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 Earlier published studies of this method are summarized, and a previously unpublished validation study, based on 4753 subjects from the UK Biobank imaging cohort, comparing the quantitative MRI method with dual-energy X-ray absorptiometry (DXA)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.
UK Biobank is a population-based cohort of half a million participants aged 40-69 years recruited between 2006 and 2010. In 2014, UK Biobank started the world's largest multi-modal imaging study, ...with the aim of re-inviting 100,000 participants to undergo brain, cardiac and abdominal magnetic resonance imaging, dual-energy X-ray absorptiometry and carotid ultrasound. The combination of large-scale multi-modal imaging with extensive phenotypic and genetic data offers an unprecedented resource for scientists to conduct health-related research. This article provides an in-depth overview of the imaging enhancement, including the data collected, how it is managed and processed, and future directions.
Increased intake of dietary carbohydrate that is fermented in the colon by the microbiota has been reported to decrease body weight, although the mechanism remains unclear. Here we use in ...vivo(11)C-acetate and PET-CT scanning to show that colonic acetate crosses the blood-brain barrier and is taken up by the brain. Intraperitoneal acetate results in appetite suppression and hypothalamic neuronal activation patterning. We also show that acetate administration is associated with activation of acetyl-CoA carboxylase and changes in the expression profiles of regulatory neuropeptides that favour appetite suppression. Furthermore, we demonstrate through (13)C high-resolution magic-angle-spinning that (13)C acetate from fermentation of (13)C-labelled carbohydrate in the colon increases hypothalamic (13)C acetate above baseline levels. Hypothalamic (13)C acetate regionally increases the (13)C labelling of the glutamate-glutamine and GABA neuroglial cycles, with hypothalamic (13)C lactate reaching higher levels than the 'remaining brain'. These observations suggest that acetate has a direct role in central appetite regulation.
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.
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.
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.
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.
These data demonstrate for the first time that increasing colonic propionate prevents weight gain in overweight adult humans.
NCT00750438.
Quantitative and accurate measurements of fat and muscle in the body are important for prevention and diagnosis of diseases related to obesity and muscle degeneration. Manually segmenting muscle and ...fat compartments in MR body-images is laborious and time-consuming, hindering implementation in large cohorts. In the present study, the feasibility and success-rate of a Dixon-based MR scan followed by an intensity-normalised, non-rigid, multi-atlas based segmentation was investigated in a cohort of 3,000 subjects.
3,000 participants in the in-depth phenotyping arm of the UK Biobank imaging study underwent a comprehensive MR examination. All subjects were scanned using a 1.5 T MR-scanner with the dual-echo Dixon Vibe protocol, covering neck to knees. Subjects were scanned with six slabs in supine position, without localizer. Automated body composition analysis was performed using the AMRA Profiler™ system, to segment and quantify visceral adipose tissue (VAT), abdominal subcutaneous adipose tissue (ASAT) and thigh muscles. Technical quality assurance was performed and a standard set of acceptance/rejection criteria was established. Descriptive statistics were calculated for all volume measurements and quality assurance metrics.
Of the 3,000 subjects, 2,995 (99.83%) were analysable for body fat, 2,828 (94.27%) were analysable when body fat and one thigh was included, and 2,775 (92.50%) were fully analysable for body fat and both thigh muscles. Reasons for not being able to analyse datasets were mainly due to missing slabs in the acquisition, or patient positioned so that large parts of the volume was outside of the field-of-view.
In conclusion, this study showed that the rapid UK Biobank MR-protocol was well tolerated by most subjects and sufficiently robust to achieve very high success-rate for body composition analysis. This research has been conducted using the UK Biobank Resource.
Hepatic steatosis affects 20% to 30% of the general adult population in the western world. Currently, the technique of choice for determining hepatic fat deposition and the stage of fibrosis is liver ...biopsy. However, it is an invasive procedure and its use is limited, particularly in children. It may also be subject to sampling error. Non-invasive techniques such as ultrasound, computerised tomography （CT）, magnetic resonance imaging （MRI） and proton magnetic resonance spectroscopy （^1H MRS） can detect hepatic steatosis, but currently cannot distinguish between simple steatosis and steatohepatitis, or stage the degree of fibrosis accurately. Ultrasound is widely used to detect hepatic steatosis, but its sensitivity is reduced in the morbidly obese and also in those with small amounts of fatty infiltration. It has been used to grade hepatic fat content, but this is subjective. CT can detect hepatic steatosis, but exposes subjects to ionising radiation, thus limiting its use in longitudinal studies and in children. Recently, magnetic resonance （MR） techniques using chemical shift imaging have provided a quantitative assessment of the degree of hepatic fatty infiltration, which correlates well with liver biopsy results in the same patients. Similarly, in vivo ^1H MRS is a fast, safe, non-invasive method for the quantification of intrahepatocellular lipid （IHCL） levels. Both techniques will be useful tools in future longitudinal clinical studies, either in examining the natural history of conditions causing hepatic steatosis （e.g. non-alcoholic fatty liver disease）, or in testing new treatments for these conditions.
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.
Non-alcoholic fatty liver disease and the risk of progression to steatohepatitis, cirrhosis and hepatocellular carcinoma have been identified as major public health concerns. We have demonstrated the ...feasibility and potential value of measuring liver fat content by magnetic resonance imaging (MRI) in a large population in this study of 4,949 participants (aged 45-73 years) in the UK Biobank imaging enhancement. Despite requirements for only a single (≤3min) scan of each subject, liver fat was able to be measured as the MRI proton density fat fraction (PDFF) with an overall success rate of 96.4%. The overall hepatic fat distribution was centred between 1-2%, and was highly skewed towards higher fat content. The mean PDFF was 3.91%, and median 2.11%. Analysis of PDFF in conjunction with other data fields available from the UK Biobank Resource showed associations of increased liver fat with greater age, BMI, weight gain, high blood pressure and Type 2 diabetes. Subjects with BMI less than 25 kg/m2 had a low risk (5%) of high liver fat (PDFF > 5.5%), whereas in the higher BMI population (>30 kg/m2) the prevalence of high liver fat was approximately 1 in 3. These data suggest that population screening to identify people with high PDFF is possible and could be cost effective. MRI based PDFF is an effective method for this. Finally, although cross sectional, this study suggests the utility of the PDFF measurement within UK Biobank, particularly for applications to elucidating risk factors through associations with prospectively acquired data on clinical outcomes of liver diseases, including non-alcoholic fatty liver disease.
The mechanisms underlying the association of steatotic liver disease with cardiovascular and cancer outcomes are poorly understood. We aimed to use MRI-derived measures of liver fat and genetics to ...investigate causal mechanisms that link higher liver fat to various health outcomes.
We conducted a genome-wide association study on 37,358 UK Biobank participants to identify genetic variants associated with liver fat measured from MRI scans. We used a Mendelian randomisation approach to investigate the causal effect of liver fat on health outcomes independent of BMI, alcohol consumption and lipids using data from published genome-wide association studies and FinnGen.
We identified 13 genetic variants associated with liver fat that had differing effects on the risks of health outcomes. Genetic variants associated with impaired hepatic triglyceride export showed liver fat-increasing alleles to be correlated with a reduced risk of coronary artery disease and myocardial infarction but an elevated risk of type 2 diabetes, while variants associated with enhanced de novo lipogenesis showed liver fat-increasing alleles to be linked to a higher risk of myocardial infarction and coronary artery disease. Genetically higher liver fat content increased the risk of non-alcohol-related cirrhosis, hepatocellular carcinoma, and intrahepatic bile duct and gallbladder cancers, exhibiting a dose-dependent relationship, irrespective of the mechanism.
This study provides fresh insight into the heterogeneous effect of liver fat on health outcomes. It challenges the notion that liver fat per se is an independent risk factor for cardiovascular disease, underscoring the dependency of this association on the specific mechanisms that drive fat accumulation in the liver. However, excess liver fat, regardless of the underlying mechanism, appears to be causally linked to cirrhosis and cancers in a dose-dependent manner.
This research advances our understanding of the heterogeneity in mechanisms influencing liver fat accumulation, providing new insights into how liver fat accumulation may impact various health outcomes. The findings challenge the notion that liver fat is an independent risk factor for cardiovascular disease and highlight the mechanistic effect of some genetic variants on fat accumulation and the development of cardiovascular diseases. This study is of particular importance for healthcare professionals including physicians and researchers, as well as patients, as it allows for more targeted and personalised treatment by understanding the relationship between liver fat and various health outcomes. The findings emphasise the need for a personalised management approach and a reshaping of risk assessment criteria. It also provides room for prioritising a clinical intervention aimed at reducing liver fat content (likely via intentional weight loss) that could help protect against liver-related fibrosis and cancer.
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•Genetic analysis of UK Biobank MRI data revealed 13 variants associated with liver fat.•Key mechanisms for liver fat accumulation include lipid retention and enhanced de novo lipogenesis.•Impaired triglyceride export lowers cardiovascular risk, while enhanced de novo lipogenesis increases it.•Higher liver fat is causally linked to non-alcoholic cirrhosis, liver cancers, and type 2 diabetes, regardless of the underlying mechanism.•Findings indicate the need for personalized treatment and risk assessment based on liver fat accumulation mechanisms.
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