PROCESS AND SYSTEM FOR IDENTIFYING INDIVIDUALS HAVING A HIGH RISK OF INFLAMMATORY BOWEL DISEASE AND A METHOD OF TREATMENT

PROCEDE ET SYSTEME PERMETTANT D'IDENTIFIER DES INDIVIDUS A HAUT RISQUE DE MALADIE INFLAMMATOIRE INTESTINALE, ET METHODE DE TRAITEMENT

English Abstract

A process and system directed to a more effective, individual based treatment regimen which is built on clinical identified predictive target biomarkers associated with predicting the risk of an individual developing IBD and includes one or more predictive panels of prediction target biomarkers that are used to determine the risk of an individual developing IBD for determining if a therapy should be administered to reduce the risk and further determines the efficacy of treating the individual with mesalamine and effectively identifies and validates novel drug targets for new IBD therapeutics, new diagnostics and diagnostics standards for IBD therapeutic strategies.

French Abstract

L'invention concerne une méthode et un système destinés à un protocole de traitement plus efficace et personnalisé, basé sur des biomarqueurs cibles à valeur prédictive identifiés cliniquement qui sont associés à la prédiction du risque pour un individu de développer une MICI, et comprenant un ou plusieurs panels prédictifs de biomarqueurs cibles à valeur prédictive qui sont utilisés pour déterminer le risque pour un individu de développer une MICI, afin de déterminer si un traitement doit être administré pour diminuer le risque, et de plus permettant de déterminer l'efficacité qu'aurait un traitement de l'individu par de la mésalamine et d'identifier et de valider de façon efficace de nouvelles cibles de médicament pour de nouveaux agents thérapeutiques contre les MICI, et de nouvelles normes diagnostiques et de nouveaux standards diagnostiques pour des stratégies thérapeutiques contre les MICI.

Claims

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CLAIMS
1. A process of identifying individuals that may have or have a high
risk of
developing inflammatory bowel disease (IBD) prior to diagnosis of IBD, the
process comprises the steps of:
identifying an individual to be tested;
obtaining a first blood sample of the individual;
selecting a panel of predictive target biomarkers;
examining the blood sample to obtain a level of each predictive target
biomarker listed on the panel of predictive target biomarkers;
determining the total level of protein in the blood sample;
selecting a prediction logistic regression model for predicting the risk of
an individual developing IBD and using the selected logistic regression model
and the levels of each predictive target biomarker and the total level of
protein
in the blood sample to calculate a risk value; and
determining if the risk value is above or below a cut-off value for the
selected prediction logistic regression model;
wherein if the risk value is greater than the cut-off value, the process
includes the step of administering a therapy to reduce the risk of the
individual
developing IBD; and
wherein if the risk value is below the cut-off value the process includes
the step of administering a therapy to monitor the individual for detecting an

increase in the risk of developing IBD.

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2. The process of Claim 1 wherein if the risk value of the individual
developing IBD is greater than the cut-off value, the process includes the
steps
of:
selecting a panel of predictive target biomarkers for use in determining
the risk of the individual developing Crohn's disease;
examining the blood sample to obtain a level of each predictive target
biomarker listed on the panel of predictive target biomarkers for use in
determining the risk of the individual developing Crohn's disease;
selecting a prediction logistic regression model for use in determining
the risk of the individual developing Crohn's disease and using the logistic
regression model and the levels of each predictive target biomarker listed on
the panel of predictive target biomarkers for use in determining the risk of
the
individual developing Crohn's disease and the total level of protein in the
blood
sample to calculate a risk value for developing Crohn's disease;
determining if the risk value for developing Crohn's disease is above or
below a cut-off value for the prediction logistic regression model for use in
determining the risk of the individual developing Crohn's disease;
wherein if the risk value for developing Crohn's disease is greater than
the cut-off value for the prediction logistic regression model for use in
determining the risk of the individual developing Crohn's disease, the process

includes the step of administering a therapy to reduce the risk of developing
Crohn's disease;
wherein if the risk value for developing Crohn's disease is below the cut-
off value for the prediction logistic regression model for use in determining
the
risk of the individual developing Crohn's disease, the process includes the
step
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of administering a therapy to monitor the individual for detecting an increase
in
the risk of developing Crohn's disease.
3. The process of Claim 1 wherein if the risk value for the individual
developing IBD is greater than the cut-off value, the process includes the
steps
of:
selecting a panel of predictive target biomarkers for use in determining
the risk of the individual developing ulcerative colitis (UC);
examining the blood sample to obtain a level of each predictive target
biomarker listed on the panel of predictive target biomarkers for use in
determining the risk of the individual developing UC;
selecting a prediction logistic regression model for use in determining
the risk of the individual developing UC and using the logistic regression
model
and the levels of each predictive target biomarker listed on the panel of
predictive target biomarkers for use in determining the risk of the individual

developing UC and the total level of protein in the blood sample to calculate
a
risk value for developing UC;
determining if the risk value for developing UC is above or below a cut-
off value for the prediction logistic regression model for use in determining
the
risk of the individual developing UC;
wherein if the risk value for developing UC is greater than the cut-off
value for the prediction logistic regression model for use in determining the
risk
of the individual developing UC disease, the process includes the step of
administering a therapy to reduce the risk of developing UC;
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wherein if the risk value for developing UC is below the cut-off value for
the prediction logistic regression model for use in determining the risk of
the
individual developing UC, the process includes the step of administering a
therapy to monitor the individual for detecting an increase in the risk of
developing UC.
4. The process of Claim 1 wherein if the risk value for the individual
developing IBD is greater than the cut-off value, the process includes the
step
of predicting the effectiveness of mesalamine treatment for the individual.
5. The process of Claim 1 wherein if the risk value for the individual
developing IBD is greater than the cut-off value, the process further includes

the step of using a blood sample from the individual to determine if
mesalamine
therapy will be effective or if an alternate therapy should be administered to
the
individual.
6. The process of Claim 1 wherein the prediction target biomarkers panel
for use in predicting the risk of the individual developing IBD, without
environmental change and/or impactful stress being considered, comprises
protein predictive target biomarkers of HP, GCSF, RETN, CRP, sICAM and
antibody target biomarkers antibody to tetanus toxoid and identifies the
relationships of sICAM x HP, GCSF x CRP and GCSF x RETN.
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7. The process of Claim 1 wherein the prediction logistic regression model
for determining the risk value for developing IBD without considering
environmental change and/or impactful stress is: Log (p/lip) = -641.8833706 +
71.65755693 x Haptoglobin ¨ 41.87442414 x GCSF ¨ 45.27490174 x RETN ¨
16.22723673 x CRP ¨ 1.029456032 x Antibody TT + 14.476981343 x sICAM +
5.667294456 x (sICAM x Haptoglobin) ¨ 0.80715758 x (GCSF x CRP) ¨
2.288843531 x (GCSF x RETN).
8. The process of Claim 1 for identifying individuals that may have or have

a high risk of developing inflammatory bowel disease (IBD), wherein the
prediction target biomarkers panel for use in predicting the risk of the
individual
developing IBD with environmental change and/or impact stress being
considered comprises protein predictive target biomarkers of sICAM, GCSF,
HP, CRP, RETN and antibody target biomarkers antibody to tetanus toxoid.
9. The process of Claim 1 wherein the prediction logistic regression model
for determining the risk value for developing IBD with considering
environmental change and/or impacfful stress is: Log (p/1 ip) = 1101.571616 ¨
0.813305575 x deployment ¨ 104.1257102 x sICAM ¨ 62.63858365 x GCSF ¨
5.604142451 x sICAM x GCSF + 65.611507602 x HP + 5.107130532 x sICAM
x HP -36.81637743 x TT ¨ 1.711888269 x GCSF x TT + 0.767135503 x CRP
+ 1.770741857 x RETN.
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10. The process of Claim 2 wherein the panel of predictive target
biomarkers
for use in determining the risk of the individual developing Crohn's disease
comprises protein predictive target biomarkers of SCL70, AcE, RETN, CRP,
GCSF and an antibody target biomarker of antibody to tetanus toxoid (TT) and
identifies the relationships of sICAM x RETN, GCSF x TT,
11. The process of Claim 2 wherein the prediction logistic regression model

for determining the risk value for developing Crohn's disease is Log (p/1ip) =
-
174.4 + 171.2 x SLC70 ¨ 4.0 x AcE ¨ 32.2 x RETN + 1.1 x CRP + 15.9 x GCSF
¨ 57.4 x TT + 11.6 x (sICAM x RETN) ¨ 2.7 x (GCSF x TT).
12. The process of Claim 3 wherein the panel of predictive target
biomarkers
for use in determining the risk of the individual developing UC comprises
protein
predictive target biomarkers of HP, SICAM1 and RETN, and identifies the
relationship of sICAM1 x HP.
13. The process of Claim 3 wherein the prediction logistic regression model

for determining the risk value for developing UC is Log (p/1-p) = 221.7 + 2.2
x
Resistin + 15.1 x sICAM + 61.5 x Haptoglobin + 4.9 x (sICAM x Haptoglobin).
14. A process of identifying individuals that may have or have a high risk
of
developing inflammatory bowel disease (IBD) prior to diagnosis of IBD, the
process comprises the steps of:
identifying an individual to be tested;
obtaining a first blood sample of the individual;

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selecting a panel of predictive target biomarkers for IBD;
examining the blood sample to obtain a level of each predictive target
biomarker listed on the panel of predictive target biomarkers for IBD;
determining the total level of protein in the blood sample;
selecting a prediction logistic regression model for predicting the risk of
an individual developing IBD and using the selected logistic regression model
for predicting the risk of an individual developing IBD and the levels of each

predictive target biomarker listed on the panel of predictive target
biomarkers
for IBD and the total level of protein in the blood sample to calculate a risk
value
for the individual developing IBD; and
determining if the risk value for the individual developing IBD is above or
below a cut-off value for the selected prediction logistic regression model
for
predicting the risk of an individual developing IBD;
wherein if the risk value for the individual developing IBD is below the
cut-off value the process includes the step of determining if a therapy to
monitor
the individual for detecting an increase in the risk of developing 1130 should
be
administered;
wherein if the risk value for the individual developing IBD is greater than
the cut-off value, the process includes the steps of:
selecting a panel of predictive target biomarkers for use in determining
the risk of the individual developing Crohn's disease;
examining the blood sample to obtain a level of each predictive target
biomarker listed on the panel of predictive target biomarkers for use in
determining the risk of the individual developing Crohn's disease;
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selecting a prediction logistic regression model for use in determining
the risk of the individual developing Crohn's disease and using the logistic
regression model and the levels of each predictive target biomarker listed on
the panel of predictive target biomarkers for use in determining the risk of
the
individual developing Crohn's disease and the total level of protein in the
blood
sample to calculate a risk value for developing Crohn's disease;
determining if the risk value for developing Crohn's disease is above or
below a cut-off value for the prediction logistic regression model for use in
determining the risk of the individual developing Crohn's disease;
wherein if the risk value for developing Crohn's disease is greater than
the cut-off value for the prediction logistic regression model for use in
determining the risk of the individual developing Crohn's disease, the process

includes the step of administering a therapy to reduce the risk of developing
Crohn's disease; and
wherein if the risk value for developing Crohn's disease is below the cut-
off value for the prediction logistic regression model for use in determining
the
risk of the individual developing Crohn's disease, the process includes the
steps
of selecting a panel of predictive target biomarkers for use in determining
the
risk of the individual developing ulcerative colitis (UC);
examining the blood sample to obtain a level of each predictive target
biomarker listed on the panel of predictive target biomarkers for use in
determining the risk of the individual developing UC;
selecting a prediction logistic regression model for use in determining
the risk of the individual developing UC and using the logistic regression
model
and the levels of each predictive target biomarker listed on the panel of
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predictive target biomarkers for use in determining the risk of the individual

developing UC and the total level of protein in the blood sample to calculate
a
risk value for developing UC;
determining if the risk value for developing UC is above or below a cut-
off value for the prediction logistic regression model for use in determining
the
risk of the individual developing UC;
wherein if the risk value for developing UC is greater than the cut-off
value for the prediction logistic regression model for use in determining the
risk
of the individual developing UC disease, the process includes the step of
administering a therapy to reduce the risk of developing UC; and
wherein if the risk value for developing UC is below the cut-off value for
the prediction logistic regression model for use in determining the risk of
the
individual developing UC, the process includes the step of determining if a
therapy to monitor the individual for detecting an increase in the risk of
developing UC should be adminstered.
15. The process of Claim 14 wherein if the risk value for the individual
developing IBD is greater than the cut-off value, the process includes the
step
of predicting the effectiveness of mesalamine treatment for the individual.
16. The process of Claim 14 wherein if the risk value for the individual
developing IBD is greater than the cut-off value, the process further includes

the step of using a blood sample from the individual to determine if
mesalamine
therapy will be effective or if an alternate therapy should be administered to
the
individual.
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17. The process of Claim 14 wherein the prediction target biomarkers panel
for use in predicting the risk of the individual developing IBD, without
environmental change and/or impactful stress being considered, comprises
protein predictive target biomarkers of HP, GCSF, RETN, CRP, sICAM and
antibody target biomarker of antibody to tetanus toxoid and identifies the
relationships of sICAM x HP, GCSF x CRP and GCSF x RETN.
18. The process of Claim 14 wherein the prediction logistic regression
model
for determining the risk value for developing IBD without considering
environmental change and/or impactful stress is: Log (p/1 ip) = -641.8833706 +

71.65755693 x Haptoglobin ¨ 41.87442414 x GCSF ¨ 45.27490174 x RETN ¨
16.22723673 x CRP ¨ 1.029456032 x Antibody TT + 14.476981343 x sICAM +
5.667294456 x (sICAM x Haptoglobin) ¨ 0.80715758 x (GCSF x CRP) ¨
2.288843531 x (GCSF x RETN).
19. The process of Claim 14 for identifying individuals that may have or
have
a high risk of developing inflammatory bowel disease (IBD), wherein the
prediction target biomarkers panel for use in predicting the risk of the
individual
developing IBD with environmental change and/or impacfful stress being
considered comprises protein predictive target biomarkers of sICAM, GCSF,
HP, CRP, RETN and antibody target biomarkers antibody to tetanus toxoid.
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20 The process of Claim 14 wherein the prediction logistic regression
model
for determining the risk value for developing IBD with considering of
environmental change and/or impactful stress is: Log (p/1 ip) = 1101.571616 ¨
0.813305575 x deployment ¨ 104.1257102 x sICAM ¨ 62.63858365 x GCSF ¨
5.604142451 x sICAM x GCSF + 65.611507602 x HP + 5.107130532 x sICAM
x HP -36.81637743 x TT ¨ 1.711888269 x GCSF x TT + 0.767135503 x CRP
+ 1.770741857 x RETN.
21. The process of Claim 14 wherein the panel of predictive target
biomarkers for use in determining the risk of the individual developing
Crohn's
disease comprises protein predictive target biomarkers of SCL70, AcE, RETN,
CRP, GCSF and antibody target biomarker of antibody to tetanus toxoid (TT)
and identifies the relationships of sICAM x RETN, GCSF x TT.
22. The process of Claim 14 wherein the prediction logistic regression
model
for determining the risk value for developing Crohn's disease is Log (p/1ip) =
-
174.4 + 171.2 x SLC70 ¨ 4.0 x AcE ¨ 32.2 x RETN + 1.1 x CRP + 15.9 x GCSF
¨ 57.4 x TT + 11.6 x (sICAM x RETN) ¨ 2.7 x (GCSF x TT).
23. The process of Claim 14 wherein the panel of predictive target
biomarkers for use in determining the risk of the individual developing UC
comprises protein predictive target biomarkers of HP, SICAM1 and RETN, and
identifies the relationship of sICAM1 x HP.

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24. The process of Claim 14 wherein the prediction logistic regression
model
for determining the risk value for developing UC is Log (p/1-p) = 221.7 + 2.2
x
Resistin + 15.1 x sICAM + 61.5 x Haptoglobin + 4.9 x (sICAM x Haptoglobin).
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Description

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Description
PROCESS AND SYSTEM FOR IDENTIFYING INDIVIDUALS HAVING A

Representative Drawing