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US 2022/0187295 A1Published application
Biomarkers for Predicting Multiple Sclerosis Disease Activity
AssigneeOctave Bioscience, 1nc.
InventorsMichael Justin Becich, Victor Michael Gehman, Ferhan Qureshi, William A. Hagstrom, Amal Kamal Katrib, Fatima Rubio da Costa
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Abstract
Disclosed herein are methods for analzying quantitative expression values of biomarkers of a biomarker panel for determining disease activity in a human subject. Further disclosed herein are kits for measuring quantitative expression values of the markers as well as computer systems and software embodiments of predictive models for determining disease activity in human subjects based on the quantitative expression values of the markers.
Claims308
A method for determining multiple sclerosis activity in a subject, the method comprising:
- obtaining or having obtained a dataset comprising expression levels of a plurality of biomarkers, wherein the plurality of biomarkers comprise each biomarker in at least one group selected from group 1, group 2, and group 3,
- wherein group 1 comprises biomarker 1, biomarker 2, biomarker 3, biomarker 4, biomarker 5, biomarker 6, biomarker 7, and biomarker 8,
- wherein biomarker 1 is NEFL, MOG, CADM3, or GFAP,
- wherein biomarker 2 is MOG, CADM3, KLK6, BCAN, OMG, or GFAP,
- wherein biomarker 3 is CD6, CD5, CRTAM, CD244, or TNFRSF9,
- wherein biomarker 4 is CXCL9, CXCL10, IL-12B, CXCL11, or GFAP,
- wherein biomarker 5 is OPG, TFF3, or ENPP2,
- wherein biomarker 6 is OPN, OMD, MEPE, or GFAP,
- wherein biomarker 7 is CXCL13, NOS3, or MMP-2, and
- wherein biomarker 8 is GFAP, NEFL, OPN, CXCL9, MOG, or CHI3L1, and
- wherein group 2 comprises biomarker 9, biomarker 10, biomarker 11, biomarker 12, biomarker 13, biomarker 14, biomarker 15, biomarker 16, and biomarker 17,
- wherein biomarker 9 is CDCP1, IL-18BP, IL-18, GFAP, or MSR1,
- wherein biomarker 10 is CCL20, CCL3, or TWEAK,
- wherein biomarker 11 is IL-12B, IL12A, or CXCL9,
- wherein biomarker 12 is APLP1, SEZ6L, BCAN, DPP6, NCAN, or KLK6,
- wherein biomarker 13 is TNFRSF10A, TNFRSF11A, SPON2, CHI3L1, or IFI30,
- wherein biomarker 14 is COL4A1, IL6, NOTCH3, or PCDH17,
- wherein biomarker 15 is SERPINA9, TNFRSF9, or CNTN4,
- wherein biomarker 16 is FLRT2, DDR1, NTRK2, CDH6, MMP-2, and
- wherein biomarker 17 is TNFSF13B, CXCL16, ALCAM, or IL-18,
- wherein group 3 comprises biomarker 18, biomarker 19, biomarker 20, and biomarker 21,
- wherein biomarker 18 is GH, GH2, or IGFBP-1,
- wherein biomarker 19 is VCAN, TINAGL1, CANT1, NECTIN2, MMP-9, or NPDC1,
- wherein biomarker 20 is PRTG, NTRK2, NTRK3, or CNTN4, and
- wherein biomarker 21 is CNTN2, DPP6, GDNFR-alpha-3, or SCARF2, and
- generating a prediction of multiple sclerosis disease activity by applying a predictive model to the expression levels of the plurality of biomarkers.
23 more elements
A method for determining multiple sclerosis activity in a subject, the method comprising:
- obtaining or having obtained a dataset comprising expression levels of a plurality of biomarkers comprising NEFL, MOG, CD6, CXCL9, OPG, OPN, CXCL13, and GFAP;
- and
- generating a prediction of multiple sclerosis disease activity by applying a predictive model to the expression levels of the plurality of biomarkers.
A method for generating quantitative data for a subject comprising:
- performing at least one immunoassay on a sample obtained from the subject to generate a dataset comprising the quantitative data, wherein the quantitative data represents at least eight protein biomarkers comprising:
- NEFL, MOG, CD6, CXCL9, OPG, OPN, CXCL13, and GFAP,
- wherein the subject has or is suspected of having multiple sclerosis.
A method for determining multiple sclerosis activity in a subject, the method comprising:
- obtaining or having obtained a dataset comprising expression levels of a plurality of biomarkers comprising:
- one or more neurodegeneration biomarkers selected from a group consisting of NEFL, APLP1, OPG, SERPINA9, PRTG, GFAP, CNTN2, and FLRT2;
- one or more inflammation biomarkers selected from a group consisting of CCL20, GH, CXCL13, IL-12B, VCAN, TNFRSF10A, TNFSF13B, CD6, and CXCL9;
- one or more immune modulation biomarkers selected from a group consisting of CDCP1, and OPN;
- one or more myelin integrity biomarkers selected from a group consisting of COL4A1 and MOG;
- and
- generating a prediction of multiple sclerosis disease activity by applying a predictive model to the expression levels of the plurality of biomarkers.
4 more elements
A method for determining multiple sclerosis activity in a subject, the method comprising:
- obtaining or having obtained a dataset comprising expression levels of a plurality of biomarkers, wherein the plurality of biomarkers comprises two or more of:
- NEFL, MOG, CD6, CXCL9, OPG, OPN, CXCL13, GFAP, CDCP1, CCL20, IL-12B, APLP1, TNFRSF10A, COL4A1, SERPINA9, FLRT2, TNFSF13B, GH, VCAN, PRTG, and CNTN2;
- and
- generating a prediction of multiple sclerosis disease activity by applying a predictive model to the expression levels of the plurality of biomarkers.
1 more element
A method for preparing a biomarker fraction from a sample obtained from a subject, the method comprising:
- (a) extracting biomarkers from the sample;
- (b) producing a fraction of the extracted biomarkers after (a),
- wherein the fraction of the extracted biomarkers after (b) comprises a plurality of biomarkers, wherein the plurality of biomarkers comprises two or more of:
- NEFL, MOG, CD6, CXCL9, OPG, OPN, CXCL13, GFAP, CDCP1, CCL20, IL-12B, APLP1, TNFRSF10A, COL4A1, SERPINA9, FLRT2, TNFSF13B, GH, VCAN, PRTG, and CNTN2;
- (c) analyzing the plurality of biomarkers of the fraction of the extracted biomarkers produced in (b).
2 more elements
A non-transitory computer readable medium for determining multiple sclerosis activity in a subject, the non-transitory computer readable medium comprising instructions that, when executed by a processor, cause the processor to:
- obtain a dataset comprising expression levels of a plurality of biomarkers, wherein the plurality of biomarkers comprise each biomarker in at least one group selected from group 1, group 2, and group 3,
- wherein group 1 comprises biomarker 1, biomarker 2, biomarker 3, biomarker 4, biomarker 5, biomarker 6, biomarker 7, and biomarker 8,
- wherein biomarker 1 is NEFL, MOG, CADM3, or GFAP,
- wherein biomarker 2 is MOG, CADM3, KLK6, BCAN, OMG, or GFAP,
- wherein biomarker 3 is CD6, CD5, CRTAM, CD244, or TNFRSF9,
- wherein biomarker 4 is CXCL9, CXCL10, IL-12B, CXCL11, or GFAP,
- wherein biomarker 5 is OPG, TFF3, or ENPP2,
- wherein biomarker 6 is OPN, OMD, MEPE, or GFAP,
- wherein biomarker 7 is CXCL13, NOS3, or MMP-2, and
- wherein biomarker 8 is GFAP, NEFL, OPN, CXCL9, MOG, or CHI3L1, and wherein group 2 comprises biomarker 9, biomarker 10, biomarker 11, biomarker 12, biomarker 13, biomarker 14, biomarker 15, biomarker 16, and biomarker 17,
- wherein biomarker 9 is CDCP1, IL-18BP, IL-18, GFAP, or MSR1,
- wherein biomarker 10 is CCL20, CCL3, or TWEAK,
- wherein biomarker 11 is IL-12B, IL12A, or CXCL9,
- wherein biomarker 12 is APLP1, SEZ6L, BCAN, DPP6, NCAN, or KLK6,
- wherein biomarker 13 is TNFRSF10A, TNFRSF11A, SPON2, CHI3L1, or IFI30,
- wherein biomarker 14 is COL4A1, IL6, NOTCH3, or PCDH17,
- wherein biomarker 15 is SERPINA9, TNFRSF9, or CNTN4,
- wherein biomarker 16 is FLRT2, DDR1, NTRK2, CDH6, MMP-2, and
- wherein biomarker 17 is TNFSF13B, CXCL16, ALCAM, or IL-18,
- wherein group 3 comprises biomarker 18, biomarker 19, biomarker 20, and biomarker 21,
- wherein biomarker 18 is GH, GH2, or IGFBP-1,
- wherein biomarker 19 is VCAN, TINAGL1, CANT1, NECTIN2, MMP-9, or NPDC1,
- wherein biomarker 20 is PRTG, NTRK2, NTRK3, or CNTN4, and
- wherein biomarker 21 is CNTN2, DPP6, GDNFR-alpha-3, or SCARF2, and
- generate a prediction of multiple sclerosis disease activity by applying a predictive model to the expression levels of the plurality of biomarkers.
22 more elements
A non-transitory computer readable medium for determining multiple sclerosis activity in a subject, the non-transitory computer readable medium comprising instructions that, when executed by a processor, cause the processor to perform steps of:
- obtaining or having obtained a dataset comprising expression levels of a plurality of biomarkers comprising NEFL, MOG, CD6, CXCL9, OPG, OPN, CXCL13, and GFAP;
- and
- generating a prediction of multiple sclerosis disease activity by applying a predictive model to the expression levels of the plurality of biomarkers.
A non-transitory computer readable medium for determining multiple sclerosis activity in a subject, the non-transitory computer readable medium comprising instructions that, when executed by a processor, cause the processor to:
- obtain a dataset comprising expression levels of a plurality of biomarkers comprising:
- one or more neurodegeneration biomarkers selected from a group consisting of NEFL, APLP1, OPG, SERPINA9, PRTG, GFAP, CNTN2, and FLRT2;
- one or more inflammation biomarkers selected from a group consisting of CCL20, GH, CXCL13, IL-12B, VCAN, TNFRSF10A, TNFSF13B, CD6, and CXCL9;
- one or more immune modulation biomarkers selected from a group consisting of CDCP1, and OPN;
- one or more myelin integrity biomarkers selected from a group consisting of COL4A1 and MOG;
- and
- generating a prediction of multiple sclerosis disease activity by applying a predictive model to the expression levels of the plurality of biomarkers.
4 more elements
A non-transitory computer readable medium for determining multiple sclerosis activity in a subject, the non-transitory computer readable medium comprising instructions that, when executed by a processor, cause the processor to:
- obtain a dataset comprising expression levels of a plurality of biomarkers, wherein the plurality of biomarkers comprises two or more of:
- NEFL, MOG, CD6, CXCL9, OPG, OPN, CXCL13, GFAP, CDCP1, CCL20, IL-12B, APLP1, TNFRSF10A, COL4A1, SERPINA9, FLRT2, TNFSF13B, GH, VCAN, PRTG, and CNTN2;
- and
- generate a prediction of multiple sclerosis disease activity by applying a predictive model to the expression levels of the plurality of biomarkers.
1 more element
A kit for assessing multiple sclerosis disease activity in a subject, the kit comprising:
- a set of reagents for determining expression levels for a plurality of biomarkers from a test sample from the subject,
- wherein the plurality of biomarkers comprise each biomarker in at least one group selected from group 1, group 2, and group 3,
- wherein group 1 comprises biomarker 1, biomarker 2, biomarker 3, biomarker 4, biomarker 5, biomarker 6, biomarker 7, and biomarker 8,
- wherein biomarker 1 is NEFL, MOG, CADM3, or GFAP,
- wherein biomarker 2 is MOG, CADM3, KLK6, BCAN, OMG, or GFAP,
- wherein biomarker 3 is CD6, CD5, CRTAM, CD244, or TNFRSF9,
- wherein biomarker 4 is CXCL9, CXCL10, IL-12B, CXCL11, or GFAP,
- wherein biomarker 5 is OPG, TFF3, or ENPP2,
- wherein biomarker 6 is OPN, OMD, MEPE, or GFAP,
- wherein biomarker 7 is CXCL13, NOS3, or MMP-2, and
- wherein biomarker 8 is GFAP, NEFL, OPN, CXCL9, MOG, or CHI3L1, and
- wherein group 2 comprises biomarker 9, biomarker 10, biomarker 11, biomarker 12, biomarker 13, biomarker 14, biomarker 15, biomarker 16, and biomarker 17,
- wherein biomarker 9 is CDCP1, IL-18BP, IL-18, GFAP, or MSR1,
- wherein biomarker 10 is CCL20, CCL3, or TWEAK,
- wherein biomarker 11 is IL-12B, IL12A, or CXCL9,
- wherein biomarker 12 is APLP1, SEZ6L, BCAN, DPP6, NCAN, or KLK6,
- wherein biomarker 13 is TNFRSF10A, TNFRSF11A, SPON2, CHI3L1, or IFI30,
- wherein biomarker 14 is COL4A1, IL6, NOTCH3, or PCDH17,
- wherein biomarker 15 is SERPINA9, TNFRSF9, or CNTN4,
- wherein biomarker 16 is FLRT2, DDR1, NTRK2, CDH6, MMP-2, and
- wherein biomarker 17 is TNFSF13B, CXCL16, ALCAM, or IL-18,
- wherein group 3 comprises biomarker 18, biomarker 19, biomarker 20, and biomarker 21,
- wherein biomarker 18 is GH, GH2, or IGFBP-1,
- wherein biomarker 19 is VCAN, TINAGL1, CANT1, NECTIN2, MMP-9, or NPDC1,
- wherein biomarker 20 is PRTG, NTRK2, NTRK3, or CNTN4, and
- wherein biomarker 21 is CNTN2, DPP6, GDNFR-alpha-3, or SCARF2, and
- instructions for using the set of reagents to determine the expression levels of biomarkers from the test sample.
24 more elements
A kit for assessing multiple sclerosis disease activity in a subject, the kit comprising:
- a set of reagents for determining expression levels for a plurality of biomarkers from a test sample from the subject, wherein the plurality of biomarkers comprise NEFL, MOG, CD6, CXCL9, OPG, OPN, CXCL13, and GFAP;
- and
- instructions for using the set of reagents to determine the expression levels of biomarkers from the test sample.
A kit for assessing multiple sclerosis disease activity in a subject, the kit comprising:
- a set of reagents for determining expression levels for a plurality of biomarkers from a test sample from the subject, wherein the plurality of biomarkers comprise:
- one or more neurodegeneration biomarkers selected from a group consisting of NEFL, APLP1, OPG, SERPINA9, PRTG, GFAP, CNTN2, and FLRT2;
- one or more inflammation biomarkers selected from a group consisting of CCL20, GH, CXCL13, IL-12B, VCAN, TNFRSF10A, TNFSF13B, CD6, and CXCL9;
- one or more immune modulation biomarkers selected from a group consisting of CDCP1, and OPN;
- one or more myelin integrity biomarkers selected from a group consisting of COL4A1 and MOG;
- and
- instructions for using the set of reagents to determine the expression levels of biomarkers from the test sample.
4 more elements
A kit for determining multiple sclerosis activity in a subject, the kit comprising:
- a set of reagents for determining expression levels for a plurality of biomarkers from a test sample from the subject, the plurality of biomarkers comprising two or more of:
- NEFL, MOG, CD6, CXCL9, OPG, OPN, CXCL13, GFAP, CDCP1, CCL20, IL-12B, APLP1, TNFRSF10A, COL4A1, SERPINA9, FLRT2, TNFSF13B, GH, VCAN, PRTG, and CNTN2;
- and
- instructions for using the set of reagents to determine the expression levels of biomarkers from the test sample.
1 more element
A system for assessing multiple sclerosis disease activity in a subject, the system comprising:
- a set of reagents used for determining expression levels for a plurality of biomarkers from a test sample from the subject, wherein the plurality of biomarkers comprise each biomarker in at least one group selected from group 1, group 2, and group 3,
- wherein group 1 comprises biomarker 1, biomarker 2, biomarker 3, biomarker 4, biomarker 5, biomarker 6, biomarker 7, and biomarker 8,
- wherein biomarker 1 is NEFL, MOG, CADM3, or GFAP,
- wherein biomarker 2 is MOG, CADM3, KLK6, BCAN, OMG, or GFAP,
- wherein biomarker 3 is CD6, CD5, CRTAM, CD244, or TNFRSF9,
- wherein biomarker 4 is CXCL9, CXCL10, IL-12B, CXCL11, or GFAP,
- wherein biomarker 5 is OPG, TFF3, or ENPP2,
- wherein biomarker 6 is OPN, OMD, MEPE, or GFAP,
- wherein biomarker 7 is CXCL13, NOS3, or MMP-2, and
- wherein biomarker 8 is GFAP, NEFL, OPN, CXCL9, MOG, or CHI3L1, and
- wherein group 2 comprises biomarker 9, biomarker 10, biomarker 11, biomarker 12, biomarker 13, biomarker 14, biomarker 15, biomarker 16, and biomarker 17,
- wherein biomarker 9 is CDCP1, IL-18BP, IL-18, GFAP, or MSR1,
- wherein biomarker 10 is CCL20, CCL3, or TWEAK,
- wherein biomarker 11 is IL-12B, IL12A, or CXCL9,
- wherein biomarker 12 is APLP1, SEZ6L, BCAN, DPP6, NCAN, or KLK6,
- wherein biomarker 13 is TNFRSF10A, TNFRSF11A, SPON2, CHI3L1, or IFI30,
- wherein biomarker 14 is COL4A1, IL6, NOTCH3, or PCDH17,
- wherein biomarker 15 is SERPINA9, TNFRSF9, or CNTN4,
- wherein biomarker 16 is FLRT2, DDR1, NTRK2, CDH6, MMP-2, and
- wherein biomarker 17 is TNFSF13B, CXCL16, ALCAM, or IL-18,
- wherein group 3 comprises biomarker 18, biomarker 19, biomarker 20, and biomarker 21,
- wherein biomarker 18 is GH, GH2, or IGFBP-1,
- wherein biomarker 19 is VCAN, TINAGL1, CANT1, NECTIN2, MMP-9, or NPDC1,
- wherein biomarker 20 is PRTG, NTRK2, NTRK3, or CNTN4, and
- wherein biomarker 21 is CNTN2, DPP6, GDNFR-alpha-3, or SCARF2, and
- an apparatus configured to receive a mixture of one or more reagents in the set and the test sample and to measure the expression levels for the biomarkers from the test sample;
- and
- a computer system communicatively coupled to the apparatus to obtain a dataset comprising the expression levels for the plurality of biomarkers from the test sample and to generate a prediction of multiple sclerosis disease activity by applying a predictive model to the expression levels of the plurality of biomarkers.
25 more elements
A system for assessing multiple sclerosis disease activity in a subject, the system comprising:
- a set of reagents used for determining expression levels for a plurality of biomarkers from a test sample from the subject, wherein the plurality of biomarkers comprise NEFL, MOG, CD6, CXCL9, OPG, OPN, CXCL13, and GFAP;
- and
- an apparatus configured to receive a mixture of one or more reagents in the set and the test sample and to measure the expression levels for the biomarkers from the test sample;
- and
- a computer system communicatively coupled to the apparatus to obtain a dataset comprising the expression levels for the plurality of biomarkers from the test sample and to generate a prediction of multiple sclerosis disease activity by applying a predictive model to the expression levels of the plurality of biomarkers.
2 more elements
A system for determining multiple sclerosis activity in a subject, the system comprising:
- a set of reagents used for determining expression levels for a plurality of biomarkers from a test sample from the subject, wherein the plurality of biomarkers comprise
- obtaining or having obtained a dataset comprising expression levels of a plurality of biomarkers comprising:
- one or more neurodegeneration biomarkers selected from a group consisting of NEFL, APLP1, OPG, SERPINA9, PRTG, GFAP, CNTN2, and FLRT2;
- one or more inflammation biomarkers selected from a group consisting of CCL20, GH, CXCL13, IL-12B, VCAN, TNFRSF10A, TNFSF13B, CD6, and CXCL9;
- one or more immune modulation biomarkers selected from a group consisting of CDCP1, and OPN;
- one or more myelin integrity biomarkers selected from a group consisting of COL4A1 and MOG;
- and
- an apparatus configured to receive a mixture of one or more reagents in the set and the test sample and to measure the expression levels for the biomarkers from the test sample;
- and
- a computer system communicatively coupled to the apparatus to obtain a dataset comprising the expression levels for the plurality of biomarkers from the test sample and to generate a prediction of multiple sclerosis disease activity by applying a predictive model to the expression levels of the plurality of biomarkers.
7 more elements
A system for determining multiple sclerosis activity in a subject, the system comprising:
- a set of reagents used for determining expression levels for a plurality of biomarkers from a test sample from the subject, wherein the plurality of biomarkers comprise two or more of:
- NEFL, MOG, CD6, CXCL9, OPG, OPN, CXCL13, GFAP, CDCP1, CCL20, IL-12B, APLP1, TNFRSF10A, COL4A1, SERPINA9, FLRT2, TNFSF13B, GH, VCAN, PRTG, and CNTN2;
- and
- an apparatus configured to receive a mixture of one or more reagents in the set and the test sample and to measure the expression levels for the biomarkers from the test sample;
- and
- a computer system communicatively coupled to the apparatus to obtain a dataset comprising the expression levels for the plurality of biomarkers from the test sample and to generate a prediction of multiple sclerosis disease activity by applying a predictive model to the expression levels of the plurality of biomarkers.
3 more elements
Dependencies are inferred from the claim text.