Abstract [en]

In this thesis, I evaluated the impact of pre-centrifugation sample management on the plasma metabolome, providing verification for the protocol used in a study where I applied metabolomics to better understand the role of body composition in fracture occurrence using a large population-based cohort. 

 In paper 1, I applied untargeted liquid chromatography-mass spectrometry (LC-MS) metabolomics analysis to plasma samples (n = 471) from healthy donors to predict and evaluate the effect of pre-centrifugation temperature and delay time on metabolomics data using a combination of random forest and generalized linear models. I found that delayed treatment (up to 210 min) of blood samples can induce variation to the plasma metabolome at all three temperatures (4, 25 and 37 °C) and thus blood samples should be managed as expediently as possible, preferably at room temperature. Metabolite panels were constructed and validated to predict the pre-centrifugation management conditions of plasma samples.

In paper 2, I used a full cohort of men and women (n = 44,366), and a subcohort of women (n = 5022) to investigate the associations between anthropometrics or body composition and fracture risk. I found that lower body mass index (BMI), prior loss of BMI and higher central obesity were associated with increased risks of fracture. The joint analysis revealed that prior gain of BMI was protective against fracture only in individuals with normal weight. The associations between lean mass index (LMI) or fat mass index (FMI) and fracture risk were heavily dependent on bone mineral density (BMD) in the study population. 

Based on findings of paper 2, a metabolome-wide association of LMI, FMI and BMD was conducted in the subcohort. Metabolites associated with at least one body composition outcome were then associated with hip fracture risk, resulting in the discovery of twenty-three metabolites of interest. Network analysis of these hip fracture-related metabolites highlighted the important role of lysoglycerophospholipids in the skeletomuscular-adipose crosstalk. Mendelian randomization analyses suggested several causal associations between these hip fracture-related metabolites and body composition measures or bone-related clinical biomarkers.

In summary, metabolites can reflect perturbations induced by pre-centrifugation management of samples and thus provide valuable information of sample quality. To optimally prevent fractures at older age, low BMI, prior BMI loss and central obesity should be avoided. Metabolites reflecting differences in, and crosstalk of skeletomuscular-adipose tissues may contribute to a further understanding of fracture occurrence and discoveries of actionable targets for prevention.

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