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Iterative advances in understanding of the genetics of type 1 diabetes have identified >70 genetic regions associated with risk of the disease, including strong associations across the HLA class II region that account for >50% of heritability. The increased availability of genetic data combined with the decreased costs of generating these data, have facilitated the development of polygenic scores that aggregate risk variants from associated loci into a single number: either a genetic risk score (GRS) or a polygenic risk score (PRS). PRSs incorporate the risk of many possibly correlated variants from across the genome, even if they do not reach genome-wide significance, whereas GRSs estimate the cumulative contribution of a smaller subset of genetic variants that reach genome-wide significance. Type 1 diabetes GRSs have utility in diabetes classification, aiding discrimination between type 1 diabetes, type 2 diabetes and MODY. Type 1 diabetes GRSs are also being used in newborn screening studies to identify infants at risk of future presentation of the disease. Most early studies of type 1 diabetes genetics have been conducted in European ancestry populations, but, to develop accurate GRSs across diverse ancestries, large case–control cohorts from non-European populations are still needed. The current barriers to GRS implementation within healthcare are mainly related to a lack of guidance and knowledge on integration with other biomarkers and clinical variables. Once these limitations are addressed, there is huge potential for 'test and treat' approaches to be used to tailor care for individuals with type 1 diabetes. [ABSTRACT FROM AUTHOR]

Aims/hypothesis: It is important to differentiate the two major phenotypes of adult-onset diabetes, autoimmune type 1 diabetes and non-autoimmune type 2 diabetes, especially as type 1 diabetes presents in adulthood. Serum GAD65 autoantibodies (GADA) are the most sensitive biomarker for adult-onset autoimmune type 1 diabetes, but the clinical value of GADA by current standard radiobinding assays (RBA) remains questionable. The present study focused on the clinical utility of GADA differentiated by a new electrochemiluminescence (ECL) assay in patients with adult-onset diabetes. Methods: Two cohorts were analysed including 771 diabetic participants, 30–70 years old, from the Action LADA study (n = 6156), and 2063 diabetic participants, 20–45 years old, from the Diabetes in Young Adults (DiYA) study. Clinical characteristics of participants, including requirement of early insulin treatment, BMI and development of multiple islet autoantibodies, were analysed according to the status of RBA-GADA and ECL-GADA, respectively, and compared between these two assays. Results: GADA was the most prevalent and predominant autoantibody, >90% in both cohorts. GADA positivity by either RBA or ECL assay significantly discriminated clinical type 1 from type 2 diabetes. However, in both cohorts, participants with ECL-GADA positivity were more likely to require early insulin treatment, have multiple islet autoantibodies, and be less overweight (for all p < 0.0001). However, clinical phenotype, age at diagnosis and BMI independently improved positive predictive value (PPV) for the requirement of insulin treatment, even augmenting ECL-GADA. Participants with GADA detectable by RBA, but not confirmed by ECL, had a phenotype more similar to type 2 diabetes. These RBA-GADA positive individuals had lower affinity GADA compared with participants in which GADA was confirmed by ECL assay. Conclusions/interpretation: Detection of GADA by ECL assay, given technical advantages over RBA-GADA, identified adult-onset diabetes patients at higher risk of requiring early insulin treatment, as did clinical phenotype, together allowing for more accurate clinical diagnosis and management. [ABSTRACT FROM AUTHOR]

Aims/hypothesis: We aimed to characterise the immunogenic background of insulin-dependent diabetes in a resource-poor rural African community. The study was initiated because reports of low autoantibody prevalence and phenotypic differences from European-origin cases with type 1 diabetes have raised doubts as to the role of autoimmunity in this and similar populations. Methods: A study of consecutive, unselected cases of recently diagnosed, insulin-dependent diabetes (n = 236, ≤35 years) and control participants (n = 200) was carried out in the ethnic Amhara of rural North-West Ethiopia. We assessed their demographic and socioeconomic characteristics, and measured non-fasting C-peptide, diabetes-associated autoantibodies and HLA-DRB1 alleles. Leveraging genome-wide genotyping, we performed both a principal component analysis and, given the relatively modest sample size, a provisional genome-wide association study. Type 1 diabetes genetic risk scores were calculated to compare their genetic background with known European type 1 diabetes determinants. Results: Patients presented with stunted growth and low BMI, and were insulin sensitive; only 15.3% had diabetes onset at ≤15 years. C-peptide levels were low but not absent. With clinical diabetes onset at ≤15, 16–25 and 26–35 years, 86.1%, 59.7% and 50.0% were autoantibody positive, respectively. Most had autoantibodies to GAD (GADA) as a single antibody; the prevalence of positivity for autoantibodies to IA-2 (IA-2A) and ZnT8 (ZnT8A) was low in all age groups. Principal component analysis showed that the Amhara genomes were distinct from modern European and other African genomes. HLA-DRB1*03:01 (p = 0.0014) and HLA-DRB1*04 (p = 0.0001) were positively associated with this form of diabetes, while HLA-DRB1*15 was protective (p < 0.0001). The mean type 1 diabetes genetic risk score (derived from European data) was higher in patients than control participants (p = 1.60 × 10−7). Interestingly, despite the modest sample size, autoantibody-positive patients revealed evidence of association with SNPs in the well-characterised MHC region, already known to explain half of type 1 diabetes heritability in Europeans. Conclusions/interpretation: The majority of patients with insulin-dependent diabetes in rural North-West Ethiopia have the immunogenetic characteristics of autoimmune type 1 diabetes. Phenotypic differences between type 1 diabetes in rural North-West Ethiopia and the industrialised world remain unexplained. [ABSTRACT FROM AUTHOR]

Physiological plasticity enables homeostasis to be maintained in biological systems, but when such allostasis fails, then disease can develop. In a new population-based study by Rolandsson et al (10.1007/s00125-019-05016-3), autoimmunity, defined by an immunogenotype, predicted adult-onset non-insulin requiring diabetes. Type 1 diabetes is no longer viewed as a disease confined to children, with a significant proportion, maybe the majority, presenting in adulthood. Such cases masquerade as type 2 diabetes and their identification has clinical utility. Nevertheless, in this study, autoimmunity had a limited effect on the overall risk of adults developing diabetes. [ABSTRACT FROM AUTHOR]

Aims/hypothesis: Adult-onset type 1 diabetes, in which the 65 kDa isoform of GAD (GAD65) is a major autoantigen, has a broad clinical phenotype encompassing variable need for insulin therapy. This study aimed to evaluate whether autoantibodies against N-terminally truncated GAD65 more closely defined a type 1 diabetes phenotype associated with insulin therapy.Methods: Of 1114 participants with adult-onset diabetes from the Action LADA (latent autoimmune diabetes in adults) study with sufficient sera, we selected those designated type 1 (n = 511) or type 2 diabetes (n = 603) and retested the samples in radiobinding assays for human full-length GAD65 autoantibodies (f-GADA) and N-terminally truncated (amino acids 96-585) GAD65 autoantibodies (t-GADA). Individuals’ clinical phenotypes were analysed according to antibody binding patterns.Results: Overall, 478 individuals were f-GADA-positive, 431 were t-GADA-positive and 628 were negative in both assays. Risk of insulin treatment was augmented in t-GADA-positive individuals (OR 4.69 [95% CI 3.57, 6.17]) compared with f-GADA-positive individuals (OR 3.86 [95% CI 2.95, 5.06]), irrespective of diabetes duration. Of 55 individuals who were f-GADA-positive but t-GADA-negative, i.e. with antibody binding restricted to the N-terminus of GAD65, the phenotype was similar to type 2 diabetes with low risk of progression to insulin treatment. Compared with these individuals with N-terminal GAD65-restricted GADA, t-GADA-positive individuals were younger at diagnosis (p = 0.005), leaner (p < 0.0001) and more often had multiple diabetes-associated autoantibodies (28.3% vs 7.3%; p = 0.0005).Conclusions/interpretation: In individuals with adult-onset diabetes, presence of N-terminally truncated GAD65 autoantibodies is associated with the clinical phenotype of autoimmune type 1 diabetes and predicts insulin therapy. [ABSTRACT FROM AUTHOR]

Purpose Of Review: Epigenetics is defined as mitotically heritable changes in gene expression that do not directly alter the DNA sequence. By implication, such epigenetic changes are non-genetically determined, although they can be affected by inherited genetic variation. Extensive evidence indicates that autoimmune diseases including type 1 diabetes are determined by the interaction of genetic and non-genetic factors. Much is known of the genetic causes of these diseases, but the non-genetic effects are less clear-cut. Further, it remains unclear how they interact to cause the destructive autoimmune process. This review identifies the key issues in the genetic/non-genetic interaction, examining the most recent evidence of the role of non-genetic effects in the disease process, including the impact of epigenetic effects on key pathways.Recent Findings: Recent research indicates that these pathways likely involve immune effector cells both of the innate and adaptive immune response. Specifically, there is evidence of cell type-specific enrichment in altered DNA methylation, changes which were temporally stable and enriched at gene regulatory elements. Epigenomics remains in its infancy, and we anticipate further studies will define how the interaction of genetic and non-genetic effects induces tissue-specific destruction and enhances our ability to predict, and possibly even modify that process. [ABSTRACT FROM AUTHOR]