Insulin Resistance Probability Scores for Apparently Healthy Individuals

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.

Prognostic value of insulin resistance and hyperglycemia biomarkers for long-term risks of cardiometabolic outcomes

We found that individuals in the top tertile of HOMA-IR and with HbA1c-defined prediabetes have elevated risk of cardiometabolic outcomes.

The relationship between insulin resistance and ion mobility lipoprotein fractions

Objective

Insulin resistance (IR) increases risk of type 2 diabetes and atherosclerotic cardiovascular disease and is associated with lipid and lipoprotein abnormalities including high triglycerides (TG) and low high-density lipoprotein cholesterol (HDL-C). Lipoprotein size and lipoprotein subfractions (LS) have also been used to assist in identifying persons with IR. Associations of LS and IR have not been validated using both direct measures of IR and direct measures of LS. We assessed the usefulness of fasting lipoprotein subfractions (LS) by ion mobility to identify individuals with IR.

Methods

Lipid panel, LS by ion mobility (LS-IM), and IR by steady-state plasma glucose (SSPG) concentration were assessed in 526 adult volunteers without diabetes. IR was defined as being in the highest tertile of SSPG concentration. LS-IM score was calculated by linear combination of regression coefficients from a stepwise regression analysis with SSPG concentration as the dependent variable. Improvement in prediction of IR was evaluated after combining LS-IM score with TG/HDL-C, TG/HDL-C and BMI as well as with TG/HDL-C, BMI, sex, race and ethnicity. IR prediction was evaluated by area under the receiver operating characteristic curve (AUC) and positive predictive value (PPV) considering the highest 5% of scores as positive test.

Results

Prediction of IR was similar by LS-IM score and TG/HDL-C (AUC=0.68; PPV=0.59 and AUC=0.70; PPV=0.59, respectively) and prediction was improved when LS-IM was combined with TG/HDL-C (AUC=0.73; PPV=0.70), TG/HDL-C and BMI (AUC=0.82; PPV=0.81) and with TG/HDL-C, BMI, sex, race and ethnicity (AUC=0.84; PPV=0.89).

Conclusion

For identifying individuals with IR, LS-IM score and TG/HDL-C are comparable and their combination further improves IR prediction by TG/HDL-C alone. Among patients who have undergone IM testing, the LS-IM score may assist prioritization of subjects for further evaluation and interventions to reduce IR.

Lipoprotein Insulin Resistance Index: A Simple, Accurate Method for Assessing Insulin Resistance in South Asians

Context

Identification of insulin resistance (IR) in South Asians, who are at a higher risk for type 2 diabetes, is important. Lack of standardization of insulin assays limits the clinical use of insulin-based surrogate indices. The lipoprotein insulin resistance index (LP-IR), a metabolomic marker, reflects the lipoprotein abnormalities observed in IR. The reliability of the LP-IR index in South Asians is unknown.

Objective

We evaluated the predictive accuracy of LP-IR compared with other IR surrogate indices in South Asians.

Methods

In a cross-sectional study (n = 55), we used calibration model analysis to assess the ability of the LP-IR score and other simple surrogate indices (Homeostatic Model Assessment of Insulin Resistance, Quantitative insulin sensitivity check index, Adipose insulin resistance index, and Matsuda Index) to predict insulin sensitivity (S_I) derived from the reference frequently sampled intravenous glucose tolerance test. LP-IR index was derived from lipoprotein particle concentrations and sizes measured by nuclear magnetic resonance spectroscopy. Predictive accuracy was determined by root mean squared error (RMSE) of prediction and leave-one-out cross-validation type RMSE of prediction (CVPE). The optimal cut-off of the LP-IR index was determined by the area under the receiver operating characteristic curve (AUROC) and the Youden index.

Results

The simple surrogate indices showed moderate correlations with S_I (r = 0.53-0.69, P < .0001). CVPE and RMSE were not different in any of the surrogate indices when compared with LP-IR. The AUROC was 0.77 (95% CI 0.64-0.89). The optimal cut-off for IR in South Asians was LP-IR >48 (sensitivity: 75%, specificity: 70%).

Conclusion

The LP-IR index is a simple, accurate, and clinically useful test to assess IR in South Asians.

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.

Complete nutrition drink with retrograded starch is low glycemic, and the individual glucose response to the low glycemic complete nutrition drink depends on fasting insulin levels and HOMA-IR in a randomized cross-over control trial

Complete nutrition drinks with a low glycemic index (GI) provide nutritional support and prevent hyperglycaemia. The present study identified GI and factors predicting individual glucose response to a new complete nutrition drink. A randomised cross-over controlled trial was conducted in eighteen healthy volunteers (FPG < 100 mg/dl). Complete nutrition drinks containing retrograded starch, glucose solution and white bread were assigned in a random sequence with 14-day wash-out intervals. Plasma glucose and insulin levels were measured from baseline to 180 min after consuming each food. Results show the adjusted GIs of the drink was 48.2 ± 10.4 and 46.7 ± 12.7 with glucose and white bread as the reference, respectively. While the drink has low GI (<55), the individual glucose responses varied (GI: 7–149). Comparing characters in individual GI < 55 (n = 12) and GI ≥ 55 (n = 6) groups revealed significantly higher baseline insulin in the low GI group (14.86 ± 16.51 μIU/ml v. 4.9 ± 3.4 μIU/ml, P < 0·05). The correlation matrix confirms only two predictive factors for having individual GI <55 were baseline insulin (r = 0·5, P = 0·03) and HOMA-IR (r = 0·55, P = 0·02). ROC curve reveals fasting insulin above 1.6 μIU/ml and HOMA-IR above 1.05 as the cut-off values. The findings suggest that the complete nutrition drink has a low GI, but there was wide variability in individual responses partly explained by fasting insulin levels and HOMA-IR. Screening for fasting insulin and HOMA-IR may be encouraged to maximise the functional benefit of the drink.

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.

Prevalence of obesity and disturbances in glucose homeostasis in HIV-infected subjects and general population - missed diagnoses of diabetes?

Objectives

Comparative data on glucose disorders using fasting blood samples between people living with HIV (PLWH) and the general population are lacking. The objective of this study was to compare the prevalence and risk factors of obesity and disturbances in glucose homeostasis between PLWH treated with modern antiretroviral therapy and the general population.

Methods

Adjusted prevalence of obesity, features of insulin resistance (triglyceride:high‐density lipoprotein cholesterol ratio and alanine aminotransferase), impaired fasting glucose (IFG), diabetes mellitus (DM) and combined dysglycaemia (presence of IFG or DM) were determined using fasting blood samples among 1041 PLWH and 7047 subjects representing the general population.

Results

People living with HIV had a lower prevalence of obesity [18.2%, 95% confidence interval (CI): 15.1–21.2 vs. 23.9%, 95% CI: 22.4–25.4], but a higher prevalence of insulin resistance and IFG (20.0%, 95% CI: 16.6–23.4 vs. 9.8%, 95% CI: 8.7–10.8) than the general population. Fasting glucose concentration was higher, but glycated haemoglobin (HbA1c) was lower, among PLWH. Prevalence of dysglycaemia for a given body mass index (BMI) was higher in PLWH than in the general population. The prevalence of DM did not differ between PLWH (13.2%, 95% CI: 10.2–15.9) and the general population (14.5%, 95% CI: 13.6–15.4).

Conclusions

The prevalence of obesity was lower, but the risk of dysglycaemia for a given BMI was significantly higher, among PLWH, highlighting the importance of prevention and treatment of obesity among HIV‐infected subjects. Regardless of the increased prevalence of insulin resistance and IFG, DM was surprisingly not more common among PLWH, raising concern about the under‐diagnosis of DM, possibly due to low sensitivity of HbA1c in this patient population.

A Simple and Improved Predictor of Insulin Resistance Extracted From the Oral Glucose Tolerance Test: The I0*G60

OBJECTIVE

To evaluate the diagnostic performance of several biochemical predictors of insulin resistance (IR).

DESIGN

A total of 90 nondiabetic subjects were tested with both the pancreatic suppression test (PST) and the oral glucose tolerance test (OGTT). Of them, 53 were non-insulin-resistant (NIR) subjects and the remaining 37 were insulin resistant subjects.

RESULTS

All glucose and insulin values from the OGTT were positively correlated with the steady-state plasma glucose (SSPG) value of the PST. Among the OGTT values, basal insulin (I0) displayed a stronger correlation with SSPG (r = 0.604). Receiver operating characteristic analysis of the OGTT data demonstrated that I0 exhibited the highest area under the receiver operating characteristic curve (AUROC), compared with the rest of the OGTT data. However, the reduced sensitivity of this predictor precluded its clinical use.We then tested six potential predictors of IR derived from the OGTT values. Of them, the I0*G60 had a correlation coefficient of 0.697 with the SSPG and an AUROC of 0.867, surpassing the respective values of the traditional biochemical predictors of IR. Its cutoff predicting IR was >1110 mg/dL*μΙU/mL (>428 nM*pM), its sensitivity was 0.865, and its global accuracy was 0.822. We then selected the six best biochemical predictors of IR according to their posttest probability ratio. The order was as follows: I0*G60, ISI composite, AUC-Gl*In/', quantitative insulin sensitivity check index, homeostatic model assessment 1 (HOMA1), and HOMA2.

CONCLUSION

We conclude that the I0*G60 is a promising, inexpensive, and easily calculable predictor of IR that outperforms the predictive power of the traditional predictors of IR, including the insulin sensitivity index composite.