Hypopituitarsim is associated with triglyceride enrichment of very low-density lipoprotein

Untargeted LC/MS-Based Metabolic Phenotyping of Hypopituitarism in Young Males

Objective: Hypopituitarism (Hypo-Pit) is partial or complete insufficiency of anterior pituitary hormones. Besides hormone metabolism, the global metabolomics in Hypo-Pit are largely unknown. We aimed to explore potential biomarkers to aid in diagnosis and personalized treatment.

Methods: Using both univariate and multivariate statistical methods, we identified 72 differentially abundant features through liquid chromatography coupled to high-resolution mass spectrometry, obtained in 134 males with Hypo-Pit and 90 age matched healthy controls.

Results: Hypopituitarism exhibits an increased abundance of metabolites involved in amino acid degradation and glycerophospholipid synthesis, but decreased content of metabolites in steroid hormone synthesis and fatty acid beta-oxidation. Significantly changed metabolites included creatine, creatinine, L-alanine, phosphocholines, androstenedione, hydroprenenolone, and acylcarnitines. In Hypo-Pit patients, the increased ratio of creatine/creatinine suggested reduced creatine uptake and impaired creatine utilization, whereas the decreased level of beta-hydroxybutyrate, acetylcarnitine (C2) and a significantly decreased ratio of decanoylcarnitine (C10) to free carnitine suggested an impaired beta-oxidation. Furthermore, the creatine/creatinine and decanoylcarnitine/carnitine ratio were identified as diagnostic biomarkers for Hypo-Pit with AUCs of 0.976 and 0.988, respectively. Finally, we found that the creatinine and decanoylcarnitine/carnitine ratio could distinguish cases that were sensitive vs. resistant to human chorionic gonadotropin therapy.

Conclusion: We provided a global picture of altered metabolic pathways in Hypo-Pit, and the identified biomarkers in creatine metabolism and beta-oxidation might be useful for the preliminary screening and diagnosis of Hypo-Pit.

Mortality in patients with pituitary disease

Pituitary disease is associated with increased mortality predominantly due to vascular disease. Control of cortisol secretion and GH hypersecretion (and cardiovascular risk factor reduction) is key in the reduction of mortality in patients with Cushing's disease and acromegaly, retrospectively. For patients with acromegaly, the role of IGF-I is less clear-cut. Confounding pituitary hormone deficiencies such as gonadotropins and particularly ACTH deficiency (with higher doses of hydrocortisone replacement) may have a detrimental effect on outcome in patients with pituitary disease. Pituitary radiotherapy is a further factor that has been associated with increased mortality (particularly cerebrovascular). Although standardized mortality ratios in pituitary disease are falling due to improved treatment, mortality for many conditions are still elevated above that of the general population, and therefore further measures are needed. Craniopharyngioma patients have a particularly increased risk of mortality as a result of the tumor itself and treatment to control tumor growth; this is a key area for future research in order to optimize the outcome for these patients.

Studying apolipoprotein turnover with stable isotope tracers: correct analysis is by modeling enrichments

Lipoprotein kinetic parameters are determined from mass spectrometry data after administering mass isotopes of amino acids, which label proteins endogenously. The standard procedure is to model the isotopic content of the labeled precursor amino acid and of proteins of interest as tracer-to-tracee ratio (TTR). It is shown here that even though the administered tracer alters amino acid mass and turnover, apolipoprotein synthesis is unaltered and hence the apolipoprotein system is in a steady state, with the total (labeled plus unlabeled) masses and fluxes remaining constant. The correct model formulation for apolipoprotein kinetics is shown to be in terms of tracer enrichment, not of TTR. The needed mathematical equations are derived. A theoretical error analysis is carried out to calculate the magnitude of error in published results using TTR modeling. It is shown that TTR modeling leads to a consistent underestimation of the fractional synthetic rate. In constant-infusion studies, the bias error percent is shown to equal approximately the plateau enrichment, generally <10%. It is shown that, in bolus studies, the underestimation error can be larger. Thus, for mass isotope studies with endogenous tracers, apolipoproteins are in a steady state and the data should be fitted by modeling enrichments.