Multi-parameter metabolic vulnerability index evaluations
Disclosed are methods and systems to determine a subject's metabolic vulnerability index (MVX) score using at least one defined mathematical model of risk. The methods comprise evaluating various biomarkers to distinguish various health risks. In one embodiment, the method comprises evaluating biomarkers to determine a relative risk of premature all-cause mortality. The model may include NMR-derived measurements of GlycA, S-HDLP, branched chain amino acids (BCAAs), ketone bodies, total serum protein, and citrate in at least one biosample of the subject.
1. A method of determining the levels of markers associated with a subject's relative risk of premature death comprising:
obtaining a sample from the subject; and
measuring GlycA, at least one high density lipoprotein particle (HDLP) subclass, at least one branched chain amino acid (BCAA), and at least one ketone body (KetoneBody), wherein the measurement of the GlycA, the at least one HDLP subclass, the at least one BCAA, and the at least one ketone body are used to generate a metabolic vulnerability index (MVX) value.
2. The method of claim 1 , wherein the HDLP subclass is small HDLP (S-HDLP).
3. The method of claim 2 , wherein the MVX value is determined using the following model: MVX=A+β1*lnGlycA+β2*lnS-HDLP+β4*lnBCAA+β5*lnKetoneBody.
4. The method of claim 2 , wherein the MVX value is determined using the following model: MVX=A+β1*lnGlycA+β2*lnS-HDLP+β3*(lnGlycA*lnS-HDLP)+β4*lnBCAA+β5*lnKetoneBody.
5. The method of claim 4 , wherein the MVX value is determined in a subject deemed to be at low-risk for a cardiovascular event.
6. The method of claim 1 , further comprising measuring at least one of citrate (Citrate) and serum protein (Protein).
7. The method of claim 6 , wherein the measuring of at least one of citrate and serum protein is performed in a subject deemed to be at high risk for CVD related death.
8. The method of claim 6 , wherein the MVX value is determined using the following model: MVX=A+β1*lnGlycA+β2*lnS-HDLP+( 33 *(lnGlycA*lnS-HDLP)+β4*lnBCAA+β5*lnKetoneBody+β6*lnCitrate+β7*lnProtein+β8*(lnCitrate*lnProtein).
9. The method of claim 1 , wherein the MVX value is defined as comprising an inflammation index (INFX) value and a metabolic malnutrition index (MMX) value.
10. The method of claim 9 , wherein the measurement of GlycA and the at least one HDLP subclass are used to generate an inflammation index (INFX) value.
11. The method of claim 9 , wherein the INFX value is determined using the following model: INFX=β1*lnGlycA+β2*lnS-HDLP+β3*(lnGlycA*lnS-HDLP).
12. The method of claim 9 , wherein the measurement of the at least one BCAA and the at least one ketone body, and optionally protein and citrate, are used to generate the metabolic malnutrition index (MMX) value.
13. The method of claim 9 , wherein the metabolic malnutrition index (MMX) value is defined as: MMX=β4*lnBCAA+β5*lnKetoneBody+β 6 *lnCitrate+β7*lnProtein+β8*(lnCitrate*lnProtein).
14. The method of claim 9 wherein the metabolic malnutrition index (MMX) comprises a first metabolic malnutrition index MMX1 value and a second metabolic malnutrition index MMX2 value.
15. The method of claim 14 , wherein MMX=β9*MMX1+β10*MMX2.
16. The method of claim 14 , wherein MMX1=β4*lnBCAA+β5*lnKetoneBody.
17. The method of claim 14 , wherein MMX2=β6*lnCitrate+β7*lnProtein+β8*(lnCitrate*lnProtein).
18. The method of claim 14 , wherein the MVX value is determined using the following model: MVX1=βi*INFX+βm*MMX1.
19. The method of claim 18 , wherein MVX1 is determined for subjects deemed to be at low risk for a CVD related event.
20. The method of claim 14 wherein the MVX value is determined using the following model: MVX=βi*INFX+βm*MMX, wherein MMX=β9*MMX1+β10*MMX2.
21. The method of claim 20 , wherein MVX is determined for subjects deemed to be at high-risk for a CVD related event.
22. The method of claim 1 , wherein the BCAA is at least one of leucine, isoleucine, or valine.
23. The method of claim 1 , wherein the ketone bodies are at least one of acetone, acetoacetate, or beta-hydroxybutyrate.
24. The method of claim 1 , wherein the measuring is performed by NMR.
25. A system comprising:
an NMR spectrometer configured to acquire an NMR spectrum and/or spectra comprising at least one signal for GlycA, at least one signal for at least one high density lipoprotein particle (HDLP) subclass, at least one signal for at least one branched chain amino acid (BCAA), and at least one signal for at least one ketone body (KetoneBody); and
a processor to determine a metabolic vulnerability index (MVX) value based on the measured at least one signal for the GlycA, the at least one high density lipoprotein particle (HDLP) subclass, the at least one branched chain amino acid (BCAA), and the at least one ketone body (KetoneBody)
wherein the processor comprises or communicates with a memory.
26. The system of claim 25 , wherein the NMR spectrometer is further configured to acquire an NMR spectrum and/or spectra comprising at least one signal for serum protein (Protein) and/or citrate (Citrate); and
the processor to further determines the MVX value based on the measured at least one signal for the serum protein (Protein) and the citrate (Citrate).
27. A method of monitoring a patient comprising:
(a) obtaining a sample from the subject;
(b) measuring GlycA, at least one high density lipoprotein particle (HDLP) subclass, at least one branched chain amino acid (BCAA), and at least one ketone body (KetoneBody) and optionally at least one of citrate (Citrate) and serum protein (Protein) in the sample;
(c) determining a metabolic vulnerability index (MVX) value based on the measurements;
(d) repeating steps (a)-(c) at a later time point; and
(e) evaluating at least whether the MVX value has increased or decreased over time.
28. The method of claim 27 , wherein the HDLP subclass is small HDLP (S-HDLP).
29. The method of claim 27 , wherein the measuring is performed by NMR.