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US 2014/0273030 A1Published application
Human biomarker test for major depressive disorder
OwnerJohn Bilello, Bo Pi +1inventors
InventorsJohn Bilello, Bo Pi, Linda Thurmond
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Abstract
Materials and methods related to diagnosing depression disorders, using a multi-parameter biomarker system and algorithms related thereto.
Claims8
A method for assessing the likelihood that an individual has major depressive disorder (MDD), comprising
- (a) identifying groups of biomarkers that may be related to MDD;
- (b) measuring the level of each of the biomarkers in biological samples from a plurality of subjects, wherein some of the subjects are diagnosed as having MDD and some of the subjects do not have MDD;
- (c) applying a normalization function to the measured level of each of the biomarkers;
- (d) applying an optimization algorithm to the measured biomarker levels and calculating coefficients for selected biomarkers within each group;
- (e) calculating the result of the algorithm for the individual to determine whether the individual is likely to have MDD or is not likely to have MDD.
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A method for calculating a diagnostic score for MDD based on biomarker measurements and body mass index (BMI), comprising:
- (a) developing an algorithm for males and an algorithm for females by obtaining measured levels of MDD biomarkers for male and female MDD patients and male and female normal subjects, and applying normalization to each of the measured levels in males and each of the measured levels in females;
- (b) obtaining a value for a patient's BMI and applying normalization to the BMI;
- (c) calculating a noontime equivalent value for MDD biomarkers with concentrations that fluctuate in accord with diurnal variation, and applying normalization to each noontime equivalent value;
- (d) optimizing each algorithm to clinical data and calculating coefficients based on normalized values of the biomarkers that enable segregation of MDD patients from normal subjects;
- and
- (e) calculating a MDD diagnostic score for an individual using the algorithm for the individual's gender, wherein the MDD diagnostic score indicates the probability that the individual has MDD.
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Dependencies are inferred from the claim text.