人类脂肪体的脂质组学分析确定了与肥胖和心脏代谢风险相关的特定脂质转移。

IF 6.3 1区 医学 Q1 MEDICINE, RESEARCH & EXPERIMENTAL
Abeer M Mahmoud, Imaduddin Mirza, Elsayed Metwally, Mohammed H Morsy, Giorgia Scichilone, Monica C Asada, Amro Mostafa, Francesco M Bianco, Mohamed M Ali, Mario A Masrur, Chandra Hassan, Brian T Layden
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引用次数: 0

摘要

背景:肥胖是一个日益严重的健康问题,经常导致代谢紊乱、全身性炎症和血管功能障碍。新的证据表明,脂肪组织来源的细胞外囊泡(脂肪体)可能传播肥胖相关的并发症。然而,它们的脂质组成及其对心脏代谢状态的影响尚不清楚。方法本研究检测了122名参与者(肥胖组75人,瘦肉组47人)的脂肪体脂质组成及其与心脏代谢风险的关系。脂质体通过超离心分离,利用纳米颗粒跟踪和质谱综合脂质组学分析进行表征。心脏代谢评估包括人体测量、身体组成、葡萄糖-胰岛素稳态、脂质谱、炎症标志物和血管功能。结果:与瘦对照组相比,肥胖个体表现出脂肪体释放升高,脂质组成发生变化,包括神经酰胺、游离脂肪酸和酰基肉碱含量升高,磷脂和鞘磷脂水平降低。这些改变与BMI升高、胰岛素抵抗、全身炎症和血管功能受损密切相关。途径富集分析强调了甘油磷脂和鞘脂代谢、胆汁分泌、促炎途径和血管收缩性的失调。利用脂肪体脂质数据的机器学习模型可以准确地对肥胖进行分类,并预测心脏代谢状况,如糖尿病、高血压、血脂异常和肝脏脂肪变性,准确率超过85%。结论肥胖深刻地重塑了脂肪体脂质格局,将脂质变化与炎症、代谢功能障碍和血管损伤联系起来。这些发现强调了脂质体脂作为肥胖和相关心脏代谢疾病的生物标志物,支持个性化干预,并在风险分层和治疗中提供治疗价值。本项目由NIH资助R01HL161386, R00HL140049, P30DK020595 (PI: AMM), R01DK104927和P30DK020595以及VA优异奖(1I01BX003382, PI: BTL)支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Lipidomic profiling of human adiposomes identifies specific lipid shifts linked to obesity and cardiometabolic risk.

BACKGROUNDObesity, a growing health concern, often leads to metabolic disturbances, systemic inflammation, and vascular dysfunction. Emerging evidence suggests that adipose tissue-derived extracellular vesicles (adiposomes) may propagate obesity-related complications. However, their lipid composition and effect on cardiometabolic state remain unclear.METHODSThis study examined the lipid composition of adiposomes in 122 participants (75 in obesity group, 47 in lean group) and its connection to cardiometabolic risk. Adiposomes were isolated via ultracentrifugation and characterized using nanoparticle tracking and comprehensive lipidomic analysis by mass spectrometry. Cardiometabolic assessments included anthropometry, body composition, glucose-insulin homeostasis, lipid profiles, inflammatory markers, and vascular function.RESULTSCompared with lean controls, individuals with obesity exhibited elevated adiposome release and shifts in lipid composition, including higher ceramides, free fatty acids, and acylcarnitines, along with reduced levels of phospholipids and sphingomyelins. These alterations strongly correlated with increased BMI, insulin resistance, systemic inflammation, and impaired vascular function. Pathway enrichment analyses highlight dysregulation in glycerophospholipid and sphingolipid metabolism, bile secretion, proinflammatory pathways, and vascular contractility. Machine-learning models utilizing adiposome lipid data accurately classified obesity and predicted cardiometabolic conditions, such as diabetes, hypertension, dyslipidemia, and liver steatosis, achieving accuracy above 85%.CONCLUSIONObesity profoundly remodels the adiposome lipid landscape, linking lipid changes to inflammation, metabolic dysfunction, and vascular impairment. These findings underscore adiposome lipids as biomarkers for obesity and related cardiometabolic disorders, supporting personalized interventions and offering therapeutic value in risk stratification and treatment.FUNDINGThis project was supported by NIH grants R01HL161386, R00HL140049, P30DK020595 (PI: AMM), R01DK104927, and P30DK020595 as well as by a VA Merit Award (1I01BX003382, PI: BTL).

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来源期刊
JCI insight
JCI insight Medicine-General Medicine
CiteScore
13.70
自引率
1.20%
发文量
543
审稿时长
6 weeks
期刊介绍: JCI Insight is a Gold Open Access journal with a 2022 Impact Factor of 8.0. It publishes high-quality studies in various biomedical specialties, such as autoimmunity, gastroenterology, immunology, metabolism, nephrology, neuroscience, oncology, pulmonology, and vascular biology. The journal focuses on clinically relevant basic and translational research that contributes to the understanding of disease biology and treatment. JCI Insight is self-published by the American Society for Clinical Investigation (ASCI), a nonprofit honor organization of physician-scientists founded in 1908, and it helps fulfill the ASCI's mission to advance medical science through the publication of clinically relevant research reports.
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