Whole body fat: content and distribution

The association of cardiometabolic, diet and lifestyle parameters with plasma glucagon-like peptide-1: An IMI DIRECT study

CONTEXT

The role of glucagon-like peptide-1(GLP-1) in Type 2 diabetes (T2D) and obesity is not fully understood.

OBJECTIVE

We investigate the association of cardiometabolic, diet and lifestyle parameters on fasting and postprandial GLP-1 in people at risk of, or living with, T2D.

METHOD

We analysed cross-sectional data from the two Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) cohorts, cohort 1(n=2127) individuals at risk of diabetes; cohort 2 (n=789) individuals with new-onset of T2D.

RESULTS

Our multiple regression analysis reveals that fasting total GLP-1 is associated with an insulin resistant phenotype and observe a strong independent relationship with male sex, increased adiposity and liver fat particularly in the prediabetes population. In contrast, we showed that incremental GLP-1 decreases with worsening glycaemia, higher adiposity, liver fat, male sex and reduced insulin sensitivity in the prediabetes cohort. Higher fasting total GLP-1 was associated with a low intake of wholegrain, fruit and vegetables inpeople with prediabetes, and with a high intake of red meat and alcohol in people with diabetes.

CONCLUSION

These studies provide novel insights into the association between fasting and incremental GLP-1, metabolic traits of diabetes and obesity, and dietary intake and raise intriguing questions regarding the relevance of fasting GLP-1 in the pathophysiology T2D.

Can Adipokine FAM19A5 Be a Biomarker of Metabolic Disorders?

Aim

One of the most critical functions of adipose tissue is the production of adipokines, ie, numerous active substances that regulate metabolism. One is the newly discovered FAM19A5, whose older name is TAFA-5.

Purpose

The study aimed to review the literature on the FAM19A5 protein.

Methods

The review was conducted in December 2023 using the PubMed (Medline) search engine. Sixty-four papers were included in the review.

Results

This protein exhibits the characteristics of an adipokine with positive features for maintaining homeostasis. The results showed that FAM19A5 was highly expressed in adipose tissue, with mild to moderate expression in the brain and ovary. FAM19A5 may also inhibit vascular smooth muscle cell proliferation and migration through the perivascular adipose tissue paracrine pathway. Serum levels of FAM19A5 were decreased in obese children compared with healthy controls. There are negative correlations between FAM19A5, body mass index, and fasting insulin. Serum FAM19A5 level is correlated with type 2 diabetes, waist circumference, waist-to-hip ratio, glutamic pyruvic transferase, fasting plasma glucose, HbA1c, and mean shoulder pulse wave velocity. FAM19A5 expression was reduced in mice with obesity. However, the data available needs to be clarified or contradictory.

Conclusion

Considering today's knowledge about FAM19A5, we cannot consider this protein as a biomarker of the metabolic syndrome. According to current knowledge, FAM19A5 cannot be considered a marker of metabolic disorders because the results of studies conducted in this area are unclear.

Improvement in Visceral Adipose Tissue and LDL Cholesterol by High PUFA Intake: 1-Year Results of the NutriAct Trial

We assessed the effect of a dietary pattern rich in unsaturated fatty acids (UFA), protein and fibers, without emphasizing energy restriction, on visceral adipose tissue (VAT) and cardiometabolic risk profile. Within the 36-months randomized controlled NutriAct trial, we randomly assigned 502 participants (50-80 years) to an intervention or control group (IG, CG). The dietary pattern of the IG includes high intake of mono-/polyunsaturated fatty acids (MUFA/PUFA 15-20% E/10-15% E), predominantly plant protein (15-25% E) and fiber (≥30 g/day). The CG followed usual care with intake of 30% E fat, 55% E carbohydrates and 15% E protein. Here, we analyzed VAT in a subgroup of 300 participants via MRI at baseline and after 12 months, and performed further metabolic phenotyping. A small but comparable BMI reduction was seen in both groups (mean difference IG vs. CG: -0.216 kg/m2 [-0.477; 0.045], partial η2 = 0.009, p = 0.105). VAT significantly decreased in the IG but remained unchanged in the CG (mean difference IG vs. CG: -0.162 L [-0.314; -0.011], partial η2 = 0.015, p = 0.036). Change in VAT was mediated by an increase in PUFA intake (ß = -0.03, p = 0.005) and induced a decline in LDL cholesterol (ß = 0.11, p = 0.038). The NutriAct dietary pattern, particularly due to high PUFA content, effectively reduces VAT and cardiometabolic risk markers, independent of body weight loss.

Abdominal adipose tissue and type 2 diabetic kidney disease: adipose radiology assessment, impact, and mechanisms

Diabetic kidney disease (DKD) is a significant healthcare burden worldwide that substantially increases the risk of kidney failure and cardiovascular events. To reduce the prevalence of DKD, extensive research is being conducted to determine the risk factors and consequently implement early interventions. Patients with type 2 diabetes mellitus (T2DM) are more likely to be obese. Abdominal adiposity is associated with a greater risk of kidney damage than general obesity. Abdominal adipose tissue can be divided into different fat depots according to the location and function, including visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), perirenal adipose tissue (PAT), and renal sinus adipose tissue (RSAT), which can be accurately measured by radiology techniques, such as computed tomography (CT) and magnetic resonance imaging (MRI). Abdominal fat depots may affect the development of DKD through different mechanisms, and radiologic abdominal adipose characteristics may serve as imaging indicators of DKD risk. This review will first describe the CT/MRI-based assessment of abdominal adipose depots and subsequently describe the current studies on abdominal adipose tissue and DKD development, as well as the underlying mechanisms in patients of T2DM with DKD.

The gut microbiome modulates associations between adherence to a Mediterranean-style diet, abdominal adiposity, and C-reactive protein in population-level analysis

BACKGROUND

Adherence to a Mediterranean-style dietary pattern is likely to have variable effects on body composition, but the impact of gut microbiome on this relationship is unknown.

OBJECTIVES

To examine the potential mediating effect of the gut microbiome on the associations between Alternate Mediterranean Diet (aMed) scores, abdominal adiposity, and inflammation in population-level analysis.

DESIGN

In a community-based sample aged 25 to 83 y (n = 620; 41% female) from Northern Germany, we assessed the role of the gut microbiome, sequenced from 16S rRNA genes, on the associations between aMed scores, estimated using validated food-frequency questionnaires, magnetic resonance imaging-determined visceral (VAT) and subcutaneous (SAT) adipose tissue and C-reactive protein (CRP).

RESULTS

Higher aMed scores were associated with lower SAT (-0.86 L (95% CI: -1.56, -0.17), P = 0.01), VAT (-0.65 L (95% CI: -1.03,-0.27), P = 0.01) and CRP concentrations (-0.35 mg/L; β: -20.1% (95% CI: 35.5, -1.09), P = 0.04) in the highest versus lowest tertile after multivariate adjustment. Of the taxa significantly associated with aMed scores, higher abundance of Porphyromonadaceae mediated 11.6%, 9.3%, and 8.7% of the associations with lower SAT, VAT, and CRP, respectively. Conversely, a lower abundance of Peptostreptococcaceae mediated 13.1% and 18.2% of the association with SAT and CRP levels. Of the individual components of the aMed score, moderate alcohol intake was associated with lower VAT (-0.2 (95% CI: -0.4, -0.1), P =0.01) with a higher abundance of Oxalobacteraceae and lower abundance of Burkholderiaceae explaining 8.3% and 9.6% of this association, respectively.

CONCLUSION

These novel data suggest that abundance of specific taxa in the Porphyromonadaceae and Peptostreptococcaceae families may contribute to the association between aMed scores, lower abdominal adipose tissue, and inflammation.

Computed Tomography-Defined Sarcopenia in Outcomes of Patients with Unresectable Hepatocellular Carcinoma Undergoing Radioembolization: Assessment with Total Abdominal, Psoas, and Paraspinal Muscles

Introduction

Sarcopenia is an adverse prognostic factor in patients with liver cirrhosis and hepatocellular carcinoma (HCC). Image-based sarcopenia assessment allows a standardized method to assess abdominal skeletal muscle. However, which is an index muscle for sarcopenia remains unclear. Therefore, we investigated whether sarcopenia defined according to different muscle groups with computed tomography (CT) scans can predict the prognosis of HCC after radioembolization.

Methods

In this retrospective study, we analyzed patients who underwent radioembolization for unresectable HCC between January 2010 and December 2019. Before treatment, the total abdominal muscle (TAM), psoas muscle (PM), and paraspinal muscle (PS) areas were evaluated using a single CT slice at the third lumbar vertebra. In previous studies, sarcopenia was determined using the TAM, PM, and PS after stratifying by sex. Finally, we investigated each muscle-defined sarcopenia to decide whether or not it can serve as a prognostic factor for overall survival (OS).

Results

We included 92 patients (74 men and 18 women). TAM, PM, and PS areas were significantly higher in the men than in the women (all p < 0.05). The patients with sarcopenia defined using PM, but not TAM and PS, exhibited significantly poorer OS than those without sarcopenia (median 15.3 vs. 23.8 months, p = 0.034, 0.821, and 0.341, respectively). After adjustment for clinical variables, such as body mass index, liver function, alpha-fetoprotein level, clinical staging, treatment response, and posttreatment curative therapy, PM-defined sarcopenia (hazard ratio: 1.899, 95% confidence interval: 1.087-3.315) remained an independent predictor for the poor OS.

Conclusion

CT-assessed sarcopenia defined using PM was an independent prognostic factor for the poorer prognosis of unresectable HCC after radioembolization.

Pediatric body composition based on automatic segmentation of computed tomography scans: a pilot study

BACKGROUND

Body composition during childhood may predispose to negative health outcomes later in life. Automatic segmentation may assist in quantifying pediatric body composition in children.

OBJECTIVE

To evaluate automatic segmentation for body composition on pediatric computed tomography (CT) scans and to provide normative data on muscle and fat areas throughout childhood using automatic segmentation.

MATERIALS AND METHODS

In this pilot study, 537 children (ages 1-17 years) who underwent abdominal CT after high-energy trauma at a Dutch tertiary center (2002-2019) were retrospectively identified. Of these, the CT images of 493 children (66% boys) were used to establish normative data. Muscle (psoas, paraspinal and abdominal wall) and fat (subcutaneous and visceral) areas were measured at the third lumbar vertebral (L3) level by automatic segmentation. A representative subset of 52 scans was also manually segmented to evaluate the performance of automatic segmentation.

RESULTS

For manually-segmented versus automatically-segmented areas (52 scans), mean Dice coefficients were high for muscle (0.87-0.90) and subcutaneous fat (0.88), but lower for visceral fat (0.60). In the control group, muscle area was comparable for both sexes until the age of 13 years, whereafter, boys developed relatively more muscle. From a young age, boys were more prone to visceral fat storage than girls. Overall, boys had significantly higher visceral-to-subcutaneous fat ratios (median 1.1 vs. 0.6, P<0.01) and girls higher fat-to-muscle ratios (median 1.0 vs. 0.7, P<0.01).

CONCLUSION

Automatic segmentation of L3-level muscle and fat areas allows for accurate quantification of pediatric body composition. Using automatic segmentation, the development in muscle and fat distribution during childhood (in otherwise healthy) Dutch children was demonstrated.

Deep learning for the prediction of type 2 diabetes mellitus from neck-to-knee Dixon MRI in the UK biobank

Rationale and objectives

We evaluate the automatic identification of type 2 diabetes from neck-to-knee, two-point Dixon MRI scans with 3D convolutional neural networks on a large, population-based dataset. To this end, we assess the best combination of MRI contrasts and stations for diabetes prediction, and the benefit of integrating risk factors.

Materials and methods

Subjects with type 2 diabetes mellitus have been identified in the prospective UK Biobank Imaging study, and a matched control sample has been created to avoid confounding bias. Five-fold cross-validation is used for the evaluation. All scans from the two-point Dixon neck-to-knee sequence have been standardized. A neural network that considers multi-channel MRI input was developed and integrates clinical information in tabular format. An ensemble strategy is used to combine multi-station MRI predictions. A subset with quantitative fat measurements is identified for comparison to prior approaches.

Results

MRI scans from 3406 subjects (mean age, 66.2 years ± 7.1 [standard deviation]; 1128 women) were analyzed with 1703 diabetics. A balanced accuracy of 78.7 %, AUC ROC of 0.872, and an average precision of 0.878 was obtained for the classification of diabetes. The ensemble over multiple Dixon MRI stations yields better performance than selecting the individually best station. Moreover, combining fat and water scans as multi-channel inputs to the networks improves upon just using single contrasts as input. Integrating clinical information about known risk factors of diabetes in the network boosts the performance across all stations and the ensemble. The neural network achieved superior results compared to the prediction based on quantitative MRI measurements.

Conclusions

The developed deep learning model accurately predicted type 2 diabetes from neck-to-knee two-point Dixon MRI scans.

Associations of aortic stiffness and intra-aortic flow parameters with epicardial adipose tissue in patients with type-2 diabetes

Background

It has been shown that increased aortic stiffness is related to type-2 diabetes (T2D) which is considered as a risk factor for cardiovascular disease. Among other risk factors is epicardial adipose tissue (EAT) which is increased in T2D and is a relevant biomarker of metabolic severity and adverse outcome.

Purpose

To assess aortic flow parameters in T2D patients as compared to healthy individuals and to evaluate their associations with EAT accumulation as an index of cardiometabolic severity in T2D patients.

Materials and methods

Thirty-six T2D patients as well as 29 healthy controls matched by age and sex were included in this study. Participants had cardiac and aortic MRI exams at 1.5 T. Imaging sequences included cine SSFP for left ventricle (LV) function and EAT assessment and aortic cine and phase-contrast imaging for strain and flow parameters quantification.

Results

In this study, we found LV phenotype to be characterized by concentric remodeling with decreased stroke volume index despite global LV mass within a normal range. EAT was increased in T2D patients compared to controls (p<0.0001). Moreover, EAT, a biomarker of metabolic severity, was negatively correlated to ascending aortic (AA) distensibility (p=0.048) and positively to the normalized backward flow volume (p=0.001). These relationships remained significant after further adjustment for age, sex and central mean blood pressure. In a multivariate model, presence/absence of T2D and AA normalized backward flow (BF) to forward flow (FF) volumes ratio are both significant and independent correlates of EAT.

Conclusion

In our study, aortic stiffness as depicted by an increased backward flow volume and decreased distensibility seems to be related to EAT volume in T2D patients. This observation should be confirmed in the future on a larger population while considering additional biomarkers specific to inflammation and using a longitudinal prospective study design.

The effect of weight loss following 18 months of lifestyle intervention on brain age assessed with resting-state functional connectivity

Background

Obesity negatively impacts multiple bodily systems, including the central nervous system. Retrospective studies that estimated chronological age from neuroimaging have found accelerated brain aging in obesity, but it is unclear how this estimation would be affected by weight loss following a lifestyle intervention.

Methods

In a sub-study of 102 participants of the Dietary Intervention Randomized Controlled Trial Polyphenols Unprocessed Study (DIRECT-PLUS) trial, we tested the effect of weight loss following 18 months of lifestyle intervention on predicted brain age based on magnetic resonance imaging (MRI)-assessed resting-state functional connectivity (RSFC). We further examined how dynamics in multiple health factors, including anthropometric measurements, blood biomarkers, and fat deposition, can account for changes in brain age.

Results

To establish our method, we first demonstrated that our model could successfully predict chronological age from RSFC in three cohorts (n=291;358;102). We then found that among the DIRECT-PLUS participants, 1% of body weight loss resulted in an 8.9 months' attenuation of brain age. Attenuation of brain age was significantly associated with improved liver biomarkers, decreased liver fat, and visceral and deep subcutaneous adipose tissues after 18 months of intervention. Finally, we showed that lower consumption of processed food, sweets and beverages were associated with attenuated brain age.

Conclusions

Successful weight loss following lifestyle intervention might have a beneficial effect on the trajectory of brain aging.

Funding

The German Research Foundation (DFG), German Research Foundation - project number 209933838 - SFB 1052; B11, Israel Ministry of Health grant 87472511 (to I Shai); Israel Ministry of Science and Technology grant 3-13604 (to I Shai); and the California Walnuts Commission 09933838 SFB 105 (to I Shai).

The impact of fasting on adipose tissue metabolism

Fasting and starvation were common occurrences during human evolution and accordingly have been an important environmental factor shaping human energy metabolism. Humans can tolerate fasting reasonably well through adaptative and well-orchestrated time-dependent changes in energy metabolism. Key features of the adaptive response to fasting are the breakdown of liver glycogen and muscle protein to produce glucose for the brain, as well as the gradual depletion of the fat stores, resulting in the release of glycerol and fatty acids into the bloodstream and the production of ketone bodies in the liver. In this paper, an overview is presented of our current understanding of the effects of fasting on adipose tissue metabolism. Fasting leads to reduced uptake of circulating triacylglycerols by adipocytes through inhibition of the activity of the rate-limiting enzyme lipoprotein lipase. In addition, fasting stimulates the degradation of stored triacylglycerols by activating the key enzyme adipose triglyceride lipase. The mechanisms underlying these events are discussed, with a special interest in insights gained from studies on humans. Furthermore, an overview is presented of the effects of fasting on other metabolic pathways in the adipose tissue, including fatty acid synthesis, glucose uptake, glyceroneogenesis, autophagy, and the endocrine function of adipose tissue.

Fat infiltration in the thigh muscles is associated with symptomatic spinal stenosis and reduced physical functioning in adults with achondroplasia

BACKGROUND

Symptomatic spinal stenosis is a prevalent complication in adults with achondroplasia. Increased muscle fat infiltration (MFI) and reduced thigh muscle volumes have also been reported, but the pathophysiology is poorly understood. We explored whether the increased MFI and reduced thigh muscle volumes were associated with the presence of symptomatic spinal stenosis and physical functioning.

METHODS

MFI and thigh muscle volumes were assessed by MRI in 40 adults with achondroplasia, and compared to 80 average-statured controls, matched for BMI, gender, and age. In achondroplasia participants, the six-minute walk-test (6MWT), the 30-s sit-to-stand test (30sSTS), and a questionnaire (the IPAQ) assessed physical functioning.

RESULTS

Symptomatic spinal stenosis was present in 25 of the participants (the stenosis group), while 15 did not have stenosis (the non-stenosis group). In the stenosis group, 84% (21/25) had undergone at least one spinal decompression surgery. The stenosis group had significantly higher MFI than the non-stenosis group, with an age-, gender and BMI-adjusted difference in total MFI of 3.3 percentage points (pp) (95% confidence interval [CI] 0.04 to 6.3 pp; p = 0.03). Compared to matched controls, the mean age-adjusted difference was 3.3 pp (95% CI 1.7 to 4.9 pp; p < 0.01). The non-stenosis group had MFI similar to controls (age-adjusted difference - 0.9 pp, 95% CI - 3.4 to 1.8 pp; p = 0.51). MFI was strongly correlated with the 6MWT (r = - 0.81, - 0.83, and - 0.86; all p-values < 0.01), and moderately correlated with the 30sSTS (r = - 0.56, - 0.57, and - 0.59; all p-values < 0.01). There were no significant differences in muscle volumes or physical activity level between the stenosis group and the non-stenosis group.

CONCLUSION

Increased MFI in the thigh muscles was associated with the presence of symptomatic spinal stenosis, reduced functional walking capacity, and reduced lower limb muscle strength. The causality between spinal stenosis, accumulation of thigh MFI, and surgical outcomes need further study. We have demonstrated that MRI might serve as an objective muscle biomarker in future achondroplasia studies, in addition to functional outcome measures. The method could potentially aid in optimizing the timing of spinal decompression surgery and in planning of post-surgery rehabilitation.

Artifact-free fat-water separation in Dixon MRI using deep learning

Chemical-shift encoded MRI (CSE-MRI) is a widely used technique for the study of body composition and metabolic disorders, where derived fat and water signals enable the quantification of adipose tissue and muscle. The UK Biobank is acquiring whole-body Dixon MRI (a specific implementation of CSE-MRI) for over 100,000 participants. Current processing methods associated with large whole-body volumes are time intensive and prone to artifacts during fat-water separation performed by the scanner, making quantitative analysis challenging. The most common artifacts are fat-water swaps, where the labels are inverted at the voxel level. It is common for researchers to discard swapped data (generally around 10%), which is wasteful and may lead to unintended biases. Given the large number of whole-body Dixon MRI acquisitions in the UK Biobank, thousands of swaps are expected to be present in the fat and water volumes from image reconstruction performed on the scanner. If they go undetected, errors will propagate into processes such as organ segmentation, and dilute the results in population-based analyses. There is a clear need for a robust method to accurately separate fat and water volumes in big data collections like the UK Biobank. We formulate fat-water separation as a style transfer problem, where swap-free fat and water volumes are predicted from the acquired Dixon MRI data using a conditional generative adversarial network, and introduce a new loss function for the generator model. Our method is able to predict highly accurate fat and water volumes free from artifacts in the UK Biobank. We show that our model separates fat and water volumes using either single input (in-phase only) or dual input (in-phase and opposed-phase) data, with the latter producing superior results. Our proposed method enables faster and more accurate downstream analysis of body composition from Dixon MRI in population studies by eliminating the need for visual inspection or discarding data due to fat-water swaps.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40537-022-00677-1.

Association Between Different Parameters of Adipose Distribution and Transient Elastography-Assessed Hepatic Steatosis in American Adults with Diabetes, Prediabetes and Normal Glucose Tolerance

OBJECTIVE

To investigate the association between adipose distribution and hepatic steatosis in American adults and to assess whether this association varies among different blood glucose states.

METHODS

Data from the American National Health and Nutrition Examination Survey (NHANES) 2017-2018 were analyzed. The subjects were divided into three groups: diabetes, prediabetes and normal glucose tolerance (NGT). Hepatic steatosis was quantified by median controlled attenuation parameter (CAP), which was measured by ultrasound transient elastography. Total abdominal fat volume, visceral adipose tissue (VAT) volume, total percent fat, trunk percent fat, android percent fat and android to gynoid ratio (AGR) was measured by dual-energy X-ray absorptiometry (DXA).

RESULTS

Data pertaining to 2986 participants (1581 with hepatic steatosis) were included in the analysis. In the NGT group, the proportion of S0 (<5% of the hepatocytes with fatty infiltration) was 58.9%, and 25.2% for S3 (≥66% of the hepatocytes with fatty infiltration). In contrast, the proportion of S0 was 11.1%, while S3 accounts for as high as 68.7% in the diabetes group. In the NGT group, all parameters of fat distribution revealed a positive relation with the occurrence of hepatic steatosis (p<0.05) except total percent fat (p=0.872) after adjusting for confounding factors. In the prediabetes group, VAT volume, trunk percent fat, android percent fat and AGR had significant influence on hepatic steatosis (p<0.05). As for diabetes, only AGR remained significantly correlated with hepatic steatosis (p=0.004).

CONCLUSION

For NGT individuals, high level of total abdominal fat volume, VAT volume, trunk percent fat, android percent fat and AGR all can be used to predict hepatic steatosis. For diabetes, only AGR can predict hepatic steatosis among the surveyed parameters of adipose distribution.

Reference Ranges of Body Composition Using Dual-Energy X-Ray Absorptiometry and Its Relation to Tri-Ponderal Mass Index

Introduction/background Increased body fat is related to obesity and its comorbidities later in life. To determine the amount of body fat in children and adolescents, reference intervals should be applied. Dual-energy X-ray absorptiometry (DXA) is a good tool for accurately measuring body composition. Methodology The body composition reference ranges in Korean children and adolescents were determined using nationally representative cross-sectional data. The performances of the body mass index (BMI) and tri-ponderal mass index (TMI) in measuring body fat were compared using the reference percentiles derived from this analysis. Results A total of 1,661 subjects (891 boys and men and 770 girls and women) were included. Age- and sex-specific percentiles and the corresponding LMS variables for DXA-assessed parameters for the whole body and the trunk were determined. The coefficients of determination of the whole body FM SDS and FMI SDS for the BMI SDS were 0.783 and 0.784, respectively, and those for the TMI SDS were 0.685 and 0.769, respectively. Conclusion Based on the reference values for body composition, the correlation coefficients of TMI for adjusted FM measured by DXA were comparable to those of BMI. TMI estimated body fat levels more accurately than BMI in this study population.

The Association Between Pancreatic Steatosis and Metabolic Syndrome: A 5-Year Follow-up Study Among a General Chinese Population

OBJECTIVES

To date, the complete natural history of pancreatic steatosis is unknown. This study aimed to investigate the association of fatty pancreas (FP) in the incidence of metabolic syndrome and its components among Chinese patients with a 5-year follow-up.

METHODS

Three independent cross-sectional surveys were carried out in 2013, 2015, and 2018. Fatty pancreas was diagnosed via transabdominal sonography. Logistic regression analysis was used to estimate the correlation between FP and metabolic syndrome. New cases of metabolic syndrome and its components were estimated by Cox proportional hazards models.

RESULTS

At baseline, 12,551 individuals classified into FP (n = 1010) and non-FP (n = 11,541) groups were finally enrolled. In cross-sectional analyses, odds ratio of FP was 2.378 (95% confidence interval [CI], 2.085-2.713; P < 0.001). In longitudinal analyses, FP was associated with the occurrence of metabolic syndrome (hazard ratio [HR], 3.179; 95% CI, 2.197-4.6; P < 0.001), type 2 diabetes mellitus (HR, 13.99; 95% CI, 7.865-24.883; P < 0.001), nonalcoholic fatty liver disease (HR, 31.843; 95% CI, 7.73-131.171; P < 0.001), and hypertension (HR, 12.801; 95% CI, 7.323-22.38; P < 0.001).

CONCLUSIONS

Pancreatic steatosis is strongly associated with the occurrence of metabolic syndrome and its components such as hypertension and diabetes.

Effects of body fat components on early renal functions of individuals following kidney donation

Objective:

Obesity stands as a risk factor for the chronic kidney disease. The objective of this study was to investigate the relationship between early renal function following kidney donation and the measurements of body fat components.

Methods:

In total, 86 donors followed up for at least 6 months postoperatively were included. Height and weight measurements and results of laboratory analysis of all donors were recorded retrospectively. Visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), hepatic fat (HF), pancreatic fat (PF) and splenic fat (SF) measurements were performed, and pancreatic splenic fat fraction difference (P−S) and pancreatic splenic fat fraction ratio (P/S) were calculated by a radiologist using the records of preoperative computed tomography scans of donors.

Results:

The estimated glomerular filtration rate (eGFR), serum creatinine and spot urinary microalbumin/creatinine ratio values of the donors at the sixth month postoperatively were statistically different from those of the preoperative values ( p < 0.001). In addition, the individuals were divided into two categories based on the postoperative eGFR: ⩾ 60 mL/min/1.73 m2 and < 60 mL/min/1.73 m2. Age, low-density lipoprotein (LDL) level and VAT/SAT ratio were lower in group eGFR: ⩾ 60 ( p < 0.001, p = 0.03, p = 0.007, respectively). Age and VAT/SAT ratio were the parameters found to be affecting the eGFR significantly, and VAT/SAT ratio (0.729, 95% CI: 0.602–0.856, p = 0.007) had higher predictive value in receiver operating characteristic curve (ROC).

Conclusion:

Preoperative measurements of body fat components may provide significant information to predict postoperative renal functions of kidney donor candidates.

Level of evidence:

Not applicable.

Circulating Levels of microRNA-122 and Hepatic Fat Change in Response to Weight-Loss Interventions: CENTRAL Trial

PURPOSE

Little is known about the relations between changes in circulating microRNA-122 (miR-122) and liver fat in response to weight-loss interventions. We aimed to investigate the association between miR-122 and changes of hepatic fat content during 18-month diet and physical activity interventions.

METHODS

The CENTRAL trial is an 18-month randomized, controlled trial among adults with abdominal obesity or dyslipidemia. Subjects were randomly assigned to a low-fat diet or a Mediterranean/low-carbohydrate diet. After 6 months of dietary intervention, each diet group was further randomized into added physical activity groups or no added physical activity groups for the following 12 months of intervention. The current study included 220 participants at baseline and 134 participants with repeated measurements on serum miR-122 and hepatic fat content over 18 months.

RESULTS

Serum miR-122 significantly increased from baseline to 18 months, while no difference was observed across the 4 intervention groups. We found a significant association between miR-122 and hepatic fat content at baseline, as per unit increment in log-transformed miR-122 was associated with 3.79 higher hepatic fat content (P < 0.001). Furthermore, we found that higher elevations in miR-122 were associated with less reductions in hepatic fat percentage during 18-month interventions (β = 1.56, P = 0.002). We also found a significant interaction between changes in miR-122 and baseline fasting plasma glucose with hepatic fat content changes in 18 months (P interaction = 0.02).

CONCLUSIONS

Our data indicate that participants with higher elevation in serum miR-122 may benefit less in reduction of hepatic fat content in response to diet and physical activity interventions.

Subcutaneous and visceral fat assessment by DXA and MRI in older adults and children

OBJECTIVE

Given the importance of body fat distribution in chronic disease development, feasible methods to assess body fat are essential. This study compared dual-energy x-ray absorptiometry (DXA) in measuring visceral and subcutaneous adipose tissue (VAT and SAT) with magnetic resonance imaging (MRI).

METHODS

VAT and SAT were assessed using similar DXA and MRI protocols among 1,795 elderly participants of the Adiposity Phenotype Study (APS) and 309 children/adolescents in Shape Up! Kids (SKids). Spearman correlations, Bland-Altman plots, and coefficients of determination (R2 ) assessed agreement between DXA and MRI measures.

RESULTS

DXA overestimated SAT values in APS (315 vs. 229 cm2 ) and SKids (212 vs. 161 cm2 ), whereas DXA underestimated VAT measures (141 vs. 167 cm2 ) in adults only. The correlations between DXA and MRI values were stronger for SAT than VAT (APS: r = 0.92 vs. 0.88; SKids: 0.90 vs. 0.74). Bland-Altman plots confirmed better agreement for SAT than VAT despite differences by sex, ethnicity, and weight status with respective R2 values for SAT and VAT of 0.88 and 0.84 (APS) and 0.81 and 0.69 (SKids).

CONCLUSION

These findings indicate that SAT by DXA reflects MRI measures in children and older adults, whereas agreement for VAT is weaker for individuals with low VAT levels.

Obesity I: Overview and molecular and biochemical mechanisms

Obesity is a chronic, relapsing condition characterized by excess body fat. Its prevalence has increased globally since the 1970s, and the number of obese and overweight people is now greater than those underweight. Obesity is a multifactorial condition, and as such, many components contribute to its development and pathogenesis. This is the first of three companion reviews that consider obesity. This review focuses on the genetics, viruses, insulin resistance, inflammation, gut microbiome, and circadian rhythms that promote obesity, along with hormones, growth factors, and organs and tissues that control its development. It shows that the regulation of energy balance (intake vs. expenditure) relies on the interplay of a variety of hormones from adipose tissue, gastrointestinal tract, pancreas, liver, and brain. It details how integrating central neurotransmitters and peripheral metabolic signals (e.g., leptin, insulin, ghrelin, peptide YY_3-36) is essential for controlling energy homeostasis and feeding behavior. It describes the distinct types of adipocytes and how fat cell development is controlled by hormones and growth factors acting via a variety of receptors, including peroxisome proliferator-activated receptor-gamma, retinoid X, insulin, estrogen, androgen, glucocorticoid, thyroid hormone, liver X, constitutive androstane, pregnane X, farnesoid, and aryl hydrocarbon receptors. Finally, it demonstrates that obesity likely has origins in utero. Understanding these biochemical drivers of adiposity and metabolic dysfunction throughout the life cycle lends plausibility and credence to the "obesogen hypothesis" (i.e., the importance of environmental chemicals that disrupt these receptors to promote adiposity or alter metabolism), elucidated more fully in the two companion reviews.

Four groups of type 2 diabetes contribute to the etiological and clinical heterogeneity in newly diagnosed individuals: An IMI DIRECT study

The presentation and underlying pathophysiology of type 2 diabetes (T2D) is complex and heterogeneous. Recent studies attempted to stratify T2D into distinct subgroups using data-driven approaches, but their clinical utility may be limited if categorical representations of complex phenotypes are suboptimal. We apply a soft-clustering (archetype) method to characterize newly diagnosed T2D based on 32 clinical variables. We assign quantitative clustering scores for individuals and investigate the associations with glycemic deterioration, genetic risk scores, circulating omics biomarkers, and phenotypic stability over 36 months. Four archetype profiles represent dysfunction patterns across combinations of T2D etiological processes and correlate with multiple circulating biomarkers. One archetype associated with obesity, insulin resistance, dyslipidemia, and impaired β cell glucose sensitivity corresponds with the fastest disease progression and highest demand for anti-diabetic treatment. We demonstrate that clinical heterogeneity in T2D can be mapped to heterogeneity in individual etiological processes, providing a potential route to personalized treatments.

Spectral analysis of ultrasound radiofrequency backscatter for the identification of epicardial adipose tissue

Purpose: The coronary arteries are embedded in a layer of fat known as epicardial adipose tissue (EAT). The EAT influences the development of coronary artery disease (CAD), and increased EAT volume can be indicative of the presence and type of CAD. Identification of EAT using echocardiography is challenging and only sometimes feasible on the free wall of the right ventricle. We investigated the use of spectral analysis of the ultrasound radiofrequency (RF) backscatter for its potential to provide a more complete characterization of the EAT. Approach: Autoregressive (AR) models facilitated analysis of the short-time signals and allowed tuning of the optimal order of the spectral estimation process. The spectra were normalized using a reference phantom and spectral features were computed from both normalized and non-normalized data. The features were used to train random forests for classification of EAT, myocardium, and blood. Results: Using an AR order of 15 with the normalized data, a Monte Carlo cross validation yielded accuracies of 87.9% for EAT, 84.8% for myocardium, and 93.3% for blood in a database of 805 regions-of-interest. Youden's index, the sum of sensitivity, and specificity minus 1 were 0.799, 0.755, and 0.933, respectively. Conclusions: We demonstrated that spectral analysis of the raw RF signals may facilitate identification of the EAT when it may not otherwise be visible in traditional B-mode images.

Automatic segmentation of whole-body adipose tissue from magnetic resonance fat fraction images based on machine learning

OBJECTIVE

To propose a fully automated algorithm, which is implemented to segment subcutaneous adipose tissue (SAT) and internal adipose tissue (IAT) from the total adipose tissue for whole-body fat distribution analysis using proton density fat fraction (PDFF) magnetic resonance images.

MATERIALS AND METHODS

Adipose tissue segmentation was implemented using the U-Net deep neural network model. All datasets were collected using a 3.0 T magnetic resonance imaging (MRI) scanner for whole-body scan of 20 volunteers covering from neck to knee with about 160 images for each volunteer. PDFF images were reconstructed based on chemical-shift-encoded fat-water imaging. After selecting the representative PDFF images (total 906 images), the manual labeling of the SAT area was used for model training (504 images), validation (168 images), and testing (234 images).

RESULTS

The automatic segmentation model was validated through three indices using the validation and test sets. The dice similarity coefficient, precision rate, and recall rate were 0.976 ± 0.048, 0.978 ± 0.048, and 0.978 ± 0.050, respectively, in both validation and test sets.

CONCLUSION

The proposed algorithm can reliably and automatically segment SAT and IAT from whole-body MRI PDFF images. The proposed method provides a simple and automatic tool for whole-body fat distribution analysis to explore the relationship between fat deposition and metabolic-related chronic diseases.

Abdominal adipose tissue components quantification in MRI as a relevant biomarker of metabolic profile

INTRODUCTION

Abnormal accumulation of adipose tissue (AT) alters the metabolic profile and underlies cardiovascular complications. Conventional measures provide global measurements for the entire body. The purpose of this study was to propose a new approach to quantify the amount and type of truncal AT automatically from MRI in metabolic patients and controls.

MATERIALS AND METHODS

DIXON acquisitions were performed at 1.5 T in 30 metabolic syndrome (MS) (59 ± 6 years), 12 obese (50 ± 11 years), 35 type 2 diabetes (T2DM) patients (56 ± 11 years) and 19 controls (52 ± 11 years). AT was segmented into: subcutaneous AT "SAT", visceral AT "VAT", deep VAT "dVAT", peri-organ VAT "pVAT" using active contours and k-means clustering algorithms. Subsequently, organ AT infiltration index "oVAT" was calculated as the normalized fat signal magnitude in organs.

RESULTS

Excellent intra- and inter-operator reproducibility was obtained for AT segmentation. MS and obese patients had the highest amount of total AT. SAT increased in MS (1144 ± 621 g) and T2DM patients (1024 ± 634 g), and twice the level of SAT in controls (505 ± 238 g), and further increased in obese patients (1429 ± 621 g). While VAT, pVAT and dVAT increased to a similar degree in the metabolic patients compared to controls, the oVAT index was able to differentiate controls from MS and T2DM patients and to discriminate the three metabolic patient groups (p < 0.01). Local AT sub-types were not related to BMI in all groups except for SAT in controls (p = 0.03).

CONCLUSION

Reproducible truncal AT sub-types quantification using 3D MRI was able to characterize patients with metabolic diseases. It may serve in the future as a non-invasive predictor of cardiovascular complications in such patients.

Cardiovascular risk factors and body composition in adults with achondroplasia

Purpose

An increased cardiovascular mortality has been reported in achondroplasia. This population-based, case–control study investigated cardiovascular risk factors and body composition in Norwegian adults with achondroplasia.

Methods

We conducted anthropometric, clinical, and laboratory assessments in 49 participants with achondroplasia, of whom 40 completed magnetic resonance imaging (MRI) for body composition analysis. Controls consisted of 98 UK Biobank participants, matched for body mass index (BMI), sex, and age.

Results

Participants were well matched for BMI (33.3 versus 32.5 kg/m²) and sex, but achondroplasia participants were younger than controls (mean age 41.1 versus 54.3 years). Individuals with achondroplasia had lower age-adjusted mean blood pressure, total and low-density lipoprotein (LDL) cholesterol, and triglycerides compared with controls, but similar fasting glucose and HbA1c values. Age-adjusted mean visceral fat store was 1.9 versus 5.3 L (difference −2.7, 95% confidence interval [CI] −3.6 to −1.9; P < 0.001), abdominal subcutaneous fat was 6.0 versus 11.2 L (−4.7, 95% CI −5.9 to −3.4; P < 0.001), and liver fat was 2.2 versus 6.9% (−2.8, 95% CI −5.2 to −0.4; P = 0.02).

Conclusion

Despite a high BMI, the cardiovascular risks appeared similar or lower in achondroplasia compared with controls, indicating that other factors might contribute to the increased mortality observed in this condition.

Large-scale biometry with interpretable neural network regression on UK Biobank body MRI

In a large-scale medical examination, the UK Biobank study has successfully imaged more than 32,000 volunteer participants with magnetic resonance imaging (MRI). Each scan is linked to extensive metadata, providing a comprehensive medical survey of imaged anatomy and related health states. Despite its potential for research, this vast amount of data presents a challenge to established methods of evaluation, which often rely on manual input. To date, the range of reference values for cardiovascular and metabolic risk factors is therefore incomplete. In this work, neural networks were trained for image-based regression to infer various biological metrics from the neck-to-knee body MRI automatically. The approach requires no manual intervention or direct access to reference segmentations for training. The examined fields span 64 variables derived from anthropometric measurements, dual-energy X-ray absorptiometry (DXA), atlas-based segmentations, and dedicated liver scans. With the ResNet50, the standardized framework achieves a close fit to the target values (median R\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^2 > 0.97$$\end{document}2>0.97) in cross-validation. Interpretation of aggregated saliency maps suggests that the network correctly targets specific body regions and limbs, and learned to emulate different modalities. On several body composition metrics, the quality of the predictions is within the range of variability observed between established gold standard techniques.

Dietary metabolite profiling brings new insight into the relationship between nutrition and metabolic risk: An IMI DIRECT study

BACKGROUND

Dietary advice remains the cornerstone of prevention and management of type 2 diabetes (T2D). However, understanding the efficacy of dietary interventions is confounded by the challenges inherent in assessing free living diet. Here we profiled dietary metabolites to investigate glycaemic deterioration and cardiometabolic risk in people at risk of or living with T2D.

METHODS

We analysed data from plasma collected at baseline and 18-month follow-up in individuals from the Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) cohort 1 n = 403 individuals with normal or impaired glucose regulation (prediabetic) and cohort 2 n = 458 individuals with new onset of T2D. A dietary metabolite profile model (T_pred) was constructed using multivariable regression of 113 plasma metabolites obtained from targeted metabolomics assays. The continuous T_pred score was used to explore the relationships between diet, glycaemic deterioration and cardio-metabolic risk via multiple linear regression models.

FINDINGS

A higher T_pred score was associated with healthier diets high in wholegrain (β=3.36 g, 95% CI 0.31, 6.40 and β=2.82 g, 95% CI 0.06, 5.57) and lower energy intake (β=-75.53 kcal, 95% CI -144.71, -2.35 and β=-122.51 kcal, 95% CI -186.56, -38.46), and saturated fat (β=-0.92 g, 95% CI -1.56, -0.28 and β=-0.98 g, 95% CI -1.53, -0.42 g), respectively for cohort 1 and 2. In both cohorts a higher T_pred score was also associated with lower total body adiposity and favourable lipid profiles HDL-cholesterol (β=0.07 mmol/L, 95% CI 0.03, 0.1), (β=0.08 mmol/L, 95% CI 0.04, 0.1), and triglycerides (β=-0.1 mmol/L, 95% CI -0.2, -0.03), (β=-0.2 mmol/L, 95% CI -0.3, -0.09), respectively for cohort 1 and 2. In cohort 2, the T_pred score was negatively associated with liver fat (β=-0.74%, 95% CI -0.67, -0.81), and lower fasting concentrations of HbA1c (β=-0.9 mmol/mol, 95% CI -1.5, -0.1), glucose (β=-0.2 mmol/L, 95% CI -0.4, -0.05) and insulin (β=-11.0 pmol/mol, 95% CI -19.5, -2.6). Longitudinal analysis showed at 18-month follow up a higher T_pred score was also associated lower total body adiposity in both cohorts and lower fasting glucose (β=-0.2 mmol/L, 95% CI -0.3, -0.01) and insulin (β=-9.2 pmol/mol, 95% CI -17.9, -0.4) concentrations in cohort 2.

INTERPRETATION

Plasma dietary metabolite profiling provides objective measures of diet intake, showing a relationship to glycaemic deterioration and cardiometabolic health.

FUNDING

This work was supported by the Innovative Medicines Initiative Joint Undertaking under grant agreement no. 115,317 (DIRECT), resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007-2013) and EFPIA companies.

Radiation protection in non-ionizing and ionizing body composition assessment procedures

Body composition assessment (BCA) represents a valid instrument to evaluate nutritional status through the quantification of lean and fat tissue, in healthy subjects and sick patients. According to the clinical indication, body composition (BC) can be assessed by different modalities. To better analyze radiation risks for patients involved, BCA procedures can be divided into two main groups: the first based on the use of ionizing radiation (IR), involving dual energy X-ray absorptiometry (DXA) and computed tomography (CT), and others based on non-ionizing radiation (NIR) [magnetic resonance imaging (MRI)]. Ultrasound (US) techniques using mechanical waves represent a separate group. The purpose of our study was to analyze publications about IR and NIR effects in order to make physicians aware about the risks for patients undergoing medical procedures to assess BCA providing to guide them towards choosing the most suitable method. To this end we reported the biological effects of IR and NIR and their associated risks, with a special regard to the excess risk of death from radio-induced cancer. Furthermore, we reported and compared doses obtained from different IR techniques, giving practical indications on the optimization process. We also summarized current recommendations and limits for techniques employing NIR and US. The authors conclude that IR imaging procedures carry relatively small individual risks that are usually justified by the medical need of patients, especially when the optimization principle is applied. As regards NIR imaging procedures, a few studies have been conducted on interactions between electromagnetic fields involved in MR exam and biological tissue. To date, no clear link exists between MRI or associated magnetic and pulsed radio frequency (RF) fields and subsequent health risks, whereas acute effects such as tissue burns and phosphenes are well-known; as regards the DNA damage and the capability of NIR to break chemical bonds, they are not yet robustly demonstrated. MRI is thus considered to be very safe for BCA as well US procedures.

Predicting and elucidating the etiology of fatty liver disease: A machine learning modeling and validation study in the IMI DIRECT cohorts

BACKGROUND

Non-alcoholic fatty liver disease (NAFLD) is highly prevalent and causes serious health complications in individuals with and without type 2 diabetes (T2D). Early diagnosis of NAFLD is important, as this can help prevent irreversible damage to the liver and, ultimately, hepatocellular carcinomas. We sought to expand etiological understanding and develop a diagnostic tool for NAFLD using machine learning.

METHODS AND FINDINGS

We utilized the baseline data from IMI DIRECT, a multicenter prospective cohort study of 3,029 European-ancestry adults recently diagnosed with T2D (n = 795) or at high risk of developing the disease (n = 2,234). Multi-omics (genetic, transcriptomic, proteomic, and metabolomic) and clinical (liver enzymes and other serological biomarkers, anthropometry, 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 (<5% or ≥5%) available for 1,514 participants. We applied LASSO (least absolute shrinkage and selection operator) to select features from the different layers of omics data and random forest analysis to develop the models. The prediction models included clinical and omics variables separately or in combination. A model including all omics and clinical variables yielded a cross-validated receiver operating characteristic area under the curve (ROCAUC) of 0.84 (95% CI 0.82, 0.86; p < 0.001), which compared with a ROCAUC of 0.82 (95% CI 0.81, 0.83; p < 0.001) for a model including 9 clinically accessible variables. The IMI DIRECT prediction models outperformed existing noninvasive NAFLD prediction tools. One limitation is that these analyses were performed in adults of European ancestry residing in northern Europe, and it is unknown how well these findings will translate to people of other ancestries and exposed to environmental risk factors that differ from those of the present cohort. Another key limitation of this study is that the prediction was done on a binary outcome of liver fat quantity (<5% or ≥5%) rather than a continuous one.

CONCLUSIONS

In this study, we developed several models with different combinations of clinical and omics data and identified biological features that appear to be associated with liver fat accumulation. In general, the clinical variables showed better prediction ability than the complex omics variables. However, the combination of omics and clinical variables yielded the highest accuracy. We have incorporated the developed clinical models into a web interface (see: https://www.predictliverfat.org/) and made it available to the community.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03814915.

Measurement of total and visceral fat mass in young adult women: a comparison of MRI with anthropometric measurements with and without bioelectrical impedance analysis

OBJECTIVE

MRI is established for measurement of body fat mass (FM) and abdominal visceral adipose tissue (VAT). Anthropometric measurements and bioelectrical impedance analysis (BIA) have been proposed as surrogates to estimation by MRI. Aim of this work is to assess the predictive value of these methods for FM and VAT measured by MRI.

METHODS

Patients were selected from cohort study PPS-Diab (prediction, prevention and subclassification of Type 2 diabetes). Total FM and VAT were quantified by MRI and BIA together with clinical variables like age, waist and hip circumference and height. Least-angle regressions were utilized to select anthropometric and BIA parameters for their use in multivariable linear regression models to predict total FM and VAT. Bland-Altman plots, Pearson correlation coefficients, Wilcoxon signed-rank tests and univariate linear regression models were applied.

RESULTS

116 females with 35 ± 3 years and a body mass index of 25.1 ± 5.3 kg/m2 were included into the analysis. A multivariable model revealed weight (β = 0.516, p < 0.001), height (β = -0.223, p < 0.001) and hip circumference (β = 0.156, p = 0.003) as significantly associated with total FM measured by MRI. A additional multivariable model also showed a significant predictive value of FMBIA (β = 0.583, p < 0.001) for FM. In addition, waist circumference (β = 0.054, p < 0.001), weight (β = 0.016, p = 0.031) in one model and FMBIA (β = 0.026, p = 0.018) in another model were significantly associated with VAT quantified by MRI. However, deviations reached more than 5 kg for total FM and more than 1 kg for VAT.

CONCLUSION

Anthropometric measurements and BIA show significant association with total FM and VAT.

ADVANCES IN KNOWLEDGE

As these measurements show significant deviations from the absolute measured values determined by MRI, MRI should be considered the gold-standard for quantification.

[Ceramides, crucial actors in the development of insulin resistance and type 2 diabetes]

In healthy subjects, the balance between glucose production and its usage is precisely controlled. When circulating glucose reaches a critical threshold, pancreatic β-cells secrete insulin, which has two major actions: lowering circulating glucose concentrations by facilitating its uptake mainly in skeletal muscles and the liver, and inhibiting glucose production. Triglycerides are the main source of fatty acids to meet the energy needs of oxidative tissues and any excess is stored in adipocytes. Thus, adipose tissue acts as a trap for excess fatty acids released from plasma triglycerides. When the buffering action of adipose tissue to store fatty acids is impaired, they accumulate in other tissues where they are metabolized in several lipid species, including sphingolipid derivatives such as ceramides. Numerous studies have shown that ceramides are among the most active lipid second messengers to inhibit insulin signalling. This review describes the major role played by ceramides in the development of insulin resistance in peripheral tissues.

The role of physical activity in metabolic homeostasis before and after the onset of type 2 diabetes: an IMI DIRECT study

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.

Ethnic differences in hepatic, pancreatic, muscular and visceral fat deposition in healthy men of white European and black west African ethnicity

AIMS

We aimed to assess ethnic differences in visceral adipose tissue (VAT), intrahepatic (IHL), intrapancreatic (IPL) and intramyocellular lipids (IMCL) between healthy white European (WE) and black west African (BWA) men.

METHODS

23 WE and 20 BWA men underwent Dixon-magnetic resonance imaging to quantify VAT, IHL and IPL; and proton-magnetic resonance spectroscopy to quantify IMCL. Insulin sensitivity and beta-cell function were determined using homeostasis model assessment (HOMA-2).

RESULTS

BWA men exhibited significantly lower VAT (P = 0.021) and IHL (P = 0.044) than WE men, but comparable IPL (P = 0.92) and IMCL (P = 0.87). VAT was associated with IPL in both ethnicities (WE: P < 0.001; BWA: P = 0.001) but the relationship with IHL differed by ethnicity (P_interaction = 0.018) and was only significant in WE men (WE: P < 0.001; BWA: P = 0.36). All ectopic fat depots inversely associated with insulin sensitivity and positively associated with beta-cell function in WE but not BWA men.

CONCLUSIONS

Lower VAT and IHL, and their lack of interrelation, in BWA men suggests ethnic differences exist in the mechanisms of ectopic fat deposition. The lack of association between ectopic fat with insulin sensitivity and beta-cell function in BWA men may indicate a lesser role for ectopic fat in the development of type 2 diabetes mellitus in black populations.

Discovery of biomarkers for glycaemic deterioration before and after the onset of type 2 diabetes: descriptive characteristics of the epidemiological studies within the IMI DIRECT Consortium

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.

A gathering storm: HIV infection and nonalcoholic fatty liver disease in low and middle-income countries

: Despite the decreasing total incidence of liver-related deaths, liver disease remains one of the major non-AIDS causes of morbidity and mortality amongst people living with HIV, and a significant proportion of liver disease in these individuals can be attributed to nonalcoholic fatty liver disease (NAFLD). NAFLD in HIV infection is a growing problem in view of increasing life expectancy associated with the use of effective antiretroviral therapy (ART), wider uptake of ART and increasing rates of obesity in many Asian as well as western countries. The problem may be more pronounced in developing countries where there are limited resources available for mass screening and diagnosis of NAFLD. There is a small but growing body of literature examining NAFLD in the setting of HIV, with data from low and middle-income countries (LMICs) particularly lacking. Here, we review the cohort data on NAFLD in HIV, and discuss the risk factors, pathogenesis of hepatic steatosis, NAFLD and nonalcoholic steatohepatitis (NASH), diagnostic approaches and therapeutic options available for NAFLD in the setting of HIV, and the specific challenges of NAFLD in HIV for LMICs.

Current knowledge of medical complications in adults with achondroplasia: A scoping review

This article provides an overview of the current knowledge on medical complications, health characteristics, and psychosocial issues in adults with achondroplasia. We have used a scoping review methodology particularly recommended for mapping and summarizing existing research evidence, and to identify knowledge gaps. The review process was conducted in accordance with the PRISMA‐ScR guidelines (Preferred Reporting Items for Systematic reviews and Meta‐Analyses Extension for Scoping Reviews). The selection of studies was based on criteria predefined in a review protocol. Twenty‐nine publications were included; 2 reviews, and 27 primary studies. Key information such as reference details, study characteristics, topics of interest, main findings and the study author's conclusion are presented in text and tables. Over the past decades, there has only been a slight increase in publications on adults with achondroplasia. The reported morbidity rates and prevalence of medical complications are often based on a few studies where the methodology and representativeness can be questioned. Studies on sleep‐related disorders and pregnancy‐related complications were lacking. Multicenter natural history studies have recently been initiated. Future studies should report in accordance to methodological reference standards, to strengthen the reliability and generalizability of the findings, and to increase the relevance for implementing in clinical practice.

Associations of Fetal and Infant Weight Change With General, Visceral, and Organ Adiposity at School Age

IMPORTANCE

Both fetal and infant growth influence obesity later in life. The association of longitudinal fetal and infant growth patterns with organ fat is unknown.

OBJECTIVE

To examine the associations of fetal and infant weight change with general, visceral, and organ adiposity at school age.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study was embedded in the Generation R Study, a population-based prospective cohort study in Rotterdam, the Netherlands. Pregnant women with a delivery date between April 2002 and January 2006 were eligible to participate. Follow-up measurements were performed for 3205 children. Data analysis of this population was performed from July 26, 2018, to February 7, 2019.

EXPOSURES

Fetal weight was estimated in the second and third trimester of pregnancy. Infant weight was measured at 6, 12, and 24 months. Fetal and infant weight acceleration or deceleration were defined as a change in standard deviation scores greater than 0.67 between 2 ages.

MAIN OUTCOMES AND MEASURES

Visceral fat index, pericardial fat index, and liver fat fraction were measured by magnetic resonance imaging.

RESULTS

The sample consisted of 3205 children (1632 girls [50.9%]; mean [SD] age, 9.8 [0.3] years). Children born small for gestational age had the lowest median body mass index compared with children born appropriate for gestational age and large for gestational age (16.4 [90% range, 14.1-23.6] vs 16.9 [90% range, 14.4-22.8] vs 17.4 [90% range, 14.9-22.7]). Compared with children with normal fetal and infant growth (533 of 2370 [22.5%]), those with fetal weight deceleration followed by infant weight acceleration (263 of 2370 [11.1%]) had the highest visceral fat index (standard deviation scores, 0.18; 95% CI, 0.03-0.33; P = .02) and liver fat fraction (standard deviation scores, 0.34; 95% CI, 0.20-0.48; P < .001).

CONCLUSIONS AND RELEVANCE

Fetal and infant weight change patterns were both associated with childhood body fat, but weight change patterns in infancy tended to have larger effects. Fetal growth restriction followed by infant growth acceleration was associated with increased visceral and liver fat.

Genome-Wide and Abdominal MRI Data Provide Evidence That a Genetically Determined Favorable Adiposity Phenotype Is Characterized by Lower Ectopic Liver Fat and Lower Risk of Type 2 Diabetes, Heart Disease, and Hypertension

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 favorable adiposity alleles are associated with higher subcutaneous fat and lower ectopic fat. We combined MRI data with genome-wide association studies of body fat percentage (%) and metabolic traits. We report 14 alleles, including 7 newly characterized alleles, associated with higher adiposity but a favorable metabolic profile. Consistent with previous studies, individuals carrying more favorable 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 a 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, whereas the allele in ANKRD55 was paradoxically associated with higher visceral fat but lower risk of type 2 diabetes. Most identified favorable adiposity alleles are associated with higher subcutaneous and lower liver fat, a mechanism consistent with the beneficial effects of storing excess triglycerides in metabolically low-risk depots.

Aging and Imaging Assessment of Body Composition: From Fat to Facts

The aging process is characterized by the chronic inflammatory status called "inflammaging", which shares major molecular and cellular features with the metabolism-induced inflammation called "metaflammation." Metaflammation is mainly driven by overnutrition and nutrient excess, but other contributing factors are metabolic modifications related to the specific body composition (BC) changes occurring with age. The aging process is indeed characterized by an increase in body total fat mass and a concomitant decrease in lean mass and bone density, that are independent from general and physiological fluctuations in weight and body mass index (BMI). Body adiposity is also re-distributed with age, resulting in a general increase in trunk fat (mainly abdominal fat) and a reduction in appendicular fat (mainly subcutaneous fat). Moreover, the accumulation of fat infiltration in organs such as liver and muscles also increases in elderly, while subcutaneous fat mass tends to decrease. These specific variations in BC are considered risk factors for the major age-related diseases, such as cardiovascular diseases, type 2 diabetes, sarcopenia and osteoporosis, and can predispose to disabilities. Thus, the maintenance of a balance rate of fat, muscle and bone is crucial to preserve metabolic homeostasis and a health status, positively contributing to a successful aging. For this reason, a detailed assessment of BC in elderly is critical and could be an additional preventive personalized strategy for age-related diseases. Despite BMI and other clinical measures, such as waist circumference measurement, waist-hip ratio, underwater weighing and bioelectrical impedance, are widely used as a surrogate measure for body adiposity, they barely reflect the distribution of body fat. Because of the great advantages offered by imaging tools in research and clinics, the attention of clinicians is now moving to powerful imaging techniques such as computed tomography, magnetic resonance imaging, dual-energy X-ray absorptiometry and ultrasound to obtain a more accurate estimation of BC. The aim of this review is to present the state of the art of the imaging techniques that are currently available to measure BC and that can be applied to the study of BC changes in the elderly, outlining advantages and disadvantages of each technique.

Subcutaneous fat mass in infancy and abdominal, pericardial and liver fat assessed by Magnetic Resonance Imaging at the age of 10 years

BACKGROUND/OBJECTIVES

Fat mass development in infancy contributes to later adiposity, but its relation to ectopic fat depots is unknown. We examined the associations of infant subcutaneous fat with childhood general and organ-specific fat.

SUBJECTS/METHODS

Among 593 children from a population-based prospective cohort study, we obtained total subcutaneous fat mass (as sum of biceps, triceps, suprailiacal, and subscapular skinfolds thickness), central-to-total subcutaneous fat ratio (sum of suprailiacal and subscapular skinfold thickness/total subcutaneous fat) at 1.5, 6 and 24 months of age. At 10 years, we assessed BMI, fat mass index (FMI) based on total body fat by dual-energy X-ray absorptiometry, and abdominal subcutaneous, visceral and pericardial fat mass indices, and liver fat fraction by Magnetic Resonance Imaging.

RESULTS

A higher central-to-total subcutaneous fat ratio at 1.5 months only and higher total subcutaneous fat at 6 and 24 months were associated with higher BMI, FMI and subcutaneous fat mass index at 10 years. The observed associations were the strongest between total subcutaneous fat at 24 months and these childhood outcomes (difference per 1-SDS increase in total subcutaneous fat: 0.15 SDS (95% Confidence Interval (CI) 0.08, 0.23), 0.17 SDS (95% CI 0.10, 0.24), 0.16 SDS (95% CI 0.08, 0.23) for BMI, FMI and childhood subcutaneous fat mass index, respectively). Infant subcutaneous fat measures at any time point were not associated with visceral and pericardial fat mass indices, and liver fat fraction at 10 years.

CONCLUSIONS

Our results suggest that infant subcutaneous fat is associated with later childhood abdominal subcutaneous fat and general adiposity, but not with other organ-specific fat depots.

Body composition techniques

Body composition is known to be associated with several diseases, such as cardiovascular disease, diabetes, cancers, osteoporosis and osteoarthritis. Body composition measurements are useful in assessing the effectiveness of nutritional interventions and monitoring the changes associated with growth and disease conditions. Changes in body composition occur when there is a mismatch between nutrient intake and requirement. Altered body composition is observed in conditions such as wasting and stunting when the nutritional intake may be inadequate. Overnutrition on the other hand leads to obesity. Many techniques are available for body composition assessment, which range from simple indirect measures to more sophisticated direct volumetric measurements. Some of the methods that are used today include anthropometry, tracer dilution, densitometry, dual-energy X-ray absorptiometry, air displacement plethysmography and bioelectrical impedance analysis. The methods vary in their precision and accuracy. Imaging techniques such as nuclear magnetic resonance imaging and computed tomography have become powerful tools due to their ability of visualizing and quantifying tissues, organs, or constituents such as muscle and adipose tissue. However, these methods are still considered to be research tools due to their cost and complexity of use. This review was aimed to describe the commonly used methods for body composition analysis and provide a brief introduction on the latest techniques available.

Body Composition Profiling in the UK Biobank Imaging Study

OBJECTIVE

This 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.

METHODS

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.

RESULTS

Matched control analysis showed that higher VAT and MFI were associated with CHD and T2D (P < 0.001). Higher liver fat was associated with T2D (P < 0.001) and lower liver fat with CHD (P < 0.05), matching on VAT. Multivariable modeling showed that lower VAT and MFI were associated with metabolic health (P < 0.001), and liver fat was nonsignificant. Associations remained significant adjusting for sex, age, BMI, alcohol, smoking, and physical activity.

CONCLUSIONS

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.

Infant breastfeeding and childhood general, visceral, liver, and pericardial fat measures assessed by magnetic resonance imaging

Background

Although a longer duration of breastfeeding has been associated with a lower risk of childhood obesity, the impact on specific organ fat depots is largely unknown.

Objective

We examined the associations of any breastfeeding, duration and exclusiveness of breastfeeding, and of age at introduction of solid foods with measures of general, visceral, and organ adiposity at 10 y.

Design

In a population-based prospective cohort study in 4444 children, we obtained information on infant feeding by questionnaires. At the mean age of 9.8 y, we estimated body mass index from height and weight; fat mass index and fat-free mass index by dual-energy X-ray absorptiometry; and visceral fat index, pericardial fat index, and liver fat fraction by MRI. MRI scans were performed in a subgroup of 2646 children.

Results

After adjustment for age and sex, we observed associations of infant feeding with all general, visceral, and organ fat outcomes, except for pericardial fat index, at the age of 10 y. After further adjustment for family-based sociodemographic, maternal lifestyle-related, and childhood factors, only the associations of shorter breastfeeding duration and nonexclusive breastfeeding with a lower fat-free mass index remained significant (P < 0.05). The associations of infant feeding with visceral fat index and liver fat fraction were attenuated to nonsignificant. Maternal education was found to be the strongest confounder.

Conclusion

Our results suggest that the assoiations of any breastfeeding, duration and exclusiveness of breastfeeding, and age at the introduction of solid foods with general, visceral, and organ fat measures at the age of 10 y are largely explained by family-based sociodemographic factors.

Fat fraction mapping using magnetic resonance imaging: insight into pathophysiology

Adipose cells have traditionally been viewed as a simple, passive energy storage depot for triglycerides. However, in recent years it has become clear that adipose cells are highly physiologically active and have a multitude of endocrine, metabolic, haematological and immune functions. Changes in the number or size of adipose cells may be directly implicated in disease (e.g. in the metabolic syndrome), but may also be linked to other pathological processes such as inflammation, malignant infiltration or infarction. MRI is ideally suited to the quantification of fat, since most of the acquired signal comes from water and fat protons. Fat fraction (FF, the proportion of the acquired signal derived from fat protons) has, therefore, emerged as an objective, image-based biomarker of disease. Methods for FF quantification are becoming increasingly available in both research and clinical settings, but these methods vary depending on the scanner, manufacturer, imaging sequence and reconstruction software being used. Careful selection of the imaging method-and correct interpretation-can improve the accuracy of FF measurements, minimize potential confounding factors and maximize clinical utility. Here, we review methods for fat quantification and their strengths and weaknesses, before considering how they can be tailored to specific applications, particularly in the gastrointestinal and musculoskeletal systems. FF quantification is becoming established as a clinical and research tool, and understanding the underlying principles will be helpful to both imaging scientists and clinicians.

MRI adipose tissue and muscle composition analysis-a review of automation techniques

MRI is becoming more frequently used in studies involving measurements of adipose tissue and volume and composition of skeletal muscles. The large amount of data generated by MRI calls for automated analysis methods. This review article presents a summary of automated and semi-automated techniques published between 2013 and 2017. Technical aspects and clinical applications for MRI-based adipose tissue and muscle composition analysis are discussed based on recently published studies. The conclusion is that very few clinical studies have used highly automated analysis methods, despite the rapidly increasing use of MRI for body composition analysis. Possible reasons for this are that the availability of highly automated methods has been limited for non-imaging experts, and also that there is a limited number of studies investigating the reproducibility of automated methods for MRI-based body composition analysis.

Advanced body composition assessment: from body mass index to body composition profiling

This paper gives a brief overview of common non-invasive techniques for body composition analysis and a more in-depth review of a body composition assessment method based on fat-referenced quantitative MRI. Earlier published studies of this method are summarized, and a previously unpublished validation study, based on 4753 subjects from the UK Biobank imaging cohort, comparing the quantitative MRI method with dual-energy X-ray absorptiometry (DXA) is presented. For whole-body measurements of adipose tissue (AT) or fat and lean tissue (LT), DXA and quantitative MRIs show excellent agreement with linear correlation of 0.99 and 0.97, and coefficient of variation (CV) of 4.5 and 4.6 per cent for fat (computed from AT) and LT, respectively, but the agreement was found significantly lower for visceral adipose tissue, with a CV of >20 per cent. The additional ability of MRI to also measure muscle volumes, muscle AT infiltration and ectopic fat, in combination with rapid scanning protocols and efficient image analysis tools, makes quantitative MRI a powerful tool for advanced body composition assessment.