Background COVID-19 has a highly variable clinical presentation, ranging from asymptomatic to severe respiratory symptoms and death. Diabetes seems to be one of the main comorbidities contributing to a worse COVID-19 outcome. Objective In here we analyze the clinical characteristics and outcomes of diabetic COVID-19 patients Kuwait. Methods In this single-center, retrospective study of 417 consecutive COVID-19 patients, we analyze and compare disease severity, outcome, associated complications, and clinical laboratory findings between diabetic and non-diabetic COVID-19 patients. Results COVID-19 patients with diabetes had more ICU admission than non-diabetic COVID-19 patients (42.4% vs. 7.7%, p < 0.001). Diabetic COVID-19 patients also recorded higher mortality in comparison to non-diabetic COVID-19 patients (34.7% vs. 3.7%, p < 0.001). Diabetic COVID-19 patients had significantly higher prevalence of comorbidities, such as hypertension. Laboratory investigations also highlighted notably higher levels of C-reactive protein in diabetic COVID019 patients and lower estimated glomerular filtration rate. They also showed a higher incidence of complications. logistic regression analysis showed that every 1 mmol/L increase in fasting blood glucose in COVID-19 patients is associated with 1.52 (95% CI: 1.34–1.72, p < 0.001) times the odds of dying from COVID-19. Conclusion Diabetes is a major contributor to worsening outcomes in COVID-19 patients. Understanding the pathophysiology underlining these findings could provide insight into better management and improved outcome of such cases.

Objective To build a clinical risk score to aid risk stratification among hospitalised COVID‐19 patients. Methods The score was built using data of 417 consecutive COVID‐19 in patients from Kuwait. Risk factors for COVID‐19 mortality were identified by multivariate logistic regressions and assigned weighted points proportional to their beta coefficient values. A final score was obtained for each patient and tested against death to calculate an Receiver‐operating characteristic curve. Youden's index was used to determine the cut‐off value for death prediction risk. The score was internally validated using another COVID‐19 Kuwaiti‐patient cohort of 923 patients. External validation was carried out using 178 patients from the Italian CoViDiab cohort. Results Deceased COVID‐19 patients more likely showed glucose levels of 7.0–11.1 mmol/L (34.4%, p < 0.0001) or >11.1 mmol/L (44.3%, p < 0.0001), and comorbidities such as diabetes and hypertension compared to those who survived (39.3% vs. 20.4% [ p = 0.0027] and 45.9% vs. 26.6% [ p = 0.0036], respectively). The risk factors for in‐hospital mortality in the final model were gender, nationality, asthma, and glucose categories (<5.0, 5.5–6.9, 7.0–11.1, or 11.1 > mmol/L). A score of ≥5.5 points predicted death with 75% sensitivity and 86.3% specificity (area under the curve (AUC) 0.901). Internal validation resulted in an AUC of 0.826, and external validation showed an AUC of 0.687. Conclusion This clinical risk score was built with easy‐to‐collect data and had good probability of predicting in‐hospital death among COVID‐19 patients.

Aims/hypothesis Antibodies specific to oxidative post-translational modifications (oxPTM) of insulin (oxPTM-INS) are present in most individuals with type 1 diabetes, even before the clinical onset. However, the antigenic determinants of such response are still unknown. In this study, we investigated the antibody response to oxPTM-INS neoepitope peptides (oxPTM-INSPs) and evaluated their ability to stimulate humoral and T cell responses in type 1 diabetes. We also assessed the concordance between antibody and T cell responses to the oxPTM-INS neoantigenic peptides. Methods oxPTM-INS was generated by exposing insulin to various reactive oxidants. The insulin fragments resulting from oxPTM were fractionated by size-exclusion chromatography further to ELISA and LC-MS/MS analysis to identify the oxidised peptide neoepitopes. Immunogenic peptide candidates were produced and then modified in house or designed to incorporate in silico-oxidised amino acids during synthesis. Autoantibodies to the oxPTM-INSPs were tested by ELISA using sera from 63 participants with new-onset type 1 diabetes and 30 control participants. An additional 18 fresh blood samples from participants with recently diagnosed type 1 diabetes, five with established disease, and from 11 control participants were used to evaluate, in parallel, CD4+ and CD8+ T cell activation by oxPTM-INSPs. Results We observed antibody and T cell responses to three out of six LC-MS/MS-identified insulin peptide candidates: A:12–21 (SLYQLENYCN, native insulin peptide 3 [Nt-INSP-3]), B:11–30 (LVEALYLVCGERGFFYTPKT, Nt-INSP-4) and B:21–30 (ERGFFYTPKT, Nt-INSP-6). For Nt-INSP-4 and Nt-INSP-6, serum antibody binding was stronger in type 1 diabetes compared with healthy control participants (p≤0.02), with oxidised forms of ERGFFYTPKT, oxPTM-INSP-6 conferring the highest antibody binding (83% binders to peptide modified in house by hydroxyl radical [●OH] and >88% to in silico-oxidised peptide; p≤0.001 vs control participants). Nt-INSP-4 induced the strongest T cell stimulation in type 1 diabetes compared with control participants for both CD4+ (p<0.001) and CD8+ (p=0.049). CD4+ response to oxPTM-INSP-6 was also commoner in type 1 diabetes than in control participants (66.7% vs 27.3%; p=0.039). Among individuals with type 1 diabetes, the CD4+ response to oxPTM-INSP-6 was more frequent than to Nt-INSP-6 (66.7% vs 27.8%; p=0.045). Overall, 44.4% of patients showed a concordant autoimmune response to oxPTM-INSP involving simultaneously CD4+ and CD8+ T cells and autoantibodies. Conclusions/interpretation Our findings support the concept that oxidative stress, and neoantigenic epitopes of insulin, may be involved in the immunopathogenesis of type 1 diabetes. Graphical abstract

Recent research focused on identifying mechanisms explaining the observed heterogeneity of type 1 diabetes (T1D) in age at onset, residual β-cell function and rate of disease progression. Mechanisms include changes in both the immune system and β-cells, leading to the loss of tissue-specific immune tolerance and disease onset. Interleukin-8 (IL-8; CXCL8) is a pro-inflammatory chemokine released by macrophages, endothelial, epithelial and airway smooth muscle cells playing a major role in the innate immune response. Macrophages release IL-8 at the site of an injury where they recruit and activate neutrophils by interacting with the IL-8 receptors CXCR1 and CXCR2. An increase in circulating IL-8 has been shown in several autoimmune disorders. IL-8 levels, but not IL-6 or TNF-α, are elevated in adolescents with T1D, and also associated with insulin resistance, suggesting a role for IL-8 beyond acute inflammation in this setting. In vitro experiments revealed that IL-8 transcription is induced by hyperglycaemia. In the present study newly diagnosed T1D patients within the first year of disease onset (mean age 16.2 ± 7.6 yrs and % HbA1c of 10.7 ± 2.7) (N=42) were studied. Clinical and laboratory features included age, gender, body mass index (BMI), disease duration, HbA1c, and C-peptide. Serum IL-8 and myeloperoxidase (MPO) were measured with commercial enzyme-linked Immunosorbent assays. When compared to normal subjects, T1D patients showed a significantly higher IL-8 values (median [IQR] 112.0 [64.74-311.8] vs 43.05 [30.94-49.70], p-value= 0.002, respectively). Furthermore, T1D patients showed a significantly higher MPO levels than controls (median [IQR], 95327 [55718 - 168974] vs 42729 [24147 - 95327], p-value= 0.0349, respectively). This study shows for the first time that IL-8 and MPO are elevated in patients with recent onset T1D compared to normal subjects. There is also a trend for a positive correlation between IL-8 and HbA1c levels suggesting that elevated IL-8 values are associated with poor metabolic control. Disclosure G.Alhamar: None. S.Fallucca: Consultant; Dompé. S.Pieralice: None. L.Valente: None. P.Pozzilli: None.