification and quantification.Student t-test, one-way ANOVA, binary linear regression and ROC curve, Pearson’s correlation along with pathway analyses were conducted. Results Twenty-eight patients were diagnosed with $ EORA^{neg} $ and 20 with PMR. $ EORA^{neg} $ patients had a mean disease activity score (DAS)-Erythrocyte Sedimentation Rate (ESR) of 6.21 ± 1.00. All PMR patients reported shoulder pain, and 90% reported pelvic pain. Fifty-eight polar metabolites were identified. Of these, 3-hydroxybutyrate, acetate, glucose, glycine, lactate, and o-acetylcholine (o-ACh), were significantly different between groups. Of interest, IL-6 correlated with different metabolites in PMR and $ EORA^{neg} $ suggesting different inflammatory activated pathways. Finally, lactate, o-ACh, taurine, and sex (female) were identified as distinguishable factors of PMR from $ EORA^{neg} $ with a sensitivity of 90%, specificity of 92.3%, and an AUC of 0.925 (p < 0.001). Conclusion These results suggest that $ EORA^{neg} $ and PMR have different serum metabolomic profiles that might be related to their pathobiology and can be used as biomarker to discriminate between both diseases..
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2023 |
|---|---|
| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:19 |
|---|---|
| Enthalten in: |
Metabolomics - 19(2023), 4 vom: 06. Apr. |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Cedeno, Martha [VerfasserIn] |
|---|
| Links: |
Volltext [lizenzpflichtig] |
|---|
| Themen: |
|---|
| Anmerkungen: |
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
|---|
| doi: |
10.1007/s11306-023-02004-y |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
SPR049968408 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | SPR049968408 | ||
| 003 | DE-627 | ||
| 005 | 20230422064718.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 230407s2023 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1007/s11306-023-02004-y |2 doi | |
| 035 | |a (DE-627)SPR049968408 | ||
| 035 | |a (SPR)s11306-023-02004-y-e | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Cedeno, Martha |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Serum metabolomic profiling identifies potential biomarkers in arthritis in older adults: an exploratory study |
| 264 | 1 | |c 2023 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a Computermedien |b c |2 rdamedia | ||
| 338 | |a Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. | ||
| 520 | |a Background Seronegative elderly-onset rheumatoid arthritis (EORA)neg and polymyalgia rheumatica (PMR) have similar clinical characteristics making them difficult to distinguish based on clinical features. We hypothesized that the study of serum metabolome could identify potential biomarkers of PMR vs. $ EORA^{neg} $. Methods Arthritis in older adults (ARTIEL) is an observational prospective cohort with patients older than 60 years of age with newly diagnosed arthritis. Patients’ blood samples were compared at baseline with 18 controls. A thorough clinical examination was conducted. A Bruker Avance 600 MHz spectrometer was used to acquire Nuclear Magnetic Resonance (NMR) spectra of serum samples. Chenomx NMR suite 8.5 was used for metabolite identification and quantification.Student t-test, one-way ANOVA, binary linear regression and ROC curve, Pearson’s correlation along with pathway analyses were conducted. Results Twenty-eight patients were diagnosed with $ EORA^{neg} $ and 20 with PMR. $ EORA^{neg} $ patients had a mean disease activity score (DAS)-Erythrocyte Sedimentation Rate (ESR) of 6.21 ± 1.00. All PMR patients reported shoulder pain, and 90% reported pelvic pain. Fifty-eight polar metabolites were identified. Of these, 3-hydroxybutyrate, acetate, glucose, glycine, lactate, and o-acetylcholine (o-ACh), were significantly different between groups. Of interest, IL-6 correlated with different metabolites in PMR and $ EORA^{neg} $ suggesting different inflammatory activated pathways. Finally, lactate, o-ACh, taurine, and sex (female) were identified as distinguishable factors of PMR from $ EORA^{neg} $ with a sensitivity of 90%, specificity of 92.3%, and an AUC of 0.925 (p < 0.001). Conclusion These results suggest that $ EORA^{neg} $ and PMR have different serum metabolomic profiles that might be related to their pathobiology and can be used as biomarker to discriminate between both diseases. | ||
| 650 | 4 | |a Metabolomics |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a PMR |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Seronegative RA |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a NMR |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Murillo-Saich, Jessica |4 aut | |
| 700 | 1 | |a Coras, Roxana |4 aut | |
| 700 | 1 | |a Cedola, Francesca |4 aut | |
| 700 | 1 | |a Brandy, Anahy |4 aut | |
| 700 | 1 | |a Prior, Agueda |4 aut | |
| 700 | 1 | |a Pedersen, Anders |4 aut | |
| 700 | 1 | |a Mateo, Lourdes |4 aut | |
| 700 | 1 | |a Martinez-Morillo, Melania |4 aut | |
| 700 | 1 | |a Guma, Monica |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Metabolomics |d Berlin : Springer, 2005 |g 19(2023), 4 vom: 06. Apr. |w (DE-627)SPR018692605 |w (DE-600)2182289-X |x 1573-3890 |7 nnns |
| 773 | 1 | 8 | |g volume:19 |g year:2023 |g number:4 |g day:06 |g month:04 |
| 856 | 4 | 0 | |u https://dx.doi.org/10.1007/s11306-023-02004-y |z lizenzpflichtig |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_SPRINGER | ||
| 951 | |a AR | ||
| 952 | |d 19 |j 2023 |e 4 |b 06 |c 04 | ||