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首页> 外文期刊>Frontiers in Nutrition >Abdominal Fat and Metabolic Health Markers but Not PNPLA3 Genotype Predicts Liver Fat Accumulation in Response to Excess Intake of Energy and Saturated Fat in Healthy Individuals
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Abdominal Fat and Metabolic Health Markers but Not PNPLA3 Genotype Predicts Liver Fat Accumulation in Response to Excess Intake of Energy and Saturated Fat in Healthy Individuals

机译:腹部脂肪和代谢健康标记物,但不是pnpla3基因型预测肝脏脂肪积聚,以应对健康个体的过度摄入和饱和脂肪的过度摄入量

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Background Saturated fat (SFA) has consistently been shown to increase liver fat, but the response appears variable at the individual level. Phenotypic and genotypic characteristics have been demonstrated to modify the hypercholesterolemic effect of SFA but it is unclear which characteristics that predict liver fat accumulation in response to a hypercaloric diet high in SFA. Objective To identify predictors of liver fat accumulation in response to an increased intake of SFA. Design We pooled our two previously conducted double-blind randomized trials (LIPOGAIN and LIPOGAIN-2, clinicaltrials.gov NCT01427140 and NCT02211612) and used data from the n=49 metabolically healthy men (n=32) and women (n=17) randomized to a hypercaloric diet through addition of SFA-rich muffins for 7-8 weeks. Associations between clinical and metabolic variables at baseline and changes in liver fat during the intervention were analyzed using Spearman rank correlation. Linear regression was used to generate a prediction model. Results Liver fat increased by 33% (IQR 5.4-82.7%; P0.0001) in response to excess energy intake and this was not associated (r=0.17, P=0.23) with the increase in body weight (1.9 kg; IQR 1.1-2.9 kg). Liver fat accumulation was similar (P=0.28) in carriers (33%, IQR 14-79%) and non-carriers (33%, IQR -11% to 87%) of the PNPLA3-I148M variant. Baseline visceral and liver fat content, as well as levels of the liver enzyme γ-glutamyl transferase (GT), were the strongest positive predictors of liver fat accumulation – in contrast, adiponectin and the fatty acid 17:0 in adipose tissue were the only negative predictors in univariate analyses. A regression model based on eight clinical and metabolic variables could explain 81% of the variation in liver fat accumulation. Conclusion Our results suggest there exists a highly inter-individual variation in the accumulation of liver fat in metabolically healthy men and women, in response to an increased energy intake from SFA and carbohydrates that occurs over circa two months. This marked variability in liver fat accumulation could largely be predicted by a set of clinical (e.g. GT and BMI) and metabolic (e.g. fatty acids, HOMA-IR and adiponectin) variables assessed at baseline.
机译:背景技术饱和脂肪(SFA)一直被证明可以增加肝脏脂肪,但响应在各个层面上显得可变。已经证明了表型和基因型特征以改变SFA的高胆固醇血糖作用,但目前尚不清楚在SFA中高钙饮食响应肝脂肪累积的哪种特征。目的鉴定肝脂肪累积的预测因子,以响应SFA增加的摄入量增加。设计我们汇集了我们的两种以前进行的双盲随机试验(脂质脂肪酸和脂痛-2,ClinicalTrials.gov NCT01427140和NCT02211612),并使用来自N = 49个代谢健康男性(n = 32)和女性的数据(n = 17)随机化通过添加SFA富含SFA的松饼7-8周来过高钙饮食。使用Spearman等级相关分析了基线下临床和代谢变量与肝脏脂肪变化的关联。线性回归用于生成预测模型。结果肝脏脂肪增加33%(IQR 5.4-82.7%; P <0.0001)响应于过量的能量摄取,并且这与体重增加(1.9公斤; IQR 1.1)没有相关(r = 0.17,p = 0.23) -2.9 kg)。肝脏脂肪累积在PNPLA3-I148M变体的33%,IQR 14-79%)和非载体(33%,IQR -11%至87%)中相似(p = 0.28)。基线内脏和肝脂肪含量,以及肝酶γ-谷氨酸转移酶(GT)的水平,是肝脂肪积累的最强阳性预测因子 - 相比之下,脂联素和脂肪酸17:0脂肪组织中唯一的单变量分析中的否定预测因子。基于八个临床和代谢变量的回归模型可以解释肝脂肪积累的81%的变化。结论我们的成绩表明,肝脏脂肪在代谢健康男性和女性积累的高度间变异,响应于SFA和碳水化合物的增加,在大约两个月内发生的SFA和碳水化合物。这种明显的肝脏脂肪累积的可变性可以通过在基线评估的一组临床(例如GT和BMI)和代谢(例如脂肪酸,HOMA-IR和脂联素)变量来预测。

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