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Background & Aims MRI-based corrected T1 (cT1) is a non-invasive method to grade the severity of steatohepatitis and liver fibrosis. We aimed to identify genetic variants influencing liver cT1 and use genetics to understand mechanisms underlying liver fibroinflammatory disease and its link with other metabolic traits and diseases. Methods First, we performed a genome-wide association study (GWAS) in 14,440 Europeans, with liver cT1 measures, from the UK Biobank. Second, we explored the effects of the cT1 variants on liver blood tests, and a range of metabolic traits and diseases. Third, we used Mendelian randomisation to test the causal effects of 24 predominantly metabolic traits on liver cT1 measures. Results We identified 6 independent genetic variants associated with liver cT1 that reached the GWAS significance threshold (p, Graphical abstract, Highlights • Variants in metal ion transporter and NAFLD genes are associated with liver MRI-derived cT1, a steatohepatitis and fibrosis proxy. • cT1 is highly heritable, and is correlated with BMI, NAFLD and VLDL, and inversely correlated with HDL. • Insulin resistance, NAFLD and higher BMI are genetically linked to higher liver cT1, whilst favourable adiposity is linked to lower cT1.

SummaryPeople with schizophrenia show higher risk for abdominal obesity than the general population, which could contribute to excess mortality. However, it is unclear whether this is driven by alterations in abdominal fat partitioning. Here, we test the hypothesis that individuals with schizophrenia show a higher proportion of visceral to total body fat measured using MRI. We recruited 38 patients with schizophrenia and 38 healthy controls matched on age, sex, ethnicity and body mass index. We found no significant difference in body fat distribution between groups, suggesting that increased abdominal obesity in schizophrenia is not associated with altered fat distribution.

Type 2 diabetes (T2D) and non-alcoholic fatty liver disease (NAFLD) often co-occur. Defining causal pathways underlying this relationship may help optimize the prevention and treatment of both diseases. Thus, we assessed the strength and magnitude of the putative causal pathways linking dysglycemia and fatty liver, using a combination of causal inference methods.Measures of glycemia, insulin dynamics, magnetic resonance imaging (MRI)-derived abdominal and liver fat content, serological biomarkers, lifestyle, and anthropometry were obtained in participants from the IMI DIRECT cohorts (n=795 with new onset T2D and 2234 individuals free from diabetes). UK Biobank (n=3641) was used for modelling and replication purposes. Bayesian networks were employed to infer causal pathways, with causal validation using two-sample Mendelian randomization.Bayesian networks fitted to IMI DIRECT data identified higher basal insulin secretion rate (BasalISR) and MRI-derived excess visceral fat (VAT) accumulation as the features of dysmetabolism most likely to cause liver fat accumulation; the unconditional probability of fatty liver (>5%) increased significantly when conditioning on high levels of BasalISR and VAT (by 23%, 32% respectively; 40% for both). Analyses in UK Biobank yielded comparable results. MR confirmed most causal pathways predicted by the Bayesian networks.Here, BasalISR had the highest causal effect on fatty liver predisposition, providing mechanistic evidence underpinning the established association of NAFLD and T2D. BasalISR may represent a pragmatic biomarker for NAFLD prediction in clinical practice.

Aims/hypothesis It is well established that physical activity, abdominal ectopic fat and glycaemic regulation are related but the underlying structure of these relationships is unclear. The previously proposed twin-cycle hypothesis (TC) provides a mechanistic basis for impairment in glycaemic control through the interactions of substrate availability, substrate metabolism and abdominal ectopic fat accumulation. Here, we hypothesise that the effect of physical activity in glucose regulation is mediated by the twin-cycle. We aimed to examine this notion in the Innovative Medicines Initiative Diabetes Research on Patient Stratification (IMI DIRECT) Consortium cohorts comprised of participants with normal or impaired glucose regulation (cohort 1: N ≤ 920) or with recently diagnosed type 2 diabetes (cohort 2: N ≤ 435). Methods We defined a structural equation model that describes the TC and fitted this within the IMI DIRECT dataset. A second model, twin-cycle plus physical activity (TC-PA), to assess the extent to which the effects of physical activity in glycaemic regulation are mediated by components in the twin-cycle, was also fitted. Beta cell function, insulin sensitivity and glycaemic control were modelled from frequently sampled 75 g OGTTs (fsOGTTs) and mixed-meal tolerance tests (MMTTs) in participants without and with diabetes, respectively. Abdominal fat distribution was assessed using MRI, and physical activity through wrist-worn triaxial accelerometry. Results are presented as standardised beta coefficients, SE and p values, respectively. Results The TC and TC-PA models showed better fit than null models (TC: χ2 = 242, p = 0.004 and χ2 = 63, p = 0.001 in cohort 1 and 2, respectively; TC-PA: χ2 = 180, p = 0.041 and χ2 = 60, p = 0.008 in cohort 1 and 2, respectively). The association of physical activity with glycaemic control was primarily mediated by variables in the liver fat cycle. Conclusions/interpretation These analyses partially support the mechanisms proposed in the twin-cycle model and highlight mechanistic pathways through which insulin sensitivity and liver fat mediate the association between physical activity and glycaemic control.

Accurate, automated quantitative segmentation of anatomical structures in radiological scans, such as Magnetic Resonance Imaging (MRI) and Computer Tomography (CT), can produce significant biomarkers and can be integrated into computer-aided diagnosis (CADx) systems to support the interpretation of medical images from multi-protocol scanners. However, there are serious challenges towards developing robust automated segmentation techniques, including high variations in anatomical structure and size, varying image spatial resolutions resulting from different scanner protocols, and the presence of blurring artefacts. This paper presents a novel computing approach for automated organ and muscle segmentation in medical images from multiple modalities by harnessing the advantages of deep learning techniques in a two-part process. (1) a 3D encoder-decoder, Rb-UNet, builds a localisation model and a 3D Tiramisu network generates a boundary-preserving segmentation model for each target structure; (2) the fully trained Rb-UNet predicts a 3D bounding box encapsulating the target structure of interest, after which the fully trained Tiramisu model performs segmentation to reveal organ or muscle boundaries for every protrusion and indentation. The proposed approach is evaluated on six different datasets, including MRI, Dynamic Contrast Enhanced (DCE) MRI and CT scans targeting the pancreas, liver, kidneys and iliopsoas muscles. We achieve quantitative measures of mean Dice similarity coefficient (DSC) that surpasses or are comparable with the state-of-the-art and demonstrate statistical stability. A qualitative evaluation performed by two independent experts in radiology and radiography verified the preservation of detailed organ and muscle boundaries.

To understand the consequences of higher adiposity uncoupled from its adverse metabolic effects, we selected 37 diseases associated with obesity and genetic variants associated with different aspects of excess weight including metabolically “favourable adiposity” (FA) and “unfavourable adiposity” (UFA). Mendelian randomisation (MR) identified two sets of diseases. First, 12 conditions where the metabolic effect of higher adiposity is the likely primary cause of the disease. Here MR with the FA and UFA genetics showed opposing effects on the risk of disease, including colorectal and ovarian cancer, and gout. Second, 7 conditions where the non-metabolic effects of excess weight (e.g. mechanical effect) is likely a cause. Here MR with the FA genetics, despite leading to lower metabolic risk, and MR with the UFA genetics, were both associated with higher disease risk, including osteoarthritis and venous thromboembolism. Individuals with high BMI are at higher risk of some diseases despite being relatively metabolically healthy.

To understand the causal role of adiposity and ectopic fat in type 2 diabetes and cardiometabolic diseases, we aimed to identify two clusters of adiposity genetic variants: one with “adverse” metabolic effects (UFA) and the other with, paradoxically, “favorable” metabolic effects (FA). We performed a multivariate genome-wide association study using body fat percentage and metabolic biomarkers from UK Biobank and identified 38 UFA and 36 FA variants. Adiposity-increasing alleles were associated with an adverse metabolic profile, higher risk of disease, higher CRP, and higher fat in subcutaneous and visceral adipose tissue, liver, and pancreas for UFA and a favorable metabolic profile, lower risk of disease, higher CRP and higher subcutaneous adipose tissue but lower liver fat for FA. We detected no sexual dimorphism. The Mendelian randomization studies provided evidence for a risk-increasing effect of UFA and protective effect of FA for type 2 diabetes, heart disease, hypertension, stroke, nonalcoholic fatty liver disease, and polycystic ovary syndrome. FA is distinct from UFA by its association with lower liver fat and protection from cardiometabolic diseases; it was not associated with visceral or pancreatic fat. Understanding the difference in FA and UFA may lead to new insights in preventing, predicting, and treating cardiometabolic diseases.

OBJECTIVE We investigated the processes underlying glycemic deterioration in type 2 diabetes (T2D). RESEARCH DESIGN AND METHODS A total of 732 recently diagnosed patients with T2D from the Innovative Medicines Initiative Diabetes Research on Patient Stratification (IMI DIRECT) study were extensively phenotyped over 3 years, including measures of insulin sensitivity (OGIS), β-cell glucose sensitivity (GS), and insulin clearance (CLIm) from mixed meal tests, liver enzymes, lipid profiles, and baseline regional fat from MRI. The associations between the longitudinal metabolic patterns and HbA1c deterioration, adjusted for changes in BMI and in diabetes medications, were assessed via stepwise multivariable linear and logistic regression. RESULTS Faster HbA1c progression was independently associated with faster deterioration of OGIS and GS and increasing CLIm; visceral or liver fat, HDL-cholesterol, and triglycerides had further independent, though weaker, roles (R2 = 0.38). A subgroup of patients with a markedly higher progression rate (fast progressors) was clearly distinguishable considering these variables only (discrimination capacity from area under the receiver operating characteristic = 0.94). The proportion of fast progressors was reduced from 56% to 8–10% in subgroups in which only one trait among OGIS, GS, and CLIm was relatively stable (odds ratios 0.07–0.09). T2D polygenic risk score and baseline pancreatic fat, glucagon-like peptide 1, glucagon, diet, and physical activity did not show an independent role. CONCLUSIONS Deteriorating insulin sensitivity and β-cell function, increasing insulin clearance, high visceral or liver fat, and worsening of the lipid profile are the crucial factors mediating glycemic deterioration of patients with T2D in the initial phase of the disease. Stabilization of a single trait among insulin sensitivity, β-cell function, and insulin clearance may be relevant to prevent progression.

Cardiometabolic diseases are an increasing global health burden. While socioeconomic, environmental, behavioural, and genetic risk factors have been identified, a better understanding of the underlying mechanisms is required to develop more effective interventions. Magnetic resonance imaging (MRI) has been used to assess organ health, but biobank-scale studies are still in their infancy. Using over 38,000 abdominal MRI scans in the UK Biobank, we used deep learning to quantify volume, fat, and iron in seven organs and tissues, and demonstrate that imaging-derived phenotypes reflect health status. We show that these traits have a substantial heritable component (8–44%) and identify 93 independent genome-wide significant associations, including four associations with liver traits that have not previously been reported. Our work demonstrates the tractability of deep learning to systematically quantify health parameters from high-throughput MRI across a range of organs and tissues, and use the largest-ever study of its kind to generate new insights into the genetic architecture of these traits.

It is well established that physical activity, abdominal ectopic fat and glycaemic regulation are related but the underlying structure of these relationships is unclear. The previously proposed twin-cycle hypothesis (TC) provides a mechanistic basis for impairment in glycaemic control through the interactions of substrate availability, substrate metabolism and abdominal ectopic fat accumulation. Here, we hypothesise that the effect of physical activity in glucose regulation is mediated by the twin-cycle. We aimed to examine this notion in the Innovative Medicines Initiative Diabetes Research on Patient Stratification (IMI DIRECT) Consortium cohorts comprised of participants with normal or impaired glucose regulation (cohort 1: N ≤ 920) or with recently diagnosed type 2 diabetes (cohort 2: N ≤ 435).We defined a structural equation model that describes the TC and fitted this within the IMI DIRECT dataset. A second model, twin-cycle plus physical activity (TC-PA), to assess the extent to which the effects of physical activity in glycaemic regulation are mediated by components in the twin-cycle, was also fitted. Beta cell function, insulin sensitivity and glycaemic control were modelled from frequently sampled 75 g OGTTs (fsOGTTs) and mixed-meal tolerance tests (MMTTs) in participants without and with diabetes, respectively. Abdominal fat distribution was assessed using MRI, and physical activity through wrist-worn triaxial accelerometry. Results are presented as standardised beta coefficients, SE and p values, respectively.The TC and TC-PA models showed better fit than null models (TC: χThese analyses partially support the mechanisms proposed in the twin-cycle model and highlight mechanistic pathways through which insulin sensitivity and liver fat mediate the association between physical activity and glycaemic control.

Psoas muscle measurements are frequently used as markers of sarcopenia and predictors of health. Manually measured cross-sectional areas are most commonly used, but there is a lack of consistency regarding the position of the measurementand manual annotations are not practical for large population studies. We have developed a fully automated method to measure iliopsoas muscle volume (comprised of the psoas and iliacus muscles) using a convolutional neural network. Magnetic resonance images were obtained from the UK Biobank for 5,000 male and female participants, balanced for age, gender and BMI. Ninety manual annotations were available for model training and validation. The model showed excellent performance against out-of-sample data (dice score coefficient of 0.912 +/- 0.018). Iliopsoas muscle volumes were successfully measured in all 5,000 participants. Iliopsoas volume was greater in male compared with female subjects. There was a small but significant asymmetry between left and right iliopsoas muscle volumes. We also found that iliopsoas volume was significantly related to height, BMI and age, and that there was an acceleration in muscle volume decrease in men with age. Our method provides a robust technique for measuring iliopsoas muscle volume that can be applied to large cohorts., Julie Fitzpatrick and Nicolas Basty are joint first authors

Cardiometabolic diseases are an increasing global health burden. While well established socioeconomic, environmental, behavioural, and genetic risk factors have been identified, our understanding of the drivers and mechanisms underlying these complex diseases remains incomplete. A better understanding is required to develop more effective therapeutic interventions. Magnetic resonance imaging (MRI) has been used to assess organ health in a number of studies, but large-scale population-based studies are still in their infancy. Using 38,683 abdominal MRI scans in the UK Biobank, we used deep learning to systematically quantify parameters from individual organs (liver, pancreas, spleen, kidneys, lungs and adipose depots), and demonstrate that image derived phenotypes (volume, fat and iron content) reflect organ health and disease. We show that these traits have a substantial heritable component (8%-44%), and identify 93 independent genome-wide significant associations, including 3 associations with liver fat and one with liver iron that have not previously been reported, and 73 in traits that have not previously been studied. Overall our work demonstrates the utility of deep learning to systematically quantify health parameters from high-throughput MRI across a range of organs and tissues of the abdomen, and to generate new insights into the genetic architecture of complex traits.

Objective Differences in the content and distribution of body fat and ectopic lipids may be responsible for ethnic variations in metabolic disease susceptibility. The aim of this study was to examine the ethnic distribution of body fat in two separate UK-based populations. Methods Anthropometry and body composition were assessed in two separate UK cohorts: the Hammersmith cohort and the UK Biobank, both comprising individuals of South Asian descent (SA), individuals of Afro-Caribbean descent (AC), and individuals of European descent (EUR). Regional adipose tissue stores and liver fat were measured by magnetic resonance techniques. Results The Hammersmith cohort (n = 747) had a mean (SD) age of 41.1 (14.5) years (EUR: 374 men, 240 women; SA: 68 men, 22 women; AC: 14 men, 29 women), and the UK Biobank (n = 9,533) had a mean (SD) age of 55.5 (7.5) years (EUR: 4,483 men, 4,873 women; SA: 80 men, 43 women, AC: 31 men, 25 women). Following adjustment for age and BMI, no significant differences in visceral adipose tissue or liver fat were observed between SA and EUR individuals in the either cohort. Conclusions Our data, consistent across two independent UK-based cohorts, present a limited number of ethnic differences in the distribution of body fat depots associated with metabolic disease. These results suggest that the ethnic variation in susceptibility to features of the metabolic syndrome may not arise from differences in body fat.

Nonalcoholic fatty liver disease (NAFLD) is characterized by low-circulating concentration of high-density lipoprotein cholesterol (HDL-C) and raised triacylglycerol (TAG). Exercise reduces hepatic fat content, improves insulin resistance and increases clearance of very-low-density lipoprotein-1 (VLDL1). However, the effect of exercise on TAG and HDL-C metabolism is unknown. We randomized male participants to 16 wk of supervised, moderate-intensity aerobic exercise ( n = 15), or conventional lifestyle advice ( n = 12). Apolipoprotein A-I (apoA-I) and VLDL-TAG and apolipoprotein B (apoB) kinetics were investigated using stable isotopes (1-[13C]-leucine and 1,1,2,3,3-2H5 glycerol) pre- and postintervention. Participants underwent MRI/spectroscopy to assess changes in visceral fat. Results are means ± SD. At baseline, there were no differences between exercise and control groups for age (52.4 ± 7.5 vs. 52.8 ± 10.3 yr), body mass index (BMI: 31.6 ± 3.2 vs. 31.7 ± 3.6 kg/m2), and waist circumference (109.3 ± 7.5 vs. 110.0 ± 13.6 cm). Percentage of liver fat was 23.8 (interquartile range 9.8–32.5%). Exercise reduced body weight (101.3 ± 10.2 to 97.9 ± 12.2 kg; P < 0.001) and hepatic fat content [from 19.6%, interquartile range (IQR) 14.6–36.1% to 8.9% (4.4–17.8%); P = 0.001] and increased the fraction HDL-C concentration (measured following ultracentrifugation) and apoA-I pool size with no change in the control group. However, plasma and VLDL1-TAG concentrations and HDL-apoA-I fractional catabolic rate (FCR) and production rate (PR) did not change significantly with exercise. Both at baseline (all participants) and after exercise there was an inverse correlation between apoA-I pool size and VLDL-TAG and -apoB pool size. The modest effect of exercise on HDL metabolism may be explained by the lack of effect on plasma and VLDL1-TAG.

We present an automated method for estimation of proton density fat fraction and iron concentration in the pancreas using both structural and quantitative imaging data present in the UK Biobank abdominal MRI acquisition protocol. Our method relies on automatic segmentation of 3D T1-weighted MRI data using a convolutional neural network and extracting the location of the multi -echo slice through the segmented volume. We finally estimate the fat and iron content in the pancreas using the extracted segmentation as a mask on the multi-echo data. Our segmentation model achieves a mean dice similarity coefficient of 0.842±0.071 on unseen data, which is comparable to the current state of the art for 3D segmentation of the pancreas. The proposed method is efficient and robust and enables an enhanced analysis of spatial distribution of proton density fat fraction and iron concentration over the current practice of manually placing regions of interest on often ambiguous multi-echo data.

BackgroundNon-alcoholic fatty liver disease (NAFLD) is highly prevalent and causes serious health complications in type 2 diabetes (T2D) and beyond. Early diagnosis of NAFLD is important, as this can help prevent irreversible damage to the liver and ultimately hepatocellular carcinomas.Methods and FindingsUtilizing the baseline data from the IMI DIRECT participants (n=1514) we sought to expand etiological understanding and develop a diagnostic tool for NAFLD using machine learning. Multi-omic (genetic, transcriptomic, proteomic, and metabolomic) and clinical (liver enzymes and other serological biomarkers, anthropometry, and measures of beta-cell function, insulin sensitivity, and lifestyle) data comprised the key input variables. The models were trained on MRI image-derived liver fat content (ConclusionsWe have developed clinically useful liver fat prediction models (see:www.predictliverfat.org) and identified biological features that appear to affect liver fat accumulation.

Aim Gut microbial dysbiosis is implicated in the pathogenesis of non-alcoholic steatohepatitis (NASH). We investigated downstream effects of gut microbiota modulation on markers of hepatic inflammation, steatosis, and hepatic and peripheral insulin sensitivity in patients with NASH using rifaximin therapy. Methods Patients with biopsy-proven NASH and elevated aminotransferase values were included in this open-label pilot study, all receiving 6 weeks rifaximin 400 mg twice daily, followed by a 6-week observation period. The primary endpoint was change in alanine aminotransferase (ALT) after 6 weeks of rifaximin. Secondary endpoints were change in hepatic lipid content and insulin sensitivity measured with a hyperinsulinemic–euglycemic clamp. Results Fifteen patients (13 men and 2 women) with a median (range) age of 46 (32–63) years were included. Seven had diabetes on oral hypoglycemic medications and 8 had no diabetes. After 6 weeks of therapy, no differences were seen in ALT (55 [33–191] vs. 63 [41–218] IU/L, P = 0.41), peripheral glucose uptake (28.9 [19.4–48.3] to 25.5 [17.7–47.9] μmol/kg/min, P = 0.30), hepatic insulin sensitivity (35.2 [15.3–51.7]% vs. 30.0 [10.8–50.5]%, P = 0.47), or hepatic lipid content (21.6 [2.2–46.2]% vs. 24.8 [1.7–59.3]%, P = 0.59) before and after rifaximin treatment. After 12 weeks from baseline, serum ALT increased to 83 (30–217) IU/L, P = 0.02. There was a significant increase in the homeostasis model assessment–estimated insulin resistance index (P = 0.05). The urinary metabolic profile indicated a significant reduction in urinary hippurate with treatment, which reverted to baseline after cessation of rifaximin, although there was no consistent difference in relative abundance of fecal microbiota with treatment. Conclusion These data do not indicate a beneficial effect of rifaximin in patients with NASH.

Aims/hypothesis Here, we describe the characteristics of the Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) epidemiological cohorts at baseline and follow-up examinations (18, 36 and 48 months of follow-up). Methods From a sampling frame of 24,682 adults of European ancestry enrolled in population-based cohorts across Europe, participants at varying risk of glycaemic deterioration were identified using a risk prediction algorithm (based on age, BMI, waist circumference, use of antihypertensive medication, smoking status and parental history of type 2 diabetes) and enrolled into a prospective cohort study (n = 2127) (cohort 1, prediabetes risk). We also recruited people from clinical registries with type 2 diabetes diagnosed 6–24 months previously (n = 789) into a second cohort study (cohort 2, diabetes). Follow-up examinations took place at ~18 months (both cohorts) and at ~48 months (cohort 1) or ~36 months (cohort 2) after baseline examinations. The cohorts were studied in parallel using matched protocols across seven clinical centres in northern Europe. Results Using ADA 2011 glycaemic categories, 33% (n = 693) of cohort 1 (prediabetes risk) had normal glucose regulation and 67% (n = 1419) had impaired glucose regulation. Seventy-six per cent of participants in cohort 1 was male. Cohort 1 participants had the following characteristics (mean ± SD) at baseline: age 62 (6.2) years; BMI 27.9 (4.0) kg/m2; fasting glucose 5.7 (0.6) mmol/l; 2 h glucose 5.9 (1.6) mmol/l. At the final follow-up examination the participants’ clinical characteristics were as follows: fasting glucose 6.0 (0.6) mmol/l; 2 h OGTT glucose 6.5 (2.0) mmol/l. In cohort 2 (diabetes), 66% (n = 517) were treated by lifestyle modification and 34% (n = 272) were treated with metformin plus lifestyle modification at enrolment. Fifty-eight per cent of participants in cohort 2 was male. Cohort 2 participants had the following characteristics at baseline: age 62 (8.1) years; BMI 30.5 (5.0) kg/m2; fasting glucose 7.2 (1.4) mmol/l; 2 h glucose 8.6 (2.8) mmol/l. At the final follow-up examination, the participants’ clinical characteristics were as follows: fasting glucose 7.9 (2.0) mmol/l; 2 h mixed-meal tolerance test glucose 9.9 (3.4) mmol/l. Conclusions/interpretation The IMI DIRECT cohorts are intensely characterised, with a wide-variety of metabolically relevant measures assessed prospectively. We anticipate that the cohorts, made available through managed access, will provide a powerful resource for biomarker discovery, multivariate aetiological analyses and reclassification of patients for the prevention and treatment of type 2 diabetes. Electronic supplementary material The online version of this article (10.1007/s00125-019-4906-1) contains peer-reviewed but unedited supplementary material, which is available to authorised users.

The accurate 3D reconstruction of organs from radiological scans is an essential tool in computer-aided diagnosis (CADx) and plays a critical role in clinical, biomedical and forensic science research. The structure and shape of the organ, combined with morphological measurements such as volume and curvature, can provide significant guidance towards establishing progression or severity of a condition, and thus support improved diagnosis and therapy planning. Furthermore, the classification and stratification of organ abnormalities aim to explore and investigate organ deformations following injury, trauma and illness. This paper presents a framework for automatic morphological feature extraction in computer-aided 3D organ reconstructions following organ segmentation in 3D radiological scans. Two different magnetic resonance imaging (MRI) datasets are evaluated. Using the MRI scans of 85 adult volunteers, the overall mean volume for the pancreas organ is 69.30 ± 32.50cm3, and the 3D global curvature is (35.23 ± 6.83) × 10−3. Another experiment evaluates the MRI scans of 30 volunteers, and achieves mean liver volume of 1547.48 ± 204.19cm3 and 3D global curvature (19.87 ± 3.62) × 10− 3. Both experiments highlight a negative correlation between 3D curvature and volume with a statistical difference (p

The problem of classifying subjects into risk categories is a common challenge in medical research. Machine Learning (ML) methods are widely used in the areas of risk prediction and classification. The primary objective of these algorithms is to predict dichotomous responses (e.g. healthy/at risk) based on several features. Similarly to statistical inference models, also ML models are subject to the common problem of class imbalance. Therefore, they are affected by the majority class increasing the false-negative rate. In this paper, we built and evaluated eighteen ML models classifying approximately 4300 female participants from the UK Biobank into three categorical risk statuses based on responses for the discretised visceral adipose tissue values from magnetic resonance imaging. We also examined the effect of sampling techniques on classification modelling when dealing with class imbalance. Results showed that the use of sampling techniques had a significant impact. They not only drove an improvement in predicting patients risk status but also facilitated an increase in the information contained within each variable. Based on domain experts criteria, the three best models for classification were finally identified. These encouraging results will guide further developments of classification models for predicting visceral adipose tissue without the need for a costly scan.

Computing pancreatic morphology in 3D radiological scans could provide significant insight about a medical condition. However, segmenting the pancreas in magnetic resonance imaging (MRI) remains challenging due to high inter-patient variability. Also, the resolution and speed of MRI scanning present artefacts that blur the pancreas boundaries between overlapping anatomical structures. This paper proposes a dual-stage automatic segmentation method: (1) a deep neural network is trained to address the problem of vague organ boundaries in high class-imbalanced data. This network integrates a novel loss function to rigorously optimise boundary delineation using the modified Hausdorff metric and a sinusoidal component; (2) Given a test MRI volume, the output of the trained network predicts a sequence of targeted 2D pancreas classes that are reconstructed as a volumetric binary mask. An energy-minimisation approach fuses a learned digital contrast model to suppress the intensities of non-pancreas classes, which, combined with the binary volume performs a refined segmentation in 3D while revealing dense boundary detail. Experiments are performed on two diverse MRI datasets containing 180 and 120 scans, in which the proposed approach achieves a mean Dice score of 84.1 ± 4.6% and 85.7 ± 2.3%, respectively. This approach is statistically stable and outperforms state-of-the-art methods on MRI.

The burden of liver disease continues to increase in the UK, with liver cirrhosis reported to be the third most common cause of premature death. Iron overload, a condition that impacts liver health, was traditionally associated with genetic disorders such as hereditary haemochromatosis, however, it is now increasingly associated with obesity, type-2 diabetes and non-alcoholic fatty liver disease. The aim of this study was to assess the prevalence of elevated levels of liver iron within the UK Biobank imaging study in a cohort of 9108 individuals. Magnetic resonance imaging (MRI) was undertaken at the UK Biobank imaging centre, acquiring a multi-echo spoiled gradient-echo single-breath-hold MRI sequence from the liver. All images were analysed for liver iron and fat (expressed as proton density fat fraction or PDFF) content using LiverMultiScan. Liver iron was measured in 97.3% of the cohort. The mean liver iron content was 1.32 ± 0.32 mg/g while the median was 1.25 mg/g (min: 0.85 max: 6.44 mg/g). Overall 4.82% of the population were defined as having elevated liver iron, above commonly accepted 1.8 mg/g threshold based on biochemical iron measurements in liver specimens obtained by biopsy. Further analysis using univariate models showed elevated liver iron to be related to male sex (p5.6% PDFF) was associated with a slight increase in prevalence of elevated liver iron (4.4% vs 6.3%, p = 0.0007). This study shows that population studies including measurement of liver iron concentration are feasible, which may in future be used to better inform patient stratification and treatment.

Acyl-ghrelin administration increases food intake, body weight, and blood glucose. In contrast, mice lacking ghrelin or ghrelin receptors (GHSRs) exhibit life-threatening hypoglycemia during starvation-like conditions, but do not consistently exhibit overt metabolic phenotypes when given ad libitum food access. These results, and findings of ghrelin resistance in obese states, imply nutritional state dependence of ghrelin's metabolic actions. Here, we hypothesized that liver-enriched antimicrobial peptide-2 (LEAP2), a recently characterized endogenous GHSR antagonist, blunts ghrelin action during obese states and postprandially. To test this hypothesis, we determined changes in plasma LEAP2 and acyl-ghrelin due to fasting, eating, obesity, Roux-en-Y gastric bypass (RYGB), vertical sleeve gastrectomy (VSG), oral glucose administration, and type 1 diabetes mellitus (T1DM) using humans and/or mice. Our results suggest that plasma LEAP2 is regulated by metabolic status: its levels increased with body mass and blood glucose and decreased with fasting, RYGB, and in postprandial states following VSG. These changes were mostly opposite of those of acyl-ghrelin. Furthermore, using electrophysiology, we showed that LEAP2 both hyperpolarizes and prevents acyl-ghrelin from activating arcuate NPY neurons. We predict that the plasma LEAP2/acyl-ghrelin molar ratio may be a key determinant modulating acyl-ghrelin activity in response to body mass, feeding status, and blood glucose.

Recent genetic studies have identified alleles associated with opposite effects on adiposity and risk of type 2 diabetes. We aimed to identify more of these variants and test the hypothesis that such “favourable adiposity” alleles are associated with higher subcutaneous fat and lower ectopic fat. We combined magnetic resonance imaging (MRI) data with genome-wide association studies (GWAS) of body fat % and metabolic traits. We report 14 alleles, including 7 newly characterized alleles, associated with higher adiposity, but a favourable metabolic profile. Consistent with previous studies, individuals carrying more “favourable adiposity” alleles had higher body fat % and higher BMI, but lower risk of type 2 diabetes, heart disease and hypertension. These individuals also had higher subcutaneous fat, but lower liver fat and lower visceral-to-subcutaneous adipose tissue ratio. Individual alleles associated with higher body fat % but lower liver fat and lower risk of type 2 diabetes included those in PPARG, GRB14 and IRS1, whilst the allele in ANKRD55 was paradoxically associated with higher visceral fat but lower risk of type 2 diabetes. Most identified “favourable adiposity” alleles are associated with higher subcutaneous and lower liver fat, a mechanism consistent with the beneficial effects of storing excess triglyceride in metabolically low risk depots. Diabetes UK RD Lawrence fellowship, European Research Council, Wellcome Trust and Royal Society grant, European Regional Development Fund, Medical Research Council, German Federal Ministry of Education and Research, German Research Foundation, Innovative Medicines Initiative Joint Undertaking, European Union's Seventh Framework Programme, Dutch Science Organisation, Scottish Government Health Directorates, Scottish Funding Council and Medical Research Council UK and the Wellcome Trust.

/SummaryBackground and aims:Understanding the aetiology, clinical presentation and prognosis of type 2 diabetes (T2D) and optimizing its treatment might be facilitated by biomarkers that help predict a person’s susceptibility to the risk factors that cause diabetes or its complications, or response to treatment. The IMI DIRECT (Diabetes Research on Patient Stratification) Study is a European Union (EU) Innovative Medicines Initiative (IMI) project that seeks to test these hypotheses in two recently established epidemiological cohorts. Here, we describe the characteristics of these cohorts at baseline and at the first main follow-up examination (18-months).Materials and methods:From a sampling-frame of 24,682 European-ancestry adults in whom detailed health information was available, participants at varying risk of glycaemic deterioration were identified using a risk prediction algorithm and enrolled into a prospective cohort study (n=2127) undertaken at four study centres across Europe (Cohort 1: prediabetes). We also recruited people from clinical registries with recently diagnosed T2D (n=789) into a second cohort study (Cohort 2: diabetes). The two cohorts were studied in parallel with matched protocols. Endogenous insulin secretion and insulin sensitivity were modelled from frequently sampled 75g oral glucose tolerance (OGTT) in Cohort 1 and with mixed-meal tolerance tests (MMTT) in Cohort 2. Additional metabolic biochemistry was determined using blood samples taken when fasted and during the tolerance tests. Body composition was assessed using MRI and lifestyle measures through self-report and objective methods.Results:Using ADA-2011 glycaemic categories, 33% (n=693) of Cohort 1 (prediabetes) had normal glucose regulation (NGR), and 67% (n=1419) had impaired glucose regulation (IGR). 76% of the cohort was male, age=62(6.2) years; BMI=27.9(4.0) kg/m2; fasting glucose=5.7(0.6) mmol/l; 2-hr glucose=5.9(1.6) mmol/l [mean(SD)]. At follow-up, 18.6(1.4) months after baseline, fasting glucose=5.8(0.6) mmol/l; 2-hr OGTT glucose=6.1(1.7) mmol/l [mean(SD)]. In Cohort 2 (diabetes): 65% (n=508) were lifestyle treated (LS) and 35% (n=271) were lifestyle + metformin treated (LS+MET). 58% of the cohort was male, age=62(8.1) years; BMI=30.5(5.0) kg/m2; fasting glucose=7.2(1.4)mmol/l; 2-hr glucose=8.6(2.8) mmol/l [mean(SD)]. At follow-up, 18.2(0.6) months after baseline, fasting glucose=7.8(1.8) mmol/l; 2-hr MMTT glucose=9.5(3.3) mmol/l [mean(SD)].Conclusion:The epidemiological IMI DIRECT cohorts are the most intensely characterised prospective studies of glycaemic deterioration to date. Data from these cohorts help illustrate the heterogeneous characteristics of people at risk of or with T2D, highlighting the rationale for biomarker stratification of the disease - the primary objective of the IMI DIRECT consortium.Abbreviations:ASATAbdominal subcutaneous adipose tissueDIRECTDiabetes Research on Patient StratificationEUEuropean UnionMMTTMixed-meal tolerance testMRIMagnetic resonance imaginghpfVMHigh-pass filtered vector magnitudeIAATIntra-abdominal adipose tissueIGRImpaired glucose regulationIMIInnovative Medicines InitiativeMEmultiechoNGRNormal glucose regulationOGTTOral glucose tolerance testPAPhysical activityTAATTotal abdominal adipose tissueT2DType 2 Diabetes

ObjectiveMethodsThis study aimed to investigate the value of imaging-based multivariable body composition profiling by describing its association with coronary heart disease (CHD), type 2 diabetes (T2D), and metabolic health on individual and population levels. The first 6,021 participants scanned by UK Biobank were included. Body composition profiles (BCPs) were calculated, including abdominal subcutaneous adipose tissue, visceral adipose tissue (VAT), thigh muscle volume, liver fat, and muscle fat infiltration (MFI), determined using magnetic resonance imaging. Associations between BCP and metabolic status were investigated using matching procedures and multivariable statistical modeling. ResultsConclusionsMatched control analysis showed that higher VAT and MFI were associated with CHD and T2D (Pamp;lt;0.001). Higher liver fat was associated with T2D (Pamp;lt;0.001) and lower liver fat with CHD (Pamp;lt;0.05), matching on VAT. Multivariable modeling showed that lower VAT and MFI were associated with metabolic health (Pamp;lt;0.001), and liver fat was nonsignificant. Associations remained significant adjusting for sex, age, BMI, alcohol, smoking, and physical activity. Body composition profiling enabled an intuitive visualization of body composition and showed the complexity of associations between fat distribution and metabolic status, stressing the importance of a multivariable approach. Different diseases were linked to different BCPs, which could not be described by a single fat compartment alone. Funding Agencies|Pfizer Inc.

Central obesity is the hallmark of a number of non-inheritable disorders. The advent of imaging techniques such as MRI 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 (AMRA(TM) 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 AMRA(TM) 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 AMRA(TM) 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 AMRA(TM) Profiler analysis, the intra-observer coefficient of variation was 1.6% for IAAT and 1.1% for ASAT, the inter-observer coefficient of variation was 1.4% for IAAT and 1.2% for ASAT, the intra-observer correlation was 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 AMRA(TM) Profiler, opening up the possibility of large-scale human phenotypic studies.

Non-alcoholic fatty liver disease (NAFLD) is a common diagnosis and is increasing in prevalence worldwide. NAFLD is usually asymptomatic at presentation; progression of the disease is unpredictable, leading to the development of a variety of techniques for screening, diagnosis and risk stratification. Clinical methods in current use include serum biomarker panels, hepatic ultrasound, magnetic resonance imaging, and liver biopsy. NAFLD is strongly associated with the metabolic syndrome, and the most common cause of death for people with the condition is cardiovascular disease. Whether NAFLD is an independent cardiovascular risk factor needs exploration. NAFLD has been associated with surrogate markers of cardiovascular disease such as carotid intima-media thickness, the presence of carotid plaque, brachial artery vasodilatory responsiveness and CT coronary artery calcification score. There is no effective medical treatment for NAFLD and evidence is lacking regarding the efficacy of interventions in mitigating cardiovascular risk. Health care professionals managing patients with NAFLD should tackle the issue with early identification of risk factors and aggressive modification. Current management strategies therefore comprise lifestyle change, with close attention to known cardiovascular risk factors.

In clinical practice, a misdiagnosis can lead to incorrect or delayed treatment, and in some cases, no treatment at all; consequently, the condition of a patient may worsen to varying degrees, in some cases proving fatal. The accurate 3D reconstruction of organs, which is a pioneering tool of medical image computing (MIC) technology, plays a key role in computer aided diagnosis (CADx), thereby enabling medical professionals to perform enhanced analysis on a region of interest. From here, the shape and structure of the organ coupled with measurements of its volume and curvature can provide significant guidance towards establishing the severity of a disorder or abnormality, consequently supporting improved diagnosis and treatment planning. Moreover, the classification and stratification of organ abnormalities is widely utilised within biomedical, forensic and MIC research for exploring and investigating organ deformations following injury, illness or trauma. This paper presents a tool that calculates, classifies and analyses pancreatic volume and curvature following their 3D reconstruction. Magnetic resonance imaging (MRI) volumes of 115 adult patients are evaluated in order to examine a correlation between these two variables. Such a tool can be utilised in the scope of much greater research and investigation. It can also be incorporated into the development of effective medical image analysis software application in the stratification of subjects and targeting of therapies.

Background: The effect of mode of infant feeding on adiposity deposition is not fully understood. Objective: The objective was to test the hypothesis that differences in total and regional adipose tissue content and intrahepatocellular lipid (IHCL) arise in early infancy between breast- and formula-fed infants and to describe longitudinal changes. Design: This prospective longitudinal cohort study was performed in 2 hospitals in the United Kingdom. Healthy, full-term, appropriate weight-for-gestational age infants were recruited; adipose tissue volume and distribution were directly quantified by using whole-body magnetic resonance imaging; IHCL was assessed by in vivo proton magnetic resonance spectroscopy. Measurements were performed after birth (median age: 13 d) and at 6–12 wk of age. Method of infant feeding was recorded prospectively by using maternally completed feeding diaries. Breastfed was defined as >80% of feeds consisting of breast milk at both points; formula-fed was defined as >80% of feeds consisting of formula milk at both points. Results: Longitudinal results were obtained from 70 infants (36 breastfed, 9 mixed-fed, and 25 formula-fed). No differences were found in total or regional adipose tissue or IHCL between breastfed and formula-fed infants. In pooled analyses including all feeding groups, IHCL and total adipose tissue approximately doubled between birth and 6–12 wk: IHCL after birth (median: 0.949; IQR: 0.521–1.711) and at 6–12 wk (1.828; 1.376–2.697; P < 0.001) and total adipose tissue after birth (0.749 L; 0.620–0.928 L) and at 6–12 wk (1.547 L; 1.332–1.790 L; P < 0.001). Increasing adiposity was characterized by greater relative increases in subcutaneous than in internal adipose tissue depots. Conclusions: No differences were detectable in adipose tissue or IHCL accretion between breastfed and formula-fed infants up to 2 mo. The substantial increase in IHCL seen over this period in both breastfed and formula-fed infants is a novel observation, which suggests that hepatic storage of lipids may be physiologic up to 2 mo. This trial was registered at www.clinicaltrials.gov as NCT02033005.

[This corrects the article DOI: 10.1371/journal.pone.0172921.].

OBJECTIVE Cannabidiol (CBD) and Δ9-tetrahydrocannabivarin (THCV) are nonpsychoactive phytocannabinoids affecting lipid and glucose metabolism in animal models. This study set out to examine the effects of these compounds in patients with type 2 diabetes. RESEARCH DESIGN AND METHODS In this randomized, double-blind, placebo-controlled study, 62 subjects with noninsulin-treated type 2 diabetes were randomized to five treatment arms: CBD (100 mg twice daily), THCV (5 mg twice daily), 1:1 ratio of CBD and THCV (5 mg/5 mg, twice daily), 20:1 ratio of CBD and THCV (100 mg/5 mg, twice daily), or matched placebo for 13 weeks. The primary end point was a change in HDL-cholesterol concentrations from baseline. Secondary/tertiary end points included changes in glycemic control, lipid profile, insulin sensitivity, body weight, liver triglyceride content, adipose tissue distribution, appetite, markers of inflammation, markers of vascular function, gut hormones, circulating endocannabinoids, and adipokine concentrations. Safety and tolerability end points were also evaluated. RESULTS Compared with placebo, THCV significantly decreased fasting plasma glucose (estimated treatment difference [ETD] = −1.2 mmol/L; P < 0.05) and improved pancreatic β-cell function (HOMA2 β-cell function [ETD = −44.51 points; P < 0.01]), adiponectin (ETD = −5.9 × 106 pg/mL; P < 0.01), and apolipoprotein A (ETD = −6.02 μmol/L; P < 0.05), although plasma HDL was unaffected. Compared with baseline (but not placebo), CBD decreased resistin (−898 pg/ml; P < 0.05) and increased glucose-dependent insulinotropic peptide (21.9 pg/ml; P < 0.05). None of the combination treatments had a significant impact on end points. CBD and THCV were well tolerated. CONCLUSIONS THCV could represent a new therapeutic agent in glycemic control in subjects with type 2 diabetes.

Plasma ghrelin is elevated in Prader-Willi syndrome (PWS). This might contribute to obesity or GH deficiency in such patients. Visceral adiposity and insulin resistance are reduced in PWS, which might lead to hyperghrelinemia. We measured fasting plasma ghrelin in control female (n = 39), PWS female (n = 12), and PWS male (n = 6) adults. In controls and PWS, ghrelin was negatively correlated with visceral adiposity, fasting insulin, and homeostasis model insulin resistance index. There was no significant correlation with serum IGF-I in PWS. In stepwise linear regression, visceral adiposity (P < 0.02) had a stronger inverse correlation with ghrelin than sc fat depots in controls and PWS, possibly through hyperinsulinemia, as the correlations with insulin resistance were even stronger (P < 0.01). PWS females had significantly (P < 0.001) elevated ghrelin (mean +/- SD, 661 +/- 360 pg/ml), compared with both nonobese (363 +/- 163) and obese (191 +/- 66) controls. Ghrelin was increased 3.4- to 3.6-fold in PWS females adjusting for total adiposity, 3.2- to 3.4-fold adjusting for visceral adiposity, and 3.0-fold adjusting for insulin resistance. Fasting plasma glucagon-like peptide-1 was normal in PWS females. The hyperghrelinemia in PWS adults is therefore not solely explained by their reduced visceral adiposity and relative hypoinsulinemia. Its cause and consequences await further elucidation.

The last few years have seen an increasing number of extremely preterm babies surviving to adulthood. The relationship between low birth weight, insulin resistance and Type 2 diabetes in adulthood is well established, but less is known regarding the effects of preterm birth on body composition and metabolic pathways. In this review, we consider the literature regarding the effects of prematurity on body composition in the neonatal period, infancy, childhood and adulthood. We also discuss prematurity and metabolic related changes including blood pressure and insulin resistance in later life. Although several studies suggest that ‘catch-up’ growth is the main factor influencing the risk of an adverse body composition and metabolic profile, there is growing evidence to indicate an independent effect of gestational age on liver fat content and blood pressure in adulthood. However, more research is needed regarding specific metabolic changes in adults born preterm.

Reduction in total lung capacity (TLC) in obese men is associated with restricted expansion of the thoracic cavity at full inflation. We hypothesized that thoracic expansion was reduced by the load imposed by increased total trunk fat volume or its distribution. Using MRI, we measured internal and subcutaneous trunk fat and total abdominal and thoracic volumes at full inflation in 14 obese men [mean age: 52.4 yr, body mass index (BMI): 38.8 (range: 36–44) kg/m2] and 7 control men [mean age: 50.1 yr, BMI: 25.0 (range: 22–27.5) kg/m2]. TLC was measured by multibreath helium dilution and was restricted (

Restriction of total lung capacity (TLC) is found in some obese subjects, but the mechanism is unclear. Two hypotheses are as follows: 1) increased abdominal volume prevents full descent of the diaphragm; and 2) increased intrathoracic fat reduces space for full lung expansion. We have measured total intrathoracic volume at full inflation using magnetic resonance imaging (MRI) in 14 asymptomatic obese men [mean age 52 yr, body mass index (BMI) 35–45 kg/m2] and 7 control men (mean age 50 yr, BMI 22–27 kg/m2). MRI volumes were compared with gas volumes at TLC. All measurements were made with subjects supine. Obese men had smaller functional residual capacity (FRC) and FRC-to-TLC ratio than control men. There was a 12% predicted difference in mean TLC between obese (84% predicted) and control men (96% predicted). In contrast, differences in total intrathoracic volume (MRI) at full inflation were only 4% predicted TLC (obese 116% predicted TLC, control 120% predicted TLC), because mediastinal volume was larger in obese than in control [heart and major vessels (obese 1.10 liter, control 0.87 liter, P = 0.016) and intrathoracic fat (obese 0.68 liter, control 0.23 liter, P < 0.0001)]. As a consequence of increased mediastinal volume, intrathoracic volume at FRC in obese men was considerably larger than indicated by the gas volume at FRC. The difference in gas volume at TLC between the six obese men with restriction, TLC < 80% predicted (OR), and the eight obese men with TLC > 80% predicted (ON) was 26% predicted TLC. Mediastinal volume was similar in OR (1.84 liter) and ON (1.73 liter), but total intrathoracic volume was 19% predicted TLC smaller in OR than in ON. We conclude that the major factor restricting TLC in some obese men was reduced thoracic expansion at full inflation.

Familial combined hyperlipidaemia (FCHL) is a complex genetic disorder conferring high risk of premature atherosclerosis, characterized by high cholesterol and/or triglyceride, low high density lipoprotein (HDL) cholesterol and insulin resistance. We examined whether pioglitazone, added to conventional lipid-lowering therapy, would favourably affect metabolic parameters and alter body fat content. We undertook a randomized, double blind, placebo-controlled study in 22 male patients with FCHL treated with pioglitazone or matching placebo 30 mg daily for 4 weeks, increasing to 45 mg for 12 weeks. Magnetic resonance imaging and proton magnetic resonance spectroscopy were performed to measure adipose tissue (AT) body content as well as intrahepatocellular lipids (IHCL) and intramyocellular lipids (IMCL) at baseline and after treatment. Significantly improved in the pioglitazone group were: triglyceride/HDL (atherogenic index of plasma) -32.3% (p=0.002), plasma glucose -4.4% (p=0.03), alanine-aminotransferase (ALT) -7.7% (p=0.005) and adiponectin 130.1% (p=0.001). Pioglitazone treatment resulted in a significant increase in total (5.3%, p=0.02) and subcutaneous (7.1%, p=0.003) adipose tissue as well as in soleus-IMCL levels (47.4%, p=0.02) without alteration in intra-abdominal AT or IHCL. Changes in ALT and AST and IHCL were strongly correlated (r=0.72, p

Objective. To test the hypothesis that oral creatine supplements with exercise are more effective than exercise alone in improving muscle function in patients with established dermatomyositis or polymyositis receiving chronic medical therapies who are clinically weak yet stable. Methods. In a 6-month, 2-center, double-blind, randomized controlled trial, patients were randomized to receive oral creatine supplements (8 days, 20 gm/day then 3 gm/day) or placebo. All patients followed a home exercise program. The primary outcome was aggregate functional performance time (AFPT), reflecting the ability to undertake high-intensity exercise. Secondary outcomes included a Functional index measuring endurance and muscle bioenergetics on P-31 magnetic resonance spectroscopy (P-31 MRS). Patients were receiving stable immunosuppressive treatment and/or corticosteroids. Results. A total of 37 patients with polymyositis or dermatomyositis were randomized (19 to creatine, 18 to placebo); 29 completed 6 months. Intent-to-treat analyses demonstrated that AFPT improved significantly at 6 months with creatine (median decrease 13%, range -32-8%) compared with placebo (median decrease 3%, range -13-16%; P = 0.029 by Mann-Whitney U test). A completer analysis also showed significant benefits from creatine (P = 0.014). The functional index improved significantly with both creatine and placebo (P < 0.05 by paired Wilcoxon's rank sum test), with a significant benefit between groups in the completer analysis only. Phosphocreatine/beta-nucleoside triphosphate ratios using MRS increased significantly in the creatine group (P < 0.05) but not in the control group. No clinically relevant adverse events were associated with creatine. Conclusion. Oral creatine supplements combined with home exercises improve functional performance without significant adverse effects in patients with polymyositis or dermatomyositis. They appear safe, effective, and inexpensive. (Less)

Objective: The colonic microbiota ferment dietary fibres, producing short chain fatty acids. Recent evidence suggests that the short chain fatty acid propionate may play an important role in appetite regulation. We hypothesised that colonic delivery of propionate would increase peptide YY (PYY) and glucagon like peptide-1 (GLP-1) secretion in humans, and reduce energy intake and weight gain in overweight adults.\ud \ud Design: To investigate whether propionate promotes PYY and GLP-1 secretion, a primary cultured human colonic cell model was developed. To deliver propionate specifically to the colon, we developed a novel inulin-propionate ester. An acute randomised, controlled cross-over study was used to assess the effects of this inulin-propionate ester on energy intake and plasma PYY and GLP-1 concentrations. The long-term effects of inulin-propionate ester on weight gain were subsequently assessed in a randomised, controlled 24-week study involving 60 overweight adults.\ud \ud Results: Propionate significantly stimulated the release of PYY and GLP-1 from human colonic cells. Acute ingestion of 10 g inulin-propionate ester significantly increased postprandial plasma PYY and GLP-1 and reduced energy intake. Over 24 weeks, 10 g/day inulin-propionate ester supplementation significantly reduced weight gain, intra-abdominal adipose tissue distribution, intrahepatocellular lipid content and prevented the deterioration in insulin sensitivity observed in the inulin-control group.\ud \ud Conclusions: These data demonstrate for the first time that increasing colonic propionate prevents weight gain in overweight adult humans.

1. The main purpose of this study was to evaluate non-invasively with magnetic resonance spectroscopy (1H-MRS) changes in the concentrations of intracellular (IT) and extracellular (between muscle fibres) triglycerides (ET) in skeletal muscles of trained males (age range: 24-38 years) during two standard exercise protocols of alternating velocities. 2. Protocol 1 consisted of locomotion in a shuttle manner between two lines 30 m apart at four different velocities (1, 2, 3, and 4 m s-1) which were alternated every minute in a standard routine for 90 min, whereas Protocol 2 included locomotion between two lines 20 m apart at only three velocities (2, 2.7 and 4 m s-1) until volitional exhaustion. The heart rate during both protocols fluctuated between 140 and 200 beats min-1. 3. Using pre-exercise muscle water to quantify individual total creatine (TCr) that was utilized as an internal standard and assuming that TCr does not change during exercise, subjects' mean IT and ET concentrations in soleus (Sol) muscle before Protocol 1 (n = 8) were 45.8 +/- 4.8 mmol (kg dry weight)-1 (mean +/- S.E.M.) and 93.1 +/- 14.1 mmol (kg dry weight)-1, respectively. After the exercise, the concentrations of IT and ET were not significantly different from the values at rest. Before Protocol 2 (n = 4), IT concentrations in Sol, gastrocnemius (Gast) and tibialis (Tib) muscles were 46.4 +/- 13.6, 35.0 +/- 12.1 and 23.1 +/- 4.8 mmol (kg dry weight)-1, respectively, and were not affected by the exhaustive exercise. The ET concentrations in Sol, Gast and Tib were 136.4 +/- 38.1, 175.3 +/- 86.5 and 79.3 +/- 20.0 mmol (kg dry weight)-1 respectively, and they did not change significantly after exhaustion. 4. The study showed that levels of IT and ET were not affected by alternating intensity exercise to fatigue. This suggests that IT and ET in human Sol, Gast and Tib muscles do not contribute significantly to the energy turnover during this type of exercise. Energy for this type of muscle contraction may arise primarily from muscle phosphocreatine (PCr) and glycogen breakdown, circulating glucose and fatty acids from triglycerides other than those encountered within and between muscle cells.

Objective:\ud To describe (1) the relationship between nutrition and the preterm-at-term infant phenotype, (2) phenotypic differences between preterm-at-term infants and healthy term born infants and (3) relationships between somatic and brain MRI outcomes.\ud \ud Design:\ud Prospective observational study.\ud \ud Setting:\ud UK tertiary neonatal unit.\ud \ud Participants:\ud Preterm infants (

If magnetic resonance spectroscopy (MRS) is to become a useful tool in clinical medicine, it will be necessary to find reliable methods for analyzing and classifying MRS data. Automated methods are desirable because they can remove user bias and can deal with large amounts of data, allowing the use of all the available information. In this study, techniques for automatically extracting features for the classification of MRS in vivo data are investigated. Among the techniques used were wavelets, principal component analysis, and linear discriminant function analysis. These techniques were tested on a set of 75 in vivo 13C spectra of human adipose tissue from subjects from three different dietary groups (vegan, vegetarian, and omnivore). It was found that it was possible to assign automatically 94% of the vegans and omnivores to their correct dietary groups, without the need for explicit identification or measurement of peaks.

Nonalcoholic fatty liver disease may be evident in women with polycystic ovary syndrome (PCOS), both conditions being associated with obesity and insulin resistance. However, few studies have accounted for the high prevalence of obesity in PCOS.The aim of this study was to determine whether PCOS is independently associated with hepatic steatosis, compared with healthy controls of similar age and body mass index (BMI), and whether steatosis is associated with hyperandrogenemia.We conducted a cross-sectional, case-control study at two tertiary referral centers.Twenty-nine women with PCOS diagnosed by the Rotterdam criteria [aged 28 yr; 95% confidence interval (CI), 26-31; BMI, 33 kg/m2; 95% CI, 31-36] and 22 healthy controls (aged 29 yr; 95% CI, 28-31; BMI, 30 kg/m2; 95% CI, 28-33) were studied.Proton-magnetic resonance spectroscopy quantified hepatic and skeletal muscle fat; whole body magnetic resonance imaging quantified internal, visceral, and sc adipose tissue volumes. Differences were assessed between PCOS and controls using t tests, and between hyperandrogenic (HA) PCOS, PCOS with normal androgens (NA), and controls using analysis of covariance.After statistical adjustment for BMI, HA-PCOS had significantly higher liver fat vs. NA-PCOS (3.7%; 95% CI, 0.6-13.1) and vs. controls (2.1%; 95% CI, 0.3-6.6). Similarly, after adjustment for homeostasis model assessment for insulin resistance, internal and visceral adipose tissue volumes, liver fat remained significantly greater in HA-PCOS compared to NA-PCOS and controls.These data suggest that HA-PCOS is associated with hepatic steatosis, independent of obesity and insulin resistance.

ObjectiveNon-alcoholic fatty liver disease (NAFLD) is reported to be more common in patients with GH deficiency (GHD) than in the general population. We aimed to determine: i) liver fat in patients with GHD compared with age and body mass index (BMI)-matched controls; and ii) effect of 6 months of GH replacement (GHR) on liver fat.Participants and methodsThe study included 28 GHD patients and 24 controls. 12 patients were studied before and after 6 months of GHR. Anthropometry, liver enzymes and lipid profiles were measured, and body composition and intrahepatocellular lipid (IHCL) were determined by magnetic resonance imaging and spectroscopy.ResultsAge and BMI (median (inter-quartile range)) of patients and controls were 52.6 (14) vs 52.6 (12) years (P=0.9) and 27.8 (24.7, 34.7) vs 27.9 (25.1, 32.1) kg/m2(P=0.9). IGF1 was lower in the patients (11.5 vs 16.0 nmol/l,P=0.002). There was no difference in liver transaminases, lipids or IHCL between patients and controls (2.8 (1.3, 8.6) vs 5.0 (1.5, 12.7),P=0.72), despite significantly higher visceral fat in GHD patients. Thirty-two percent of patients and 50% of controls had NAFLD (defined as IHCL >5.6%), and the relationship between IHCL and BMI was the same in each group. GHR significantly reduced abdominal subcutaneous and visceral fat in all patients; however, GHR did not reduce liver fat.ConclusionsNAFLD is equally common in patients with GHD and matched controls. GHR is associated with a hierarchical reduction in fat deposition (fat loss: visceral > subcutaneous > liver). Further studies involving GHD patients with NAFLD are required to conclude the role of GHR in treating NAFLD.

Liver disease is an increasing cause of morbidity and mortality worldwide. Currently, the gold standard for diagnosis and assessment of parenchymal disease is histopathological assessment of a percutaneous or transjugular liver biopsy. The risks and limitations of this technique are well recognized and as a result, significant effort has gone into the development of novel noninvasive methods of diagnosis and longitudinal assessment. Imaging techniques have improved significantly over the past decade and new technologies are beginning to enter clinical practice. Ultrasound, computed tomography and MRI are the main modalities currently used, but novel MRI-based techniques will have an increasing role. While there has been extensive research into the imaging of focal liver disease, the evidence base for imaging in diffuse disease has also undergone recent rapid development, particularly in the assessment of fibrosis and steatosis. Both of these abnormalities of the parenchyma can lead to cirrhosis and/or hepatocellular carcinoma and represent an important opportunity for detection of early liver disease. We discuss the recent advances in liver imaging techniques and their role in the diagnosis and monitoring of diffuse liver disease, with a focus on their current and potential clinical relevance and whether they may replace or augment liver biopsy. We also discuss techniques currently under development and their potential clinical applications in the future.

Abdominal adiposity and metabolic ill health in Asian Indians are a growing public health concern. Causal pathways are unknown. Preventive measures in adults have had limited success. The aim of this observational case-control study was to compare adipose tissue partitioning in 69 healthy full term Asian Indian and white European newborns born in Pune, India and London, UK, respectively. The main outcome measures were total and regional adipose tissue content measured by whole body magnetic resonance imaging. Although smaller in weight (95% CI for difference -0.757 to -0.385 kg, p < 0.001), head circumference (-2.15 to -0.9 cm, p < 0.001), and length (-2.9 to -1.1 cm p < 0.001), the Asian Indian neonates had significantly greater absolute adiposity in all three abdominal compartments, internal (visceral) (0.012-0.023 L, p < 0.001), deep s.c. (0.003-0.017 L, p = 0.006) and superficial s.c. (0.006-0.043 L, p = 0.011) and a significant reduction in nonabdominal superficial s.c. adipose tissue (-0.184 to -0.029 L, p = 0.008) in comparison to the white European babies despite similar whole body adipose tissue content (-0.175 to 0.034 L, p = 0.2). We conclude that differences in adipose tissue partitioning exist at birth. Investigative, screening, and preventive measures must involve maternal health, intrauterine life, and infancy.

AIM: To assess the effectiveness of the current UK clinical practice in reducing hepatic fat (IHCL). METHODS: Whole body MRI and 1H MRS were obtained, before and after 6 mo nutritional counselling, from liver, soleus and tibialis muscles in 10 subjects with non-alcoholic fatty liver disease (NAFLD). RESULTS: A 500 Kcal-restricted diet resulted in an average weight loss of 4% (-3.4 kg,) accompanied by significant reductions in most adipose tissue (AT) depots, including subcutaneous (-9.9%), abdominal subcutaneous (-10.2%) and intra-abdominal-AT (-11.4%). Intramyocellular lipids (IMCL) were significantly reduced in the tibialis muscle (-28.2%). Decreases in both IHCL (-39.9%) and soleus IMCL (-12.2%) content were also observed, although these were not significant. Several individuals showed dramatic decreases in IHCL, while others paradoxically showed increases in IHCL content. Changes in body composition were accompanied by improvements in certain liver function tests: serum aspartate aminotransferase (AST) and alanine aminotransferase (ALT). Significant correlations were found between decreases in IHCL and reductions in both intra-abdominal and abdominal subcutaneous AT. Improvements in liver function tests were associated with reductions in intra-abdominal AT, but not with changes in IHCL. CONCLUSION: This study shows that even a very modest reduction in body weight achieved through lifestyle modification can result in changes in body fat depots and improvements in LFTs.

The distribution and quantity of adipose tissue are markers of morbidity risk in children and adults. Poor intrauterine growth and accelerated postnatal growth are believed to add to these risks. The aim of this study was to assess adipose tissue content and distribution at birth and 6 wk in relation to intrauterine growth restriction, postnatal growth, and infant diet. We measured weight, length, and head circumference and adipose content and distribution using magnetic resonance imaging at 6 wk of age in appropriately grown for gestational age (AGA) and growth-restricted (GR) infants and compared this with birth data. By 6 wk, GR infants showed complete catch-up in comparison to AGA infants in relation to head growth and adiposity. Catch-up in length and weight was not complete. Accelerated linear growth, but not accelerated weight gain, was associated with a highly significant increase in adiposity (r = 0.57, p = 0.001) regardless of AGA/GR status. The highest adiposity at 6 wk, allowing for baseline variables and linear growth, was seen in exclusively breast-fed GR infants (mean, 95% confidence interval: 33.5%, 29.51-37.5). Adipose tissue distribution remained constant and was unrelated to growth and diet. Reduced birth adiposity (B = -0.185, p = 0.003), but not low birth head size (B = 0.32, p = 0.093), was a significant predictor of accelerated postnatal head growth (R(2) = 0.29, adjusted R(2) = 0.23, p = 0.012). Increasing adiposity appears to be an inevitable accompaniment of accelerated linear growth. Low total adipose tissue quantity at birth appears to direct nutrition toward head growth. Adipose tissue may be involved in the signaling of catch-up growth.

The quantity and distribution of adipose tissue are markers of morbidity risk. The third trimester of human development is a period of rapid adipose tissue deposition. Preterm infants may be at risk of altered adiposity. We measured anthropometric indices and quantified total, subcutaneous, and intraabdominal adipose tissue volumes using whole-body magnetic resonance adipose tissue imaging in 38 infants born at