Protein and lipid biomarkers providing consistent improvement to the prediction of type 2 diabetes

Abstract

The invention relates to biomarkers associated with Diabetes, including protein and lipid metabolite biomarkers, methods of using the biomarkers to determine the risk that an individual will develop Diabetes, and methods of screening a population to identify persons at risk for developing Diabetes and other pre-diabetic conditions.

What is claimed is: 
     
         1 . A method of evaluating risk for developing a diabetic condition, the method comprising:
 (a) obtaining biomarker measurement data for an individual, wherein the biomarker measurement data is representative of measurements of biomarkers in at least one biological sample from the individual; wherein said biomarkers comprise: (i) glucose, (ii) at least three protein biomarkers selected from the protein biomarkers in Table 1 and (iii) at least one lipid metabolite selected from the lipid metabolites in Table 2; and   (b) evaluating risk for the individual developing a diabetic condition based on an output from a model, wherein the model is executed based on an input of the biomarker measurement data.   
     
     
         2 . The method of  claim 1 , wherein the obtaining step comprises measuring the biomarkers in the at least one biological sample. 
     
     
         3 . The method of  claim 2 , further comprising a step, prior to the measuring the biomarkers, of obtaining at least one biological sample from the individual. 
     
     
         4 . The method of  claim 1 , wherein obtaining biomarker measurement data comprises obtaining data representative of a measurement of the level of at least one biomarker from a preexisting record. 
     
     
         5 . The method of any one of  claims 1  to  4 , wherein the evaluating step includes comparing the biomarker measurement data from the individual with biomarker measurement data of the same biomarkers from a population, and evaluating risk for the individual developing a diabetic condition from the comparison. 
     
     
         6 . The method of any one of  claims 1  to  5 , further comprising displaying the risk evaluation from (b) on a visual display. 
     
     
         7 . The method of any one of  claims 1  to  6 , further comprising printing or storing the risk evaluation on paper or an electronic storage medium. 
     
     
         8 . The method of any one of  claims 1  to  7 , further comprising advising said individual or a health care practitioner of said risk evaluation. 
     
     
         9 . The method of any one of  claims 1  to  8 , further comprising:
 obtaining clinical measurement data for the individual for at least one clinical parameter selected from the group consisting of age, body mass index (BMI), diastolic blood pressure (DBP), family history (FHX), past gestational diabetes mellitus (GDM), height (HT), hip circumference (Hip), race, sex, systolic blood pressure (SBP), waist circumference (Waist), and weight (WT), 
 wherein the model is executed based on an input of the biomarker measurement data and the clinical measurement data. 
 
     
     
         10 . A method of evaluating risk for developing a diabetic condition, the method comprising:
 (a) obtaining measurements of biomarkers from at least one biological sample isolated from an individual, wherein said biomarkers comprise: (i) glucose, (ii) at least three protein biomarkers selected from the protein biomarkers in Table 1 and (iii) at least one lipid metabolite selected from the lipid metabolites in Table 2; and   (b) calculating a risk for developing a diabetic condition from the output of a model, wherein the inputs to said model comprise said measurements of biomarkers, and wherein said model was developed by fitting data from a longitudinal study of a population of individuals and said fitted data comprises levels of said biomarkers and conversion to Diabetes in said selected population of individuals.   
     
     
         11 . The method of  claim 10 , wherein the obtaining step comprises measuring the biomarkers in the at least one biological sample. 
     
     
         12 . The method of  claim 10  or  11 , further comprising displaying the calculated risk from (b) on a visual display. 
     
     
         13 . The method of any one of  claims 10  to  12 , further comprising printing or storing the calculated risk on paper or an electronic storage medium. 
     
     
         14 . The method of any one of  claims 10  to  13 , further comprising advising said individual or a health care practitioner of said risk evaluation. 
     
     
         15 . The method of any one of  claims 10  to  14 , further comprising:
 obtaining at least one clinical measurement for the individual for at least one clinical parameter selected from the group consisting of age, body mass index (BMI), diastolic blood pressure (DBP), family history (FHX), past gestational diabetes mellitus (GDM), height (HT), hip circumference (Hip), race, sex, systolic blood pressure (SBP), waist circumference (Waist), and weight (WT), 
 wherein the inputs to the model further comprise said at least one clinical measurement. 
 
     
     
         16 . The method of any one of  claims 1  to  15 , wherein the individual has not been previously diagnosed as having Diabetes, pre-Diabetes, or a pre-diabetic condition. 
     
     
         17 . The method of any one of  claims 1  to  15 , wherein the individual has a pre-diabetic condition, and the method evaluates or calculates risk for the individual developing Diabetes. 
     
     
         18 . The method of any one of  claims 1  to  17 , wherein the individual is pregnant. 
     
     
         19 . The method according to any one of  claims 1  to  18 , wherein the diabetic condition is selected from the group consisting of Type 2 Diabetes, pre-Diabetes, Metabolic Syndrome, Impaired Glucose Tolerance, and Impaired Fasting Glycemia. 
     
     
         20 . The method according to any one of  claims 1  to  19 , wherein said at least one biological sample comprises whole blood, serum, or plasma. 
     
     
         21 . The method according to any one of  claims 1  to  20 , wherein at least one of said biomarker measurements is obtained by a method selected from the group consisting of immunoassay and enzymatic activity assay. 
     
     
         22 . The method according to any one of  claims 1  to  21 , wherein the method using said biomarkers has an area under the ROC curve, reflecting the degree of diagnostic accuracy for predicting development of the diabetic condition, of at least 0.75, 0.76, 0.77, 0.78, 0.79, 0.80, 0.81, 0.82, 0.83, 0.84, or 0.85. 
     
     
         23 . The method according to any one of  claims 1  to  22 , wherein the method using said biomarkers has an area under the ROC curve, reflecting the degree of diagnostic accuracy for predicting development of the diabetic condition, of at least 0.02, 0.03, 0.04, 0.05, 0.06, 0.07, 0.08, 0.09, 0.10, 0.11, 0.12, 0.13, 0.14, or 0.15 greater than a corresponding method wherein the biomarkers consist of the glucose and the protein biomarkers but not the lipid metabolites. 
     
     
         24 . A kit comprising reagents for measuring a group of biomarkers, wherein the biomarkers are:
 (i) glucose,   (ii) at least three protein biomarkers selected from the protein biomarkers in Table 1 and   (iii) at least one lipid metabolite selected from the lipid metabolites in Table 2.   
     
     
         25 . The kit of  claim 24 , wherein at least one of the reagents comprises a detectable label. 
     
     
         26 . The kit of  claim 24 , wherein the reagents for the protein biomarkers and lipid metabolites are attached to a solid support. 
     
     
         27 . 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 measurements of at least the following: (i) glucose, (ii) at least three protein biomarkers selected from the protein biomarkers in Table 1 and (iii) at least one lipid metabolite selected from the lipid metabolites in Table 2; 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.   
     
     
         28 . 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, wherein said biomarkers comprise: (i) glucose, (ii) at least three protein biomarkers selected from the protein biomarkers in Table 1 and (iii) at least one lipid metabolite selected from the lipid metabolites in Table 2; 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.   
     
     
         29 . The medical diagnostic test system of  claim 28 , wherein the analysis tool comprises a first analysis tool comprising a first statistical analysis engine, the system further comprising a second analysis tool comprising a second statistical analysis engine adapted to select the representation of the correlation between the risk for developing a diabetic condition and measurements of the biomarkers from among a plurality of representations capable of representing the correlation. 
     
     
         30 . The system of  claim 28  or  29 , further comprising a reporting tool adapted to generate a report comprising the index value. 
     
     
         31 . 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; wherein said biomarkers for which measurement data is obtained comprise: (i) glucose, (ii) at least three protein biomarkers selected from the protein biomarkers in Table 1 and (iii) at least one lipid metabolite selected from the lipid metabolites in Table 2;   inputting the biomarker measurement data of at least a subset of the population into a model; and   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.   
     
     
         32 . 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, wherein said biomarkers comprise: (i) glucose, (ii) at least three protein biomarkers selected from the protein biomarkers in Table 1 and (iii) at least one lipid metabolite selected from the lipid metabolites in Table 2; and   evaluating the current status of 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.   
     
     
         33 . 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; wherein said biomarkers comprise: (i) glucose, (ii) at least three protein biomarkers selected from the protein biomarkers in Table 1 and (iii) at least one lipid metabolite selected from the lipid metabolites in Table 2; and   evaluating a diabetic disease surrogate endpoint in the individual based on an output from a model, wherein the model is executed based on an input of the biomarker measurement data.   
     
     
         34 . The method, kit, computer readable medium, or system of any one of  claims 1  to  33 , wherein said biomarkers comprise at least four, at least five, at least six, at least seven, at least eight, at least nine, or at least ten protein biomarkers from Table 1. 
     
     
         35 . The method, kit, computer readable medium, or system of any one of  claims 1  to  33 , wherein said at least three protein biomarkers are selected from the group consisting of adiponectin, C-reactive protein (CRP), HbAlc, IGFBPI, IGFBP2, Insulin, IL2RA, ferritin, and LEP. 
     
     
         36 . The method, kit, computer readable medium, or system of any one of  claims 1  to  33 , wherein said at least three protein biomarkers are selected from the group consisting of: adiponectin, C-reactive protein (CRP), IL2RA, ferritin, insulin, and HbAlc. 
     
     
         37 . The method, kit, computer readable medium, or system of any one of  claims 1  to  33 , wherein said at least three protein biomarkers include at least one glycemic index marker selected from insulin and HbAlc. 
     
     
         38 . The method, kit, computer readable medium, or system of any one of  claims 1  to  33 , wherein said at least three protein biomarkers comprise adiponectin, insulin, and C-reactive protein. 
     
     
         39 . The method, kit, computer readable medium, or system of any one of  claims 1  to  33 , wherein said at least three protein biomarkers adiponectin, CRP and HbAlc 
     
     
         40 . The method, kit, computer readable medium, or system of any one of  claims 1  to  33 , wherein said at least three protein biomarkers are selected from the combinations of any one of  FIGS. 8-26 . 
     
     
         41 . The method, kit, computer readable medium, or system of any one of  claims 1  to  40 , wherein said at least three protein markers and at least one lipid metabolite are selected from the combinations of any one of  FIGS. 27-35 . 
     
     
         42 . The method, kit, computer readable medium, or any system of any one of  claims 1 - 41 , wherein said biomarkers comprise at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, or at least ten lipid metabolites from Table 2. 
     
     
         43 . The method, kit, computer readable medium, or system of any one of  claims 1  to  42 , wherein said at least one lipid metabolite comprises at least one cholesterol ester. 
     
     
         44 . The method, kit, computer readable medium, or system of any one of  claims 1  to  42 , wherein said at least one lipid metabolite comprises at least one lipid metabolite selected from the group consisting of AC6:0, AC8:0, AC10:0, CE16:0, CE16:ln7, CE18:0, CE18:3n6, CE18:ln9, CE 18:2n6, CE20:3n6, CE20:4n3, TGTL, DG16:0, DG18:0, DG18:ln9, DG18:2n6, DG18:3n3, DGTL, FA16:0, FA16:ln7, FA18:ln9, FA18:2n6, FA24:0, LY16:ln7, LY18:ln7, LY18:ln9, LY18:2n6, PC16:ln7, PC18:2n6, PC18:3n6, PC18:ln7, PC20:3n9, PC22:4n6, PC22:5n3, PCdml8:0, PCdml8:ln9, PCdml6:0, PC20:3n6, PC20:4n3, PEdm18:ln9, PE16:ln7, PE18:2n6, PE20:2n6, PE22:0, PE24:ln9 PEdml8:0, TG16:0, TG16:ln7, TG18:0, TG18:ln7, TG18:ln9, TG18:2n6 and TG18:3n3. 
     
     
         45 . The method, kit, computer readable medium, or system of any one of  claims 1  to  42 , wherein said at least one lipid metabolite selected from the group consisting of CE16:ln7, CE20:3n6, CE18:2n6, CE16:0, CE18:ln9, LY18:2n6, LY18:ln7 and LY18:ln9. 
     
     
         46 . The method, kit, computer readable medium, or system of any one of  claims 1  to  42 , wherein said at least one lipid metabolite comprises CE 16:ln7. 
     
     
         47 . The method, kit, computer readable medium, or system of any one of  claims 1  to  42 , wherein said at least one lipid metabolite comprises CE 20:3n6. 
     
     
         48 . The method, kit, computer readable medium, or system of any one of  claims 1  to  42 , wherein said at least one lipid metabolite comprises CE18:2n6. 
     
     
         49 . The method, kit, computer readable medium, or system of any one of  claims 1  to  42 , wherein said at least one lipid metabolite comprises CE16:0. 
     
     
         50 . The method, kit, computer readable medium, or system of any one of  claims 1  to  42 , wherein said at least one lipid metabolite comprises CE18:ln9. 
     
     
         51 . The method, kit, computer readable medium, or system of any one of  claims 1  to  42 , wherein said at least one lipid metabolite comprises LY18:2n6. 
     
     
         52 . The method, kit, computer readable medium, or system of any one of  claims 1  to  42 , wherein said at least one lipid metabolite comprises LY18:ln7 or LY18:ln9. 
     
     
         53 . A method of prophylaxis for Diabetes comprising:
 obtaining risk score data representing a Diabetes risk score for an individual, wherein the Diabetes risk score is computed according to the method of  claim 2  for calculating a risk of developing a diabetic condition; and   generating prescription treatment data representing a prescription for a treatment regimen to delay or prevent the onset of Diabetes to an individual identified by the Diabetes risk score as being at elevated risk for Diabetes.   
     
     
         54 . A method of prophylaxis for Diabetes comprising:
 evaluating or calculating risk, for at least one subject, of developing a diabetic condition according to the method of any one of  claims 1 - 23  and  34 - 52 ; 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.   
     
     
         55 . The method according to  claim 53  or  54 , wherein the treatment regimen comprises at least one therapeutic selected from the group consisting of: INS, INS analogs, hypoglycemic agents, anti-inflammatory agents, lipid-reducing agents, calcium channel blockers, beta-adrenergic receptor blocking agents, cyclooxygenase-2 (COX-2) inhibitors, prodrugs of COX-2 inhibitors, angiotensin II antagonists, angiotensin converting enzyme (ACE) inhibitors, renin inhibitors, lipase inhibitors, amylin analogs, sodium-glucose cotransporter 2 inhibitors, dual adipose triglyceride lipase and PI3 kinase activators, antagonists of neuropeptide Y receptors, human hormone analogs, cannabinoid receptor antagonists, triple monoamine oxidase reuptake inhibitors, inhibitors of norepinephrine and dopamine reuptake, inhibitors of 11 Beta-hydroxysteroid dehydrogenase type 1 (I lb-HSDI), inhibitors of Cortisol synthesis, inhibitors of gluconeogenesis, glucokinase activators, antisense inhibitors of protein tyrosine phosphatase-IB, islet neogenesis therapy, and betahistine. 
     
     
         56 . The method according to  claim 53  or  54 , wherein the treatment region comprises at least one therapeutic at least one therapeutic selected from the group consisting of acarbose, metformin, troglitazone, and rosightazone. 
     
     
         57 . A method of ranking or grouping a population of individuals, comprising:
 calculating for developing a diabetic condition according to the method of any one of  claims 10  to  23  for individuals comprised within the population; 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 risk for developing a diabetic condition.   
     
     
         58 . The method of  claim 57 , further comprising using ranking data representing the ranking or grouping of the population of individuals for one or more of the following purposes:
 to determine an individual's eligibility for health insurance;   to determine an individual's premium for health insurance;   to determine an individual's premium for membership in a health care plan, health maintenance organization, or preferred provider organization; and   to assign health care practitioners to an individual in a health care plan, health maintenance organization, or preferred provider organization.   
     
     
         59 . The method of  claim 57  or  58 , further comprising using ranking data representing the ranking or grouping of the population of individuals for one or more purposes selected from the group consisting of:
 to recommend therapeutic intervention or lifestyle intervention to an individual or group of individuals; 
 to manage the health care of an individual or group of individuals; 
 to monitor the health of an individual or group of individuals; and 
 to monitor the health care treatment, therapeutic intervention, or lifestyle intervention for an individual or group of individuals. 
 
     
     
         60 . 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 based on an output from a model, wherein the model is executed based on an input of the biomarker measurement data;   wherein said biomarkers comprise: (i) glucose, (ii) at least three protein biomarkers selected from the protein biomarkers in Table 1 and (iii) at least one lipid metabolite selected from the lipid metabolites in Table 2.