Intra-pancreatic fat deposition and its relation to obesity: a magnetic resonance imaging study.

OBJECTIVES: Intra-pancreatic fat deposition (IPFD) is suspected to be associated with various medical conditions. This study aimed to assess pancreatic fat content in lean and obese individuals, characterize obese individuals with and without IPFD, and explore the underlying mechanisms. MATERIALS AND METHODS: Sixty-two obese individuals without diabetes and 35 lean controls underwent magnetic resonance imaging (MRI) using proton density fat fraction (PDFF) maps to evaluate pancreatic and hepatic fat content, and visceral adipose tissue (VAT) content. Pancreatic fibrosis was explored by T1 relaxation time and MR elastography (MRE) measurements. Associations between pancreatic fat, measures of obesity and metabolic syndrome were examined using uni- and multivariate regression analyses. RESULTS: Pancreatic PDFF was higher in obese than in lean controls (median 8.0%, interquartile range (6.1;13.3) % vs 2.6(1.7;3.9)%, p < 0.001). Obese individuals with IPFD (PDFF ≥6.2%) had higher waist circumference (114.0 ± 12.5 cm vs 105.2 ± 8.7 cm, p = 0.007) and VAT (224.9(142.1; 316.1) cm2 vs 168.2(103.4; 195.3) cm2, p < 0.001) than those without. In univariate analysis, pancreatic PDFF in obese individuals correlated with BMI (r = 0.27, p = 0.03), waist circumference (r = 0.44, p < 0.001), VAT (r = 0.37, p = 0.004), hepatic PDFF (r = 0.25, p = 0.046) and diastolic blood pressure (r = 0.32, p = 0.01). However, in multivariate analysis, only VAT was associated to pancreatic fat content. MRI measures of pancreatic fibrosis indicated no evident fibrosis in relation to increased pancreatic fat content. CONCLUSIONS: Pancreatic fat content was increased in obese individuals compared with lean controls and predominantly correlated with the amount of visceral adipose tissue. Pancreatic fat content was not clearly linked to measures of pancreatic fibrosis.

MRI-based quantification of renal fat in obese individuals using different image analysis approaches.

PURPOSE: The purpose of this study was to evaluate different renal proton density fat fraction (PDFF) analysis approaches. Additionally, we assessed renal fat in obese individuals and lean individuals. METHODS: This was a retrospective observational case-control study. Twenty-eight obese individuals and 14 lean controls underwent MRI with multi-point Dixon technique for PDFF maps. The following renal PDFF image analysis approaches were performed and compared: (1) five circular regions of interest (ROIs) in six slices, (2) three circular ROIs in one slice, (3) freehand segmentation of renal parenchyma in one slice, and (4) freehand segmentation of renal parenchyma avoiding the renal border in one slice. Furthermore, renal PDFF was compared between obese and lean individuals. RESULTS: Methods 1, 2, and 4 were positively correlated (r ≥ 0.498, p ≤ 0.001). Renal PDFF values varied more with regards to ROI placement within slices than mean PDFF between slices. Using all methods, the obese individuals had significantly higher renal PDFF values compared with the lean controls. CONCLUSION: Renal PDFF should be measured covering large areas of the kidney while excluding artifacts. This can be achieved using multiple circular ROIs. Increased lipid accumulation in the kidneys was related to obesity.

Extracellular vesicle-associated proteins as potential biomarkers.

Every cell in the body secretes extracellular vesicles (EVs) possibly as cellular signaling components and these cell-derivatives can be found in multiple numbers in biological fluids. EVs have in the scientific field received great attention in relation to pathophysiology and disease diagnostics. Altered protein expressions associated with circulating EVs in diseased individuals can serve as biomarkers for different disease states. This capacity paves the way for non-invasive screening tools and early diagnostic markers. However, no isolation method of EVs has been acknowledged as the "golden standard," thus reproducibility of the studies remains inadequate. Increasing interest in EV proteins as disease biomarkers could give rise to more scientific knowledge with diagnostic applicability. In this chapter, studies of proteins believed to be associated with EVs within cancer, autoimmunity, metabolic and neurodegenerative diseases have been outlined.

Mass-Spectrometry Based Proteome Comparison of Extracellular Vesicle Isolation Methods: Comparison of ME-kit, Size-Exclusion Chromatography, and High-Speed Centrifugation.

Extracellular vesicles (EVs) are small membrane-enclosed particles released by cells under various conditions specific to cells' biological states. Hence, mass-spectrometry (MS) based proteome analysis of EVs in plasma has gained much attention as a method to discover novel protein biomarkers. MS analysis of EVs in plasma is challenging and EV isolation is usually necessary. Therefore, we compared differences in abundance, subtypes, and contamination for EVs isolated by high-speed centrifugation, size exclusion chromatography (SEC), and peptide-affinity precipitation (PAP/ME kit) for subsequent MS-based proteome analysis. Successful EV isolation was evaluated by nanoparticle-tracking analysis, immunoblotting, and transmission electron microscopy, while EV abundance, EV subtypes, and contamination was evaluated by label-free tandem MS. High-speed centrifugation and SEC isolates showed high EV abundance at the expense of contamination by non-EV proteins and lipoproteins, respectively. These two methods also resulted in EVs of a similar type, however, with smaller EVs in SEC isolates. PAP isolates had a relatively low EV abundance and high contamination. We consider high-speed centrifugation and SEC suitable as EV isolation for MS biomarker studies, where the choice between the two should depend on the scientific questions and whether the focus is on larger or smaller EVs or a combination of both.