Rasmus Stenlid, Med. Stud.1,3,4, Peter Bergsten, M.D., Ph.D.3, Jing Cen, M.D., Ph.D.3, David
Olsson, M.D.1,2, Anna Nordenström M.D., Ph.D.1,2 Maria Halldin, M.D. Ph.D.1,2
1. Department of women’s and children’s health, Karolinska Institutet, Solna, Sweden
2. Karolinska University Hospital Solna, Sweden
3. Department of medical cell biology, Uppsala University, Uppsala, Sweden
4. Corresponding author: Rasmus.Stenlid@stud.ki.se #0046762152982
Defining metabolic phenotypes in β-oxidation defects (FAO) is challenging. There is a need of improved tools to evaluate the severity of the disorders and to individualize treatment. The Seahorse Extracellular Flux Analyzer (SEFA) makes it possible to analyze metabolism at cellular level. It has been used in the study of inborn errors of metabolism, using mainly fibroblasts, which are complicated and requires time to obtain. Leukocytes are easily accessible and less invasive. We have developed the SEFA method further, using leukocytes, for the study of patients with FAO.
Leukocytes from controls, patients with MCAD and VLCAD were isolated and analyzed within 12h after blood sampling. In the SEFA the leukocytes were exposed to either different concentrations of glucose, or fatty acids of C8 or C16 chain length. Oxygen consumption rate (OCR) was determined in basal state, the β-oxidation was measured after injection of Etomoxir blocking CPT-1. Oligomycin was added to calculate ATP-production, FCCP to determine maximal mitochondrial OCR, and a Rotenone and Antimycin A mixture to determine non-mitochondrial OCR.
MCAD and VLCAD patients had lower basal OCR compared to controls. MCAD patients increased basal OCR when exposed to C16, VLCAD patients did not. ATP-coupled OCR was higher for controls than the patients regardless of disease or exposure. Non-mitochondrial OCR was higher for MCAD patients than VLCAD patients when exposed to C16
Through neonatal screening more patients with FAO defects are identified. In some disorders the relation between genotype and phenotype is not obvious, with big individual variations in severity. This makes it difficult to determine the therapeutic interventions for the individual patient, highlighting the necessity to describe the metabolic phenotype and evaluate the degree of severity for each patient. We here present a method to evaluate metabolic parameters from a routine blood sample using the SEFA.