AI Article Synopsis

  • Current methods for assessing glucocorticoid status mainly rely on clinical evaluations and serum cortisol levels, which might not fully reflect an individual’s actual glucocorticoid health, especially with less extreme variations.
  • The review explores alternative assessment methods, including metabolomic profiles and novel biomarkers like micro RNA and gene expression, which could offer better insights into individual glucocorticoid status beyond just cortisol measurements.

Article Abstract

Glucocorticoid (GC) hormones are secreted in a circadian and ultradian rhythm and play a critical role in maintaining physiological homeostasis, with both excess and insufficient GC associated with adverse effects on health. Current assessment of GC status is primarily clinical, often in conjunction with serum cortisol values, which may be stimulated or suppressed depending on the GC disturbance being assessed. In the setting of extreme perturbations in cortisol levels ie, markedly low or high levels, symptoms and signs of GC dysfunction may be overt. However, when disturbances in cortisol GC status values are less extreme, such as when assessing optimization of a GC replacement regimen, signs and symptoms can be more subtle or nonspecific. Current tools for assessing GC status are best suited to identifying profound disturbances but may lack sensitivity for confirming optimal GC status. Moreover, single cortisol values do not necessarily reflect an individual's GC status, as they are subject to inter- and intraindividual variation and do not take into account the pulsatile nature of cortisol secretion, variation in binding proteins, or local tissue concentrations as dictated by 11beta-hydroxysteroid dehydrogenase activity, as well as GC receptor sensitivity. In the present review, we evaluate possible alternative methods for the assessment of GC status that do not solely rely on the measurement of circulating cortisol levels. We discuss the potential of changes in metabolomic profiles, micro RNA, gene expression, and epigenetic and other novel biomarkers such as growth differentiating factor 15 and osteocalcin, which could in the future aid in the objective classification of GC status.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11581704PMC
http://dx.doi.org/10.1210/endrev/bnae016DOI Listing

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