Identification of Novel T1D Risk Loci and Their Association With Age and Islet Function at Diagnosis in Autoantibody-Positive T1D Individuals: Based on a Two-Stage Genome-Wide Association Study

Genetic Associations with C-peptide Levels before Type 1 Diabetes Diagnosis in At-Risk Relatives

OBJECTIVE

We sought to determine whether the type 1 diabetes genetic risk score-2 (T1D-GRS2) and single nucleotide polymorphisms (SNPs) are associated with C-peptide preservation before type 1 diabetes diagnosis.

METHODS

We conducted a retrospective analysis of 713 autoantibody-positive participants who developed type 1 diabetes in the TrialNet Pathway to Prevention Study who had T1DExomeChip data. We evaluated the relationships of 16 known SNPs and T1D-GRS2 with area under the curve (AUC) C-peptide levels during oral glucose tolerance tests conducted in the 9 months before diagnosis.

RESULTS

Higher T1D-GRS2 was associated with lower C-peptide AUC in the 9 months before diagnosis in univariate (β=-0.06, P<0.0001) and multivariate (β=-0.03, P=0.005) analyses. Participants with the JAZF1 rs864745 T allele had lower C-peptide AUC in both univariate (β=-0.11, P=0.002) and multivariate (β=-0.06, P=0.018) analyses.

CONCLUSIONS

The type 2 diabetes-associated JAZF1 rs864745 T allele and higher T1D-GRS2 are associated with lower C-peptide AUC prior to diagnosis of type 1 diabetes, with implications for the design of prevention trials.

Familial aggregation and heritability of childhood-onset and adult-onset type 1 diabetes: a Swedish register-based cohort study

BACKGROUND

Type 1 diabetes in children is known to be highly heritable, but much less is known about the heritability of adult-onset type 1 diabetes. Thus, our objective was to compare the familial aggregation and heritability of type 1 diabetes in adults and children.

METHODS

This Swedish nationwide register-based cohort study included individuals born from Jan 1, 1982, to Dec 31, 2010, identified through the Medical Birth Register who were linked to their parents, full siblings, half siblings, and cousins through the Multi-Generation Register (MGR). We excluded multiple births, deaths within the first month of life, individuals who could not be linked to MGR, or individuals with contradictory information on sex. Information on diagnoses of type 1 diabetes was retrieved by linkages to the National Diabetes Register and National Patient Register (1982-2020). Individuals with inconsistent records of diabetes type were excluded. We estimated the cumulative incidence and hazard ratios (HRs) of type 1 diabetes in adults (aged 19-30 years) and children (aged 0-18 years) by family history of type 1 diabetes and the heritability of adult-onset and childhood-onset type 1 diabetes based on tetrachoric correlations, using sibling pairs.

FINDINGS

2 943 832 individuals were born in Sweden during the study period, 2 832 755 individuals were included in the analysis of childhood-onset type 1 diabetes and 1 805 826 individuals were included in the analysis of adult-onset type 1 diabetes. 3240 cases of adult-onset type 1 diabetes (median onset age 23·4 years [IQR 21·1-26·2]; 1936 [59·7%] male and 1304 [40·2%] female) and 17 914 cases of childhood-onset type 1 diabetes (median onset age 9·8 years [6·2-13·3]; 9819 [54·8%] male and 8095 [45·2%] female) developed during follow-up. Having a first-degree relative with type 1 diabetes conferred an HR of 7·21 (95% CI 6·28-8·28) for adult-onset type 1 diabetes and 9·92 (9·38-10·50) for childhood-onset type 1 diabetes. The HR of developing type 1 diabetes before the age 30 years was smaller if a first-degree relative developed type 1 diabetes during adulthood (6·68 [6·04-7·39]) rather than during childhood (10·54 [9·92-11·19]). Similar findings were observed for type 1 diabetes in other relatives. Heritability was lower for adult-onset type 1 diabetes (0·56 [0·45-0·66]) than childhood-onset type 1 diabetes (0·81 [0·77-0·85]).

INTERPRETATION

Adult-onset type 1 diabetes seems to have weaker familial aggregation and lower heritability than childhood-onset type 1 diabetes. This finding suggests a larger contribution of environmental factors to the development of type 1 diabetes in adults than in children and highlights the need to identify and intervene on such factors.

FUNDING

Swedish Research Council, the Swedish Research Council for Health, Working Life and Welfare, Swedish Diabetes Foundation, and the China Scholarship Council.

Age at onset of type 1 diabetes between puberty and 30 years old is associated with increased diabetic nephropathy risk

Diabetic nephropathy is a critical complication of patients with type 1 diabetes, while epidemiological studies were scarce among Asian countries. We conducted a cross-sectional study to identify factors associated with diabetic nephropathy by questionnaires, using student's t-test, chi-square test, and multivariable logistic regression. Among 898 participants, 16.7% had diabetic nephropathy. Compared with non-diabetic nephropathy patients, the patients with diabetic nephropathy had significantly higher percentage with onset age of type 1 diabetes between puberty and under 30 years old (female ≥ 12 or male ≥ 13 years old to 29 years old), longer diabetes duration, having family history of diabetes and diabetic nephropathy, accompanied with hypertension, hyperlipidemia, or coronary artery disease (CAD). Compared with patients with onset age before puberty, the odds of diabetic nephropathy occurrence increased to 1.61 times in patients with onset age between puberty and under 30 years old (p = 0.012) after adjusting diabetes duration. Age of diabetes onset between puberty and under 30 years old, diabetes duration, HbA1c, hospital admission within 3 years, diabetic retinopathy, hypertension, systolic blood pressure (SBP), triglyceride levels, and use of angiotensin converting enzyme inhibitor (ACEI) and/or angiotensin receptor blockers (ARB) were independent factors associated with diabetic nephropathy Screening for proteinuria is important in daily clinical practice and should be part of diabetes self-management education for patients with type 1 diabetes.

Synergistic effects of BTN3A1, SHP2, CD274, and STAT3 gene polymorphisms on the risk of systemic lupus erythematosus: a multifactorial dimensional reduction analysis

OBJECTIVE

Systemic lupus erythematosus is a complex autoimmune disorder, and evidence supports the significance of genetic polymorphisms in SLE genetic susceptibility. The aim of this study was to assess the effects of BTN3A1 (butyrophilin 3A1), SHP2 (Src homology-2 containing protein tyrosine phosphatase), CD274 (programmed cell death 1 ligand 1), and STAT3 (signal transducer-activator of transcription 3) gene interactions on SLE risk.

MATERIALS AND METHODS

Two hundred and ninety patients diagnosed with SLE and 370 healthy controls were recruited. A multifactor dimensionality reduction (MDR) approach was used to determine the epistasis among single nucleotide polymorphisms (SNPs) on the BTN3A1 (rs742090), SHP2 (rs58116261), CD174 (rs702275), and STAT3 (rs8078731) genes. The best risk prediction model was identified in terms of precision and cross-validation consistency.

RESULTS

Allele A and genotype AA were negatively related to genetic susceptibility of SLE for BTN3A1 rs742090 (OR = 0.788 (0.625-0.993), P = 0.044; OR = 0.604 (0.372-0.981), P = 0.040). For STAT3 rs8078731, allele A and genotype AA were positively related to the risk of SLE (OR = 1.307 (1.032-1.654), P = 0.026; OR = 1.752 (1.020-3.010), P = 0.041). MDR analysis revealed the most significant interaction between BTN3A1 rs742090 and SHP2 rs58116261. The best risk prediction model was a combination of BTN3A1 rs742090, SHP2 rs58116261, and STAT3 rs8078731 (accuracy = 0.5866, consistency = 10/10, OR = 1.9870 (1.5964-2.4731), P = 0.001).

CONCLUSION

These data indicate that risk prediction models formed by gene interactions (BTN3A1, SHP2, STAT3) can identify susceptible populations of SLE. Key Points • BTN3A1 rs742090 polymorphism was a protective factor for systemic lupus erythematosus, while STAT3 rs8078731 polymorphism was a risk factor. • There was a strong synergistic effect of BTN3A1 rs742090 and SHP2 rs58116261, and interaction among BTN3A1 rs742090, SHP2 rs58116261, and STAT3 rs8078731 constructed the best model to show association with SLE risk.

Association of RPS26 gene polymorphism with different types of diabetes in Chinese individuals

AIMS/INTRODUCTION

Different types of diabetes show distinct genetic characteristics, but the specific genetic susceptibility factors remain unclear. Our study aimed to explore the associations between the ribosomal protein S26 (RPS26) gene rs1131017 polymorphisms and susceptibility to type 1 diabetes mellitus, latent autoimmune diabetes in adults (LADA) and type 2 diabetes mellitus in the Chinese Han population, and their correlations with clinical features.

MATERIALS AND METHODS

Genotyping of the rs1131017 variant was carried out for 1,006 type 1 diabetes mellitus patients, 210 LADA patients, 642 type 2 diabetes mellitus patients and 2,099 control individuals.

RESULTS

We found that the rs1131017 C allele was a risk locus for both type 1 diabetes mellitus and LADA (odds ratio [OR] 1.50, 95% confidence interval [CI] 1.33-1.69, P < 0.001; OR 1.31, 95% CI 1.04-1.64, P = 0.021, respectively). Nevertheless, this association was not found for type 2 diabetes mellitus. Carrying the C allele genotype was associated with a lower postprandial C-peptide for type 1 diabetes mellitus (OR 1.41, 95% CI 1.11-1.80, P = 0.006) and lower fasting C-peptide for LADA (OR 1.55, 95% CI 1.01-2.38, P = 0.047). Interestingly, a lower GC frequency was noted for LADA than for type 1 diabetes mellitus, regardless of classification based on age at diagnosis, C-peptide or glutamic acid decarboxylase antibody positivity.

CONCLUSIONS

The RPS26 polymorphism was associated with susceptibility and clinical characteristics of type 1 diabetes mellitus and LADA in the Chinese population, but was not related to type 2 diabetes mellitus. Thus, it might serve as a novel biomarker for particular types of diabetes.

Genetic evidence for the causal association between type 1 diabetes and the risk of polycystic ovary syndrome

BACKGROUND

Accumulating observational studies have identified associations between type 1 diabetes (T1D) and polycystic ovary syndrome (PCOS). Still, the evidence about the causal effect of this association is uncertain.

METHODS

We performed a two-sample Mendelian randomization (MR) analysis to test for the causal association between T1D and PCOS using data from a large-scale biopsy-confirmed genome-wide association study (GWAS) in European ancestries. We innovatively divided T1D into nine subgroups to be analyzed separately, including: type1 diabetes wide definition, type1 diabetes early onset, type 1 diabetes with coma, type 1 diabetes with ketoacidosis, type 1 diabetes with neurological complications, type 1 diabetes with ophthalmic complications, type 1 diabetes with peripheral circulatory complications, type 1 diabetes with renal complications, and type 1 diabetes with other specified/multiple/unspecified complications. GWAS data for PCOS were obtained from a large-scale GWAS (10,074 cases and 103,164 controls) for primary analysis and the IEU consortium for replication and meta-analysis. Sensitivity analyses were conducted to evaluate heterogeneity and pleiotropy.

RESULTS

Following rigorous instrument selection steps, the number of SNPs finally used for T1D nine subgroups varying from 6 to 36 was retained in MR estimation. However, we did not observe evidence of causal association between type 1 diabetes nine subgroups and PCOS using the IVW analysis, MR-Egger regression, and weighted median approaches, and all P values were > 0.05 with ORs near 1. Subsequent replicates and meta-analyses also yielded consistent results. A number of sensitivity analyses also did not reveal heterogeneity and pleiotropy, including Cochran's Q test, MR-Egger intercept test, MR-PRESSO global test, leave-one-out analysis, and funnel plot analysis.

CONCLUSION

This is the first MR study to investigate the causal relationship between type 1 diabetes and PCOS. Our findings failed to find substantial causal effect of type 1 diabetes on risk of PCOS. Further randomized controlled studies and MR studies are necessary.

Understanding diabetes heterogeneity: key steps towards precision medicine in diabetes

Diabetes is a highly heterogeneous condition; yet, it is diagnosed by measuring a single blood-borne metabolite, glucose, irrespective of aetiology. Although pragmatically helpful, disease classification can become complex and limit advances in research and medical care. Here, we describe diabetes heterogeneity, highlighting recent approaches that could facilitate management by integrating three disease models across all forms of diabetes, namely, the palette model, the threshold model and the gradient model. Once diabetes has developed, further worsening of established diabetes and the subsequent emergence of diabetes complications are kept in check by multiple processes designed to prevent or circumvent metabolic dysfunction. The impact of any given disease risk factor will vary from person-to-person depending on their background, diabetes-related propensity, and environmental exposures. Defining the consequent heterogeneity within diabetes through precision medicine, both in terms of diabetes risk and risk of complications, could improve health outcomes today and shine a light on avenues for novel therapy in the future.

Combining polygenic risk scores and human leukocyte antigen variants for personalized risk assessment of type 1 diabetes in the Taiwanese population

AIMS

To analyse the genome-wide association study (GWAS) data of patients with type 1 diabetes mellitus (T1D) in order to develop a risk score for the genetic effects on T1D risk and age at diagnosis in the Taiwanese population.

MATERIALS AND METHODS

We selected 610 patients with T1D and 2511 healthy individuals from an electronic medical record database of more than 300 000 individuals with genetic information, analysed their GWAS data, and developed a polygenic risk score (PRS).

RESULTS

The PRS, based on 149 selected single-nucleotide polymorphisms, could effectively predict T1D risk. A PRS increase was associated with increased T1D risk (odds ratio [OR] 2.09, 95% confidence interval [CI] 1.72-2.55). Moreover, a 1-unit increase in standardized T1D PRS decreased the age at diagnosis by 0.74 years. Combined PRS and human leukocyte antigen (HLA) DQA1*03:02-DQA1*05:01 genotypes could accurately predict T1D risk. In multivariable models, HLA variants and PRS were independent risk factors for T1D risk (OR 3.76 [95% CI 1.54-9.16] and 1.71 [95% CI 1.37-2.13] for HLA DQA1*03:02-DQA1*05:01 and PRS, respectively). In a limited study population of those aged ≤18 years, PRS remained significantly associated with T1D risk. The association between T1D PRS and age at diagnosis was more obvious among males and patients aged ≤18 years.

CONCLUSIONS

Polygenic risk score and HLA variations enable personalized risk estimates, enhance newborn screening efficiency for ketoacidosis prevention, and addresses the gap in data on T1D prediction in isolated Asian populations.

Prevalence, clinical characteristics and HLA genotypes of idiopathic type 1 diabetes: A cross-sectional study

AIMS

Idiopathic type 1 diabetes (T1D) is a neglected subtype of T1D. Our aim was to investigate the frequency, clinical characteristics, and human leucocyte antigen (HLA) genotypes of idiopathic T1D.

METHODS

We enrolled 1205 newly diagnosed T1D patients in our analysis. To exclude monogenic diabetes in autoantibody-negative patients, we utilised a custom monogenic diabetes gene panel. Individuals negative for autoantibodies and subsequently excluded for monogenic diabetes were diagnosed with idiopathic T1D. We collected clinical characteristics, measured islet autoantibodies by radioligand assay and obtained HLA data.

RESULTS

After excluding 11 patients with monogenic diabetes, 284 cases were diagnosed with idiopathic T1D, accounting for 23.8% (284/1194) of all newly diagnosed T1D cases. When compared with autoimmune T1D, idiopathic T1D patients showed an older onset age, higher body mass index among adults, lower haemoglobin A1c, higher levels of fasting C-peptide and 2-h postprandial C-peptide, and were likely to have type 2 diabetes (T2D) family history and carry 0 susceptible HLA haplotype (all p < 0.01). A lower proportion of individuals carrying 2 susceptible HLA haplotypes in idiopathic T1D was observed in the adult-onset subgroup (15.7% vs. 38.0% in child-onset subgroup, p < 0.001) and in subgroup with preserved beta-cell function (11.0% vs. 30.1% in subgroup with poor beta-cell function, p < 0.001). Multivariable correlation analyses indicated that being overweight, having T2D family history and lacking susceptible HLA haplotypes were associated with negative autoantibodies.

CONCLUSIONS

Idiopathic T1D represents about 1/4 of newly diagnosed T1D, with adult-onset and preserved beta-cell function patients showing lower HLA susceptibility and more insulin resistance.

Utility of genetic risk scores in type 1 diabetes

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.

HLA Class I Association With Autoimmune Diabetes in Chinese People: Distinct Implications in Classic Type 1 Diabetes and LADA

CONTEXT

We aimed to investigate whether human leukocyte antigen (HLA) Class I loci differentially modulated the risk for and clinical features of Chinese people with classic type 1 diabetes (T1D) and latent autoimmune diabetes in adults (LADA).

METHODS

In this case-control study, genotypes of HLA-A, -B, -C, -DRB1, -DQA1, and -DQB1 loci were obtained from 1067 cases with classic T1D, 1062 cases with LADA, and 1107 normal controls using next-generation sequencing.

RESULTS

Despite 4 alleles shared between classic T1D and LADA (protective: A*02:07 and B*46:01; susceptible: B*54:01 and C*08:01), 7 Class I alleles conferred risk exclusively for classic T1D (A*24:02, B*15:02, B*15:18, B*39:01, B*40:06, B*48:01, and C*07:02) whereas only A*02:01 was an additional risk factor for LADA. Class I alleles affected a wide spectrum of T1D clinical features, including positive rate of protein tyrosine phosphatase autoantibody and zinc transporter 8 autoantibody (A*24:02), C-peptide levels (A*24:02), and age at diagnosis (B*46:01, C*01:02, B*15:02, C*07:02, and C*08:01). By contrast, except for the detrimental effect of C*08:01 on C-peptide concentrations in LADA, no other Class I associations with clinical characteristics of LADA could be reported. The addition of Class I alleles refined the risk model consisting only of DR-DQ data in classic T1D while the overall predictive value of the LADA risk model comprising both Class I and II information was relatively low.

CONCLUSION

The attenuated HLA Class I susceptibility to LADA was indicative of a less deleterious immunogenetic nature compared with classic T1D. These autoimmune diabetes-related Class I variants might serve as additional markers in future screening among Chinese people.

Lessons and Gaps in the Prediction and Prevention of Type 1 Diabetes

Type 1 diabetes (T1D) is a serious chronic autoimmune condition. Even though the root cause of T1D development has yet to be determined, enough is known about the natural history of T1D pathogenesis to allow study of interventions that may delay or even prevent the onset of hyperglycemia and clinical T1D. Primary prevention aims to prevent the onset of beta cell autoimmunity in asymptomatic people at high genetic risk for T1D. Secondary prevention strategies aim to preserve functional beta cells once autoimmunity is present, and tertiary prevention aims to initiate and extend partial remission of beta cell destruction after the clinical onset of T1D. The approval of teplizumab in the United States to delay the onset of clinical T1D marks an impressive milestone in diabetes care. This treatment opens the door to a paradigm shift in T1D care. People with T1D risk need to be identified early by measuring T1D related islet autoantibodies. Identifying people with T1D before they have symptoms will facilitate better understanding of pre-symptomatic T1D progression and T1D prevention strategies that may be effective.

Heterogeneity of circulating CXCR5-PD-1hiTph cells in patients of type 2 and type 1 diabetes in Chinese population

AIMS

Circulating peripheral helper T (Tph) cells are shown to promote the progression of autoimmune diseases. However, the role of Tph cells in inflammatory diseases such as type 2 diabetes mellitus (T2DM) and the differences between T2DM and autoimmune diabetes remain unclear.

METHODS

We recruited 92 T2DM patients, 106 type 1 diabetes mellitus (T1DM) patients and 84 healthy control individuals. Peripheral blood mononucleated cells were isolated and examined by multicolor flow cytometry. We further evaluated the correlations between circulating Tph cells and clinical biochemical parameters, islet function, disease progression and islet autoantibodies.

RESULTS

Circulating Tph cells were significantly higher in both T2DM and T1DM patients than in healthy control individuals. A significant positive correlation was observed between Tph cells and B cells in T1DM patients and overweight T2DM patients. Furthermore, Tph cells were negatively correlated with the area under the C-peptide curve (C-PAUC), and Tph cells were significantly positively correlated with fasting glucose and glycated hemoglobin levels in T2DM patients. However, no correlation was found between Tph cells and the above clinical indicators in T1DM patients. The frequency of Tph cells positively correlated with the titer of GAD autoantibodies and duration of disease in T1DM patients. In addition, we demonstrated that the frequency of Tph cells was decreased after rituximab therapy in T1DM patients.

CONCLUSIONS

Circulating Tph cells are associated with blood glucose levels and islet function in T2DM patients. In T1DM patients, circulating Tph cells are associated with B cells and islet autoantibodies. This may suggest that Tph cells have different pathogenic mechanisms in the two types of diabetes.

CLINICAL TRIAL INFORMATION

http://ClinicalTrials.gov NCT01280682 (registered July, 2010).

Understanding Insulin in the Age of Precision Medicine and Big Data: Under-Explored Nature of Genomics

Insulin is amongst the human genome's most well-studied genes/proteins due to its connection to metabolic health. Within this article, we review literature and data to build a knowledge base of Insulin (INS) genetics that influence transcription, transcript processing, translation, hormone maturation, secretion, receptor binding, and metabolism while highlighting the future needs of insulin research. The INS gene region has 2076 unique variants from population genetics. Several variants are found near the transcriptional start site, enhancers, and following the INS transcripts that might influence the readthrough fusion transcript INS-IGF2. This INS-IGF2 transcript splice site was confirmed within hundreds of pancreatic RNAseq samples, lacks drift based on human genome sequencing, and has possible elevated expression due to viral regulation within the liver. Moreover, a rare, poorly characterized African population-enriched variant of INS-IGF2 results in a loss of the stop codon. INS transcript UTR variants rs689 and rs3842753, associated with type 1 diabetes, are found in many pancreatic RNAseq datasets with an elevation of the 3'UTR alternatively spliced INS transcript. Finally, by combining literature, evolutionary profiling, and structural biology, we map rare missense variants that influence preproinsulin translation, proinsulin processing, dimer/hexamer secretory storage, receptor activation, and C-peptide detection for quasi-insulin blood measurements.

The phenotype of type 1 diabetes in sub-Saharan Africa

The phenotype of type 1 diabetes in Africa, especially sub-Saharan Africa, is poorly understood. Most previously conducted studies have suggested that type 1 diabetes may have a different phenotype from the classical form of the disease described in western literature. Making an accurate diagnosis of type 1 diabetes in Africa is challenging, given the predominance of atypical diabetes forms and limited resources. The peak age of onset of type 1 diabetes in sub-Saharan Africa seems to occur after 18-20 years. Multiple studies have reported lower rates of islet autoantibodies ranging from 20 to 60% amongst people with type 1 diabetes in African populations, lower than that reported in other populations. Some studies have reported much higher levels of retained endogenous insulin secretion than in type 1 diabetes elsewhere, with lower rates of type 1 diabetes genetic susceptibility and HLA haplotypes. The HLA DR3 appears to be the most predominant HLA haplotype amongst people with type 1 diabetes in sub-Saharan Africa than the HLA DR4 haplotype. Some type 1 diabetes studies in sub-Saharan Africa have been limited by small sample sizes and diverse methods employed. Robust studies close to diabetes onset are sparse. Large prospective studies with well-standardized methodologies in people at or close to diabetes diagnosis in different population groups will be paramount to provide further insight into the phenotype of type 1 diabetes in sub-Saharan Africa.

Association analysis between the TLR9 gene polymorphism rs352140 and type 1 diabetes

Background

To a great extent, genetic factors contribute to the susceptibility to type 1 diabetes (T1D) development, and by triggering immune imbalance, Toll-like receptor (TLR) 9 is involved in the development of T1D. However, there is a lack of evidence supporting a genetic association between polymorphisms in the TLR9 gene and T1D.

Methods

In total, 1513 individuals, including T1D patients (n=738) and healthy control individuals (n=775), from the Han Chinese population were recruited for an association analysis of the rs352140 polymorphism of the TLR9 gene and T1D. rs352140 was genotyped by MassARRAY. The allele and genotype distributions of rs352140 in the T1D and healthy groups and those in different T1D subgroups were analyzed by the chi-squared test and binary logistic regression model. The chi-square test and Kruskal-Wallis H test were performed to explore the association between genotype and phenotype in T1D patients.

Results

The allele and genotype distributions of rs352140 were significantly different in T1D patients and healthy control individuals (p=0.019, p=0.035). Specifically, the T allele and TT genotype of rs352140 conferred a higher risk of T1D (OR=1.194, 95% CI=1.029-1.385, p=0.019, OR=1.535, 95% CI=1.108-2.126, p=0.010). The allele and genotype distributions of rs352140 were not significantly different between childhood-onset and adult-onset T1D and between T1D with a single islet autoantibody and T1D with multiple islet autoantibodies (p=0.603, p=0.743). rs352140 was associated with T1D susceptibility according to the recessive and additive models (p=0.015, p=0.019) but was not associated with T1D susceptibility in the dominant and overdominant models (p=0.117, p=0.928). Moreover, genotype-phenotype association analysis showed that the TT genotype of rs352140 was associated with higher fasting C-peptide levels (p=0.017).

Conclusion

In the Han Chinese population, the TLR9 polymorphism rs352140 is associated with T1D and is a risk factor for susceptibility to T1D.

Identification of multiple novel susceptibility genes associated with autoimmune thyroid disease

Background

Autoimmune thyroid disease (AITD) is induced by various factors, including inheritability, which regulates gene expression. Multiple loci correlated with AITD have been discovered utilizing genome-wide association studies (GWASs). Nevertheless, demonstrating the biological relevance and function of these genetic loci is difficult.

Methods

The FUSION software was utilized to define genes that were expressed differentially in AITD using a transcriptome-wide association study (TWAS) method in accordance with GWAS summary statistics from the largest genome-wide association study of 755,406 AITD individuals (30,234 cases and 725,172 controls) and levels of gene expression from two tissue datasets (blood and thyroid). Further analyses were performed such as colocalization, conditional, and fine-mapping analyses to extensively characterize the identified associations, using functional mapping and annotation (FUMA) to conduct functional annotation of the summary statistics of 23329 significant risk SNPs (P < 5 × 10^-8) recognized by GWAS, together with summary-data-based mendelian randomization (SMR) for identifying functionally related genes at the loci in GWAS.

Results

There were 330 genes with transcriptome-wide significant differences between cases and controls, and the majority of these genes were new. 9 of the 94 unique significant genes had strong, colocalized, and potentially causal correlations with AITD. Such strong associations included CD247, TPO, KIAA1524, PDE8B, BACH2, FYN, FOXK1, NKX2-3, and SPATA13. Subsequently, applying the FUMA approach, novel putative AITD susceptibility genes and involved gene sets were detected. Furthermore, we detected 95 probes that showed strong pleiotropic association with AITD through SMR analysis, such as CYP21A2, TPO, BRD7, and FCRL3. Lastly, we selected 26 genes by integrating the result of TWAS, FUMA, and SMR analysis. A phenome-wide association study (pheWAS) was then carried out to determine the risk of other related or co-morbid phenotypes for AITD-related genes.

Conclusions

The current work provides further insight into widespread changes in AITD at the transcriptomic level, as well as characterized the genetic component of gene expression in AITD by validating identified genes, establishing new correlations, and uncovering novel susceptibility genes. Our findings indicate that the genetic component of gene expression plays a significant part in AITD.

The missing heritability in type 1 diabetes

Type 1 diabetes (T1D) is a complex autoimmune disease characterized by an absolute deficiency of insulin. It affects more than 20 million people worldwide and imposes an enormous financial burden on patients. The underlying pathogenic mechanisms of T1D are still obscure, but it is widely accepted that both genetics and the environment play an important role in its onset and development. Previous studies have identified more than 60 susceptible loci associated with T1D, explaining approximately 80%-85% of the heritability. However, most identified variants confer only small increases in risk, which restricts their potential clinical application. In addition, there is still a so-called 'missing heritability' phenomenon. While the gap between known heritability and true heritability in T1D is small compared with that in other complex traits and disorders, further elucidation of T1D genetics has the potential to bring novel insights into its aetiology and provide new therapeutic targets. Many hypotheses have been proposed to explain the missing heritability, including variants remaining to be found (variants with small effect sizes, rare variants and structural variants) and interactions (gene-gene and gene-environment interactions; e.g. epigenetic effects). In the following review, we introduce the possible sources of missing heritability and discuss the existing related knowledge in the context of T1D.

Adult-onset autoimmune diabetes

Adult-onset autoimmune (AOA) diabetes pathophysiology starts with immune changes, followed by dysglycaemia and overt disease. AOA diabetes can occur as classic type 1 diabetes when associated with severe loss of insulin secretion. More frequently, it is diagnosed as latent autoimmune diabetes in adults, a slowly progressing form with late onset, a long period not requiring insulin, and it is often misdiagnosed as type 2 diabetes. As its clinical presentation varies remarkably and immune markers often lack specificity, it is challenging to classify each case ad hoc, especially when insulin treatment is not required at diagnosis. Proper care of AOA diabetes aims to prevent complications and to improve quality of life and life expectancy. To achieve these goals, attention should be paid to lifestyle factors, with the aid of pharmacological therapies properly tailored to each individual clinical setting. Given the heterogeneity of the disease, choosing the right therapy for AOA diabetes is challenging. Most of the trials testing disease-modifying therapies for autoimmune diabetes are conducted in people with childhood onset, whereas non-insulin diabetes therapies have mostly been studied in the larger population with type 2 diabetes. More randomized controlled trials of therapeutic agents in AOA diabetes are needed.

Host-microbiota interactions shaping T-cell response and tolerance in type 1 diabetes

Type-1 Diabetes (T1D) is a complex polygenic autoimmune disorder involving T-cell driven beta-cell destruction leading to hyperglycemia. There is no cure for T1D and patients rely on exogenous insulin administration for disease management. T1D is associated with specific disease susceptible alleles. However, the predisposition to disease development is not solely predicted by them. This is best exemplified by the observation that a monozygotic twin has just a 35% chance of developing T1D after their twin’s diagnosis. This makes a strong case for environmental triggers playing an important role in T1D incidence. Multiple studies indicate that commensal gut microbiota and environmental factors that alter their composition might exacerbate or protect against T1D onset. In this review, we discuss recent literature highlighting microbial species associated with T1D. We explore mechanistic studies which propose how some of these microbial species can modulate adaptive immune responses in T1D, with an emphasis on T-cell responses. We cover topics ranging from gut-thymus and gut-pancreas communication, microbial regulation of peripheral tolerance, to molecular mimicry of islet antigens by microbial peptides. In light of the accumulating evidence on commensal influences in neonatal thymocyte development, we also speculate on the link between molecular mimicry and thymic selection in the context of T1D pathogenesis. Finally, we explore how these observations could inform future therapeutic approaches in this disease.

Type 1 diabetes in diverse ancestries and the use of genetic risk scores

Over 75 genetic loci within and outside of the HLA region influence type 1 diabetes risk. Genetic risk scores (GRS), which facilitate the integration of complex genetic information, have been developed in type 1 diabetes and incorporated into models and algorithms for classification, prognosis, and prediction of disease and response to preventive and therapeutic interventions. However, the development and validation of GRS across different ancestries is still emerging, as is knowledge on type 1 diabetes genetics in populations of diverse genetic ancestries. In this Review, we provide a summary of the current evidence on the evolutionary genetic variation in type 1 diabetes and the racial and ethnic differences in type 1 diabetes epidemiology, clinical characteristics, and preclinical course. We also discuss the influence of genetics on type 1 diabetes with differences across ancestries and the development and validation of GRS in various populations.

The Role of Polymorphisms at the Interleukin-1, Interleukin-4, GATA-3 and Cyclooxygenase-2 Genes in Non-Surgical Periodontal Therapy

Periodontitis is a multifactorial disease. The aim of this explorative study was to investigate the role of Interleukin-(IL)-1, IL-4, GATA-3 and Cyclooxygenase-(COX)-2 polymorphisms after non-surgical periodontal therapy with adjunctive systemic antibiotics (amoxicillin/metronidazole) and subsequent maintenance in a Caucasian population. Analyses were performed using blood samples from periodontitis patients of a multi-center trial (ClinicalTrials.gov NCT00707369=ABPARO-study). Polymorphisms were analyzed using quantitative real-time PCR. Clinical attachment levels (CAL), percentage of sites showing further attachment loss (PSAL) ≥1.3 mm, bleeding on probing (BOP) and plaque score were assessed. Exploratory statistical analysis was performed. A total of 209 samples were genotyped. Patients carrying heterozygous genotypes and single-nucleotide-polymorphisms (SNP) on the GATA-3-IVS4 +1468 gene locus showed less CAL loss than patients carrying wild type. Heterozygous genotypes and SNPs on the IL-1A-889, IL-1B +3954, IL-4-34, IL-4-590, GATA-3-IVS4 +1468 and COX-2-1195 gene loci did not influence CAL. In multivariate analysis, CAL was lower in patients carrying GATA-3 heterozygous genotypes and SNPs than those carrying wild-types. For the first time, effects of different genotypes were analyzed in periodontitis progression after periodontal therapy and during supportive treatment using systemic antibiotics demonstrating a slight association of GATA-3 gene locus with CAL. This result suggests that GATA-3 genotypes are a contributory but non-essential risk factor for periodontal disease progression.

3DFAACTS-SNP: using regulatory T cell-specific epigenomics data to uncover candidate mechanisms of type 1 diabetes (T1D) risk

Background

Genome-wide association studies (GWAS) have enabled the discovery of single nucleotide polymorphisms (SNPs) that are significantly associated with many autoimmune diseases including type 1 diabetes (T1D). However, many of the identified variants lie in non-coding regions, limiting the identification of mechanisms that contribute to autoimmune disease progression. To address this problem, we developed a variant filtering workflow called 3DFAACTS-SNP to link genetic variants to target genes in a cell-specific manner. Here, we use 3DFAACTS-SNP to identify candidate SNPs and target genes associated with the loss of immune tolerance in regulatory T cells (Treg) in T1D.

Results

Using 3DFAACTS-SNP, we identified from a list of 1228 previously fine-mapped variants, 36 SNPs with plausible Treg-specific mechanisms of action. The integration of cell type-specific chromosome conformation capture data in 3DFAACTS-SNP identified 266 regulatory regions and 47 candidate target genes that interact with these variant-containing regions in Treg cells. We further demonstrated the utility of the workflow by applying it to three other SNP autoimmune datasets, identifying 16 Treg-centric candidate variants and 60 interacting genes. Finally, we demonstrate the broad utility of 3DFAACTS-SNP for functional annotation of all known common (> 10% allele frequency) variants from the Genome Aggregation Database (gnomAD). We identified 9376 candidate variants and 4968 candidate target genes, generating a list of potential sites for future T1D or other autoimmune disease research.

Conclusions

We demonstrate that it is possible to further prioritise variants that contribute to T1D based on regulatory function, and illustrate the power of using cell type-specific multi-omics datasets to determine disease mechanisms. Our workflow can be customised to any cell type for which the individual datasets for functional annotation have been generated, giving broad applicability and utility.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13072-022-00456-5.

High Residual β-cell Function in Chinese Patients With Autoimmune Type 1 Diabetes

OBJECTIVE

The destruction of pancreatic β cells causes type 1 diabetes mellitus (T1D), an autoimmune disease. Studies have demonstrated that there is heterogeneity in residual β-cell function in Caucasians; therefore, we aimed to evaluate β-cell function in Chinese autoimmune T1D patients.

METHODS

β-cell function was determined using oral glucose tolerance testing or standardized steamed bread meal tolerance test in 446 participants with autoantibody-positive T1D. Clinical factors, such as age onset, sex, duration, body mass index, autoantibodies, other autoimmune diseases, diabetic ketoacidosis, hypoglycemia events, glycosylated hemoglobin, and insulin dose, were retrieved. We also analyzed single nucleotide polymorphism (SNP) data for C-peptides from 144 participants enrolled in the Chinese-T1D genome-wide association study.

RESULTS

Of 446 T1D patients, 98.5%, 97.4%, 86.9%, and 42.6% of individuals had detectable C-peptide values (≥ 0.003 nmol/L) at durations of < 1 year, 1 to 2 years, 3 to 6 years, and ≥ 7 years, respectively. A total of 60.7% of patients diagnosed at ≥ 18 years old and 15.8% of those diagnosed at < 18 years had detectable C-peptide after ≥ 7 years from the diagnosis. Furthermore, the patients diagnosed at ≥ 18 years old had higher absolute values of stimulated C-peptide (≥ 0.2 nmol/L). Diabetic ketoacidosis, hypoglycemia events, and insulin doses were shown to be associated with β-cell function. SNPs rs1770 and rs55904 were associated with C-peptide levels.

CONCLUSION

Our results have indicated that there are high residuals of β-cell mass in Chinese patients with autoimmune T1D. These findings may aid in the consideration of therapeutic strategies seeking prevention and reversal of β-cell function among Chinese T1D patients.

The Foundation for Engineering a Pancreatic Islet Niche

Progress in diabetes research is hindered, in part, by deficiencies in current experimental systems to accurately model human pathophysiology and/or predict clinical outcomes. Engineering human-centric platforms that more closely mimic in vivo physiology, however, requires thoughtful and informed design. Summarizing our contemporary understanding of the unique and critical features of the pancreatic islet can inform engineering design criteria. Furthermore, a broad understanding of conventional experimental practices and their current advantages and limitations ensures that new models address key gaps. Improving beyond traditional cell culture, emerging platforms are combining diabetes-relevant cells within three-dimensional niches containing dynamic matrices and controlled fluidic flow. While highly promising, islet-on-a-chip prototypes must evolve their utility, adaptability, and adoptability to ensure broad and reproducible use. Here we propose a roadmap for engineers to craft biorelevant and accessible diabetes models. Concurrently, we seek to inspire biologists to leverage such tools to ask complex and nuanced questions. The progenies of such diabetes models should ultimately enable investigators to translate ambitious research expeditions from benchtop to the clinic.

The common rs13266634 C > T variant in SLC30A8 contributes to the heterogeneity of phenotype and clinical features of both type 1 and type 2 diabetic subtypes

AIMS

T2D and T1D are phenotypically heterogeneous. This study aims to reveal the relationship between the common SLC30A8 rs13266634 variant and subgroups of T2D and T1D and their clinical characteristics.

METHODS

We included 3158 OGTT-based healthy controls, unrelated 1754 T2D, and 1675 autoantibody-positive T1D individuals. The associations between rs13266634 and subtypes of T2D, T1D, autoantibody status and glycemic-related quantitative traits were performed by binary logistic regression analysis under the additive model and multiple linear regression with appropriate adjustment.

RESULTS

We found that the T allele of rs13266634 was protectively associated with lean (OR = 0.810, P = 6.91E-04) but not obese T2D with considerable heterogeneity (P = 0.018). This allele also conferred significant protection with T1D of single (OR = 0.847, P = 9.76E-03), but not multi autoantibodies with substantial heterogeneity (P = 0.005). This variant significantly affected OGTT-related insulin release in lean (P = 2.66E-03, 3.88E-03 for CIR and DI, respectively) but not obese healthy individuals. Furthermore, rs13266634 T allele correlated with the risk of ZnT8A (OR = 1.440, P = 3.31E-05) and IA-2A (OR = 1.219, P = 1.32E-03) positivity, with more effect size in children/adolescents compared with adult-onset T1D subtypes.

CONCLUSIONS

These suggested that the SLC30A8 rs13266634 variant might be put into genetic risk scores to assess the risk of the subtypes of T1D and T2D and their related clinical features.

Differences of Circulating CD25hi Bregs and Their Correlations with CD4 Effector and Regulatory T Cells in Autoantibody-Positive T1D Compared with Age-Matched Healthy Individuals

Circulating CD25^hi B cells, a subset of regulatory B cells in humans, are closely related to inflammation and autoimmune diseases. This study is aimed at investigating the alternation of CD25^hi Bregs and their correlation with CD4 effector and regulatory T cells in T1D individuals. We included 68 autoantibody-positive T1D and 68 age-matched healthy individuals with peripheral blood mononuclear cells (PBMCs) and assessed them with CD25^hi Bregs and CD4 effector or regulatory T cells by flow cytometry. Here, we demonstrate that the frequency of CD25^hi Bregs was significantly decreased in T1D subjects (P = 0.0016), but they were not affected by disease status (age at T1D diagnosis or duration) or T1D risk loci (rs2104286 or rs12251307) in IL2RA (all P > 0.05). Moreover, higher IgD (P = 0.043) and lower CD27 (P = 0.0003) expression was observed in CD25^hi Bregs of T1D individuals, but not the expression of IgM, CD24, or CD38 (all P > 0.05). Although there was no correlation between CD25^hi Bregs and CD4 effector T cell subsets in either T1D or healthy individuals (all P > 0.05), we found a positive correlation between CD25^hi Bregs and CD4 Tregs in healthy controls (Sp. r = 0.3544, P = 0.0249), which disappeared in T1D subjects (Sp. r = 0.137, P = 0.401). In conclusion, our results suggest that decreased CD25^hi Bregs and alternation of their phenotypes are features of T1D regardless of disease duration and T1D genetic risk loci, and an impaired balance between CD25^hi Bregs and CD4 Tregs might contribute to the pathogenesis of T1D.

Genome-Wide Identification of N6-Methyladenosine Associated SNPs as Potential Functional Variants for Type 1 Diabetes

OBJECTIVES

N6-methyladenosine (m6A) is essential in the regulation of the immune system, but the role that its single nucleotide polymorphisms (SNPs) play in the pathogenesis of type 1 diabetes (T1D) remains unknown. This study demonstrated the association between genetic variants in m6A regulators and T1D risk based on a case-control study in a Chinese population.

METHODS

The tagging SNPs in m6A regulators were genotyped in 1005 autoantibody-positive patients with T1D and 1257 controls using the Illumina Human OmniZhongHua-8 platform. Islet-specific autoantibodies were examined by radioimmunoprecipitation in all the patients. The mixed-meal glucose tolerance test was performed on 355 newly diagnosed patients to evaluate their residual islet function. The functional annotations for the identified SNPs were performed in silico. Using 102 samples from a whole-genome expression microarray, key signaling pathways associated with m6A regulators in T1D were comprehendingly evaluated.

RESULTS

Under the additive model, we observed three tag SNPs in the noncoding region of the PRRC2A (rs2260051, rs3130623) and YTHDC2 (rs1862315) gene are associated with T1D risk. Although no association was found between these SNPs and islet function, patients carrying risk variants had a higher positive rate for ZnT8A, GADA, and IA-2A. Further analyses showed that rs2260051[T] was associated with increased expression of PRRC2A mRNA (P = 7.0E-13), and PRRC2A mRNA was significantly higher in peripheral blood mononuclear cell samples from patients with T1D compared to normal samples (P = 0.022). Enrichment analyses indicated that increased PRRC2A expression engages in the most significant hallmarks of cytokine-cytokine receptor interaction, cell adhesion and chemotaxis, and neurotransmitter regulation pathways. The potential role of increased PRRC2A in disrupting immune homeostasis is through the PI3K/AKT pathway and neuro-immune interactions.

CONCLUSION

This study found intronic variants in PRRC2A and YTHDC2 associated with T1D risk in a Chinese Han population. PRRC2A rs2260051[T] may be implicated in unbalanced immune homeostasis by affecting the expression of PRRC2A mRNA. These findings enriched our understanding of m6A regulators and their intronic SNPs that underlie the pathogenesis of T1D.

Rs864745 in JAZF1, an Islet Function Associated Variant, Correlates With Plasma Lipid Levels in Both Type 1 and Type 2 Diabetes Status, but Not Healthy Subjects

OBJECTIVE

This study aims to reveal the association between JAZF1 rs864745 A>G variant and type 2 diabetes (T2D), type 1 diabetes (T1D) risk, and their correlation with clinical features, including islet function, islet autoimmunity, and plasma lipid levels.

METHODS

We included 2505 healthy controls based on oral glucose tolerance test (OGTT), 1736 unrelated T2D, and 1003 unrelated autoantibody-positive T1D individuals. Binary logistic regression was performed to evaluate the relationships between rs864745 in JAZF1 and T2D, T1D, and islet-specific autoantibody status under the additive model, while multiple linear regression was used to assess its effect on glycemic-related quantitative traits and plasma lipid levels.

RESULTS

We did not find any association between rs864745 in JAZF1 and T2D, T1D, or their subgroups (All P > 0.05). For glycemic traits, we found that the G allele of this variant was significantly associated with higher 120 min insulin level, insulinogenic index (IGI), corrected insulin response (CIR), and acute insulin response (BIGTT-AIR) (P = 0.033, 0.006, 0.009, and 0.016, respectively) in healthy individuals. Similar associations were observed in newly diagnosed T2D but not T1D individuals. Although this variant had no impact on islet autoimmunity (All P > 0.05), significant associations with plasma total cholesterol (TC) and low-density lipoprotein (LDL) level stratified by JAZF1 rs864745 variant were observed in the disease status of T2D (P = 0.002 and 0.003) and T1D (P = 0.024 and 0.009), with significant heterogeneity to healthy individuals.

CONCLUSIONS

The common JAZF1 rs864745 variant contributes to islet function and lipid metabolism, which might be put into genetic risk scores to assess the risk of related clinical features.

Genome-wide association study reveals novel loci for adult type 1 diabetes in a 5-year nested case-control study

BACKGROUND

Type 1 diabetes (T1D) is a severe and prevalent metabolic disease. Due to its high heredity, an increasing number of genome-wide association studies have been performed, most of which were from hospital-based case-control studies with a relatively small sample size. The association of single nucleotide polymorphisms (SNPs) and T1D has been less studied and is less understood in natural cohorts.

AIM

To investigate the significant variants of T1D, which could be potential biomarkers for T1D prediction or even therapy.

METHODS

A genome-wide association study (GWAS) of adult T1D was performed in a nested case-control study (785 cases vs 804 controls) from a larger 5-year cohort study in Suzhou, China. Potential harmful or protective SNPs were evaluated for T1D. Subsequent expression and splicing quantitative trait loci (eQTL and sQTL) analyses were carried out to identify target genes modulated by these SNPs.

RESULTS

A harmful SNP for T1D, rs3117017 [odds ratio (OR) = 3.202, 95% confidence interval (CI): 2.296-4.466, P = 9.33 × 10^-4] and three protective SNPs rs55846421 (0.113, 0.081-0.156, 1.76 × 10^-9), rs75836320 (0.283, 0.205-0.392, 1.07 × 10^-4), rs362071 (0.568, 0.495-0.651, 1.66 × 10^-4) were identified. Twenty-two genes were further identified as potential candidates for T1D onset.

CONCLUSION

We identified a potential genetic basis of T1D, both protective and harmful, using a GWAS in a larger nested case-control study of a Chinese population.

HLA imputation and its application to genetic and molecular fine-mapping of the MHC region in autoimmune diseases

Variations of human leukocyte antigen (HLA) genes in the major histocompatibility complex region (MHC) significantly affect the risk of various diseases, especially autoimmune diseases. Fine-mapping of causal variants in this region was challenging due to the difficulty in sequencing and its inapplicability to large cohorts. Thus, HLA imputation, a method to infer HLA types from regional single nucleotide polymorphisms, has been developed and has successfully contributed to MHC fine-mapping of various diseases. Different HLA imputation methods have been developed, each with its own advantages, and recent methods have been improved in terms of accuracy and computational performance. Additionally, advances in HLA reference panels by next-generation sequencing technologies have enabled higher resolution and a more reliable imputation, allowing a finer-grained evaluation of the association between sequence variations and disease risk. Risk-associated variants in the MHC region would affect disease susceptibility through complicated mechanisms including alterations in peripheral responses and central thymic selection of T cells. The cooperation of reliable HLA imputation methods, informative fine-mapping, and experimental validation of the functional significance of MHC variations would be essential for further understanding of the role of the MHC in the immunopathology of autoimmune diseases.

Adult-Onset Type 1 Diabetes: Current Understanding and Challenges

Recent epidemiological data have shown that more than half of all new cases of type 1 diabetes occur in adults. Key genetic, immune, and metabolic differences exist between adult- and childhood-onset type 1 diabetes, many of which are not well understood. A substantial risk of misclassification of diabetes type can result. Notably, some adults with type 1 diabetes may not require insulin at diagnosis, their clinical disease can masquerade as type 2 diabetes, and the consequent misclassification may result in inappropriate treatment. In response to this important issue, JDRF convened a workshop of international experts in November 2019. Here, we summarize the current understanding and unanswered questions in the field based on those discussions, highlighting epidemiology and immunogenetic and metabolic characteristics of adult-onset type 1 diabetes as well as disease-associated comorbidities and psychosocial challenges. In adult-onset, as compared with childhood-onset, type 1 diabetes, HLA-associated risk is lower, with more protective genotypes and lower genetic risk scores; multiple diabetes-associated autoantibodies are decreased, though GADA remains dominant. Before diagnosis, those with autoantibodies progress more slowly, and at diagnosis, serum C-peptide is higher in adults than children, with ketoacidosis being less frequent. Tools to distinguish types of diabetes are discussed, including body phenotype, clinical course, family history, autoantibodies, comorbidities, and C-peptide. By providing this perspective, we aim to improve the management of adults presenting with type 1 diabetes.

Why all MODY variants are dominantly inherited: a hypothesis

Maturity-onset diabetes in the young (MODY) comprises monogenic phenotypes of young-onset, insulinopenic diabetes. All its forms are dominantly inherited. Why? Are the pancreatic β cells only harmed by heterozygous variants? We propose that recessive MODYs do exist but have escaped detection due to lack of family history suggestive of monogenic inheritance.

Genetic overlap between type 1 diabetes and other autoimmune diseases

Type 1 diabetes (T1D) is a chronic disease caused by the destruction of pancreatic β cells, which is driven by autoreactive T lymphocytes. It has been described that a high proportion of T1D patients develop other autoimmune diseases (AIDs), such as autoimmune thyroid disease, celiac disease, or vitiligo, which suggests the existence of common etiological factors among these disorders. In this regard, genetic studies have identified a high number of loci consistently associated with T1D that also represent established genetic risk factors for other AIDs. In addition, studies focused on identifying the shared genetic component in autoimmunity have described several common susceptibility loci with a potential role in T1D. Elucidation of this genetic overlap has been useful in identifying key molecular pathways with a pathogenic role in multiple disorders. In this review, we summarize recent advances in understanding the shared genetic component between T1D and other AIDs and discuss how the identification of common pathogenic mechanisms can help in the development of new therapeutic approaches as well as in improving the use of existing drugs.

HLA class I genes modulate disease risk and age at onset together with DR-DQ in Chinese patients with insulin-requiring type 1 diabetes

AIMS/HYPOTHESIS

The study aimed to investigate the effects of HLA class I genes on susceptibility to type 1 diabetes with different onset ages, in addition to the well-established effects of HLA class II genes.

METHODS

A total of 361 patients with type 1 diabetes (192 patients with onset <18 years and 169 patients with onset ≥18 years) and 500 healthy control participants from China were enrolled and genotyped for the HLA-A, -B, -C, -DQA1, -DQB1 and -DRB1 genes using next-generation sequencing.

RESULTS

The susceptible DR3 (β = -0.09, p = 0.0009) and DR4-DQ8 (β = -0.13, p = 0.0059) haplotypes were negatively associated with onset age, while the protective DR11 (β = 0.21, p = 0.0314) and DR12 (β = 0.27, p < 0.0001) haplotypes were positively associated with onset age. After adjustment for linkage disequilibrium with DR-DQ haplotypes, A*11:01:01 was positively associated with onset age (β = 0.06, p = 0.0370), while the susceptible C*15:02:01 was negatively associated with onset age (β = -0.21, p = 0.0050). The unit for β was double square-root (fourth root) transformed years of change in onset age associated with per copy of the HLA haplotype/allele. In addition, B*46:01:01 was protective (OR 0.41, 0.46; pc [corrected for multiple comparisons] = 0.0044, 0.0040), whereas A*24:02:01 (OR 2.71, 2.25; pc = 0.0003, 0.0002) and B*54:01:01 (OR 3.96, 3.79; pc = 0.0018, 0.0004) were predisposing in both the <18 group and the ≥18 group compared with healthy control participants. In the context of DR4-DQ4, A*11:01:01 (61.29% vs 28.26%, pc = 0.0144) was increased while the predisposing A*24:02:01 (19.35% vs 47.83%, pc = 0.0403) was decreased in patients with onset ≥18 years when compared with patients with onset <18 years.

CONCLUSIONS/INTERPRETATION

In addition to DR-DQ haplotypes, novel HLA class I alleles were detected to play a role in susceptibility to type 1 diabetes with different onset ages, which could improve the understanding of disease heterogeneity and has implications for the design of future studies.

Fine-mapping, trans-ancestral and genomic analyses identify causal variants, cells, genes and drug targets for type 1 diabetes

We report the largest and most diverse genetic study of type 1 diabetes (T1D) to date (61,427 participants), yielding 78 genome-wide-significant (P < 5 × 10-8) regions, including 36 that are new. We define credible sets of T1D-associated variants and show that they are enriched in immune-cell accessible chromatin, particularly CD4+ effector T cells. Using chromatin-accessibility profiling of CD4+ T cells from 115 individuals, we map chromatin-accessibility quantitative trait loci and identify five regions where T1D risk variants co-localize with chromatin-accessibility quantitative trait loci. We highlight rs72928038 in BACH2 as a candidate causal T1D variant leading to decreased enhancer accessibility and BACH2 expression in T cells. Finally, we prioritize potential drug targets by integrating genetic evidence, functional genomic maps and immune protein-protein interactions, identifying 12 genes implicated in T1D that have been targeted in clinical trials for autoimmune diseases. These findings provide an expanded genomic landscape for T1D.

Differences in Maturation Status and Immune Phenotypes of Circulating Helios+ and Helios- Tregs and Their Disrupted Correlations With Monocyte Subsets in Autoantibody-Positive T1D Individuals

CD4 Tregs are involved in the regulation of various autoimmune diseases but believed to be highly heterogeneous. Studies have indicated that Helios controls a distinct subset of functional Tregs. However, the immunological changes in circulating Helios⁺ and Helios⁻ Tregs are not fully explored in type 1 diabetes (T1D). Here, we elucidated the differences in maturation status and immune regulatory phenotypes of Helios⁺ and Helios⁻ Tregs and their correlations with monocyte subsets in T1D individuals. As CD25^−/low FOXP3⁺ Tregs also represent a subset of functional Tregs, we defined Tregs as FOXP3⁺CD127^−/low and examined circulating Helios⁺ and Helios⁻ Treg subpopulations in 68 autoantibody-positive T1D individuals and 68 age-matched healthy controls. We found that expression of both FOXP3 and CTLA4 diminished in Helios⁻ Tregs, while the proportion of CD25^−/low Tregs increased in Helios⁺ Tregs of T1D individuals. Although the frequencies of neither Helios⁺ nor Helios⁻ Tregs were affected by investigated T1D genetic risk loci, Helios⁺ Tregs correlated with age at T1D diagnosis negatively and disease duration positively. Moreover, the negative correlation between central and effector memory proportions of Helios⁺ Tregs in healthy controls was disrupted in T1D individuals. Finally, regulatory non-classical and intermediate monocytes also decreased in T1D individuals, and positive correlations between these regulatory monocytes and Helios⁺/Helios⁻ Treg subsets in healthy controls disappeared in T1D individuals. In conclusion, we demonstrated the alternations in maturation status and immune phenotypes in Helios⁺ and Helios⁻ Treg subsets and revealed the missing association between these Treg subsets and monocyte subsets in T1D individuals, which might point out another option for elucidating T1D mechanisms.

Assessment of differentially methylated loci in individuals with end-stage kidney disease attributed to diabetic kidney disease: an exploratory study

BACKGROUND

A subset of individuals with type 1 diabetes mellitus (T1DM) are predisposed to developing diabetic kidney disease (DKD), the most common cause globally of end-stage kidney disease (ESKD). Emerging evidence suggests epigenetic changes in DNA methylation may have a causal role in both T1DM and DKD. The aim of this exploratory investigation was to assess differences in blood-derived DNA methylation patterns between individuals with T1DM-ESKD and individuals with long-duration T1DM but no evidence of kidney disease upon repeated testing to identify potential blood-based biomarkers. Blood-derived DNA from individuals (107 cases, 253 controls and 14 experimental controls) were bisulphite treated before DNA methylation patterns from both groups were generated and analysed using Illumina's Infinium MethylationEPIC BeadChip arrays (n = 862,927 sites). Differentially methylated CpG sites (dmCpGs) were identified (false discovery rate adjusted p ≤ × 10^-8 and fold change ± 2) by comparing methylation levels between ESKD cases and T1DM controls at single site resolution. Gene annotation and functionality was investigated to enrich and rank methylated regions associated with ESKD in T1DM.

RESULTS

Top-ranked genes within which several dmCpGs were located and supported by functional data with methylation look-ups in other cohorts include: AFF3, ARID5B, CUX1, ELMO1, FKBP5, HDAC4, ITGAL, LY9, PIM1, RUNX3, SEPTIN9 and UPF3A. Top-ranked enrichment pathways included pathways in cancer, TGF-β signalling and Th17 cell differentiation.

CONCLUSIONS

Epigenetic alterations provide a dynamic link between an individual's genetic background and their environmental exposures. This robust evaluation of DNA methylation in carefully phenotyped individuals has identified biomarkers associated with ESKD, revealing several genes and implicated key pathways associated with ESKD in individuals with T1DM.

A deep learning method for HLA imputation and trans-ethnic MHC fine-mapping of type 1 diabetes

Conventional human leukocyte antigen (HLA) imputation methods drop their performance for infrequent alleles, which is one of the factors that reduce the reliability of trans-ethnic major histocompatibility complex (MHC) fine-mapping due to inter-ethnic heterogeneity in allele frequency spectra. We develop DEEP*HLA, a deep learning method for imputing HLA genotypes. Through validation using the Japanese and European HLA reference panels (n = 1,118 and 5,122), DEEP*HLA achieves the highest accuracies with significant superiority for low-frequency and rare alleles. DEEP*HLA is less dependent on distance-dependent linkage disequilibrium decay of the target alleles and might capture the complicated region-wide information. We apply DEEP*HLA to type 1 diabetes GWAS data from BioBank Japan (n = 62,387) and UK Biobank (n = 354,459), and successfully disentangle independently associated class I and II HLA variants with shared risk among diverse populations (the top signal at amino acid position 71 of HLA-DRβ1; P = 7.5 × 10^-120). Our study illustrates the value of deep learning in genotype imputation and trans-ethnic MHC fine-mapping.

The association of HLA-DP loci with autoimmune diabetes in Chinese

AIMS

To determine if HLA-DP loci independently contribute to classic type 1 diabetes (T1D) of all ages, childhood-onset T1D and latent autoimmune diabetes in adults (LADA) among Chinese Han population.

METHODS

A total of 518 patients with classic T1D (Among them 180 participants manifested T1D between 1 and 14 years), 519 patients with LADA and 527 normal controls were genotyped for both HLA-DPA1 and -DPB1 loci. The frequencies of DP alleles and haplotypes in patients were directly compared to those in controls, followed by adjustment for linkage disequilibrium (LD) with DR-DQ haplotypes.

RESULTS

In the direct comparison, DPA1*01:03, DPB1*04:01 and DPA1*01:03-DPB1*04:01 showed disease-predisposing effects in both the overall T1D group and the childhood-onset T1D group mainly due to their conjunction with the known susceptible DR3 haplotype. Conditioning on DR-DQ haplotypes, only DPA1*02:02-DPB1*02:02 significantly increased T1D risk among those diagnosed during childhood (OR = 2.02, 95% CI = 1.35-3.01). Whether or not adjusted for LD, no statistically significant HLA-DP association could be observed for LADA.

CONCLUSION

HLA-DP is implicated in the pathogenesis of childhood-onset T1D in Chinese, independent of the predominant DR-DQ loci and might serve as additional markers in genetic models for the recognition of those genetically at-risk individuals.

Decreased serum fibroblast growth factor 19 level is a risk factor for type 1 diabetes

Background

Increasing evidence suggests that fibroblast growth factor 19 (FGF19) is a regulator of glucose metabolism and may provide a new therapeutic target for type 1 diabetes (T1D). However, the clinical relevance of FGF19 in T1D remains unclear. In this study, we examined the relationship between the serum FGF19 concentration and T1D.

Methods

This study included 81 newly diagnosed T1D patients and 80 sex- and age-matched healthy controls. The correlation between the FGF19 concentration and clinical characteristics of T1D patients and healthy controls was investigated. Logistic regression analysis was performed to determine whether levels of FGF19 were independently associated with T1D.

Results

The fasting serum FGF19 levels in the T1D group were significantly lower than those in the control group [159.9 (100.0–272.7) vs. 205.0 (126.9–307.9) pg/mL, P=0.008]. In all subjects, serum FGF19 levels were negatively correlated with fasting blood glucose (FBG) (r=−0.192, P=0.015). In the control group, serum FGF19 levels were positively correlated with total cholesterol (TC) (r=0.338, P=0.002) and low-density lipoprotein cholesterol (LDL-c) (r=0.300, P=0.007). In addition to sex and body mass index (BMI), FGF19 was an independent impact factor for T1D [odds ratio (OR) =0.541, P=0.023; adjusted for sex, age, BMI, presence of hypertension, and presence of dyslipidemia].

Conclusions

Low serum FGF19 level is associated with T1D, which could serve as a risk factor for T1D.

Risk for Coexistent Autoimmune Diseases in Familial and Sporadic Type 1 Diabetes is Related to Age at Diabetes Onset

OBJECTIVE

Type 1 diabetes (T1D) is frequently associated with other autoimmune diseases (AIDs). Although most of T1D patients are sporadic cases (S-T1D), 10% to 15% have a familial form (F-T1D) involving 2 or more first-degree relatives. This study evaluated the effect of T1D family aggregation and age onset on AIDs occurrence.

METHODS

In this observational, cross-sectional, case-control, single center study, we enrolled 115 F-T1D and 115 S-T1D patients matched for gender, age, T1D age onset, and duration. With respect to T1D age onset (before or after 18 years), both groups were further subdivided into young- or adult-onset F-T1D and young- or adult-onset S-T1D. The presence of organ-specific antibodies and/or overt AIDs was evaluated.

RESULTS

The F-T1D group had a higher percentage of AIDs (29.8% vs 18.4%, P = .04) and a significant earlier onset of AIDs at Cox regression analysis (P = .04) than the S-T1D group. Based on multivariate analysis, the adult-onset F-T1D subgroup had the highest prevalence of both additional organ-specific antibodies (60.5%) and overt AIDs (34.9%), whereas the adult S-T1D subgroup was the least frequently involved (29.1% and 12.7%, respectively). In F-T1D patients, offsprings develop T1D and AIDs earlier than their parents do.

CONCLUSIONS

In T1D patients, familial aggregation and adult-onset of T1D increase the risk for coexistent AIDs. These clinical predictors could guide clinicians to address T1D patients for the screening of T1D-related AIDs.

The clinical consequences of heterogeneity within and between different diabetes types

Advances in molecular methods and the ability to share large population-based datasets are uncovering heterogeneity within diabetes types, and some commonalities between types. Within type 1 diabetes, endotypes have been discovered based on demographic (e.g. age at diagnosis, race/ethnicity), genetic, immunological, histopathological, metabolic and/or clinical course characteristics, with implications for disease prediction, prevention, diagnosis and treatment. In type 2 diabetes, the relative contributions of insulin resistance and beta cell dysfunction are heterogeneous and relate to demographics, genetics and clinical characteristics, with substantial interaction from environmental exposures. Investigators have proposed approaches that vary from simple to complex in combining these data to identify type 2 diabetes clusters relevant to prognosis and treatment. Advances in pharmacogenetics and pharmacodynamics are also improving treatment. Monogenic diabetes is a prime example of how understanding heterogeneity within diabetes types can lead to precision medicine, since phenotype and treatment are affected by which gene is mutated. Heterogeneity also blurs the classic distinctions between diabetes types, and has led to the definition of additional categories, such as latent autoimmune diabetes in adults, type 1.5 diabetes and ketosis-prone diabetes. Furthermore, monogenic diabetes shares many features with type 1 and type 2 diabetes, which make diagnosis difficult. These challenges to the current classification framework in adult and paediatric diabetes require new approaches. The 'palette model' and the 'threshold hypothesis' can be combined to help explain the heterogeneity within and between diabetes types. Leveraging such approaches for therapeutic benefit will be an important next step for precision medicine in diabetes. Graphical abstract.

Type 1 diabetes in Africa: an immunogenetic study in the Amhara of North-West Ethiopia

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.

Management of Latent Autoimmune Diabetes in Adults: A Consensus Statement From an International Expert Panel

A substantial proportion of patients with adult-onset diabetes share features of both type 1 diabetes (T1D) and type 2 diabetes (T2D). These individuals, at diagnosis, clinically resemble T2D patients by not requiring insulin treatment, yet they have immunogenetic markers associated with T1D. Such a slowly evolving form of autoimmune diabetes, described as latent autoimmune diabetes of adults (LADA), accounts for 2-12% of all patients with adult-onset diabetes, though they show considerable variability according to their demographics and mode of ascertainment. While therapeutic strategies aim for metabolic control and preservation of residual insulin secretory capacity, endotype heterogeneity within LADA implies a personalized approach to treatment. Faced with a paucity of large-scale clinical trials in LADA, an expert panel reviewed data and delineated one therapeutic approach. Building on the 2020 American Diabetes Association (ADA)/European Association for the Study of Diabetes (EASD) consensus for T2D and heterogeneity within autoimmune diabetes, we propose "deviations" for LADA from those guidelines. Within LADA, C-peptide values, proxy for β-cell function, drive therapeutic decisions. Three broad categories of random C-peptide levels were introduced by the panel: 1) C-peptide levels <0.3 nmol/L: a multiple-insulin regimen recommended as for T1D; 2) C-peptide values ≥0.3 and ≤0.7 nmol/L: defined by the panel as a "gray area" in which a modified ADA/EASD algorithm for T2D is recommended; consider insulin in combination with other therapies to modulate β-cell failure and limit diabetic complications; 3) C-peptide values >0.7 nmol/L: suggests a modified ADA/EASD algorithm as for T2D but allowing for the potentially progressive nature of LADA by monitoring C-peptide to adjust treatment. The panel concluded by advising general screening for LADA in newly diagnosed non-insulin-requiring diabetes and, importantly, that large randomized clinical trials are warranted.

Association Study of Genetic Variants in Autophagy Pathway and Risk of Non-syndromic Cleft Lip With or Without Cleft Palate

Although genetic variants in autophagy pathway genes were associated with the risk of oral cancers and early development in embryos, their associations with non-syndromic cleft lip with or without cleft palate (NSCL/P) risk remained unclear. A two-stage case-control study (2,027 NSCL/P cases and 1,843 controls) was performed to investigate the associations between single nucleotide polymorphisms (SNPs) in 23 autophagy pathway genes and NSCL/P susceptibility. The logistic regression model was used to calculate effects of SNPs on NSCL/P susceptibility. Gene-based analysis was performed via the sequence kernel association test (SKAT) and multi-marker analysis of genomic annotation (MAGMA) methods. Expression quantitative trait loci (eQTL) analysis was conducted using NSCL/P lip tissue samples. Gene expression during embryonic development was evaluated using RNA-Seq. Functional roles were explored by luciferase activity assay, cell apoptosis, proliferation, and cycle in vitro. Rs2301104 in HIF1A was significantly associated with NSCL/P susceptibility in the combined analysis (OR: 1.29, 95% CI: 1.09-1.29, P = 3.39 × 10^-03), and showed strong evidence of association heterogeneity (P = 9.06 × 10^-03) with obvious association in the female (OR: 1.80; 95% CI: 1.32-2.45; P = 1.79 × 10^-04). The G allele of rs2301104 was associated with enhanced transcription activity and high expression of HIF1A compared with that of C allele. Moreover, rs2301104 exhibited an eQTL effect for HIF1A with its GC/CC genotypes associated with decreased HIF1A expression compared with those with GG genotypes (P = 3.1 × 10^-2). Knockdown of HIF1A induced cell apoptosis and inhibited cell proliferation in human embryonic palate mesenchyme (HEPM) and human oral epithelium cells (HOEC). This study demonstrated that rs2301104 in autophagy pathway gene HIF1A was associated with susceptibility of NSCL/P.

Identification of genetic features associated with fine particulate matter (PM2.5) modulated DNA damage using improved random forest analysis

Recent studies have found multiple single nucleotide variants (SNVs) associated with DNA damage. However, previous association analysis may ignore the potential interaction effects between SNVs. Therefore, we used an improved random forest (RF) analysis to identify the SNVs related to personal DNA damage in exon-focused genome-wide association study (GWAS). A total of 301 subjects from three independent centers (Zhuhai, Wuhan, and Tianjin) were retained for analysis. An improved RF procedure was used to systematically screen key SNVs associated with DNA damage. Furthermore, we used genetic risk score (GRS) and mediation analysis to investigate the integrative effect and potential mechanism of these genetic variants on DNA damage. Besides, gene set enrichment analysis was conducted to identify the pathways enriched by key SNVs using the Data-driven Expression Prioritized Integration for Complex Traits (DEPICT). Finally, a set of 24 SNVs with the lowest mean square errors (MSE) were identified by improved RF analysis. Both weighted and unweighted GRSs were associated with increased DNA damage levels (P_weight < 0.001 and P_unweight < 0.001). Gene set enrichment analysis indicated that these loci were significantly enriched in several biological features associated with DNA damage. These findings suggested the role of SNVs in modifying DNA damage levels. It may be convincing that this improved RF analysis can effectively identify SNVs associated with DNA damage levels.

Analysis of potential hub genes involved in the pathogenesis of Chinese type 1 diabetic patients

Background

Type 1 diabetes is an autoimmune disease strongly related to genetic factors. Although studies on T1D susceptibility genes have achieved great progress, the molecular mechanism of T1D remains to be explained.

Methods

To explore the underlying mechanisms of T1D, bioinformatic analysis based on a microarray database was used to determine the key biomarkers of T1D as well as their biofunctions and interactions. The microarray database GSE55100 was downloaded from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were processed by packages in R Software. The database for Annotation, Visualization, and Integrated Discovery (DAVID, version 6.8) was used to conduct gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. The protein-protein interaction network was analyzed with the Search Tool for the Retrieval of Interacting Genes (STRING), and the module analysis was performed using Cytoscape.

Results

Seventy-eight DEGs and 13 hub genes were identified. The biofunctions and pathways of these DEGs were enriched in immune response, extracellular exosome, cytokine activity and antigen processing and presentation. Thirteen DEGs with MCODE score ≥2 were selected as hub genes including MMP9, ARG1, CAMP, CHI3L1, CRISP3, SLPI, LCN2, PGLYRP1, LTF, RETN, CEACAM1, CEACAM8 and MS4A3.

Conclusions

The identification and analyses of the DEGs and hub genes from database GSE55100 provide novel prospectives of the pathogenesis of T1D.