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 Cawthorn, Prof Ewan Pearson & Prof Jimmy Bell

Centre/Institute: Centre for Cardiovascular Science 

Background

Bone marrow adipose tissue (MAT) accounts for up to 70% of total bone marrow volume and approximately 10% of total fat mass in lean, healthy humans [1]. MAT 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, MAT also increases during caloric restriction in animals and in humans with anorexia nervosa [1-3]. Thus, MAT 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. This suggests that MAT plays a role in normal physiological function and might also impact skeletal, metabolic and ageing-associated diseases. However, study of MAT has been extremely limited, and therefore the formation and function of MAT remains poorly understood.

Magnetic resonance imaging (MRI) is emerging as a key tool for non-invasively assessing the properties of MAT. 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 small-scale human cohort studies, revealing some insights into MAT’s association with human skeletal and metabolic health [4]. However, MRI-based MAT 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 MAT development, as well as highlighting how altered MAT content might impact human health and disease.

Aims

  1. Determine how MAT 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 1,000 scans will generate a foundational dataset. Secondly, this foundational dataset will be used for initial association analyses (Aim 2) and to generate machine-learning algorithms to automate MAT analysis of the remaining Biobank MRI scans. These approaches will establish how the key properties of MAT vary across a large population.
  2. Identify the physiological, pathological and genetic determinants of altered MAT. The MAT 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). MAT 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 MAT 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 MAT on health and disease. Mendelian Randomisation studies will be done to determine if SNPs associated with altered MAT (as identified in Aim 2) are also causally associated with physiological and pathological phenomena. This will reveal if alterations in MAT 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. This project provides a unique opportunity to comprehensively establish how MAT impacts human health and disease.

References

  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 Wednesday 10th January 2018.
  • Please note all applications for the Precision Medicine DTP should be submitted to University of Edinburgh, even those applying for a project at the University of Glasgow.
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