Methods for quantification of insulin and C-peptide

Abstract

To provide an accurate and reliable method for determining an insulin resistance.SOLUTION: The present invention relates to methods for diagnosing or prognosing insulin resistance in diabetic and pre-diabetic patients, the method comprising the steps of: determining an amount of insulin and C- peptide in a sample; detecting and quantifying insulin and C-peptide in a biological sample utilizing enrichment and / or purification methods coupled with tandem mass spectrometric or high resolution / high accuracy mass spectrometric techniques.SELECTED DRAWING: Figure 1A

Description

[Technical Field]

[0001] Cross-reference to related patent applications This application claims the benefit under 35 U.S.C. §119(e) of U.S. Provisional Application No. 62 / 480,029, filed March 31, 2017, and U.S. Provisional Application No. 62 / 644,378, filed March 16, 2018, the contents of which are incorporated herein by reference in their entireties. [Background technology]

[0002] Insulin resistance varies several-fold in apparently healthy populations, and the most insulin-resistant individuals, approximately one-quarter to one-third, are at increased risk for developing a constellation of metabolic disorders and associated clinical syndromes. Direct estimation of insulin-mediated glucose disposal is impractical at the clinical level. However, plasma insulin concentrations are highly correlated with direct measures of insulin-mediated glucose disposal, leading to the introduction of several surrogate estimates of insulin resistance based on measurements of plasma insulin and glucose concentrations. Unfortunately, no standardized insulin assays exist. As a result, it has been impossible to establish universally applicable numerical cutpoints by which to identify apparently healthy individuals who are sufficiently insulin resistant to be at high risk for multiple adverse clinical outcomes.

[0003] In response to this dilemma, several surrogate markers based on commonly measured metabolic abnormalities associated with IR have been proposed to help identify insulin-resistant individuals before the onset of overt disease. For example, the diagnosis of metabolic syndrome (MetS) is an example of this approach. Although the diagnosis of MetS is associated with direct measurements of insulin-mediated glucose disposal, only approximately 50% of the most insulin-resistant group—the one-third of apparently healthy individuals—met the MetS diagnosis. Summary of the Invention [Problem to be solved by the invention]

[0004] There is a need for reliable and accurate methods to identify insulin resistance. [Means for solving the problem]

[0005] In one aspect, provided herein is a method for diagnosing or prognosing insulin resistance in diabetes and prediabetes patients, the method comprising measuring insulin and c-peptide levels in the patient by determining the amount of insulin and C-peptide in a sample.

[0006] In certain embodiments, the methods provided herein include a multiplex assay for simultaneously measuring the amount of insulin and C-peptide in a sample by mass spectrometry. In some embodiments, the method includes (a) subjecting insulin and C-peptide from the sample to an ionization source under conditions suitable for generating one or more insulin and C-peptide ions detectable by mass spectrometry, and (b) determining the amount of the one or more insulin and C-peptide ions by mass spectrometry.

[0007] In some embodiments, insulin resistance is diagnosed when insulin levels are 7 μIU / mL or greater, as determined by the mass spectrometry methods described herein. In some embodiments, insulin resistance is diagnosed when insulin levels are 8 μIU / mL or greater, as determined by the mass spectrometry methods described herein. In some embodiments, insulin resistance is diagnosed when insulin levels are 9 μIU / mL or greater, as determined by the mass spectrometry methods described herein. In some embodiments, insulin resistance is diagnosed when insulin levels are 10 μIU / mL or greater, as determined by the mass spectrometry methods described herein. In some embodiments, insulin resistance is diagnosed when insulin levels are 11 μIU / mL or greater, as determined by the mass spectrometry methods described herein. In some embodiments, insulin resistance is diagnosed when insulin levels are 12 μIU / mL or greater, as determined by the mass spectrometry methods described herein. In some embodiments, insulin resistance is diagnosed when insulin levels are 13 μIU / mL or greater, as determined by the mass spectrometry methods described herein. In some embodiments, insulin resistance is diagnosed when insulin levels are 14 μIU / mL or greater, as determined by the mass spectrometry methods described herein. In some embodiments, insulin resistance is diagnosed if the insulin level is 15 μIU / mL or greater as determined by the mass spectrometry methods described herein.

[0008] In a preferred embodiment, insulin resistance is diagnosed if the insulin level is 15 μIU / mL or greater as determined by the mass spectrometry methods described herein.

[0009] In some embodiments, insulin resistance is diagnosed when C-peptide levels are 1.4 ng / mL or higher as determined by the mass spectrometry methods described herein. In some embodiments, insulin resistance is diagnosed when C-peptide levels are 1.5 ng / mL or higher as determined by the mass spectrometry methods described herein. In some embodiments, insulin resistance is diagnosed when C-peptide levels are 1.6 ng / mL or higher as determined by the mass spectrometry methods described herein. In some embodiments, insulin resistance is diagnosed when C-peptide levels are 1.7 ng / mL or higher as determined by the mass spectrometry methods described herein. In some embodiments, insulin resistance is diagnosed when C-peptide levels are 1.8 ng / mL or higher as determined by the mass spectrometry methods described herein. In some embodiments, insulin resistance is diagnosed when C-peptide levels are 1.9 ng / mL or higher as determined by the mass spectrometry methods described herein. In some embodiments, insulin resistance is diagnosed when C-peptide levels are 2 ng / mL or higher as determined by the mass spectrometry methods described herein. In some embodiments, insulin resistance is diagnosed when C-peptide levels are 2.1 ng / mL or higher as determined by the mass spectrometry methods described herein. In some embodiments, insulin resistance is diagnosed when C-peptide levels are 2.2 ng / mL or higher as determined by the mass spectrometry methods described herein. In some embodiments, insulin resistance is diagnosed when C-peptide levels are 2.3 ng / mL or higher as determined by the mass spectrometry methods described herein. In some embodiments, insulin resistance is diagnosed when C-peptide levels are 2.4 ng / mL or higher as determined by the mass spectrometry methods described herein.

[0010] In a preferred embodiment, insulin resistance is diagnosed if the C-peptide level is 2.4 ng / mL or greater as determined by the mass spectrometry methods described herein.

[0011] In some embodiments, an insulin resistance score (RS) and / or a probability of developing insulin resistance P(IR) are provided herein based on insulin and C-peptide levels measured by the methods provided herein.

[0012] In some embodiments, the insulin resistance score (RS) and / or the probability of developing insulin resistance P(IR) is determined by: RS = (insulin x 0.0295) + (C-peptide x 0.00372)

[0013]

number

[0014] In some embodiments, an insulin resistance score (RS) and / or probability of developing insulin resistance P(IR) is provided herein based on insulin and C-peptide levels measured by the methods provided herein and creatine levels measured by standard methods.

[0015] In some embodiments, the insulin resistance score (RS) and / or the probability of developing insulin resistance P(IR) is determined by: RS = (insulin x 0.0265) + (C-peptide x 0.00511) + (creatinine x -3.2641)

[0016]

number

[0017] In some embodiments, an insulin resistance score (RS) and / or probability of developing insulin resistance P(IR) is provided herein based on levels of insulin and C-peptide measured by the methods provided herein, and creatine, triglycerides (TG) / HDL-C, and BMI measured by standard methods.

[0018] In some embodiments, the insulin resistance score (RS) and / or the probability of developing insulin resistance P(IR) is determined by: RS = (insulin x 0.0227) + (C-peptide x 0.0046) + (creatinine x -3.5553) + (TG / HDL-C x 0.101) + (BMI x 0.0711)

[0019]

number

[0020] In some embodiments, insulin resistance is diagnosed if the steady-state plasma glucose (SSPG) concentration is in the upper tertile of a given population. In some embodiments, insulin resistance is diagnosed if the SSPG concentration is ≧190 mg / dL. In some embodiments, insulin resistance is diagnosed if the SSPG concentration is ≧195 mg / dL. In some embodiments, insulin resistance is diagnosed if the SSPG concentration is ≧198 mg / dL. In some embodiments, insulin resistance is diagnosed if the SSPG concentration is ≧200 mg / dL. In some embodiments, insulin resistance is diagnosed if the SSPG concentration is ≧205 mg / dL.

[0021] In some embodiments, insulin resistance is diagnosed by a combination of insulin and C-peptide levels determined by the mass spectrometry methods described herein. In some embodiments, insulin resistance is diagnosed by a combination of insulin and C-peptide levels determined by the mass spectrometry methods described herein. In some embodiments, insulin resistance is diagnosed by a combination of insulin and C-peptide levels and SSPG concentrations determined by the mass spectrometry methods described herein.

[0022] In some embodiments, the determined amount of one or more ions is used to determine the amount of insulin and C-peptide in the sample, hi some embodiments, the amount of insulin and C-peptide in the sample is related to the amount of insulin in the patient.

[0023] In some embodiments, the method includes (a) subjecting the sample to a concentration step to obtain a fraction enriched in insulin and C-peptide; (b) subjecting the enriched insulin and C-peptide to an ionization source under conditions suitable for generating one or more insulin and C-peptide ions detectable by mass spectrometry; and (c) determining the amount of the one or more insulin and C-peptide ions by mass spectrometry. In some embodiments, the determined amount of one or more ions is used to determine the amount of insulin and C-peptide in the sample. In some embodiments, the amount of insulin and C-peptide in the sample is related to the amount of insulin in the patient. In some embodiments, the amount of insulin and C-peptide in the sample is used to determine the ratio of insulin to C-peptide in the patient.

[0024] In some embodiments, the enrichment process provided herein comprises immunocapturing insulin and C-peptide using antibodies. In some embodiments, the method comprises (a) immunocapturing insulin and C-peptide, (b) subjecting the immunocaptured insulin and C-peptide to an ionization source under conditions suitable for generating one or more insulin and C-peptide ions detectable by mass spectrometry, and (c) determining the amount of the one or more insulin and C-peptide ions by mass spectrometry.

[0025] In some embodiments, the immunocapturing step provided herein comprises using an anti-insulin antibody and an anti-C-peptide antibody. In some embodiments, the antibody provided herein is a monoclonal antibody. In some embodiments, the antibody provided herein is a mouse monoclonal antibody. In some embodiments, the antibody provided herein is a monoclonal IgG antibody. In some embodiments, the antibody provided herein is a polyclonal antibody.

[0026] In some embodiments, the anti-insulin and anti-C-peptide antibodies are immobilized on magnetic beads, hi some embodiments, the immunocaptured insulin and C-peptide on the magnetic beads are washed and eluted.

[0027] In some embodiments, the serum is delipidated prior to quantification by mass spectrometry. In some embodiments, one or more delipidation reagents are used to remove lipids from the sample. In some embodiments, the delipidation reagent is CLEANASCITE®.

[0028] In some embodiments, the methods provided herein include purifying the sample prior to mass spectrometry. In some embodiments, the methods include purifying the sample using liquid chromatography. In some embodiments, the liquid chromatography includes high performance liquid chromatography (HPLC) or high turbulence liquid chromatograph (HTLC). In some embodiments, the methods include subjecting the sample to solid phase extraction (SPE).

[0029] In some embodiments, the mass spectrometry comprises tandem mass spectrometry. In some embodiments, the mass spectrometry is high-resolution mass spectrometry. In some embodiments, the mass spectrometry is high-resolution / high-accuracy mass spectrometry.

[0030] In some embodiments, ionization is by electrospray ionization (ESI). In some embodiments, ionization is by atmospheric pressure chemical ionization (APCI). In some embodiments, the ionization is in positive ion mode.

[0031] In some embodiments, the methods provided herein include adding an internal standard to the sample. In some embodiments, the internal standard for insulin is bovine insulin. In some embodiments, the internal standard for C-peptide is a C-peptide heavy internal standard. In some embodiments, the internal standard is labeled. In some embodiments, the internal standard is deuterated or isotopically labeled.

[0032] In some embodiments, the patient sample is a serum sample. In some embodiments, the patient sample is a plasma sample. In some embodiments, the patient sample is a blood, saliva, or urine sample.

[0033] In some embodiments, the sample is subjected to acidic conditions prior to ionization. In some embodiments, subjecting the sample to acidic conditions comprises exposing the concentrated insulin and C-peptide to formic acid.

[0034] In some embodiments, the sample is subjected to basic conditions prior to mass spectrometry. In some embodiments, subjecting the sample to basic conditions comprises exposing the sample to Trizma. In some embodiments, subjecting the sample to basic conditions comprises exposing the sample to Trizma and ethanol.

[0035] In some embodiments, the one or more ions comprise an insulin precursor ion having a mass-to-charge ratio (m / z) of 968.7±0.5. In some embodiments, the one or more ions comprise one or more fragment ions selected from the group consisting of ions having m / z of 136.0±0.5, 226.1±0.5, and 345.2±0.5. In some embodiments, the insulin fragment ion having m / z of 226.1±0.5 is a quantifier ion. In some embodiments, the one or more ions comprise a bovine insulin precursor ion having a mass-to-charge ratio (m / z) of 956.8±0.5. In some embodiments, the one or more ions comprise one or more fragment ions selected from the group consisting of ions having m / z of 136.0±0.5, 226.1±0.5, and 315.2±0.5. In some embodiments, a bovine insulin fragment ion with m / z of 136.0±0.5 is the quantifier ion.

[0036] In some embodiments, the one or more ions comprise a C-peptide precursor ion having a mass-to-charge ratio (m / z) of 1007.7±0.5. In some embodiments, the one or more ions comprise one or more fragment ions selected from the group consisting of ions having m / z of 533.3±0.5, 646.4±0.5, and 927.5±0.5. In some embodiments, the intensity of any or the sum of the C-peptide fragment ions having m / z of 533.3±0.5, 646.4±0.5, and 927.5±0.5 can be used for quantitation. In some embodiments, the one or more ions comprise a C-peptide heavy internal standard precursor ion having a mass-to-charge ratio (m / z) of 1009.5±0.5. In some embodiments, the one or more ions include one or more fragment ions selected from the group consisting of ions having m / z of 540.3±0.5, 653.4±0.5, and 934.5±0.5, hi some embodiments, the intensity of any one or the sum of the C-peptide heavy internal standard fragment ions having m / z of 540.3±0.5, 653.4±0.5, and 934.5±0.5 can be used for quantitation.

[0037] In some embodiments, provided herein is the use of mass spectrometry to determine the amount of insulin and C-peptide in a sample, the method comprising: (a) concentrating insulin and C-peptide in the sample by extraction techniques; (b) subjecting the purified insulin and C-peptide from step (a) to liquid chromatography to obtain an insulin- and C-peptide-enriched fraction from the sample; (c) subjecting the concentrated insulin to an ionization source under conditions suitable for generating insulin precursor ions detectable by mass spectrometry; and (d) determining the amount of one or more fragment ions by mass spectrometry. In some embodiments, the determined amount of one or more ions is used to determine the amount of insulin and C-peptide in the sample. In some embodiments, the amount of insulin and C-peptide in the sample is correlated with the amount of insulin in the patient. In some embodiments, the amount of insulin and C-peptide in the sample is used to determine the ratio of insulin to C-peptide in the patient.

[0038] In some embodiments, extraction techniques provided herein include immunocapture of insulin and C-peptide using antibodies, hi some embodiments, extraction techniques provided herein include solid phase extraction (SPE).

[0039] In some embodiments, the collision energy is in the range of about 40-60 V. In some embodiments, the collision energy is in the range of about 40-50 V.

[0040] In another aspect, provided herein are methods for determining the amount of insulin or C-peptide in a sample by mass spectrometry, the methods comprising: (a) immunocapturing insulin or C-peptide; (b) subjecting the immunocaptured insulin or C-peptide to an ionization source under conditions suitable for generating one or more insulin or C-peptide ions detectable by mass spectrometry; and (c) determining the amount of the one or more insulin or C-peptide ions by mass spectrometry. In some embodiments, provided herein are methods for determining the amount of insulin in a sample by mass spectrometry, the methods comprising: (a) immunocapturing insulin; (b) subjecting the immunocaptured insulin to an ionization source under conditions suitable for generating one or more insulin ions detectable by mass spectrometry; and (c) determining the amount of the one or more insulin ions by mass spectrometry. In some embodiments, provided herein are methods for determining the amount of C-peptide in a sample by mass spectrometry, comprising: (a) immunocapturing C-peptide; (b) subjecting the immunocaptured C-peptide to an ionization source under conditions suitable for generating one or more C-peptide ions detectable by mass spectrometry; and (c) determining the amount of the one or more C-peptide ions by mass spectrometry. In some embodiments, the immunocapturing step comprises using an anti-insulin antibody or an anti-C-peptide antibody. In some embodiments, the anti-insulin antibody or anti-C-peptide antibody is immobilized on magnetic beads. In some embodiments, the immunocaptured insulin or C-peptide on the magnetic beads is washed and eluted.

[0041] In another aspect, provided herein are methods for diagnosing diabetes and other glycemic disorders in pre-diabetic patients. In some embodiments, the methods provided herein for quantifying endogenous insulin and C-peptide are used to diagnose diabetes. In some embodiments, the methods provided herein for quantifying endogenous insulin and C-peptide are used to distinguish between insulin-secreting tumors and exogenous insulin administration as causes of hypoglycemia. In some embodiments, the methods provided herein for quantifying endogenous insulin and C-peptide are used to distinguish between type 1 diabetes and type 2 diabetes. In some embodiments, the methods provided herein for quantifying endogenous insulin and C-peptide are used to assess the risk of diabetes in pre-diabetic patients.

[0042] In some embodiments, the mass spectrometry comprises tandem mass spectrometry. In some embodiments, the mass spectrometry is high-resolution mass spectrometry. In some embodiments, the mass spectrometry is high-resolution / high-accuracy mass spectrometry.

[0043] In another aspect, certain methods described herein utilize high-resolution / high-accuracy mass spectrometry to determine the amount of insulin in a sample. In some embodiments utilizing high-accuracy / high-resolution mass spectrometry, the method includes (a) subjecting insulin from a sample to an ionization source under conditions suitable for generating multiply charged insulin ions (which can be detected by mass spectrometry), and (b) determining the amount of one or more multiply charged insulin ions by high-resolution / high-accuracy mass spectrometry. In these embodiments, the amount of one or more ions determined in step (b) is related to the amount of insulin in the sample. In some embodiments, the high-resolution / high-accuracy mass spectrometry is performed with a FWHM of 10,000 and a mass accuracy of 50 ppm. In some embodiments, the high-resolution / high-accuracy mass spectrometry is performed using a high-resolution / high-accuracy time-of-flight (TOF) mass spectrometer. In some embodiments, the ionization conditions include ionizing insulin under acidic conditions. In some related embodiments, the acidic conditions include treating the sample with formic acid prior to ionization. In some embodiments, the multiply charged insulin ions are selected from the group consisting of 4+, 5+, and 6+ charged insulin ions.

[0044] In some embodiments, the one or more insulin ions in the 6+ charge state include one or more ions having an m / z within the range of about 968.8±1.5. In some embodiments, the one or more insulin ions in the 6+ charge state include one or more ions selected from the group consisting of ions having an m / z of 968.28±0.1, 968.45±0.1, 968.62±0.1, 968.79±0.1, 968.95±0.1, 969.12±0.1, 969.28±0.1, 969.45±0.1, 969.61±0.1, such as an ion having an m / z of 968.95±0.1.

[0045] In some embodiments, the one or more insulin ions in the 5+ charge state include one or more ions having an m / z within the range of about 1162.5±1.0. In some embodiments, the one or more insulin ions in the 5+ charge state include one or more ions selected from the group consisting of ions having an m / z of 1161.72±0.1, 1161.92±0.1, 1162.12±0.1, 1162.32±0.1, 1162.52±0.1, 1162.72±0.1, 1162.92±0.1, 1163.12±0.1, 1163.32±0.1, such as an ion having an m / z of 1162.54±0.1.

[0046] In some embodiments, the one or more insulin ions in the 4+ charge state include one or more ions having an m / z within the range of about 1452.9±0.8.

[0047] In any of the methods described herein, the sample may comprise a biological sample. In some embodiments, the biological sample may comprise a biological fluid such as urine, plasma, or serum. In some embodiments, the biological sample may comprise a sample from a human, e.g., an adult male or female, or a juvenile male or female, where juvenile is under 18, under 15, under 12, or under 10 years of age. The human sample may be analyzed to diagnose or monitor a disease state or condition, or to monitor the efficacy of a treatment for a disease state or condition. In some related embodiments, the methods described herein can be used to determine the amount of insulin in a biological sample when obtained from a human.

[0048] In embodiments utilizing tandem mass spectrometry, the tandem mass spectrometry can be performed by methods known in the art, including, for example, multiple reaction monitoring, precursor ion scanning, or product ion scanning.

[0049] In some embodiments, tandem mass spectrometry includes fragmenting a precursor ion into one or more fragment ions. In embodiments in which the amount of two or more fragment ions is determined, the measured ion amounts can be subjected to mathematical manipulations known in the art to relate the amounts to the amount of insulin in the sample. For example, the amounts of two or more fragment ions can be summed as part of determining the amount of insulin in the sample.

[0050] In any of the methods described herein, the analyte of interest (e.g., insulin, or chemically modified or unmodified insulin) can be purified from the sample by high performance liquid chromatography (HPLC) prior to ionization. In any of the methods described herein, the analyte of interest can be purified from the sample by an extraction technique, such as, for example, applying the sample to a solid phase extraction (SPE) column. In some embodiments, the extraction technique is not an immunopurification technique. Specifically, in some embodiments, the SPE column is not an immunoaffinity column. In some embodiments, immunopurification is not used at any stage of the method. In some embodiments, the extraction technique and HPLC can be performed online to allow for automated sample processing and analysis.

[0051] In some embodiments, high-resolution / high-accuracy mass analysis is performed at a resolution (FWHM) of about 10,000 or greater, such as about 15,000 or greater, such as about 20,000 or greater, such as about 25,000 or greater. In some embodiments, high-resolution / high-accuracy mass analysis is performed at an accuracy of about 50 ppm or less, such as about 20 ppm or less, such as about 10 ppm or less, such as about 5 ppm or less, or about 3 ppm or less. In some embodiments, high-resolution / high-accuracy mass analysis is performed at a resolution (FWHM) of about 10,000 or greater and an accuracy of about 50 ppm or less. In some embodiments, the resolution is about 15,000 or greater and the accuracy is about 20 ppm or less. In some embodiments, the resolution is about 20,000 or greater and the accuracy is about 10 ppm or less, preferably the resolution is about 20,000 or greater and the accuracy is about 5 ppm or less, such as about 3 ppm or less.

[0052] In some embodiments, high resolution / accuracy mass analysis can be performed using an orbitrap mass spectrometer, a time-of-flight (TOF) mass spectrometer, or a Fourier transform ion cyclotron resonance mass spectrometer (sometimes known as a Fourier transform mass spectrometer).

[0053] In some embodiments, the one or more insulin ions detectable by high-resolution / high-accuracy mass spectrometry are one or more ions selected from the group consisting of ions having m / z within the ranges of about 1452.9±0.8, 1162.5±1, and 968.8±1.5. Ions within these ranges correspond to insulin ions with 4+, 5+, and 6+ charges, respectively. Monoisotopic ions with these charges primarily fall within the m / z ranges listed. However, lower abundance naturally occurring isotopic variants may exist outside this range. Insulin ions within the range of 1162.5±1 preferably include insulin ions having m / z of about 1161.72±0.1, 1161.92±0.1, 1162.12±0.1, 1162.32±0.1, 1162.52±0.1, 1162.72±0.1, 1162.92±0.1, 1163.12±0.1, 1163.32±0.1, such as an ion having m / z of 1162.54±0.1. Insulin ions within the range of 968.8±1.5 preferably include insulin ions having m / z of about 968.28±0.1, 968.45±0.1, 968.62±0.1, 968.79±0.1, 968.95±0.1, 969.12±0.1, 969.28±0.1, 969.45±0.1, 969.61±0.1, such as an ion having m / z of 968.95±0.1. In some embodiments, relating the amount of one or more insulin ions detected by mass spectrometry to the amount of insulin protein in the sample includes comparison to an internal standard, such as human or non-human insulin protein. The internal standard can optionally be isotopically labeled.

[0054] In any of the methods described herein, the sample may comprise a biological sample, preferably a bodily fluid sample, including, for example, plasma or serum.

[0055] Mass spectrometry (tandem or high resolution / high accuracy) can be performed in positive ion mode. Alternatively, mass spectrometry can be performed in negative ion mode. Various ionization sources can be used to ionize insulin, including, for example, atmospheric pressure chemical ionization (APCI) or electrospray ionization (ESI). In some embodiments, insulin and / or chemically modified or unmodified insulin B chains are ionized by ESI in positive ion mode.

[0056] In any of the methods described herein, a separately detectable internal standard can be added to the sample, and its amount can also be determined in the sample. In embodiments utilizing a separately detectable internal standard, all or a portion of both the analyte of interest and the internal standard present in the sample are ionized to produce multiple ions that can be detected by a mass spectrometer, and one or more ions produced from each are detected by mass spectrometry. In these embodiments, the presence or amount of ions produced from the analyte of interest can be related to the amount of analyte of interest present in the sample by comparison with the amount of the detected internal standard ions.

[0057] Alternatively, the amount of insulin in a sample can be determined by comparison to one or more external reference standards, such as blank plasma or serum spiked with human or non-human insulin, synthetic insulin analogs, or isotopically labeled variants thereof.

[0058] In some embodiments, the method is capable of determining the amount of insulin in a sample at levels within the range of about 10 μIU / mL to 500 μIU / mL.

[0059] The above summary of the invention is non-limiting; other features and advantages of the invention will be apparent from the following detailed description of the invention and from the claims. [Brief explanation of the drawings]

[0060] [Figure 1A]1 is a graph showing odds ratios for those in the top quartile for insulin or C-peptide levels versus those not in the top quartile. The odds ratios are from models adjusted for age, sex, fasting plasma glucose, insulin, C-peptide, HDL-C, LDL-C, triglycerides, creatinine, alanine aminotransferase, body mass index, systolic and diastolic blood pressure. [Figure 1B] 1 is a graph showing odds ratios for those in the top quartile for insulin or C-peptide levels versus those not in the top quartile. The odds ratios are from models adjusted for age, sex, fasting plasma glucose, insulin, C-peptide, HDL-C, LDL-C, triglycerides, creatinine, alanine aminotransferase, body mass index, systolic and diastolic blood pressure. [Figure 1C] 1 is a graph showing odds ratios for those in the top quartile for insulin or C-peptide levels versus those not in the top quartile. The odds ratios are from models adjusted for age, sex, fasting plasma glucose, insulin, C-peptide, HDL-C, LDL-C, triglycerides, creatinine, alanine aminotransferase, body mass index, systolic and diastolic blood pressure. [Figure 2] Boxplots showing fasting insulin levels in patients with fasting glucose <90 mg / dL (left), 90 to <100 mg / dL (center), and 100 to 125 mg / dL (right). Differences in insulin levels between categories were assessed by parametric (ANOVA) and nonparametric (Kruksal-Wallis) methods. [Figure 3] Box plots showing fasting insulin levels in normoglycemic participants (fasting glucose <100 mg / dL). Left: BMI <26; Right: BMI ≥ 26. Differences in insulin levels between categories were assessed by t-test. [Figure 4] 1 is a graph showing the relationship between fasting blood glucose measurements and fasting insulin levels. [Figure 5]1 is a graph showing the relationship between fasting blood glucose measurements and fasting C-peptide levels. [Figure 6] Graph showing insulin levels by BMI category, sex, and fasting glucose. [Figure 7] FIG. 1 shows an overview of the methods presented herein. [Figure 8] FIG. 1 shows the fragmentation of intact insulin and the mass-to-charge ratios of the measured ions. [Figure 9] FIG. 1 shows the fragmentation of C-peptide and the mass-to-charge ratios of the measured ions. [Figure 10-1] 1 is a graph showing the chromatography of insulin and C-peptide. [Figure 10-2] Continued from Figure 10-1. [Figure 11-1] 1 is a graph showing standard curves for insulin and C-peptide. [Figure 11-2] Continued from Figure 11-1. [Figure 12] FIG. 1 shows the accuracy of controls versus calibrators adjusted for peptide content. [Figure 13] FIG. 1 is a graph showing insulin correlation (n=117) of the method presented herein versus the Beckman assay. [Figure 14] FIG. 1 is a graph showing C-peptide correlation (n=121) of the method presented herein versus the Centaur ICMA assay. [Figure 15] 10 is a graph showing C-peptide calibrators in the Centaur ICMA. [Figure 16] FIG. 1 shows an overview of the verification results for insulin. [Figure 17] FIG. 1 shows an overview of the verification results for C-peptide. [Figure 18] 1 is a graph showing the relationship between creatinine and C-peptide. [Figure 19] FIG. 1 shows the insulin resistance scores of samples based on insulin and C-peptide levels. DETAILED DESCRIPTION OF THE INVENTION

[0061] As used herein, the singular forms "a," "an," and "the" include plural referents unless otherwise indicated. Thus, for example, reference to "a protein" includes a plurality of protein molecules.

[0062] As used herein, the terms "purify," "purify," and "enrich" do not refer to the removal of all substances from a sample other than the analyte(s) of interest. Instead, these terms refer to procedures that enhance the amount of one or more analytes of interest relative to other components in the sample that may interfere with detection of the analytes of interest. Purification of a sample by various means allows for the relative reduction of one or more interfering substances, e.g., one or more substances that may or may not interfere with detection of selected parent or daughter ions by mass spectrometry. Relative reduction, as used in this term, does not require that the purification completely removes substances that are present along with the analytes of interest in the material to be purified.

[0063] As used herein, the terms "immunopurification" or "immunopurifying" refer to a purification procedure that utilizes antibodies, including polyclonal or monoclonal antibodies, to enrich for one or more analytes of interest. Immunopurification can be performed using any of the immunopurification methods known in the art. Often, immunopurification procedures utilize antibodies bound, conjugated, or otherwise attached to a solid support, such as a column, well, tube, gel, capsule, particle, or the like. Immunopurification, as used herein, includes, without limitation, procedures often referred to in the art as immunoprecipitation, as well as procedures often referred to in the art as affinity chromatography or immunoaffinity chromatography.

[0064] As used herein, the term "immunoparticle" refers to a capsule, bead, gel particle, or the like, having antibodies bound, conjugated, or otherwise attached to its surface (on and / or within the particle). In certain preferred embodiments, the immunoparticle is a sepharose or agarose bead. In alternative preferred embodiments, the immunoparticle comprises glass, plastic, or silica beads, or silica gel.

[0065] As used herein, the term "anti-insulin antibody" refers to a polyclonal or monoclonal antibody that has affinity for insulin. In various embodiments, the specificity of the insulin antibody for chemical species other than insulin can vary; for example, in certain preferred embodiments, the anti-insulin antibody is specific for insulin and therefore has little or no affinity for chemical species other than insulin, while in other preferred embodiments, the anti-insulin antibody is non-specific and binds to a specific chemical species other than insulin.

[0066] As used herein, the term "sample" refers to a sample that may contain an analyte of interest. As used herein, the term "body fluid" refers to a fluid that can be separated from an individual's body. For example, "body fluid" may include blood, plasma, serum, bile, saliva, urine, tears, sweat, and the like. In a preferred embodiment, the sample comprises a body fluid sample from a human, preferably plasma or serum.

[0067] As used herein, the term "solid-phase extraction" or "SPE" refers to a method for separating a chemical mixture into components as a result of the affinity of the components dissolved or suspended in a solution (i.e., a mobile phase) for a solid (i.e., a solid phase) through which the solution flows. In some cases, as the mobile phase flows through or around the solid phase, undesired components of the mobile phase may be retained by the solid phase, resulting in the purification of the analyte in the mobile phase. In other cases, the analyte may be retained by the solid phase, allowing the undesired components of the mobile phase to flow through or around the solid phase. In these cases, a second mobile phase is then used to elute the retained analyte from the solid phase for further processing or analysis. SPE, including TFLC, can function by single- or mixed-mode mechanisms. A mixed-mode mechanism utilizes ion exchange and hydrophobic retention in the same column; for example, the solid phase of a mixed-mode SPE column may exhibit strong anion exchange and hydrophobic retention, or strong cation exchange and hydrophobic retention.

[0068] Generally, the affinity of the SPE column packing material for the analyte can result from any of a variety of mechanisms, such as one or more chemical interactions or immunoaffinity interactions. In some embodiments, SPE of insulin is performed without the use of an immunoaffinity column packing material. That is, in some embodiments, insulin is purified from a sample by an SPE column that is not an immunoaffinity column.

[0069] As used herein, the term "chromatography" means a process by which a mixture of chemicals carried by a liquid or gas is separated into components as a result of differential partitioning of the chemicals as they flow around or over a stationary liquid or solid phase.

[0070] As used herein, the term "liquid chromatography" or "LC" refers to a method in which one or more components of a fluid solution are selectively retarded as the fluid uniformly permeates a column or capillary passage of fine material. The retardation results from the partitioning of the components of the mixture between one or more stationary phases and the bulk fluid (i.e., mobile phase) as the fluid moves relative to the stationary phase(s). Examples of "liquid chromatography" include reversed-phase liquid chromatography (RPLC), high-performance liquid chromatography (HPLC), and turbulent flow liquid chromatography (TFLC) (sometimes known as high-turbulence liquid chromatography (HTLC) or high-throughput liquid chromatography).

[0071] As used herein, the term "high performance liquid chromatography" or "HPLC" (sometimes known as "high pressure liquid chromatography") refers to liquid chromatography that increases the degree of separation by forcing a mobile phase under pressure through a stationary phase, typically a tightly packed column.

[0072] As used herein, the term "turbulent flow liquid chromatography" or "TFLC" (sometimes known as high-turbulence liquid chromatography or high-throughput liquid chromatography) refers to a form of chromatography that utilizes the turbulent flow of assayed substances through a column packing as the basis for separation. TFLC was applied to the preparation of samples containing two unknown drugs prior to analysis by mass spectrometry. See, e.g., Zimmer et al., J Chromatogr A854:23-35 (1999). See also U.S. Pat. Nos. 5,968,367, 5,919,368, 5,795,469, and 5,772,874, which further describe TFLC. Those skilled in the art understand "turbulent flow." When a fluid flows slowly and smoothly, the flow is called "laminar flow." For example, a fluid moving at a low flow rate through an HPLC column is laminar. In laminar flow, the motion of fluid particles is orderly, and particles generally move in a substantially straight line. At higher velocities, the inertia of the water overcomes the frictional forces of the fluid, and turbulent flow results. Fluid not in contact with an irregular boundary "overtakes" it and is slowed by friction or deflected by an uneven surface. When a fluid is flowing turbulently, it flows in eddies (or spirals) with greater "drag" than when the flow is laminar. Many references are available to help determine when a fluid flow is laminar or turbulent (e.g., Turbulent Flow Analysis: Measurement and Prediction, P.S. Bernard & J.M.Wallace, John Wiley & Sons, Inc. (2000); An Introduction to Turbulent Flow, Jean Mathieu & Julian Scott, Cambridge University Press (2001)).

[0073] As used herein, the term "gas chromatography" or "GC" refers to chromatography in which a sample mixture is vaporized and injected into a stream of carrier gas (such as nitrogen or helium) that moves through a column containing a stationary phase consisting of a liquid or particulate solid, separating its component compounds according to their affinity for the stationary phase.

[0074] As used herein, the term "large particle column" or "extraction column" refers to a chromatography column containing an average particle diameter greater than about 50 μm. As used in this context, the term "about" means ±10%.

[0075] As used herein, the term "analytical column" refers to a chromatography column having sufficient chromatographic stages to achieve a separation of materials in a sample eluting from the column sufficient to allow for the determination of the presence or amount of an analyte. Such columns are often distinguished from "extraction columns," which have the general purpose of separating or extracting retained materials from unretained materials to obtain a purified sample for further analysis. As used in this context, the term "about" means ±10%. In a preferred embodiment, the analytical column contains particles about 5 μm in diameter.

[0076] As used herein, the terms "online" and "in-line" refer to a procedure that is performed without the need for operator intervention, as used, for example, in "online automated fashion" or "online extraction." In contrast, the term "offline," as used herein, refers to a procedure that requires manual operator intervention. Thus, if a sample is subjected to precipitation and then the supernatant is manually loaded into an autosampler, the precipitation and loading steps are offline from the subsequent steps. In various embodiments of the method, one or more steps can be performed in an online automated fashion.

[0077] As used herein, the term "mass spectrometry" or "MS" refers to an analytical technique for identifying compounds by their mass. MS refers to a method for filtering, detecting, and measuring ions based on the ions' mass-to-charge ratio, or "m / z." MS techniques generally include the steps of (1) ionizing compounds to produce charged compounds, and (2) detecting the molecular weights of the charged compounds and calculating their mass-to-charge ratios. Compounds can be ionized and detected by any suitable means. A "mass spectrometer" generally includes an ionizer, a mass analyzer, and an ion detector. Generally, one or more molecules of interest are ionized, and the ions are then introduced into a mass analyzer, where a combination of magnetic and electric fields causes the ions to follow a path in space that depends on their mass ("m") and charge ("z"). See, for example, U.S. Patent No. 6,204,500, entitled "Mass Spectrometry From Surfaces," U.S. Patent No. 6,107,623, entitled "Methods and Apparatus for Tandem Mass Spectrometry," U.S. Patent No. 6,268,144, entitled "DNA Diagnostics Based On Mass Spectrometry," U.S. Patent No. 6,124,137, entitled "Surface-Enhanced Photolabile Attachment And Release For Desoption And Detection Of Analytes," Wright et al., Prostate Cancer and Prostatic Diseases, 1999, 2:264-76, and Merchant and Weinberger, Electrophoresis, 2000, 21:1164-67.

[0078] As used herein, "high resolution / accuracy mass analysis" refers to mass analysis performed using a mass spectrometer capable of measuring the mass-to-charge ratio of charged species with sufficient precision and accuracy to identify a unique chemical ion. Identification of a unique chemical ion is possible for an ion when its individual isotopic peaks are readily distinguishable. The specific resolution and mass accuracy required to identify a unique chemical ion will vary depending on the mass and charge state of the ion.

[0079] As used herein, "resolution" or "resolution (FWHM)" (known in the art as "m / Δm 50% ") refers to the observed mass-to-charge ratio divided by the width of the mass peak at 50% of its maximum height (full width at half maximum, "FWHM").

[0080] As used herein, a "unique chemical ion" in the context of mass spectrometry means a single ion having a single atomic constitution. A single ion can be singly or multiply charged.

[0081] As used herein, "accuracy" (or "mass accuracy") in reference to mass spectrometry refers to the possible deviation of the instrument response from the true m / z of the ion being studied. Accuracy is typically expressed in parts per million (ppm).

[0082] The high-resolution / high-accuracy mass spectrometry methods of the present invention can be performed on instruments capable of performing mass analysis with FWHMs greater than 10,000, 15,000, 20,000, 25,000, 50,000, 100,000, or even greater. Similarly, the methods of the present invention can be performed on instruments capable of performing mass analysis with accuracies of less than 50 ppm, 20 ppm, 15 ppm, 10 ppm, 5 ppm, 3 ppm, or even less. Instruments capable of these performance characteristics may incorporate certain Orbitrap mass analyzers, time-of-flight ("TOF") mass analyzers, or Fourier transform ion cyclotron resonance mass analyzers. In preferred embodiments, the methods are performed on instruments comprising Orbitrap mass analyzers or TOF mass analyzers.

[0083] The term "orbitrap" describes an ion trap consisting of a barrel-like outer electrode and a coaxial inner electrode. Ions are injected tangentially into the electric field between the electrodes and are trapped because the electrostatic interaction between the ions and the electrode balances the centrifugal force as the ions orbit the coaxial inner electrode. As the ions orbit the coaxial inner electrode, their orbits oscillate along the axis of the central electrode at harmonic frequencies dependent on the ions' mass-to-charge ratio. Detection of the orbital frequency allows the orbitrap to be used as a mass spectrometer with high accuracy (as low as 1-2 ppm) and high resolution (FWHM) (up to approximately 200,000). Mass spectrometers based on orbitraps are described in detail in U.S. Pat. No. 6,995,364, which is incorporated herein by reference in its entirety.

[0084] As used herein, the term "operating in negative ion mode" refers to a mass spectrometry method that generates and detects negative ions. As used herein, the term "operating in positive ion mode" refers to a mass spectrometry method that generates and detects positive ions. In a preferred embodiment, mass spectrometry is performed in positive ion mode.

[0085] As used herein, the terms "ionization" or "ionize" refer to a process that produces analyte ions having a net charge equal to one or more electron units. Negative ions are those that have a net negative charge of one or more electron units, while positive ions are those that have a net positive charge of one or more electron units.

[0086] As used herein, the term "electron ionization" or "EI" refers to a method in which an analyte of interest in the gas or vapor phase interacts with a stream of electrons. Collisions between the electrons and the analyte produce analyte ions that can then be subjected to mass spectrometry techniques.

[0087] As used herein, the term "chemical ionization" or "CI" refers to a method in which a reagent gas (e.g., ammonia) is subjected to electron bombardment to produce analyte ions through interaction of the reagent gas ions with analyte molecules.

[0088] As used herein, the term "fast atom bombardment" or "FAB" refers to a method in which a beam of high-energy atoms (often Xe or Ar) bombards a nonvolatile sample, desorbing and ionizing the molecules contained within. The test sample is dissolved in a viscous liquid matrix, such as glycerol, thioglycerol, m-nitrobenzyl alcohol, 18-crown-6 crown ether, 2-nitrophenyl octyl ether, sulfolane, diethanolamine, and triethanolamine. The selection of an appropriate matrix for a compound or sample is an empirical process.

[0089] As used herein, the term "matrix-assisted laser desorption ionization" or "MALDI" refers to a method in which a non-volatile sample is exposed to laser radiation that desorbs and ionizes analytes in the sample by various ionization pathways, including photoionization, protonation, deprotonation, and cluster decay. For MALDI, the sample is mixed with an energy-absorbing matrix that facilitates desorption of analyte molecules.

[0090] As used herein, the term "surface-enhanced laser desorption ionization" or "SELDI" refers to another method in which a nonvolatile sample is exposed to laser radiation that desorbs and ionizes analytes in the sample by various ionization pathways, including photoionization, protonation, deprotonation, and cluster decay. For SELDI, the sample is typically bound to a surface that preferentially retains one or more analytes of interest. Like MALDI, this method can also use energy-absorbing materials to facilitate ionization.

[0091] As used herein, the term "electrospray ionization" or "ESI" refers to a method in which a solution is passed through a short capillary tube, to the end of which a high positive or negative potential is applied. The solution reaches the end of the tube and is evaporated (atomized) into a jet or spray of very small droplets of the solution in solvent vapor. This spray of droplets flows through an evaporation chamber. As the droplets become smaller, the surface charge density increases to the point where natural repulsion between like-sign charges causes the release of ions as well as neutral molecules.

[0092] As used herein, the term "atmospheric pressure chemical ionization" or "APCI" refers to a mass spectrometry technique similar to ESI, but APCI generates ions through ion-molecule reactions that occur in a plasma at atmospheric pressure. The plasma is sustained by an electrical discharge between a nebulizing capillary and a counter electrode. Ions are then extracted into a mass spectrometer, typically using a pair of differentially pumped skimmer stages. Counterflow dry, preheated N2 gas can be used to improve solvent removal. Gas-phase ionization in APCI can be more effective than ESI for analyzing less polar species.

[0093] The term "atmospheric pressure photoionization" or "APPI," as used herein, refers to a form of mass spectrometry in which the mechanism of ionization of a molecule M is the absorption of a photon and the ejection of an electron, producing a molecular ion, M+. Because the photon energy is typically just above the ionization potential, the molecular ion is not susceptible to dissociation. In many cases, it is possible to analyze samples without the need for chromatography, which can save considerable time and money. In the presence of water vapor or a protic solvent, the molecular ion can abstract H to form MH+. This tends to occur when M has a high proton affinity. This does not affect the accuracy of quantitation, since the sum of M+ and MH+ is constant. Drug compounds in protic solvents are typically observed as MH+, while nonpolar compounds such as naphthalene or testosterone typically form M+. See, e.g., Robb et al., Anal. Chem., 2000, 72(15), 3653-3659.

[0094] As used herein, the term "inductively coupled plasma" or "ICP" refers to a method in which a sample interacts with a partially ionized gas at a temperature high enough that most elements are atomized and ionized.

[0095] As used herein, the term "field desorption" refers to a method in which a non-volatile test sample is placed on an ionizing surface and a strong electric field is used to generate analyte ions.

[0096] As used herein, the term "desorption" refers to the removal of an analyte from a surface and / or the entry of the analyte into the gas phase. Laser desorption thermal desorption is a technique in which a sample containing an analyte is thermally desorbed into the gas phase by a laser pulse. The laser illuminates the backside of a specially made 96-well plate with a metal base. The laser pulse heats the bottom, and the heat transfers the sample into the gas phase. The gas phase sample is then drawn into a mass spectrometer.

[0097] As used herein, the term "selected ion monitoring" refers to a detection mode in a mass spectrometer instrument in which only ions within a relatively narrow mass range, typically within about one mass unit, are detected.

[0098] As used herein, "multiple reaction mode," sometimes known as "selective reaction monitoring," is a detection mode of a mass spectrometer instrument in which a precursor ion and one or more fragment ions are selectively detected.

[0099] As used herein, the terms "lower limit of quantitation," "lower limit of quantitation," or "LLOQ" refer to the point at which a measurement becomes quantitatively meaningful. The analyte response at this LOQ is identifiable, distinct, and reproducible with a relative standard deviation (RSD%) of less than 20% and an accuracy of 85% to 115%.

[0100] As used herein, the term "limit of detection" or "LOD" is the point at which a measurement is greater than its associated uncertainty. The LOD is the point at which a value exceeds the uncertainty associated with its measurement and is defined as three times the RSD of the mean at zero concentration.

[0101] As used herein, the "amount" of an analyte in a bodily fluid sample generally refers to an absolute value reflecting the mass of analyte that can be detected in a volume of sample. However, amount also contemplates a relative amount compared to the amount of other analytes. For example, the amount of an analyte in a sample can be an amount that is greater than a control or normal level of the analyte that is normally present in the sample.

[0102] The term "about," as used herein with respect to quantitative measurements that do not involve measurement of the mass of an ion, means plus or minus 10% of the stated value. Mass spectrometry instruments may vary slightly in determining the mass of a given analyte. The term "about," with respect to the mass or mass-to-charge ratio of an ion, means + / - 0.50 atomic mass units.

[0103] Quantitation of serum insulin is primarily used to diagnose glycemic disorders in diabetic and prediabetic patients in the evaluation of insulin resistance syndrome. C-peptide is a peptide that connects the two peptide chains of insulin and is released from proinsulin during processing and then co-secreted from pancreatic beta cells. Due to differences in half-lives and hepatic clearance, peripheral blood levels of C-peptide and insulin are no longer equimolar, but are still highly correlated. In this embodiment, the method provided herein measures endogenous insulin and C-peptide to (1) distinguish exogenous insulin administration from insulin-secreting tumors as a cause of hypoglycemia and (2) distinguish type 1 from type 2 diabetes.

[0104] In one aspect, provided herein are methods for measuring insulin levels in a patient by determining the amount of insulin and C-peptide in a sample using mass spectrometry. In some embodiments, the methods provided herein include a multiplex assay that simultaneously measures the amount of insulin and C-peptide in a sample by mass spectrometry. In some embodiments, the method includes (a) subjecting insulin and C-peptide from the sample to an ionization source under conditions suitable for generating one or more insulin and C-peptide ions detectable by mass spectrometry, and (b) determining the amount of the one or more insulin and C-peptide ions by mass spectrometry. In some embodiments, the determined amount of one or more ions is used to determine the amount of insulin and peptide in the sample. In some embodiments, the amount of insulin and C-peptide in the sample is related to the amount of insulin in the patient. In some embodiments, the amount of insulin and C-peptide in the sample is used to determine the ratio of insulin to C-peptide in the patient.

[0105] In some embodiments, the method includes (a) subjecting the sample to a concentration step to obtain a fraction enriched in insulin and C-peptide; (b) subjecting the enriched insulin and C-peptide to an ionization source under conditions suitable for generating one or more insulin and C-peptide ions detectable by mass spectrometry; and (c) determining the amount of one or more insulin and C-peptide ions by mass spectrometry. In some embodiments, the determined amount of one or more ions is used to determine the amount of insulin and C-peptide in the sample. In some embodiments, the amount of insulin and C-peptide in the sample is correlated with the amount of insulin in the patient. In some embodiments, the amount of insulin and C-peptide in the sample is used to determine the ratio of insulin to C-peptide in the patient. In some embodiments, the concentration step provided herein includes immunocapture of insulin and C-peptide using antibodies. In some embodiments, the method comprises (a) immunocapturing insulin and C-peptide; (b) subjecting the immunocaptured insulin and C-peptide to an ionization source under conditions suitable for generating one or more insulin and C-peptide ions detectable by mass spectrometry; and (c) determining the amount of the one or more insulin and C-peptide ions by mass spectrometry. In some embodiments, the immunocapturing step provided herein comprises using an anti-insulin antibody and an anti-C-peptide antibody. In some embodiments, the antibody provided herein is a monoclonal antibody. In some embodiments, the antibody provided herein is a mouse monoclonal antibody. In some embodiments, the antibody provided herein is a monoclonal IgG antibody. In some embodiments, the antibody provided herein is a polyclonal antibody. In some embodiments, the anti-insulin antibody and the anti-C-peptide antibody are immobilized on magnetic beads. In some embodiments, the immunocaptured insulin and C-peptide on the magnetic beads are washed and eluted.

[0106] In some embodiments, the serum is delipidated prior to quantification by mass spectrometry. In some embodiments, one or more delipidation reagents are used to remove lipids from the sample. In some embodiments, the delipidation reagent is CLEANASCITE®.

[0107] In some embodiments, the methods provided herein include purifying the sample prior to mass spectrometry. In some embodiments, the methods include purifying the sample using liquid chromatography. In some embodiments, the liquid chromatography includes high performance liquid chromatography (HPLC) or high turbulence liquid chromatograph (HTLC). In some embodiments, the methods include subjecting the sample to solid phase extraction (SPE).

[0108] In some embodiments, the mass analysis comprises tandem mass analysis. In some embodiments, the mass analysis is high-resolution mass analysis. In some embodiments, the mass analysis is high-resolution / high-accuracy mass analysis. In some embodiments, the ionization is by electrospray ionization (ESI). In some embodiments, the ionization is by atmospheric pressure chemical ionization (APCI). In some embodiments, the ionization is in positive ion mode.

[0109] In some embodiments, the methods provided herein include adding an internal standard to the sample. In some embodiments, the internal standard for insulin is bovine insulin. In some embodiments, the internal standard for C-peptide is a C-peptide heavy internal standard. In some embodiments, the internal standard is labeled. In some embodiments, the internal standard is deuterated or isotopically labeled.

[0110] In some embodiments, the patient sample is a serum sample. In some embodiments, the patient sample is a plasma sample. In some embodiments, the patient sample is a blood, saliva, or urine sample.

[0111] In some embodiments, the sample is subjected to acidic conditions prior to ionization. In some embodiments, subjecting the sample to acidic conditions comprises exposing the concentrated insulin and C-peptide to formic acid. In some embodiments, the sample is subjected to basic conditions prior to ionization. In some embodiments, subjecting the sample to basic conditions comprises exposing the sample to Trizma. In some embodiments, subjecting the sample to basic conditions comprises exposing the sample to Trizma and ethanol.

[0112] In some embodiments, the one or more ions comprise an insulin precursor ion having a mass-to-charge ratio (m / z) of 968.7±0.5. In some embodiments, the one or more ions comprise one or more fragment ions selected from the group consisting of ions having m / z of 136.0±0.5, 226.1±0.5, and 345.2±0.5. In some embodiments, the insulin fragment ion having m / z of 226.1±0.5 is a quantifier ion. In some embodiments, the one or more ions comprise a bovine insulin precursor ion having a mass-to-charge ratio (m / z) of 956.8±0.5. In some embodiments, the one or more ions comprise one or more fragment ions selected from the group consisting of ions having m / z of 136.0±0.5, 226.1±0.5, and 315.2±0.5. In some embodiments, a bovine insulin fragment ion having an m / z of 136.0±0.5 is a quantifier ion. In some embodiments, the one or more ions comprise a C-peptide precursor ion having a mass-to-charge ratio (m / z) of 1007.7±0.5. In some embodiments, the one or more ions comprise one or more fragment ions selected from the group consisting of ions having m / z of 533.3±0.5, 646.4±0.5, and 927.5±0.5. In some embodiments, any of the C-peptide fragment ions having m / z of 533.3±0.5, 646.4±0.5, and 927.5±0.5 can be used as a quantifier ion. In some embodiments, the one or more ions comprise a C-peptide heavy internal standard precursor ion having a mass-to-charge ratio (m / z) of 1009.5±0.5. In some embodiments, the one or more ions include one or more fragment ions selected from the group consisting of ions having m / z of 540.3±0.5, 653.4±0.5, and 934.5±0.5, hi some embodiments, any of the C-peptide heavy internal standard fragment ions having m / z of 540.3±0.5, 653.4±0.5, and 934.5±0.5 can be used as a quantifier ion.

[0113] In some embodiments, provided herein is a method for utilizing mass spectrometry to determine the amount of insulin and C-peptide in a sample, the method comprising: (a) enriching insulin and C-peptide in the sample by an extraction technique; (b) subjecting the purified insulin and C-peptide from step (a) to liquid chromatography to obtain an insulin- and C-peptide-enriched fraction from the sample; (c) subjecting the enriched insulin to an ionization source under conditions suitable for generating insulin precursor ions detectable by mass spectrometry; and (d) determining the amount of one or more fragment ions by mass spectrometry. In some embodiments, the determined amount of one or more ions is used to determine the amount of insulin and C-peptide in the sample. In some embodiments, the amount of insulin and C-peptide in the sample is correlated with the amount of insulin in a patient. In some embodiments, the amount of insulin and C-peptide in the sample is used to determine the ratio of insulin to C-peptide in a patient. In some embodiments, the extraction technique provided herein comprises immunocapture of insulin and C-peptide using antibodies. In some embodiments, the extraction technique provided herein comprises solid-phase extraction (SPE).

[0114] In some embodiments, the collision energy is in the range of about 40 to 60 eV, hi some embodiments, the collision energy is in the range of about 40 to 50 eV.

[0115] In another aspect, provided herein are methods for determining the amount of insulin or C-peptide in a sample by mass spectrometry, the methods comprising: (a) immunocapturing insulin or C-peptide; (b) subjecting the immunocaptured insulin or C-peptide to an ionization source under conditions suitable for generating one or more insulin or C-peptide ions detectable by mass spectrometry; and (c) determining the amount of the one or more insulin or C-peptide ions by mass spectrometry. In some embodiments, provided herein are methods for determining the amount of insulin in a sample by mass spectrometry, the methods comprising: (a) immunocapturing insulin; (b) subjecting the immunocaptured insulin to an ionization source under conditions suitable for generating one or more insulin ions detectable by mass spectrometry; and (c) determining the amount of the one or more insulin ions by mass spectrometry. In some embodiments, provided herein are methods for determining the amount of C-peptide in a sample by mass spectrometry, comprising: (a) immunocapturing C-peptide; (b) subjecting the immunocaptured C-peptide to an ionization source under conditions suitable for generating one or more C-peptide ions detectable by mass spectrometry; and (c) determining the amount of the one or more C-peptide ions by mass spectrometry. In some embodiments, the immunocapturing step comprises using an anti-insulin antibody or an anti-C-peptide antibody. In some embodiments, the anti-insulin antibody or anti-C-peptide antibody is immobilized on magnetic beads. In some embodiments, the immunocaptured insulin or C-peptide on the magnetic beads is washed and eluted.

[0116] In another aspect, provided herein are methods for diagnosing glycemic disorders or insulin resistance syndromes in diabetic and prediabetic patients. In some embodiments, the methods provided herein for quantifying endogenous insulin and C-peptide are used to diagnose diabetes. In some embodiments, the methods provided herein for quantifying endogenous insulin and C-peptide are used to distinguish between insulin-secreting tumors and exogenous insulin administration as causes of hypoglycemia. In some embodiments, the methods provided herein for quantifying endogenous insulin and C-peptide are used to distinguish between type 1 diabetes and type 2 diabetes. In some embodiments, the methods provided herein for quantifying endogenous insulin and C-peptide are used to assess the risk of diabetes in prediabetic patients.

[0117] Suitable test samples for use in the methods of the present invention are those that may contain the analyte of interest. In some preferred embodiments, the sample is a biological sample, i.e., a sample obtained from a biological source such as an animal, cell culture, organ culture, etc. In certain preferred embodiments, the sample is obtained from a mammal, such as a dog, cat, horse, etc. Particularly preferred mammals are primates, most preferably male or female humans. Preferred samples include bodily fluid or tissue samples, such as blood, plasma, serum, saliva, cerebrospinal fluid, etc., preferably plasma and serum. Such samples can be obtained, for example, from patients, i.e., living male or female individuals presenting to a clinical facility for diagnosis, prognosis, or treatment of a disease or condition. In embodiments in which the sample comprises a biological sample, the method can be used to determine the amount of insulin in the sample when the sample is obtained from a biological source.

[0118] The present invention also contemplates a kit for a quantitative assay of insulin. The kit for a quantitative assay of insulin may include a kit containing the composition provided herein. For example, the kit may include packaging materials and a quantity of an isotope-labeled internal standard sufficient for at least one assay. Typically, the kit also includes instructions recorded in a tangible form (e.g., contained on paper or electronic media) for using the packaged reagent for a quantitative assay of insulin.

[0119] Calibration and QC pools used in embodiments of the present invention are preferably prepared using a matrix similar to the sample matrix of interest, provided that insulin is essentially absent.

[0120] Preparation of samples for mass spectrometry In preparation for mass spectrometry, insulin can be enriched relative to one or more other components in the sample by a variety of methods known in the art, including, for example, immunocapture, liquid chromatography, filtration, centrifugation, thin layer chromatography (TLC), electrophoresis, including capillary electrophoresis, affinity separation, including immunoaffinity separation, extraction methods, including ethyl acetate or methanol extraction, and the use of chaotropic agents, or any combination of the above or the like.

[0121] One method of sample purification that can be used prior to mass spectrometry analysis is to apply the sample to a solid phase extraction (SPE) column under conditions where the analyte of interest is reversibly retained by the column packing, while one or more other substances are not. In this technique, first mobile phase conditions can be used when the analyte of interest is retained by the column, and second mobile phase conditions can be subsequently used to remove the retained substances from the column once the unretained substances have been washed away.

[0122] In some embodiments, insulin in a sample can be reversibly retained on an SPE column containing a packing material containing an alkyl-bonded surface. For example, in some embodiments, a C-8 online SPE column (such as an Oasis HLB online SPE column / cartridge (2.1 mm x 20 mm) from Phenomenex, Inc. or equivalent) can be used to concentrate insulin prior to mass spectrometry analysis. In some embodiments, the SPE column is used with HPLC-grade 0.2% aqueous formic acid as the wash solution and 0.2% formic acid in acetonitrile as the elution solution.

[0123] In other embodiments, the method includes immunopurifying the insulin prior to mass spectrometry analysis. The immunopurification step can be performed using any of the immunopurification methods known in the art. Often, immunopurification procedures utilize antibodies bound, conjugated, immobilized, or otherwise attached to a solid support, such as a column, well, tube, capsule, particle, or the like. Generally, immunopurification methods include (1) incubating a sample containing the analyte of interest with an antibody so that the analyte binds to the antibody, (2) performing one or more wash steps, and (3) eluting the analyte from the antibody.

[0124] In certain embodiments, the incubation step of immunopurification is performed with free antibody in solution, and the antibody is then bound or attached to a solid surface before the washing step. In certain embodiments, this can be achieved using a primary antibody that is an anti-insulin antibody and a secondary antibody bound to a solid surface that has affinity for the primary anti-insulin antibody. In an alternative embodiment, the primary antibody is bound to a solid surface before the incubation step.

[0125] Suitable solid supports include, without limitation, tubes, slides, columns, beads, capsules, particles, gels, and the like. In some preferred embodiments, the solid support is a multi-well plate, such as a 96-well plate, a 384-well plate, and the like. In some embodiments, the solid support is a Sepharose or agarose bead or gel. There are many methods known in the art by which an antibody (e.g., an insulin antibody or a secondary antibody) can be bound, attached, immobilized, or linked to a solid support, such as covalent or non-covalent adsorption, affinity binding, ionic binding, and the like. In some embodiments, the antibody is linked using CNBr. For example, the antibody can be linked to CNBr-activated Sepharose. In other embodiments, the antibody is attached to the solid support via an antibody-binding protein, such as Protein A, Protein G, Protein A / G, or Protein L.

[0126] The wash step of the immunopurification method generally requires washing the solid support so that the insulin remains bound to the anti-insulin antibodies on the solid support. The elution step of the immunopurification method generally requires the addition of a solution that disrupts the binding of insulin to the anti-insulin antibodies. Exemplary elution solutions include organic solutions, salt solutions, and high or low pH solutions.

[0127] Another method of sample purification that can be used prior to mass spectrometry analysis is liquid chromatography (LC). In liquid chromatography techniques, analytes can be purified by applying the sample to a chromatographic analytical column under mobile phase conditions in which the analyte of interest elutes at a different rate than one or more other substances. Such procedures can enhance the amount of one or more analytes of interest relative to one or more other components of the sample.

[0128] Certain methods of liquid chromatography, including HPLC, rely on relatively slow laminar flow techniques. Traditional HPLC analysis relies on column packing, where laminar flow of the sample through the column is the basis for separation of the analytes of interest from the sample. Those skilled in the art will understand that separation in such columns is a partitioning process and will be able to select LC, including HPLC, instruments, and columns suitable for use with C-peptides. Chromatographic analytical columns generally contain a medium (i.e., packing material) to facilitate separation (i.e., fractionation) of compound components. The medium may comprise fine particles. The particles generally contain binding surfaces that interact with various compound components to facilitate separation of the compound components. One suitable binding surface is a hydrophobic binding surface, such as an alkyl- or cyano-bound surface. The alkyl-bound surface may comprise C-4, C-8, C-12, or C-18-bound alkyl groups. In some embodiments, the chromatographic analytical column is a monolithic C-18 column. The chromatographic analytical column includes an inlet port for receiving a sample and an outlet port for discharging an eluate containing the fractionated sample. The sample can be fed directly into the inlet or from an SPE column, such as an online SPE column, or a TFLC column. In some embodiments, an online filter can be used before the SPE column and / or HPLC column to remove particles and phospholipids in the sample before it reaches the SPE and / or TFLC and / or HPLC column.

[0129] In one embodiment, a sample can be applied to an LC column at an inlet port, eluted with a solvent or solvent mixture, and discharged at an outlet port. Various solvent modes can be selected to elute the analyte(s) of interest. For example, liquid chromatography can be performed using gradient, isocratic, or polymorphic (i.e., mixed) modes. During chromatography, separation of substances is affected by variables such as the choice of eluent (also known as the "mobile phase"), elution mode, gradient conditions, temperature, etc.

[0130] In some embodiments, insulin in a sample is concentrated by HPLC. The HPLC can be performed using a monolith C-18 column chromatographic system, such as an Onyx monolith C-18 column (50x2.0 mm) manufactured by Phenomenex Inc., or equivalent. In certain embodiments, the HPLC is performed using 0.2% aqueous formic acid for HPLC as solvent A and 0.2% formic acid in acetonitrile as solvent B.

[0131] By careful selection of valves and connecting piping, two or more chromatography columns can be connected as needed to allow material to pass from one chromatography column to the next without the need for manual steps. In a preferred embodiment, the selection of valves and piping is controlled by a computer preprogrammed to perform the necessary steps. Most preferably, the chromatography system is also connected to a detection system, e.g., an MS system, in such an on-line manner. Thus, an operator can load a tray of samples into the autosampler, and the remaining operations are performed under computer control, resulting in the purification and analysis of all selected samples.

[0132] In some embodiments, TFLC can be used for purification of insulin prior to mass spectrometry analysis. In such embodiments, samples can be extracted using a TFLC column that captures the analyte. The analyte is then eluted and transferred online to an analytical HPLC column. For example, sample extraction can be achieved using a TFLC extraction cartridge containing large particle size (50 μm) packing. The sample eluted from this column can be transferred online to an analytical HPLC column for further purification prior to mass spectrometry analysis. The steps involved in these chromatographic procedures can be linked in an automated manner, minimizing the need for operator involvement during analyte purification. This feature potentially saves time and money and eliminates the opportunity for operator error.

[0133] In some embodiments, one or more of the above-mentioned purification techniques can be used in parallel for the purification of insulin to allow for simultaneous processing of multiple samples, hi some embodiments, the purification techniques used exclude immunopurification techniques such as immunoaffinity chromatography.

[0134] Detection and quantification of insulin by mass spectrometry Mass spectrometry is performed using a mass spectrometer that includes an ion source for ionizing the fractionated sample and generating charged molecules for further analysis. In various embodiments, insulin can be ionized by methods known to those skilled in the art. For example, insulin can be ionized by electron ionization, chemical ionization, electrospray ionization (ESI), photon ionization, atmospheric pressure chemical ionization (APCI), photoionization, atmospheric pressure photoionization (APPI), laser diode thermal desorption (LDTD), fast atom bombardment (FAB), liquid secondary ionization (LSI), matrix-assisted laser desorption ionization (MALDI), field ionization, field desorption, thermospray / plasma spray ionization, surface-enhanced laser desorption ionization (SELDI), inductively coupled plasma (ICP), and particle beam ionization. Those skilled in the art will appreciate that the choice of ionization method can be determined based on the analyte to be measured, the type of sample, the type of detector, the choice of positive versus negative mode, etc., and insulin may be ionized in either positive or negative mode. In a preferred embodiment, insulin is ionized by ESI in positive ion mode.

[0135] In mass spectrometry techniques, a sample is generally ionized and the resulting positively or negatively charged ions can then be analyzed to determine the mass-to-charge ratio (m / z). Various analyzers for determining m / z include quadrupole analyzers, ion trap analyzers, time-of-flight analyzers, Fourier transform ion cyclotron resonance mass analyzers, and orbitrap analyzers. Some exemplary ion trap methods are described in Bartolucci et al., Rapid Commun. Mass Spectrom., 2000, 14, 967-73.

[0136] Ions can be detected using several detection modes. For example, selected ions can be detected using selected ion monitoring (SIM), or alternatively, mass transitions due to collision-induced dissociation or neutral loss can be monitored, for example, by multiple reaction monitoring (MRM) or selected reaction monitoring (SRM). In some embodiments, mass-to-charge ratios are determined using a quadrupole analyzer. In a "quadrupole" or "quadrupole ion trap" instrument, ions in an oscillating radio frequency field experience a force proportional to the DC potential applied between the electrodes, the amplitude of the RF signal, and the mass-to-charge ratio. The voltage and amplitude can be selected so that only ions with a specific mass-to-charge ratio traverse the quadrupole, while all other ions are deflected. Thus, quadrupole instruments can function as both a "mass filter" and a "mass detector" for ions injected into the instrument.

[0137] When ions strike the detector, they produce pulses of electrons that are converted into digital signals. The acquired data is transferred to a computer, which plots the counts of collected ions against time. The resulting mass chromatogram is similar to that obtained with traditional HPLC-MS methods. The area under the peaks corresponding to specific ions or the amplitude of such peaks can be measured and correlated with the amount of the analyte of interest. In certain embodiments, the area under the curve or amplitude of the fragment ion(s) and / or precursor ion peaks is measured to determine the amount of insulin. The relative abundance of a given ion can be converted to the absolute amount of the original analyte using a calibration standard curve based on one or more ion peaks of an internal or external molecular standard.

[0138] The resolution of MS techniques using certain mass analyzers can be improved by "tandem mass spectrometry" or "MS / MS." In this technique, precursor ions (also called parent ions) from a molecule of interest can be filtered by the MS instrument, and the precursor ions are then fragmented to produce one or more fragment ions (also called daughter ions or product ions) that are analyzed in a second MS step. By careful selection of precursor ions, only ions produced by a specific analyte are passed to a fragmentation chamber, where the fragment ions are generated by collision with atoms of an inert gas. Because both precursor and fragment ions are reproducibly generated under a set of predetermined ionization / fragmentation conditions, MS / MS techniques can be an extremely powerful analytical tool. For example, a combination of filtration and fragmentation can be used to remove interfering substances, which can be particularly useful for complex samples such as biological samples. In certain embodiments, tandem mass spectrometry is performed using a mass analysis instrument that includes a multiple quadrupole analyzer (e.g., a triple quadrupole instrument).

[0139] In certain embodiments using MS / MS techniques, precursor ions are isolated for further fragmentation and collision-activated dissociation (CAD) is used to generate fragment ions from the precursor ions for subsequent detection. In CAD, precursor ions gain energy through collisions with an inert gas and then fragment through a process called "unimolecular decomposition." Sufficient energy must be deposited in the precursor ion so that the increased vibrational energy can break specific bonds within the ion.

[0140] In some embodiments, insulin in a sample is detected and / or quantified using MS / MS as follows: The sample is first subjected to SPE and then to liquid chromatography, preferably HPLC, to concentrate insulin in the sample. The liquid solvent flow from the chromatographic analytical column enters the heated nebulizer interface of the MS / MS analyzer, and the solvent / analyte mixture is converted to vapor in the heated charging tube of the interface. During these processes, the analyte (i.e., insulin) is ionized. Ions, e.g., precursor ions, pass through the instrument's orifice and enter the first quadrupole. Quadrupoles 1 and 3 (Q1 and Q3) are mass filters that allow ion selection based on the ion's mass-to-charge ratio (m / z) (i.e., selection of "precursor" and "fragment" ions in Q1 and Q3, respectively). Quadrupole 2 (Q2) is a collision cell where ions are fragmented. The first quadrupole (Q1) of the mass spectrometer selects molecules with the m / z of insulin ions. Precursor ions with the correct m / z are passed into the collision chamber (Q2), while unwanted ions with other m / z collide with the sides of the quadrupole and are removed. Precursor ions entering Q2 collide with neutral gas molecules (such as argon molecules) and are fragmented. The resulting fragment ions are passed into quadrupole 3 (Q3), where the fragment ions are selected for detection.

[0141] Ionization of insulin can result in multiply charged precursor ions (such as 4+, 5+, 6+, etc. precursor ions). The ionization conditions, particularly the pH of the buffer used in the electrospray technique, significantly affect the identity and quantity of the insulin precursor ions produced. For example, under acidic conditions, positive electrospray ionization can generate primarily 5+ and 6+ charged insulin precursor ions with m / z values ​​of 1162.5±0.5 and 968.5±0.5, respectively. However, under basic conditions, positive electrospray ionization can generate primarily 4+ and 5+ charged insulin precursor ions with m / z values ​​of 1453.75±0.5 and 1162.94±0.5, respectively. The method can utilize acidic or basic conditions, preferably acidic conditions.

[0142] The method can include MS / MS performed in positive or negative ion mode, preferably positive ion mode. In certain embodiments, the electrospray buffer is acidic and Q1 selects insulin precursor ions having m / z of about 1162.5±0.5 or 968.5±0.5. Fragmentation of any of these insulin precursor ions produces fragment ions having m / z of about 226.21±0.5 and / or 135.6±0.5. Thus, in embodiments in which Q1 selects one or more insulin precursor ions selected from the group consisting of ions having m / z of about 1162.5±0.5 and 968.5±0.5, Q3 can select one or more fragment ions selected from the group of ions having m / z of about 226.21±0.5 and 135.6±0.5. In certain embodiments, the relative abundance of a single fragment ion from a single precursor ion can be measured. Alternatively, the relative abundance of two or more fragment ions from a single precursor ion can be measured. In these embodiments, the relative abundance of each fragment ion can be subjected to known mathematical treatments to quantitatively assess the original insulin in the sample. In other embodiments, one or more fragment ions from two or more precursor ions can be measured and utilized as described above to qualitatively assess the original insulin in the sample.

[0143] Alternative modes of operating a tandem mass spectrometer instrument that can be used in certain embodiments include product ion scanning and precursor ion scanning. For a description of these modes of operation, see, for example, E. Michael Thurman et al., Chromatographic-Mass Spectrometric Food Analysis for Trace Determination of Pesticide Residues, Chapter 8 (Amadeo R. Fernandez-Alba, ed., Elsevier 2005) (387).

[0144] In other embodiments, high-resolution / high-accuracy mass spectrometers can be used for quantitative analysis of insulin according to the methods of the present invention. To achieve acceptable accuracy in quantitative results, the mass spectrometer must be capable of exhibiting a resolving power (FWHM) of 10,000 or greater with an accuracy of about 50 ppm or less for the ions of interest. Preferably, the mass spectrometer exhibits a resolving power (FWHM) of 18,000 or greater with an accuracy of about 5 ppm or less, such as a resolving power (FWHM) of 20,000 or greater with an accuracy of about 3 ppm or less, such as a resolving power (FWHM) of 25,000 or greater with an accuracy of about 3 ppm or less. Three exemplary spectrometers capable of exhibiting the required level of performance for insulin ions are Orbitrap mass spectrometers, certain Time-of-Flight mass spectrometers, and Fourier transform ion cyclotron resonance mass spectrometers.

[0145] Elements found in biologically active molecules, such as carbon, oxygen, and nitrogen, occur naturally in many different isotopes. For example, most carbon is 12 C, but about 1% of all naturally occurring carbon is 13 C. Thus, a portion of a naturally occurring molecule containing at least one carbon atom will have at least one 13 The inclusion of naturally occurring elemental isotopes in molecules results in multiple molecular isotopes. The difference in mass between molecular isotopes is at least 1 atomic mass unit (amu). This is because elemental isotopes differ by at least one neutron (the mass of one neutron is approximately 1 amu). When molecular isotopes are ionized to multiply charged states, the mass difference between isotopes can be difficult to distinguish because detection in mass spectrometry is based on mass-to-charge ratio (m / z). For example, two isotopes that differ in mass by 1 amu, both ionized to the 5+ state, exhibit a difference in their m / z of only 0.2. High-resolution / high-accuracy mass spectrometry can distinguish isotopes of highly multiply charged ions (such as ions with ±2, ±3, ±4, ±5, or higher charges).

[0146] Due to naturally occurring elemental isotopes, multiple isotopes typically exist for every molecular ion (each of which may produce a separately detectable spectral peak when analyzed by a sufficiently sensitive mass spectrometer). The m / z ratios and relative abundances of the multiple isotopes collectively comprise the isotopic signature of the molecular ion. In some embodiments, the m / z ratios and relative abundances of two or more molecular isotopes can be utilized to confirm the identity of the molecular ion under consideration. In some embodiments, one or more isotopic mass spectrometric peaks are used to quantify the molecular ion. In some related embodiments, a single mass spectrometric peak of one isotope is used to quantify the molecular ion. In other related embodiments, multiple isotopic peaks are used to quantify the molecular ion. In these latter embodiments, the multiple isotopic peaks can be subjected to appropriate mathematical treatments. Some mathematical treatments are known in the art and include, but are not limited to, summing the areas under multiple peaks or averaging the responses due to multiple peaks.

[0147] In some embodiments, the relative abundance of one or more ions is measured by high-resolution / high-accuracy mass spectrometry to qualitatively assess the amount of insulin in a sample. In some embodiments, the one or more ions measured by high-resolution / high-accuracy mass spectrometry are multiply charged insulin ions. These multiply charged ions may include one or more ions having m / z values ​​within the range of about 1453±0.8 (i.e., one or more monoisotopic peaks of 4+ ions) and / or 1162±1 (i.e., one or more monoisotopic peaks of 5+ ions) and / or 968.8±1.5 (i.e., one or more monoisotopic peaks of 6+ ions).

[0148] The results of an analyte assay can be related to the amount of analyte in the original sample by many methods known in the art. For example, if sampling and analytical parameters are carefully controlled, the relative abundance of a given ion can be compared to a table that converts the relative abundance to the absolute amount of the original molecule. Alternatively, external standards can be run with the sample, and a standard curve is generated based on the ions from those standards. Such a standard curve can be used to convert the relative abundance of a given ion to the absolute amount of the original molecule. In certain preferred embodiments, an internal standard is used to generate a standard curve for calculating the amount of insulin. Methods for generating and using such standard curves are well known in the art, and one of skill in the art can select an appropriate internal standard. For example, in a preferred embodiment, one or more forms of isotopically labeled insulin can be used as the internal standard. Many other methods for relating the amount of an ion to the amount of the original molecule are known to those of skill in the art.

[0149] As used herein, an "isotopic label" results in a mass shift of the labeled molecule compared to the unlabeled molecule when analyzed by mass spectrometry techniques. Examples of suitable labels include deuterium ( 2 H), 13 C and 15 N. One or more isotopic labels can be incorporated at one or more positions in a molecule, and one or more types of isotopic labels can be used in the same isotopically labeled molecule.

[0150] In other embodiments, insulin can be subjected to chemical treatment to obtain its component chains prior to mass spectrometry. The B chain of insulin can be separated by chemical treatments known in the art to cause disulfide reduction. For example, insulin can be treated with TCEP (tris(2-carboxyethyl)phosphine) to reduce the disulfide bridges of insulin and separate the A and B chains.

[0151] The following examples serve to illustrate the invention, but are not intended to limit the scope of the method. [Example]

[0152] Example 1: Human insulin resistance studies Human subjects were apparently healthy, self-described non-Hispanic Caucasians with no history of cardiovascular disease. All individuals provided written informed consent to participate in the study.

[0153] Subjects with a fasting glucose ≥ 126 mg / dL or subjects taking hypoglycemic medications or with a diagnosis of diabetes were excluded from the analysis.

[0154] Race and ethnicity were determined during medical history. Weight and height were measured while the individual was lightly dressed and shoeless. Body mass index was calculated by dividing weight in kilograms by height in meters squared. Blood pressure was measured using an automated blood pressure recorder. Prior to these measurements, subjects sat quietly in a chair for 5 minutes with both feet on the floor and arms supported at heart level. Three blood pressure readings were taken at 1-minute intervals using an appropriately sized cuff and averaged. Metabolic syndrome was present if three of the following characteristics were present: BMI > 30 kg / m2; FG > 100 mg / dL; hypertension (SBP ≥ 130 mmHg or DBP ≥ 85 mmHg), low HDL-C (< 50 mg / dL, women; < 40 mg / dL, men), and TG ≥ 150 mg / dL.

[0155] The insulin suppression test (IST) was used to quantify insulin-mediated glucose disposal. Evaluation of octreotide to assess insulin-mediated glucose disposal by the insulin suppression test. One catheter was used to draw blood samples, and the other catheter was used to administer octreotide (0.27 μg / m 2 / min), insulin (32mU / m 2 / min) and glucose (267 mg / m 2A 180-minute infusion of 1000kJ / min (1000kcal / min) was administered. Blood samples were taken at 10-minute intervals from 150 to 180 minutes into the infusion to determine steady-state plasma glucose (SSPG) and steady-state plasma insulin (SSPI) concentrations. Because SSPI concentrations were similar in all individuals during IST, SSPG concentrations provide a direct measure of insulin's ability to mediate the disposal of the infused glucose load. Thus, the higher the SSPG concentration, the more insulin-resistant the individual. Insulin-mediated glucose disposal determined by IST is highly correlated with that obtained using the euglycemic hyperinsulinemic clamp technique. In this study, IR was defined as falling into the upper tertile of measured insulin resistance (SSPG ≥ 198 mg / dL). Serum samples used for insulin and C-peptide measurements were derived from fasting baseline samples obtained before the start of the IST protocol.

[0156] The analysis included 335 subjects (39% male) with a complete series of biochemical and anthropometric measurements.

[0157] In this population, 118 of 335 subjects had metabolic syndrome.

[0158] The clinical characteristics of the categorized study patient population are shown in Table 1, where subjects are classified according to insulin resistance status. Those with insulin resistance had a higher proportion of men and higher fasting plasma glucose (FPG), insulin, C-peptide, triglycerides, alanine aminotransferase, body mass index (BMI), and systolic blood pressure. HDL-C and LDL-C were lower in those with insulin resistance.

[0159] [Table 1]

[0160] Example 2: Insulin and C-peptide measurements We used SSPG to assess IR in 632 non-diabetic (FG < 125 mg / dL and no diagnosed diabetes) non-Hispanic white participants. IR was defined as the upper tertile of SSPG (≥ 201 mg / dL) in this population.

[0161] Insulin and C-peptide were assessed by multiplex tandem mass spectrometry assay.

[0162] Serum was delipidated, and then insulin and C-peptide were immunocaptured using antibodies immobilized on magnetic beads. The beads were washed, and the peptides were eluted from the beads using acidified acetonitrile in water. Trizma base was added to increase peptide stability. The steps of calibrator preparation, addition of internal standards, delipidation, bead deposition, immunocapture, washing, and elution of peptides from the beads were automated using a Hamilton STAR® robotic liquid handler.

[0163] The elution plate was transferred to a ThermoFisher TurboFlow Aria TX4 HTLC system. The sample was injected onto a hydrophilic / lipophilic balance (HLB) capture column to further enrich insulin and C-peptide from background contaminants. A mobile solvent was used to release the peptides from the extraction cartridge and transfer them to a reversed-phase analytical column. Acetonitrile gradient chromatography separated insulin and C-peptide from remaining background contaminants and each other.

[0164] The solvent flow from the HPLC column was directed into the heated electrospray source of an Agilent 6490 mass spectrometer. In the mass spectrometer, only ions with the desired mass-to-charge ratio were allowed to pass through the quadrupole 1 (Q1) region and into the collision chamber (Q2). The accelerated ions then collided with neutral argon gas molecules to form small fragments. Finally, in Q3, only selected ions were selected to reach the detector. The signal intensity at the detector was proportional to the number of molecules entering the mass spectrometer. Peak area ratios were then calculated for a series of known calibrators to establish a calibration curve. The calibration equations could then be used to determine the concentrations of insulin and C-peptide in patient samples.

[0165] Insulin m / z of 968.7 (precursor) and 136.0, 226.1, and 345.2 (fragments) were used. C-peptide m / z of 1007.7 (precursor) and 533.3, 646.4, and 927.5 (fragments) were used.

[0166] Example 3: Intra- and inter-assay precision Intra-assay precision, defined as the reproducibility of measurements within an assay, was obtained by assaying five replicates from QCL, QCM, and QCH. The coefficient of variation (CV) of five replicate samples was used to determine whether reproducibility was acceptable (≤15%). Statistical analysis of the analytical results confirmed that the reproducibility (CV) for QC ranged from 6.2 to 11.5% for insulin and from 5.1 to 6.3% for C-peptide (Table 2). Intra-assay precision can also be calculated across all assays (see 930TP5319: Assay Validation Calculator). For insulin, the intra-run CV ranged from 4.7 to 9.6%, and for C-peptide, the intra-run CV ranged from 4.7 to 7.0%.

[0167] Inter-assay variability is defined as the reproducibility of measurements between assays. QC, QCM, and QCH were evaluated over 5 days. The inter-assay variability (%CV) of the pools ranged from 7.3 to 11.3% for insulin and 6.2 to 9.0% for C-peptide. All insulin and C-peptide QC pools met the requirement for acceptable reproducibility of ≤15%CV (Table 3).

[0168] Example 4: Analytical sensitivity (detection limit) Limit of Blank (LOB): The LOB is the point at which the measured value is greater than its associated uncertainty and is arbitrarily defined as two standard deviations (SD) from zero concentration. Selectivity is the ability of an analytical method to discriminate and quantify an analyte in the presence of other components in the sample. For selectivity, an analysis of a blank sample of an appropriate biological matrix (strip serum) was obtained and tested for interferences and guaranteed selectivity at the lower limit of quantitation. The blank was measured 20 times and the resulting area ratios were back-calculated.

[0169] LOB was determined to be 0.9 μIU / mL for insulin and 0.06 ng / mL for C-peptide.

[0170] Limit of Detection (LOD): LOD is the point at which the measured value is greater than its associated uncertainty and is arbitrarily defined as 4 standard deviations (SD) from zero concentration. Selectivity is the ability of an analytical method to discriminate and quantify an analyte in the presence of other components in the sample. For selectivity, analyses of blank samples of an appropriate biological matrix (strip serum) were obtained and tested for interferences and guaranteed selectivity at the lower limit of quantitation. The blank was measured 20 times and the resulting area ratios were back-calculated.

[0171] The LODs were determined to be 1.5 μIU / mL for insulin and 0.10 ng / mL for C-peptide.

[0172] Limit of Quantitation (LOQ): The LOQ is the point at which a measurement becomes quantitatively meaningful. Insulin and C-peptide respond, differentiate, and separate at this LOQ, reproducibly with 20% precision and 80% to 120% accuracy. The LOQ was determined by assaying five samples (1.25, 2.5, 5, 10, and 20 μIU / mL for insulin and 0.11, 0.22, 0.44, 0.85, and 0.17 ng / mL for C-peptide) at concentrations close to the expected LOQ, and then assessing intra-assay reproducibility in seven runs and inter-assay reproducibility in eight additional runs (Table 5). 2.5 μIU / mL and 0.11 ng / mL for insulin and C-peptide, respectively, are the lowest concentrations that yield acceptable performance, with the 95% confidence intervals for CVs remaining below 20%.

[0173] The LOQ was set at 2.5 or 3 μIU / mL for insulin and 0.11 ng / mL for C-peptide.

[0174] Example 5: Analyte Measurement Range (AMR) Calibration Verification: Ten spiked strip serum sample pools (calibrator concentrations were 1.25, 2.5, 5, 10, 20, 40, 80, 160, 240 and 320 μIU / mL and 0.11, 0.21, 0.43, 0.85, 1.70, 3.40, 6.80, 13.60, 20.40 and 27.20 ng / mL for insulin) were prepared and analyzed 18 times on 13 separate days.

[0175] Weighted (1 / X) quadratic regression (ignoring the origin) from the 18 curves yielded correlation coefficients of 0.989 or better for insulin and 0.992 or better for C-peptide with an accuracy of ±20%, demonstrating a linear range of 5 to 320 μIU / mL for insulin and 0.11 to 27.20 ng / mL for C-peptide (Table 6).

[0176] Example 6: Diagnosis of insulin resistance Anthropomorphic measurements (age, sex, SBP, DBP, and BMI) and biomarkers (FG, insulin, C-peptide, HDL-C, LDL-C, TG, creatinine, and alanine aminotransferase (ALT)) were all available for 335 of the participants. Among these 335 participants, we found that FG, insulin, C-peptide, HDL-C, TG, and BMI (all P < 0.0001), ALT (P = 0.002), and SBP (P = 0.008) were associated with IR in models adjusted for age and sex. Using stepwise model selection, we found that an IR model including only insulin, C-peptide, and BMI had an AUC of 0.89. When model selection was restricted to biomarkers, a model including only insulin and c-peptide had an AUC of 0.88. In conclusion, in this study of nondiabetic, non-Hispanic whites, fasting serum insulin and C-peptide concentrations were both associated with measures of IR and, when combined, provided highly accurate information about the prevalence of IR.

[0177] Differences in traditional risk factors between those with and without IR were assessed using the Wilcoxon rank-sum test for discrete variables and the chi-square test for continuous variables. The associations between insulin and C-peptide and IR were assessed using logistic regression models adjusted for age, sex, SBP, DBP, BMI, FG, HDL-C, LDL-C, TG, creatinine, and ALT. Risk score 1 included insulin, C-peptide, and BMI. Risk score 2 included insulin and C-peptide. All probability values ​​are two-sided, and 95% confidence intervals (CIs) are presented. All analyses were performed using SAS version 9.2.

[0178] The associations between insulin resistance and biochemical and anthropometric measures are shown in Table 2. After adjusting for age, sex, and ethnicity, all but creatinine were associated with insulin resistance (P < 0.05). However, when all biochemical and anthropometric measures were included in the model, only insulin, C-peptide, creatinine, and BMI were associated with insulin resistance.

[0179] [Table 2]

[0180] [Table 3]

[0181] Because insulin, C-peptide, creatinine, and BMI emerged as the most important variables in our modeling, we combined them into a single risk score (Model 1). This analysis demonstrated that using this approach, individuals in the top quartile of this risk score were >15 times more likely to have insulin resistance than those outside the top quartile (OR = 15.1, 95% CI 8.7–26.3) in models adjusted for age, sex, ethnicity, fasting plasma glucose, LDL-C, HDL-C, triglycerides, alanine aminotransferase, and systolic and diastolic blood pressure (Table 3).

[0182] Recognizing that incorporating clinical variables into laboratory diagnoses can present practical challenges, we also tested the performance of risk scores that included only insulin, C-peptide, and creatinine (Model 2) or only insulin and C-peptide (Model 3). The risk score incorporating insulin, C-peptide, and creatinine (Model 2) slightly reduced the odds of IR for individuals in the top quartile of this score to 13.6 (95% CI 7.9–23.6) for individuals in the top quartile of this risk score versus those not in this quartile. Finally, using only insulin and C-peptide results (Model 3), individuals in the top quartile of this risk score had 9 times higher odds of being insulin resistant than those not in this quartile (OR = 9.9, 95% CI 5.8–17.0).

[0183] Metabolic syndrome has long been recognized as strongly associated with insulin resistance and future risk of developing type 2 diabetes. In this study population, we found that metabolic syndrome was associated with insulin resistance (OR = 3.7, 95% CI 2.4–5.8), even in models adjusted for age, sex, ethnicity, LDL-C, creatinine, alanine aminotransferase, systolic and diastolic blood pressure. In contrast, metabolic syndrome was not associated with insulin resistance after further adjustment for insulin and C-peptide (OR = 1.1, 95% CI 0.6–1.9) (Table 1). Notably, all three risk scores were associated with insulin resistance, regardless of whether metabolic syndrome was present (Table 4).

[0184] [Table 4]

[0185] The information from these models can be used to define the probability that an individual is insulin resistant. Table 5 shows the probability that an individual is insulin resistant at various percentiles of three different risk scores that include either 1) C-peptide and insulin, 2) C-peptide, insulin, creatinine, and BMI, and 3) C-peptide, insulin, creatinine, and BMI. While slight differences exist between the models, it is clear that the majority of the information is contained within the model that incorporates C-peptide and insulin.

[0186] [Table 5]

[0187] FIG. 1 shows that insulin and C-peptide are associated with insulin resistance (IR) in individuals with and without metabolic syndrome.

[0188] We tested the ability of clinical parameters and laboratory results to predict insulin resistance levels derived from formal measurements of insulin resistance using SSPG in a multiethnic cohort studied in a GCRC setting over a 12-year period. Consistent with prior research (REFS), we observed that a wide range of clinical parameters, including FPG, insulin, C-peptide, HDL-C, LDL-C, triglycerides, alanine aminotransferase, body mass index (BMI), and blood pressure, were associated with formal measures of insulin resistance, even after adjusting for age, sex, and ethnicity. Notably, most of these associations did not remain significant after adjusting for insulin and C-peptide outcomes, suggesting that these themselves reflect an underlying state of insulin resistance, which almost completely explains the model adjustment by including insulin and C-peptide levels. Only BMI and creatinine remained marginally significant when the model included insulin and C-peptide measures.

[0189] A surprising finding from this study was the observation that measurements of both insulin and C-peptide contribute significantly to the ability to accurately predict the level of insulin resistance measured using SSPG.

[0190] In this study, we used a multiplexed assay to measure intact insulin and C-peptide using high-throughput liquid chromatography-tandem mass spectrometry, which allows the definition of specific thresholds that persist over time.

[0191] While there are many ways in which information about estimated insulin resistance levels can be conveyed, we anticipate that one of the most useful ways to represent this data will be to present the probability that an individual has a particular threshold of insulin resistance. To this end, we express this as the probability of insulin resistance, defined here as SSPG ≥ 198 mg% (upper tertile). While creatinine and BMI measurably modify this prediction tool, insulin and C-peptide account for the majority of the information.

[0192] In summary, we demonstrated that a model incorporating fasting and C-peptide measurements can predict formal measurements of insulin resistance levels using SSPG with good accuracy. The strengths of this study are the model's simplicity and its validity regardless of whether clinical parameters or other laboratory values ​​are available. Our findings suggest that such a risk score may be useful in assessing an individual's level of insulin resistance, regardless of whether clinical signs are present. These findings also suggest that such measurements may be beneficial for the longitudinal assessment of subjects undergoing lifestyle or pharmacological interventions to reduce insulin resistance, an assessment that is currently difficult outside of a research setting.

[0193] Insulin and C-peptide are associated with insulin resistance independently of each other and of traditional risk factors, including fasting glucose.

[0194] Insulin and C-peptide can be used to assess the probability of insulin resistance, formally assessed using the SSPG method, in individuals with and without metabolic syndrome.

[0195] A risk score that combines C-peptide and insulin (using standardized, traceable C-peptide and insulin measurements) can be derived and used to provide patients with their probability of having insulin resistance.

[0196] This technique of high-throughput mass spectrometry assay that simultaneously quantifies intact insulin and C-peptide concentrations may serve as a reference point in the standardization of insulin and C-peptide measurements and, ultimately, the creation of a universally accepted quantitative method for identifying insulin resistance. The current study uses this method to measure intact insulin and C-peptide and evaluates the utility of these standardized measurements for assessing insulin resistance, as measured by insulin-mediated glucose disposal, in non-diabetic, apparently healthy individuals. The current analysis applies this method to an initial cohort (self-identified non-Hispanic white individuals) for which all measurements were available.

[0197] Example 6: Intact insulin and C-peptide levels measured by multiplex mass spectrometry Elevated insulin levels have been shown to be associated with an increased risk of developing diabetes. Although clinical testing for insulin and C-peptide has been available for decades, insulin measurements have not been widely used in clinical practice, at least in part due to the wide range of available immunoassays and the difficulty of correlating results from one assay platform with those from other platforms. This shortcoming has been noted in the literature for both insulin and C-peptide. Therefore, we developed a multiplexed mass spectrometry-based assay that measures both intact insulin and C-peptide. We investigated the relationship between insulin, C-peptide, and glucose levels in fasting serum samples from a cohort of apparently healthy volunteers.

[0198] Apparently healthy subjects provided informed consent (WIRB#20121940), and fasting venous blood samples were obtained. Glucose levels were determined using an Olympus AU2700™ chemistry-immunoanalyzer (Melville, NY), and insulin and C-peptide levels were determined by multiplex mass spectrometry assays. Anthropometric measurements were obtained at the time of blood collection.

[0199] The study included 103 apparently healthy volunteers (46.7% male, median age = 35, median BMI = 26.1). The median insulin level in this population was 8.07 μIU / ml (IQR 5.38-12.55), and 19.4% of subjects had elevated insulin (≥ 15 μIU / ml). Among those with either impaired fasting glucose or fasting glucose between 90 and < 100 mg / dL, 50% and 40%, respectively, had elevated insulin levels; in contrast, only 9.6% of those with fasting glucose < 90 mg / dL had elevated insulin levels. The median insulin level was 14.78 μIU / ml (IQR 6.44-42.29) in 10 subjects with impaired fasting glucose, 9.79 μIU / ml (8.43-17.70) in 20 subjects with fasting glucose 90-<100 mg / dL, and 7.26 μIU / ml (4.49-9.47) in 73 subjects with fasting glucose <90 mg / dL (P=0.0004 for the difference between medians). Insulin levels in those with a BMI >26 (median = 9.17 μIU / ml, IQR 6.96-17.33) were greater than those with a BMI ≤26 (median = 6.92 μIU / ml, IQR 4.08-9.09; P=0.0003). Insulin and C-peptide levels were highly correlated (r=0.88).

[0200] Clinical sample collection and preparation Blood was obtained from apparently healthy adult volunteers (WIRB protocol #1085473). Anthropomorphic measurements were obtained at the time of sampling. Blood was obtained using barrier-free serum preparation tubes (red top) and allowed to clot. The obtained serum was processed immediately and then stored at -80°C until analysis. Enrichment of insulin and C-peptide from patient serum (150 μL) was performed using two monoclonal antibodies immobilized on magnetic beads. Samples were processed using a robotic liquid handler (Microlab STAR, Hamilton, Reno, NV).

[0201] Assay Analytical separation of intact insulin and C-peptide from remaining matrix components was achieved prior to MS using a TurboFlow Aria TLX-4 (Thermo-Fisher, San Jose, CA), a fully automated online two-dimensional liquid chromatography system. A 6490 Triple Quadrupole Mass Spectrometer (Agilent, Santa Clara, CA) equipped with an iFunnel served as the MS / MS detector. Detailed descriptions of LC and MS conditions have been previously described. 9 Glucose levels were determined using an Olympus AU2700™ chemistry-immunoanalyzer (Melville, NY).

[0202] statistical analysis Differences in insulin levels between participants with low (<90 mg / dL), intermediate (90-<100 mg / dL), and high (100-125 mg / dL) fasting glucose levels were assessed by parametric (ANOVA) and nonparametric (Kruksal-Wallis) tests. Differences in insulin levels between patients with low (<26) and high (≥26) BMI were assessed by unpaired t-tests. The association between BMI and insulin was assessed in multivariate regression models adjusted for age, sex, and fasting glucose levels.

[0203] Median insulin levels were 7.26 μIU / ml (4.49-9.47) in 73 subjects with fasting glucose <90 mg / dL, 9.79 μIU / ml (8.43-17.70) in 20 subjects with fasting glucose 90-<100 mg / dL, and 14.78 μIU / ml (IQR 6.44-42.29) in 10 subjects with impaired fasting glucose (Fig. 2).

[0204] Insulin levels in those with a BMI > 26 (median = 9.17 μIU / ml, IQR 6.96–17.33) were greater than those with a BMI ≤ 26 (median = 6.92 μIU / ml, IQR 4.08–9.09; P = 0.0003) (Fig. 3).

[0205] Insulin and C-peptide levels were found to increase in response to fasting glucose (Figures 4 and 5).

[0206] In a multivariate regression model, after adjusting for age, sex, and fasting glucose, BMI was associated with fasting insulin (P = 0.00002). Each unit increase in BMI was associated with a 0.59 μIU increase in fasting insulin (95% CI 0.33-0.85) (Figure 6).

[0207] Consideration This study demonstrates the application of a multiplexed mass spectrometry-based assay for measuring intact insulin and C-peptide, an SI-traceable assay standardized by calibration to the WHO insulin reference material 83 / 500. C-peptide measurements were carefully quantified using calibrators assigned by quantitative amino acid analysis. Our findings indicate that (1) elevated insulin is observed in a significant number of individuals with fasting blood glucose within the normal range, and (2) a progressively increasing proportion exhibit elevated insulin at higher glucose levels within the normal range.

[0208] conclusion We used multiplex intact insulin and C-peptide assays to define normal ranges for both analytes.

[0209] Focusing on these definitions of normal ranges to use individuals with normal fasting glucose, normal hemoglobin A1C, and a BMI <26 results in a normal range of <16 microIU / mL for insulin and 0.68-2.16 ng / mL for C-peptide.

[0210] Fasting levels of insulin and C-peptide increased progressively as fasting glucose increased.

[0211] Fasting insulin levels were strongly influenced by BMI.

[0212] By using well-characterized assessments of insulin resistance and defining the relationship between fasting insulin and C-peptide in an individual and fasting glucose and anthropomorphic measurements, it is possible to define tools that allow for easy assessment of insulin sensitivity levels.

[0213] Example 7: Identification of insulin resistance in apparently healthy individuals by measuring insulin and C-peptide levels by mass spectrometry We determined that a risk score including insulin, C-peptide, TG / HDL ratio, creatinine, and BMI can help identify individuals with insulin resistance, both with and without metabolic syndrome.

[0214] All study participants were apparently healthy and had no history of cardiovascular disease. Individuals with a fasting glucose ≥ 126 mg / dL or taking hypoglycemic medications at baseline were excluded from the analysis.

[0215] Race and ethnicity were determined during medical history. Weight and height were measured while the individual was lightly dressed and shoeless. Body mass index was calculated by dividing weight in kilograms by height in meters squared. Blood pressure was measured using an automated blood pressure recorder. Prior to these measurements, subjects sat quietly in a chair for 5 minutes with both feet on the floor and arms supported at heart level. Three blood pressure readings were taken at 1-minute intervals using an appropriately sized cuff and averaged. Metabolic syndrome was present if three of the following characteristics were present: BMI > 30 kg / m2; FG > 100 mg / dL; hypertension (SBP ≥ 130 mmHg or DBP ≥ 85 mmHg), low HDL-C (< 50 mg / dL, women; < 40 mg / dL, men), and TG ≥ 150 mg / dL.

[0216] After an overnight fast, intravenous catheters were placed in each arm. One catheter was used to draw blood samples, and the other catheter was used to administer octreotide (0.27 μg / m2 / min), insulin (32mU / m 2 / min) and glucose (267 mg / m 2 A 180-minute infusion of 1000kJ / min (SSPG) was administered. Blood samples were taken at 10-minute intervals between 150 and 180 minutes of the infusion to determine steady-state plasma glucose (SSPG) and steady-state plasma insulin (SSPI) concentrations. Because SSPI concentrations were similar in all individuals during IST, SSPG concentrations provide a direct measure of insulin's ability to mediate the disposal of the infused glucose load. Thus, the higher the SSPG concentration, the more insulin-resistant the individual. Insulin-mediated glucose disposal determined by IST is highly correlated with glucose disposal obtained using the euglycemic-hyperinsulinemic clamp technique. In this study, IR was defined as falling into the upper tertile of measured insulin resistance (SSPG ≥ 198 mg / dL). Serum samples used for insulin and C-peptide measurements were derived from fasting baseline samples obtained before the start of the IST protocol. Insulin and C-peptide measurements were performed as described herein.

[0217] [Table 6]

[0218] Differences in biochemical and anthropometric measurements between those with and without IR were assessed using Wilcoxon rank-sum tests or t-tests for continuous variables and chi-square tests for discrete variables. Associations between study variables and IR were assessed in logistic regression models adjusted for the covariates listed in the table. Because SSPG distribution histograms appeared different for non-Hispanic whites (n = 335), Hispanics (n = 42), and others (n = 158), ethnicity was coded as a categorical variable for these three groups. Risk score components were selected in stepwise regression. All available variables were eligible for inclusion in the model. After optimal fit, available variables meeting specified significance inclusion cutoffs were added to the model, and all candidate variables in the model were evaluated and removed if their significance increased beyond the specified exclusion level. This process was repeated until no variables were added or removed for the inclusion and exclusion cutoffs indicated in the text. Risk score coefficients were determined in models adjusted for age, sex, ethnicity, insulin, C-peptide, creatinine, BMI, TG / HDLC, FG, SBP, DBP, LDL-C, and alanine aminotransferase, excluding variables that were part of the risk score. All p-values ​​are two-sided, and 95% confidence intervals are shown. All analyses were performed using SAS version 9.2.

[0219] The biochemical and anthropometric measurements of the study participants are shown in Table 1 according to their insulin resistance status. Insulin-resistant participants had higher levels of FG, insulin, C-peptide, HDL-C, TG, TG / HDL, AAT, BMI, and SBP. Insulin-resistant participants had lower levels of HDL-C and LDL-C.

[0220] We examined the association between study variables and insulin resistance while adjusting for age, sex, ethnicity, FG, insulin, C-peptide, LDL-C, TG / HDL, creatinine, AAT, BMI, and SBP and DBP (Table 2). In this fully adjusted analysis, insulin, C-peptide, creatinine, BMI, and TG / HDL were associated with insulin resistance. Regardless of the levels of C-peptide and other study variables, each 10 pmol / L increase in insulin was associated with a 1.2-fold increased odds of insulin resistance (SSPG ≥ 198 mg / dL) (95% CI 1.1-1.4). Similarly, each 100 pmol / L increase in C-peptide was associated with a 1.6-fold increased odds of insulin resistance (95% CI 1.3-2.0).

[0221] Because insulin and C-peptide are highly correlated (r=0.85), we examined the prevalence of IR by insulin and C-peptide tertiles (Figure 18). Within each insulin tertile, the fraction of IR individuals increased with C-peptide tertile level. Conversely, within each C-peptide tertile, the fraction of IR individuals increased with insulin tertile level.

[0222] [Table 7]

[0223] [Table 8]

[0224] We used a stepwise model selection procedure to identify variables for the IR risk model from among those listed in Table 2, as well as age and sex. We used P < 0.001 as the criterion for variables to be included and not removed from the model. These included insulin, C-peptide, and creatinine (in that order). For individuals in the top quartile of the risk score including these variables (vs. those not in the top quartile), the unadjusted odds ratio for IR was 18.7 (95% CI 11.4–30.7, Table 3). After adjusting for variables not included in the risk score, the odds ratio was 10.8 (95% CI 6.2–19.0). Because insulin and C-peptide can be measured in a single multiplex test, we also tested a model including only insulin and C-peptide and found the unadjusted odds ratio for IR was 12.8 (95% CI 8.0–20.4). Using looser selection criteria for including and not excluding variables (P<0.05), five variables were included in the final model: insulin, C-peptide, creatinine, BMI, and TG / HDL (in that order). For individuals in the top quartile of the risk score that included these variables, the unadjusted odds ratio for IR was 20.0 (95% CI 12.1-33.0). After adjusting for variables not included in the risk score, the odds ratio was 16.1 (95% CI 9.5-27.3).

[0225] We also tested HOMA-IR, a commonly used method to estimate insulin resistance, and found that those in the top quartile of HOMA-IR (vs. those outside the top quartile) had an unadjusted odds ratio for IR of 10.3 (95% CI 6.6-16.1). After adjusting for variables not included in the risk score, the odds ratio was 1.5 (95% CI 0.8-2.7).

[0226] When the study population was restricted to those with metabolic syndrome, these risk scores remained associated with IR: after adjusting each score for variables not included in the score, OR = 9.1 (95% CI 4.2 to 19.5) for the insulin and C-peptide score, OR = 13.3 (95% CI 5.9 to 30.1) for the insulin, C-peptide, and creatinine score, and OR = 13.7 (95% CI 6.3 to 29.9) for the insulin, C-peptide, creatinine, BMI, and TG / HDL score.

[0227] The clinical characteristics of the categorized study patient population are shown in Table 1, where subjects are classified according to insulin resistance status. Those with insulin resistance had a higher proportion of men and higher fasting plasma glucose (FPG), insulin, C-peptide, triglycerides, alanine aminotransferase, body mass index (BMI), and systolic blood pressure. HDL-C and LDL-C were lower in those with insulin resistance.

[0228] We also used these risk scores to estimate the probability that an individual had IR (Table 4). Thus, rather than assigning a likelihood of IR based on a single cutpoint (e.g., whether a patient falls in the top quartile of the risk score), we can calculate the probability of having IR for each percentile of risk. For each of the three risk scores in Tables 3 and 4, we provided formulas that can be used to calculate the probability of IR from measurements of the risk score components.

[0229] The associations between insulin resistance and biochemical and anthropometric measures are shown in Table 2. After adjusting for age, sex, and ethnicity, all but creatinine were associated with insulin resistance (P < 0.05). However, when all biochemical and anthropometric measures were included in the model, only insulin, C-peptide, creatinine, and BMI were associated with insulin resistance.

[0230] Because insulin, C-peptide, creatinine, and BMI emerged as the most important variables in our modeling, we combined them into a single risk score (Model 1). This analysis demonstrated that using this approach, individuals in the top quartile of this risk score were >15 times more likely to have insulin resistance than those outside the top quartile (OR = 15.1, 95% CI 8.7–26.3) in models adjusted for age, sex, ethnicity, fasting plasma glucose, LDL-C, HDL-C, triglycerides, alanine aminotransferase, and systolic and diastolic blood pressure (Table 3).

[0231] Recognizing that incorporating clinical variables into laboratory diagnoses can present practical challenges, we also tested the performance of risk scores that included only insulin, C-peptide, and creatinine (Model 2) or only insulin and C-peptide (Model 3). The risk score incorporating insulin, C-peptide, and creatinine (Model 2) slightly reduced the odds of IR for individuals in the top quartile of this score to 13.6 (95% CI 7.9–23.6) for individuals in the top quartile of this risk score versus those not in this quartile. Finally, using only insulin and C-peptide results (Model 3), individuals in the top quartile of this risk score had 9 times higher odds of being insulin resistant than those not in this quartile (OR = 9.9, 95% CI 5.8–17.0).

[0232] In this study population, we found that metabolic syndrome was associated with insulin resistance (OR = 3.7, 95% CI 2.4-5.8), even in models adjusted for age, sex, ethnicity, LDL-C, creatinine, alanine aminotransferase, systolic and diastolic blood pressure. In contrast, metabolic syndrome was not associated with insulin resistance after further adjustment for insulin and C-peptide (OR = 1.1, 95% CI 0.6-1.9) (Table 1). Notably, all three risk scores were associated with insulin resistance, regardless of whether metabolic syndrome was present (Table 4). Table 4 shows the probability of an individual being insulin resistant at various percentiles.

[0233] [Table 9]

[0234] Risk score calculation and probability of IR Risk score 1: insulin (pmol / L), C-peptide (pmol / L), creatinine (mg / dL) (1.1)RS = (insulin x 0.0265) + (C-peptide x 0.00511) + (creatinine x -3.2641)

[0235]

number

[0236]

number

[0237]

number

[0238] A surprising finding from this study was the observation that measurements of both insulin and C-peptide contribute significantly to the ability to accurately predict the level of insulin resistance measured using SSPG.

[0239] We demonstrated that a model incorporating fasting and C-peptide measurements can predict formal measurements of insulin resistance levels using SSPG with good accuracy.

[0240] Those in the top quartile of a risk score including insulin, C-peptide, creatinine, and BMI were more likely to have IR than those in the lower quartile (OR = 15.1, 95% CI 8.7-26.3). This association was observed in both those with metabolic syndrome (OR = 17.7, 95% CI 7.8-40.5) and those without metabolic syndrome (OR = 16.9, 95% CI 7.3-39.2).

[0241] The contents of the articles, patents, and patent applications, and all other literature and electronically available information mentioned or cited herein are incorporated by reference in their entirety to the same extent as if each individual publication was specifically and individually indicated to be incorporated by reference. Applicants reserve the right to physically incorporate into this application any and all materials and information from any such articles, patents, patent applications, or other physical and electronic literature.

[0242] The methods illustratively described herein may suitably be practiced in the absence of any element or elements, limitation or limitations not specifically disclosed herein. Thus, for example, the terms "comprising," "including," "containing," etc., should be read expansively and without limitation. Moreover, the terms and expressions used herein are used for purposes of description and not limitation, and the use of such terms and expressions is not intended to exclude any equivalents of the shown and described features or portions thereof. It is recognized that various modifications are possible within the scope of the invention as claimed. Thus, while the invention has been specifically disclosed by preferred embodiments and optional features, it should be understood that modifications and variations of the invention disclosed and embodied therein may be employed by those skilled in the art, and such modifications and variations are considered to be within the scope of the invention.

[0243] The invention has been described broadly and generically herein. Each of the narrower species and subspecies falling within the generic disclosure also forms part of the method. This includes a general description of the method with a condition or negative limitation that removes any subject matter from the genus, whether or not the removed material is specifically set forth herein.

[0244] Other embodiments are within the scope of the following claims. Furthermore, where features or aspects of a method are described in terms of a Markush group, one of ordinary skill in the art will understand that the invention may also be described in terms of any individual member or subgroup of members of the Markush group.

Claims

1. 1. A method for measuring insulin resistance in a diabetic or prediabetic patient by mass spectrometry, comprising: (a) measuring the level of creatinine in a sample; (b) purifying the sample containing insulin and C-peptide by liquid chromatography; (c) ionizing insulin and C-peptide from said sample with an ionization source under conditions suitable to generate one or more insulin and C-peptide ions detectable by mass spectrometry; (d) determining the amount of one or more insulin and C-peptide ions by mass spectrometry; (e) determining the amount of insulin and C-peptide in the sample based on the amount of the one or more insulin and C-peptide ions; and (f) determining an insulin resistance score (RS) and / or a probability of developing insulin resistance (P(IR)) from the amounts of insulin and C-peptide and the creatinine level in the sample, wherein insulin resistance in a diabetic or pre-diabetic patient is measured by the RS and / or the P(IR), wherein the RS and the P(IR) are as follows: RS = (insulin (pmol / L) × 0.0265) + (C-peptide (pmol / L) × 0.00511) + (creatinine (mg / dL) × −3.2641), The steps A method comprising:

2. 10. The method of claim 1, further comprising measuring body mass index (BMI), triglyceride (TG) levels, high density lipoprotein C (HDL-C) levels, BMI, TG, or HDL-C levels.

3. 10. The method of claim 1, wherein the sample is a plasma or serum sample.

4. The method of claim 1 , wherein the ionization source is an electrospray (ESI) ionization source.

5. The method of claim 1 , wherein the sample is subjected to acidic or basic conditions prior to mass spectrometry.

6. 6. The method of claim 5, wherein subjecting the sample to acidic conditions comprises exposing the sample to formic acid.

7. 6. The method of claim 5, wherein subjecting the sample to basic conditions comprises exposing the sample to Trizma and / or ethanol.

8. 2. The method of claim 1, wherein the one or more ions comprise an insulin precursor ion having a mass-to-charge ratio (m / z) of 968.9±0.

5.

9. 2. The method of claim 1, wherein the one or more ions comprise one or more insulin fragment ions selected from the group consisting of ions having m / z of 136.0±0.5, 226.1±0.5, and 345.2±0.

5.

10. 2. The method of claim 1, wherein the one or more ions comprise a C-peptide precursor ion having a mass-to-charge ratio (m / z) of 1007.7±0.

5.

11. 2. The method of claim 1, wherein the one or more ions comprise one or more C-peptide fragment ions selected from the group consisting of ions having m / z of 533.3±0.5, 646.4±0.5, and 927.5±0.

5.

12. 10. The method of claim 1, wherein the sample is delipidated prior to quantification by mass spectrometry.

13. 10. The method of claim 1, wherein the liquid chromatography comprises high performance liquid chromatography (HPLC) or high turbulence liquid chromatograph (HTLC).

14. The method of claim 1 , wherein the mass spectrometry is tandem mass spectrometry, high resolution mass spectrometry, or high resolution / high accuracy mass spectrometry.

15. 10. The method of claim 1, further comprising subjecting the sample to a concentration step to obtain a fraction enriched in insulin and C-peptide.

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