Biomarkers and Methods for Measuring and Monitoring Inflammatory Disease Activity

Abstract

Biomarkers useful for diagnosing and assessing inflammatory disease are provided, along with kits for measuring their expression. The invention also provides predictive models, based on the biomarkers, as well as computer systems, and software embodiments of the models for scoring and optionally classifying samples. The biomarkers include at least two biomarkers selected from the DAIMRK group and the score is a disease activity index (DAI).

1 . A method for scoring a sample, said method comprising:
 receiving a first dataset associated with a first sample obtained from a first subject, wherein said first dataset comprises quantitative data for at least two markers selected from the group consisting of: apolipoprotein A-I (APOA 1); apolipoprotein C-III (APOC3); calprotectin (heteropolymer of protein subunits S 100A8 and S 100A9); chemokine (C—C motif) ligand 22 (CCL22); chitinase 3-like 1 (cartilage glycoprotein-39) (CHI3L1); C-reactive protein, pentraxin-related (CRP); epidermal growth factor (beta-urogastrone) (EGF); intercellular adhesion molecule 1 (ICAM1); ICTP; interleukin 18 (interferon-gamma-inducing factor) (IL18); interleukin 1, beta (IL1B); interleukin 1 receptor antagonist (IL1RN); interleukin 6 (interferon, beta 2) (IL6); interleukin 6 receptor (IL6R); interleukin 8 (IL8); keratan sulfate; leptin (LEP); matrix metallopeptidase 1 (interstitial collagenase) (MMP1); matrix metallopeptidase 3 (stromelysin 1, progelatinase) (MMP3); pyridinoline (PYD); resistin (RETN); serum amyloid A1 (SAA1); tumor necrosis factor receptor superfamily, member 1A (TNFRSF1A); tumor necrosis factor (ligand) superfamily, member 13b (TNFSF13B, or BAFF); vascular cell adhesion molecule 1 (VCAM1); and, vascular endothelial growth factor A (VEGFA); and   determining, a first DAI score from said first dataset using an interpretation function, wherein said first DAI score provides a quantitative measure of inflammatory disease activity in said first subject.   
     
     
         2 . The method of  claim 1 , wherein said first dataset is obtained by a method comprising:
 obtaining said first sample from said first subject, wherein said first sample comprises a plurality of analytes;   contacting said first sample with a reagent;   generating a plurality of complexes between said reagent and said plurality of analytes; and   detecting said plurality of complexes to obtain said first dataset associated with said first sample, wherein said first dataset comprises quantitative data for said least two markers.   
     
     
         3 . The method of  claim 1 , wherein said inflammatory disease activity is rheumatoid arthritis disease activity and further comprising predicting a Sharp score change from said first subject, based on said DAI score. 
     
     
         4 . The method of  claim 1 , wherein said first DAI score is predictive of a clinical assessment. 
     
     
         5 . The method of  claim 4 , wherein said interpretation function is based on a predictive model. 
     
     
         6 . The method of  claim 4 , wherein said clinical assessment is selected from the group consisting of: a DAS, a DAS28, a DAS28-CRP, a Sharp score, a tender joint count (TJC), and a swollen joint count (SJC). 
     
     
         7 .- 8 . (canceled) 
     
     
         9 . The method of  claim 6 , wherein DAS28-CRP comprises a component selected from the group consisting of tender joint count (TJC), the swollen joint count (SJC), and the patient global health assessment. 
     
     
         10 . The method of  claim 4 , wherein said clinical assessment is TJC and said first dataset comprises quantitative data for at least one marker selected from the group consisting of CHI3L1, EGF, IL6, LEP, SAA1, TNFRSF1A, VCAM1, and VEGFA. 
     
     
         11 . The method of  claim 4 , wherein said clinical assessment is SJC and said first dataset comprises quantitative data for at least one marker selected from the group consisting of CHI3L1, EGF, IL6, LEP, SAA1, TNFRSF1A, VCAM1, and VEGFA. 
     
     
         12 . The method of  claim 4 , wherein said clinical assessment is patient global health assessment and said first dataset comprises quantitative data for at least one marker selected from the group consisting of EGF, IL6, LEP, MMP1, MMP3, RETN, SAA1, TNFRSF1A, VCAM1, and VEGFA. 
     
     
         13 . The method of  claim 5 , wherein said predictive model is developed using an algorithm comprising a forward linear stepwise regression algorithm; a Lasso shrinkage and selection method for liner regression; or an Elastic Net for regularization and variable selection for linear regression. 
     
     
         14 . The method of  claim 1 , further comprising:
 receiving a second dataset associated with a second sample obtained from said first subject, wherein said first sample and said second sample are obtained from said first subject at different times;   determining a second DAI score from said second dataset using said interpretation function; and   comparing said first DAI score and said second DAI score to determine a change in said DAI scores, wherein said change indicates a change in said inflammatory disease activity in said first subject.   
     
     
         15 . The method of  claim 14 , wherein said inflammatory disease activity is rheumatoid arthritis activity and said indicated change in rheumatoid arthritis disease activity indicates the presence, absence or extent of the subject's response to a therapeutic regimen. 
     
     
         16 . The method of  claim 14 , further comprising determining a rate of said change in DAI scores, wherein said rate indicates the extent of said first subject's response to a therapeutic regimen. 
     
     
         17 . The method of  claim 14 , wherein said inflammatory disease activity is rheumatoid arthritis disease activity and further comprising predicting a Sharp score change rate for said first subject, based on said indicated change in rheumatoid arthritis disease activity. 
     
     
         18 . The method of  claim 17 , further comprising determining a prognosis for rheumatoid arthritis progression in said first subject based on said predicted Sharp score change rate. 
     
     
         19 . The method of  claim 1 , wherein said inflammatory disease is rheumatoid arthritis. 
     
     
         20 .- 231 . (canceled) 
     
     
         232 . The method of  claim 19 , further comprising selecting an inflammatory disease therapeutic regimen based on said DAI score. 
     
     
         233 . The method of  claim 19 , further comprising determining an inflammatory disease treatment course based on the DAI score.