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
{"title":"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。","authors":"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","doi":"10.1172/jci.insight.191872","DOIUrl":null,"url":null,"abstract":"<p><p>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).</p>","PeriodicalId":14722,"journal":{"name":"JCI insight","volume":"10 12","pages":""},"PeriodicalIF":6.3000,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Lipidomic profiling of human adiposomes identifies specific lipid shifts linked to obesity and cardiometabolic risk.\",\"authors\":\"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\",\"doi\":\"10.1172/jci.insight.191872\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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).</p>\",\"PeriodicalId\":14722,\"journal\":{\"name\":\"JCI insight\",\"volume\":\"10 12\",\"pages\":\"\"},\"PeriodicalIF\":6.3000,\"publicationDate\":\"2025-06-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"JCI insight\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1172/jci.insight.191872\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MEDICINE, RESEARCH & EXPERIMENTAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"JCI insight","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1172/jci.insight.191872","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
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).
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.