Erythropoietin and vascular endothelial growth factor as risk markers for severe hypoglycaemia in type 1 diabetes

Abstract

Objective: Circulating erythropoietin (EPO) and vascular endothelial growth factor (VEGF) increase during hypoglycaemia and may represent protective hormonal counter-regulatory responses. We tested the hypothesis that low levels of EPO and VEGF are associated with a higher frequency of severe hypoglycaemia in a cohort of patients with type 1 diabetes. Design: Prospective observational follow-up study. Methods: Totally 219 patients with type 1 diabetes (41% females, age 46G13 years (meanGS.D.), duration of diabetes 21G12 years, and HbAlc 8.5G1.1%) were followed in a 1-year observational study. Plasma EPO and serum VEGF levels were measured at baseline with ELISA. Events of severe hypoglycaemia defined by third party assistance were recorded and validated in telephone interviews within 24 h. Results: Totally 235 episodes of severe hypoglycaemia (1.1 episodes per patient-year) were reported by 82 patients (37%). At baseline, plasma EPO was 8.6 (3.1-34.3) U/l (median (range)), and serum VEGF was 52.2 (6.6-337) pg/ml. The levels of EPO and VEGF were not associated with frequency of severe and mild hypoglycaemia. The levels of EPO were not associated with age, sex, duration of diabetes, body mass index, HbAlc, C-peptide level or hypoglycaemia awareness status. The levels of VEGF were positively associated with age and female sex. Conclusions: Although several studies suggest that VEGF and EPO may affect brain function during hypoglycaemia, this study does not support random VEGF or EPO levels to determine future risk of severe hypoglycaemia in people with type 1 diabetes.

The polar-generalized normal distribution: properties, Bayesian estimation and applications

“…However, the distribution of data were collected from a wide range of applications reveals asymmetry. Examples arise, for instance, in wind speed data (Zhu and Genton 2012), temperature data (North et al 2011), soil and air pollution data (Jafari Khaledi and Rivaz 2009;Zareifard and Jafari Khaledi 2013), precipitation data (Xu and Genton 2017) and diabetes data (Kristensen et al 2010). The skew-normal (SN) distribution, introduced by Azzalini (1985), has been used successfully to model data sets that have asymmetric behavior.…”

The polar-generalized normal distribution

“…However, the distribution of data were collected from a wide range of applications reveals asymmetry. Examples arise, for instance, in wind speed data (Zhu and Genton, 2012), temperature data (North et al, 2011), soil and air pollution data (Jafari Khaledi and Rivaz, 2009; Zareifard and Jafari , precipitation data (Xu and Genton, 2017) and diabetes data (Kristensen et al, 2010). The skew-normal (SN) distribution, introduced by Azzalini (1985), has been used successfully to model data sets that have asymmetric behavior.…”

The Recombinant Human Erythropoietin Administered in Neonatal Rats After Excitotoxic Damage Induces Molecular Changes in the Hippocampus

“…The evidences has shown that not only stressors with a hypoxic component but also other stressors in the brain, such as neurotoxicity and hypoglycemia, are able to induce changes in the expression level of EPO (Morishita et al, 1997; Brines and Cerami, 2008; Kristensen et al, 2010; Yamada et al, 2011; Kastner et al, 2012; Nguyen et al, 2014; Rainville et al, 2016; Nekoui and Blaise, 2017). Although EPO gene expression in the brain is also induced by activation of hypoxia-inducible factors, EPO is not the primary inducer of EPOR (Chin et al, 2000; Grasso et al, 2004); therefore, the regulatory mechanisms of both the production and the processing of EPOR transcripts are uncertain, even under hypoxic conditions.…”