Lactate production is a prioritized feature of adipocyte metabolism.

Adipose tissue is essential for whole-body glucose homeostasis, with a primary role in lipid storage. It has been previously observed that lactate production is also an important metabolic feature of adipocytes, but its relationship to adipose and whole-body glucose disposal remains unclear. Therefore, using a combination of metabolic labeling techniques, here we closely examined lactate production of cultured and primary mammalian adipocytes. Insulin treatment increased glucose uptake and conversion to lactate, with the latter responding more to insulin than did other metabolic fates of glucose. However, lactate production did not just serve as a mechanism to dispose of excess glucose, because we also observed that lactate production in adipocytes did not solely depend on glucose availability and even occurred independently of glucose metabolism. This suggests that lactate production is prioritized in adipocytes. Furthermore, knocking down lactate dehydrogenase specifically in the fat body of Drosophila flies lowered circulating lactate and improved whole-body glucose disposal. These results emphasize that lactate production is an additional metabolic role of adipose tissue beyond lipid storage and release.

Urinary Metabolome Analyses of Patients with Acute Kidney Injury Using Capillary Electrophoresis-Mass Spectrometry.

Acute kidney injury (AKI) is defined as a rapid decline in kidney function. The associated syndromes may lead to increased morbidity and mortality, but its early detection remains difficult. Using capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS), we analyzed the urinary metabolomic profile of patients admitted to the intensive care unit (ICU) after invasive surgery. Urine samples were collected at six time points: before surgery, at ICU admission and 6, 12, 24 and 48 h after. First, urine samples from 61 initial patients (non-AKI: 23, mild AKI: 24, severe AKI: 14) were measured, followed by the measurement of urine samples from 60 additional patients (non-AKI: 40, mild AKI: 20). Glycine and ethanolamine were decreased in patients with AKI compared with non-AKI patients at 6-24 h in the two groups. The linear statistical model constructed at each time point by machine learning achieved the best performance at 24 h (median AUC, area under the curve: 89%, cross-validated) for the 1st group. When cross-validated between the two groups, the AUC showed the best value of 70% at 12 h. These results identified metabolites and time points that show patterns specific to subjects who develop AKI, paving the way for the development of better biomarkers.