Biomarker for Seronegative Rheumatoid Arthritis
AssigneeMayo Foundation for Medical Education and Research
InventorsJaeyun Sung, John M. Davis, III, Benjamin Hur
Life of this patent
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Abstract
The disclosure generally relates to methods of selecting a biomarker associated with a disorder or disease, and computer program products and systems for performing such methods. The disclosure further relates to biomarkers for rheumatoid arthritis and methods of use such biomarkers.
Claims21
A method of treating a subject afflicted with rheumatoid arthritis (RA), said method comprising the steps of diagnosing the subject with rheumatoid arthritis (RA), comprising:
- (a) obtaining a blood sample from the subject;
- and
- (b) determining the amount of a plurality of biomolecules comprising plasma proteins, plasma metabolites and plasma autoantibodies in the blood sample;
- wherein
- (i) the amount of at least 25 plasma proteins from Table A, and/or at least 25 plasma metabolites from Table B, and/or at least 25 plasma autoantibodies from Table C, or a combination of at least 50 biomolecules from Tables A, B and C, is higher in the blood sample relative to an amount of the biomolecules in a control sample from a subject without RA and indicates the subject has seronegative RA (ACPA− RA);
- or
- (ii) the amount of at least 25 plasma proteins from Table D, and/or at least 25 plasma metabolites from Table E, and/or at least 25 plasma autoantibodies from Table F, or a combination of at least 50 biomolecules from Tables D, E and F, is higher in the blood sample relative to an amount of the biomolecules in a control sample from a subject without RA indicates the subject has seropositive RA (ACPA+ RA);
- and
- (c) administering at least one therapy to the subject.
(canceled)
(canceled)
A method of diagnosing a subject with rheumatoid arthritis (RA), said method comprising the steps of preparing a RA phenotype classification network comprising:
- (a) receiving multi-omic data from a blood sample from a subject, wherein the multi-omic data includes proteomic, metabolomic, and autoantibody profiles;
- (b) processing the received multi-omic data through a trained machine learning model;
- (c) classifying the subject's RA phenotype based on the processed multi-omic data;
- and
- (d) outputting the classification result;
- and wherein:
- (i) the classification is ACPA− RA when the amount of at least 25 plasma proteins from Table A, and/or at least 25 plasma metabolites from Table B, and/or at least 25 plasma autoantibodies from Table C, or a combination of at least 50 biomolecules from Tables A, B and C is detected;
- or
- (ii) the classification is ACPA+ RA when the amount of at least 25 plasma proteins from Table D, and/or at least 25 plasma metabolites from Table E, and/or at least 25 plasma autoantibodies from Table F, or a combination of at least 50 biomolecules from Tables D, E and F is detected.
A method of treating a subject with rheumatoid arthritis (RA), said method comprising the steps of:
- (I) diagnosing a subject with rheumatoid arthritis (RA), said method comprising the steps of preparing a RA phenotype classification network comprising:
- (a) receiving multi-omic data from a blood sample from a subject, wherein the multi-omic data includes proteomic, metabolomic, and autoantibody profiles;
- (b) processing the received multi-omic data through a trained machine learning model;
- (c) classifying the subject's RA phenotype based on the processed multi-omic data;
- and
- (d) outputting the classification result;
- and wherein:
- (i) the classification is ACPA− RA when the amount of at least 25 plasma proteins from Table A, and/or at least 25 plasma metabolites from Table B, and/or at least 25 plasma autoantibodies from Table C, or a combination of at least 50 biomolecules from Tables A, B and C is detected;
- or
- (ii) the classification is ACPA+ RA when the amount of at least 25 plasma proteins from Table D, and/or at least 25 plasma metabolites from Table E, and/or at least 25 plasma autoantibodies from Table F, or a combination of at least 50 biomolecules from Tables D, E and F is detected;
- and
- (II) administering at least one therapy to the subject
Dependencies are inferred from the claim text.