Multi-parameter diabetes risk evaluations

A computer program product for evaluating in vitro patient biosamples, the computer program product comprising:

• a non-transitory computer readable storage medium having computer readable program code embodied in the medium, the computer-readable program code comprising:
• computer readable program code that provides at least one mathematical model of risk to progression to type 2 diabetes in the future, wherein the at least one mathematical model of risk to progression to type 2 diabetes includes a plurality of components, including at least one lipoprotein component, at least one inflammatory biomarker and at least one branched chain amino acid;
• and computer readable program code that calculates a diabetes risk index associated with a patient's biosample based on the at least one mathematical model of a risk of developing type 2 diabetes, wherein the defined mathematical model of risk comprises GlycA or GlycB as the inflammatory biomarker, and wherein the at least one lipoprotein component includes an interaction parameter of a measurement of GlycA or GlycB multiplied by a concentration of a defined subpopulation of high density lipoprotein (HDL) particles,
• wherein GlycA is a composite Nuclear Magnetic Resonance signal from carbohydrate portions of acute phase reactant glycoproteins containing N-acetylglucosamine and/or N-acetylgalactosamine moieties that is detectable at about 2.00 ppm when Nuclear Magnetic Resonance measurements are performed at about 47 degrees C., and
• wherein GlycB is a composite NMR signal from the carbohydrate portions of acute phase reactant glycoproteins containing N-acetylneuraminic acid (sialic acid) moieties, more particularly from the protons of the 5-N acetyl methyl groups that is detectable at about 2.04 ppm when Nuclear Magnetic Resonance measurements are performed at about 47 degrees C.

An NMR system comprising:

• a NMR spectrometer;
• a flow probe in communication with the spectrometer;
• and at least one processor in communication with the spectrometer configured to obtain (i) NMR signal of a defined GlycA or GlycB fitting region of NMR spectra associated with GlycA or GlycB of a blood plasma or serum specimen in the flow probe;
• (ii) NMR signal of a defined branched chain amino acid fitting region of NMR spectra associated with the specimen in the flow probe;
• and (iii) NMR signal of lipoprotein subclasses;
• wherein the at least one processor is configured to calculate measurements of (i) GlycA or GlycB, (ii) at least one branched chain amino acid and (iii) the lipoprotein subclasses using the NMR signals, and wherein the at least one processor is configured to calculate a diabetes risk index that uses the calculated measurements of at least one of GlycA or GlycB, the at least one branched chain amino acid and some of the lipoprotein subclasses
• wherein GlycA is a composite Nuclear Magnetic Resonance signal from carbohydrate portions of acute phase reactant glycoproteins containing N-acetylglucosamine and/or N-acetylgalactosamine moieties that is detectable at about 2.00 ppm when Nuclear Magnetic Resonance measurements are performed at about 47 degrees C., and
• wherein GlycB is a composite NMR signal from the carbohydrate portions of acute phase reactant glycoproteins containing N-acetylneuraminic acid (sialic acid) moieties, more particularly from the protons of the 5-N acetyl methyl groups that is detectable at about 2.04 ppm when Nuclear Magnetic Resonance measurements are performed at about 47 degrees C.

A method of monitoring a patient to evaluate a therapy or to determine whether the patient is at-risk of developing type 2 diabetes, comprising:

• programmatically evaluating a plurality of NMR derived measurements of selected lipoprotein subclasses and at least one of (i) GlycA or GlycB or (ii) at least one branched chain amino acid and at least one of GlycA or GlycB, of at least one patient in vitro biosample;
• programmatically calculating a diabetes risk index of respective patients using the NMR derived, measurements;
• and evaluating at least one of (i) whether the diabetes risk index is above a defined level of a population norm associated with increased risk of developing type 2 diabetes;
• and/or (ii) whether the diabetes risk index is increasing or decreasing over time to thereby evaluate change in risk status that may be in response to a therapy,
• wherein GlycA is a composite Nuclear Magnetic Resonance signal from carbohydrate portions of acute phase reactant glycoproteins containing N-acetylglucosamine and/or N-acetylgalactosamine moieties that is detectable at about 2.00 ppm when Nuclear Magnetic Resonance measurements are performed at about 47 degrees C.
• wherein GlycB is a composite NMR signal from the carbohydrate portions of acute phase reactant glycoproteins containing N-acetylneuraminic acid (sialic acid) moieties, more particularly from the protons of the 5-N acetyl methyl groups that is detectable at about 2.04 ppm when Nuclear Magnetic Resonance measurements are performed at about 47 degrees C.