Longitudinal Pattern of First-Phase Insulin Response Is Associated With Genetic Variants Outside the Class II HLA Region in Children With Multiple Autoantibodies

Integrating multi-omics data to analyze the potential pathogenic mechanism of CTSH gene involved in type 1 diabetes in the exocrine pancreas

Type 1 diabetes (T1D) is an autoimmune disease caused by the destruction of insulin-producing pancreatic islet beta cells. Despite significant advancements, the precise pathogenesis of the disease remains unknown. This work integrated data from expression quantitative trait locus (eQTL) studies with Genome wide association study (GWAS) summary data of T1D and single-cell transcriptome data to investigate the potential pathogenic mechanisms of the CTSH gene involved in T1D in exocrine pancreas. Using the summary data-based Mendelian randomization (SMR) approach, we obtained four potential causative genes associated with T1D: BTN3A2, PGAP3, SMARCE1 and CTSH. To further investigate these genes'roles in T1D development, we validated them using a scRNA-seq dataset from pancreatic tissues of both T1D patients and healthy controls. The analysis showed a significantly high expression of the CTSH gene in T1D acinar cells, whereas the other three genes showed no significant changes in the scRNA-seq data. Moreover, single-cell WGCNA analysis revealed the strongest positive correlation between the module containing CTSH and T1D. In addition, we found cellular ligand-receptor interactions between the acinar cells and different cell types, especially ductal cells. Finally, based on functional enrichment analysis, we hypothesized that the CTSH gene in the exocrine pancreas enhances the antiviral response, leading to the overexpression of pro-inflammatory cytokines and the development of an inflammatory microenvironment. This process promotes β cells injury and ultimately the development of T1D. Our findings offer insights into the underlying pathogenic mechanisms of T1D.

Genetic and Epigenetic Aspects of Type 1 Diabetes Mellitus: Modern View on the Problem

Omics technologies accumulated an enormous amount of data that advanced knowledge about the molecular pathogenesis of type 1 diabetes mellitus and identified a number of fundamental problems focused on the transition to personalized diabetology in the future. Among them, the most significant are the following: (1) clinical and genetic heterogeneity of type 1 diabetes mellitus; (2) the prognostic significance of DNA markers beyond the HLA genes; (3) assessment of the contribution of a large number of DNA markers to the polygenic risk of disease progress; (4) the existence of ethnic population differences in the distribution of frequencies of risk alleles and genotypes; (5) the infancy of epigenetic research into type 1 diabetes mellitus. Disclosure of these issues is one of the priorities of fundamental diabetology and practical healthcare. The purpose of this review is the systemization of the results of modern molecular genetic, transcriptomic, and epigenetic investigations of type 1 diabetes mellitus in general, as well as its individual forms. The paper summarizes data on the role of risk HLA haplotypes and a number of other candidate genes and loci, identified through genome-wide association studies, in the development of this disease and in alterations in T cell signaling. In addition, this review assesses the contribution of differential DNA methylation and the role of microRNAs in the formation of the molecular pathogenesis of type 1 diabetes mellitus, as well as discusses the most currently central trends in the context of early diagnosis of type 1 diabetes mellitus.

Quantifying beta cell function in the preclinical stages of type 1 diabetes

Clinically symptomatic type 1 diabetes (stage 3 type 1 diabetes) is preceded by a pre-symptomatic phase, characterised by progressive loss of functional beta cell mass after the onset of islet autoimmunity, with (stage 2) or without (stage 1) measurable changes in glucose profile during an OGTT. Identifying metabolic tests that can longitudinally track changes in beta cell function is of pivotal importance to track disease progression and measure the effect of disease-modifying interventions. In this review we describe the metabolic changes that occur in the early pre-symptomatic stages of type 1 diabetes with respect to both insulin secretion and insulin sensitivity, as well as the measurable outcomes that can be derived from the available tests. We also discuss the use of metabolic modelling to identify insulin secretion and sensitivity, and the measurable changes during dynamic tests such as the OGTT. Finally, we review the role of risk indices and minimally invasive measures such as those derived from the use of continuous glucose monitoring.

Heterogeneity and endotypes in type 1 diabetes mellitus

Despite major advances over the past decade, prevention and treatment of type 1 diabetes mellitus (T1DM) remain suboptimal, with large and unexplained variations in individual responses to interventions. The current classification schema for diabetes mellitus does not capture the complexity of this disease or guide clinical management effectively. One of the approaches to achieve the goal of applying precision medicine in diabetes mellitus is to identify endotypes (that is, well-defined subtypes) of the disease each of which has a distinct aetiopathogenesis that might be amenable to specific interventions. Here, we describe epidemiological, clinical, genetic, immunological, histological and metabolic differences within T1DM that, together, suggest heterogeneity in its aetiology and pathogenesis. We then present the emerging endotypes and their impact on T1DM prediction, prevention and treatment.

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.

Cathepsin H: molecular characteristics and clues to function and mechanism

Cathepsin H (CatH) is a lysosomal cysteine protease with a unique aminopeptidase activity that is extensively expressed in the lung, pancreas, thymus, kidney, liver, skin, and brain. Owing to its specific enzymatic activity, CatH has critical effects on the regulation of biological behaviours of cancer cells and pathological processes in brain diseases. Moreover, a neutral pH level is optimal for CatH activity, so it is expected to be active in the extra-lysosomal and extracellular space. In the present review, we describe the expression, maturation, and enzymatic properties of CatH, and summarize the available experimental evidence that mechanistically links CatH to various physiological and pathological processes. Finally, we discuss the challenges and potentials of CatH inhibitors in CatH-induced disease therapy.

Non-HLA Gene Polymorphisms in the Pathogenesis of Type 1 Diabetes: Phase and Endotype Specific Effects

The non-HLA loci conferring susceptibility to type 1 diabetes determine approximately half of the genetic disease risk, and several of them have been shown to affect immune-cell or pancreatic β-cell functions. A number of these loci have shown associations with the appearance of autoantibodies or with progression from seroconversion to clinical type 1 diabetes. In the current study, we have re-analyzed 21 of our loci with prior association evidence using an expanded DIPP follow-up cohort of 976 autoantibody positive cases and 1,910 matched controls. Survival analysis using Cox regression was applied for time periods from birth to seroconversion and from seroconversion to type 1 diabetes. The appearance of autoantibodies was also analyzed in endotypes, which are defined by the first appearing autoantibody, either IAA or GADA. Analyzing the time period from birth to seroconversion, we were able to replicate our previous association findings at PTPN22, INS, and NRP1. Novel findings included associations with ERBB3, UBASH3A, PTPN2, and FUT2. In the time period from seroconversion to clinical type 1 diabetes, prior associations with PTPN2, CD226, and PTPN22 were replicated, and a novel association with STAT4 was observed. Analyzing the appearance of autoantibodies in endotypes, the PTPN22 association was specific for IAA-first. In the progression phase, STAT4 was specific for IAA-first and ERBB3 to GADA-first. In conclusion, our results further the knowledge of the function of non-HLA risk polymorphisms in detailing endotype specificity and timing of disease development.

Heterogeneity of beta-cell function in subjects with multiple islet autoantibodies in the TEDDY family prevention study - TEFA

BACKGROUND

Individuals with multiple islet autoantibodies are at increased risk for clinical type 1 diabetes and may proceed gradually from stage to stage complicating the recruitment to secondary prevention studies. We evaluated multiple islet autoantibody positive subjects before randomisation for a clinical trial 1 month apart for beta-cell function, glucose metabolism and continuous glucose monitoring (CGM). We hypothesized that the number and type of islet autoantibodies in combination with different measures of glucose metabolism including fasting glucose, HbA1c, oral glucose tolerance test (OGTT), intra venous glucose tolerance test (IvGTT) and CGM allows for more precise staging of autoimmune type 1 diabetes than the number of islet autoantibodies alone.

METHODS

Subjects (n = 57) at 2-50 years of age, positive for two or more islet autoantibodies were assessed by fasting plasma insulin, glucose, HbA1c as well as First Phase Insulin Response (FPIR) in IvGTT, followed 1 month later by OGTT, and 1 week of CGM (n = 24).

RESULTS

Autoantibodies against GAD65 (GADA; n = 52), ZnT8 (ZnT8A; n = 40), IA-2 (IA-2A; n = 38) and insulin (IAA; n = 28) were present in 9 different combinations of 2-4 autoantibodies. Fasting glucose and HbA1c did not differ between the two visits. The estimate of the linear relationship between log2-transformed FPIR as the outcome and log2-transformed area under the OGTT glucose curve (AUC) as the predictor, adjusting for age and sex was - 1.88 (- 2.71, - 1.05) p = 3.49 × 10-5. The direction of the estimates for all glucose metabolism measures was positive except for FPIR, which was negative. FPIR was associated with higher blood glucose. Both the median and the spread of the CGM glucose data were significantly associated with higher glucose values based on OGTT, higher HbA1c, and lower FPIR. There was no association between glucose metabolism, autoantibody number and type except that there was an indication that the presence of at least one of ZnT8(Q/R/W) A was associated with a lower log2-transformed FPIR (- 0.80 (- 1.58, - 0.02), p = 0.046).

CONCLUSIONS

The sole use of two or more islet autoantibodies as inclusion criterion for Stage 1 diabetes in prevention trials is unsatisfactory. Staging type 1 diabetes needs to take the heterogeneity in beta-cell function and glucose metabolism into account.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT02605148 , November 16, 2015.

The β Cell in Diabetes: Integrating Biomarkers With Functional Measures

The pathogenesis of hyperglycemia observed in most forms of diabetes is intimately tied to the islet β cell. Impairments in propeptide processing and secretory function, along with the loss of these vital cells, is demonstrable not only in those in whom the diagnosis is established but typically also in individuals who are at increased risk of developing the disease. Biomarkers are used to inform on the state of a biological process, pathological condition, or response to an intervention and are increasingly being used for predicting, diagnosing, and prognosticating disease. They are also proving to be of use in the different forms of diabetes in both research and clinical settings. This review focuses on the β cell, addressing the potential utility of genetic markers, circulating molecules, immune cell phenotyping, and imaging approaches as biomarkers of cellular function and loss of this critical cell. Further, we consider how these biomarkers complement the more long-established, dynamic, and often complex measurements of β-cell secretory function that themselves could be considered biomarkers.

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.

De-coding genetic risk variants in type 1 diabetes

The conceptual basis for a genetic predisposition underlying the risk for developing type 1 diabetes (T1D) predates modern human molecular genetics. Over half of the genetic risk has been attributed to the human leukocyte antigen (HLA) class II gene region and to the insulin (INS) gene locus - both thought to confer direction of autoreactivity and tissue specificity. Notwithstanding, questions still remain regarding the functional contributions of a vast array of minor polygenic risk variants scattered throughout the genome that likely influence disease heterogeneity and clinical outcomes. Herein, we summarize the available literature related to the T1D-associated coding variants defined at the time of this review, for the genes PTPN22, IFIH1, SH2B3, CD226, TYK2, FUT2, SIRPG, CTLA4, CTSH and UBASH3A. Data from genotype-selected human cohorts are summarized, and studies from the non-obese diabetic (NOD) mouse are presented to describe the functional impact of these variants in relation to innate and adaptive immunity as well as to β-cell fragility, with expression profiles in tissues and peripheral blood highlighted. The contribution of each variant to progression through T1D staging, including environmental interactions, are discussed with consideration of how their respective protein products may serve as attractive targets for precision medicine-based therapeutics to prevent or suspend the development of T1D.

Beta cell function in participants with single or multiple islet autoantibodies at baseline in the TEDDY Family Prevention Study: TEFA

Aim

The aim of the present study was to assess beta cell function based on an oral glucose tolerance test (OGTT) in participants with single islet autoantibody or an intravenous glucose tolerance test (IvGTT) in participants with multiple islet autoantibodies.

Materials and methods

Healthy participants in Sweden and Finland, between 2 and 49.99 years of age previously identified as positive for a single (n = 30) autoantibody to either insulin, glutamic acid decarboxylase, islet antigen-2, zinc transporter 8 or islet cell antibodies or multiple autoantibodies (n = 46), were included. Participants positive for a single autoantibody underwent a 6-point OGTT while participants positive for multiple autoantibodies underwent an IvGTT. Glucose, insulin and C-peptide were measured from OGTT and IvGTT samples.

Results

All participants positive for a single autoantibody had a normal glucose tolerance test with 120 minutes glucose below 7.70 mmol/L and HbA1c values within the normal range (<42 mmol/mol). Insulin responses to the glucose challenge on OGTT ranged between 13.0 and 143 mIU/L after 120 minutes with C-peptide values between 0.74 and 4.60 nmol/L. In Swedish participants, the first-phase insulin response (FPIR) on IvGTT was lower in those positive for three or more autoantibodies (n = 13; median 83.0 mIU/L; range 20.0-343) compared to those with two autoantibodies (n = 15; median 146 mIU/L; range 19.0-545; P = .0330).

Conclusion

Participants positive for a single autoantibody appeared to have a normal beta cell function. Participants positive for three or more autoantibodies had a lower FPIR as compared to participants with two autoantibodies, supporting the view that their beta cell function had deteriorated.

The β-Cell Genomic Landscape in T1D: Implications for Disease Pathogenesis

PURPOSE OF REVIEW

Type 1 diabetes (T1D) develops as a consequence of a combination of genetic predisposition and environmental factors. Combined, these events trigger an autoimmune disease that results in progressive loss of pancreatic β cells, leading to insulin deficiency. This article reviews the current knowledge on the genetics of T1D with a specific focus on genetic variation in pancreatic islet regulatory networks and its implication to T1D risk and disease development.

RECENT FINDINGS

Accumulating evidence suggest an active role of β cells in T1D pathogenesis. Based on such observation several studies aimed in mapping T1D risk variants acting at the β cell level. Such studies unravel T1D risk loci shared with type 2 diabetes (T2D) and T1D risk variants potentially interfering with β-cell responses to external stimuli. The characterization of regulatory genomics maps of disease-relevant states and cell types can be used to elucidate the mechanistic role of β cells in the pathogenesis of T1D.

Genetic and environmental factors regulate the type 1 diabetes gene CTSH via differential DNA methylation

Cathepsin H (CTSH) is a type 1 diabetes (T1D) risk gene; large-scale genetic and epidemiological studies found that T1D genetic risk correlates with high CTSH expression, rapid decline of beta-cell function, and early onset T1D. Counterintuitively, transcriptional downregulation of CTSH by proinflammatory cytokines has been shown to promote beta-cell apoptosis. Here, we potentially explain these observed contrasting effects, describing a new mechanism where proinflammatory cytokines and T1D genetic risk variants regulate CTSH transcription via differential DNA methylation. We show that, in human islets, CTSH downregulation by the proinflammatory cytokine cocktail interleukin 1β + tumor necrosis factor α + interferon γ was coupled with DNA hypermethylation in an open chromatin region in CTSH intron 1. A luciferase assay in human embryonic kidney 293 cells revealed that methylation of three key cytosine-phosphate-guanine dinucleotide (CpG) residues in intron 1 was responsible for the reduction of promoter activity. We further found that cytokine-induced intron 1 hypermethylation is caused by lowered Tet1/3 activities, suggesting that attenuated active demethylation lowered CTSH transcription. Importantly, individuals who carry the T1D risk variant showed lower methylation variability at the intron 1 CpG residues, presumably making them less sensitive to cytokines, whereas individuals who carry the protective variant showed higher methylation variability, presumably making them more sensitive to cytokines and implying differential responses to environment between the two patient populations. These findings suggest that genetic and environmental influences on a T1D locus are mediated by differential variability and mean of DNA methylation.

The role of beta-cell dysfunction in early type 1 diabetes

PURPOSE OF REVIEW

Emerging data have suggested that β-cell dysfunction may exacerbate the development and progression of type 1 diabetes (T1D). In this review, we highlight clinical and preclinical studies suggesting a role for β-cell dysfunction during the evolution of T1D and suggest agents that may promote β-cell health in T1D.

RECENT FINDINGS

Metabolic abnormalities exist years before development of hyperglycemia and exhibit a reproducible pattern reflecting progressive deterioration of β-cell function and increases in β-cell stress and death. Preclinical studies indicate that T1D may be prevented by modification of pathways impacting intrinsic β-cell stress and antigen presentation. Recent findings suggest that differences in metabolic phenotypes and β-cell stress may reflect differing endotypes of T1D. Multiple pathways representing potential drug targets have been identified, but most remain to be tested in human populations with preclinical disease.

SUMMARY

This cumulative body of work shows clear evidence that β-cell stress, dysfunction, and death are harbingers of impending T1D and likely contribute to progression of disease and insulin deficiency. Treatment with agents targeting β-cell health could augment interventions with immunomodulatory therapies but will need to be tested in intervention studies with endpoints carefully designed to capture changes in β-cell function and health.

Pancreatic β-cells in type 1 and type 2 diabetes mellitus: different pathways to failure

Loss of functional β-cell mass is the key mechanism leading to the two main forms of diabetes mellitus - type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM). Understanding the mechanisms behind β-cell failure is critical to prevent or revert disease. Basic pathogenic differences exist in the two forms of diabetes mellitus; T1DM is immune mediated and T2DM is mediated by metabolic mechanisms. These mechanisms differentially affect early β-cell dysfunction and eventual fate. Over the past decade, major advances have been made in the field, mostly delivered by studies on β-cells in human disease. These advances include studies of islet morphology and human β-cell gene expression in T1DM and T2DM, the identification and characterization of the role of T1DM and T2DM candidate genes at the β-cell level and the endoplasmic reticulum stress signalling that contributes to β-cell failure in T1DM (mostly IRE1 driven) and T2DM (mostly PERK-eIF2α dependent). Here, we review these new findings, focusing on studies performed on human β-cells or on samples obtained from patients with diabetes mellitus.