Antilipolytic Insulin Sensitivity Indices Measured during an Oral Glucose Challenge: Associations with Insulin-Glucose Clamp and Central Adiposity in Women without Diabetes

Foued Naimi; Christophe Richer dit Laflèche; Marie-Claude Battista; André C. Carpentier; Jean-Patrice Baillargeon

doi:10.3803/EnM.2024.2129

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Original Article Antilipolytic Insulin Sensitivity Indices Measured during an Oral Glucose Challenge: Associations with Insulin-Glucose Clamp and Central Adiposity in Women without Diabetes: Foued Naimi¹, Christophe Richer dit Laflèche¹, Marie-Claude Battista¹, André C. Carpentier^1,2, Jean-Patrice Baillargeon^1,2; DOI: https://doi.org/10.3803/EnM.2024.2129
Published online: March 18, 2025

¹Division of Endocrinology, Department of Medicine, University of Sherbrooke (Université de Sherbrooke), Sherbrooke, QC, Canada

²Research Centre of the Sherbrooke University Hospital Centre (Centre de recherche du Centre hospitalier universitaire de Sherbrooke), Sherbrooke, QC, Canada

Corresponding author: Jean-Patrice Baillargeon Division of Endocrinology, University of Sherbrooke (Université de Sherbrooke), 3001, 12th Ave North, Sherbrooke, Quebec J1H 5N4, Canada Tel: +1-819-564-5241, Fax: +1-819-564-5292, E-mail: JP.Baillargeon@USherbrooke.ca

• Received: August 3, 2024 • Revised: October 28, 2024 • Accepted: January 21, 2025

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
Article information
References

ABSTRACT

Background
Tissue overexposure to non-esterified fatty acids (NEFA) contributes to the development of metabolic conditions, with insulin-mediated suppression of lipolysis being an important mechanism in limiting this overexposure. We investigated which dynamic NEFA insulin-suppression indices derived from the oral glucose tolerance test (OGTT) were best associated with those derived from the insulin-glucose clamp, as well as with central adiposity and glucoregulatory parameters.
Methods
This cross-sectional study recruited 29 women without diabetes, 15 healthy women, and 14 women with polycystic ovary syndrome. The OGTT indices of NEFA insulin-suppression were the decremental NEFA area under the curve, negative log-linear NEFA slope, percentage of NEFA suppression (%NEFA_supp) and time to suppress NEFA levels by 50% (T50_NEFA). The indices derived from the two-step euglycemic-hyperinsulinemic clamp (low-dose insulin step) were delta NEFA and %NEFA_supp.
Results
Among the OGTT and clamp indices, T50_NEFA[OGTT] and %NEFA_supp[clamp] showed the closest associations in both subgroups (r=–0.58). Additionally, T50_NEFA correlated significantly in all women with waist circumference (r=0.64), body fat percentage (r=0.60), fasting insulinemia (r=0.53), and M-value insulin sensitivity index (r=–0.45). Similarly, %NEFA_supp[clamp] correlated significantly in all women with waist circumference (r=–0.57), body fat percentage (r=–0.54), fasting insulinemia (r=–0.55), and M-value insulin sensitivity index (r=0.51). T50_NEFA and %NEFA_supp[clamp] also correlated with other anthropometric and metabolic parameters associated with lipotoxicity.
Conclusion
For dynamic testing of NEFA insulin-suppression in women, T50_NEFA was the OGTT-derived index best correlated with a clamp index (%NEFA_supp). These indices were also the most closely associated with anthropometric and glucoregulatory parameters. Thus, the OGTT-derived T50_NEFA appears valid for assessing dynamic antilipolytic insulin action.
Keywords: Lipolysis; Fatty acids, nonesterified; Adipose tissue; Lipotoxicity; Insulin resistance; Endocrinology and metabolism

INTRODUCTION

Insulin resistance (IR) is a metabolic condition that can lead to the development of type 2 diabetes (T2D) and cardiovascular complications [1]. A key mechanism underlying IR and beta-cell dysfunction is lipotoxicity, which results from excessive exposure of non-adipose tissues to non-esterified fatty acids (NEFA) [2]. Postprandial increases in insulin levels suppress circulating NEFA concentrations [3], primarily by inhibiting adipose tissue lipolysis [4,5]. Conversely, during fasting, low basal insulin levels reduce this inhibition, leading to elevated circulating NEFA [6-8]. Accordingly, antilipolytic IR contributes to persistently high NEFA levels in both fasting and fed states, playing a significant role in the development of lipotoxicity [9]. This suggests that women with pronounced antilipolytic IR may respond particularly well to insulin sensitizers or lipotoxicity-targeting therapies, such as peroxisome proliferator-activated receptor γ agonists. Therefore, insulin-mediated suppression of NEFA levels is a critical parameter for assessing an individual’s risk of developing non-adipose tissue lipotoxicity, which can lead to cardiometabolic complications such as T2D.

The gold standard for dynamically assessing peripheral tissue IR in glucose regulation is the euglycemic-hyperinsulinemic clamp. This method measures the glucose disposal rate during high-dose insulin infusion (40 mU/m²/min) [10]. Some researchers have evaluated the antilipolytic action of insulin using a 3-step euglycemic-hyperinsulinemic clamp, incorporating two low-dose insulin steps (4 and 8 mU/m²/min). These low doses do not fully suppress NEFA levels, allowing for the quantification of adipose tissue insulin sensitivity by measuring the insulin concentration required to suppress half of the glycerol rate of appearance (using glycerol or palmitate radiotracers) [11-13]. While straightforward to interpret, this technique is time-consuming, costly, and impractical for large-scale studies.

Antilipolytic insulin sensitivity has also been estimated using fasting blood samples to measure insulin and NEFA levels, such as with the adipose tissue insulin resistance (Adipo-IR) index. Adipo-IR is simple to calculate and has been validated against the 3-step hyperinsulinemic clamp following 3 days of a standardized diet [13]. However, unlike dynamic test-derived indices, Adipo-IR is an indirect measure of insulin-dependent NEFA suppression, making it suboptimal for mechanistic studies, as previously noted [13].

In contrast, the oral glucose tolerance test (OGTT) is a widely used, straightforward method for assessing glucose tolerance following a 75-g glucose load. This dynamic test has also been employed to estimate insulin-mediated glucose disappearance through various integrative indices [14,15], which correlate well with the gold-standard clamp technique [16]. Given its simplicity and widespread use in large cohorts [17], the OGTT has recently been proposed as a method to estimate the antilipolytic action of insulin using surrogate indices [18-21]. However, no consensus exists on a gold-standard OGTT-derived index specifically for measuring insulin sensitivity in lipolysis. Additionally, while mathematical modeling of NEFA kinetics during the OGTT shows promise [22,23], these methods are complex and require advanced expertise in mathematical modeling for accurate interpretation.

The primary objective of this study was to determine whether dynamic NEFA insulin-suppression indices derived from the OGTT correlate with those obtained from the euglycemic-hyperinsulinemic clamp. The secondary objective was to evaluate the association of these dynamic indices with markers of adiposity, central obesity, IR, and glucose tolerance, all of which are linked to lipotoxicity [24], to assess their convergent validity.

The present study is a secondary analysis of baseline data from an incomplete clinical trial (ClinicalTrials.gov NCT01019356).
Participants: To evaluate the performance of insulin-mediated NEFA suppression indices in a population with significant variability in insulin sensitivity, a subgroup of women with polycystic ovary syndrome (PCOS) was recruited. Women with PCOS are known to exhibit greater IR compared to women without PCOS, even when matched for obesity levels [25]. This approach was chosen to ensure a wide range of insulin sensitivity within the sample. Recruitment was facilitated by Dr. Baillargeon, the principal investigator, who specializes in reproductive endocrinology and oversees a PCOS clinic. A convenience sample of healthy women and women with PCOS was recruited between January 2007 and September 2011 at the Centre de recherche du Centre hospitalier universitaire de Sherbrooke (CRCHUS). Healthy volunteers were recruited through advertisements or personal contacts, while women with PCOS were recruited from the CHUS Reproductive Endocrinology Clinic under Dr. Baillargeon’s direction. Eligible participants were women aged 18 to 40 years with a body mass index (BMI) between 18 and 40 kg/m² who were not taking medications known to affect glucose or NEFA metabolism, including oral contraceptives, for at least 3 months prior to screening. Women with diabetes, as determined by an OGTT (fasting glucose ≥7.0 mmol/L or 2-hour glucose ≥11.1 mmol/L), or those who were pregnant were excluded [26]. PCOS diagnosis was based on the Androgen Excess & PCOS diagnostic criteria, which include clinical assessment of hyperandrogenism (hirsutism, acne, or alopecia) and oligo- or anovulation by a specialized reproductive endocrinologist. Other androgen-excess disorders were ruled out based on total testosterone ≤5 nmol/L, 17-hydroxyprogesterone <6 nmol/L in the follicular phase, and dehydroepiandrosterone sulfate ≤19 µmol/L, along with normal levels of thyroid-stimulating hormone, prolactin, and follicle-stimulating hormone (if amenorrheic) [27]. Most participants did not undergo transvaginal ovarian ultrasound. The study was approved by the CHUS Human Research Ethics Committee (#2007-69, 06-075), and written informed consent was obtained from all participants in accordance with the Declaration of Helsinki.
Oral glucose tolerance test and euglycemic-hyperinsulinemic clamp: Participants were instructed to fast for 12 hours and avoid strenuous exercise, alcohol consumption, or smoking more than five cigarettes per day for 48 hours prior to each experimental visit. Both tests were conducted during the early follicular phase of the menstrual cycle (days 2 to 5). For the OGTT, blood samples were collected at 10-minute intervals from –20 to 0 minutes (baseline) and from 0 to 120 minutes after a 75-g glucose load. For the two-step euglycemic-hyperinsulinemic clamp, plasma NEFA and insulin levels were measured at 30, 20, 10, and 0 minutes for baseline. At time 0, a prime-continuous infusion of human regular insulin (Novolin, Novo Nordisk Pharmaceuticals, Princeton, NJ, USA) was initiated at a low-dose of 10 mU/m²/min body surface area and continued for 120 minutes to measure insulin-mediated NEFA suppression. At 120 minutes, the insulin infusion rate was increased to 40 mU/m²/min and maintained for an additional 2 hours to measure insulin-mediated glucose disappearance (M-value). Arterialized blood samples were collected every 5 minutes throughout the clamp to assess plasma glucose levels using the glucose oxidase method (Beckman Coulter Glucose Analyzer II, Mississauga, ON, Canada). Plasma glucose was maintained at 5.0±0.5 mmol/L by adjusting the infusion rate of a 20% dextrose solution.
Biochemical assays: Blood samples were promptly centrifuged and stored at –80°C for subsequent analysis. Plasma glucose concentrations were measured using the glucose hexokinase technique (Raichem). Human insulin levels were determined by radioimmunoassay (RIA Kit; Millipore Human Insulin assay). NEFA levels were measured in a single run using a colorimetric assay (FUJIFILM Wako NEFA assay kit) following the manufacturer’s instructions. The assay has a lower detection limit of 0.0014 mmol/L, which was applied for readings below this threshold, and an inter-assay coefficient of variation of less than 5%. Although the manufacturer notes slight interference from bilirubin, this was not expected to significantly affect the results.
Calculations: The area under the curve (AUC) was calculated using the trapezoidal method. OGTT-derived glucose insulin sensitivity was estimated by calculating the Matsuda insulin sensitivity index [ISI Matsuda=10,000/(square root [fasting glucose (mg⁄dL)×fasting insulin (µU⁄mL)×mean glucose (mg⁄dL)×mean insulin (µU⁄mL)])] [17]. To estimate the sensitivity to insulin-mediated NEFA suppression during OGTT, the following indices were calculated: decremental NEFA AUC [dAUC_NEFA =(basal mean NEFA×120 min)–total post-OGTT NEFA AUC], negative slope of the log-linear of NEFA curve (SlopeLn_NEFA), the percentage of NEFA suppression [%NEFA_supp=([mean baseline levels-nadir levels]/mean baseline levels)] and time to suppress NEFA levels by 50% (T50_NEFA). Higher anti-lipolytic insulin sensitivity results in more pronounced NEFA suppression and thus, higher values for dAUC_NEFA, SlopeLn_NEFA (steeper slope), and %NEFA_supp; but a shorter T50_NEFA.; Insulin-mediated glucose utilization during the clamp (M-value) was calculated as the mean glucose infusion rate (µmol/min) during the last 20 minutes of the high-dose insulin clamp (steady-state) corrected for the participants’ lean mass (µmol/kg/min). Indices of insulin-induced NEFA suppression calculated from the low-insulin step of the clamp were: delta NEFA [∆NEFA=(mean NEFA levels; from 100–120 min)–(mean NEFA levels; from baseline)] and %NEFA_supp=[∆NEFA/mean baseline NEFA].; The Adipo-IR index was calculated by obtaining the product of baseline fasting plasma levels of NEFA and insulin [28]. Similarly, the homeostatic model for assessment of insulin resistance (HOMA-IR; fasting insulin levels×fasting glycemia/22.5 [28]) index was calculated to measure fasting glucose insulin sensitivity, and the revised version of the quantitative insulin sensitivity check index (QUICKI) was used to measure global regulatory insulin sensitivity, since it incorporates both fasting glucose and NEFA levels (revised QUICKI; 1/[log(fasting insulinemia×fasting glycemia×fasting NEFA)]) [29].
Anthropometric measures: Weight, body fat percentage, and lean mass were measured using standing electrical bioimpedance (Tanita weight scale model TBF-300A, Arlington Heights, IL, USA). Height, waist circumference (WC), and hip circumference were also recorded. Anthropometric indices included BMI (weight [kg]/height [m]²), body fat percentage, total fat mass to lean mass ratio (FM/LM), fat mass index (FMI; [weight (kg)×body fat (%)]/height [m]²), WC, and waist-to-hip (W/H) ratio.
Statistical analyses: Data are presented as mean±standard deviation, except for non-normally distributed variables, which are summarized as the median (interquartile range). Variables with non-normal distributions were ln-transformed to achieve normality, and normality was visually confirmed using probability-probability (P-P) plots. Between-group comparisons were performed using Mann-Whitney non-parametric tests. After confirming linearity, Pearson correlation coefficients were calculated to assess significant correlations between dynamic NEFA insulin-suppression indices derived from the OGTT and the clamp. To evaluate convergent validity with parameters associated with lipotoxicity [24], the dynamic NEFA insulin-suppression indices showing the strongest correlation between the OGTT and clamp were further correlated with Adipo-IR, glucose insulin-resistance indices, and anthropometric measures. Other NEFA suppression indices were also included in these analyses to confirm whether their convergent validity was lower. Sensitivity analyses were conducted using Spearman correlation coefficients. To ensure the validity of indices across both women with and without PCOS, multivariate linear regressions were performed for each correlation to assess interactions between PCOS status and NEFA insulin-suppression indices or other parameters. When significant interactions were found, correlation and regression coefficients were stratified by PCOS subgroup, as interactions test for differences in regression slopes between groups. Additionally, to confirm that correlations between indices were consistent across the entire range of BMI, WC, and/or age, interaction factors between age or BMI and NEFA insulin-suppression indices were evaluated. Statistical significance was set at P≤0.05 for all analyses, except for interaction analyses, which used a threshold of P≤0.10. Correlation analyses were conducted using GraphPad Prism software version 10.1.1 (GraphPad Software, San Diego, CA, USA), and regressions were performed using IBM SPSS Statistics for Windows version 28.0 (IBM Corp., Armonk, NY, USA). Correlations were classified as ‘strong’ (>0.50), ‘moderate’ (0.30–0.50), or ‘weak’ (<0.30), based on Cohen’s effect size interpretation principles [30].; As this is a secondary analysis, the sample size was not determined a priori, and all eligible participants from the original clinical trial were included. However, with the achieved sample size, an α level of 5%, and 80% power, the study was adequately powered to detect Pearson’s r coefficients of at least 0.31 for the whole group and 0.46 for subgroup analyses (calculated using G*Power version 3.1, Heinrich Heine University, Düsseldorf, Germany). Given the study’s aim to identify an OGTT index with strong correlations to a clamp index and to anthropometric and metabolic parameters, detecting lower correlations was not considered relevant.

Anthropometric and metabolic parameters: Twenty-nine non-Hispanic Caucasian women were recruited for this study, comprising 15 women without PCOS and 14 women with PCOS. None of the participants had impaired fasting glucose, but two women without PCOS (13%) and three women with PCOS (21%) exhibited impaired glucose tolerance (17% of all participants). Participant characteristics are summarized in Table 1. Women were of similar age and W/H ratio, but women with PCOS had significantly higher weight, BMI, WC, body fat percentage, FMI, and FM/LM compared to women without PCOS (all P<0.001). Women with PCOS also had significantly higher fasting NEFA levels (P=0.004) and post-OGTT NEFA AUC (P=0.03), elevated 2-hour insulin levels (P=0.01) and post-OGTT insulin AUC (P=0.002), reduced glucose insulin sensitivity (44% lower for ISI Matsuda, P<0.001; 33% lower for M-value, P=0.01), and increased Adipo-IR (P=0.003) and revised QUICKI (P=0.004) compared to women without PCOS.
Correlations between OGTT- and clamp-derived indices of NEFA suppression: Correlations between OGTT- and clamp-derived indices are presented in Table 2, wherein correlations with an unexpected direction are in parentheses. The OGTT-derived NEFA suppression index that best correlated with any clamp index was T50_NEFA, which displayed a strong positive correlation with %NEFA_supp [clamp], with no interaction (P for interaction=0.82) (Fig. 1). This correlation was very consistent between women with or without PCOS (r=–0.56 and r=–0.57). Other indices showed less conclusive results. For example, other significant correlations included dAUC_NEFA, which was highly and positively correlated with ΔNEFA in participants with PCOS (P for interaction=0.03); %NEFA_supp (OGTT), which displayed a strong negative, unexpected, correlation with ΔΝEFA in women without PCOS (P for interaction=0.04); and SlopeLn_NEFA, which showed a strong positive correlation with %NEFA_supp[clamp] in women with PCOS (P for interaction=0.03). Of note, there was a strong significant correlation between OGTT- and clamp-derived indices of glucose insulin sensitivity (ISI Matsuda vs. M-value, r=0.66, P<0.001, data not shown).
Correlations between indices of NEFA suppression and anthropometric and metabolic parameters: Correlations between NEFA suppression indices and anthropometric measures are presented in Table 3, and metabolic parameters are presented in Table 4, with correlation coefficients in the unexpected direction shown in parentheses. On one hand, T50_NEFA correlated with all anthropometric measures, showing mostly strong associations, and adverse metabolic parameters, showing moderate to strong associations, except for fasting glycemia, which did not exhibit a correlation. There were significant interactions for FM/LM, insulinemia 2-hour post-glucose load, OGTT insulin AUC, ISI Matsuda, HOMA-IR, and Adipo-IR, which had correlations only in women with PCOS, and for BMI and FMI, which showed higher associations in women with PCOS. On the other hand, %NEFA_supp (clamp) also displayed moderate to strong significant correlations with all anthropometric measures and most metabolic parameters, although it did not correlate with fasting, 2-hour post-load, or AUC glycemia. There were significant interactions only for FMI, FM/LM, and OGTT insulin AUC. dAUC_NEFA, SlopeLn_NEFA, %NEFA_supp (OGTT), and ΔNEFA (clamp) were not as consistently correlated with anthropometric and/or adverse metabolic parameters.; Sensitivity analyses showed that assessing the correlations using the non-parametric Spearman analyses did not have an impact on the results (data not shown). Moreover, there were no significant interactions between T50_NEFA and BMI or age for its correlation with %NEFA_supp (clamp), meaning that T50_NEFA and %NEFA_supp (clamp) correlated consistently with each other throughout the whole range of BMI (18.8 to 37.9 kg/m²), WC (0.62 to 1.08 m), and age (21 to 38 years).

DISCUSSION

In this sample of 29 women presenting a large range of weight and glucose insulin sensitivity, T50_NEFA was the only OGTT-derived index of insulin-mediated NEFA suppression that was significantly associated with a corresponding clamp-derived index, namely %NEFA_supp, in all women (Table 2). This correlation was consistent across both women with and without PCOS and remained robust regardless of age, WC, or BMI.

T50_NEFA is an index of IR defined as the time needed to suppress 50% of NEFA levels from baseline during an OGTT, a response driven by the rise in insulin levels following the glucose load. A prolonged T50_NEFA indicates reduced NEFA suppression by insulin, reflecting IR. While the euglycemic-hyperinsulinemic clamp is the predominant method for assessing insulin-mediated lipolysis suppression in the literature [11,31], few studies have explored the use of the OGTT for this purpose. To our knowledge, only one prior study [18] has compared OGTT-derived indices of antilipolytic insulin sensitivity with those obtained from the clamp.

The current study provides the first evidence that the T50_NEFA index derived from the OGTT is significantly associated with clamp results, as well as adverse metabolic and anthropometric parameters, thus supporting its use in clinical studies. The correlation between T50_NEFA and %NEFA_supp was almost as strong as the correlation between ISI Matsuda, the OGTT-derived index of glucose insulin sensitivity, and the M-value, a clamp-derived measure (i.e., r=0.66 in this study and r=0.73 in the original study by Matsuda et al. [17]). To our knowledge, the T50_NEFA index has not been previously described in the literature, with the exception of only one study published by our group in peripubertal girls at risk of PCOS, which was measured during a frequently sampled intravenous glucose tolerance test as opposed to an OGTT [32]. In this previous study, T50_NEFA was found to be significantly doubled in girls at risk for PCOS as compared to controls, which was corroborated by a significantly steeper slope of suppression of NEFA during the frequently sampled intravenous glucose tolerance test in these girls.

The euglycemic-hyperinsulinemic clamp is the gold standard for assessing glucose insulin sensitivity [10], and it has also been used to evaluate the antilipolytic action of insulin, typically using two low-dose insulin steps (4 and 8 mU/m²/min) [12,18,21,33]. Previous studies have proposed %NEFA_supp as a clamp-derived measure of insulin sensitivity for lipolysis [34-36], where greater NEFA suppression from baseline reflects higher antilipolytic insulin sensitivity. Since the clamp technique used in this study was not the gold standard for assessing adipose tissue insulin sensitivity, OGTT and clamp NEFA indices were evaluated for convergent validity against parameters associated with lipotoxicity, including anthropometric measures, glucometabolic indices, and Adipo-IR.

Obesity, particularly abdominal obesity (clinically measured by WC or the W/H ratio), is a well-established risk factor for T2D and cardiovascular diseases [37], largely due to its association with lipotoxicity [2]. Lipotoxicity refers to tissue or cellular dysfunction caused by prolonged exposure to elevated NEFA levels [2]. Adipose tissue plays a central role in NEFA storage and release, regulated primarily by insulin [38]. In the postprandial state, rising insulin levels stimulate lipoprotein lipase activity to store circulating triglycerides while inhibiting hormone-sensitive lipase to reduce lipolysis [39,40]. Antilipolytic IR in adipocytes leads to excessive NEFA release into the circulation [39], contributing to peripheral tissue overexposure and lipotoxicity [24]. Visceral fat, in particular, is more resistant to insulin’s antilipolytic action than subcutaneous fat [41]. Accordingly, our results show that in all women, both T50_NEFA and %NEFA_supp correlated well with all measured anthropometric parameters, including WC, W/H ratio, and body fat percentage. This clinically validates the use of these indices as dynamic measures of adiposity-related antilipolytic insulin sensitivity in women.

For further convergent validation, our indices were compared against metabolic parameters associated with glucose insulin sensitivity, measured during the clamp, OGTT, and fasting blood samples. Prolonged elevation of circulating NEFA levels has been shown to reduce muscle and hepatic insulin sensitivity and impair beta-cell function in healthy individuals [42,43], a mechanism by which lipotoxicity contributes to global metabolic IR and the development of impaired glucose tolerance or T2D [44]. By contributing to the development of lipotoxicity, resistance to the antilipolytic action of insulin should thus be associated with abnormal glucose metabolism. Accordingly, T50_NEFA and %NEFA_supp were significantly associated with glucose insulin sensitivity parameters in all women, and T50_NEFA was also associated with glucose tolerance. Since T50_NEFA and %NEFA_supp were associated with the established glucoregulatory consequences of lipotoxicity, these results further validate that our indices appropriately measure antilipolytic insulin sensitivity in women.

When matched for BMI, women with PCOS are known to have higher levels of visceral adiposity and glucoregulatory IR than healthy women. Women with PCOS were thus included in this study in order to expand the spectrum of BMI and insulin sensitivity in our population of women [45], as shown in Table 1. Interestingly, several antilipolytic sensitivity indices were more strongly associated with anthropometric parameters, OGTT measures of glucose insulin sensitivity, and insulinemia in women with PCOS compared to women without PCOS. These findings suggest that women with PCOS may be more susceptible to the consequences of antilipolytic IR or lipotoxicity, particularly with increased BMI, or to the concurrent development of both types of IR. However, this hypothesis requires further investigation in future studies.

Although our conclusions are supported by rigorous analyses and highly significant, consistent results, several limitations must be acknowledged. First, the large number of correlations performed raises the possibility that some significant associations may have occurred by chance due to multiple testing. Isolated significant findings should therefore be interpreted with caution. However, the consistent and robust correlations observed for T50_NEFA and %NEFA_supp across multiple parameters and in all women strengthen the validity of these results. Second, the relatively small sample size of each subgroup limits the generalizability of subgroup-specific findings, which should be considered exploratory rather than confirmatory. Additionally, the absence of statistical significance for some subgroup differences or interactions may reflect insufficient statistical power, despite the use of a more liberal significance threshold to mitigate this issue. The overall small sample size also restricts the broader applicability of our conclusions, underscoring the need for validation in larger studies. Third, while more complex three-step clamp techniques or palmitate/glycerol tracer methods with kinetic modeling may provide more robust measures of antilipolytic insulin action [23,46], the goal of this study was to identify practical and valid indices that could be easily applied in research settings, particularly those derived from the widely used OGTT. Fourth, although inhibition of adipose tissue lipolysis is recognized as the primary mechanism of postprandial NEFA suppression mediated by insulin [5], a study has found that incorporating NEFA uptake parameters into kinetic models improves their accuracy compared to models focusing solely on NEFA appearance rates [23]. Additionally, in vitro evidence indicates that insulin stimulates NEFA uptake via CD36 transporter translocation [47]. These findings support the possibility that T50_NEFA and %NEFA_supp (clamp) measure total NEFA suppression and not the antilipolytic action of insulin. However, since participants were fasting at baseline and postprandial NEFA levels were influenced solely by monosaccharide ingestion (without lipid intake), and given that NEFA uptake plays a minimal role in postprandial NEFA suppression [5,23,48], we considered NEFA suppression and adipose tissue lipolysis to be synonymous in this context [49]. Fifth, the presented indices were not adjusted for insulin levels or kinetics, which may seem counterintuitive given the focus on insulin-dependent NEFA suppression. However, standardizing for insulin excursion (% increase, insulin AUC, or delta) during the OGTT either had no effect or artificially inflated correlations due to the strong association of insulin with most parameters, thereby complicating the validation of our indices (data not shown). Sixth, factors such as fasting duration (required to be at least 12 hours) and ketogenic states, which can influence fasting NEFA levels and fatty acid metabolism, were neither measured nor accounted for in the analyses. These factors may have introduced variability in the antilipolytic insulin response, potentially affecting the results. Finally, the study included only PCOS and non-IR, women without PCOS, limiting the generalizability of the findings to men and IR, women without PCOS. Although PCOS diagnoses were made by specialized endocrinologists, the lack of research-level confirmation at inclusion means some misclassification may have occurred. However, this is unlikely given the specialized care provided in a tertiary academic center, and any such misclassification is not expected to have significantly impacted the results or conclusions.

In conclusion, this study found that in women, T50_NEFA, a dynamic index of insulin-stimulated NEFA suppression derived from the OGTT, showed a strong and consistent association with the %NEFA_supp derived from the clamp. Both these indices were also significantly and consistently associated with anthropometric measures and parameters of glucose metabolism. This study thus suggests that both T50_NEFA and %NEFA_supp are valid indices of antilipolytic insulin sensitivity in women. Since the OGTT is easier to perform and less expensive than the glucose insulin clamp technique, these findings support the use of the OGTT-derived T50_NEFA to estimate antilipolytic IR in women, especially in large cohorts that already include an OGTT in the experimental procedure.

Article information

CONFLICTS OF INTEREST

Jean-Patrice Baillargeon is a Senior Clinical-Investigator of the Fonds de recherche du Québec – Santé (FRQS). André C. Carpentier is the Canada Research Chair in Molecular Imaging of Diabetes.

ACKNOWLEDGMENTS

This work was funded in part by the Canadian Institutes of Health Research (CIHR, MOP-97965). This article is based on FN’s master’s thesis (Naimi F. Nouveaux indices de suppression de la lipolyse par l’insuline déterminés lors de l’hyperglycémie provoquée par voie orale: comparaisons avec le clamp euglycémique-hyperinsulinémique et les paramètres métaboliques chez les femmes [master’s thesis]. Sherbrooke: University of Sherbrooke; 2016). Note that the manuscript presented therein was rejected for publication in a scientific journal.

We would like to thank the research nurses Diane Lessard and Caroll-Lynn Thibodeau of the Centre de recherche du Centre hospitalier universitaire de Sherbrooke for the realization of research visits and techniques with participants.

AUTHOR CONTRIBUTIONS

Conception or design: F.N., A.C.C., J.P.B. Acquisition, analysis, or interpretation of data: F.N., C.R.L., M.C.B. Drafting the work or revising: F.N., C.R.L., M.C.B., A.C.C., J.P.B. Final approval of the manuscript: F.N., C.R.L., M.C.B., A.C.C., J.P.B.

Fig. 1.

Correlation between time to suppress non-esterified fatty acid (NEFA) levels by 50% (T50_NEFA) derived from the oral glucose tolerance test (OGTT) and percentage of NEFA suppression (%NEFA_supp) derived from the euglycemic-hyperinsulinemic clamp in all participants. %NEFA_supp is log-natural transformed. PCOS, polycystic ovary syndrome.

Table 1.

Participants’ Characteristics

Characteristic	All	Non-PCOS women	PCOS women
Number	29	15	14
Age, yr	29.5±5.5	28.5±5.9	30.6±5.0
Weight, kg	70.4±13.0	62.4±6.2	78.9±13.1^a
BMI, kg/m²	25.9±5.6	22.7±2.3	29.3±6.3^a
Waist circumference, cm	83±12	75±7	90±12^a
W/H ratio	0.80±0.08	0.78±0.07	0.82±0.08
Fat %, %	33.2±8.0	28.2±5.0	38.6±7.0^a
FMI, kg/m²	9.01±4.15	6.51±1.73	11.68±4.36^a
FM/LM, ratio	0.52±0.19	0.40±0.10	0.65±0.19^a
Adipo-IR	2.43 (1.05–3.72)	1.14 (0.81–2.70)	3.59 (2.06–6.93)^a
Revised QUICKI	0.46±0.08	0.49±0.07	0.42±0.06^a
HOMA-IR	0.91 (0.51–1.74)	0.84 (0.49–1.03)	1.07 (0.75–2.47)
Fasting glucose, mg/dL	78.8±6.8	78.8±6.1	78.8±7.7
Fasting insulin, µU/mL	4.00 (2.15–8.21)	3.45 (2.07–4.72)	5.12 (3.36–11.46)
Fasting NEFA, mmol/L	0.46±0.18	0.37±0.13	0.56±0.19^a
OGTT-derived metabolic parameters
Glucose at 120 min, mg/dL	120.0±25.1	113.0±19.6	127.5±28.7
Insulin at 120 min, µU/mL	43.5 (25.2–69.9)	35.3 (24.5–22.2)	59.2 (38.2–104.5)^a
AUC glucose, mmol/min/L	859±166	803±111	919±197
AUC insulin, mU/min/L	5.32 (3.68–7.62)	3.86 (3.13–5.32)	6.49 (5.31–11.26)^a
ISI Matsuda	8.38±4.13	10.66±3.35	5.92±3.49^a
AUC NEFA, mmol/min/L	16.3 (11.6–23.0)	13.0 (9.4–16.7)	22.4 (15.0–28.6)^a
Clamp-derived metabolic parameters
M-value, µmol/kg/min	48.1±20.6	57.3±16.1	38.2±20.9^a

Values are expressed as mean±standard deviation or median (interquartile range).

PCOS, polycystic ovary syndrome; BMI, body mass index; W/H, waist-to-hip; FMI, fat mass index [(weight (kg)/fat %)/height² (m)]; FM/LM, ratio of total fat mass to total non-fat mass (approximate lean mass); Adipo-IR, adipose tissue insulin resistance index (fasting insulin×fasting NEFA); QUICKI, quantitative insulin sensitivity check index (glucose and NEFA insulin sensitivity index [1/log(fasting insulin×fasting glucose×fasting NEFA)]); HOMA-IR, homeostatic model for assessment of insulin resistance (fasting insulin×fasting glucose/22.5); NEFA, non-esterified fatty acid; OGTT, oral glucose tolerance test; AUC, area under the curve; ISI, insulin sensitivity index [10,000/square root(fasting glucose×fasting insulin×mean OGTT glucose×mean OGTT insulin)]; M-value, measure of insulin-mediated glucose utilization (insulin sensitivity).

^a P value ≤0.05 for difference between groups.

Table 2.

Correlations between Oral Glucose Tolerance Test- and Clamp-Derived Indices

OGTT	Item	Euglycemic-hyperinsulinemic clamp
		Insulin sensitivity indices
		∆NEFA	P value	%NEFA_supp	P value
Insulin sensitivity indices
dAUC_NEFA	All women (n=29)	0.49^a	0.007	0.11	0.58
	Non-PCOS women (n=15)	0.08	0.78
	β	1.6
	PCOS women (n=14)	0.65	0.01
	β	7.0
SlopeLn_NEFA	All women (n=29)	(–0.34)	0.07	0.17^a	0.39
	Non-PCOS women (n=15)			(–0.13)	0.63
	β			–9.8
	PCOS women (n=14)			0.56	0.04
	β			84.9
%NEFA_supp	All women (n=29)	(–0.27)^a	0.16	(–0.06)	0.75
	Non-PCOS women (n=15)	(–0.58)	0.02
	β	–86.7
	PCOS women (n=14)	0.14	0.64
	β	24.9
Insulin resistance index
T50_NEFA	All women (n=29)	(0.27)	0.15	–0.58	0.0009

The results are Pearson correlation coefficients, and the regression coefficients (β) are shown in square brackets where interactions are significant. Parentheses mean that the correlation is in the unexpected direction. In order to normalize their distributions for correlations, %NEFA_supp (OGTT and Clamp) values were transformed using log_n.

OGTT, oral glucose tolerance test; ΔNEFA, differece between mean steady-state non-esterified fatty acid (NEFA) levels and baseline from clamp; %NEFA_supp, percentage of NEFA suppression; dAUC_NEFA, decremental NEFA area under the curve; PCOS, polycystic ovary syndrome; SlopeLn_NEFA, negative log_n-linear slope of the decrease in NEFA levels during the entire course of the OGTT; T50_NEFA, time to suppress NEFA levels by 50%.

^a P≤0.10 for interaction with the women’s groups, meaning that the correlations are significantly different between groups and thus correlations should be considered for each women’s group separately.

Table 3.

Correlations between Oral Glucose Tolerance Test- and Clamp-Derived Indices and Anthropometric Parameters

NEFA levels & calculated indices		Anthropometric measures
NEFA levels & calculated indices		BMI	WC	W/H	Fat %	FMI	FM/LM
OGTT
Indices of sensitivity to antilipolytic insulin action
dAUC_NEFA	All women	(0.03)	(0.24)	(0.35)	(0.18)	(0.09)	(0.16)
SlopeLn_NEFA	All women	–0.29^a	–0.34^a	–0.28	–0.14^a	–0.25^a	–0.20^a
	Non-PCOS women	–0.02	–0.06		(0.20)	(0.07)	(0.14)
	β	–3.5	–0.4		74.1	8.5	1.0
	PCOS women	–0.64^b	–0.75^b		–0.60^b	–0.64^b	–0.62^b
	β	–475.7	–10.2		–494.2	–326.9	–13.5
%NEFA_supp	All women	–0.26^a	–0.33^a	–0.34	–0.15^a	–0.25^a	–0.20^a
	Non-PCOS women	(0.08)	–0.03		(0.23)	(0.12)	(0.17)
	β	0.2	–0.002		1.0	0.2	0.01
	PCOS women	–0.52	–0.65^b		–0.51	–0.56^b	–0.53^b
	β	–3.3	–0.1		–3.7	–2.5	–0.1
Index of resistance to antilipolytic insulin action
T50_NEFA	All women	0.64^a,b	0.64^b	0.44^b	0.60^b	0.63^a,b	0.62^a,b
	Non-PCOS women	0.70^b				0.60^b	0.50
	β	0.1				0.1	0.004
	PCOS women	0.70^b				0.74^b	0.77^b
	β	0.3				0.2	0.01
Euglycemic clamp
Indices of sensitivity to antilipolytic insulin action
∆NEFA	All women	(0.03)	(0.32)	(0.50^b)	(0.01)	(0.03)	(0.05)
%NEFA_supp	All women	–0.56^b	–0.57^b	–0.45^b	–0.54^b	–0.56^a,b	–0.55^a,b
	Non-PCOS women					–0.28	–0.24
	β					–0.5	–0.02
	PCOS women					–0.67^b	–0.70^b
	β					–2.2	–0.1

NEFA, non-esterified fatty acids; BMI, body mass index; WC, waist circumference; W/H, waist-to-hip; Fat %, percentage of fat measured by foot to foot bioimpedance; FMI, fat mass index [(weight (kg)/fat %)/height² (m)]; FM/LM, ratio of total fat mass to total non-fat mass (approximate lean mass); OGTT, oral glucose tolerance test; dAUC_NEFA, decremental NEFA area under the curve; SlopeLn_NEFA, negative slope of the log-linear NEFA curve; PCOS, polycystic ovary syndrome; %NEFA_supp, percentage of NEFA suppression; T50_NEFA, time to suppress NEFA levels by 50%; ΔNEFA, difference between mean steady-state NEFA levels and baseline from clamp.

^b P≤0.05 for correlation.

Table 4.

Correlations between Oral Glucose Tolerance Test- and Clamp-Derived Indices and Metabolic Parameters

Calculated indices		Adverse metabolic parameters						Glucose insulin sensitivity		Glucose insulin resistance	NEFA insulin resistance	Global insulin sensitivity
Calculated indices		Fast Gluc	Gluc 2 hr	AUC Gluc	Fast Ins	Ins 2 hr	AUC Ins	ISI Matsuda	M-value	HOMA-IR	Adipo-IR	Revised QUICKI
OGTT
Indices of sensitivity to antilipolytic insulin action
dAUC_NEFA	All women	–0.14	(0.60^b)	(0.47^b)	–0.06	(0.23)	(0.16)	(–0.11)	(–0.09)	–0.08	(0.33)	(–0.36)
SlopeLn_NEFA	All women	–0.30	–0.17	–0.32	–0.30^a	(0.05)	(0.06)	0.10^a	0.29	–0.34^a	–0.27^a	0.26
	Non-PCOS women				–0.13			(–0.17)		–0.20	–0.11
	β				–5.8			–42.2		–8.5	–5.7
	PCOS women				–0.57^b			0.50		–0.59^b	–0.56^b
	β				–52.7			205.2		–53.4	–56.8
%NEFA_supp	All women:	–0.33	–0.04	–0.20	–0.18	(0.17)	(0.11)	0.01	0.10	–0.22	–0.18	0.17
Index of resistance to antilipolytic insulin action
T50_NEFA	All women	0.14	0.43^b	0.38^b	0.53^a,b	0.41^a,b	0.22^a	–0.42^a,b	–0.45^b	0.55^a,b	0.62^a,b	–0.63^b
	Non-PCOS women				0.17	(–0.24)	(–0.50)	(0.08)		0.21	0.35
	β				0.01	–0.01	–0.02	0.02		0.01	0.02
	PCOS women				0.73^b	0.69^b	0.55^b	–0.80^b		0.75^b	0.82^b
	β				0.04	0.04	0.02	–0.2		0.04	0.05
Euglycemic clamp
Indices of sensitivity to antilipolytic insulin action
∆NEFA	All women	–0.09	(0.54^a,b)	(0.37^b)	–0.06	0.00	–0.10	0.08	(–0.19)	–0.107	(0.20)	(–0.19)
	Non-PCOS women		-0.17
	β		0.001
	PCOS women		(0.77^b)
	β		0.01
%NEFA_supp	All women	(0.22)	–0.29	–0.29	–0.55^b	–0.47^b	–0.39^a,b	0.51^b	0.63^b	–0.53^b	–0.50^b	0.47^b
	Non-PCOS women						–0.13
	β						0.1
	PCOS women						–0.58^b
	β						–0.3

NEFA, non-esterified fatty acid; Fast Gluc, fasting glucose; Gluc 2 hr, glucose level at 120 minutes during OGTT; AUC Gluc, area under the glucose curve during OGTT; Fast Ins, fasting insulin; Ins 2 hr, insulin level at 120 minutes during OGTT; AUC Ins, area under the insulin curve during OGTT; ISI, insulin sensitivity index; M-value, glucose infusion rate during clamp steady-state corrected for weight; HOMA-IR, homeostatic model for assessment of insulin resistance; Adipo-IR, adipose tissue insulin resistance index; QUICKI, quantitative insulin sensitivity check index (glucose and NEFA insulin sensitivity index); OGTT, oral glucose tolerance test; dAUC_NEFA, decremental NEFA area under the curve; SlopeLn_NEFA, negative slope of the log-linear NEFA curve; PCOS, polycystic ovary syndrome; %NEFA_supp, percentage of NEFA suppression; T50_NEFA, time to suppress NEFA levels by 50%;ΔNEFA, difference between mean steady-state NEFA levels and baseline from clamp.

^b P≤0.05 for correlation.

References

1. Lewis GF, Carpentier A, Adeli K, Giacca A. Disordered fat storage and mobilization in the pathogenesis of insulin resistance and type 2 diabetes. Endocr Rev 2002;23:201–29.Article PubMed
2. Carpentier AC. Postprandial fatty acid metabolism in the development of lipotoxicity and type 2 diabetes. Diabetes Metab 2008;34:97–107.Article PubMed
3. Frayn KN, Shadid S, Hamlani R, Humphreys SM, Clark ML, Fielding BA, et al. Regulation of fatty acid movement in human adipose tissue in the postabsorptive-to-postprandial transition. Am J Physiol 1994;266(3 Pt 1):E308–17.Article PubMed
4. Carpentier AC, Frisch F, Cyr D, Genereux P, Patterson BW, Giguere R, et al. On the suppression of plasma nonesterified fatty acids by insulin during enhanced intravascular lipolysis in humans. Am J Physiol Endocrinol Metab 2005;289:E849–56.Article PubMed
5. Carpentier AC, Frisch F, Brassard P, Lavoie F, Bourbonnais A, Cyr D, et al. Mechanism of insulin-stimulated clearance of plasma nonesterified fatty acids in humans. Am J Physiol Endocrinol Metab 2007;292:E693–701.Article PubMed
6. Jansson PA, Larsson A, Smith U, Lonnroth P. Glycerol production in subcutaneous adipose tissue in lean and obese humans. J Clin Invest 1992;89:1610–7.Article PubMed PMC
7. Ruge T, Hodson L, Cheeseman J, Dennis AL, Fielding BA, Humphreys SM, et al. Fasted to fed trafficking of fatty acids in human adipose tissue reveals a novel regulatory step for enhanced fat storage. J Clin Endocrinol Metab 2009;94:1781–8.Article PubMed
8. Jensen MD, Haymond MW, Gerich JE, Cryer PE, Miles JM. Lipolysis during fasting: decreased suppression by insulin and increased stimulation by epinephrine. J Clin Invest 1987;79:207–13.Article PubMed PMC
9. Campbell PJ, Carlson MG, Nurjhan N. Fat metabolism in human obesity. Am J Physiol 1994;266(4 Pt 1):E600–5.Article PubMed
10. DeFronzo RA, Tobin JD, Andres R. Glucose clamp technique: a method for quantifying insulin secretion and resistance. Am J Physiol 1979;237:E214–23.Article PubMed
11. Groop LC, Bonadonna RC, Simonson DC, Petrides AS, Shank M, DeFronzo RA. Effect of insulin on oxidative and nonoxidative pathways of free fatty acid metabolism in human obesity. Am J Physiol 1992;263(1 Pt 1):E79–84.Article PubMed
12. Stumvoll M, Wahl HG, Loblein K, Becker R, Volk A, Renn W, et al. A novel use of the hyperinsulinemic-euglycemic clamp technique to estimate insulin sensitivity of systemic lipolysis. Horm Metab Res 2001;33:89–95.Article PubMed
13. Sondergaard E, Espinosa De Ycaza AE, Morgan-Bathke M, Jensen MD. How to measure adipose tissue insulin sensitivity. J Clin Endocrinol Metab 2017;102:1193–9.Article PubMed PMC PDF
14. Henderson M, Baillargeon JP, Rabasa-Lhoret R, Chiasson JL, Hanley J, Lambert M. Estimating insulin secretion in youth using simple indices derived from the oral glucose tolerance test. Diabetes Metab 2012;38:309–15.Article PubMed
15. Abdul-Ghani MA, Lyssenko V, Tuomi T, DeFronzo RA, Groop L. Fasting versus postload plasma glucose concentration and the risk for future type 2 diabetes: results from the Botnia Study. Diabetes Care 2009;32:281–6.PubMed PMC
16. Cheng C, Campbell KL, Kushner H, Falkner BE. Correlation of oral glucose tolerance test-derived estimates of insulin sensitivity with insulin clamp measurements in an African-American cohort. Metabolism 2004;53:1107–12.Article PubMed
17. Matsuda M, DeFronzo RA. Insulin sensitivity indices obtained from oral glucose tolerance testing: comparison with the euglycemic insulin clamp. Diabetes Care 1999;22:1462–70.Article PubMed PDF
18. Van Pelt RE, Gozansky WS, Kohrt WM. A novel index of whole body antilipolytic insulin action. Obesity (Silver Spring) 2013;21:E162–5.PubMed PMC
19. Axelsen M, Lonnroth P, Lenner RA, Taskinen MR, Smith U. Suppression of nocturnal fatty acid concentrations by bedtime carbohydrate supplement in type 2 diabetes: effects on insulin sensitivity, lipids, and glycemic control. Am J Clin Nutr 2000;71:1108–14.Article PubMed
20. Holt HB, Wild SH, Wood PJ, Zhang J, Darekar AA, Dewbury K, et al. Non-esterified fatty acid concentrations are independently associated with hepatic steatosis in obese subjects. Diabetologia 2006;49:141–8.Article PubMed PDF
21. Hudak S, Huber P, Lamprinou A, Fritsche L, Stefan N, Peter A, et al. Reproducibility and discrimination of different indices of insulin sensitivity and insulin secretion. PLoS One 2021;16:e0258476.Article PubMed PMC
22. Boston RC, Moate PJ. NEFA minimal model parameters estimated from the oral glucose tolerance test and the meal tolerance test. Am J Physiol Regul Integr Comp Physiol 2008;295:R395–403.Article PubMed PMC
23. Ramos-Roman MA, Lapidot SA, Phair RD, Parks EJ. Insulin activation of plasma nonesterified fatty acid uptake in metabolic syndrome. Arterioscler Thromb Vasc Biol 2012;32:1799–808.Article PubMed PMC
24. Carpentier AC. The 2012 CDA-CIHR INMD young investigator award lecture: dysfunction of adipose tissues and the mechanisms of ectopic fat deposition in type 2 diabetes. Can J Diabetes 2013;37:109–14.Article PubMed
25. Baillargeon JP, Jakubowicz DJ, Iuorno MJ, Jakubowicz S, Nestler JE. Effects of metformin and rosiglitazone, alone and in combination, in nonobese women with polycystic ovary syndrome and normal indices of insulin sensitivity. Fertil Steril 2004;82:893–902.Article PubMed
26. American Diabetes Association. Standards of medical care in diabetes: 2014. Diabetes Care 2014;37 Suppl 1:S14–80.Article PubMed PDF
27. Azziz R, Carmina E, Dewailly D, Diamanti-Kandarakis E, Escobar-Morreale HF, Futterweit W, et al. The Androgen Excess and PCOS Society criteria for the polycystic ovary syndrome: the complete task force report. Fertil Steril 2009;91:456–88.Article PubMed
28. Zhang K, Pan H, Wang L, Yang H, Zhu H, Gong F. Adipose tissue insulin resistance is closely associated with metabolic syndrome in Northern Chinese populations. Diabetes Metab Syndr Obes 2021;14:1117–28.Article PubMed PMC PDF
29. Rabasa-Lhoret R, Bastard JP, Jan V, Ducluzeau PH, Andreelli F, Guebre F, et al. Modified quantitative insulin sensitivity check index is better correlated to hyperinsulinemic glucose clamp than other fasting-based index of insulin sensitivity in different insulin-resistant states. J Clin Endocrinol Metab 2003;88:4917–23.Article PubMed
30. Cohen J. Statistical power analysis for the behavioral sciences; Revised ed. New York: Academic Press; 1977.
31. Jensen MD, Caruso M, Heiling V, Miles JM. Insulin regulation of lipolysis in nondiabetic and IDDM subjects. Diabetes 1989;38:1595–601.Article PubMed
32. Trottier A, Battista MC, Geller DH, Moreau B, Carpentier AC, Simoneau-Roy J, et al. Adipose tissue insulin resistance in peripubertal girls with first-degree family history of polycystic ovary syndrome. Fertil Steril 2012;98:1627–34.Article PubMed PMC
33. Jocken JW, Goossens GH, Boon H, Mason RR, Essers Y, Havekes B, et al. Insulin-mediated suppression of lipolysis in adipose tissue and skeletal muscle of obese type 2 diabetic men and men with normal glucose tolerance. Diabetologia 2013;56:2255–65.Article PubMed PMC PDF
34. Lomonaco R, Ortiz-Lopez C, Orsak B, Webb A, Hardies J, Darland C, et al. Effect of adipose tissue insulin resistance on metabolic parameters and liver histology in obese patients with nonalcoholic fatty liver disease. Hepatology 2012;55:1389–97.Article PubMed
35. McLaughlin T, Yee G, Glassford A, Lamendola C, Reaven G. Use of a two-stage insulin infusion study to assess the relationship between insulin suppression of lipolysis and insulin-mediated glucose uptake in overweight/obese, nondiabetic women. Metabolism 2011;60:1741–7.Article PubMed PMC
36. Kelsey MM, Forster JE, Van Pelt RE, Reusch JE, Nadeau KJ. Adipose tissue insulin resistance in adolescents with and without type 2 diabetes. Pediatr Obes 2014;9:373–80.Article PubMed
37. Despres JP. Abdominal obesity and cardiovascular disease: is inflammation the missing link? Can J Cardiol 2012;28:642–52.Article PubMed
38. Frayn KN. Adipose tissue as a buffer for daily lipid flux. Diabetologia 2002;45:1201–10.Article PubMed PDF
39. Unger RH. Lipotoxicity in the pathogenesis of obesity-dependent NIDDM: genetic and clinical implications. Diabetes 1995;44:863–70.Article PubMed
40. Borel AL, Boulet G, Nazare JA, Smith J, Almeras N, Tremblay A, et al. Improved plasma FFA/insulin homeostasis is independently associated with improved glucose tolerance after a 1-year lifestyle intervention in viscerally obese men. Diabetes Care 2013;36:3254–61.Article PubMed PMC PDF
41. Tchernof A, Despres JP. Pathophysiology of human visceral obesity: an update. Physiol Rev 2013;93:359–404.Article PubMed
42. Carpentier A, Mittelman SD, Lamarche B, Bergman RN, Giacca A, Lewis GF. Acute enhancement of insulin secretion by FFA in humans is lost with prolonged FFA elevation. Am J Physiol 1999;276:E1055–66.Article PubMed
43. Carpentier A, Mittelman SD, Bergman RN, Giacca A, Lewis GF. Prolonged elevation of plasma free fatty acids impairs pancreatic beta-cell function in obese nondiabetic humans but not in individuals with type 2 diabetes. Diabetes 2000;49:399–408.Article PubMed PDF
44. Boden G. Role of fatty acids in the pathogenesis of insulin resistance and NIDDM. Diabetes 1997;46:3–10.Article PubMed
45. Yildiz BO, Knochenhauer ES, Azziz R. Impact of obesity on the risk for polycystic ovary syndrome. J Clin Endocrinol Metab 2008;93:162–8.Article PubMed
46. Sondergaard E, Jensen MD. Quantification of adipose tissue insulin sensitivity. J Investig Med 2016;64:989–91.Article PubMed PDF
47. Bell JA, Reed MA, Consitt LA, Martin OJ, Haynie KR, Hulver MW, et al. Lipid partitioning, incomplete fatty acid oxidation, and insulin signal transduction in primary human muscle cells: effects of severe obesity, fatty acid incubation, and fatty acid translocase/CD36 overexpression. J Clin Endocrinol Metab 2010;95:3400–10.Article PubMed PMC
48. Carpentier AC. 100th Anniversary of the discovery of insulin perspective: insulin and adipose tissue fatty acid metabolism. Am J Physiol Endocrinol Metab 2021;320:E653–70.Article PubMed
49. Abdul-Ghani MA, Molina-Carrion M, Jani R, Jenkinson C, Defronzo RA. Adipocytes in subjects with impaired fasting glucose and impaired glucose tolerance are resistant to the anti-lipolytic effect of insulin. Acta Diabetol 2008;45:147–50.Article PubMed PDF

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Figure

Antilipolytic Insulin Sensitivity Indices Measured during an Oral Glucose Challenge: Associations with Insulin-Glucose Clamp and Central Adiposity in Women without Diabetes

Fig. 1. Correlation between time to suppress non-esterified fatty acid (NEFA) levels by 50% (T50NEFA) derived from the oral glucose tolerance test (OGTT) and percentage of NEFA suppression (%NEFAsupp) derived from the euglycemic-hyperinsulinemic clamp in all participants. %NEFAsupp is log-natural transformed. PCOS, polycystic ovary syndrome.

Fig. 1.

Antilipolytic Insulin Sensitivity Indices Measured during an Oral Glucose Challenge: Associations with Insulin-Glucose Clamp and Central Adiposity in Women without Diabetes

Characteristic	All	Non-PCOS women	PCOS women
Number	29	15	14
Age, yr	29.5±5.5	28.5±5.9	30.6±5.0
Weight, kg	70.4±13.0	62.4±6.2	78.9±13.1^a
BMI, kg/m²	25.9±5.6	22.7±2.3	29.3±6.3^a
Waist circumference, cm	83±12	75±7	90±12^a
W/H ratio	0.80±0.08	0.78±0.07	0.82±0.08
Fat %, %	33.2±8.0	28.2±5.0	38.6±7.0^a
FMI, kg/m²	9.01±4.15	6.51±1.73	11.68±4.36^a
FM/LM, ratio	0.52±0.19	0.40±0.10	0.65±0.19^a
Adipo-IR	2.43 (1.05–3.72)	1.14 (0.81–2.70)	3.59 (2.06–6.93)^a
Revised QUICKI	0.46±0.08	0.49±0.07	0.42±0.06^a
HOMA-IR	0.91 (0.51–1.74)	0.84 (0.49–1.03)	1.07 (0.75–2.47)
Fasting glucose, mg/dL	78.8±6.8	78.8±6.1	78.8±7.7
Fasting insulin, µU/mL	4.00 (2.15–8.21)	3.45 (2.07–4.72)	5.12 (3.36–11.46)
Fasting NEFA, mmol/L	0.46±0.18	0.37±0.13	0.56±0.19^a
OGTT-derived metabolic parameters
Glucose at 120 min, mg/dL	120.0±25.1	113.0±19.6	127.5±28.7
Insulin at 120 min, µU/mL	43.5 (25.2–69.9)	35.3 (24.5–22.2)	59.2 (38.2–104.5)^a
AUC glucose, mmol/min/L	859±166	803±111	919±197
AUC insulin, mU/min/L	5.32 (3.68–7.62)	3.86 (3.13–5.32)	6.49 (5.31–11.26)^a
ISI Matsuda	8.38±4.13	10.66±3.35	5.92±3.49^a
AUC NEFA, mmol/min/L	16.3 (11.6–23.0)	13.0 (9.4–16.7)	22.4 (15.0–28.6)^a
Clamp-derived metabolic parameters
M-value, µmol/kg/min	48.1±20.6	57.3±16.1	38.2±20.9^a

OGTT	Item	Euglycemic-hyperinsulinemic clamp
		Insulin sensitivity indices
		∆NEFA	P value	%NEFA_supp	P value
Insulin sensitivity indices
dAUC_NEFA	All women (n=29)	0.49^a	0.007	0.11	0.58
	Non-PCOS women (n=15)	0.08	0.78
	β	1.6
	PCOS women (n=14)	0.65	0.01
	β	7.0
SlopeLn_NEFA	All women (n=29)	(–0.34)	0.07	0.17^a	0.39
	Non-PCOS women (n=15)			(–0.13)	0.63
	β			–9.8
	PCOS women (n=14)			0.56	0.04
	β			84.9
%NEFA_supp	All women (n=29)	(–0.27)^a	0.16	(–0.06)	0.75
	Non-PCOS women (n=15)	(–0.58)	0.02
	β	–86.7
	PCOS women (n=14)	0.14	0.64
	β	24.9
Insulin resistance index
T50_NEFA	All women (n=29)	(0.27)	0.15	–0.58	0.0009

NEFA levels & calculated indices		Anthropometric measures
NEFA levels & calculated indices		BMI	WC	W/H	Fat %	FMI	FM/LM
OGTT
Indices of sensitivity to antilipolytic insulin action
dAUC_NEFA	All women	(0.03)	(0.24)	(0.35)	(0.18)	(0.09)	(0.16)
SlopeLn_NEFA	All women	–0.29^a	–0.34^a	–0.28	–0.14^a	–0.25^a	–0.20^a
	Non-PCOS women	–0.02	–0.06		(0.20)	(0.07)	(0.14)
	β	–3.5	–0.4		74.1	8.5	1.0
	PCOS women	–0.64^b	–0.75^b		–0.60^b	–0.64^b	–0.62^b
	β	–475.7	–10.2		–494.2	–326.9	–13.5
%NEFA_supp	All women	–0.26^a	–0.33^a	–0.34	–0.15^a	–0.25^a	–0.20^a
	Non-PCOS women	(0.08)	–0.03		(0.23)	(0.12)	(0.17)
	β	0.2	–0.002		1.0	0.2	0.01
	PCOS women	–0.52	–0.65^b		–0.51	–0.56^b	–0.53^b
	β	–3.3	–0.1		–3.7	–2.5	–0.1
Index of resistance to antilipolytic insulin action
T50_NEFA	All women	0.64^a,b	0.64^b	0.44^b	0.60^b	0.63^a,b	0.62^a,b
	Non-PCOS women	0.70^b				0.60^b	0.50
	β	0.1				0.1	0.004
	PCOS women	0.70^b				0.74^b	0.77^b
	β	0.3				0.2	0.01
Euglycemic clamp
Indices of sensitivity to antilipolytic insulin action
∆NEFA	All women	(0.03)	(0.32)	(0.50^b)	(0.01)	(0.03)	(0.05)
%NEFA_supp	All women	–0.56^b	–0.57^b	–0.45^b	–0.54^b	–0.56^a,b	–0.55^a,b
	Non-PCOS women					–0.28	–0.24
	β					–0.5	–0.02
	PCOS women					–0.67^b	–0.70^b
	β					–2.2	–0.1

Calculated indices		Adverse metabolic parameters						Glucose insulin sensitivity		Glucose insulin resistance	NEFA insulin resistance	Global insulin sensitivity
Calculated indices		Fast Gluc	Gluc 2 hr	AUC Gluc	Fast Ins	Ins 2 hr	AUC Ins	ISI Matsuda	M-value	HOMA-IR	Adipo-IR	Revised QUICKI
OGTT
Indices of sensitivity to antilipolytic insulin action
dAUC_NEFA	All women	–0.14	(0.60^b)	(0.47^b)	–0.06	(0.23)	(0.16)	(–0.11)	(–0.09)	–0.08	(0.33)	(–0.36)
SlopeLn_NEFA	All women	–0.30	–0.17	–0.32	–0.30^a	(0.05)	(0.06)	0.10^a	0.29	–0.34^a	–0.27^a	0.26
	Non-PCOS women				–0.13			(–0.17)		–0.20	–0.11
	β				–5.8			–42.2		–8.5	–5.7
	PCOS women				–0.57^b			0.50		–0.59^b	–0.56^b
	β				–52.7			205.2		–53.4	–56.8
%NEFA_supp	All women:	–0.33	–0.04	–0.20	–0.18	(0.17)	(0.11)	0.01	0.10	–0.22	–0.18	0.17
Index of resistance to antilipolytic insulin action
T50_NEFA	All women	0.14	0.43^b	0.38^b	0.53^a,b	0.41^a,b	0.22^a	–0.42^a,b	–0.45^b	0.55^a,b	0.62^a,b	–0.63^b
	Non-PCOS women				0.17	(–0.24)	(–0.50)	(0.08)		0.21	0.35
	β				0.01	–0.01	–0.02	0.02		0.01	0.02
	PCOS women				0.73^b	0.69^b	0.55^b	–0.80^b		0.75^b	0.82^b
	β				0.04	0.04	0.02	–0.2		0.04	0.05
Euglycemic clamp
Indices of sensitivity to antilipolytic insulin action
∆NEFA	All women	–0.09	(0.54^a,b)	(0.37^b)	–0.06	0.00	–0.10	0.08	(–0.19)	–0.107	(0.20)	(–0.19)
	Non-PCOS women		-0.17
	β		0.001
	PCOS women		(0.77^b)
	β		0.01
%NEFA_supp	All women	(0.22)	–0.29	–0.29	–0.55^b	–0.47^b	–0.39^a,b	0.51^b	0.63^b	–0.53^b	–0.50^b	0.47^b
	Non-PCOS women						–0.13
	β						0.1
	PCOS women						–0.58^b
	β						–0.3

Table 1. Participants’ Characteristics

Values are expressed as mean±standard deviation or median (interquartile range).

P value ≤0.05 for difference between groups.

Table 2. Correlations between Oral Glucose Tolerance Test- and Clamp-Derived Indices

P≤0.10 for interaction with the women’s groups, meaning that the correlations are significantly different between groups and thus correlations should be considered for each women’s group separately.

Table 3. Correlations between Oral Glucose Tolerance Test- and Clamp-Derived Indices and Anthropometric Parameters

P≤0.05 for correlation.

Table 4. Correlations between Oral Glucose Tolerance Test- and Clamp-Derived Indices and Metabolic Parameters

Articles

ABSTRACT

INTRODUCTION

METHODS

RESULTS

DISCUSSION

Article information

References

Figure & Data

References

Citations

Fig. 1.

Table 1.

Table 2.

Table 3.

Table 4.