Esther Askani, Susanne Rospleszcz, Roberto Lorbeer, Charlotte Wintergerst, Katharina Müller-Peltzer, Lena S Kiefer, Elias Kellner, Marco Reisert, Wolfgang Rathmann, Annette Peters, Christopher L Schlett, Fabian Bamberg, Corinna Storz
{"title":"肾上腺体积与脂肪组织分区之间的关联--一项全身核磁共振成像研究。","authors":"Esther Askani, Susanne Rospleszcz, Roberto Lorbeer, Charlotte Wintergerst, Katharina Müller-Peltzer, Lena S Kiefer, Elias Kellner, Marco Reisert, Wolfgang Rathmann, Annette Peters, Christopher L Schlett, Fabian Bamberg, Corinna Storz","doi":"10.1186/s12986-024-00823-x","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Obesity is associated with alterations in the hypothalamic-pituitary-adrenal (HPA) axis. Effects of glucocorticoids on adipose tissues appear to depend on the specific adipose depot, in which they take place. In this study, we aimed to investigate the role of MRI-based adrenal gland volume as an imaging marker in association with different adipose tissue compartments.</p><p><strong>Methods: </strong>The study cohort derives from the population-based research platform KORA (Cooperative Health Research in the Augsburg Region, Germany) MRI sub-study, a cross-sectional sub-study investigating the interactions between subclinical metabolic changes and cardiovascular disease in a study sample of 400 participants. Originally, eligible subjects underwent a whole-body MRI. MRI-based segmentations were performed manually and semi-automatically for adrenal gland volume, visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), epi- and pericardial fat and renal sinus fat. Hepatic and pancreatic lipid content were measured as pancreatic proton density fraction (PDFF) and MR-spectroscopic hepatic fat fraction (HFF). Multivariable linear regression analyses were performed.</p><p><strong>Results: </strong>A number of 307 participants (56.2 ± 9.1 years, 60.3% male, 14.3% with type 2 diabetes (T2DM), 30.6% with obesity, 34.2% with hypertension) were included. In multivariable analyses, strong positive associations between adrenal gland volume and VAT, total adipose tissue (TAT) as well as HFF persisted after extensive step-wise adjustment for possible metabolic confounders (VAT: beta = 0.31, 95%-CI [0.71, 0.81], p < 0.001; TAT: beta = 0.14, 95%-CI [0.06, 0.23], p < 0.001; HFF: beta = 1.17, 95%-CI [1.04, 1.31], p = 0.009). In contrast, associations between adrenal gland volume and SAT were attenuated in multivariate analysis after adjusting for BMI. Associations between pancreatic PDFF, epi- and pericardial fat and renal sinus fat were mediated to a great extent by VAT (pancreatic PDFF: 72%, epicardial adipose tissue: 100%, pericardial adipose tissue: 100%, renal sinus fat: 81.5%).</p><p><strong>Conclusion: </strong>Our results found MRI-based adrenal gland volume as a possible imaging biomarker of unfavorable adipose tissue distribution, irrespective of metabolic risk factors. Thus, adrenal gland volume may serve as a potential MRI-based biomarker of metabolic changes and contributes to an individual characterization of metabolic states and individual risk stratification. Future studies should elucidate in a longitudinal study design, if and how HPA axis activation may trigger unfavorable adipose tissue distribution and whether and to which extent this is involved in the pathogenesis of manifest metabolic syndrome.</p>","PeriodicalId":19196,"journal":{"name":"Nutrition & Metabolism","volume":"21 1","pages":"45"},"PeriodicalIF":3.9000,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11234623/pdf/","citationCount":"0","resultStr":"{\"title\":\"Associations between adrenal gland volume and adipose tissue compartments - a whole body MRI study.\",\"authors\":\"Esther Askani, Susanne Rospleszcz, Roberto Lorbeer, Charlotte Wintergerst, Katharina Müller-Peltzer, Lena S Kiefer, Elias Kellner, Marco Reisert, Wolfgang Rathmann, Annette Peters, Christopher L Schlett, Fabian Bamberg, Corinna Storz\",\"doi\":\"10.1186/s12986-024-00823-x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Obesity is associated with alterations in the hypothalamic-pituitary-adrenal (HPA) axis. Effects of glucocorticoids on adipose tissues appear to depend on the specific adipose depot, in which they take place. In this study, we aimed to investigate the role of MRI-based adrenal gland volume as an imaging marker in association with different adipose tissue compartments.</p><p><strong>Methods: </strong>The study cohort derives from the population-based research platform KORA (Cooperative Health Research in the Augsburg Region, Germany) MRI sub-study, a cross-sectional sub-study investigating the interactions between subclinical metabolic changes and cardiovascular disease in a study sample of 400 participants. Originally, eligible subjects underwent a whole-body MRI. MRI-based segmentations were performed manually and semi-automatically for adrenal gland volume, visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), epi- and pericardial fat and renal sinus fat. Hepatic and pancreatic lipid content were measured as pancreatic proton density fraction (PDFF) and MR-spectroscopic hepatic fat fraction (HFF). Multivariable linear regression analyses were performed.</p><p><strong>Results: </strong>A number of 307 participants (56.2 ± 9.1 years, 60.3% male, 14.3% with type 2 diabetes (T2DM), 30.6% with obesity, 34.2% with hypertension) were included. In multivariable analyses, strong positive associations between adrenal gland volume and VAT, total adipose tissue (TAT) as well as HFF persisted after extensive step-wise adjustment for possible metabolic confounders (VAT: beta = 0.31, 95%-CI [0.71, 0.81], p < 0.001; TAT: beta = 0.14, 95%-CI [0.06, 0.23], p < 0.001; HFF: beta = 1.17, 95%-CI [1.04, 1.31], p = 0.009). In contrast, associations between adrenal gland volume and SAT were attenuated in multivariate analysis after adjusting for BMI. Associations between pancreatic PDFF, epi- and pericardial fat and renal sinus fat were mediated to a great extent by VAT (pancreatic PDFF: 72%, epicardial adipose tissue: 100%, pericardial adipose tissue: 100%, renal sinus fat: 81.5%).</p><p><strong>Conclusion: </strong>Our results found MRI-based adrenal gland volume as a possible imaging biomarker of unfavorable adipose tissue distribution, irrespective of metabolic risk factors. Thus, adrenal gland volume may serve as a potential MRI-based biomarker of metabolic changes and contributes to an individual characterization of metabolic states and individual risk stratification. Future studies should elucidate in a longitudinal study design, if and how HPA axis activation may trigger unfavorable adipose tissue distribution and whether and to which extent this is involved in the pathogenesis of manifest metabolic syndrome.</p>\",\"PeriodicalId\":19196,\"journal\":{\"name\":\"Nutrition & Metabolism\",\"volume\":\"21 1\",\"pages\":\"45\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2024-07-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11234623/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nutrition & Metabolism\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1186/s12986-024-00823-x\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"NUTRITION & DIETETICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nutrition & Metabolism","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12986-024-00823-x","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"NUTRITION & DIETETICS","Score":null,"Total":0}
Associations between adrenal gland volume and adipose tissue compartments - a whole body MRI study.
Background: Obesity is associated with alterations in the hypothalamic-pituitary-adrenal (HPA) axis. Effects of glucocorticoids on adipose tissues appear to depend on the specific adipose depot, in which they take place. In this study, we aimed to investigate the role of MRI-based adrenal gland volume as an imaging marker in association with different adipose tissue compartments.
Methods: The study cohort derives from the population-based research platform KORA (Cooperative Health Research in the Augsburg Region, Germany) MRI sub-study, a cross-sectional sub-study investigating the interactions between subclinical metabolic changes and cardiovascular disease in a study sample of 400 participants. Originally, eligible subjects underwent a whole-body MRI. MRI-based segmentations were performed manually and semi-automatically for adrenal gland volume, visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), epi- and pericardial fat and renal sinus fat. Hepatic and pancreatic lipid content were measured as pancreatic proton density fraction (PDFF) and MR-spectroscopic hepatic fat fraction (HFF). Multivariable linear regression analyses were performed.
Results: A number of 307 participants (56.2 ± 9.1 years, 60.3% male, 14.3% with type 2 diabetes (T2DM), 30.6% with obesity, 34.2% with hypertension) were included. In multivariable analyses, strong positive associations between adrenal gland volume and VAT, total adipose tissue (TAT) as well as HFF persisted after extensive step-wise adjustment for possible metabolic confounders (VAT: beta = 0.31, 95%-CI [0.71, 0.81], p < 0.001; TAT: beta = 0.14, 95%-CI [0.06, 0.23], p < 0.001; HFF: beta = 1.17, 95%-CI [1.04, 1.31], p = 0.009). In contrast, associations between adrenal gland volume and SAT were attenuated in multivariate analysis after adjusting for BMI. Associations between pancreatic PDFF, epi- and pericardial fat and renal sinus fat were mediated to a great extent by VAT (pancreatic PDFF: 72%, epicardial adipose tissue: 100%, pericardial adipose tissue: 100%, renal sinus fat: 81.5%).
Conclusion: Our results found MRI-based adrenal gland volume as a possible imaging biomarker of unfavorable adipose tissue distribution, irrespective of metabolic risk factors. Thus, adrenal gland volume may serve as a potential MRI-based biomarker of metabolic changes and contributes to an individual characterization of metabolic states and individual risk stratification. Future studies should elucidate in a longitudinal study design, if and how HPA axis activation may trigger unfavorable adipose tissue distribution and whether and to which extent this is involved in the pathogenesis of manifest metabolic syndrome.
期刊介绍:
Nutrition & Metabolism publishes studies with a clear focus on nutrition and metabolism with applications ranging from nutrition needs, exercise physiology, clinical and population studies, as well as the underlying mechanisms in these aspects.
The areas of interest for Nutrition & Metabolism encompass studies in molecular nutrition in the context of obesity, diabetes, lipedemias, metabolic syndrome and exercise physiology. Manuscripts related to molecular, cellular and human metabolism, nutrient sensing and nutrient–gene interactions are also in interest, as are submissions that have employed new and innovative strategies like metabolomics/lipidomics or other omic-based biomarkers to predict nutritional status and metabolic diseases.
Key areas we wish to encourage submissions from include:
-how diet and specific nutrients interact with genes, proteins or metabolites to influence metabolic phenotypes and disease outcomes;
-the role of epigenetic factors and the microbiome in the pathogenesis of metabolic diseases and their influence on metabolic responses to diet and food components;
-how diet and other environmental factors affect epigenetics and microbiota; the extent to which genetic and nongenetic factors modify personal metabolic responses to diet and food compositions and the mechanisms involved;
-how specific biologic networks and nutrient sensing mechanisms attribute to metabolic variability.