NMR QUANTIFICATION OF TMAO

A defined peak region residing between about 3.2 and 3.4 ppm of a proton NMR spectrum of an in vitro biosample is electronically evaluated to determine a level of trimethylamine-N-oxide (“TMAO”). The biosamples may be any suitable biosamples including human serum with a normal biologic range of between about 1-50 μM or urine with a normal biologic range of between about 0-1000 μM.

NMR quantification of TMAO

A defined peak region residing between about 3.2 and 3.4 ppm of a proton NMR spectrum of an in vitro biosample is electronically evaluated to determine a level of trimethylamine-N-oxide (“TMAO”). The biosamples may be any suitable biosamples including human serum with a normal biologic range of between about 1-50 μM or urine with a normal biologic range of between about 0-1000 μM.

NMR measurements of NMR biomarker GlycA

Biomarkers and/or risk assessments identify patients having an increased risk of certain clinical disease states including, for example, CHD, type 2 diabetes, dementia, or all-cause death (ACD) using NMR signal to measure a level of “GlycA” in arbitrary units or in defined units (e.g., μmol/L) that can be determined using a defined single peak region of proton NMR spectra. The GlycA measurement can be used as an inflammation biomarker for clinical disease states. The NMR signal for GlycA can include a fitting region of signal between about 2.080 ppm and 1.845 ppm of the proton NMR spectra.

NMR Measurements of NMR Biomarker GlycA

Biomarkers and/or risk assessments identify patients having an increased risk of certain clinical disease states including, for example, CHD, type 2 diabetes, dementia, or all-cause death (ACD) using NMR signal to measure a level of “GlycA” in arbitrary units or in defined units (e.g., μmol/L) that can be determined using a defined single peak region of proton NMR spectra. The GlycA measurement can be used as an inflammation biomarker for clinical disease states . The NMR signal for GlycA can include a fitting region of signal between about 2.080 ppm and 1.845 ppm of the proton NMR spectra.

Multi-Parameter Diabetes Risk Evaluations

Methods, systems and circuits evaluate a subject's risk of developing type 2 diabetes or developing or having prediabetes using at least one defined mathematical model of risk of progression that can stratify risk for patients having the same glucose measurement. The model may include NMR derived measurements of GlycA and a plurality of selected lipoprotein components of at least one biosample of the subject. 1. A method of evaluating a subject's risk of developing type 2 diabetes and/or of having prediabetes , comprising:programmatically calculating a diabetes risk index score of a subject using at least one defined mathematical model of risk of developing type 2 diabetes that includes at least one lipoprotein component, at least one branched chain amino acid and at least one inflammatory biomarker obtained from at least one in vitro biosample of the subject.2. The method of claim 1 , further comprising programmatically defining at least two different mathematical models of risk of developing type 2 diabetes claim 1 , the at least two different mathematical models including one for subjects on a statin therapy that includes lipoprotein component that are statin insensitive and one for subjects not on a statin therapy.3. The method of claim 1 , further comprising programmatically defining at least two different mathematical models of risk of developing type 2 diabetes claim 1 , the at least two different mathematical models with different lipoprotein components including one for fasting biosamples claim 1 , and one for non-fasting biosamples.45.-. (canceled)6. The method of claim 1 , wherein the at least one defined mathematical model of risk includes NMR derived measurements of a plurality of selected lipoprotein components of the at least one biosample of the subject claim 1 , and NMR measurements of at least one of GlycA and valine.78.-. (canceled)9. The method of claim 1 , wherein the defined mathematical risk model includes only NMR derived measurements of a ...

NMR quantification of TMAO

A defined peak region residing between about 3.2 and 3.4 ppm of a proton NMR spectrum of an in vitro biosample is electronically evaluated to determine a level of trimethylamine-N-oxide (“TMAO”). The biosamples may be any suitable biosamples including human serum with a normal biologic range of between about 1-50 μM or urine with a normal biologic range of between about 0-1000 μM.

Multi-parameter diabetes risk evaluations

Methods, systems and circuits evaluate a subject's risk of developing type 2 diabetes or having prediabetes using at least one defined mathematical model of risk of progression that can stratify risk for patients having the same glucose measurement. The model may include NMR derived measurements of GlycA and a plurality of selected lipoprotein components of at least one biosample of the subject.

NMR QUANTIFICATION OF TMAO

A defined peak region residing between about 3.2 and 3.4 ppm of a proton NMR spectrum of an in vitro biosample is electronically evaluated to determine a level of trimethylamine-N-oxide (“TMAO”). The biosamples may be any suitable biosamples including human serum with a normal biologic range of between about 1-50 μM or urine with a normal biologic range of between about 0-1000 μM. 1. A method of determining a measure of TMAO in in vitro biosamples , comprising:electronically determining a level of trimethylamine-N-oxide (“TMAO”) of an in vitro biosample using a defined TMAO peak region having a single TMAO peak residing between about 3.2 and 3.4 ppm of a proton NMR spectrum.2. The method of claim 1 , further comprising:electronically identifying a pH-stable reference peak region in the NMR spectrum of the biosample;electronically identifying a defined calibration peak region in the NMR spectrum of the biosample, wherein the calibration peak region has a location that changes based on pH of the biosample; andelectronically calculating a distance between the reference and calibration peak regions; thenelectronically determining a location of the TMAO peak for the defined TMAO peak region based on the calculated distance.3. The method of claim 2 , wherein the electronically determining the TMAO peak region location is carried out using a defined relationship of location of the reference peak region to location of the calibration peak region.4. The method of claim 1 , wherein the biosample is a blood plasma or serum wherein the defined TMAO peak is at about 3.30 ppm.5. The method of claim 1 , further comprising:electronically identifying a defined calibration peak multiplet with peaks that can vary in distance apart from one another based on pH of the biosample;determining at least one distance between one or more of the peaks in the calibration peak multiplet; andelectronically determining a pH of the biosample based on the at least one determined distance;wherein the ...

Nmr measurements of glyca

Biomarkers and/or risk assessments identify patients having an increased risk of certain clinical disease states including, for example, CHD, type 2 diabetes, dementia, or all-cause death (ACD) using NMR signal to measure a level of “GlycA” in arbitrary units or in defined units (e.g., μmol/L) that can be determined using a defined single peak region of proton NMR spectra. The GlycA measurement can be used as an inflammation biomarker for clinical disease states. The NMR signal for GlycA can include a fitting region of signal between about 2.080 ppm and 1.845 ppm of the proton NMR spectra.

MULTI-PARAMETER DIABETES RISK EVALUATIONS

Methods, systems and circuits evaluate a subject's risk of developing type 2 diabetes or developing or having prediabetes using at least one defined mathematical model of risk of progression that can stratify risk for patients having the same glucose measurement. The model may include NMR derived measurements of GlycA and a plurality of selected lipoprotein components of at least one biosample of the subject. 1. A method of evaluating a subject's risk of developing type 2 diabetes and/or of having prediabetes , comprising:programmatically calculating a diabetes risk index score of a subject using at least one defined mathematical model of risk of developing type 2 diabetes that includes at least one lipoprotein component, at least one branched chain amino acid and at least one inflammatory biomarker obtained from at least one in vitro biosample of the subject.2. The method of claim 1 , further comprising programmatically defining at least two different mathematical models of risk of developing type 2 diabetes claim 1 , the at least two different mathematical models including one for subjects on a statin therapy that includes lipoprotein component that are statin insensitive and one for subjects not on a statin therapy.3. The method of claim 1 , further comprising programmatically defining at least two different mathematical models of risk of developing type 2 diabetes claim 1 , the at least two different mathematical models with different lipoprotein components including one for fasting biosamples claim 1 , and one for non-fasting biosamples.4. The method of claim 1 , further comprising programmatically generating a report with a graph of risk of progression to type 2 diabetes in the future over a 1-7 year period versus ranges of fasting glucose levels and a quartile of risk associated with the diabetes risk index score.5. The method of claim 1 , wherein the graph shows references of at least first (low) and fourth (high) quartile DRI scores based on a defined ...

Multi-Parameter Diabetes Risk Evaluations

Methods, systems and circuits evaluate a subject's risk of developing type 2 diabetes or developing or having prediabetes using at least one defined mathematical model of risk of progression that can stratify risk for patients having the same glucose measurement. The model may include NMR derived measurements of GlycA and a plurality of selected lipoprotein components of at least one biosample of the subject. 1. A method of evaluating a subject's risk of developing type 2 diabetes and/or of having prediabetes , comprising:programmatically calculating a diabetes risk index score of a subject using at least one defined mathematical model of risk of developing type 2 diabetes that includes at least one lipoprotein component, at least one branched chain amino acid and at least one inflammatory biomarker obtained from at least one in vitro biosample of the subject.2. The method of claim 1 , further comprising programmatically defining at least two different mathematical models of risk of developing type 2 diabetes claim 1 , the at least two different mathematical models including one for subjects on a statin therapy that includes lipoprotein component that are statin insensitive and one for subjects not on a statin therapy.3. The method of claim 1 , further comprising pro grammatically defining at least two different mathematical models of risk of developing type 2 diabetes claim 1 , the at least two different mathematical models with different lipoprotein components including one for fasting biosamples claim 1 , and one for non-fasting biosamples.45-. (canceled)6. The method of claim 1 , wherein the at least one defined mathematical model of risk includes NMR derived measurements of a plurality of selected lipoprotein components of the at least one biosample of the subject claim 1 , and NMR measurements of at least one of GlycA and valine.7. The method of claim 1 , further comprising programmatically evaluating a fasting blood glucose measurement of the subject using at ...

NMR Measurements of NMR Biomarker GlycA

Biomarkers and/or risk assessments identify patients having an increased risk of certain clinical disease states including, for example, CHD, type 2 diabetes, dementia, or all-cause death (ACD) using NMR signal to measure a level of “GlycA” in arbitrary units or in defined units (e.g., μmol/L) that can be determined using a defined single peak region of proton NMR spectra. The GlycA measurement can be used as an inflammation biomarker for clinical disease states. The NMR signal for GlycA can include a fitting region of signal between about 2.080 ppm and 1.845 ppm of the proton NMR spectra.

Nmr quantification of tmao

A defined peak region residing between about 3.2 and 3.4 ppm of a proton NMR spectrum of an in vitro biosample is electronically evaluated to determine a level of trimethylamine-N-oxide (“TMAO”). The biosamples may be any suitable biosamples including human serum with a normal biologic range of between about 1-50 μM or urine with a normal biologic range of between about 0-1000 μM.

MULTI-PARAMETER DIABETES RISK EVALUATIONS

Methods, systems and circuits evaluate a subject's risk of developing type 2 diabetes or having prediabetes using at least one defined mathematical model of risk of progression that can stratify risk for patients having the same glucose measurement. The model may include NMR derived measurements of GlycA and a plurality of selected lipoprotein components of at least one biosample of the subject. 1. A method of evaluating a subject's risk of developing type 2 diabetes , comprising:programmatically calculating a diabetes risk index of a subject using at least one defined mathematical model of risk of developing type 2 diabetes that includes a measurement of at least one lipoprotein component and at least one of a measurement of (i) GlycA or GlycB or (ii) at least one branched chain amino acid, obtained from at least one in vitro biosample of the subject.2. The method of claim 1 , wherein one or more of the at least one lipoprotein component forms a numerator claim 1 , denominator or multiplication factor of at least one interaction parameter.3. The method of claim 1 , wherein the defined mathematical model of risk comprises GlycA claim 1 , wherein the at least one lipoprotein component comprises an interaction parameter defined by the measurement of GlycA multiplied by a concentration of a defined subpopulation of high density lipoprotein (HDL) particles.4. The method of claim 1 , wherein the at least one lipoprotein component of the defined mathematical model of risk comprises a first interaction parameter of the measurement of GlycA multiplied by a concentration of a defined subpopulation of high density lipoprotein (HDL) particles and wherein the HDL subpopulation comprises only medium HDL particle subclasses with diameters between about 8.3 nm (average) to about 10.0 nm (average).56-. (canceled)7. The method of claim 1 , further comprising programmatically generating a report with a graph of risk of progression to type 2 diabetes in the future versus ranges of ...

NMR Quantification of TMAO

A defined peak region residing between about 3.2 and 3.4 ppm of a proton NMR spectrum of an in vitro biosample is electronically evaluated to determine a level of trimethylamine-N-oxide (“TMAO”). The biosamples may be any suitable biosamples including human serum with a normal biologic range of between about 1-50 μM or urine with a normal biologic range of between about 0-1000 μM. 1. A method of determining a measure of TMAO in in vitro biosamples , comprising:calibrating NMR measurements for trimethylamine-N-oxide (“TMAO”) by identifying a location of a reference peak and using a defined linear relationship between the location of the reference peak and a location of the calibration peak;generating a proton NMR spectrum for an in vitro biosample; andelectronically determining a level of TMAO in the in vitro biosample using a defined TMAO peak region having a single TMAO peak residing between about 3.2 and 3.4 ppm of the proton NMR spectrum,wherein the calibration peak is electronically identified in a defined calibration peak region in the NMR spectrum of the biosample.2. The method of claim 1 , further comprising:electronically calculating a distance between the reference and calibration peak regions; andelectronically determining a location of the TMAO peak for the defined TMAO peak region based on the calculated distance.3. (canceled)4. The method of claim 1 , wherein the biosample is a blood plasma or serum wherein the defined TMAO peak is at about 3.30 ppm.5. The method of claim 1 , further comprising:electronically identifying a defined calibration peak multiplet with peaks that can vary in distance apart from one another based on pH of the biosample;determining at least one distance between one or more of the peaks in the calibration peak multiplet; andelectronically determining a pH of the biosample based on the at least one determined distance;wherein the electronically determining the location of the TMAO peak for the defined TMAO peak region is carried ...

Multi-parameter diabetes risk evaluations

Methods, systems and circuits evaluate a subject's risk of developing type 2 diabetes or having prediabetes using at least one defined mathematical model of risk of progression that can stratify risk for patients having the same glucose measurement. The model may include NMR derived measurements of GlycA and a plurality of selected lipoprotein components of at least one biosample of the subject.

Multi-parameter diabetes risk evaluations

Methods, systems and circuits evaluate a subject's risk of developing type 2 diabetes or having prediabetes using at least one defined mathematical model of risk of progression that can stratify risk for patients having the same glucose measurement. The model may include NMR derived measurements of GlycA and a plurality of selected lipoprotein components of at least one biosample of the subject.

NMR quantification of TMAO

A defined peak region residing between about 3.2 and 3.4 ppm of a proton NMR spectrum of an in vitro biosample is electronically evaluated to determine a level of trimethylamine-N-oxide (“TMAO”). The biosamples may be any suitable biosamples including human serum with a normal biologic range of between about 1-50 μM or urine with a normal biologic range of between about 0-1000 μM.

Nmr measurements of glyca

Biomarkers and/or risk assessments identify patients having an increased risk of certain clinical disease states including, for example, CHD, type 2 diabetes, dementia, or all-cause death (ACD) using NMR signal to measure a level of "GlycA" in arbitrary units or in defined units (e.g., µmol/L) that can be determined using a defined single peak region of proton NMR spectra. The GlycA measurement can be used as an inflammation biomarker for clinical disease states. The NMR signal for GlycA can include a fitting region of signal between about 2.080 ppm and 1.845 ppm of the proton NMR spectra.

Nmr measurements of glyca

Nmr measurements of glyca

Biomarkers and/or risk assessments identify patients having an increased risk of certain clinical disease states including, for example, CHD, type 2 diabetes, dementia, or all-cause death (ACD) using NMR signal to measure a level of "GlycA" in arbitrary units or in defined units (e.g., µmοl/L) that can be determined using a defined single peak region of proton NMR spectra. The GlycA measurement can be used as an inflammation biomarker for clinical disease states. The NMR signal for GlycA can include a fitting region of signal between about 2.080 ppm and 1.845 ppm of the proton NMR spectra.

Nmr measurements of glyca

Biomarkers and/or risk assessments identify patients having an increased risk of certain clinical disease states including, for example, CHD, type 2 diabetes, dementia, or all-cause death (ACD) using NMR signal to measure a level of "GlycA" in arbitrary units or in defined units (e.g., µmol/L) that can be determined using a defined single peak region of proton NMR spectra. The GlycA measurement can be used as an inflammation biomarker for clinical disease states. The NMR signal for GlycA can include a fitting region of signal between about 2.080 ppm and 1.845 ppm of the proton NMR spectra.

Nmr measurements of glyca

(12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization International Bureau (43) International Publication Date 12 December 2013 (12.12.2013) WIPOIPCT (10) International Publication Number WO 2013/184483 A1 (51) International Patent Classification: G01N24/08 (2006.01) G01N33/49 (2006.01) A61B 5/055 (2006.01) (21) International Application Number: (22) International Filing Date: (25) Filing Language: (26) Publication Language: PCT/US2013/043343 30 May 2013 (30.05.2013) English (30) Priority Data: 61/657,315 8 June 2012 (08.06.2012) 61/711,471 9 October 2012 (09.10.2012) 61/739,305 19 December 2012 (19.12.2012) 13/830,199 14 March 2013 (14.03.2013) English US US us us (71) Applicant: LIPOSCIENCE, INC. [US/US]; 2500 Sumner Boulevard, Raleigh, North Carolina 27616 (US). (72) Inventors: OTVOS, James D.; 1117 Wellstone Circle, Apex, North Carolina 27502 (US). SHALAUROVA, Ir- ina Y.; 315 Ambermore Place, Cary, North Carolina 27519 (US). BENNETT, Dennis W.; 4242 North Morris Blvd., Shorewood, Wisconsin 53211 (US). WOLAK- DINSMORE, Justyna E.; 2808 Mebane Ln., Durham, North Carolina 27703 (US). (74) Agent: MYERS BIGEL SIBLEY & SAJOVEC, P.A.; P.O. Box 37428, Raleigh, North Carolina 27627 (US). (81) Designated States (unless otherwise indicated, for every kind of national protection available)'. AE, AG, AL, AM, AO, AT, AU, AZ, BA, BB, BG, BH, BN, BR, BW, BY, BZ, CA, CH, CL, CN, CO, CR, CU, CZ, DE, DK, DM, DO, DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, HR, HU, ID, IL, IN, IS, JP, KE, KG, KN, KP, KR, KZ, LA, LC, LK, LR, LS, LT, LU, LY, MA, MD, ME, MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, OM, PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SC, SD, SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW. (84) Designated States (unless otherwise indicated, for every kind of regional protection available)'. ARIPO (BW, GH, GM, KE, LR, LS, MW, MZ, NA ...

Nmr measurements of glyca

Biomarkers and/or risk assessments identify patients having an increased risk of certain clinical disease states including, for example, CHD, type 2 diabetes, dementia, or all-cause death (ACD) using NMR signal to measure a level of "GlycA" in arbitrary units or in defined units (e.g., mol/L) that can be determined using a defined single peak region of proton NMR spectra. The GlycA measurement can be used as an inflammation biomarker for clinical disease states. The NMR signal for GlycA can include a fitting region of signal between about 2.080 ppm and 1.845 ppm of the proton NMR spectra.

Multi-Parameter Diabetes Risk Evaluations

Methods, systems and circuits evaluate a subject's risk of developing type 2 diabetes or developing or having prediabetes using at least one defined mathematical model of risk of progression that can stratify risk for patients having the same glucose measurement. The model may include NMR derived measurements of GlycA and a plurality of selected lipoprotein components of at least one biosample of the subject.

Multi-parameter diabetes risk evaluations

Multi-parameter diabetes risk evaluations

Methods, systems and circuits evaluate a subject's risk of developing type 2 diabetes or having prediabetes using at least one defined mathematical model of risk of progression that can stratify risk for patients having the same glucose measurement. The model may include NMR derived measurements of GlycA and a plurality of selected lipoprotein components of at least one biosample of the subject.

Methods and Systems for Measuring Citrate and Creatinine Levels by NMR Spectroscopy

Methods and systems for detecting a presence and a concentration of biomarkers relevant to kidney stone formation may be useful in determining a personalized therapeutic approach for a subject. Nuclear Magnetic Resonance (NMR) spectroscopy may be a valuable tool in detecting various biomarkers related to various disease states. A biosample obtained from a subject may be examined using NMR spectroscopy to determine the presence and the concentration of relevant biomarkers.

Nmr quantification of tmao

A defined peak region residing between about 3.2 and 3.4 ppm of a proton NMR spectrum of an in vitro biosample is electronically evaluated to determine a level of trimethylamine-N-oxide ("TMAO"). The biosamples may be any suitable biosamples including human serum with a normal biologic range of between about 1-50 µM or urine with a normal biologic range of between about 0-1000 µM.

Nmr quantification of tmao

NMR Quantification of TMAO

A defined peak region residing between about 3.2 and 3.4 ppm of a proton NMR spectrum of an in vitro biosample is electronically evaluated to determine a level of trimethylamine-N-oxide (“TMAO”). The biosample may be any suitable biosamples including human serum with a normal biologic range of between about 1-50 μM or urine with a normal biologic range of between about 0-1000 μM.

Methods and systems for measuring citrate and creatinine levels by nmr spectroscopy

Methods and systems for detecting a presence and a concentration of biomarkers relevant to kidney stone formation may be useful in determining a personalized therapeutic approach for a subject. Nuclear Magnetic Resonance (NMR) spectroscopy may be a valuable tool in detecting various biomarkers related to various disease states. A biosample obtained from a subject may be examined using NMR spectroscopy to determine the presence and the concentration of relevant biomarkers.

Multi-parameter diabetes risk evaluations

Methods, systems and circuits evaluate a subject's risk of developing type 2 diabetes or having prediabetes using at least one defined mathematical model of risk of progression that can stratify risk for patients having the same glucose measurement. The model may include NMR derived measurements of GlycA and a plurality of selected lipoprotein components of at least one biosample of the subject.

Nmr measurements of glyca for determining coronary heart disease risk

Nmr measurements of glyca for determining coronary heart disease risk

Biomarkers and/or risk assessments identify patients having an increased risk of certain clinical disease states including, for example, CHD, type 2 diabetes, dementia, or all-cause death (ACD) using NMR signal to measure a level of "GlycA" in arbitrary units or in defined units (e.g., µmol/L) that can be determined using a defined single peak region of proton NMR spectra. The GlycA measurement can be used as an inflammation biomarker for clinical disease states. The NMR signal for GlycA can include a fitting region of signal between about 2.080 ppm and 1.845 ppm of the proton NMR spectra.