POS1109 PUTATIVE ROLE OF THE HISTIDINE AND TRYPTOPHAN BIOCHEMICAL PATHWAYS IN THE MODE OF ACTION OF UPADACITINIB IN PATIENTS WITH ANKYLOSING SPONDYLITIS
Notice bibliographique
Résumé
Background Upadacitinib (UPA) 15 mg QD is efficacious in patients with active ankylosing spondylitis (AS) exhibiting inadequate responses to nonsteroidal anti-inflammatory drugs (NSAIDs-IR).[1] Objectives We determined the impact of UPA on the global metabolome in these patients. Methods Baseline (BL), weeks 4, and 14 serum samples were obtained from a subset of patients enrolled in SELECT-AXIS1 (PBO, n = 59 out of 94; UPA, n = 59 out of 93). Patients met the modified New York AS criteria and had active disease at BL. Samples were processed using dansyl-12C-labeling kits or DmPA-12C-labeling kits for each chemical-group channel and analyzed by LC-MS–based metabolomics. Data analysis was performed using a commercial software and metabolite identification was done using a commercial reference database.[2] Tier 1 and 2 metabolites matched single compounds from a labeled metabolite library and a linked identity library, respectively. Tier 3 metabolites matched more than 1 compound. Differentially modulated metabolites (DMM) were identified using a mixed linear model measuring change from BL for each treatment group (selection criteria, absolute Log10 fold change ≥ 0.079, and false discovery rate ≤ 0.1). Pathway enrichment analyses were conducted using a dedicated software.[3] Relationships between metabolite level changes, and clinical changes were assessed by Pearson’s correlation. Results We detected a total of 8020 distinct metabolites (ie, ≥ 80% detectability across timepoints within each treatment group) across the global metabolome. From these 8020 metabolites, we identified 289 and 221 DMM at weeks 4 and 14 in the UPA group vs 32 and 89 in the PBO group, respectively. Most DMM in the UPA group (187 and 144 at weeks 4 and 14, respectively) belonged to the Tier 3 identification category, and 51 and 40 at weeks 4 and 14, respectively, belonged to the Tier 1 and 2 categories. Pathway enrichment suggests UPA affects the histidine and tryptophan biochemical pathways (Figure 1), consistent with increases in metabolites observed in the UPA group. Increases in histidine and tryptophan levels were significantly associated with an improvement in CRP levels and Ankylosing Spondylitis Disease Activity Score-CRP scores (P ≤.05). Increases in histidine levels were also associated with the improvement in MRI Spondyloarthritis Research Consortium of Canada Spine indices. Conclusion This is the first comprehensive metabolome analysis of serum samples collected from patients with AS treated with UPA. Data highlight the promise of advanced metabolomics to elucidate therapeutic agent’s mode of action in AS. The putative effect of UPA on the tryptophan biochemical pathway is of particular interest because the tryptophan/kynurenine pathway is associated with chronic pain[4] and is perturbed toward the degradation of tryptophan in patients with AS.[5] We hypothesize that the increase in tryptophan and histidine may be related to the mode of action of UPA in NSAID-IR patients with AS. References [1]Van der Heijde D, et al. Lancet. 2019;394:2108. [2]Blackmore D, et al. Metabolomics. 2020;16:10. [3]Pang Z, et al. Nucleic Acids Res. 2021;49:W388. [4]Jovanovic F, et al. Int J Mol Sci. 2020;21:6045. [5]Eryavuz Onmaz D, et al. Int Immunopharmacol. 2021;99:108018. Acknowledgements Medical writing assistance, funded by AbbVie, was provided by Steve Page, PhD, and Lamara D. Shrode, PhD, CMPP™, of JB Ashtin. Disclosure of Interests Thierry Sornasse Shareholder of: AbbVie, Employee of: AbbVie, Liang Li Shareholder of: Founder of Nova Medical Testing Inc. (NovaMT)., Consultant of: Meliomics Inc., Grant/research support from: Matching fund from NovaMT as part of a Mitacs PDF support and receives grant royalty payment from Bruker on a licensed QTOF Metabolomics Technology., Employee of: founder of Nova Medical Testing Inc. (NovaMT)., Shuang Zhao: None declared, Xiaohang Wang: None declared, Fang Cai Shareholder of: AbbVie, Employee of: AbbVie, Yingtao Bi Shareholder of: AbbVie, Employee of: AbbVie, In-Ho Song Shareholder of: AbbVie, Employee of: AbbVie, Stephanie Wichuk: None declared, Robert Lambert: None declared, Walter P Maksymowych Consultant of: AbbVie, Bristol Myers Squibb, Boehringer, Celgene, Eli Lilly, Galapagos, Janssen, Novartis, Pfizer, and UCB, Grant/research support from: AbbVie, Novartis, Pfizer, and UCB.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».