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Aims/hypothesis: The euglycaemic-hyperinsulinaemic clamp (EIC) is the reference standard for the measurement of whole-body insulin sensitivity but is laborious and expensive to perform. We aimed to assess the incremental value of high-throughput plasma proteomic profiling in developing signatures correlating with the M value derived from the EIC., Methods: We measured 828 proteins in the fasting plasma of 966 participants from the Relationship between Insulin Sensitivity and Cardiovascular disease (RISC) study and 745 participants from the Uppsala Longitudinal Study of Adult Men (ULSAM) using a high-throughput proximity extension assay. We used the least absolute shrinkage and selection operator (LASSO) approach using clinical variables and protein measures as features. Models were tested within and across cohorts. Our primary model performance metric was the proportion of the M value variance explained (R 2 )., Results: A standard LASSO model incorporating 53 proteins in addition to routinely available clinical variables increased the M value R 2 from 0.237 (95% CI 0.178, 0.303) to 0.456 (0.372, 0.536) in RISC. A similar pattern was observed in ULSAM, in which the M value R 2 increased from 0.443 (0.360, 0.530) to 0.632 (0.569, 0.698) with the addition of 61 proteins. Models trained in one cohort and tested in the other also demonstrated significant improvements in R 2 despite differences in baseline cohort characteristics and clamp methodology (RISC to ULSAM: 0.491 [0.433, 0.539] for 51 proteins; ULSAM to RISC: 0.369 [0.331, 0.416] for 67 proteins). A randomised LASSO and stability selection algorithm selected only two proteins per cohort (three unique proteins), which improved R 2 but to a lesser degree than in standard LASSO models: 0.352 (0.266, 0.439) in RISC and 0.495 (0.404, 0.585) in ULSAM. Reductions in improvements of R 2 with randomised LASSO and stability selection were less marked in cross-cohort analyses (RISC to ULSAM R 2 0.444 [0.391, 0.497]; ULSAM to RISC R 2 0.348 [0.300, 0.396]). Models of proteins alone were as effective as models that included both clinical variables and proteins using either standard or randomised LASSO. The single most consistently selected protein across all analyses and models was IGF-binding protein 2., Conclusions/interpretation: A plasma proteomic signature identified using a standard LASSO approach improves the cross-sectional estimation of the M value over routine clinical variables. However, a small subset of these proteins identified using a stability selection algorithm affords much of this improvement, especially when considering cross-cohort analyses. Our approach provides opportunities to improve the identification of insulin-resistant individuals at risk of insulin resistance-related adverse health consequences., (© 2023. The Author(s).)

Distinct tissue-specific mechanisms mediate insulin action in fasting and postprandial states. Previous genetic studies have largely focused on insulin resistance in the fasting state, where hepatic insulin action dominates. Here we studied genetic variants influencing insulin levels measured 2 h after a glucose challenge in >55,000 participants from three ancestry groups. We identified ten new loci (P < 5 × 10 -8 ) not previously associated with postchallenge insulin resistance, eight of which were shown to share their genetic architecture with type 2 diabetes in colocalization analyses. We investigated candidate genes at a subset of associated loci in cultured cells and identified nine candidate genes newly implicated in the expression or trafficking of GLUT4, the key glucose transporter in postprandial glucose uptake in muscle and fat. By focusing on postprandial insulin resistance, we highlighted the mechanisms of action at type 2 diabetes loci that are not adequately captured by studies of fasting glycemic traits., (© 2023. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Background: Fasting insulin resistance indexes are used extensively nowadays. We intended to analyze a new recently presented fasting index, SPISE (sensitivity formula: 600 × HDL-cholesterol 0.185 /triglycerides 0.2 /BMI 1.338 ), in comparison with three previously known fasting indexes, regarding correlation with the insulin clamp index, and for the predictive effects of future long-term risks of coronary heart disease (CHD) or manifest type 2 diabetes. Methods: A total of 1049 71-year-old male subjects from the Swedish ULSAM study, median follow-up 8 years, were included. All subjects performed the euglycemic insulin clamp, and analyses of four fasting insulin resistance indexes: SPISE-IR (= 10/SPISE), QUICKI-IR, Log HOMA-IR, and Revised QUICKI-IR. Results: Spearman correlation coefficients with the insulin clamp were 0.60-0.62 for all indexes. Area under curve at ROC analysis was 0.80 for SPISE-IR, and 0.84 for QUICKI-IR, Log HOMA-IR, and Rev QUICKI-IR. Adjusted hazard ratios per 1 SD index increase for long-term risk CHD were similar in all patients: 1.20-1.24 ( p  = 0.02-0.03). However, comparing the highest quartile (recommended to define insulin resistance) with the lower quartiles, SPISE-IR was the strongest and the only statistically significant insulin resistance index: HR 1.53 ( p  = 0.02). Adjusted odds ratios per 1 SD index increase for long-term risk of type 2 diabetes were fairly similar ( p  < 0.001) in all patients: 1.62 for SPISE-IR, 1.97 for QUICKI-IR and Log HOMA-IR, and 2.04 for Rev QUICKI-IR, and also when comparing the highest versus the lower quartiles: 2.8-3.1 ( p  < 0.001). Conclusion: SPISE, easily applicable, performed equally well as other fasting insulin indexes previously recommended for clinical use, regarding correlation with the insulin clamp, and as predictor for future long-term risks of CHD or type 2 diabetes.

Background: The plasma concentration ratio of triglyceride (TG)/high-density lipoprotein cholesterol (HDL-C) is a simple way to estimate insulin resistance. We aimed to evaluate the TG/HDL-C ratio as a simple clinical way to identify apparently healthy individuals with insulin resistance and enhanced risk of future cardiovascular disease (CVD)., Methods: One thousand seven hundred twenty men, aged 50 years, free from diabetes and CVD when evaluated at baseline in 1970-1974 were followed for 40 years regarding incident CVD (myocardial infarction and/or ischemic stroke, n = 576)., Results: Participants with a high TG/HDL-C ratio (highest quartile >1.8) at baseline were more insulin resistant, with a significantly more adverse cardiometabolic risk profile (P < 0.001) at baseline, compared with those with a lower ratio. This group also showed an increased risk of CVD [hazard ratio, HR 1.47 (95% confidence interval 1.26-1.93) P < 0.001]. Fourteen percent of subjects with metabolic syndrome, in whom insulin resistance is increased, were also at enhanced CVD risk [HR 1.75 (1.42-2.16) P < 0.001]., Conclusions: Twenty-five percent of apparently healthy 50-year-old men with the highest TG/HDL-C plasma concentration ratio had a significantly more adverse cardiometabolic profile at baseline, and developed more CVD over the next 40 years, compared with those not meeting this cut point. Determining the TG/HDL-C ratio in middle-aged men provided a simple and potentially clinically useful way to identify increased risk of developing CVD in persons free of diabetes or manifest CVD.

Aim: The predictive effect of various insulin resistance indexes for risk of cardiovascular diseases (CVD) or type 2 diabetes (T2DM) is still unclear., Methods: One thousand and forty-nine 71-years-old male subjects from the Swedish ULSAM study, mean follow-up 9 years. All subjects performed the euglycemic insulin clamp for M/I [glucose disposal/mean insulin], and 75-g oral glucose tolerance test for Ceder-IR: 1/glucose uptake rate/[mean glucose×log mean insulin]; Matsuda-IR: 1/10,000/square root [glucose0×insulin0×glucose120×insulin120]; Belfiore-IR: 1/([glucose0+glucose120]/normal mean glucose×[insulin0+insulin120]/normal mean insulin)+1); and HOMA-IR: [glucose0×insulin0]/22.5., Results: Bland-Altman plots showed best agreement between M/I versus Belfiore-IR and Ceder-IR with mean difference near zero, -0.21 to -0.46, while -0.68 to -0.77 for the other indexes. ISI-Ceder was the strongest predictor for incident nonfatal/fatal ischemic heart disease (CHD) or CVD at Cox regression in all subjects, and for incident T2DM at logistic regression in 1024 subjects with no baseline T2DM, with significantly higher hazard ratios or odds ratios than with all other indexes, also with best model fit, after adjusting for clinical characteristics and the traditional cardiovascular risk factors, including metabolic syndrome for CVD risk., Conclusion: Ceder-IR performed strongest as independent predictor for incidences of CHD/CVD and T2DM., (Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.)

The adipocyte-secreted protein adiponectin is associated with insulin sensitivity in observational studies. We aimed to evaluate whether this relationship is causal using a Mendelian randomization approach. In a sample of Swedish men aged 71 years (n = 942) from the Uppsala Longitudinal Study of Adult Men (ULSAM), insulin sensitivity (M/I ratio) was measured by the euglycemic insulin clamp. We used three genetic variants in the ADIPOQ locus as instrumental variables (IVs) to estimate the potential causal effect of adiponectin on insulin sensitivity and compared these with results from conventional linear regression. The three ADIPOQ variants, rs17300539, rs3774261, and rs6444175, were strongly associated with serum adiponectin levels (all P ≤ 5.3 × 10(-9)) and were also significantly associated with M/I ratio in the expected direction (all P ≤ 0.022). IV analysis confirmed that genetically determined adiponectin increased insulin sensitivity (β = 0.47-0.81, all P ≤ 0.014) comparable with observational estimates (β = 0.50, all P(difference) ≥ 0.136). Adjustment for BMI and waist circumference partly explained the association of both genetically determined and observed adiponectin levels with insulin sensitivity. The observed association between higher adiponectin levels and increased insulin sensitivity is likely to represent a causal relationship partly mediated by reduced adiposity.

Introduction: Seasonal variations in hemoglobin-A1c have been reported in diabetic patients, but the underlying mechanisms have not been elucidated., Aims: To study if insulin sensitivity, insulin secretion, and fasting plasma glucose showed seasonal variations in a Swedish population-based cohort of elderly men., Methods: Altogether 1117 men were investigated with a euglycemic insulin clamp and measurements of fasting plasma glucose and insulin secretion after an oral glucose tolerance test. Values were analyzed in linear regression models with an indicator variable for winter/summer season and outdoor temperature as predictors., Results: During winter, insulin sensitivity (M/I, unit = 100 × mg × min(-1) × kg(-1)/(mU × L(-1))) was 11.0% lower (4.84 versus 5.44, P = 0.0003), incremental area under the insulin curve was 16.4% higher (1167 versus 1003 mU/L, P = 0.007). Fasting plasma glucose was, however, not statistically significantly different (5.80 versus 5.71 mmol/L, P = 0.28) compared to the summer season. There was an association between outdoor temperature and M/I (0.57 units increase (95% CI 0.29-0.82, P < 0.0001) per 10°C increase of outdoor temperature) independent of winter/summer season. Adjustment for life-style factors, type 2 diabetes, and medication did not alter these results., Conclusions: Insulin sensitivity showed seasonal variations with lower values during the winter and higher during the summer season. Inverse compensatory variations of insulin secretion resulted in only minor variations of fasting plasma glucose. Insulin sensitivity was associated with outdoor temperature. These phenomena should be further investigated in diabetic patients.

Aim: To investigate the relationships of serum fatty acid (FA) composition and estimated desaturase activities with the liver fat marker alanine aminotransferase (ALT)., Methods: 546 Swedish elderly men of a population-based cohort participated in this cross-sectional study. FA composition was assessed in serum cholesterol esters to determine dietary fat quality (e.g. linoleic) and desaturation products (e.g. dihomo-gamma-linolenic acid). Desaturase indices, including stearoyl coenzymeA desaturase-1 (SCD-1), were calculated by FA product-to-precursor ratios., Results: In linear regression analyses adjusting for lifestyle, abdominal obesity and insulin sensitivity, the dietary biomarker linoleic acid (n-6), but not n-3 FAs, was inversely related to ALT. Desaturation products including palmitoleic, oleic, gamma-linolenic and dihomo-gamma-linolenic acids, and Delta6-desaturase and SCD-1 indices were directly related to ALT (all p<0.05). After further adjustment for factors previously linked to fatty liver (i.e. serum lipids, adiponectin concentrations), SCD-1 index (p=0.004) and insulin resistance (p<0.0001) were independent determinants of ALT activity, whereas waist circumference, triglycerides, non-esterified FA and adiponectin were not., Conclusion: A low dietary intake of linoleic acid and elevated SCD-1 index may contribute to higher ALT activity in elderly men, even independently of obesity and insulin resistance.

Background: Impaired acute insulin response (AIR) and insulin resistance (IR) are characteristics of Type 2 diabetes (T2DM). The aim was to develop risk models for T2DM and impaired fasting glucose (IFG), reflecting estimates both of AIR and IR, and of their interaction, as predictors over 20 years of follow-up., Methods: We developed predictive models using hierarchic multiple regression analyses in a population-based cohort of 1227 men with normal fasting blood glucose at baseline (1970-73) and were reinvestigated after 10 and after 20 years. Using IVGTT-variables correlated either to AIR or to IR, separate models were developed. Combined models were also estimated from which prediction scores, representing individual risk, were calculated., Results: In combined models, interaction between prediction scores reflecting AIR and IR predicted T2DM and IFG. Lowest tertile of AIR and the highest tertile of IR showed a relative risk (RR) of 15.3 (95%-CI=5.58-41.84) for T2DM compared to the contrast group (high AIR and low IR). Corresponding RR for IFG was 13.23 (95%-CI=6.53-26.78). C-statistic increased from 0.76 to 0.79 (p=0.018) for T2DM and from 0.77 to 0.80 for IFG (p=0.062) taking interaction into account. Main effects of lowest tertile of AIR and highest tertile of IR versus best were: RR for T2DM, 8.80 (95%-CI=4.25-18.21) and 6.31 (95%-CI=3.26-12.21); for IFG, 9.07, (95%-CI=5.38-15.29) and 4.49 (95%-CI=2.98-6-76)., Conclusion: The interaction between low AIR and high IR revealed a high relative risk for T2DM or IFG reflecting the interplay between these factors over long time on worsening glucose tolerance and development of manifest disease.

Context: Diabetes and obesity are established risk factors for congestive heart failure (CHF) and are both associated with insulin resistance., Objective: To explore if insulin resistance may predict CHF and may provide the link between obesity and CHF., Design, Setting, and Participants: The Uppsala Longitudinal Study of Adult Men, a prospective, community-based, observational cohort in Uppsala, Sweden. We investigated 1187 elderly (>or=70 years) men free from CHF and valvular disease at baseline between 1990 and 1995, with follow-up until the end of 2002. Variables reflecting insulin sensitivity (including euglycemic insulin clamp glucose disposal rate) and obesity were analyzed together with established risk factors (prior myocardial infarction, hypertension, diabetes, electrocardiographic left ventricular hypertrophy, smoking, and serum cholesterol level) as predictors of subsequent incidence of CHF, using Cox proportional hazards analyses., Main Outcome Measure: First hospitalization for heart failure., Results: One hundred four men developed CHF during a median follow-up of 8.9 (range, 0.01-11.4) years. In multivariable Cox proportional hazards models adjusted for established risk factors for CHF, increased risk of CHF was associated with a 1-SD increase in the 2-hour glucose value of an oral glucose tolerance test (hazard ratio [HR], 1.44; 95% confidence interval [CI], 1.08-1.93), fasting serum proinsulin level (HR, 1.29; 95% CI, 1.02-1.64), body mass index (HR, 1.35; 95% CI, 1.11-1.65), and waist circumference (HR, 1.36; 95% CI, 1.10-1.69), whereas a 1-SD increase in clamp glucose disposal rate decreased the risk (HR, 0.66; 95% CI, 0.51-0.86). When adding clamp glucose disposal rate to these models as a covariate, the obesity variables were no longer significant predictors of subsequent CHF., Conclusions: Insulin resistance predicted CHF incidence independently of established risk factors including diabetes in our large community-based sample of elderly men. The previously described association between obesity and subsequent CHF may be mediated largely by insulin resistance.

Objective: It is clinically important to find noninvasive markers of insulin resistance and hyperproinsulinemia because they both predict cardiovascular and diabetes risk. Sagittal abdominal diameter (SAD) or "supine abdominal height" is a simple anthropometric measure previously shown to predict mortality in men, but its association with insulin resistance and hyperproinsulinemia is unknown., Research Design and Methods: In a common high-risk group of 59 moderately obese men (aged 35-65 years, BMI 32.6 +/- 2.3 kg/m(2)), we determined anthropometry (SAD, BMI, waist girth, and waist-to-hip ratio [WHR]); insulin sensitivity (euglycemic-hyperinsulinemic clamp); and plasma concentrations of intact proinsulin, specific insulin, C-peptide, glucose, and serum IGF binding protein-1 (IGFBP-1). To compare SAD with other anthropometric measures, univariate and multiple regression analyses were used to determine correlations between anthropometric and metabolic variables., Results: SAD showed stronger correlations to all measured metabolic variables, including insulin sensitivity, than BMI, waist girth, and WHR. SAD explained the largest degree of variation in insulin sensitivity (R(2) = 0.38, P < 0.0001) compared with other anthropometric measures. In multiple regression analyses, including all anthropometric measures, SAD was the only independent anthropometric predictor of insulin resistance (P < 0.001) and hyperproinsulinemia (P < 0.001)., Conclusions: In obese men, SAD seems to be a better correlate of insulin resistance and hyperproinsulinemia (i.e., cardiovascular risk) than other anthropometric measures. In overweight and obese individuals, SAD could represent a simple, cheap, and noninvasive tool that could identify the most insulin resistant in both the clinic and clinical trials evaluating insulin sensitizers. These results need confirmation in larger studies that also include women and lean subjects.

Objective: Defects in insulin secretion and insulin action are the major abnormalities in the development of type 2 diabetes. In middle-aged subjects, elevated plasma proinsulin has been found to predict type 2 diabetes. Therefore, our aim was to study the longitudinal relationships between baseline determinations of insulin sensitivity index (S(i)) assessed by euglycemic insulin clamp, the early insulin response (EIR) at an oral glucose tolerance test (OGTT), fasting intact proinsulin, 32-33 split proinsulin and specific insulin, and the development of type 2 diabetes in a population-based cohort of 70-year-old nondiabetic men (n = 667) with 7-year follow-up., Research Design and Methods: A euglycemic insulin clamp study and a 75-g OGTT were performed at baseline, and fasting peptide concentrations were measured using specific two-site immunometric assays. Results from logistic regression models are presented as odds ratios (ORs) with 95% CIs for a 1-SD increase in the predictor variable., Results: In separate multivariate analyses adjusted for EIR (OR 0.72, 95% CI 0.59-0.89) and S(i) (0.68, 0.58-0.88), 32-33 split proinsulin (1.49, 1.18-1.88) or intact proinsulin (1.30, 1.04-1.63) were significantly associated with the development of type 2 diabetes, whereas specific insulin (1.24, 0.91-1.66) was not. The significant associations between 32-33 split or intact proinsulin and the development of type 2 diabetes were unaltered after adjustment for BMI and glucose tolerance., Conclusions: Insulin propeptides predicted type 2 diabetes over a 7-year period in elderly men, independent of the EIR and S(i).

The adipocyte-secreted protein adiponectin is associated with insulin sensitivity in observational studies. We aimed to evaluate whether this relationship is causal using a Mendelian randomization approach. In a sample of Swedish men aged 71 years (n = 942) from the Uppsala Longitudinal Study of Adult Men (ULSAM), insulin sensitivity (M/I ratio) was measured by the euglycemic insulin clamp. We used three genetic variants in the ADIPOQ locus as instrumental variables (IVs) to estimate the potential causal effect of adiponectin on insulin sensitivity and compared these with results from conventional linear regression. The three ADIPOQ variants, rs17300539, rs3774261, and rs6444175, were strongly associated with serum adiponectin levels (all P ≤ 5.3 3 10-9) and were also significantly associated with M/I ratio in the expected direction (all P ≤ 0.022). IV analysis confirmed that genetically determined adiponectin increased insulin sensitivity (β = 0.47-0.81, all P ≤ 0.014) comparable with observational estimates (β = 0.50, all Pdifference ≥ 0.136). Adjustment for BMI and waist circumference partly explained the association of both genetically determined and observed adiponectin levels with insulin sensitivity. The observed association between higher adiponectin levels and increased insulin sensitivity is likely to represent a causal relationship partly mediated by reduced adiposity. [ABSTRACT FROM AUTHOR]

OBJECTIVE--Phthalates are ubiquitous industrial high-volume chemicals known as ligands to peroxisome proliferator--activated receptors (PPARs). Because PPAR-γ agonists modulate insulin sensitivity and are used to treat type 2 diabetes, we investigated whether circulating levels of phthalate metabolites are related to prevalent type 2 diabetes. RESEARCH DESIGN AND METHODS--A total of 1,016 subjects, aged 70 years, were investigated in the Prospective Investigation of the Vasculature in Uppsala Seniors Study. Four phthalate metabolites were detected in almost all participant sera by an API 4000 liquid chromatograph/tandem mass spectrometer. Type 2 diabetes was defined as the use of pharmacological hypoglycemic agents or a fasting plasma glucose >7.0 mmol/L. RESULTS--A total of 114 subjects were shown to have diabetes. Following adjustment for sex, BMI, serum cholesterol and triglycerides, educational level, and smoking and exercise habits, high levels of the phthalate metabolites monomethyl phthalate (MMP) (P < 0.01), monoisobutyl phthalate (MiBP) (P <0.05), and monoethyl phthalate (MEP) (P <0.05), but not mono(2-ethylhexyl) phthalate, were associated with an increased prevalence of diabetes. Using the fasting proinsulin--to--insulin ratio as amarker of insulin secretion and the homeostasis model assessment-insulin resistance index as a marker of insulin resistance, MiBP was mainly related to poor insulin secretion, whereas MEP and MMP mainly were related to insulin resistance. CONCLUSIONS--The findings in this cross-sectional study showed that several phthalate metabolites are related to diabetes prevalence, as well as to markers of insulin secretion and resistance. These findings support the view that these commonly used chemicals might influence major factors that are regulating glucose metabolism in humans at the level of exposure of phthalate metabolites seen in the general elderly population. [ABSTRACT FROM AUTHOR]

Reports on the results of epidemiological and clinical studies on insulin resistance and diabetes. Relationships between muscle morphology and insulin resistance; Left ventricular hypertrophy; Cognitive function.

The article presents the results of a case study regarding the risk associated with the metabolic syndrome versus the sum of its individual components. The study found that metabolic syndrome did not provide risk information above and beyond its individual components. The metabolic syndrome predicts mortality independently of established cardiovascular risk factors and may thus merit attention in the clinical setting. The metabolic syndrome might be viewed as a clinically handy summary measure of nontraditional risk factors rather than as a strong biological entity.

This letter replies to Dr. Stefan and colleagues who commented on the authors' study on insulin resistance and congestive heart failure and mentions adiponectin deficiency.

Aims Assessing the association between BMI and risk of coronary heart disease (CHD), cardiovascular disease (CVD) and mortality in patients with type 2 diabetes, also with regard to higher or lower levels of the ratio triglycerides-to-HDL-cholesterol (TG:HDL). Methods 54,061 patients with BMI ≥ 18.5 kg/m 2 , mean age and duration 61.5 ± 8 and 6.9 ± 6 years, 59% males, 14% with CVD history, from the Swedish National Diabetes Register, followed for mean 4.8 years. Results Adjusting at Cox regression for non-BMI-linked (age, sex, smoking, CVD history) and BMI-linked (blood lipids, blood pressure, HbA1c, albuminuria) covariates, hazard ratios (HR) for fatal/nonfatal CHD and CVD were mainly increased with prominent obesity (BMI ≥ 35 kg/m 2 ), 1.19 ( p = 0.01) and 1.17 ( p = 0.009), compared to normal weight (BMI 18.5–24.9 kg/m 2 ), although increased also with obesity (BMI 30–34.9 kg/m 2 ), 1.34 and 1.30 ( p < 0.001), when adjusting only for non-BMI-linked covariates. Stratifying by 75th percentile of TG:HDL, with normal weight and TG:HDL < 1.9 as reference, obese and prominently obese with TG:HDL ≥ 1.9 had considerably increased HR around 1.7 for fatal/nonfatal CHD and 1.6 for CVD ( p < 0.001), while obese and prominently obese with TG:HDL < 1.9 only had HR 1.2–1.3 for CHD and CVD ( p 0.003–<0.01). Conclusion Obese T2D patients with high TG:HDL, associated with increased insulin resistance, had considerably increased risk of CHD and CVD. [ABSTRACT FROM AUTHOR]