No evidence of association between functional polymorphisms located withinIL6RandIL6STgenes and Henoch-Schönlein purpura

Correlation between interleukin gene polymorphisms and current prevalence and mortality rates due to novel coronavirus disease 2019 (COVID-2019) in 23 countries

Background

The novel coronavirus disease 2019 (COVID‐19) infection may rely on a potential genetic background for the variations in the inflammatory response. We aimed to investigate the possible correlation between polymorphisms in the IL‐6 gene at rs1800796/rs1800795, in IL‐6R at rs2228145, in IL‐10 at rs1800896 and rs1800871, in IL‐17 at rs2275913 and rs763780 loci, and COVID‐19 prevalence and mortality rates among populations of 23 countries.

Methods

We searched the literature for polymorphisms in China, Japan, India, Spain, Mexico, Sweden, Turkey, Brazil, Russia, Poland, Italy, South Africa, Netherlands, Greece, Germany, UK, Iran, Finland, Czechia, Tunisia, Norway, Egypt, Croatia. We recorded the prevalence and mortality rates (per million) caused by the Coronavirus infection recorded on 7th September 2020 and 6th December 2020.

Results

There was a significant positive correlation between the frequency of AG genotype of rs1800896 and prevalence recorded on 6th December 2020 (r: 0.53, r²: 0.28, p < .05). There was a significant negative correlation between the mortality rates recorded on 7th September, and the AG genotype of rs2275913 (r: −0.51, r²: 0.26, p < .05). There was a significant positive correlation between the prevalence recorded on 6th December, and TT genotype at rs763780 (r: 0.65, r²:0.42, p < .05) while a negative correlation between prevalence and TC genotype at rs763780 (r: −0.66, r²: 0.43, p < .05). Also, a significant negative correlation was found between mortality rates recorded on 6th December 2020 and CC genotype at rs763780 (r: −0.56, r²: 0.31, p < .05).

Conclusion

The variations in prevalence of COVID‐19 and its mortality rates among countries may be explained by the polymorphisms at rs1800896 in IL‐10, rs2275913 in IL‐17A, and rs763780 loci in the IL‐17F gene.

The variations in prevalence of COVID‐19 and its mortality rates among 23 countries may be explained by the polymorphisms at rs1800896 in IL‐10, rs2275913 in IL‐17A, and rs763780 loci in the IL‐17F gene.

AG genotype frequency of rs1800896 was positively correlated with prevalence recorded on 6th December 2020.

The mortality rates recorded on 7th September was negatively correlated with AG genotype frequency of rs2275913.

The prevalence recorded on 6th December was positively correlated with frequency of TT and negatively with TC genotype at rs763780.

The mortality rates recorded on 6th December 2020 was negatively correlated with CC genotype frequency at rs763780.

Clinical significance of the serum biomarker index detection in children with Henoch-Schonlein purpura

OBJECTIVE

To explore a panel of serum biomarkers for laboratory diagnosis of pediatric Henoch-Schönlein purpura (HSP).

METHODS

The blood white blood cells (WBC) and serum levels of serum amyloid A (SAA), interleukin 6 (IL-6), immunoglobulin A (IgA), immunoglobulin G (IgG), immunoglobulin M (IgM), immunoglobulin E (IgE), C-reactive protein (CRP), complement component 3 (C3), complement component 4 (C4), and ASO (anti-streptolysin O) were detected in 127 patients with Henoch-Schonlein purpura (HSP), 110 cases of septicemia patients, and 121 healthy volunteers. The diagnostic ability of biomarkers selected from HSP and septicemia patients was analyzed by ROC curve. By designing the calculation model, the biomarker index was calculated for laboratory diagnosis of HSP and differential diagnosis between HSP and septicemia.

RESULTS

The levels of serum WBC, CRP, IL-6 and SAA in the septicemia patients were significantly higher than those in the control group (p<0.05). Compared with the healthy individuals, serum levels of WBC, CRP, IL-6, SAA, IgA and IgM were significantly increased in patients with HSP (p<0.05). The area under the curve (AUC) of SAA, IgA, IgM, WBC, IL-6, and CRP in the patients with HSP was 0.964, 0.855, 0.849, 0.787, 0.765, and 0.622, respectively. The values of SAA, IgA, IgM, WBC, IL-6, and CRP in septicemia patients were 0.700, 0.428, 0.689, 0.682, 0.891, and 0.853, respectively. Biomarker index=SAA+IgA/4000+IgM/4000×0.4CRPmean valueCRPi_. The biomarker index in HSP patients was significantly higher than that of the healthy controls. However, the biomarker index in septicemia patients was significantly lower than the control.

CONCLUSION

The biomarker index of HSP patients is higher than that of the control group. While in the infectious disease represented by septicemia, it is decreased. The detection of biomarker index could exclude the interference of infection as the auxiliary examination to HSP patients.