Computer implemented system and method for assessing a neuropsychiatric condition of a human subject

Abstract

The disclosure provides methods for assessing a neuropsychiatric condition of a human subject by combining the subject's biomarker data and thought marker data into a quantitative assessment of the subject's neuropsychiatric condition.

What is claimed is: 
     
         1 - 50 . (canceled) 
     
     
         51 . A method for assessing a neuropsychiatric condition of a human subject, the method comprising
 determining one or more neuropsychiatric condition associated biological markers in a biological sample from the subject to provide biomarker data for the subject, the markers determined by a method comprising one or more of a polymerase chain reaction (PCR), a reverse transcription PCR reaction (RT-PCR), mass spectroscopy (MS), high pressure liquid chromatography (HPLC), LC-MS, DNA sequencing, and an enzyme-linked, bead based, or sandwich immunoassay,   generating, using one or more computer processors, a biomarker score based on the strength of the association of the biomarker data with the neuropsychiatric condition,   obtaining thought-marker data from the subject, the thought marker data including one or more of the subject's recorded thoughts, spoken words, transcribed speech, and writings,   generating, using one or more computer processors, a thought-marker score based on the strength of the association of the thought marker data with the neuropsychiatric condition by a method comprising the steps of
 determining a correlation between (i) the thought marker data of the subject and (ii) a corpus of thought data pertaining to the neuropsychiatric condition, 
 the correlation determined using a machine learning method implementing a classification algorithm selected from the group consisting of decision trees, classification rules, function models, and instance-based learner methods, 
 the machine learning method comprising extracting and quantifying relevant content features of the thought marker data and creating a heterogeneous, multidimensional feature space, normalizing the feature values, and generating the thought-marker score based upon the strength of the correlation, 
   and   generating a neuropsychiatric condition score based on the biomarker score and the thought-marker score, thereby providing a quantitative assessment of the neuropsychiatric condition of the subject.   
     
     
         52 . The method of  claim 51 , wherein the neuropsychiatric condition is suicide attempt risk. 
     
     
         53 . The method of  claim 52 , wherein the step of determining the one or more neuropsychiatric condition associated biological markers includes a step of determining a level of a hydroxyindoleacetic acid (5HIAA). 
     
     
         54 . The method of  claim 52 , wherein the step of determining the one or more neuropsychiatric condition associated biological markers includes a step of determining the presence of the S and L alleles of the 5′ upstream regulatory region of the serotonin transporter gene (5-HTTLPR). 
     
     
         55 . The method of  claim 52 , wherein the step of determining the one or more neuropsychiatric condition associated biological markers includes a step of determining the presence of one or more single nucleotide polymorphisms taken from a group consisting of A218C of the TPH1 gene, A779C of the TPH1 gene, and A59G of the SLC6A3 gene. 
     
     
         56 . The method of  claim 52 , wherein the step of determining the one or more neuropsychiatric condition associated biological markers includes a step of determining an mRNA level of 5-HT(2A) mRNA. 
     
     
         57 . The method of  claim 52 , wherein the step of determining the one or more neuropsychiatric condition associated biological markers includes a step of determining a level of one or more cytokines taken from a group consisting of IL-6, IL-2, IFN-γ, IL-4 and TGF-β1. 
     
     
         58 . The method of  claim 52 , wherein the step of determining the one or more neuropsychiatric condition associated biological markers includes a step of determining a level of serotonin (5-HT). 
     
     
         59 . The method of  claim 51 , further comprising receiving clinical data of the subject associated with the neuropsychiatric condition. 
     
     
         60 . The method of  claim 59 , wherein the clinical data includes one or more of data pertaining to a level of interpersonal discord, data pertaining to a presence of a mood disorder, data pertaining to a history of substance use, data pertaining to a history of impulsive aggression, data pertaining to a family history of suicidal behavior, data pertaining to access to weapons such as firearms, and data pertaining to recent psychosocial stressors. 
     
     
         61 . A method for assessing a suicide attempt risk of a human subject, the method comprising
 determining one or more suicide risk associated biological markers in a biological sample obtained from the subject by a method comprising one or more of a polymerase chain reaction (PCR), a reverse transcription PCR reaction (RT-PCR), mass spectroscopy (MS), high pressure liquid chromatography (HPLC), LC-MS, DNA sequencing, and an enzyme-linked, bead based, or sandwich immunoassay,   receiving, using one or more computer processors, one or more thought markers of the subject, the one or more thought markers including one or more of the subject's recorded thoughts, spoken words, transcribed speech, and writings;   executing, using one or more computer processors, a first query and transmitting the first query to a database to obtain a plurality of suicide notes associated with prior completions of suicides, the one or more processors being communicatively coupled to the database using one or more communications networks;   comparing, using a machine learning method, the one or more thought markers and the obtained plurality of suicide notes to determine a correlation between (a) the one or more thought markers of the subject and (b) the obtained plurality of suicide notes, and generating a thought-marker score based upon a strength of the correlation,   generating a suicide attempt risk score based on a combination of the biomarker score and the thought-marker score; and   generating, using the suicide attempt risk score, an assessment of the subject.   
     
     
         62 . The method of  claim 61 , wherein the machine learning method comprises an implementation of a classification algorithm including at least one of a decision tree, a classification rule, a function model, an instance-based learner method, and combinations thereof. 
     
     
         63 . The method of  claim 61 , wherein the machine learning method comprises extracting and quantifying relevant content features of the one or more thought markers and generating, based on the extracted and quantified content features, a heterogeneous, multidimensional feature space containing a plurality of feature values corresponding to the extracted and quantified content features. 
     
     
         64 . The method of  claim 63 , further comprising normalizing the generated feature values and generating, using the normalized generated feature values, a thought-marker score based upon a strength of the correlation between (a) and (b). 
     
     
         65 . The method of  claim 64 , further comprising normalizing, using one or more computer processors, the one or more determined suicide risk associated biological markers and generating a normalized score for each marker based on the strength of marker's association with suicide risk. 
     
     
         66 . The method of  claim 65 , further comprising generating, using one or more computer processors, a biomarker score based on a sum of individual normalized scores for the one or more determined suicide risk associated biological markers.