The Relation of Copper and Zinc with Incidence of Neonatal Sepsis and Possible Prediction Biomarker Role

Determination of trace elements and electrolyte levels in kidney tissue of simvastatin-treated septic rats

Trace elements are cofactors in various enzymes in the antioxidant defense and cell homeostasis required in the tissue during inflammation. In acute kidney injury induced by lipopolysaccharide (LPS), renal cells are affected by cytotoxicity. Renal evacuation and gastrointestinal absorption rates are important in regulating plasma levels of trace elements. Simvastatin is a widely used anti-lipidemic drug with known anti-inflammatory effects. This study aimed to examine the effect of simvastatin on trace elements and electrolyte levels in kidney tissue in rats with LPS-induced sepsis. Adult male Wistar albino rats were divided into four groups: control, LPS (20 mg/kg, i.p., single dose), simvastatin (20 mg/kg, o.p., 5 days), and LPS + Simvastatin (LPS + Sim). Sodium, potassium, calcium, magnesium, selenium, zinc, copper, and histological structural changes were examined in kidney tissue samples 4 h after LPS execution. The inductively coupled plasma optical emission spectroscopy technique (ICP-OES) was used to determine the tissue trace element levels. In rats with sepsis-induced LPS, selenium, calcium, sodium, and magnesium levels significantly decreased while copper, potassium, and zinc levels significantly increased compared to other experimental groups. In sepsis treated with the simvastatin (LPS + Simvastatin) group, trace elements and electrolyte levels are like the control groups, apart from selenium levels. Selenium levels were significantly decreased in the LPS + Simvastatin group compared to the controls. As a result of examining the kidney tissues under a light microscope, simvastatin improved tissue damage caused by LPS-induced acute kidney injury. LPS-induced renal injury and simvastatin caused significant changes in the oxidant/antioxidant system. In septic rats, simvastatin was shown to balance some trace element levels, and it may improve damage in the kidney tissue.

Association between DNA Damage and Serum Levels of Copper, Zinc, and Selenium in Full-Term Neonates with Late-Onset Sepsis

Objective The alteration in certain trace elements is usually associated with impaired immune function and higher oxidative stress. Therefore, these elements are suggested to play an important role in the pathogenesis of neonatal sepsis. We aimed to evaluate copper (Cu), zinc (Zn), and selenium (Se) serum levels in full-term neonates with late-onset sepsis (LOS) and correlate these levels with DNA damage and other risk factors of sepsis.

Methods The study included a group of 100 neonates diagnosed with sepsis serving as the case group and another one of 60 neonates serving as the control group. DNA damage was assessed using the comet assay method and trace elements were measured using inductively coupled plasma mass spectrometry.

Results Compared with controls, the percentage of DNA damage was significantly elevated in patients with sepsis, while serum levels of Cu, Zn, and Se were markedly decreased (p = 0.001). A strong negative correlation was revealed between Se and DNA damage (r = −0.6, p = 0.001). However, no correlations were found between Cu or Zn and DNA damage. Univariate logistic regression analysis revealed that DNA damage as well as Cu, Zn, and Se serum levels can be considered as relevant risk factors for neonatal sepsis (p = 0.008, 0.004, 0.004, and 0.003, respectively). Receiver-operating characteristic curve analysis showed that the strongest indicator for neonatal sepsis was Se (area under the curve [AUC] = 0.94, confidence interval [CI] = 0.9–0.98, p = 0.001), followed by Cu (AUC = 0.9, CI = 0.85–0.96, p = 0.001), and then Zn (AUC = 0.87, CI = 0.8–0.93, p = 0.001).

Conclusion The percentage of DNA damage may help in the assessment of neonatal sepsis severity. Altered levels of Cu, Zn, and Se may play significant role in the pathogenesis of neonatal sepsis. Se serum level is strongly correlated with percentage of DNA damage. Therefore, Se can predict the severity of LOS.