Changes of renal sinus fat and renal parenchymal fat during an 18-month randomized weight loss trial

Zelicha, Hila; Schwarzfuchs, Dan; Shelef, Ilan; Gepner, Yftach; Tsaban, Gal; Tene, Lilac; Meir, Anat Yaskolka; Bilitzky, Avital; Komy, Oded; Cohen, Noa; Bril, Nitzan; Rein, Michal; Serfaty, Dana; Kenigsbuch, Shira; Chassidim, Yoash; Sarusi, Benjamin; Thiery, Joachim; Ceglarek, Uta; Stümvoll, Michael; Blüher, Matthias; Haviv, Yosef S.; Stampfer, Meir J.; Rudich, Assaf; Shai, Iris

doi:10.1016/j.clnu.2017.04.007

Cited by 49 publications

(53 citation statements)

References 29 publications

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“…Further studies that modulate the amount of RSF, notably weight loss are warranted [27], however, it will be difficult to tease out the specific effects of a reduction in RSF volume on renal function, when VAT and total body fat are concomitantly lowered. Furthermore, it will be interesting to measure proteins and cytokines that are secreted by RSF in different disease conditions such as obesity or T2D to better assess RSF function.…”

Section: Discussionmentioning

confidence: 99%

Renal sinus fat and renal hemodynamics: a cross-sectional analysis

Spit

Muskiet

Tonneijck

et al. 2019

Magn Reson Mater Phy

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Objectives Increased renal sinus fat (RSF) is associated with hypertension and chronic kidney disease, but underlying mechanisms are incompletely understood. We evaluated relations between RSF and gold-standard measures of renal hemodynamics in type 2 diabetes (T2D) patients. Methods Fifty-one T2D patients [age 63 ± 7 years; BMI 31 (28-34) kg/m 2 ; GFR 83 ± 16 mL/min/1.73 m 2 ] underwent MRIscanning to quantify RSF volume, and subcutaneous and visceral adipose tissue compartments (SAT and VAT, respectively). GFR and effective renal plasma flow (ERPF) were determined by inulin and PAH clearances, respectively. Effective renal vascular resistance (ERVR) was calculated. Results RSF correlated negatively with GFR (r = − 0.38; p = 0.006) and ERPF (r = − 0.38; p = 0.006) and positively with mean arterial pressure (MAP) (r = 0.29; p = 0.039) and ERVR (r = 0.45, p = 0.001), which persisted after adjustment for VAT, MAP, sex, and BMI. After correction for age, ERVR remained significantly related to RSF. Conclusions In T2D patients, higher RSF volume was negatively associated to GFR. In addition, RSF volume was positively associated with increased renal vascular resistance, which may mediate hypertension and CKD development. Further research is needed to investigate how RSF may alter the (afferent) vascular resistance of the renal vasculature.Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Section: Discussionmentioning

confidence: 99%

Renal sinus fat and renal hemodynamics: a cross-sectional analysis

Spit

Muskiet

Tonneijck

et al. 2019

Magn Reson Mater Phy

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“…The flow of the study selection procedure which followed the literature search is summarised in Figure 1 Table 2 . Five trials [45][46][47][48][49] did not include LDL-C as an outcome; ten trials [50][51][52][53][54][55][56][57][58][59] were performed on participants with Diabetes mellitus and/or CVD; eleven trials [60][61][62][63][64][65][66][67][68][69][70] had less than 100 randomised participants; three [71][72][73] had duration < 6 months; two trials 74,75 did not report on SD or 95% CI; seven trials [76][77][78][79][80][81][82] were irrelevant with inappropriate intervention; and one trial 83 was dismissed based on high attrition rate and high risk of bias.…”

Section: Literature Searchmentioning

confidence: 99%

“…Hu et al(2015) 45 McManus et al(2001) 46 Viegener et al(1990) 47 Zelicha et al(2017) 48 Blüher et al(2012) 138 D. mellitus and/or CVD Shai et al (2008) 50 Cardillo et al (2006) 51 Tsai et al (2005) 52 Stern et al (2004) 53 Dyson et al (2007) 54 Samaha et al (2003) 55 Yancy et al (2010) 56 Hu et al (2016) 57 Turer et al (2012) 58 Qi et al (2015) 59 <100 participants on start Lim et al (2010) 60 Das et al (2007) 61 Foster et al (2003) 62 Seshadri et al (2004) 63 Brehm et al (2003) 64 Keogh et al (2007) 65 Ebbeling et al (2007) 66 Bradley et al (2009) 67 Tay et al (2008) 68 Dansinger et al (2005) 69 Leichtle et al (2011) 70…”

Section: Reason For Exclusion Authors No Ldl-c Reportedmentioning

confidence: 99%

Effects of carbohydrate-restricted diets on low-density lipoprotein cholesterol levels in overweight and obese adults: a systematic review and meta-analysis

et al. 2018

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Carbohydrate restricted diets may increase low density lipoprotein-cholesterol and thereby cardiovascular risk. Objective A systematic review and meta-analyses was conducted to compare the effects of very low, low and moderate carbohydrate higher fat diets versus high-carbohydrate low-fat diets on low density lipoprotein-cholesterol and other lipid markers in overweight/obese adults. Data Sources Medline, PubMed, Cochrane Central, and CINAHL Plus were searched to identify large randomised controlled trials (n > 100) with duration ≥ 6 months. Data Extraction Eight randomised controlled trials (n = 1633, 818 carbohydrate restricted, 815 low fat diet) were included. Data Analysis Quality assessment and risk of bias, a random effects model, sensitivity and subgroup analysis based on the degree of carbohydrate restriction were performed using Cochrane Review Manager. Results were reported according to 'Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocol'. Results Carbohydrate restricted diets showed a none significant difference in low density lipoproteincholesterol after 6, 12, and 24 months. While an overall pooled analysis statistically favoured low-fat diets [0.07 mmol/L; 95% CI 0.02, 0.13; p = 0.009] this was clinically insignificant. High density lipoprotein-cholesterol and plasma triglycerides at 6 and 12 months, favoured carbohydrate restricted diets [0.08 mmol/L, 95% CI 0.06, 0.11; p < 1x10-5 and-0.13 mmol/L, 95% CI-0.19,-0.08; p < 1x10-5 ] respectively. These favourable changes were more marked in the subgroup with very-low carbohydrate content (< 50 g/day) [0.12 mmol/L, 95% CI 0.10, 0.14; p < 1x10-5 and-0.19 mmol/L, 95% CI-0.26,-0.12, p = 0.02] respectively.

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“…As perivascular fat depot it is in close contact with the adventitia of large, medium and small arteries and possesses unique features differing from other fat depots. Renal sinus fat is apparently directly linked to obesity [9] as well as liver function [10] and is thought to obstruct the blood and lymph outflow of the kidney, thus increasing parenchymal hydrostatic pressure leading to increasing organ volume [11]. Similarly, to other perivascular fat tissue particularly intrahepatic fat and visceral adipose tissue (VAT), it is associated with cardiovascular risk factors such as hypertension, diabetes and chronic kidney disease [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Renal and renal sinus fat volumes as quantified by magnetic resonance imaging in subjects with prediabetes, diabetes, and normal glucose tolerance

Notohamiprodjo

Goepfert

Will³

et al. 2020

PLoS ONE

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We hypothesize that MRI-based renal compartment volumes, particularly renal sinus fat as locally and potentially independently acting perivascular fat tissue, increase with glucose intolerance. We therefore analyze the distribution of renal volumes in individuals with normal glucose levels and prediabetic and diabetic individuals and investigate potential associations with other typical cardiometabolic biomarkers. Material and methods The sample comprised N = 366 participants who were either normoglycemic (N = 230), had prediabetes (N = 87) or diabetes (N = 49), as determined by Oral Glucose Tolerance Test. Other covariates were obtained by standardized measurements and interviews. Wholebody MR measurements were performed on a 3 Tesla scanner. For assessment of the kidneys, a coronal T1w dual-echo Dixon and a coronal T2w single shot fast spin echo sequence were employed. Stepwise semi-automated segmentation of the kidneys on the Dixon-sequences was based on thresholding and geometric assumptions generating volumes for the kidneys and sinus fat. Inter-and intra-reader variability were determined on a subset of 40 subjects. Associations between glycemic status and renal volumes were evaluated by linear regression models, adjusted for other potential confounding variables. Furthermore, the association of renal volumes with visceral adipose tissue was assessed by linear regression models and Pearson's correlation coefficient.

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Changes of renal sinus fat and renal parenchymal fat during an 18-month randomized weight loss trial

Cited by 49 publications

References 29 publications

Renal sinus fat and renal hemodynamics: a cross-sectional analysis

Renal sinus fat and renal hemodynamics: a cross-sectional analysis

Effects of carbohydrate-restricted diets on low-density lipoprotein cholesterol levels in overweight and obese adults: a systematic review and meta-analysis

Renal and renal sinus fat volumes as quantified by magnetic resonance imaging in subjects with prediabetes, diabetes, and normal glucose tolerance

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