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OBJECTIVE: Proteomic profiling can identify useful biomarkers. Monozygotic (MZ) twins discordant for a condition represent an ideal test population. We aimed to investigate and validate proteomic profiling in twins with type 1 diabetes and in other well-characterized cohorts. RESEARCH DESIGN AND METHODS: A broad, multiplex analysis of 4,068 proteins in serum samples from MZ twins concordant (n = 43) and discordant (n = 27) for type 1 diabetes identified major differences that were subsequently validated by a trypsin(ogen) assay in MZ pairs concordant (n = 39) and discordant (n = 42) for type 1 diabetes, individuals at risk for (n = 195) and with (n = 990) type 1 diabetes, as well as individuals with non–insulin-requiring adult-onset diabetes diagnosed as either autoimmune (n = 96) or type 2 (n = 291). RESULTS: Proteomic analysis identified major differences between exocrine enzyme levels in discordant MZ twin pairs despite a strong correlation between twins, whether concordant or discordant for type 1 diabetes (P < 0.01 for both). In validation experiments, trypsin(ogen) levels were lower in twins with diabetes than in the co-twin without diabetes (P < 0.0001) and healthy control participants (P < 0.0001). In recently diagnosed participants, trypsin(ogen) levels were lower than in control participants across a broad age range. In at-risk relatives, levels <15 ng/mL were associated with an increased risk of progression (uncorrected P = 0.009). Multiple linear regression in recently diagnosed participants showed that trypsin(ogen) levels were associated with insulin dose and diabetic ketoacidosis, while age and BMI were confounders. CONCLUSIONS: Type 1 diabetes is associated with altered exocrine function, even before onset. Twin data suggest roles for genetic and nongenetically determined factors. Exocrine/endocrine interactions are important underinvestigated factors in type 1 diabetes. [ABSTRACT FROM AUTHOR]

Objective: To describe the relationship between type 2 diabetes and all-cause mortality among adults with coronavirus disease 2019 (COVID-19) in the critical care setting.Research Design and Methods: This was a nationwide retrospective cohort study in people admitted to hospital in England with COVID-19 requiring admission to a high dependency unit (HDU) or intensive care unit (ICU) between 1 March 2020 and 27 July 2020. Cox proportional hazards models were used to estimate 30-day in-hospital all-cause mortality associated with type 2 diabetes, with adjustment for age, sex, ethnicity, obesity, and other major comorbidities (chronic respiratory disease, asthma, chronic heart disease, hypertension, immunosuppression, chronic neurological disease, chronic renal disease, and chronic liver disease).Results: A total of 19,256 COVID-19-related HDU and ICU admissions were included in the primary analysis, including 13,809 HDU (mean age 70 years) and 5,447 ICU (mean age 58 years) admissions. Of those admitted, 3,524 (18.3%) had type 2 diabetes and 5,077 (26.4%) died during the study period. Patients with type 2 diabetes were at increased risk of death (adjusted hazard ratio [aHR] 1.23 [95% CI 1.14, 1.32]), and this result was consistent in HDU and ICU subsets. The relative mortality risk associated with type 2 diabetes decreased with higher age (age 18-49 years aHR 1.50 [95% CI 1.05, 2.15], age 50-64 years 1.29 [1.10, 1.51], and age ≥65 years 1.18 [1.09, 1.29]; P value for age-type 2 diabetes interaction = 0.002).Conclusions: Type 2 diabetes may be an independent prognostic factor for survival in people with severe COVID-19 requiring critical care treatment, and in this setting the risk increase associated with type 2 diabetes is greatest in younger people. [ABSTRACT FROM AUTHOR]

Objective: With rising obesity, it is becoming increasingly difficult to distinguish between type 1 diabetes (T1D) and type 2 diabetes (T2D) in young adults. There has been substantial recent progress in identifying the contribution of common genetic variants to T1D and T2D. We aimed to determine whether a score generated from common genetic variants could be used to discriminate between T1D and T2D and also to predict severe insulin deficiency in young adults with diabetes.Research Design and Methods: We developed genetic risk scores (GRSs) from published T1D- and T2D-associated variants. We first tested whether the scores could distinguish clinically defined T1D and T2D from the Wellcome Trust Case Control Consortium (WTCCC) (n = 3,887). We then assessed whether the T1D GRS correctly classified young adults (diagnosed at 20-40 years of age, the age-group with the most diagnostic difficulty in clinical practice; n = 223) who progressed to severe insulin deficiency <3 years from diagnosis.Results: In the WTCCC, the T1D GRS, based on 30 T1D-associated risk variants, was highly discriminative of T1D and T2D (area under the curve [AUC] 0.88 [95% CI 0.87-0.89]; P < 0.0001), and the T2D GRS added little discrimination (AUC 0.89). A T1D GRS >0.280 (>50th centile in those with T1D) is indicative of T1D (50% sensitivity, 95% specificity). A low T1D GRS (<0.234, <5th centile T1D) is indicative of T2D (53% sensitivity, 95% specificity). Most discriminative ability was obtained from just nine single nucleotide polymorphisms (AUC 0.87). In young adults with diabetes, T1D GRS alone predicted progression to insulin deficiency (AUC 0.87 [95% CI 0.82-0.92]; P < 0.0001). T1D GRS, autoantibody status, and clinical features were independent and additive predictors of severe insulin deficiency (combined AUC 0.96 [95% CI 0.94-0.99]; P < 0.0001).Conclusions: A T1D GRS can accurately identify young adults with diabetes who will require insulin treatment. This will be an important addition to correctly classifying individuals with diabetes when clinical features and autoimmune markers are equivocal. [ABSTRACT FROM AUTHOR]

The article presents a study which found that that the detection of monogenic diabetes in a population can be improved by excluding individuals with type 1 diabetes (T1D) identified by having low C-peptide levels and/or the presence of GAD autoantibodies (GADA) or IA-2 autoantibodies (IA-2A). The study informs that zinc transporter 8 autoantibodies (ZnT8A) and a Type 1 diabetes genetic risk score can exclude individuals with Type 1 Diabetes.