Quantifying the improvement of surrogate indices of hepatic insulin resistance using complex measurement techniques

We evaluated the ability of simple and complex surrogate-indices to identify individuals from an overweight/obese cohort with hepatic insulin-resistance (HEP-IR). Five indices, one previously defined and four newly generated through step-wise linear regression, were created against a single-cohort sample of 77 extensively characterised participants with the metabolic syndrome (age 55.6±1.0 years, BMI 31.5±0.4 kg/m2; 30 males). HEP-IR was defined by measuring endogenous-glucose-production (EGP) with [6–62H2] glucose during fasting and euglycemic-hyperinsulinemic clamps and expressed as EGP*fasting plasma insulin. Complex measures were incorporated into the model, including various non-standard biomarkers and the measurement of body-fat distribution and liver-fat, to further improve the predictive capability of the index. Validation was performed against a data set of the same subjects after an isoenergetic dietary intervention (4 arms, diets varying in protein and fiber content versus control). All five indices produced comparable prediction of HEP-IR, explaining 39–56% of the variance, depending on regression variable combination. The validation of the regression equations showed little variation between the different proposed indices (r2 = 27–32%) on a matched dataset. New complex indices encompassing advanced measurement techniques offered an improved correlation (r = 0.75, P<0.001). However, when validated against the alternative dataset all indices performed comparably with the standard homeostasis model assessment for insulin resistance (HOMA-IR) (r = 0.54, P<0.001). Thus, simple estimates of HEP-IR performed comparable to more complex indices and could be an efficient and cost effective approach in large epidemiological investigations

Risk-taking, thinking styles, and criminality: A fuzzy-trace theory perspective

Preferred modes of thinking, otherwise known as biases, have been well documented in adult reasoning and decision-making (Evans, 2003; Gilovich, Griffin, & Kahneman, 2002; Reyna & Brainerd, 2011; Tversky & Kahneman, 1986). Researchers have explained these biases by proposing that the basis for them is a system of thought that relies mostly on intuition and “gut feelings” rather than logical analysis of the situation (Reyna & Brainerd, 2011; Tversky & Kahneman, 1986). According to standard dual-process theories, intuition is described as a thought process so quick, it is automatic and, at times unconscious; conversely, analytical thinking is slow and steady, involving analysis and conscious deliberation (Reyna & Brainerd, 2011). Though several dual-process models for cognition have been proposed, including system 1/system 2, prototype/willingness, and the hot/cold empathy gap, only fuzzy-trace theory offers concrete predictions concerning development that are consistent with known data (Kruglanski & Gigerenzer, 2011; Reyna & Casillas, 2009). For example, research has shown that adults display greater reasoning biases than children, in that adults are more likely than children to process and use extraneous information, such as inconsequential differences in wording, in their decisions (Jacobs & Potenza, 1991; Reyna & Ellis, 1994). Of interest for the current study, fuzzy-trace theory posits that different ways of processing lead to different outcomes in risk-taking behavior. Further, fuzzy-trace theory proposes a framework that explains how risk perception changes across the lifespan and how these changes often lead to less risk-taking from childhood and adolescence into adulthood (Reyna, 2012; Reyna et al., 2018; Reyna & Adam, 2003; Reyna & Farley, 2006)

Nonsuppressed Glucagon After Glucose Challenge as a Potential Predictor for Glucose Tolerance

Glucagon levels are classically suppressed after glucose challenge. It is still not clear as to whether a lack of suppression contributes to hyperglycemia and thus to the development of diabetes. We investigated the association of postchallenge change in glucagon during oral glucose tolerance tests (OGTTs), hypothesizing that higher postchallenge glucagon levels are observed in subjects with impaired glucose tolerance (IGT). Glucagon levels were measured during OGTT in a total of 4,194 individuals without diabetes in three large European cohorts. Longitudinal changes in glucagon suppression were investigated in 50 participants undergoing a lifestyle intervention. Only 66-79% of participants showed suppression of glucagon at 120 min (fold change glucagon(120/0)Peer reviewe

Association between abdominal adiposity and subclinical measures of left-ventricular remodeling in diabetics, prediabetics and normal controls without history of cardiovascular disease as measured by magnetic resonance imaging: results from the KORA-FF4 Study

Objectives: Local, abdominal fat depots may be related to alterations in cardiac function and morphology due to a metabolic linkage. Thus, we aimed to determine their association with subtle cardiac changes and the potential interaction with hyperglycemic metabolic states. Methods: Subjects from the general population and without history of cardiovascular disease were drawn from the Cooperative Health Research in the Region of Augsburg FF4 cohort and underwent 3 T cardiac and body MRI. Measures of abdominal adiposity such as hepatic proton-density fat fraction [PDFFhepatic], subcutaneous (SAT) and visceral abdominal fat (VAT) as well as established cardiac left-ventricular (LV) measures including LV remodeling index (LVCI) were derived. Associations were determined using linear regression analysis based on standard deviation normalized predictors. Results: Among a total of 374 subjects (56.2 ± 9.1 years, 58% males), 49 subjects had diabetes, 99 subjects had prediabetes and 226 represented normal controls. Only subtle cardiac alterations were observed (e.g. LVCI: 1.13 ± 0.30). While SAT was not associated, increasing VAT and increasing PDFFhepatic were independently associated with increasing LVCI (β = 0.11 and 0.06, respectively), decreasing LV end-diastolic volume (β = − 6.70 and 3.23, respectively), and decreasing LV stroke volume (β = − 3.91 and − 2.20, respectively). Hyperglycemic state did not modify the associations between VAT or PDFF and LV measures (interaction term: all p ≥ 0.29). Conclusion: In a healthy population, VAT but also PDFFhepatic were associated with subclinical measures of LV remodeling without evidence for a modifying effect of hyperglycemic state

Impact of the Adipokine Adiponectin and the Hepatokine Fetuin-A on the Development of Type 2 Diabetes: Prospective Cohort- and Cross-Sectional Phenotyping Studies

Background: Among adipokines and hepatokines, adiponectin and fetuin-A were consistently found to predict the incidence of type 2 diabetes, both by regulating insulin sensitivity. Objective: To determine to what extent circulating adiponectin and fetuin-A are independently associated with incident type 2 diabetes in humans, and the major mechanisms involved. Methods: Relationships with incident diabetes were tested in two cohort studies: within the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam study (628 cases) and the Nurses' Health Study (NHS; 470 cases). Relationships with body fat compartments, insulin sensitivity and insulin secretion were studied in the Tübingen Lifestyle Intervention Program (TULIP; N = 358). Results: Circulating adiponectin and fetuin-A, independently of several confounders and of each other, associated with risk of diabetes in EPIC-Potsdam (RR for 1 SD: adiponectin: 0.45 [95% CI 0.37–0.54], fetuin-A: 1.18 [1.05–1.32]) and the NHS (0.51 [0.42–0.62], 1.35 [1.16–1.58]). Obesity measures considerably attenuated the association of adiponectin, but not of fetuin-A. Subjects with low adiponectin and concomitantly high fetuin-A had the highest risk. Whereas both proteins were independently (both p<1.8×10−7) associated with insulin sensitivity, circulating fetuin-A (r = −0.37, p = 0.0004), but not adiponectin, associated with insulin secretion in subjects with impaired glucose tolerance. Conclusions: We provide novel information that adiponectin and fetuin-A independently of each other associate with the diabetes risk. Furthermore, we suggest that they are involved in the development of type 2 diabetes via different mechanisms, possibly by mediating effects of their source tissues, expanded adipose tissue and nonalcoholic fatty liver

Investigating A Dose Response Relationship between High Fat Diet Consumption and the Contractile Performance of Isolated Mouse Soleus, EDL and Diaphragm Muscles

PurposeRecent evidence has demonstrated an obesity-induced, skeletal muscle-specific reduction in contractile performance. The extent and magnitude of these changes in relation to total dose of high-fat diet consumption remains unclear. This study aimed to examine the dose–response relationship between a high-fat diet and isolated skeletal muscle contractility.Methods120 female CD1 mice were randomly assigned to either control group or groups receiving 2, 4, 8 or 12 weeks of a high-calorie diet (N = 24). At 20 weeks, soleus, EDL or diaphragm muscle was isolated (n = 8 in each case) and isometric force, work loop power output and fatigue resistance were measured.ResultsWhen analysed with respect to feeding duration, there was no effect of diet on the measured parameters prior to 8 weeks of feeding. Compared to controls, 8-week feeding caused a reduction in normalised power of the soleus, and 8- and 12-week feeding caused reduced normalised isometric force, power and fatigue resistance of the EDL. Diaphragm from the 12-week group produced lower normalised power, whereas 8- and 12-week groups produced significantly lower normalised isometric force. Correlation statistics indicated that body fat accumulation and decline in contractility will be specific to the individual and independent of the feeding duration.ConclusionThe data indicate that a high-fat diet causes a decline in muscle quality with specific contractile parameters being affected in each muscle. We also uniquely demonstrate that the amount of fat gain, irrespective of feeding duration, may be the main factor in reducing contractile performance

Body fat MRS

The increasing levels of obesity, and its associated comorbidities, have prompted a reassessment of the techniques used for assessing body fat, including content, distribution, and composition. Magnetic resonance spectroscopy (MRS) is one among the many invaluable in vivo tools available today to evaluate the role of body fat in health and disease. However, although MRS has become a powerful technique for assessing ectopic fat in vivo, it has had limited use in other areas of research associated with body fat. MRS has found some success as a fast method to determine whole body adiposity in rodent models of disease, as well as a noninvasive method of obtaining an index of the overall composition of body fat in human subjects. Its more significant use has been in the understanding of bone marrow fat content, where important advances have been made, especially in longitudinal studies. In conclusion, in the area of body fat, MRS continues to be an adjunct technique to more precise and versatile MRI methods

Validation of a fast method for quantification of intra-abdominal and subcutaneous adipose tissue for large-scale human studies

Central obesity is the hallmark of a number of non-inheritable disorders. The advent of imaging techniques such asMRI has allowed for a fast and accurate assessment of body fat content and distribution. However, image analysis continues to be one of the major obstacles to the use of MRI in large-scale studies. In this study we assess the validity of the recently proposed fat–muscle quantitation system (AMRATM Profiler) for the quantification of intra-abdominal adipose tissue (IAAT) and abdominal subcutaneous adipose tissue (ASAT) from abdominal MR images. Abdominal MR images were acquired from 23 volunteers with a broad range of BMIs and analysed using sliceOmatic, the current gold-standard, and the AMRATM Profiler based on a non-rigid image registration of a library of segmented atlases. The results show that there was a highly significant correlation between the fat volumes generated by the two analysis methods, (Pearson correlation r = 0.97, p < 0.001), with the AMRATM Profiler analysis being significantly faster (~3 min) than the conventional sliceOmatic approach (~40 min). There was also excellent agreement between the methods for the quantification of IAAT (AMRA 4.73 ± 1.99 versus sliceOmatic 4.73 ± 1.75 l, p = 0.97). For the AMRATM Profiler analysis, the intra-observer coefficient of variation was 1.6% for IAAT and 1.1% for ASAT, the inter-observer coefficient of variationwas 1.4%for IAAT and 1.2%for ASAT, the intra-observer correlationwas 0.998 for IAAT and 0.999 for ASAT, and the inter-observer correlation was 0.999 for both IAAT and ASAT. These results indicate that precise and accurate measures of body fat content and distribution can be obtained in a fast and reliable form by the AMRATM Profiler, opening up the possibility of large-scale human phenotypic studies

Metabolism and metabolomics by MRS

The main use of magnetic resonance spectroscopy (MRS) is for the assessment of metabolism in vivo; that is because it has the unique ability to monitor metabolism noninvasively without the use of ionizing radiation. In recent years, MRS has also become widely used for metabolomics, the science that aspires to monitor the metabolome – the totality of small-molecule metabolites in an organism, a cell, or a disease. This article discusses the properties of MRS that make it suitable for metabolomic studies and the reasons why such studies are mainly performed ex vivo, as well as the methods used for preparing samples, performing the MRS and analyzing the resulting data. Further sections discuss MRS detection of metabolic aspects of the common cellular processes apoptosis, necrosis, and autophagy. The final section summarizes metabolic studies of some diseases by MRS: cancer, cardiovascular disease, neurological and neurodegenerative diseases, and muscle disease.This is the author accepted manuscript. The final version is available from Wiley via http://dx.doi.org/10.1002/9780470034590.emrstm146

Feasibility of MR-Based Body Composition Analysis in Large Scale Population Studies

Introduction Quantitative and accurate measurements of fat and muscle in the body are important for prevention and diagnosis of diseases related to obesity and muscle degeneration. Manually segmenting muscle and fat compartments in MR body-images is laborious and time-consuming, hindering implementation in large cohorts. In the present study, the feasibility and success-rate of a Dixon-based MR scan followed by an intensity-normalised, non-rigid, multi-atlas based segmentation was investigated in a cohort of 3,000 subjects. Materials and Methods 3,000 participants in the in-depth phenotyping arm of the UK Biobank imaging study underwent a comprehensive MR examination. All subjects were scanned using a 1.5 T MR-scanner with the dual-echo Dixon Vibe protocol, covering neck to knees. Subjects were scanned with six slabs in supine position, without localizer. Automated body composition analysis was performed using the AMRA Profiler™ system, to segment and quantify visceral adipose tissue (VAT), abdominal subcutaneous adipose tissue (ASAT) and thigh muscles. Technical quality assurance was performed and a standard set of acceptance/rejection criteria was established. Descriptive statistics were calculated for all volume measurements and quality assurance metrics. Results Of the 3,000 subjects, 2,995 (99.83%) were analysable for body fat, 2,828 (94.27%) were analysable when body fat and one thigh was included, and 2,775 (92.50%) were fully analysable for body fat and both thigh muscles. Reasons for not being able to analyse datasets were mainly due to missing slabs in the acquisition, or patient positioned so that large parts of the volume was outside of the field-of-view. Discussion and Conclusions In conclusion, this study showed that the rapid UK Biobank MR-protocol was well tolerated by most subjects and sufficiently robust to achieve very high success-rate for body composition analysis. This research has been conducted using the UK Biobank Resource