Diabetes-related biomarkers and methods of use thereof

• US 20090012716A1
• Filed: 04/18/2008
• Published: 01/08/2009
• Est. Priority Date: 10/11/2005
• Status: Active Grant

• Current Assignee: True Health Diagnostics LLC (True Health Group LLC)
• Original Assignee: Tethys Bioscience, Inc.
• Inventors: Arensdorf, Patrick A., McKenna, Michael P., Urdea, Michael S.
• Granted Patent: US 8,119,358 B2
• Time in Patent Office: Days
• US Class Current: 702/19
• CPC Class Codes: G01N 2800/042 Disorders of carbohydrate metabolism, e.g. diabetes, glucose metabolism
• CPC Class Codes: G01N 2800/52 Predicting or monitoring the response to treatment, e.g. for selection of therapy based on assay results in personalised medicine; Prognosis
• CPC Class Codes: G01N 33/48714 for determining substances foreign to the organism, e.g. drugs or heavy metals drugs by chemical analysis G01N33/94
• CPC Class Codes: G01N 33/6893 related to diseases not provided for elsewhere
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment
• CPC Class Codes: Y02A 90/10 Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Abstract

The invention describes biomarkers which can be used to predict the likelihood that an individual will develop Diabetes. The biomarkers can also be used to screen large groups in order to identify individuals at risk of developing Diabetes.

Claims

1-108. -108. (canceled)

109. A method with a predetermined level of predictability for assessing a risk of development of Diabetes Mellitus or a pre-diabetic condition in a subject comprising:

a.) measuring the level of an effective amount of two or more ALLDBRISKS selected from the group consisting of ALLDBRISKS 1-20, 22-112, 114-125, 127, 128, 130-208, 210-232 and 236-267 in a sample from a subject, and

b.) measuring a clinically significant alteration in the level of the two or more ALLDBRISKS in the sample, wherein the alteration indicates an increased risk of developing Diabetes Mellitus or a pre-diabetic condition in the subject.

110. The method of claim 109, wherein the level of an effective amount of five or more ALLDBRISKS is measured.

111. A method for evaluating the risk of developing a diabetic condition in a subject comprising:

a.) measuring at least two biomarkers in a sample from the subject, selected from the biomarkers within the group consisting of Core Biomarkers I and Core Biomarkers II and measuring at least a third biomarker from any of the biomarkers listed in Table 4; and

b.) evaluating the risk of developing a diabetic condition in the subject using the biomarker measurements.

112. A method comprising:

obtaining biomarker measurement data from at least three biomarkers selected from ALLDBRISKS, CPS and TLRFs of Table 1, Table 2 and Table 3, wherein the biomarker measurement data is representative of measurements of biomarkers in at least one biological sample from an individual; and

evaluating a diabetic condition or risk of developing a diabetic condition in the individual based on an output from a model, wherein the model is executed based on an input of the biomarker measurement data.

113. The method of claim 112, wherein said biomarkers comprise:

(i) at least three biomarkers, where three of the biomarkers are selected from one of sets of the RDMARKER sets listed in FIG. 6A;

or

(ii) at least four biomarkers selected from RDMARKERS;

or

(iii) at least three biomarkers, where two biomarkers are selected from ADIPOQ;

CRP;

GLUCOSE;

GPT;

HBA1C;

HSPA1B;

IGFBP1;

IGFBP2;

INS, LEP; and

TRIG; and

one biomarker is selected from the ALLDBRISKS, CPs, and TLRFs of Table 1, Table 2, and Table 3;

or

(iv) at least three biomarkers, where at least one biomarker is selected from GLUCOSE and HBA1C;

at least one biomarker is selected from ADIPOQ, CRP, GPT, HSPA1B, IGFBP1, IGFBP2, INS, LEP, and TRIG; and

at least one biomarker is selected from the ALLDBRISKS, CPs, and TLRFs of Table 1, Table 2, and Table 3;

or

(v) at least three biomarkers, where at least two biomarkers are selected from the biomarkers within the group consisting of Core Biomarkers I and Core Biomarkers II and at least a third biomarker is selected from any of the biomarkers listed in Table 4.

114. In a method of evaluating the risk of developing a diabetic condition in a subject by measuring one or more of Clinical Parameters and Traditional Laboratory Risk Factors, the improvement comprising:

obtaining biomarker measurement data that is representative of measurements of at least two biomarkers in a sample from the subject, wherein the at least two biomarkers are selected from the group consisting of Core Biomarkers I and Core Biomarkers II; and

evaluating the risk of developing a diabetic condition in the subject according to the method of claim 112.

115. The method of claim 112, wherein evaluating risk comprises computing an index value using the model based on the biomarker measurement data, wherein the index value is correlated with risk of developing a diabetic condition in the subject.

116. The method of claim 112, wherein the diabetic condition is Type 2 Diabetes.

117. The method of claim 112, wherein the diabetic condition is pre-Diabetes or gestational diabetes.

118. The method of claim 112, wherein the diabetic condition is selected from the group consisting of Metabolic Syndrome, Impaired Glucose Tolerance, and Impaired Fasting Glycemia.

119. The method of claim 112, wherein evaluating risk comprises computing a Diabetes risk score.

120. The method of claim 119, further comprising reporting the Diabetes risk score to at least one entity selected from:

the individual, an organization, or a database.

121. The method of claim 119, wherein the Diabetes risk score is a risk score for type II Diabetes.

122. The method of claim 119, further comprising computing a second Diabetes risk score for the individual, wherein the first and second Diabetes risk scores are based on biomarker measurement data representing measurements of biomarker status at different points in time.

127. The method of claim 112, wherein said biomarkers comprise at least three biomarkers selected from one of the sets of the RDMARKER sets listed in FIG. 6A.

128. The method of claim 112, wherein the biomarkers comprise at least four biomarkers selected from RDMARKERS.

129. The method of claim 112, wherein the biomarkers comprise at least five biomarkers selected from RDMARKERS, and preferably at least six, or at least seven, or at least eight, or at least nine, or at least ten, or eleven biomarkers selected from RDMARKERS.

130. The method of claim 112, wherein said biomarkers comprise at least three biomarkers,

where at least two biomarkers are selected from ADIPOQ;

CRP;

GLUCOSE;

GPT;

HBA1C;

HSPA1B;

IGFBP1;

IGFBP2;

INS;

LEP; and

TRIG; and

where at least one biomarker is selected from the ALLDBRISKS, CPs, and TLRFs of Table 1, Table 2, and Table 3.

131. The method of claim 112, wherein said biomarkers comprise at least three biomarkers,

where at least one biomarker is selected from GLUCOSE and HBA1C;

at least one biomarker is selected from ADIPOQ, CRP, GPT, HSPA1B, IGFBP1, IGFBP2, INS, LEP, and TRIG; and

at least one biomarker is selected from the ALLDBRISKS, CPs, and TLRFs of Table 1, Table 2, and Table 3.

132. The method of claim 112, wherein said biomarkers comprises at least three biomarkers,

wherein at least two biomarkers are selected from the biomarkers within the group consisting of Core Biomarkers I and Core Biomarkers II, and

at least a third biomarker is selected from any of the biomarkers listed in Table 4.

133. The method of claim 132, wherein at least three biomarkers are selected from the biomarkers within the group consisting of Core Biomarkers I and Core Biomarkers II.

134. The method of claim 132, wherein at least 2 of the biomarkers are selected from the biomarkers within Core Biomarkers I.

135. The method of claim 134, wherein at least two of the biomarkers are selected from the biomarkers within Core Biomarkers II.

136. The method of claim 132, wherein at least three of the biomarkers are selected from the biomarkers within Core Biomarkers I.

137. The method of claim 132, wherein at least one biomarker is selected from the biomarkers within Clinical Parameters in Table 4.

138. The method of claim 132, wherein at least one biomarker is selected from the biomarkers within Additional Biomarkers I.

139. The method of claim 132, wherein at least one biomarker is selected from the biomarkers within Additional Biomarkers II.

140. The method of claim 132, wherein at least 3 of the biomarkers are selected from the biomarkers within the group consisting of Core Biomarkers I, Core Biomarkers II, Traditional Laboratory Risk Factors, Clinical Parameters, and Additional Biomarkers I.

141. The method of claim 132, wherein at least 3 of the biomarkers are selected from the biomarkers within the group consisting of Core Biomarkers I, Core Biomarkers II, Traditional Laboratory Risk Factors, Clinical Parameters, and Additional Biomarkers II.

142. The method of claim 132, wherein at least 3 of the biomarkers are selected from the biomarkers within the group consisting of Core Biomarkers I, Core Biomarkers II, Traditional Laboratory Risk Factors, and Clinical Parameters.

143. The method of claim 132, wherein at least 3 of the biomarkers are selected from the group consisting of Core Biomarkers II.

144. The method of claim 132, wherein said biomarkers comprise at least four biomarkers selected from the biomarkers within the group consisting of Core Biomarkers I, Core Biomarkers II, Traditional Laboratory Risk Factors, Clinical Parameters, Additional Biomarkers I, and Additional Biomarkers II.

145. The method of claim 132, wherein said biomarkers comprise at least five biomarkers selected from the biomarkers within the group consisting of Core Biomarkers I, Core Biomarkers II, Traditional Laboratory Risk Factors, Clinical Parameters, Additional Biomarkers I, and Additional Biomarkers II.

146. The method of claim 132, wherein at least one of the markers is systolic blood pressure (SBP).

147. The method of claim 132, wherein a first biomarker is ADIPOQ, a second biomarker is selected from the biomarkers within Core Biomarkers I, and a third biomarker is selected from the biomarkers within Core Biomarkers I or Core Biomarkers II.

148. The method of claim 147, wherein the second biomarker is IGFBP1.

149. The method of claim 148, wherein the third biomarker is INS.

150. The method of claim 132, wherein at least four biomarkers are selected from the biomarkers within each of Core Biomarkers I and Core Biomarkers II.

151. The method of claim 112, wherein one of the biomarkers is INS (INS).

152. The method of claim 112, wherein one of the biomarkers is LEP.

153. The method of claim 112, wherein one of the biomarkers is ADIPOQ.

154. The method of claim 112, wherein one of the biomarkers is CRP.

155. The method of claim 112, wherein one of the biomarkers is fibrinogen alpha chain (FGA).

156. The method of claim 112, wherein one of the biomarkers is HBA1C.

157. The method of claim 112, wherein one of the biomarkers is Glucose.

158. The method of claim 112, wherein said biomarkers comprise interleukin 18 (IL-18).

159. The method of claim 112, wherein said biomarkers comprise ferritin (FTH).

160. The method of claim 112, wherein the biomarkers comprise the three markers in a Panel selected from the panels in FIG. 2.

161. The method of claim 112, wherein the biomarkers comprise the three markers set forth in a Panel selected from the panels in FIG. 6A.

162. The method of claim 112, wherein the biomarkers comprise the three markers set forth in a Panel selected from the panels in FIG. 7A.

163. The method of claim 112, wherein the biomarkers comprise at least five ALLDBRISKS markers.

164. The method of claim 163, wherein the biomarkers comprise at least ten ALLDBRISKS markers.

165. The method of claim 164, wherein the biomarkers comprise Markers of Interest in FIG. 12.

166. A method of prophylaxis for Diabetes comprising:

evaluating risk, for at least one subject, of developing a diabetic condition according to the method of claim 112; and

treating a subject identified as being at elevated risk for a diabetic condition with a treatment regimen to delay or prevent the onset of Diabetes.

167. A method of ranking or grouping a population of individuals, comprising:

obtaining Diabetes risk score data representing a Diabetes risk score for individuals comprised within said population, wherein said Diabetes risk score is calculated according to the method or improvement of claim 119; and

ranking individuals within the population relative to the remaining individuals in the population or dividing the population into at least two groups, based on factors comprising said obtained Diabetes risk score data.

168. A method of evaluating the current status of a diabetic condition in an individual, the method comprising:

obtaining biomarker measurement data, wherein the biomarker measurement data is representative of measurements of biomarkers in at least one biological sample from the individual; and

evaluating the current status of a diabetic condition in the individual according to the method of claim 112.

169. A method of evaluating a diabetic disease surrogate endpoint an individual, the method comprising:

obtaining biomarker measurement data, wherein the biomarker measurement data is representative of measurements of biomarkers in at least one biological sample from the individual; and

evaluating a diabetic disease surrogate endpoint in the individual according to the method of claim 112.

170. A method of evaluating risk for developing a diabetic condition in an individual with a known glucose class, the method comprising:

obtaining biomarker measurement data, wherein the biomarker measurement data is representative of measurements of biomarkers in at least one biological sample from the individual; and

evaluating risk for developing a diabetic condition according to the method of claim 112.

123. A computer readable medium having computer executable instructions for evaluating risk for developing a diabetic condition, the computer readable medium comprising:

a routine, stored on the computer readable medium and adapted to be executed by a processor, to store biomarker measurement data representing;

(i) at least three biomarkers, where three of the biomarkers are selected from one of sets of the RDMARKER sets listed in FIG. 6A;

or

(ii) at least four biomarkers selected from RDMARKERS;

or

(iii) at least three biomarkers, where two biomarkers are selected from ADIPOQ;

CRP;

GLUCOSE;

GPT;

HBA1C;

HSPA1B;

IGFBP1;

IGFBP2;

INS;

LEP; and

TRIG; and

one biomarker is selected from the ALLDBRISKS, CPs, and TLRFs of Table 1, Table 2, and Table 3;

or

(iv) at least three biomarkers, where at least one biomarker is selected from GLUCOSE and HBA1C;

at least one biomarker is selected from ADIPOQ, CRP, GPT, HSPA1B, IGFBP1, IGFBP2, INS, LEP, and TRIG; and

at least one biomarker is selected from the ALLDBRISKS, CPs, and TLRFs of Table 1, Table 2, and Table 3;

or

(v) at least three biomarkers, where at least two biomarkers are selected from the biomarkers within the group consisting of Core Biomarkers I and Core Biomarkers II and at least a third biomarker is selected from any of the biomarkers listed in Table 4; and

a routine stored on the computer readable medium and adapted to be executed by a processor to analyze the biomarker measurement data to evaluate a risk for developing a diabetic condition.

124. A diagnostic test system comprising:

means for obtaining test results data representing levels of multiple biomarkers in at least one biological sample;

means for collecting and tracking test results data for one or more individual biological samples;

means for computing an index value from biomarker measurement data according to a DRS Formula, wherein said biomarker measurement data is representative of measured levels of biomarkers, and further wherein said measured levels of biomarkers comprise the levels of;

(i) at least three biomarkers, where three of the biomarkers are selected from one of sets of the RDMARKER sets listed in FIG. 6A;

or

(ii) at least four biomarkers selected from RDMARKERS;

or

(iii) at least three biomarkers, where two biomarkers are selected from ADIPOQ;

CRP;

GLUCOSE;

GPT;

HBA1C;

HSPA1B;

IGFBP1;

IGFBP2;

INS;

LEP; and

TRIG; and

one biomarker is selected from the ALLDBRISKS, CPs, and TLRFs of Table 1, Table 2, and Table 3;

or

(iv) at least three biomarkers, where at least one biomarker is selected from GLUCOSE and HBA1C;

at least one biomarker is selected from ADIPOQ, CRP, GPT, HSPA1B, IGFBP1, IGFBP2, INS, LEP, and TRIG; and

at least one biomarker is selected from the ALLDBRISKS, CPs, and TLRFs of Table 1, Table 2, and Table 3;

or

(v) at least three biomarkers, where at least two biomarkers are selected from the biomarkers within the group consisting of Core Biomarkers I and Core Biomarkers II and at least a third biomarker is selected from any of the biomarkers listed in Table 4.

and means for reporting said index value.

125. A medical diagnostic test system for evaluating risk for developing a diabetic condition, the system comprising:

a data collection tool adapted to collect biomarker measurement data representative of measurements of biomarkers in at least one biological sample from an individual; and

an analysis tool comprising a statistical analysis engine adapted to generate a representation of a correlation between a risk for developing a diabetic condition and measurements of the biomarkers, wherein the representation of the correlation is adapted to be executed to generate a result; and

an index computation tool adapted to analyze the result to determine the individual'"'"'s risk for developing a diabetic condition and represent the result as an index value

wherein said biomarkers comprise;

(i) at least three biomarkers, where three of the biomarkers are selected from one of sets of the RDMARKER sets listed in FIG. 6A;

or

(ii) at least four biomarkers selected from RDMARKERS;

or

(iii) at least three biomarkers, where two biomarkers are selected from ADIPOQ;

CRP;

GLUCOSE;

GPT;

HBA1C;

HSPA1B;

IGFBP1;

IGFBP2;

INS;

LEP; and

TRIG; and

one biomarker is selected from the ALLDBRISKS, CPs, and TLRFs of Table 1, Table 2, and Table 3;

or

(iv) at least three biomarkers, where at least one biomarker is selected from GLUCOSE and HBA1C;

at least one biomarker is selected from ADIPOQ, CRP, GPT, HSPA1B, IGFBP1, IGFBP2, INS, LEP, and TRIG; and

at least one biomarker is selected from the ALLDBRISKS, CPs, and TLRFs of Table 1, Table 2, and Table 3;

or

(v) at least three biomarkers, where at least two biomarkers are selected from the biomarkers within the group consisting of Core Biomarkers I and Core Biomarkers II and at least a third biomarker is selected from any of the biomarkers listed in Table 4.

126. A method of developing a model for evaluation of risk for developing a diabetic condition, the method comprising:

obtaining biomarker measurement data, wherein the biomarker measurement data is representative of measurements of biomarkers from a population and includes endpoints of the population;

inputting the biomarker measurement data of at least a subset of the population into a model;

training the model for endpoints using the inputted biomarker measurement data to derive a representation of a correlation between a risk of developing a diabetic condition and measurements of biomarkers in at least one biological sample from an individual;

wherein said biomarkers for which measurement data is obtained comprise;

(i) at least three biomarkers, where three of the biomarkers are selected from one of sets of the RDMARKER sets listed in FIG. 6A;

or

(ii) at least four biomarkers selected from RDMARKERS;

or

(iii) at least three biomarkers, where two biomarkers are selected from ADIPOQ;

CRP;

GLUCOSE;

GPT;

HBA1C;

HSPA1B;

IGFBP1;

IGFBP2;

INS;

LEP; and

TRIG; and

one biomarker is selected from the ALLDBRISKS, CPs, and TLRFs of Table 1, Table 2, and Table 3;

or

(iv) at least three biomarkers, where at least one biomarker is selected from GLUCOSE and HBA1C;

at least one biomarker is selected from ADIPOQ, CRP, GPT, HSPA1B, IGFBP1, IGFBP2, INS, LEP, and TRIG; and

at least one biomarker is selected from the ALLDBRISKS, CPs, and TLRFs of Table 1, Table 2, and Table 3;

or

(v) at least three biomarkers, where at least two biomarkers are selected from the biomarkers within the group consisting of Core Biomarkers I and Core Biomarkers II and at least a third biomarker is selected from any of the biomarkers listed in Table 4.