Patent ID: 11946927
Assignee: nan
Field: Pharmaceuticals (Chemistry)
Classification: CPC G  A  Y | IPC A  G

Claim 5:
6. A process of identifying and treating an individual that may have or have a high risk of developing inflammatory bowel disease (IBD) prior to the individual showing symptoms of IBD, the process comprises the steps of:
selecting an individual to be tested, wherein the individual is selected based on the individual not showing symptoms of IBD such that the individual would be diagnosed with having IBD, and Disease Factors of the individual;
obtaining a first blood sample of the selected individual;
using a first prediction panel of predictive target biomarkers for use in predicting the risk of an individual developing IBD, wherein the prediction panel of predictive target biomarkers comprises the predictive target biomarkers of Haptoglobin (HP), Granulocyte Colony Stimulating Factor (GCSF), Resistin (RETN), C-Reactive Protein (CRP), Soluble Interacellular Adhesion Molecule 1 (sICAM1) and Antibody TT and identifies the relationships of sICAM1×HP, GCSF×CRP and GCSF×RETN;
examining the blood sample to obtain a level of each predictive target biomarker listed on the panel of in the prediction panel of predictive target biomarkers;
determining the total level of protein in the blood sample;
using a first prediction logistic regression model for predicting the risk of an individual developing IBD and using the first prediction logistic regression model and the levels of each predictive target biomarker in the first prediction panel of predictive target biomarkers and the total level of protein in the blood sample to calculate a first risk value and determine if the first risk value is above or below the cut-off value for the first prediction logistic regression model;
wherein the first prediction logistic regression model for calculating the risk value of an individual developing IBD is: Log (p/1ip)=−641.8833706+71.65755693×HP−41.87442414×GCSF−45.27490174×RETN−16.22723673×CRP−1.029456032×Antibody TT+14.476981343×sICAM1+5.667294456×(sICAM1×HP)−0.80715758×(GCSF×CRP)−2.288843531×(GCSF×RETN) and wherein the cut-off value is 0.68;
using a second prediction panel of predictive target biomarkers for use in predicting the risk of an individual developing IBD, wherein the second prediction panel of predictive target biomarkers comprises the predictive target biomarkers of sICAM1, GCSF, HP, CRP, RETN and Antibody TT;
using a second prediction logistic regression model for predicting the risk value of an individual developing IBD and the levels of each predictive target biomarker in said second prediction panel of predictive target biomarkers and the total level of protein in the blood sample to calculate a second risk value and determine if the second risk value is above or below the cut-off value for the second prediction logistic regression model, wherein the second prediction logistic regression model is: Log (p/1ip)=1101.571616−0.813305575×deployment−104.1257102×sICAM1−62.63858365×GCSF−5.604142451×sICAM1×GCSF+65.611507602×HP+5.107130532×sICAM1×HP−36.81637743×Antibody TT−1.711888269×GCSF×Antibody TT+0.767135503×CRP+1.770741857×RETN, wherein the cut-off value is 0.56;
wherein if the first risk value for developing IBD is greater than the cut-off value for the first prediction logistic regression model or if the second risk value for developing IBD is greater than the cut-off value for the second prediction logistic regression model, using a prediction logistic regression model, the total level of protein in the blood sample and the level of each predictive target biomarker listed in a prediction panel of predictive target biomarkers for determining the risk of an individual developing Crohn's disease to determine a risk value for the selected individual developing Crohn's disease, wherein the predictive panel of target biomarkers comprises the predictive target biomarkers AutoAb to topisomerase type 1 (SLC70), Angiotensin 1 converting enzyme (AcE), RETN, CRP, GCSF and Antibody TT and identifies the relationships of sICAM1×RETN, GCSF×Antibody TT;
wherein the prediction logistic regression model for determining the risk value for developing Crohn's disease is Log (p/1ip)=−174.4+171.2×SLC70−4.0×AcE−32.2×RETN+1.1×CRP+15.9×GCSF−57.4×Antibody TT+11.6×(sICAM1×RETN)−2.7×(GCSF×Antibody TT), and wherein the cut-off value is 0.5;
wherein if the risk value for developing Crohn's disease is greater than a cut-off value for the prediction logistic regression model for use in determining the risk of an individual developing Crohn's disease, administering a therapy to the selected individual for treating Crohn's disease;
wherein the therapy includes administering a medication for treating Crohn's disease and repeating the process of determining the risk value of the selected individual for developing Crohn's disease and wherein if the risk value remains the same or increases, making modifications to the therapy and repeating the process of determining the risk value for the selected individual developing Crohn's disease and continue with the therapy or modify the therapy until the risk value for the selected individual developing Crohn's disease is below the cut-off value; and
wherein the process includes using a prediction panel of predictive target biomarkers for use in determining the risk of an individual developing ulcerative colitis (UC), wherein the prediction panel of predictive target biomarkers for use in determining the risk of an individual developing UC comprises the predictive target biomarkers of HP, SICAM1 and RETN;
examining the blood sample to obtain a level of each predictive target biomarker in the prediction panel of predictive target biomarkers for use in determining the risk of an individual developing UC;
using a prediction logistic regression model for use in determining the risk of an individual developing UC and using the logistic regression model, the total level of protein in the blood sample and the level of each predictive target biomarker listed in the prediction panel of predictive target biomarkers for use in determining the risk of an individual developing UC to calculate a risk value for the selected individual developing UC, wherein the prediction logistic regression model for determining the risk value of an individual developing UC is Log (p/1−p)=221.7+2.2×RETN+15.1×sICAM1+61.5×HP+4.9×(sICAM1×HP), and the cut-off value is 0.52;
determining if the risk value for the selected individual developing UC is above or below a cut-off value for the prediction logistic regression model for use in determining the risk of an individual developing UC;
wherein if the risk value for the selected individual developing UC is greater than the cut-off value for the prediction logistic regression model for use in determining the risk of an individual developing UC, the process includes the step of administering a therapy for treating UC, wherein the therapy includes administering a medication for treating UC and repeating the process of determining the risk value of the selected individual developing UC, wherein if the risk value remains the same or increases, making modifications to the therapy and repeating the process of determining the risk value of the selected individual developing UC and continue with the therapy or modify the therapy until the risk value for the selected individual developing UC is below the cut off value;
wherein if the first risk value for the selected individual developing IBD is greater than the cut-off value for the first prediction logistic regression model or if the second risk value for the selected individual developing IBD is greater than the cut-off value for the second prediction logistic regression model and the risk value for the selected individual developing Crohn's disease is less than the cut-off value for the prediction logistic regression model for developing Crohn's disease and the risk value for the selected individual developing UC is less than the cut-off value for the prediction logistic regression model for developing UC, the process includes administering a therapy to reduce the risk value of the selected individual developing IBD, wherein the therapy includes administering a medication known to treat IBD; and
wherein if the risk value for the selected individual developing IBD is below the cut-off value for the prediction logistic regression model used for determining the risk value of an individual developing IBD, the process includes using Disease Factors of the selected individual to determine if the process is to be performed again at a future date or administer a therapy to the selected individual when the selected individual is diagnosed with IBD, Crohn's disease or UC for treating IBD, Crohn's disease or UC.