基线脂肪组织特征对肥胖者低热量饮食中脂肪组织体积变化的影响——LION研究结果

发布时间：2024-12-25 09:58

控制饮食中的饱和脂肪和反式脂肪，它们会增加热量并可能影响减肥效果。 #生活常识# #日常生活小窍门# #运动健身建议# #减肥小贴士#

AbstractBackground/ObjectivesWeight loss outcomes vary individually. Magnetic resonance imaging (MRI)-based evaluation of adipose tissue (AT) might help to identify AT characteristics that predict AT loss. This study aimed to assess the impact of an 8-week low-calorie diet (LCD) on different AT depots and to identify predictors of short-term AT loss using MRI in adults with obesity.MethodsEighty-one adults with obesity (mean BMI 34.08 ± 2.75 kg/m², mean age 46.3 ± 10.97 years, 49 females) prospectively underwent baseline MRI (liver dome to femoral head) and anthropometric measurements (BMI, waist-to-hip-ratio, body fat), followed by a post-LCD-examination.

摘要背景/目的减肥结果因人而异。基于磁共振成像（MRI）的脂肪组织（AT）评估可能有助于确定预测AT损失的AT特征。本研究旨在评估8周低热量饮食（LCD）对不同AT仓库的影响，并使用MRI确定肥胖成年人短期AT损失的预测因子。方法前瞻性地对51名肥胖成年人（平均BMI 34.08±2.75 kg/m²，平均年龄46.3±10.97岁，49名女性）进行基线MRI（肝顶至股骨头）和人体测量（BMI，腰臀比，体脂），然后进行LCD后检查。

Visceral and subcutaneous AT (VAT and SAT) volumes and AT fat fraction were extracted from the MRI data. Apparent lipid volumes based on MRI were calculated as approximation for the lipid contained in the AT. SAT and VAT volumes were subdivided into equidistant thirds along the craniocaudal axis and normalized by length of the segmentation.

从MRI数据中提取内脏和皮下AT（VAT和SAT）体积和AT脂肪分数。基于MRI的表观脂质体积计算为AT中所含脂质的近似值。SAT和VAT体积沿颅尾轴细分为等距的三分之一，并通过分割长度进行归一化。

T-tests compared baseline and follow-up measurements and sex differences. Effect sizes on subdivided AT volumes were compared. Spearman Rank correlation explored associations between baseline parameters and AT loss. Multiple regression analysis identified baseline predictors for AT loss.ResultsFollowing the LCD, participants exhibited significant weight loss (11.61 ± 3.07 kg, p < 0.01) and reductions in all MRI-based AT parameters (p < 0.01).

T检验比较了基线和随访测量以及性别差异。比较了细分AT体积的影响大小。Spearman等级相关性探讨了基线参数与损失之间的关联。多元回归分析确定了损失的基线预测因子。结果LCD后，参与者体重明显减轻（11.61±3.07 kg，p<0.01），所有基于MRI的AT参数均降低（p<0.01）。

Absolute SAT loss exceeded VAT loss, while relative apparent lipid loss was higher in VAT (both p < 0.01). The lower abdominopelvic third showed the most significant SAT and VAT reduction. The predictor of most AT and apparent lipid losses was the normalized baseline SAT volume in the lower abdominopelvic third, with smaller volumes favoring g.

绝对SAT损失超过VAT损失，而VAT中相对表观脂质损失更高（均p<0.01）。下腹盆腔第三位显示SAT和VAT降低最为显着。大多数AT和表观脂质损失的预测因子是下腹盆腔第三位的标准化基线SAT体积，较小的体积有利于g。

IntroductionOne strategy to prevent obesity-related comorbidities such as diabetes, cardiovascular disease, and certain cancers is a lifestyle intervention aiming at weight loss, ideally by reducing excess adipose tissue (AT) and ectopic fat [1]. The various fat depots have distinct metabolic profiles due to substantial functional differences [2].

引言预防肥胖相关合并症（如糖尿病，心血管疾病和某些癌症）的一种策略是旨在减肥的生活方式干预，理想情况下是通过减少过量脂肪组织（at）和异位脂肪（1）。由于功能差异很大，各种脂肪库具有不同的代谢特征（2）。

Weight loss is also accompanied by loss of organ- and muscle mass; thus, the success of a weight loss intervention is best assessed by evaluating changes in the AT.Outcomes of a short-term weight-reducing intervention have a significant impact on long-term weight maintenance success [3,4,5]. This short-term effect, in turn, varies substantially between persons, with varying loss of AT in the different AT depots.

体重减轻还伴随着器官和肌肉质量的减少；因此，减肥干预的成功最好通过评估AT的变化来评估。短期减肥干预的结果对长期体重维持的成功有显着影响[3,4,5]。反过来，这种短期影响因人而异，不同AT站点的AT损失不同。

The ability to accomplish short-term weight loss is dependent on many factors, including adherence to the intervention [6], insulin resistance [7, 8], genetics and epigenetics [9, 10], gut microbiota [11], sleeping habits [12, 13] or basal metabolic rate [14, 15]. Age and sex are also factors often discussed, but findings from several studies are inconsistent [16].The distribution of AT is also relevant for the success of a weight loss intervention.

完成短期减肥的能力取决于许多因素，包括坚持干预（6），胰岛素抵抗（7，8），遗传学和表观遗传学（9，10），肠道微生物群（11），睡眠习惯（12，13）或基础代谢率（14，15）。年龄和性别也是经常讨论的因素，但几项研究的结果不一致（16）。AT的分布也与减肥干预的成功有关。

People with abdominal obesity and thus more visceral adipose tissue (VAT) benefit more from weight loss than those with gluteal-femoral obesity, who tend to have more subcutaneous adipose tissue (SAT) [17]. Such AT characteristics might be predictors for an intervention’s success but are mainly assessed by anthropometric measurements [16, 18, 19].

腹部肥胖者和内脏脂肪组织（VAT）较多的人比臀股肥胖者从体重减轻中获益更多，臀股肥胖者往往有更多的皮下脂肪组织（SAT）。这种AT特征可能是干预成功的预测因素，但主要通过人体测量来评估[16，18，19]。

A few studies used imaging techniques and found that increased VAT, VAT/SAT ratio, or total AT at baseline are associated with greater weight- and VAT loss [20,21,22,23,24,25]. However, most studies performing a weight loss interv.

一些研究使用成像技术，发现基线时增值税，增值税/SAT比率或总AT的增加与更大的体重和增值税损失相关[20,21,22,23,24,25]。然而，大多数研究进行减肥interv。

The network results from the deep learning-based automated segmentation pipeline are available at: https://github.com/BMRRgroup/lion-abd-seg-nnunet and https://github.com/BMRRgroup/lion-abd-seg-3dunet. The anthropometric and imaging datasets analyzed during the current study are available from the corresponding author on reasonable request..

基于深度学习的自动细分管道的网络结果可在以下网站获得：https://github.com/BMRRgroup/lion-abd-seg-nnunet和https://github.com/BMRRgroup/lion-abd-seg-3dunet.本研究期间分析的人体测量和成像数据集可根据合理要求从通讯作者处获得。。

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Download referencesAcknowledgementsThe authors would like to thank Sandhanakrishnan Ravichandran for his help and input in the data cleaning process and Lisa Patzelt for her help with the MR scanning. Furthermore, the authors are grateful to all participants of the LION Study and to all members of the LION study team, especially Vincent Winkler, Miriam Neidhardt, Bea Klos, Sandra Bayer, Judith Bodensteiner, Christine Reimers, Christina Ikkert, Andrea Stiglmeier, Alexandra Sandner, Bärbel Huber, and Kurt Rack.

下载参考文献致谢作者要感谢Sandhanakrishnan Ravichandran在数据清理过程中的帮助和投入，以及Lisa Patzelt在MR扫描方面的帮助。此外，作者感谢LION研究的所有参与者以及LION研究团队的所有成员，特别是文森特·温克勒（Vincent Winkler），米丽亚姆·奈达德（Miriam Neidhardt），比亚克洛斯（Bea Klos），桑德拉·拜尔（Sandra Bayer），朱迪思·博登斯坦（Judith Bodensteiner），克里斯蒂娜·赖默斯（Christine Reimers），克里斯蒂娜·艾克特（Christina Ikkert），安德里亚·斯蒂格梅尔（Andrea Stiglmeier），亚历山。

We thank the Munich Study Center for support in data management.FundingThis study is funded by the German Federal Ministry of Education and Research (BMBF, grant number: 01EA1709) within the framework of the Junior Research Group “Personalized Nutrition & eHealth (PeNut)” of the enable Competence Cluster of Nutrition Research.

我们感谢慕尼黑研究中心在数据管理方面的支持。资助本研究由德国联邦教育和研究部（BMBF，资助号：01EA1709）在营养研究能力集群的初级研究小组“个性化营养与电子健康（PeNut）”的框架内资助。

In addition, the analysis was part of the project “Imaging, metabolic risk, and genetics: Algorithms based on Artificial Intelligence to predict metabolic changes through Lifestyle Intervention (IMaGENE)” funded by BMBF (grant number: 16DKWN075). Further, the present work was supported by the German Research Foundation (project number 450799851 and project number 455422993/FOR5298-iMAGO-P1).

此外，该分析是由BMBF资助的项目“成像，代谢风险和遗传学：基于人工智能的算法，通过生活方式干预预测代谢变化（IMaGENE）”的一部分（授权号：16DKWN075）。此外，目前的工作得到了德国研究基金会的支持（项目编号450799851和项目编号455422993/FOR5298-iMAGO-P1）。

The authors from the Institute of Radiology also acknowledge research support from Philips Healthcare. Open Access funding enabled and organized by Projekt DEAL.Author informationAuthor notesThese authors jointly supervised this work: Christina Holzapfel, Dimitrios C. Karampinos.Authors and AffiliationsInstitute of Diagnostic and Interventional Radiology, School of Medicine and Health, Technical University of Munich, Munich, GermanyDaniela Junker, Mingming Wu, Johannes Raspe, Selina Rupp, Jessie Han, Stella M.

放射学研究所的作者也感谢飞利浦医疗保健的研究支持。由Projekt交易启用和组织的开放获取资金。作者信息作者注意到这些作者共同监督了这项工作：克里斯蒂娜·霍尔扎普费尔（ChristinaHolzapfel），迪米特里奥斯·卡兰皮诺斯（DimitriosC.Karampinos）。作者和附属机构慕尼黑工业大学医学与健康学院诊断与介入放射学研究所，德国Daniela Junker，吴明明，Johannes Raspe，Selina Rupp，Jessie Han，Stella M。

Näbauer, Arun Somasundaram, E.

Nábauer，Arun Somasundaram，E。

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PubMed Google ScholarContributionsDJ: conception and design of the study protocol, medical supervision, data extraction, analysis and interpretation, drafting and revision of the manuscript. MWu: setting up the MRI protocol, collecting and extracting data, setting up the segmentation pipeline, cleaning data, revision of the manuscript.

PubMed谷歌学术贡献SDJ：研究方案的概念和设计，医疗监督，数据提取，分析和解释，手稿的起草和修订。MWu：建立MRI协议，收集和提取数据，建立分割管道，清理数据，修改稿件。

JR: setting up the algorithm for subdivision of the segmented region, MRI data collection, revision of the manuscript. SR, JH and SMN: study coordination on the part of Radiology, MRI procedures and data collection, data cleaning, data extraction and data analysis. AR: study coordination on the part of Nutritional Medicine, recruitment and screening of study participants, data collection, analysis and interpretation, revision of the manuscript.

JR：建立分割区域细分的算法，MRI数据收集，手稿修订。SR，JH和SMN：放射学，MRI程序和数据收集，数据清理，数据提取和数据分析方面的研究协调。AR：营养医学方面的研究协调，研究参与者的招募和筛选，数据收集，分析和解释，手稿的修订。

MWi: study coordination on the part of Nutritional Medicine, recruitment and screening of study participants, data collection and extraction. AS: setting up the segmentation pipeline, data extraction and data cleaning. EB: medical supervision and supervision of data collection and segmentation. BW: data analysis and interpretation, providing detailed advice on all statistical issues.

MWi：营养医学方面的研究协调，研究参与者的招募和筛选，数据收集和提取。AS：设置分割管道，数据提取和数据清理。EB：医疗监督和数据收集和分割监督。BW：数据分析和解释，就所有统计问题提供详细建议。

MRM: conception and design of the study. HH: conception and design of the study, data interpretation, revision of the manuscript. CH: conception, design and supervision of the study, data collection, extraction and analysis, data interpretation, revision of the manuscript. DCK: conception and design of the study, supervision of data collection, extraction and analysis, data interpretation, revision of the manuscript.Corresponding authorCorrespondence to.

MRM：研究的概念和设计。HH：研究的概念和设计，数据解释，手稿修订。CH：研究的概念，设计和监督，数据收集，提取和分析，数据解释，稿件修订。DCK：研究的概念和设计，数据收集的监督，提取和分析，数据解释，手稿的修订。对应作者对应。

Daniela Junker.Ethics declarations

丹妮拉·容克。道德宣言

Competing interests

相互竞争的利益

DCK receives grant support from Philips Healthcare. HH is a member of the scientific advisory board of Oviva AG (Zurich, Switzerland) and CH of 4sigma GmbH (Oberhaching, Germany). HH and CH received speaker honoraria from Novo Nordisk (Copenhagen, Denmark). The other authors declare no conflicts of interest..

DCK获得飞利浦医疗保健的资助。HH是Oviva AG（瑞士苏黎世）科学顾问委员会和4sigma GmbH（德国奥伯海兴）科学顾问委员会的成员。HH和CH收到了诺和诺德（丹麦哥本哈根）的演讲者酬金。其他作者声明没有利益冲突。。

All procedures were performed following the ethical standards of the institutional research committee and with the Helsinki Declaration and its later amendments or comparable ethical standards. Written informed consent was obtained from all participants prior to data collection. Study protocols and procedures were approved by the ethical committee of the School of Medicine and Health of the Technical University of Munich, Germany..

所有程序均按照机构研究委员会的道德标准以及《赫尔辛基宣言》及其后来的修正案或类似的道德标准进行。在收集数据之前，已获得所有参与者的书面知情同意。研究方案和程序已获得德国慕尼黑工业大学医学与健康学院伦理委员会的批准。。

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Reprints and permissionsAbout this articleCite this articleJunker, D., Wu, M., Reik, A. et al. Impact of baseline adipose tissue characteristics on change in adipose tissue volume during a low calorie diet in people with obesity—results from the LION study.

转载和许可本文引用本文Junker，D.，Wu，M.，Reik，A。等人。LION研究结果显示，基线脂肪组织特征对肥胖人群低热量饮食期间脂肪组织体积变化的影响。

Int J Obes (2024). https://doi.org/10.1038/s41366-024-01568-6Download citationReceived: 12 January 2024Revised: 04 June 2024Accepted: 12 June 2024Published: 26 June 2024DOI: https://doi.org/10.1038/s41366-024-01568-6Share this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy to clipboard.

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