A high-throughput mass spectrometry assay to simultaneously measure intact insulin and C-peptide

Insulin overdose with fatal outcome?: Two forensic cases

Intentional overdose with insulin preparations is rare. However, fatal consequences due to severe hypoglycemia could occur. Postmortem toxicology screening of insulin is a challenge, given the chemical characteristics of this protein and the difficulty of distinguishing between endogenous and exogenous insulin in blood. Here, we describe two cases of patients with diabetes using insulin and oral anti-diabetics. The main question in both cases was whether or not disturbance in glucose metabolism contributed to death. In case A, there was strong evidence that self-poisoning with insulin and subsequent hypoglycemia caused the death. However, this could not be confirmed due to lack of adequate forensic toxicology tests. In case B, no hypoglycemia was observed. Though, compared with case A, additional forensic examination was performed to investigate whether glycemic disturbances could have contributed to the death. In this report, we focus on the most appropriate analytical methods for the detection of exogenous insulin in the human body and give recommendations for toxicology testing of glucose levels and insulin in postmortem specimens.

Interlaboratory Comparison of Antibody-Free LC-MS/MS Measurements of C-peptide and Insulin

BACKGROUND

The enhanced precision and selectivity of liquid chromatography-tandem mass spectrometry (LC-MS/MS) makes it an attractive alternative to certain clinical immunoassays. Easily transferrable work flows could help facilitate harmonization and ensure high-quality patient care. We aimed to evaluate the interlaboratory comparability of antibody-free multiplexed insulin and C-peptide LC-MS/MS measurements.

METHODS

The laboratories that comprise the Targeted Mass Spectrometry Assays for Diabetes and Obesity Research (TaMADOR) consortium verified the performance of a validated peptide-based assay (reproducibility, linearity, and lower limit of the measuring interval [LLMI]). An interlaboratory comparison study was then performed using shared calibrators, de-identified leftover laboratory samples, and reference materials.

RESULTS

During verification, the measurements were precise (2.7% to 3.7%CV), linear (4 to 15 ng/mL for C-peptide and 2 to 14 ng/mL for insulin), and sensitive (LLMI of 0.04 to 0.10 ng/mL for C-peptide and 0.03 ng/mL for insulin). Median imprecision across the 3 laboratories was 13.4% (inter-quartile range [IQR] 11.6%) for C-peptide and 22.2% (IQR 20.9%) for insulin using individual measurements, and 10.8% (IQR 8.7%) and 15.3% (IQR 14.9%) for C-peptide and insulin, respectively, when replicate measurements were averaged. Method comparison with the University of Missouri reference method for C-peptide demonstrated a robust linear correlation with a slope of 1.044 and r2 = 0.99.

CONCLUSIONS

Our results suggest that combined LC-MS/MS measurements of C-peptide and insulin are robust and adaptable and that standardization with a reference measurement procedure could allow accurate and precise measurements across sites, which could be important to diabetes research and help patient care in the future.

Recent developments in mass-spectrometry-based targeted proteomics of clinical cancer biomarkers

Routine measurement of cancer biomarkers is performed for early detection, risk classification, and treatment monitoring, among other applications, and has substantially contributed to better clinical outcomes for patients. However, there remains an unmet need for clinically validated assays of cancer protein biomarkers. Protein tumor markers are of particular interest since proteins carry out the majority of biological processes and thus dynamically reflect changes in cancer pathophysiology. Mass spectrometry-based targeted proteomics is a powerful tool for absolute peptide and protein quantification in biological matrices with numerous advantages that make it attractive for clinical applications in oncology. The use of liquid chromatography-tandem mass spectrometry (LC-MS/MS) based methodologies has allowed laboratories to overcome challenges associated with immunoassays that are more widely used for tumor marker measurements. Yet, clinical implementation of targeted proteomics methodologies has so far been limited to a few cancer markers. This is due to numerous challenges associated with paucity of robust validation studies of new biomarkers and the labor-intensive and operationally complex nature of LC-MS/MS workflows. The purpose of this review is to provide an overview of targeted proteomics applications in cancer, workflows used in targeted proteomics, and requirements for clinical validation and implementation of targeted proteomics assays. We will also discuss advantages and challenges of targeted MS-based proteomics assays for clinical cancer biomarker analysis and highlight some recent developments that will positively contribute to the implementation of this technique into clinical laboratories.

Insulin resistance probability score and incident cardiovascular disease

BACKGROUND

Insulin resistance (IR) is associated with cardiovascular disease (CVD). However, insulin immunoassay variability and scarce research of the elderly have hindered the adoption of IR assessment for CVD prevention. We asked whether the probability of having IR [p(IR)]-derived from insulin and C-peptide mass-spectrometry assays-was associated with CVD in the elderly.

METHODS

A random cohort was drawn from MPP, a population-based study of the elderly. After excluding those with missing data, CVD, or diabetes, 3645 participants (median age = 68) remained.

RESULTS

During follow-up (13.3 years), 794 incident CVD events were observed. p(IR) > 80% (n = 152) compared with p(IR) ≤ 80% was associated with incident CVD (HR = 1.51, 95% CI 1.12-2.05, p = 0.007) and CVD or all-cause mortality (HR = 1.43, 95% CI 1.16-1.77, p = 0.0009) after adjusting for age, sex, hypertension, smoking, HDL-cholesterol, total cholesterol, triglycerides, BMI, and prediabetes.

CONCLUSION

High p(IR) was associated with >50% greater risk of incident CVD. IR assessment in the elderly may be warranted.

Simultaneous monitoring of multiple hormones from human islets of Langerhans using solid-phase extraction-mass spectrometry

Islets of Langerhans release peptide hormones in controlled amounts and patterns to ensure proper maintenance of blood glucose levels. The overall release of the hormones is shaped by external factors and by autocrine and paracrine interactions occurring within the islets. To better understand what controls the secretion of islet-secreted peptides, and how these processes go awry in diabetes, methods to monitor the release of multiple hormones simultaneously are needed. While antibody-based assays are typically used, they are most often applied to quantification of a single hormone. Mass spectrometry (MS), on the other hand, is well suited for quantifying multiple hormones simultaneously but typically requires time-consuming separation steps with biological samples. In this report, response surface methodology was used to identify a set of optimal solid-phase extraction (SPE) conditions for the islet-secreted peptides, insulin, C-peptide, glucagon, and somatostatin. The optimized SPE method was used with multiple reaction monitoring and isotopically labeled standards to quantify secretion levels. Calibrations were linear from 0.5 to 50 nM with < 15% RSD peak area ratios. A microfluidic system was used to perfuse 30 human islets with different glucose conditions, and fractions were collected every 2 min for SPE-MS analysis. Results showed the release dynamics of the individual peptides, as well as patterns, such as positively and negatively correlated release and oscillations. This rapid SPE-MS method is expected to be useful for examining other peptide and small-molecule secretions from islets and could be applied to a number of other biological systems for investigating cellular communication.

Insulin: Know what your immunoassay detects. Evaluation of two new immunoassays

BACKGROUND

Insulin is essential for glycemic regulation but diseases can cause a default or an excess of insulin secretion leading to dysregulated glycemia. Hence, measurement of insulinemia is useful to investigate hypoglycemia, determine the pathogenesis of diabetes and evaluate β-cell function. Thus, diabetic patients need supplementation with recombinant human insulin and/or insulin analogues. Analogues have primary sequences different from native human insulin and may not be detected by some immunoassays. The objective of our study was to evaluate new insulin immunoassays by determining their ability to detect different types of human insulin or analogues.

METHODS

This study compared the reactivity of two new insulin immunoassays with five well-established immunoassays on ten commercial insulins. We also measured insulin in blood samples from diabetic or pancreas transplant patients with known treatment.

RESULTS

Contrary to recombinant human insulin, there were differences in the specificity to insulin analogues. We distinguished three immunoassay categories: those recognizing all types of insulin such as the non-specific BI-INS-IRMA®, Architect® and Access® immunoassays; those recognizing human insulin only (Cobas®); and those recognizing human insulin and analogues in variable proportions (Liaison XL®, iFlash® and Maglumi®).

CONCLUSION

An accurate biological interpretation of insulinemia relies on knowledge of the specificity of the immunoassay used.

Automated proteomic sample preparation: The key component for high throughput and quantitative mass spectrometry analysis

Sample preparation for mass spectrometry-based proteomics has many tedious and time-consuming steps that can introduce analytical errors. In particular, the steps around the proteolytic digestion of protein samples are prone to inconsistency. One route for reliable sample processing is the development and optimization of a workflow utilizing an automated liquid handling workstation. Diligent assessment of the sample type, protocol design, reagents, and incubation conditions can significantly improve the speed and consistency of preparation. When combining robust liquid chromatography-mass spectrometry with either discovery or targeted methods, automated sample preparation facilitates increased throughput and reproducible quantitation of biomarker candidates. These improvements in analysis are also essential to process the large patient cohorts necessary to validate a candidate biomarker for potential clinical use. This article reviews the steps in the workflow, optimization strategies, and known applications in clinical, pharmaceutical, and research fields that demonstrate the broad utility for improved automation of sample preparation in the proteomic field.

Comparability of C-Peptide Measurements - Current Status and Clinical Relevance

C-peptide is an increasingly used and established marker for beta cell function by assessing endogenous insulin secretion. Accurate and comparable C-peptide measurements are needed in clinical practice and research studies. For example, to calculate HOMA-indices, the C-peptide/glucose ratio, and the classification of recently published novel subgroups of diabetes and prediabetes have used C-peptide measurements. Although the process for standardization of C-peptide measurements is advanced, its full implementation is still missing; therefore, the current status of the comparability of C-peptide measurements using different immunoassays is unclear. Here we compared five widely used C-peptide immunoassays on different analyzers (Abbott ALINITY i, DiaSorin Liaison XL, Roche Cobas e411, Siemens Healthineers ADVIA Centaur XPT, and Immulite 2000 XPi) using serum samples covering the clinically relevant C-peptide concentration range. Although all investigated immunoassays are traceable to the international reference reagent for C-peptide (NIBSC code: 84/510), results of C-peptide measurements showed significant differences between analyzers in the entire concentration range, especially with increasing C-peptide concentrations. The mean bias was largest (36.6%) between results of the immunoassays by Roche and Siemens Healthineers (ADVIA Centaur XPT), and both assays revealed large discrepancies compared to immunoassays by Abbott, DiaSorin, and Siemens Healthineers (Immulite 2000 XPi). In contrast, the three latter assays showed similar C-peptide results (mean bias: 2.3% to 4.2%). Consequently, C-peptide discrepancies might affect clinical diagnosis and the interpretation of study results. Therefore, there is an urgent need to implement and finalize the standardization process of C-peptide measurements to improve patient care and the comparability of research studies.

Impact of VALID Act implementation on mass spectrometry-based clinical proteomic laboratory developed tests

Mass spectrometry (MS)-based clinical proteomic Laboratory Developed Tests (LDTs) for the measurement of protein biomarkers related to endocrinology, cardiovascular disease, cancer, and Alzheimer's disease are gaining traction in clinical laboratories due to their value in supporting diagnostic and treatment decisions for patients. Under the current regulatory landscape, MS-based clinical proteomic LDTs are regulated by Clinical Laboratory Improvement Amendments (CLIA) under the auspices of the Centers for Medicaid and Medicare Services (CMS). However, should the Verifying Accurate Leading-Edge In Vitro Clinical Test Development (VALID) Act pass, it will grant the FDA greater authority to oversee diagnostic tests, including LDTs. This could impede clinical laboratories' ability to develop new MS-based proteomic LDTs to support existing and emerging patient care needs. Therefore, this review discusses the currently available MS-based proteomic LDTs and their current regulatory landscape in the context of the potential impacts imposed by the passage of the VALID Act.

LC-MS/MS based detection of circulating proinsulin derived peptides in patients with altered pancreatic beta cell function

Routine immunoassays for insulin and C-peptide have the potential to cross-react with partially processed proinsulin products, although in healthy patients these are present at such low levels that the interference is insignificant. Elevated concentrations of proinsulin and des-31,32 proinsulin arising from pathological conditions, or injected insulin analogues, however can cause significant assay interferences, complicating interpretation. Clinical diagnosis and management therefore sometimes require methods that can distinguish true insulin and C-peptide from partially processed proinsulin or injected insulin analogues. In this scenario, the high specificity of mass spectrometric analysis offers potential benefit for patient care. A high throughput targeted LC-MS/MS method was developed as a fit for purpose investigation of insulin, insulin analogues, C-peptide and proinsulin processing intermediates in plasma samples from different patient groups. Using calibration standards and bovine insulin as an internal standard, absolute concentrations of insulin and C-peptide were quantified across a nominal human plasma postprandial range and correlated strongly with immunoassay-based measurements. The ability to distinguish between insulin, insulin analogues and proinsulin intermediates in a single extraction is an improvement over existing immunological based techniques, offering the advantage of exact identification of the species being measured. The method promises to aid in the detection of circulating peptides which have previously been overlooked but may interfere with standard insulin and C-peptide immunoassays.

A homogeneous enzyme-free ratiometric immunoassay for the determination of C-peptide

In this study, a homogeneous enzyme-free ratiometric (HOMO- EF-RA) immunoassay was developed for the sensitive detection of C-peptide. In the immunoassay, there have been a miscible detection system by mixing with the fluorescent quantum dots conjugated antigen (QD-Ag conjugates) and the dylight dye conjugated antibody (DL-Ab conjugates). When connecting between Ag-QD conjugate and Ab-DL conjugate by specific recognition, the system emitted fluorescence resonant energy transfer (FRET). The target C-peptide can inhibit the connection and FRET formation between QD-Ag conjugates and DL-Ab conjugates, thus changing the dual fluorescence. By measuring the ratio dual fluorescence changes of the system, the content of C-peptide was evaluated without any enzyme used and multiple incubation and washing steps. This immunoassay realized the highly sensitive (as low as 0.12 ng mL^-1), selective and rapid (as less as 6 min) detection of C-peptide. Furthermore, the the simple and convenient immunoassay was applied successfully to the determination of C-peptide in real serum samples.

Multiplexed quantification of insulin and C-peptide by LC-MS/MS without the use of antibodies

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Simultaneous quantification of insulin and C-peptide without antibodies.

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Proteolysis with Glu-C permits sensitive and precise measurements.

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Calibration with certified reference material provides traceability.

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Relatively large bias when compared with a commercially available immunoassay.

Introduction

The measurement of insulin and C-peptide provides a valuable tool for the clinical evaluation of hypoglycemia. In research, these biomarkers are used together to better understand hyperinsulinemia, hepatic insulin clearance, and beta cell function. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is an attractive approach for the analysis of insulin and C-peptide because the platform is specific, can avoid certain limitations of immunoassays, and can be multiplexed. Previously described LC-MS/MS methods for the simultaneous quantification of insulin and C-peptide measure the intact analytes and most have relied on immunoaffinity enrichment. These approaches can be limited in terms of sensitivity and interference from auto-antibodies, respectively. We have developed a novel method that does not require antibodies and uses proteolytic digestion to yield readily ionizable proteotypic peptides that enables the sensitive, specific, and simultaneous quantitation of insulin and C-peptide.

Methods

Serum samples were precipitated with acetonitrile. Analytes were enriched using solid phase extraction and then digested with endoproteinase Glu-C. Surrogate peptides for insulin and C-peptide were analyzed using targeted LC-MS/MS.

Results

Inter-day imprecision was below 20 %CV and linearity was observed down to the lower limit of quantitation for both analytes (insulin = 0.09 ng/mL, C-peptide = 0.06 ng/mL). Comparison to a commercially available insulin immunoassay (Beckman Coulter UniCel DxI 600 Access) revealed a 30% bias between methods.

Conclusion

A novel LC-MS/MS method for the simultaneous analysis of insulin and C-peptide using Glu-C digestion was developed and evaluated. A detailed standard operating procedure is provided to help facilitate implementation in other laboratories.

Proprotein Convertase Subtilisin Kexin 9 (PCSK9) and nonHDL Particles Rise During Normal Pregnancy and Differ by BMI

BACKGROUND

Serum lipids, including total cholesterol (TC), triglycerides (TG), and low-density lipoprotein cholesterol (LDL-c), increase during pregnancy. Serum Proprotein Convertase Subtilisin Kexin 9 (PCSK9) is a vital regulator in lipoprotein metabolism. Circulating PCSK9 downregulates the LDL receptor on the surface of liver cells inhibiting clearance of LDL-c.

OBJECTIVE

To determine the influence of weeks of pregnancy and obesity on circulating levels of essential lipid lipoproteins and PCSK9 in women with normal, uncomplicated pregnancies and deliveries.

METHODS

We performed a comprehensive lipid and lipoprotein profile during each trimester of pregnancy in 70 mostly Caucasian women with uncomplicated normal pregnancies and deliveries. Based on their first trimester BMI, we placed them into one of three categories: (<25 kg/m² n=23, 25-30 kg/m² n=25, or >30 n=22) kg/m². Cholesterol, triglycerides, LDL cholesterol (LDL-c), non-HDL particles, and lipoprotein(a) were measured by spectrophotometry, ion mobility, and immunoturbidimetric assays. Elisa assay determined PCSK9 (active and total). Homeostatic Model Assessment (HOMA-IR) assessed insulin resistance in the second and third trimesters of pregnancy.

RESULTS

Total and active PCSK9, LDL-c, and nonHDL particle concentrations were higher than reported for non-pregnant normal values, increased after the first trimester of pregnancy, and were highest from mid-gestation to the last trimester of pregnancy in the overweight and the obese.

CONCLUSION

PCSK9 levels rise as normal pregnancy progresses. Levels are higher in persons who are obese, even after adjustment for insulin resistance. Defining normal PCSK9 levels during pregnancy must adjust for gestational age and BMI.

The potential for isotope dilution-LC-MS/MS to improve laboratory measurement of C-peptide: Reasons and critical determinants

Human C-peptide is secreted in equimolar amounts with insulin by pancreatic beta-cells. Measurement of C-peptide plays an important role in the diagnosis and treatment of diabetes where it is used to evaluate the function of islet cells. However, C-peptide measurement results across different laboratories vary considerably and there is an urgent need to improve comparability between laboratories. As it is sensitive and specific, isotope dilution-liquid chromatography-tandem mass spectrometry (ID-LC-MS/MS) has made a major contribution and will continue to play a significant role in the standardization of C-peptide measurement. Here, we reviewed the application of ID-LC-MS/MS in C-peptide measurement by discussing the biochemical properties of C-peptide, common sample preparation procedures, and the sensitivity problems often encountered with ID-LC-MS/MS C-peptide measurement. Collectively, these factors are crucial for the development of ID-LC-MS/MS methods for C-peptide measurement. We also discussed the advantages, disadvantages, and progress of implementing ID-LC-MS/MS as a routine measurement tool for C-peptide in clinical laboratories. Finally, we summarized the existing reference system and the status of C-peptide measurement in clinical laboratories to convey the necessity of improving the comparability of C-peptide measurement in clinical laboratories using ID-LC-MS/MS.

Development and Validation of a Novel LC-MS/MS Assay for C-Peptide in Human Serum

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Quantification of C-peptide without an antibody or multidimensional chromatography.

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High-throughput method with good comparability to reference measurement procedure.

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Proteolysis improves limit of detection over intact C-peptide.

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Glu-C is an important proteolytic enzyme for targeted proteomic workflows.

Introduction

 C-peptide is used as a marker of endogenous insulin secretion in the assessment of residual β-cell function in diabetes and in the diagnostic workup of hypoglycemia. Previously developed LC-MS/MS methods to quantify serum concentrations of C-peptide have monitored intact peptide, which ionizes poorly. As a result, methods have leveraged immunoaffinity enrichment or two-dimensional chromatography. In this study, we aimed to use proteolysis during sample preparation to enhance the sensitivity of traditional LC-MS/MS.

Methods

 Due to the absence of arginine and lysine residues in C-peptide, we utilized Glu-C as the proteolytic enzyme in the method. After protein precipitation using acetonitrile and solid phase extraction with mixed anion exchange, lower molecular weight polypeptides were reduced, alkylated, and proteolyzed. The two amino-terminal peptide fragments, EAEDLQVGQVE and LGGGPGAGSLQPLALE, were monitored using multiple reaction monitoring in positive ion mode (Acquity ULPC-Xevo TQ-S, Waters). The former peptide was used for quantification and the latter for quality assurance.

Results

 Glu-C was determined to be a reliable proteolytic enzyme with monotonic digestion kinetics. The assay was linear between 0.1 and 15 ng/mL and had a lower limit of quantification of 0.06 ng/mL. Total imprecision was 7.7 %CV and long-term imprecision at 0.16 ng/mL was 10.0%. Spike-recovery experiments demonstrated a mean recovery of 98.2 % (± 9.1 %) and the method compared favorably with a commercially available immunoassay and a reference measurement procedure.

Conclusion

 Protein precipitation with solid phase extraction and proteolysis with Glu-C is a robust sample preparation method for quantification of C-peptide in human serum by LC-MS/MS.

Intact Fasting Insulin Identifies Nonalcoholic Fatty Liver Disease in Patients Without Diabetes

CONTEXT

Patients with nonalcoholic fatty liver disease (NAFLD) are characterized by insulin resistance and hyperinsulinism. However, insulin resistance measurements have not been shown to be good diagnostic tools to predict NAFLD in prior studies.

OBJECTIVE

We aimed to assess a newly validated method to measure intact molecules of insulin by mass spectrometry to predict NAFLD.

METHODS

Patients underwent a 2-hour oral glucose tolerance test (OGTT), a liver magnetic resonance spectroscopy (1H-MRS), and a percutaneous liver biopsy if they had a diagnosis of NAFLD. Mass spectrometry was used to measure intact molecules of insulin and C-peptide.

RESULTS

A total of 180 patients were recruited (67% male; 52 ± 11 years of age; body mass index [BMI] 33.2 ± 5.7 kg/m2; 46% with diabetes and 65% with NAFLD). Intact fasting insulin was higher in patients with NAFLD, irrespective of diabetes status. Patients with NAFLD without diabetes showed ~4-fold increase in insulin secretion during the OGTT compared with all other subgroups (P = 0.008). Fasting intact insulin measurements predicted NAFLD in patients without diabetes (area under the receiver operating characteristic curve [AUC] of 0.90 [0.84-0.96]). This was significantly better than measuring insulin by radioimmunoassay (AUC 0.80 [0.71-0.89]; P = 0.007). Intact fasting insulin was better than other clinical variables (eg, aspartate transaminase, triglycerides, high-density lipoprotein, glucose, HbA1c, and BMI) to predict NAFLD. When combined with alanine transaminase (ALT) (intact insulin × ALT), it detected NAFLD with AUC 0.94 (0.89-0.99) and positive and negative predictive values of 93% and 88%, respectively. This newly described approach was significantly better than previously validated noninvasive scores such as NAFLD-LFS (P = 0.009), HSI (P < 0.001), and TyG index (P = 0.039).

CONCLUSION

In patients without diabetes, accurate measurement of fasting intact insulin levels by mass spectrometry constitutes an easy and noninvasive strategy to predict presence of NAFLD.

Peptidomics: A Review of Clinical Applications and Methodologies

Improvements in both liquid chromatography (LC) and mass spectrometry (MS) instrumentation have greatly enhanced proteomic and small molecule metabolomic analysis in recent years. Less focus has been on the improved capability to detect and quantify small bioactive peptides, even though the exact sequences of the peptide species produced can have important biological consequences. Endogenous bioactive peptide hormones, for example, are generated by the targeted and regulated cleavage of peptides from their prohormone sequence. This process may include organ specific variants, as proglucagon is converted to glucagon in the pancreas but glucagon-like peptide-1 (GLP-1) in the small intestine, with glucagon raising, whereas GLP-1, as an incretin, lowering blood glucose. Therefore, peptidomics workflows must preserve the structure of the processed peptide products to prevent the misidentification of ambiguous peptide species. The poor in vivo and in vitro stability of peptides in biological matrices is a major factor that needs to be considered when developing methods to study them. The bioinformatic analysis of peptidomics data sets requires the inclusion of specific post-translational modifications, which are critical for the function of many bioactive peptides. This review aims to discuss and contrast the various extraction, analytical, and bioinformatics approaches used for human peptidomics studies in a multitude of matrices.

Hyperinsulinemia and Its Pivotal Role in Aging, Obesity, Type 2 Diabetes, Cardiovascular Disease and Cancer

For many years, the dogma has been that insulin resistance precedes the development of hyperinsulinemia. However, recent data suggest a reverse order and place hyperinsulinemia mechanistically upstream of insulin resistance. Genetic background, consumption of the “modern” Western diet and over-nutrition may increase insulin secretion, decrease insulin pulses and/or reduce hepatic insulin clearance, thereby causing hyperinsulinemia. Hyperinsulinemia disturbs the balance of the insulin–GH–IGF axis and shifts the insulin : GH ratio towards insulin and away from GH. This insulin–GH shift promotes energy storage and lipid synthesis and hinders lipid breakdown, resulting in obesity due to higher fat accumulation and lower energy expenditure. Hyperinsulinemia is an important etiological factor in the development of metabolic syndrome, type 2 diabetes, cardiovascular disease, cancer and premature mortality. It has been further hypothesized that nutritionally driven insulin exposure controls the rate of mammalian aging. Interventions that normalize/reduce plasma insulin concentrations might play a key role in the prevention and treatment of age-related decline, obesity, type 2 diabetes, cardiovascular disease and cancer. Caloric restriction, increasing hepatic insulin clearance and maximizing insulin sensitivity are at present the three main strategies available for managing hyperinsulinemia. This may slow down age-related physiological decline and prevent age-related diseases. Drugs that reduce insulin (hyper) secretion, normalize pulsatile insulin secretion and/or increase hepatic insulin clearance may also have the potential to prevent or delay the progression of hyperinsulinemia-mediated diseases. Future research should focus on new strategies to minimize hyperinsulinemia at an early stage, aiming at successfully preventing and treating hyperinsulinemia-mediated diseases.

Increased C-Peptide Immunoreactivity in Insulin Autoimmune Syndrome (Hirata Disease) Due to High Molecular Weight Proinsulin

Background

Determination of C-peptide is important in the investigation of unexplained hyperinsulinemic hypoglycemia because a high C-peptide concentration usually indicates endogenous insulin hypersecretion. Insulin autoimmune syndrome (IAS) denotes hyperinsulinemic hypoglycemia due to insulin-binding antibodies that prolong insulin half-life. C-peptide clearance is considered to be unaffected, and although a marked C-peptide immunoreactivity in hypoglycemic samples has been reported, it has been suspected to be artifactual. High-resolution mass spectrometry enables examination of the basis of C-peptide-immunoreactivity in IAS.

Methods

Precipitation of plasma with polyethylene glycol was followed by C-peptide immunoassay. Plasma peptides extracted by solvent precipitation were characterized by nano-LC–MS/MS and analyzed using an untargeted data-dependent method. Peptides related to proinsulin, in amino acid sequence, were identified using proprietary bioinformatics software and confirmed by repeat LC–MS/MS analysis. Gel filtration chromatography coupled to LC–MS/MS was used to identify proinsulin-related peptides present in IAS immunocomplexes. Results were compared with those from C-peptide immunoassay.

Results

Polyethylene glycol precipitation of IAS plasma, but not control plasma, depleted C-peptide immunoreactivity consistent with immunoglobulin-bound C-peptide immunoreactivity. LC–MS/MS detected proinsulin and des 31,32 proinsulin at higher abundance in IAS plasma compared with control plasma. Analysis by gel filtration chromatography coupled to LC–MS/MS demonstrated proinsulin and des 31,32 proinsulin, but no C-peptide, in plasma immunocomplexes.

Conclusions

Antibody binding can enrich proinsulin and des 31,32 proinsulin in IAS immunocomplexes. Proinsulin cross-reactivity in some C-peptide immunoassays can lead to artifactually increased C-peptide results.

Measuring Insulin Resistance in Humans

BACKGROUND

Insulin resistance is a pathophysiological condition associated with diabetes and cardiometabolic diseases that is characterized by a diminished tissue response to insulin action. Our understanding of this complex phenomenon and its role in the pathogenesis of cardiometabolic diseases is rooted in the discovery of insulin, its isolation and purification, and the challenges encountered with its therapeutic use.

SUMMARY

In this historical perspective, we explore the evolution of the term "insulin resistance" and demonstrate how advances in insulin and glucose analytics contributed to the recognition and validation of this metabolic entity. We identify primary discoveries which were pivotal in expanding our knowledge of insulin resistance, the challenges in measurement and interpretation, contemporary techniques, and areas of future exploration. Key Message: Measurements of insulin resistance are important tools for defining and treating cardiometabolic diseases. Accurate quantification of this pathophysiological entity requires careful consideration of the assumptions and pitfalls of the methodological techniques and the historical and clinical context when interpreting and applying the results.

Development and validation of a method for quantification of human insulin and its synthetic analogues in plasma and post-mortem sera by LC-MS/HRMS

Analysis of human insulin and its synthetic analogues is increasingly requested for clinical monitoring, for anti-doping purposes, but also for forensic cases. Indeed, insulin analogues may be abused for suicide or homicide - whence their forensic interest. Collection and storage conditions, as well as the phenomenon of degradation make post-mortem serum samples analytically challenging and consequently, the rate of exogenous insulin administration as cause of death is undoubtedly underestimated. However, with recent technological advances and the development of new extraction techniques particularly for anti-doping analyses, detection of insulins in post-mortem samples seems to be achievable. This study describes the first validated quantitative method for analysis human insulin and its six analogues (lispro, aspart, glulisine, glargine, detemir and degludec) in plasma and post-mortem sera. Various extraction processes, namely precipitation + solid phase extraction (SPE), filtration + SPE, precipitation + SPE + immunopurification, and filtration + immunopurification, were assessed to evaluate the lowest limit of detection for all target analogues. The selected sample preparation consists of filtration step followed by immunopurification extraction with an anti-body precoated ELISA plate for plasma. For post-mortem sera, the first step of precipitation was added to remove matrix interferences. The extracts were analyzed by ultra-high-performance liquid chromatography-high resolution mass spectrometry (LC-HRMS), interfaced by electrospray (ESI). The method was validated with respect linearity, precision, accuracy, recovery, matrix effect, dilution and carryover. The limit of quantification (LOQ) in plasma was 0.5 ng/mL for human insulin and rapid-acting insulins, 1.0 ng/mL for glargine, 2.5 ng/mL for degludec and 10 ng/mL for detemir. Two types of post-mortem sera were studied based on the post-mortem interval (PMI): inferior or superior to 48 h. The obtained LOQ were the same for each analogue, independent from the PMI: 1.0 ng/mL for human insulin and rapid-acting insulins, 1.0 ng/mL for glargine, 2.5 ng/mL for degludec and 10 ng/mL for detemir. At the LOQ level, for all insulins and all samples, accuracy was between 70 and 130% and precision inferior to 30%. The validated method was applied to five subjects participating in therapeutic monitoring of insulin and to seven post-mortem cases.

Is insulin intoxication still the perfect crime? Analysis and interpretation of postmortem insulin: review and perspectives in forensic toxicology

Insulin is an anabolic hormone essential to glucose homeostasis. Insulin therapy, comprising human insulin (HI) or biosynthetic analogs, is critical for the management of type-1 diabetes and many of type-2 diabetes. However, medication error including non-adapted dose and confusion of insulin type, and misuse, such as massive self-administration or with criminal intent, can have lethal consequences. The aim of this paper is to review the state of knowledge of insulin analysis in biological samples and of the interpretation of insulin concentrations in the situation of insulin-related death investigations. Analytic aspects are considered, as quantification can be strongly impacted by methodology. Immunoanalysis, the historical technique, has a prominent role due to its sensitivity and ease of implementation. Recently, liquid chromatography coupled to mass spectrometry has provided indispensable selectivity in forensic contexts, distinguishing HI, analogs, and degradation products. We review the numerous antemortem (dose, associated pathology, injection-to-death interval, etc.) and postmortem parameters (in corpore degradation, in vitro degradation related to hemolysis, etc.) involved in the interpretation of insulin concentration. The interest and limitations of various alternative matrices providing a valuable complement to blood analysis are discussed. Vitreous humor is one of the most interesting, but the low diffusion of insulin in this matrix entails very low concentrations. Injection site analysis is relevant for identifying which type of insulin was administered. Muscle and renal cortex are matrices of particular interest, although additional studies are required. A table containing most case reports of fatal insulin poisoning published, with analytical data, completes this review. A logic diagram is proposed to highlight analytical issues and the main parameters to be considered for the interpretation of blood concentrations. Finally, it remains a challenge to provide reliable biological data and solid interpretation in the context of death related to insulin overdose. However, the progress of analytical tools is making the "perfect crime" ever more difficult to commit.

At-line high throughput site-specific glycan profiling using targeted mass spectrometry

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High throughput, site-specific glycan profiling using targeted mass spectrometry.

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Rapid analysis of glycan profiles directly from culture media.

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Methodology is fully compatible with automation.

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Methodology can be integrated into cell line selection and process development.

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Strategy can be used for multi-attribute product quality screening/monitoring.

Protein post-translational modification (PTM) plays an important role in many biological processes; of which glycosylation is arguably one of the most complex and diverse modifications and is crucial for the safety and efficacy of biotherapeutic proteins.

Mass spectrometric characterization of protein glycosylation is well established with clear advantages and disadvantages; on one hand it is precise and information-rich, as well as being relative inexpensive in terms of the reagents and consumables despite the instrumentation cost and, depending on the method, can give site specific information; on the other hand it generally suffers from low throughput, restriction to largely purified samples and is less quantitative, especially for sialylated glycan species.

Here, we describe a high throughput, site-specific, targeted mass spectrometric peptide mapping approach to quickly screen/rank candidate production cell lines and culture conditions that give favourable glycosylation profiles directly from conditioned culture media for an Fc-fusion protein. The methodology is fully compatible with automation and combines the speed of ‘top-down’ mass spectrometry with the site-specific information of ‘bottom-up’ mass spectrometry. In addition, this strategy can be used for multi-attribute product quality screening/monitoring as an integral part of cell line selection and process development.

Protein Biomarker Quantification by Immunoaffinity Liquid Chromatography–Tandem Mass Spectrometry: Current State and Future Vision

Immunoaffinity–mass spectrometry (IA-MS) is an emerging analytical genre with several advantages for profiling and determination of protein biomarkers. Because IA-MS combines affinity capture, analogous to ligand binding assays (LBAs), with mass spectrometry (MS) detection, this platform is often described using the term hybrid methods. The purpose of this report is to provide an overview of the principles of IA-MS and to demonstrate, through application, the unique power and potential of this technology. By combining target immunoaffinity enrichment with the use of stable isotope-labeled internal standards and MS detection, IA-MS achieves high sensitivity while providing unparalleled specificity for the quantification of protein biomarkers in fluids and tissues. In recent years, significant uptake of IA-MS has occurred in the pharmaceutical industry, particularly in the early stages of clinical development, enabling biomarker measurement previously considered unattainable. By comparison, IA-MS adoption by CLIA laboratories has occurred more slowly. Current barriers to IA-MS use and opportunities for expanded adoption are discussed. The path forward involves identifying applications for which IA-MS is the best option compared with LBA or MS technologies alone. IA-MS will continue to benefit from advances in reagent generation, more sensitive and higher throughput MS technologies, and continued growth in use by the broader analytical community. Collectively, the pursuit of these opportunities will secure expanded long-term use of IA-MS for clinical applications.

Recent advances in the determination of insulins from biological fluids

The qualitative and quantitative determination of insulin and its related substances (e. g., C-peptide) is of great importance in many different areas of analytical chemistry. In particular, due to the steadily increasing prevalence of metabolic disorders such as diabetes mellitus, an adequate control of the circulating amount of insulin is desirable. In addition, also in forensics and doping control analysis, the determination of insulin in blood, urine or other biological matrices plays a major role. However, in order to establish general reference values for insulin and C-peptide for diabetology, the comparability of measured concentrations is indispensable. This has not yet been fully implemented, although enormous progress has been made in recent years, and the search for a "gold standard" method is still ongoing. In addition to established ligand-binding assays, an increasing number of mass-spectrometric methods have been developed and employed as the to-date available systems (for example, high-resolution/high accuracy mass spectrometers) provide the sensitivity required to determine analyte concentrations in the sub-ng/mL (sub-100pmol/L) level. Meanwhile, also high-throughput measurements have been realized to meet the requirement of testing a high number of samples in a short period of time. Further developments aim at enabling the online measurement of insulin in the blood with the help of an insulin sensor and, in the following, in addition to a brief review, today's state of the art testing developments are summarized.

Targeting of lipid metabolism with a metabolic inhibitor cocktail eradicates peritoneal metastases in ovarian cancer cells

Ovarian cancer is an intra-abdominal tumor in which the presence of ascites facilitates metastatic dissemination, and associated with poor prognosis. However, the significance of metabolic alterations in ovarian cancer cells in the ascites microenvironment remains unclear. Here we show ovarian cancer cells exhibited increased aggressiveness in ascites microenvironment via reprogramming of lipid metabolism. High lipid metabolic activities are found in ovarian cancer cells when cultured in the ascites microenvironment, indicating a metabolic shift from aerobic glycolysis to β-oxidation and lipogenesis. The reduced AMP-activated protein kinase (AMPK) activity due to the feedback effect of high energy production led to the activation of its downstream signaling, which in turn, enhanced the cancer growth. The combined treatment of low toxic AMPK activators, the transforming growth factor beta-activated kinase 1 (TAK1) and fatty acid synthase (FASN) inhibitors synergistically impair oncogenic augmentation of ovarian cancer. Collectively, targeting lipid metabolism signaling axis impede ovarian cancer peritoneal metastases.

Validation of a Fully Automated Immunoaffinity Workflow for the Detection and Quantification of Insulin Analogs by LC–MS-MS in Postmortem Vitreous Humor

The analysis of biological specimens collected at autopsy for the presence of exogenous insulin(s) is of special interest in select death investigations as they may be suspected in the cause of a death. Technical challenges include the limited stability of insulin, and the forensic requirement of differentiating endogenous insulin from pharmaceutical analogs. A novel method was developed for the detection and quantification of human insulin, Glulisine, Lispro, Aspart, Glargine and Detemir in vitreous fluid. An immunoaffinity extraction procedure is performed followed by separation of the insulin α- and β-chains. Liquid chromatography tandem mass spectrometry analysis of the β-chain allows for the unequivocal identification of each insulin analog. The analytical measurement range for each insulin was 0.5–25 ng/mL. The method was evaluated for accuracy, precision, carryover, interferences and stability. Eight vitreous fluid samples collected from cases where untoward insulin use was suspected were subjected to analysis. Positive results were obtained from three samples, and a detailed case history is provided for one of these cases. Even though insulin instability in postmortem biological fluid remains a challenge, this method allows for a reliable forensic-level analysis in vitreous fluid.

Development and Validation of Apolipoprotein AI-Associated Lipoprotein Proteome Panel for the Prediction of Cholesterol Efflux Capacity and Coronary Artery Disease

BACKGROUND

Cholesterol efflux capacity (CEC) is a measure of HDL function that, in cell-based studies, has demonstrated an inverse association with cardiovascular disease. The cell-based measure of CEC is complex and low-throughput. We hypothesized that assessment of the lipoprotein proteome would allow for precise, high-throughput CEC prediction.

METHODS

After isolating lipoprotein particles from serum, we used LC-MS/MS to quantify 21 lipoprotein-associated proteins. A bioinformatic pipeline was used to identify proteins with univariate correlation to cell-based CEC measurements and generate a multivariate algorithm for CEC prediction (pCE). Using logistic regression, protein coefficients in the pCE model were reweighted to yield a new algorithm predicting coronary artery disease (pCAD).

RESULTS

Discovery using targeted LC-MS/MS analysis of 105 training and test samples yielded a pCE model comprising 5 proteins (Spearman r = 0.86). Evaluation of pCE in a case–control study of 231 specimens from healthy individuals and patients with coronary artery disease revealed lower pCE in cases (P = 0.03). Derived within this same study, the pCAD model significantly improved classification (P &lt; 0.0001). Following analytical validation of the multiplexed proteomic method, we conducted a case–control study of myocardial infarction in 137 postmenopausal women that confirmed significant separation of specimen cohorts in both the pCE (P = 0.015) and pCAD (P = 0.001) models.

CONCLUSIONS

Development of a proteomic pCE provides a reproducible high-throughput alternative to traditional cell-based CEC assays. The pCAD model improves stratification of case and control cohorts and, with further studies to establish clinical validity, presents a new opportunity for the assessment of cardiovascular health.

Towards Point-of-Care Insulin Detection

Good glucose management through an insulin dose regime based on the metabolism of glucose helps millions of people worldwide manage their diabetes. Since Banting and Best extracted insulin, glucose management has improved due to the introduction of insulin analogues that act from 30 minutes to 28 days, improved insulin dose regimes, and portable glucose meters, with a current focus on alternative sampling sites that are less invasive. However, a piece of the puzzle is still missing-the ability to measure insulin directly in a Point-of-Care device. The ability to measure both glucose and insulin concurrently will enable better glucose control by providing an improved estimate for insulin sensitivity, minimizing variability in control, and maximizing safety from hypoglycaemia. However, direct detection of free insulin has provided a challenge due to the size of the molecule, the low concentration of insulin in blood, and the selectivity against interferants in blood. This review summarizes current insulin detection methods from immunoassays to analytical chemistry, and sensors. We also discuss the challenges and potential of each of the methods towards Point-of-Care insulin detection.

Insulin: a review of analytical methods

Insulin is an important polypeptide hormone that regulates carbohydrate metabolism.

Feasibility of a plasma bioassay to assess oxidative protection of low-density lipoproteins by high-density lipoproteins

BACKGROUND

Traditionally, the impact of lipoproteins on vascular disease has been evaluated in light of their quantity, that is, cholesterol content, in plasma. However, recent studies of high-density lipoproteins (HDLs) have focused on functionality with regard to atheroprotection. For example, bioassays have emerged to assess the ability of HDL, in its near native plasma environment, to promote cholesterol removal (efflux) from cells. As a result, attention has focused on developing plasma-based assays for other putative HDL protective functions including protecting low-density lipoproteins (LDLs) from oxidative damage.

OBJECTIVE

To determine the feasibility of such an assay in a complex sample such as plasma, we evaluated the contribution of HDL vs other plasma factors in preventing LDL oxidation.

METHODS

We separated normolipidemic human plasma by gel filtration chromatography and assessed each fraction for its ability to prevent LDL modification by water soluble radical and copper-initiated oxidation mechanisms.

RESULTS

Using proteomics and selective precipitation methods, we identified major antioxidative contributions for fibrinogen, immunoglobulin G, albumin, and small soluble molecules like uric acid and ascorbate, with albumin being especially dominant in copper-initiated mechanisms. HDL particles were minor contributors (∼1%-2%) to the antioxidant capacity of plasma, irrespective of oxidation mechanism.

CONCLUSIONS

Given the overwhelming background of antioxidant capacity inherent to highly abundant plasma proteins, specific bioassays of HDL antioxidative function will likely require its complete separation from plasma.

Insulin Resistance Probability Scores for Apparently Healthy Individuals

Context

Insulin resistance (IR) can progress to type 2 diabetes. Therefore, timely identification of IR could facilitate disease prevention efforts. However, direct measurement of IR is not feasible in a clinical setting.

Objective

Develop a clinically practical probability score to assess IR in apparently healthy individuals based on levels of insulin, C-peptide, and other risk factors.

Design

Cross-sectional study.

Participants

Apparently healthy individuals who volunteered to participate in studies of IR.

Main Outcome Measure

IR, defined as the top tertile of steady-state plasma glucose during an insulin-suppression test.

Results

In a study of 535 participants, insulin, C-peptide, creatinine, body mass index (BMI), and triglycerides to high-density lipoprotein cholesterol ratio (TG/HDL-C) were independently associated with IR (all P < 0.05) in a model that included age, sex, ethnicity, BMI, blood pressure, insulin, C-peptide, fasting glucose, low-density lipoprotein cholesterol, TG/HDL-C, alanine aminotransferase, and creatinine. For an IR probability score based on a model that included insulin, C-peptide, creatinine, TG/HDL-C, and BMI, the odds ratio was 26.7 (95% CI 14.0 to 50.8) for those with scores >66% compared with those with scores <33%. When only insulin and C-peptide were included in the model, the odds ratio was 15.6 (95% CI 7.5 to 32.4) for those with scores >66% compared with those with scores <33%.

Conclusions

An IR probability score based on insulin, C-peptide, creatinine, TG/HDL-C, and BMI or a score based on only insulin and C-peptide may help assess IR in apparently healthy individuals.

Considerations regarding the validation of chromatographic mass spectrometric methods for the quantification of endogenous substances in forensics

The requirement for correct evaluation of forensic toxicological results in daily routine work and scientific studies is reliable analytical data based on validated methods. Validation of a method gives the analyst tools to estimate the efficacy and reliability of the analytical method. Without validation, data might be contested in court and lead to unjustified legal consequences for a defendant. Therefore, new analytical methods to be used in forensic toxicology require careful method development and validation of the final method. Until now, there are no publications on the validation of chromatographic mass spectrometric methods for the detection of endogenous substances although endogenous analytes can be important in Forensic Toxicology (alcohol consumption marker, congener alcohols, gamma hydroxy butyric acid, human insulin and C-peptide, creatinine, postmortal clinical parameters). For these analytes, conventional validation instructions cannot be followed completely. In this paper, important practical considerations in analytical method validation for endogenous substances will be discussed which may be used as guidance for scientists wishing to develop and validate analytical methods for analytes produced naturally in the human body. Especially the validation parameters calibration model, analytical limits, accuracy (bias and precision) and matrix effects and recovery have to be approached differently. Highest attention should be paid to selectivity experiments.