Population-level imaging, genomic and phenotypic analyses to determine how bone marrow adiposity impacts human health

人群水平成像、基因组和表型分析以确定骨髓肥胖如何影响人类健康

• 批准号: MR/S010505/1
• 负责人: William Cawthorn
• 金额: $ 71.77万
• 依托单位: University of Edinburgh
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FS010505%2F1
• 关键词: Population; level; imaging; genomic; phenotypic

Stop and think about your bones: what images come to mind? Perhaps a skull with grinning jaws, or the strong white limbs stretching out towards your fingers and toes. You might even think of the bone marrow within them, producing the blood that courses through your veins. But this is not the whole picture, for your skeleton hides a secret: it is full of fat, and no one knows why.This unsolved mystery is surprising. Scientists first noticed that our bone marrow contains fat-storing cells, called adipocytes, over a century ago. Having fat in our bones might strike you as unusual, but it is not: in humans and other mammals, this bone marrow adipose tissue (BMAT) develops steadily after birth and accumulates rapidly during puberty. Indeed, by the time we reach adulthood BMAT can comprise up to 70% of bone marrow volume, representing almost 10% of our total fat stores. Therefore, it seems likely that BMAT plays some role in the normal functioning of our bodies.Recent studies suggest that BMAT may also influence numerous diseases. One way of measuring BMAT is by a technique called magnetic resonance imaging (MRI). MRI scans have shown that BMAT further increases with ageing and in many diseases. For example, BMAT often increases in osteoporosis, suggesting that it might contribute to the bone fragility that defines this disease. Increased BMAT also occurs in obesity and type 2 diabetes, metabolic diseases that are placing a huge burden on our society. Therefore, excessive BMAT may lead to poor metabolic health. Finally, BMAT might enhance the growth of tumours within the bone, such as those that have spread from breast or prostate cancers, as well as leukaemia and other cancers that begin in the bone marrow.Based on these findings, BMAT is now attracting considerable interest as a potential player in the development of numerous diseases. Unfortunately, study of BMAT has been relatively limited, and analysis of BMAT using MRI has never been done across large populations. Consequently, the roles of BMAT in normal physiology and disease remain poorly understood. So, what is the function of BMAT, and how might it impact human health?Our team of scientists from the Universities of Edinburgh, Westminster and Dundee is now working to answer these key questions. To do so, we will use information being collected by the UK Biobank, a major study that is following the health and wellbeing of 500,000 volunteers from across the UK. The UK Biobank is doing MRI scans of 100,000 participants, which is estimated to be completed before the end of our 3-year research project. Using this MRI data, we will measure BMAT in each participant. This will be done by using artificial intelligence techniques to create computer software for automatic analysis of the MRI scans. These approaches will establish how the amount of BMAT varies across this very large population. The power of the UK Biobank is that it has also collected DNA samples and health data on each participant. Therefore, once we have measured participants' BMAT we will be able to discover how this relates to other aspects of human health and disease. This includes physiological factors, such as age and sex; genetic factors, such as mutations in particular genes; and disease outcomes, such as heart disease, obesity, diabetes, osteoporosis, and many other conditions of ill health. Together, this unprecedented, large-scale research project will help to unravel the mystery of BMAT whilst also establishing new methods for automated MRI analysis. The latter will be of huge help to the NHS, which currently faces a major backlog of unanalysed MRI scans. More broadly, understanding the impact of BMAT on human health has great potential to improve diagnoses and treatment of numerous diseases, including osteoporosis, diabetes, cardiovascular disease and several types of cancer. This will be vital if we are to reduce the public health impact of these worldwide health problems.

停下来想想你的骨头：脑海中浮现出什么画面？也许是一个咧着嘴的头骨，或者是强壮的白色四肢伸向你的手指和脚趾。你甚至可以想到它们里面的骨髓，产生通过你的静脉的血液。但这并不是全貌，因为你的骨架隐藏着一个秘密：它充满了脂肪，没有人知道为什么。这个未解之谜令人惊讶。早在世纪前，科学家们就首次发现我们的骨髓中含有储存脂肪的细胞，称为脂肪细胞。在我们的骨骼中含有脂肪可能会让你觉得不寻常，但事实并非如此：在人类和其他哺乳动物中，这种骨髓脂肪组织（BMAT）在出生后稳定发育，并在青春期迅速积累。事实上，当我们成年时，BMAT可以占骨髓体积的70%，占我们总脂肪储存的近10%。因此，BMAT似乎在我们身体的正常功能中起着一定的作用。最近的研究表明，BMAT也可能影响许多疾病。测量BMAT的一种方法是通过一种称为磁共振成像（MRI）的技术。MRI扫描显示，BMAT随着年龄的增长和许多疾病而进一步增加。例如，BMAT通常在骨质疏松症中增加，这表明它可能有助于定义这种疾病的骨脆性。增加的BMAT也发生在肥胖和2型糖尿病中，这些代谢疾病给我们的社会带来了巨大的负担。因此，过量的BMAT可能导致代谢健康不良。最后，BMAT可能会促进骨内肿瘤的生长，例如那些从乳腺癌或前列腺癌扩散而来的肿瘤，以及白血病和其他开始于骨髓的癌症。基于这些发现，BMAT现在作为许多疾病发展的潜在参与者引起了相当大的兴趣。不幸的是，对BMAT的研究相对有限，并且从未在大规模人群中使用MRI对BMAT进行过分析。因此，BMAT在正常生理和疾病中的作用仍然知之甚少。那么，BMAT的功能是什么，以及它如何影响人类健康？我们来自爱丁堡大学、威斯敏斯特大学和邓迪大学的科学家团队现在正在努力回答这些关键问题。为此，我们将使用英国生物银行收集的信息，这是一项主要研究，跟踪来自英国各地的50万志愿者的健康和福祉。英国生物银行正在对10万名参与者进行MRI扫描，预计将在我们为期3年的研究项目结束前完成。使用这些MRI数据，我们将测量每个参与者的BMAT。这将通过使用人工智能技术来创建用于自动分析MRI扫描的计算机软件来完成。这些方法将确定BMAT的数量如何在这个非常大的人群中变化。英国生物库的强大之处在于它还收集了每个参与者的DNA样本和健康数据。因此，一旦我们测量了参与者的BMAT，我们将能够发现这与人类健康和疾病的其他方面的关系。这包括生理因素，如年龄和性别;遗传因素，如特定基因的突变;和疾病结果，如心脏病，肥胖症，糖尿病，骨质疏松症和许多其他健康状况不佳。总之，这个前所未有的大规模研究项目将有助于揭开BMAT的神秘面纱，同时建立自动MRI分析的新方法。后者将对NHS有巨大的帮助，NHS目前面临着大量未分析的MRI扫描积压。更广泛地说，了解BMAT对人类健康的影响具有很大的潜力，可以改善许多疾病的诊断和治疗，包括骨质疏松症，糖尿病，心血管疾病和几种类型的癌症。如果我们要减少这些全球性健康问题对公共健康的影响，这将是至关重要的。

项目成果

A novel deep learning method for large-scale analysis of bone marrow adiposity using UK Biobank Dixon MRI data

使用英国生物银行 Dixon MRI 数据大规模分析骨髓肥胖的新型深度学习方法

• DOI: 10.1101/2022.12.06.22283151
• 发表时间: 2022
• 作者: Morris D

Guidelines for Biobanking of Bone Marrow Adipose Tissue and Related Cell Types: Report of the Biobanking Working Group of the International Bone Marrow Adiposity Society.

• DOI: 10.3389/fendo.2021.744527
• 发表时间: 2021
• 期刊: Frontiers in endocrinology
• 影响因子: 5.2
• 作者: Lucas S;Tencerova M;von der Weid B;Andersen TL;Attané C;Behler-Janbeck F;Cawthorn WP;Ivaska KK;Naveiras O;Podgorski I;Reagan MR;van der Eerden BCJ
• 通讯作者: van der Eerden BCJ

A novel deep learning method for large-scale analysis of bone marrow adiposity using UK Biobank Dixon MRI data.

一种新型的深度学习方法，用于使用UK Biobank Dixon MRI数据对骨髓肥胖进行大规模分析。

• DOI: 10.1016/j.csbj.2023.12.029
• 发表时间: 2024-12
• 期刊: Computational and structural biotechnology journal
• 影响因子: 6