Method and system for improving disease diagnosis using measured analytes

Abstract

Methods for improving clinical diagnostic tests are provided, along with associated diagnostic techniques.

1 . A computer-implemented system for diagnosing a disease, the system comprising:
 a communication component for receiving the concentration of at least three predetermined analytes in a blind sample from a subject; and   a processor in communication with the communication component, the processor being configured for:
 receiving said concentration of at least three predetermined analytes in a blind sample from a subject from said communications component; 
 selecting one or more meta-variables associated with the subject, which varies in a population associated with the subject for members of the population who are known either to have or not have the disease; 
 computing a pseudo-concentration that represents each analyte by transforming the concentrations of the at least three predetermined analytes as a function of one or more population distribution characteristics and the one or more meta-variables; 
 comparing the pseudo-concentrations to a training set model of pseudo-concentrations determined for members of the population who are known either to have or not have the disease, wherein said comparison includes spatial analysis in a multi-dimensional space; 
 determining whether the comparison indicates that the subject has the disease; and 
 displaying the result of said comparison indicating whether the subject has the disease. 
   
     
     
         2 . The system of  claim 1 , wherein said at least three predetermined analytes are selected from the set comprising immune system pro-inflammatory, anti-inflammatory, anti-tumor genesis, angiogenesis, cell apoptosis, vascularization proteins and tissue markers. 
     
     
         3 . The system of  claim 1 , wherein the disease is a solid tissue cancer including at least one of breast cancer, prostate cancer and lung cancer. 
     
     
         4 . A system for creating a training set capable of diagnosing a disease, the system comprising:
 a non-transitory computer readable storage medium for storing a training set of samples from a group of subjects;   a processor in communication with the non-transitory computer readable storage medium, the processor being configured for:
 determining the concentrations of at least three predetermined analytes in said training set of samples from a group of subjects; 
 selecting a meta-variable associated with the group of subjects, which varies in a population associated with the group of subjects for members of the population who are known either to have or not have the disease; 
 computing a pseudo-concentration that represents each analyte by transforming the concentrations of the at least three predetermined analytes as a function of one or more population distribution characteristics and the one or more meta-variables; and 
 computing the training set model from the pseudo-concentrations determined for members of the populations who are known either to have or not have the disease, wherein said computing retains clustering. 
   
     
     
         5 . The system of  claim 4 , wherein said at least three predetermined analytes are selected from the set comprising immune system pro-inflammatory, anti-inflammatory, anti-tumor genesis, angiogenesis, cell apoptosis, vascularization proteins and tissue markers. 
     
     
         6 . The system of  claim 5 , wherein any one or more of said analytes other than the tissue markers are low abundance proteins with determined concentrations below 1 pg/ml for at least 20% of a relevant population for a given subject, wherein said analytes are spatially analyzed in a multi-dimensional space, and wherein said population also has the disease. 
     
     
         7 . The system of  claim 4 , wherein the at least three predetermined analytes are selected from the group consisting of at least four, at least five and at least six analytes. 
     
     
         8 . The system of  claim 4 , wherein the one or more meta-variables are age. 
     
     
         9 . The system of  claim 4 , wherein the one or more meta-variables are selected from the groups consisting of: pre, peri and post-menopausal status, pubescence, body mass, geographic location of the source of the sample, body fat percent, age, race or racial mix or ethnicity, species or era of time. 
     
     
         10 . A computer-implemented system for diagnosing a disease, the system comprising:
 a communication component for receiving the concentration of at least three predetermined biomarkers in a sample from a subject; and   a processor in communication with the communication component, the processor being configured for:
 determining the concentrations in said biological sample of at least three biomarkers selected from the set comprising: immune system pro-inflammatory, anti-inflammatory, anti-tumor genesis, angiogenesis, cell apoptosis, vascularization proteins and tissue markers, wherein said biomarkers are spatially analyzed in a multi-dimensional space, and wherein said population also has the disease. 
   
     
     
         11 . The system of  claim 6 , wherein the disease is a solid tissue cancer including at least one of breast cancer, prostate cancer and lung cancer. 
     
     
         12 . The system of  claim 6 , wherein said at least three biomarkers comprise at least four, five or more, six or more, seven or more, eight or more, nine or more or ton or more biomarkers.