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Title:

Metabolomic signature of short-term low energy availability

Document type:
Konferenzbeitrag
Author(s):
Nusser, Valentin; Murphy, Caise; Wasserfurth, Paulina; Koehler, Karsten
Pages contribution:
98
Abstract:
INTRODUCTION: The impact of low energy availability (LEA) on metabolic processes has been widely documented in theliterature, with notable alterations observed in various metabolic, endocrine and physiological pathways, e.g., sex hor-mones as well as indicators of bone and iron metabolism. However, a comprehensive understanding of the metabolicperturbations associated with LEA remains elusive. Metabolomics, capable of analyzing a vast array of metabolites atonce, provides a unique opportunity to uncover the potentially complex metabolic signature of LEA, which holds promisefor improved detection and characterization of LEA status. METHODS: In this study, we employed nuclear magnetic resonance-based metabolomics to quantify 250 metabolites andmetabolite ratios in post-intervention blood samples obtained following short-term exposure to LEA (15 kcal/kg fat-freemass (FFM)/day) and normal EA as control (CON; 40 kcal/kg FFM/day). Blood samples utilized in our analysis weresourced from two larger crossover design studies (n=13, 85% males, aged 23.2±3.5 years), one of which involved dailyaerobic exercise across both conditions, expending 15 kcal/kg FFM/day. We used generalized estimating equations toevaluate the effects of LEA on metabolite concentrations, while employing multiple logistic regression to predict LEA statusbased on metabolic profiles. RESULTS: We observed significant condition effects in 120 out of 250 metabolites, independent of exercise. Notably, triglyc-erides (LEA vs. CON: 0.63±0.20 vs. 0.99±0.44 mmol/L, adjusted p<0.05), fatty acids (9.22±1.38 vs. 10.65±2.51 mmol/L,adjusted p<0.05), ketone bodies (0.30±0.25 vs. 0.03±0.02 mmol/L, adjusted p<.001) and very-low density lipoprotein(VLDL) sub-classes (adjusted p<0.05) exhibited significant differences. Furthermore, the stepwise inclusion of these varia-bles into a logistic regression model demonstrated their ability in predicting LEA status (LEA ~ Acetoacetate + Total triglyc-erides + Ratio of saturated fatty acids to total fatty acids, AIC=18.3, p<.001). CONCLUSION: Our analysis revealed significant group differences across a broad spectrum of metabolites, indicative of atransition towards increased fat utilization, ketosis, VLDL lipolysis and lipid transfer to high-density lipoprotein particles.These findings underscore the potential of metabolomics for identifying the metabolic signature of LEA, which may in turnbe used to identify individuals currently exposed to LEA
Dewey Decimal Classification:
570 Biowissenschaften, Biologie; 610 Medizin und Gesundheit; 790 Sport, Spiele, Unterhaltung
Book / Congress title:
29th Annual Congress of the European College of Sports Science
Volume:
Book of Abstracts
Organization:
European College of Sports Science
Year:
2024
E-ISBN:
978-3-9818414-7-3
Reviewed:
ja
Language:
en
Semester:
SS 24
TUM Institution:
Professur für Bewegung, Ernährung und Gesundheit
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