Precision Medicine Doctoral Training Programme

Population-level imaging and genetic analyses to determine how bone marrow adiposity impacts human health

Project Details - Population-level imaging and genetic analyses to determine how bone marrow adiposity impacts human health

Supervisor(s): Dr William CawthornProf Ewan Pearson & Prof Jimmy Bell

Centre/Institute: Centre for Cardiovascular Science 


Bone marrow adipose tissue (BMAT) accounts for up to 70% of total bone marrow volume and approximately 10% of total fat mass in lean, healthy humans [1]. BMAT further increases with ageing and in diverse clinical conditions, including osteoporosis, obesity, type 1 diabetes, oestrogen deficiency, radiotherapy and glucocorticoid treatment. In striking contrast to other adipose depots, BMAT also increases during caloric restriction in animals and in humans with anorexia nervosa [1-3]. Thus, BMAT is a major component of normal human anatomy; it is distinct to other types of adipose tissue; and it is altered in numerous clinical contexts.

These observations suggest that BMAT plays a role in normal physiological function and might also impact skeletal, metabolic and ageing-associated diseases. However, study of BMAT has been extremely limited, and therefore the formation and function of BMAT remains poorly understood.

Magnetic resonance imaging (MRI) is emerging as a key tool for non-invasively assessing the properties of BMAT. For example, MRI can measure both the extent of bone marrow adiposity (BMA) and the degree of saturated and unsaturated lipids within the bone marrow. This approach has been applied in a handful of smaller-scale human cohort studies, revealing some insights into BMAT’s association with human skeletal and metabolic health [4]. However, MRI-based BMAT analysis has never been done on a larger scale. Such population-level studies would have enormous potential to reveal fundamental knowledge of the formation and function of MAT, including the association with physiological, pathological and genetic variables. Such knowledge would provide new understanding about the factors that regulate BMAT development, as well as highlighting how altered BMAT content might impact human health and disease.


  1. Determine how BMAT properties vary on a population level. The UK Biobank has begun a major study to MRI scan 100,000 participants. Data from this ongoing study will be analysed to determine the percentage of BMA and the degree of saturated and unsaturated lipids in bone marrow of each participant [4]. This will be done in two phases: firstly, manual analysis of up to 500 scans will generate a foundational dataset. Secondly, this foundational dataset will be used for initial association analyses (Aim 2) and to develop machine-learning algorithms to automate BMAT analysis of the remaining Biobank MRI scans. These approaches will establish how the key properties of BMAT vary across a large population.
  2. Identify the physiological, pathological and genetic determinants of altered MAT. The BMAT properties established in Aim 1 will be analysed for associations with physiological (e.g. age, sex, ethnicity, hormonal status), pathological (e.g. obesity, diabetes, osteoporosis, clinical treatments) and genetic (e.g. SNPs) parameters. The latter will initially focus on SNPs known to impact bone mineral density or circulating adiponectin, two parameters implicated with altered MAT. These associations will first be assessed using the foundational scanning dataset of 1,000 individuals (Aim 1). BMAT analysis has never been done on even this initial smaller scale, so this approach will likely identify factors that directly influence, or are influenced by, MAT. Subsequent, larger-scale automated BMAT analysis, from the remaining Biobank scans, will then allow testing of associations across 100,000 subjects, providing unprecedented power to dissect the causes and consequences of altered MAT.
  3. Determine the impact of BMAT on health and disease. Mendelian Randomisation studies will be done to determine if SNPs associated with altered BMAT (as identified in Aim 2) are also causally associated with physiological and pathological phenomena. This will reveal if alterations in BMAT can directly influence physiological traits and/or the etiology of diverse diseases.

Training Outcomes

By pursuing these aims, the student will gain skills in image analysis (MRI), computational biology (machine learning algorithms), genomics (e.g. interrogation of UK Biobank genomic data, Mendelian Randomisation), bioinformatics and data management (e.g. programming for management and analysis of large-scale datasets), and a key understanding of human physiology and pathology. Thus, by employing an arsenal of cutting-edge, interdisciplinary approaches, this project provides a unique opportunity to comprehensively establish how BMAT impacts human health and disease.


  1. Scheller, E.L., W.P. Cawthorn, A.A. Burr, M.C. Horowitz, and O.A. MacDougald, Marrow Adipose Tissue: Trimming the Fat. Trends Endocrinol Metab, 2016. 27(6): p. 392-403.
  2. Cawthorn, W.P., E.L. Scheller, S.D. Parlee, H.A. Pham, B.S. Learman, C.M. Redshaw, R.J. Sulston, A.A. Burr, A.K. Das, B.R. Simon, H. Mori, A.J. Bree, B. Schell, V. Krishnan, and O.A. MacDougald, Expansion of Bone Marrow Adipose Tissue During Caloric Restriction Is Associated With Increased Circulating Glucocorticoids and Not With Hypoleptinemia. Endocrinology, 2016. 157(2): p. 508-21.
  3. Cawthorn, W.P., et al., Bone Marrow Adipose Tissue Is an Endocrine Organ that Contributes to Increased Circulating Adiponectin during Caloric Restriction. Cell Metabolism, 2014. 20(2): p. 368-75.
  4. Cordes, C., T. Baum, M. Dieckmeyer, S. Ruschke, M.N. Diefenbach, H. Hauner, J.S. Kirschke, and D.C. Karampinos, MR-Based Assessment of Bone Marrow Fat in Osteoporosis, Diabetes, and Obesity. Front Endocrinol (Lausanne), 2016. 7: p. 74.

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  • The deadline for 18/19 applications is 5pm on Monday 16th April 2018.
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