Methods for predicting patient response to DMARDs
The present invention provides a method for predicting whether a patient having, suspected of having, or at risk of developing an inflammatory condition will respond to treatment with a disease-modifying antirheumatic drug (DMARD) comprising measuring the level of at least one specialized pro-resolving mediator (SPM) in a DMARD naïve patient sample and classifying the patient as a predicted DMARD responder or a predicted DMARD non-responder. The present invention also provides a method of assessing the efficacy of a disease-modifying antirheumatic drug (DMARD) for use in the treatment of an inflammatory condition in a patient. The present invention also provides a method of predicting which rheumatoid arthritis pathotype a patient having, suspected of having, or at risk of developing rheumatoid arthritis will develop.
1 . A method treating an inflammatory condition comprising:
(i) measuring the level of at least one specialized pro-resolving mediator (SPM) in a disease-modifying antirheumatic drug (DMARD) naïve patient sample from a patient having the inflammatory condition and classifying the patient as a predicted DMARD responder or a predicted DMARD non-responder; and
(ii) administering to the patient:
(a) a non-biological DMARD if the patient is a predicted DMARD responder; or
(b) a biological DMARD if the patient is a predicted DMARD non-responder.
2 . The method of claim 1 , comprising measuring the levels of at least two SPM and inputting the levels of the at least two SPM into a trained machine learning algorithm, the trained machine learning algorithm being arranged to:
(i) compare the levels of the at least two SPM from the sample with the levels of the same at least two SPM in a database, and
(ii) output whether the patient is a DMARD responder or a DMARD non-responder.
3 . The method of claim 2 wherein the trained machine learning algorithm is trained based on training data, the training data comprising:
first data including lipid mediator profiles for a plurality of patients; and
second data identifying whether each of the plurality of patients is a DMARD responder or a DMARD non-responder.
4 . The method according to claim 1 , wherein the inflammatory condition is rheumatoid arthritis.
5 . The method according to claim 1 , wherein the patient is classified as a predicted DMARD non-responder when the level of the at least one SPM is increased compared to a control.
6 . The method according to claim 1 , further comprising measuring the level of at least one pro-inflammatory eicosanoid, and wherein an increase in the level of at least one pro-inflammatory eicosanoid compared to a control predicts that the patient is a DMARD non-responder.
7 . The method of claim 6 , wherein the pro-inflammatory eicosanoid is PGD 2 and/or PGE 2 .
8 . The method of claim 1 , wherein the at least one SPM is a DHA metabolite, n-3 DPA metabolite, AA metabolite and/or an EPA metabolite.
9 . The method of claim 1 , wherein the at least one SPM is RvT3; RvT4; RvE2; RvD1; MaR1 n-3 DPA ; RvT4; 14-oxo-MaR1; 17R-RvD3; 15R-LXB 4 ; RvD3; RvD4; TxB 2 ; LTB 4 ; 20-COOH-LTB 4 ; LTE 4 ; 10S, 17S,diHDHA (PDX); 17R-PD1; 15R-LXA 4 ; PGE 2 ; PGD 2 ; 10S, 17S-diHDPA; 5S, 12S-diHETE; 4S, 14S-diHDHA; and/or 5S, 15S-diHETE.
10 . The method of claim 1 , wherein the at least one SPM is RvD4, MaR1 n-3 DPA , 10S, 17S-diHDPA and/or 15R-LXA 4 .
11 . The method of claim 1 , wherein the at least one SPM is:
(a) involved in coordinating the host response during ongoing inflammation; and/or
(b) a mediator linked with pain modulation.
12 . The method of claim 1 , further comprising measuring one or more markers of ALOX5 activity; one or more markers of ALOX12 activity and/or one or more markers of ALOX15 activity.
13 . The method of claim 12 , wherein:
(a) the one or more markers of ALOX5 activity are selected from the group consisting of 5-HETE, 5HEPE, 7-HDPA and 7-HDHA;
(b) the one or more markers of ALOX12 activity are selected from the group consisting of 14-HDPA and 14-HDHA; and/or
(c) the one or more markers of ALOX15 activity are selected from the group consisting of 17-HDPA, 17-HDHA, 15-HEPE and 15-HETE.
14 . The method of claim 1 , comprising measuring the levels of at least two SPM and wherein a multivariate analysis is used to detect an increase in the levels of the at least two SPM compared to controls.
15 . The method of claim 1 , comprising measuring the levels of at least two SPM and wherein a trained machine learning model is used to detect an increase in the levels of the at least two SPM compared to controls.
16 . The method of claim 1 , wherein the sample is a plasma sample or a whole blood sample.
17 . The method of claim 1 , wherein the level of the at least one SPM is measured using liquid chromatography tandem mass spectrometry (LC-MS/MS).
18 . The method of claim 1 , wherein the level of the at least one SPM is measured using an immunoassay.
19 . The method of claim 1 , wherein the at least one SPM is at least four SPM wherein the at least four SPM comprise RvD4, 10S, 17S-diHDPA, 15R-LXA 4 and MaR1 n-3 DPA .
20 . The method of claim 1 , wherein the at least one SPM is RvD4, 5S, 12S-diHETE, 4S, 14S-diHDHA, MaR1 n-3 DPA , 10S, 17S-diHDPA and/or 15R-LXA 4 .
21 . The method of claim 1 , wherein the at least one SPM is at least six SPM wherein the at least six SPM comprise (i) RvD4; (ii) 5S, 12S-diHETE; (iii) 4S, 14S-diHDHA; (iv) MaR1 n-3 DPA ; (v) 10S, 17S-diHDPA; and (vi) 15R-LXA 4 .
22 . The method of claim 1 , wherein the DMARD is a non-biological DMARD selected from the group consisting of methotrexate, aspiring, hydroxychloroquine, leflunomide, sulfasalazine, gold salts, azathioprine, and cyclosporine.