Fine mapping of type 1 diabetes susceptibility loci and evidence for colocalization of causal variants with lymphoid gene enhancers

Decoding the immune dance: Unraveling the interplay between beta cells and type 1 diabetes

BACKGROUND

Type 1 diabetes (T1D) is an autoimmune disease characterized by the specific destruction of insulin-producing beta cells in the pancreas by the immune system, including CD4 cells which orchestrate the attack and CD8 cells which directly destroy the beta cells, resulting in the loss of glucose homeostasis.

SCOPE OF REVIEW

This comprehensive document delves into the complex interplay between the immune system and beta cells, aiming to shed light on the mechanisms driving their destruction in T1D. Insights into the genetic predisposition, environmental triggers, and autoimmune responses provide a foundation for understanding the autoimmune attack on beta cells. From the role of viral infections as potential triggers to the inflammatory response of beta cells, an intricate puzzle starts to unfold. This exploration highlights the importance of beta cells in breaking immune tolerance and the factors contributing to their targeted destruction. Furthermore, it examines the potential role of autophagy and the impact of cytokine signaling on beta cell function and survival.

MAJOR CONCLUSIONS

This review collectively represents current research findings on T1D which offers valuable perspectives on novel therapeutic approaches for preserving beta cell mass, restoring immune tolerance, and ultimately preventing or halting the progression of T1D. By unraveling the complex dynamics between the immune system and beta cells, we inch closer to a comprehensive understanding of T1D pathogenesis, paving the way for more effective treatments and ultimately a cure.

A genome-wide association study identified PTPN2 as a population-specific susceptibility gene locus for primary biliary cholangitis

BACKGROUND AND AIMS

Previous genome-wide association studies (GWAS) have indicated the involvement of shared (population-nonspecific) and nonshared (population-specific) susceptibility genes in the pathogenesis of primary biliary cholangitis (PBC) among European and East-Asian populations. Although a meta-analysis of these distinct populations has recently identified more than 20 novel PBC susceptibility loci, analyses of population-specific genetic architecture are still needed for a more comprehensive search for genetic factors in PBC.

APPROACH AND RESULTS

Protein tyrosine phosphatase nonreceptor type 2 ( PTPN2) was identified as a novel PBC susceptibility gene locus through GWAS and subsequent genome-wide meta-analysis involving 2181 cases and 2699 controls from the Japanese population (GWAS-lead variant: rs8098858, p = 2.6 × 10 -8 ). In silico and in vitro functional analyses indicated that the risk allele of rs2292758, which is a primary functional variant, decreases PTPN2 expression by disrupting Sp1 binding to the PTPN2 promoter in T follicular helper cells and plasmacytoid dendritic cells. Infiltration of PTPN2-positive T-cells and plasmacytoid dendritic cells was confirmed in the portal area of the PBC liver by immunohistochemistry. Furthermore, transcriptomic analysis of PBC-liver samples indicated the presence of a compromised negative feedback loop in vivo between PTPN2 and IFNG in patients carrying the risk allele of rs2292758.

CONCLUSIONS

PTPN2 , a novel susceptibility gene for PBC in the Japanese population, may be involved in the pathogenesis of PBC through an insufficient negative feedback loop caused by the risk allele of rs2292758 in IFN-γ signaling. This suggests that PTPN2 could be a potential molecular target for PBC treatment.

Clinical glycoproteomics: methods and diseases

Glycoproteins, representing a significant proportion of posttranslational products, play pivotal roles in various biological processes, such as signal transduction and immune response. Abnormal glycosylation may lead to structural and functional changes of glycoprotein, which is closely related to the occurrence and development of various diseases. Consequently, exploring protein glycosylation can shed light on the mechanisms behind disease manifestation and pave the way for innovative diagnostic and therapeutic strategies. Nonetheless, the study of clinical glycoproteomics is fraught with challenges due to the low abundance and intricate structures of glycosylation. Recent advancements in mass spectrometry-based clinical glycoproteomics have improved our ability to identify abnormal glycoproteins in clinical samples. In this review, we aim to provide a comprehensive overview of the foundational principles and recent advancements in clinical glycoproteomic methodologies and applications. Furthermore, we discussed the typical characteristics, underlying functions, and mechanisms of glycoproteins in various diseases, such as brain diseases, cardiovascular diseases, cancers, kidney diseases, and metabolic diseases. Additionally, we highlighted potential avenues for future development in clinical glycoproteomics. These insights provided in this review will enhance the comprehension of clinical glycoproteomic methods and diseases and promote the elucidation of pathogenesis and the discovery of novel diagnostic biomarkers and therapeutic targets.

Whole Exome Sequencing in Children With Type 1 Diabetes Before Age 6 Years Reveals Insights Into Disease Heterogeneity

Aims: This study is aimed at comparing whole exome sequencing (WES) data with the clinical presentation in children with type 1 diabetes onset ≤ 5 years of age (EOT1D). Methods: WES was performed in 99 unrelated children with EOT1D with subsequent analysis to identify potentially deleterious rare variants in MODY genes. High-resolution HLA class II haplotyping, SNP genotyping, and T1D-genetic risk score (T1D-GRS) were also evaluated. Results: Eight of the ninety-nine EOT1D participants carried a potentially deleterious rare variant in a MODY gene. Rare variants affected five genes: GCK (n = 1), HNF1B (n = 2), HNF4A (n = 1), PDX1 (n = 2), and RFX6 (n = 2). At diagnosis, these children had a mean age of 3.0 years, a mean HbA1c of 10.5%, a detectable C-peptide in 5/8, and a positive islet autoantibody in 6/7. Children with MODY variants tend to exhibit a lower number of pancreatic autoantibodies and a lower fasting C-peptide compared to EOT1D without MODY rare variants. They also carried at least one high-risk DR3-DQ2 or DR4-DQ8 haplotype and exhibited a T1D-GRS similar to the other individuals in the EOT1D cohort, but higher than healthy controls. Conclusions: WES found potentially deleterious rare variants in MODY genes in 8.1% of EOT1D, occurring in the context of a T1D genetic background. Such genetic variants may contribute to disease precipitation by a β-cell dysfunction mechanism. This supports the concept of different endotypes of T1D, and WES at T1D onset may be a prerequisite for the implementation of precision therapies in children with autoimmune diabetes.

Genetic correlation between chronic sinusitis and autoimmune diseases

Objective

The association between autoimmune diseases and chronic rhinosinusitis in observational studies remains unclear. This study aimed to explore the genetic correlation between chronic rhinosinusitis and autoimmune diseases.

Methods

We employed Mendelian randomization (MR) analysis and linkage disequilibrium score regression (LDSC) to investigate causal relationships and genetic correlations between autoimmune phenotypes and chronic rhinosinusitis. Additionally, transcriptome-wide association (TWAS) analysis was conducted to identify the shared genes between the two conditions to demonstrate their relationship. The CRS GWAS (genome-wide association study) data and other autoimmune diseases were retrieved from ieuOpenGWAS (https://gwas.mrcieu.ac.uk/), the FinnGen alliance (https://r8.finngen.fi/), the UK Biobank (https://www.ukbiobank.ac.uk/), and the EBI database (https://www.ebi.ac.uk/).

Results

Utilizing a bivariate two-sample Mendelian randomization approach, our findings suggest a significant association of chronic rhinosinusitis with various autoimmune diseases, including allergic rhinitis (p = 9.55E-10, Odds Ratio [OR] = 2,711.019, 95% confidence interval [CI] = 261.83391-28,069.8), asthma (p = 1.81E-23, OR = 33.99643, 95%CI = 17.52439-65.95137), rheumatoid arthritis (p = 9.55E-10, OR = 1.115526, 95%CI = 1.0799484-1.1522758), hypothyroidism (p = 2.08828E-2, OR = 4.849254, 95%CI = 1.7154455-13.707962), and type 1 diabetes (p = 2.08828E-2, OR = 01.04849, 95%CI = 1.0162932-1.0817062). LDSC analysis revealed a genetic correlation between the positive autoimmune phenotypes mentioned above and chronic rhinosinusitis: AR (rg = 0.344724754, p = 3.94E-8), asthma (rg = 0.43703672, p = 1.86E-10), rheumatoid arthritis (rg = 0.27834931, p = 3.5376E-2), and hypothyroidism (rg = -0.213201473, p = 3.83093E-4). Utilizing the Transcriptome-Wide Association Studies (TWAS) approach, we identified several genes commonly associated with both chronic rhinosinusitis and autoimmune diseases. Genes such as TSLP/WDR36 (Chromosome 5, top SNP: rs1837253), ORMDL3 (Chromosome 13, top SNP: rs11557467), and IL1RL1/IL18R1 (Chromosome 2, top SNP: rs12905) exhibited a higher degree of consistency in their shared involvement across atopic dermatitis (AT), allergic rhinitis (AR), and chronic rhinosinusitis (CRS).

Conclusion

Current evidence suggests a genetic correlation between chronic rhinosinusitis and autoimmune diseases like allergic rhinitis, asthma, rheumatoid arthritis, hypothyroidism, and type 1 diabetes. Further research is required to elucidate the mechanisms underlying these associations.

Genetic association with autoimmune diseases identifies molecular mechanisms of coronary artery disease

Autoimmune patients have a significantly increased risk of developing coronary artery disease (CAD) compared to the general population. However, autoimmune patients often lack traditional risk factors for CAD and there is increasing recognition of inflammation in CAD development. In this study, we leveraged genome-wide association study (GWAS) data to understand whether there is a genetic relationship between CAD and autoimmunity. Statistical genetic comparison methods were used to identify correlated and causal SNPs between various autoimmune diseases and CAD. Pleiotropic SNPs were identified by cross-phenotype association analysis (CPASSOC) and overlap between GWAS. Causal SNPs were identified using Mendelian Randomization (MR) and Colocalization (COLOC). Using SNP-to-gene mapping, we additionally identified pleiotropic and causal genes and pathways associated between autoimmunity and CAD, which were contextualized by documentation of enrichment in individual cell types identified from coronary atherosclerotic plaques by single-cell RNA sequencing. These results provide insight into potential inflammatory therapeutic targets for CAD.

Glucose and Lipid Metabolism Disorders in Adults with Spinal Muscular Atrophy Type 3

BACKGROUND

Spinal muscular atrophy type 3 (juvenile SMA, Kugelberg-Welander disease) is a genetic disease caused by changes in the survival motor neuron 1 (SMN) gene. However, there is increasing evidence of metabolic abnormalities in SMA patients, such as altered fatty acid metabolism, impaired glucose tolerance, and defects in the functioning of muscle mitochondria. Given that data in the literature are scarce regarding this subject, the purpose of this study was to estimate the prevalence of glucose and lipid metabolism disorders in adult patients with SMA type 3.

METHODS

We conducted a cross-sectional study of 23 adult patients with SMA type 3 who underwent a comprehensive evaluation, including a physical examination, biochemical analysis, and an oral glucose tolerance test during 2020-2023.

RESULTS

At least one lipid abnormality was observed in 60.8% of patients. All four lipid parameters were atypical in 4.3% of patients, three lipid parameters were abnormal in 21.7% of patients, and two lipid parameters were altered in 8.7% patients. A total of 91.3% of SMA3 patients met the HOMA-IR criteria for insulin resistance, with 30.43% having impaired glucose tolerance. None of the patients met the criteria for a diagnosis of overt DM2.

CONCLUSIONS

The prevalence of dyslipidemia and altered glucose metabolism in our study sets apart the adult population with SMA3 from the general population, confirming a significant interplay between muscle, liver, and adipose tissue. Ensuring metabolic care for aging patients with SMA 3 is crucial, as they are vulnerable to metabolic derangements and cardiovascular risks.

Genetic evidence for efficacy of targeting IL-2, IL-6 and TYK2 signalling in the prevention of type 1 diabetes: a Mendelian randomisation study

AIMS/HYPOTHESIS

We aimed to investigate the genetic evidence that supports the repurposing of drugs already licensed or in clinical phases of development for prevention of type 1 diabetes.

METHODS

We obtained genome-wide association study summary statistics for the risk of type 1 diabetes, whole-blood gene expression and serum protein levels and investigated genetic polymorphisms near seven potential drug target genes. We used co-localisation to examine whether the same genetic variants that are associated with type 1 diabetes risk were also associated with the relevant drug target genetic proxies and used Mendelian randomisation to evaluate the direction and magnitude of the associations. Furthermore, we performed Mendelian randomisation analysis restricted to functional variants within the drug target genes.

RESULTS

Co-localisation revealed that the blood expression levels of IL2RA (encoding IL-2 receptor subunit α [IL2RA]), IL6R (encoding IL-6 receptor [IL6R]) and IL6ST (encoding IL-6 cytokine family signal transducer [IL6ST]) shared the same causal variant with type 1 diabetes liability near the corresponding genes (posterior probabilities 100%, 96.5% and 97.0%, respectively). The OR (95% CI) of type 1 diabetes per 1-SD increase in the genetically proxied gene expression of IL2RA, IL6R and IL6ST were 0.22 (0.17, 0.27), 1.98 (1.48, 2.65) and 1.90 (1.45, 2.48), respectively. Using missense variants, genetically proxied TYK2 (encoding tyrosine kinase 2) expression levels were associated with type 1 diabetes risk (OR 0.61 [95% CI 0.54, 0.69]).

CONCLUSIONS/INTERPRETATION

Our findings support the targeting of IL-2, IL-6 and TYK2 signalling in prevention of type 1 diabetes.

DATA AVAILABILITY

The analysis code is available at https://github.com/jkoskenniemi/T1DSCREEN , which also includes instructions on how to download the original GWAS summary statistics.

Enhancing genetic association power in endometriosis through unsupervised clustering of clinical subtypes identified from electronic health records

Endometriosis is a complex and heterogeneous condition affecting 10% of reproductive-age women, and yet, it often goes undiagnosed for several years. Limited observed heritability (7%) of large genetic association studies may be attributable to underlying heterogeneity of disease mechanisms. Therefore, we conducted this study to investigate genetic associations across sub-phenotypes of endometriosis. We performed unsupervised clustering of 4,078 women with endometriosis based on known endometriosis risk factors, symptoms, and concomitant conditions. The clusters were characterized by examining electronic health record (EHR) data and comprehensive chart reviews. We then performed genetic association for each cluster with 39 endometriosis-associated loci (Total Nendometriosis cases = 12,350). We identified five sub-phenotype clusters: (1) pain comorbidities, (2) uterine disorders, (3) pregnancy complications, (4) cardiometabolic comorbidities, and (5) HER-asymptomatic. Bonferroni significant loci included PDLIM5 for the cluster 1, GREB1 for cluster 2, WNT4 for cluster 3, RNLS for cluster 4, and ABO for cluster 5. The difference in associations between the groups suggests complex and varied genetic mechanisms of endometriosis and its symptoms. This study enhances our understanding of the clinical patterns of endometriosis sub-phenotypes, showcasing the innovative approach employed to investigate this complex disease.

A functional variant rs912304 for late-onset T1D risk contributes to islet dysfunction by regulating proinflammatory cytokine-responsive gene STXBP6 expression

BACKGROUND

Our previous genome‑wide association studies (GWAS) have suggested rs912304 in 14q12 as a suggestive risk variant for type 1 diabetes (T1D). However, the association between this risk region and T1D subgroups and related clinical risk features, the underlying causal functional variant(s), putative candidate gene(s), and related mechanisms are yet to be elucidated.

METHODS

We assessed the association between variant rs912304 and T1D, as well as islet autoimmunity and islet function, stratified by the diagnosed age of 12. We used epigenome bioinformatics analyses, dual luciferase reporter assays, and expression quantitative trait loci (eQTL) analyses to prioritize the most likely functional variant and potential causal gene. We also performed functional experiments to evaluate the role of the causal gene on islet function and its related mechanisms.

RESULTS

We identified rs912304 as a risk variant for T1D subgroups with diagnosed age ≥ 12 but not < 12. This variant is associated with residual islet function but not islet-specific autoantibody positivity in T1D individuals. Bioinformatics analysis indicated that rs912304 is a functional variant exhibiting spatial overlaps with enhancer active histone marks (H3K27ac and H3K4me1) and open chromatin status (ATAC-seq) in the human pancreas and islet tissues. Luciferase reporter gene assays and eQTL analyses demonstrated that the biallelic sites of rs912304 had differential allele-specific enhancer activity in beta cell lines and regulated STXBP6 expression, which was defined as the most putative causal gene based on Open Targets Genetics, GTEx v8 and Tiger database. Moreover, Stxbp6 was upregulated by T1D-related proinflammatory cytokines but not high glucose/fat. Notably, Stxbp6 over-expressed INS-1E cells exhibited decreasing insulin secretion and increasing cell apoptosis through Glut1 and Gadd45β, respectively.

CONCLUSIONS

This study expanded the genomic landscape regarding late-onset T1D risk and supported islet function mechanistically connected to T1D pathogenesis.

Leveraging pleiotropy identifies common-variant associations with selective IgA deficiency

Selective IgA deficiency (SIgAD) is the most common inborn error of immunity (IEI). Unlike many IEIs, evidence of a role for highly penetrant rare variants in SIgAD is lacking. Previous SIgAD studies have had limited power to identify common variants due to their small sample size. We overcame this problem first through meta-analysis of two existing GWAS. This identified four novel common-variant associations and enrichment of SIgAD-associated variants in genes linked to Mendelian IEIs. SIgAD showed evidence of shared genetic architecture with serum IgA and a number of immune-mediated diseases. We leveraged this pleiotropy through the conditional false discovery rate procedure, conditioning our SIgAD meta-analysis on large GWAS of asthma and rheumatoid arthritis, and our own meta-analysis of serum IgA. This identified an additional 18 variants, increasing the number of known SIgAD-associated variants to 27 and strengthening the evidence for a polygenic, common-variant aetiology for SIgAD.

Associations between diabetes-related genetic risk scores and residual beta cell function in type 1 diabetes: the GUTDM1 study

AIMS/HYPOTHESIS

Use of genetic risk scores (GRS) may help to distinguish between type 1 diabetes and type 2 diabetes, but less is known about whether GRS are associated with disease severity or progression after diagnosis. Therefore, we tested whether GRS are associated with residual beta cell function and glycaemic control in individuals with type 1 diabetes.

METHODS

Immunochip arrays and TOPMed were used to genotype a cross-sectional cohort (n=479, age 41.7 ± 14.9 years, duration of diabetes 16.0 years [IQR 6.0-29.0], HbA1c 55.6 ± 12.2 mmol/mol). Several GRS, which were originally developed to assess genetic risk of type 1 diabetes (GRS-1, GRS-2) and type 2 diabetes (GRS-T2D), were calculated. GRS-C1 and GRS-C2 were based on SNPs that have previously been shown to be associated with residual beta cell function. Regression models were used to investigate the association between GRS and residual beta cell function, assessed using the urinary C-peptide/creatinine ratio, and the association between GRS and continuous glucose monitor metrics.

RESULTS

Higher GRS-1 and higher GRS-2 both showed a significant association with undetectable UCPCR (OR 0.78; 95% CI 0.69, 0.89 and OR 0.84: 95% CI 0.75, 0.93, respectively), which were attenuated after correction for sex and age of onset (GRS-2) and disease duration (GRS-1). Higher GRS-C2 was associated with detectable urinary C-peptide/creatinine ratio (≥0.01 nmol/mmol) after correction for sex and age of onset (OR 6.95; 95% CI 1.19, 40.75). A higher GRS-T2D was associated with less time below range (TBR) (OR for TBR<4% 1.41; 95% CI 1.01 to 1.96) and lower glucose coefficient of variance (β -1.53; 95% CI -2.76, -0.29).

CONCLUSIONS/INTERPRETATION

Diabetes-related GRS are associated with residual beta cell function in individuals with type 1 diabetes. These findings suggest some genetic contribution to preservation of beta cell function.

Antigen-specific T cell responses in autoimmune diabetes

Autoimmune diabetes is a disease characterized by the selective destruction of insulin-secreting β-cells of the endocrine pancreas by islet-reactive T cells. Autoimmune disease requires a complex interplay between host genetic factors and environmental triggers that promote the activation of such antigen-specific T lymphocyte responses. Given the critical involvement of self-reactive T lymphocyte in diabetes pathogenesis, understanding how these T lymphocyte populations contribute to disease is essential to develop targeted therapeutics. To this end, several key antigenic T lymphocyte epitopes have been identified and studied to understand their contributions to disease with the aim of developing effective treatment approaches for translation to the clinical setting. In this review, we discuss the role of pathogenic islet-specific T lymphocyte responses in autoimmune diabetes, the mechanisms and cell types governing autoantigen presentation, and therapeutic strategies targeting such T lymphocyte responses for the amelioration of disease.

Genetic relations between type 1 diabetes, coronary artery disease and leukocyte counts

AIMS/HYPOTHESIS

Type 1 diabetes is associated with excess coronary artery disease (CAD) risk even when known cardiovascular risk factors are accounted for. Genetic perturbation of haematopoiesis that alters leukocyte production is a novel independent modifier of CAD risk. We examined whether there are shared genetic determinants and causal relationships between type 1 diabetes, CAD and leukocyte counts.

METHODS

Genome-wide association study summary statistics were used to perform pairwise linkage disequilibrium score regression and heritability estimation from summary statistics (ρ-HESS) to respectively estimate the genome-wide and local genetic correlations, and two-sample Mendelian randomisation to estimate the causal relationships between leukocyte counts (335,855 healthy individuals), type 1 diabetes (18,942 cases, 501,638 control individuals) and CAD (122,733 cases, 424,528 control individuals). A latent causal variable (LCV) model was performed to estimate the genetic causality proportion of the genetic correlation between type 1 diabetes and CAD.

RESULTS

There was significant genome-wide genetic correlation (rg) between type 1 diabetes and CAD (rg=0.088, p=8.60 × 10-3) and both diseases shared significant genome-wide genetic determinants with eosinophil count (rg for type 1 diabetes [rg(T1D)]=0.093, p=7.20 × 10-3, rg for CAD [rg(CAD)]=0.092, p=3.68 × 10-6) and lymphocyte count (rg(T1D)=-0.052, p=2.76 × 10-2, rg(CAD)=0.176, p=1.82 × 10-15). Sixteen independent loci showed stringent Bonferroni significant local genetic correlations between leukocyte counts, type 1 diabetes and/or CAD. Cis-genetic regulation of the expression levels of genes within shared loci between type 1 diabetes and CAD was associated with both diseases as well as leukocyte counts, including SH2B3, CTSH, MORF4L1, CTRB1, CTRB2, CFDP1 and IFIH1. Genetically predicted lymphocyte, neutrophil and eosinophil counts were associated with type 1 diabetes and CAD (lymphocyte OR for type 1 diabetes [ORT1D]=0.67, p=2.02-19, ORCAD=1.09, p=2.67 × 10-6; neutrophil ORT1D=0.82, p=5.63 × 10-5, ORCAD=1.17, p=5.02 × 10-14; and eosinophil ORT1D=1.67, p=5.45 × 10-25, ORCAD=1.07, p=2.03 × 10-4. The genetic causality proportion between type 1 diabetes and CAD was 0.36 ± 0.16 (pLCV=1.30 × 10-2), suggesting a possible intermediary causal variable.

CONCLUSIONS/INTERPRETATION

This study sheds light on shared genetic mechanisms underlying type 1 diabetes and CAD, which may contribute to their co-occurrence through regulation of gene expression and leukocyte counts and identifies cellular and molecular targets for further investigation for disease prediction and potential drug discovery.

Genetic association and machine learning improves discovery and prediction of type 1 diabetes

Type 1 diabetes (T1D) has a large genetic component, and expanded genetic studies of T1D can lead to novel biological and therapeutic discovery and improved risk prediction. In this study, we performed genetic association and fine-mapping analyses in 817,718 European ancestry samples genome-wide and 29,746 samples at the MHC locus, which identified 165 independent risk signals for T1D of which 19 were novel. We used risk variants to train a machine learning model (named T1GRS) to predict T1D, which highly differentiated T1D from non-disease and type 2 diabetes (T2D) in Europeans as well as African Americans at or beyond the level of current standards. We identified extensive non-linear interactions between risk loci in T1GRS, for example between HLA-DQB1*57 and INS, coding and non-coding HLA alleles, and DEXI, INS and other beta cell loci, that provided mechanistic insight and improved risk prediction. T1D individuals formed distinct clusters based on genetic features from T1GRS which had significant differences in age of onset, HbA1c, and renal disease severity. Finally, we provided T1GRS in formats to enhance accessibility of risk prediction to any user and computing environment. Overall, the improved genetic discovery and prediction of T1D will have wide clinical, therapeutic, and research applications.

Cracking the type 1 diabetes code: Genes, microbes, immunity, and the early life environment

Type 1 diabetes (T1D) results from a complex interplay of genetic predisposition, immunological dysregulation, and environmental triggers, that culminate in the destruction of insulin-secreting pancreatic β cells. This review provides a comprehensive examination of the multiple factors underpinning T1D pathogenesis, to elucidate key mechanisms and potential therapeutic targets. Beginning with an exploration of genetic risk factors, we dissect the roles of human leukocyte antigen (HLA) haplotypes and non-HLA gene variants associated with T1D susceptibility. Mechanistic insights gleaned from the NOD mouse model provide valuable parallels to the human disease, particularly immunological intricacies underlying β cell-directed autoimmunity. Immunological drivers of T1D pathogenesis are examined, highlighting the pivotal contributions of both effector and regulatory T cells and the multiple functions of B cells and autoantibodies in β-cell destruction. Furthermore, the impact of environmental risk factors, notably modulation of host immune development by the intestinal microbiome, is examined. Lastly, the review probes human longitudinal studies, unveiling the dynamic interplay between mucosal immunity, systemic antimicrobial antibody responses, and the trajectories of T1D development. Insights garnered from these interconnected factors pave the way for targeted interventions and the identification of biomarkers to enhance T1D management and prevention strategies.

Association between primary biliary cholangitis with diabetes and cardiovascular diseases: A bidirectional multivariable Mendelian randomization study

BACKGROUND AND AIMS

Primary biliary cholangitis (PBC) is an autoimmune disease often accompanied by multisystem damage. This study aimed to explore the causal association between genetically predicted PBC and diabetes, as well as multiple cardiovascular diseases (CVDs).

METHODS

Genome-wide association studies (GWAS) summary data of PBC in 24,510 individuals of European ancestry from the European Association for the Study of the Liver was used to identify genetically predicted PBC. We conducted 2-sample single-variable Mendelian randomization (SVMR) and multivariable Mendelian randomization (MVMR) to estimate the impacts of PBC on diabetes (N = 17,685 to 318,014) and 20 CVDs from the genetic consortium (N = 171,875 to 1,030,836).

RESULTS

SVMR provided evidence that genetically predicted PBC is associated with an increased risk of type 1 diabetes (T1D), type 2 diabetes (T2D), myocardial infarction (MI), heart failure (HF), hypertension, atrial fibrillation (AF), stroke, ischemic stroke, and small-vessel ischemic stroke. Additionally, there was no evidence of a causal association between PBC and coronary atherosclerosis. In the MVMR analysis, PBC maintained independent effects on T1D, HF, MI, and small-vessel ischemic stroke in most models.

CONCLUSION

Our findings revealed the causal effects of PBC on diabetes and 7 CVDs, and no causal relationship was detected between PBC and coronary atherosclerosis.

Untangling the genetics of beta cell dysfunction and death in type 1 diabetes

BACKGROUND

Type 1 diabetes (T1D) is a complex multi-system disease which arises from both environmental and genetic factors, resulting in the destruction of insulin-producing pancreatic beta cells. Over the past two decades, human genetic studies have provided new insight into the etiology of T1D, including an appreciation for the role of beta cells in their own demise.

SCOPE OF REVIEW

Here, we outline models supported by human genetic data for the role of beta cell dysfunction and death in T1D. We highlight the importance of strong evidence linking T1D genetic associations to bona fide candidate genes for mechanistic and therapeutic consideration. To guide rigorous interpretation of genetic associations, we describe molecular profiling approaches, genomic resources, and disease models that may be used to construct variant-to-gene links and to investigate candidate genes and their role in T1D.

MAJOR CONCLUSIONS

We profile advances in understanding the genetic causes of beta cell dysfunction and death at individual T1D risk loci. We discuss how genetic risk prediction models can be used to address disease heterogeneity. Further, we present areas where investment will be critical for the future use of genetics to address open questions in the development of new treatment and prevention strategies for T1D.

β-cell neogenesis: A rising star to rescue diabetes mellitus

BACKGROUND

Diabetes Mellitus (DM), a chronic metabolic disease characterized by elevated blood glucose, is caused by various degrees of insulin resistance and dysfunctional insulin secretion, resulting in hyperglycemia. The loss and failure of functional β-cells are key mechanisms resulting in type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM).

AIM OF REVIEW

Elucidating the underlying mechanisms of β-cell failure, and exploring approaches for β-cell neogenesis to reverse β-cell dysfunction may provide novel strategies for DM therapy.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Emerging studies reveal that genetic susceptibility, endoplasmic reticulum (ER) stress, oxidative stress, islet inflammation, and protein modification linked to multiple signaling pathways contribute to DM pathogenesis. Over the past few years, replenishing functional β-cell by β-cell neogenesis to restore the number and function of pancreatic β-cells has remarkably exhibited a promising therapeutic approach for DM therapy. In this review, we provide a comprehensive overview of the underlying mechanisms of β-cell failure in DM, highlight the effective approaches for β-cell neogenesis, as well as discuss the current clinical and preclinical agents research advances of β-cell neogenesis. Insights into the challenges of translating β-cell neogenesis into clinical application for DM treatment are also offered.

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.

Genomic variants associated with age at diagnosis of childhood-onset type 1 diabetes

Age at diagnosis (AAD) of Type 1 diabetes (T1D) is determined by the age at onset of the autoimmune attack and by the rate of beta cell destruction that follows. Twin studies found that T1D AAD is strongly influenced by genetics, notably in young children. In young UK, Finnish, Sardinian patients AAD-associated genomic variants were previously identified, which may vary across populations and with time. In 1956 children of European ancestry born in mainland France in 1980-2008 who declared T1D before 15 years, we tested 94 T1D-associated SNPs for their association with AAD using nonparametric Kruskal-Wallis test. While high-risk HLA genotypes were not found to be associated with AAD, fourteen SNPs located in 12 non-HLA loci showed a strong association (2.9 × 10-12 < P < 1.4 × 10-3 after FDR correction). Four of these loci have been associated with AAD in previous cohorts (GSDMB, IL2, TNFAIP3, IL1), supporting a partially shared genetic influence on AAD of T1D in the studied European populations. In contrast, the association of 8 new loci CLEC16A, TYK2, ERBB3, CCR7, FCRL3, DNAH2, FGF3/4, and HPSE2 with AAD is novel. The 12 protein-coding genes located within these loci are involved in major immune pathways or in predisposition to other autoimmune diseases, which suggests a prominent role for these genes in the early immune mechanisms of beta cell destruction.

Identification of functional enhancer variants associated with type I diabetes in CD4+ T cells

Type I diabetes is an autoimmune disease mediated by T-cell destruction of β cells in pancreatic islets. Currently, there is no known cure, and treatment consists of daily insulin injections. Genome-wide association studies and twin studies have indicated a strong genetic heritability for type I diabetes and implicated several genes. As most strongly associated variants are noncoding, there is still a lack of identification of functional and, therefore, likely causal variants. Given that many of these genetic variants reside in enhancer elements, we have tested 121 CD4+ T-cell enhancer variants associated with T1D. We found four to be functional through massively parallel reporter assays. Three of the enhancer variants weaken activity, while the fourth strengthens activity. We link these to their cognate genes using 3D genome architecture or eQTL data and validate them using CRISPR editing. Validated target genes include CLEC16A and SOCS1. While these genes have been previously implicated in type 1 diabetes and other autoimmune diseases, we show that enhancers controlling their expression harbor functional variants. These variants, therefore, may act as causal type 1 diabetic variants.

The causal relationship between autoimmune diseases and age-related macular degeneration: A two-sample mendelian randomization study

OBJECTIVE

The aim of this study is to investigate the potential causal relationship between autoimmune diseases, including systemic lupus erythematosus, rheumatoid arthritis, inflammatory bowel disease, multiple sclerosis, and Type 1 diabetes, and age-related macular degeneration (AMD). By utilizing the two-sample Mendelian Randomization (MR) approach, we endeavor to address this complex medical issue.

METHODS

Genome-wide association study (GWAS) data for autoimmune diseases and AMD were obtained from the IEU Open GWAS database and the FinnGen consortium. A series of stringent SNP filtering steps was applied to ensure the reliability of the genetic instruments. MR analyses were conducted using the TwoSampleMR and MR-PRESSO packages in R. The inverse-variance weighted (IVW) method served as the primary analysis, complemented by multiple supplementary analyses and sensitivity tests.

RESULTS

Within the discovery sample, only a statistically significant inverse causal relationship between multiple sclerosis (MS) and AMD was observed (OR = 0.92, 95% CI: 0.88-0.97, P = 0.003). This finding was confirmed in the replication sample (OR = 0.85, 95% CI: 0.80-0.89, P = 3.32×10-12). No statistically significant associations were detected between systemic lupus erythematosus, rheumatoid arthritis, inflammatory bowel disease, and Type 1 diabetes and AMD.

CONCLUSION

Strong evidence is provided by this study to support the existence of an inverse causal relationship between multiple sclerosis and age-related macular degeneration. However, no causal evidence was found linking other autoimmune diseases with AMD. These findings not only offer novel insights into the potential etiological mechanisms underlying AMD but also suggest possible directions for future clinical interventions.

Proteome-wide Mendelian randomization identifies potential therapeutic targets for nonalcoholic fatty liver diseases

Nonalcoholic fatty liver disease (NAFLD) is the predominant cause of liver pathology. Current evidence highlights plasma proteins as potential therapeutic targets. However, their mechanistic roles in NAFLD remain unclear. This study investigated the involvement of specific plasma proteins and intermediate risk factors in NAFLD progression. Two-sample Mendelian randomization (MR) analysis was conducted to examine the association between plasma proteins and NAFLD. Colocalization analysis determined the shared causal variants between the identified proteins and NAFLD. The MR analysis was applied separately to proteins, risk factors, and NAFLD. Mediator shares were computed by detecting the correlations among these elements. Phenome-wide association studies (phewas) were utilized to assess the safety implications of targeting these proteins. Among 1,834 cis-protein quantitative trait loci (cis-pQTLs), after-FDR correction revealed correlations between the plasma levels of four gene-predicted proteins (CSPG3, CILP2, Apo-E, and GCKR) and NAFLD. Colocalization analysis indicated shared causal variants for CSPG3 and GCKR in NAFLD (posterior probability > 0.8). Out of the 22 risk factors screened for MR analysis, only 8 showed associations with NAFLD (p ≤ 0.05), while 4 linked to CSPG3 and GCKR. The mediator shares for these associations were calculated separately. Additionally, reverse MR analysis was performed on the pQTLs, risk factors, and NAFLD, which exhibited a causal relationship with forward MR analysis. Finally, phewas summarized the potential side effects of associated-targeting proteins, including CSPG3 and GCKR. Our research emphasized the potential therapeutic targets for NAFLD and provided modifiable risk factors for preventing NAFLD.

A multi-ancestry genome-wide association study in type 1 diabetes

Type 1 diabetes (T1D) is an autoimmune disease caused by destruction of the pancreatic β-cells. Genome-wide association (GWAS) and fine mapping studies have been conducted mainly in European ancestry (EUR) populations. We performed a multi-ancestry GWAS to identify SNPs and HLA alleles associated with T1D risk and age at onset. EUR families (N = 3223), and unrelated individuals of African (AFR, N = 891) and admixed (Hispanic/Latino) ancestry (AMR, N = 308) were genotyped using the Illumina HumanCoreExome BeadArray, with imputation to the TOPMed reference panel. The Multi-Ethnic HLA reference panel was utilized to impute HLA alleles and amino acid residues. Logistic mixed models (T1D risk) and frailty models (age at onset) were used for analysis. In GWAS meta-analysis, seven loci were associated with T1D risk at genome-wide significance: PTPN22, HLA-DQA1, IL2RA, RNLS, INS, IKZF4-RPS26-ERBB3, and SH2B3, with four associated with T1D age at onset (PTPN22, HLA-DQB1, INS, and ERBB3). AFR and AMR meta-analysis revealed NRP1 as associated with T1D risk and age at onset, although NRP1 variants were not associated in EUR ancestry. In contrast, the PTPN22 variant was significantly associated with risk only in EUR ancestry. HLA alleles and haplotypes most significantly associated with T1D risk in AFR and AMR ancestry differed from that seen in EUR ancestry; in addition, the HLA-DRB1*08:02-DQA1*04:01-DQB1*04:02 haplotype was 'protective' in AMR while HLA-DRB1*08:01-DQA1*04:01-DQB1*04:02 haplotype was 'risk' in EUR ancestry, differing only at HLA-DRB1*08. These results suggest that much larger sample sizes in non-EUR populations are required to capture novel loci associated with T1D risk.

Genetic mapping across autoimmune diseases reveals shared associations and mechanisms

Autoimmune and inflammatory diseases are polygenic disorders of the immune system. Many genomic loci harbor risk alleles for several diseases, but the limited resolution of genetic mapping prevents determining whether the same allele is responsible, indicating a shared underlying mechanism. Here, using a collection of 129,058 cases and controls across 6 diseases, we show that ~40% of overlapping associations are due to the same allele. We improve fine-mapping resolution for shared alleles twofold by combining cases and controls across diseases, allowing us to identify more expression quantitative trait loci driven by the shared alleles. The patterns indicate widespread sharing of pathogenic mechanisms but not a single global autoimmune mechanism. Our approach can be applied to any set of traits and is particularly valuable as sample collections become depleted.

Enhancing Genetic Association Power in Endometriosis through Unsupervised Clustering of Clinical Subtypes Identified from Electronic Health Records

Background

Endometriosis affects 10% of reproductive-age women, and yet, it goes undiagnosed for 3.6 years on average after symptoms onset. Despite large GWAS meta-analyses (N > 750,000), only a few dozen causal loci have been identified. We hypothesized that the challenges in identifying causal genes for endometriosis stem from heterogeneity across clinical and biological factors underlying endometriosis diagnosis.

Methods

We extracted known endometriosis risk factors, symptoms, and concomitant conditions from the Penn Medicine Biobank (PMBB) and performed unsupervised spectral clustering on 4,078 women with endometriosis. The 5 clusters were characterized by utilizing additional electronic health record (EHR) variables, such as endometriosis-related comorbidities and confirmed surgical phenotypes. From four EHR-linked genetic datasets, PMBB, eMERGE, AOU, and UKBB, we extracted lead variants and tag variants 39 known endometriosis loci for association testing. We meta-analyzed ancestry-stratified case/control tests for each locus and cluster in addition to a positive control (Total N endometriosis cases = 10,108).

Results

We have designated the five subtype clusters as pain comorbidities, uterine disorders, pregnancy complications, cardiometabolic comorbidities, and EHR-asymptomatic based on enriched features from each group. One locus, RNLS , surpassed the genome-wide significant threshold in the positive control. Thirteen more loci reached a Bonferroni threshold of 1.3 x 10 -3 (0.05 / 39) in the positive control. The cluster-stratified tests yielded more significant associations than the positive control for anywhere from 5 to 15 loci depending on the cluster. Bonferroni significant loci were identified for four out of five clusters, including WNT4 and GREB1 for the uterine disorders cluster, RNLS for the cardiometabolic cluster, FSHB for the pregnancy complications cluster, and SYNE1 and CDKN2B-AS1 for the EHR-asymptomatic cluster. This study enhances our understanding of the clinical presentation patterns of endometriosis subtypes, showcasing the innovative approach employed to investigate this complex disease.

Massively parallel reporter assay confirms regulatory potential of hQTLs and reveals important variants in lupus and other autoimmune diseases

We designed a massively parallel reporter assay (MPRA) in an Epstein-Barr virus transformed B cell line to directly characterize the potential for histone post-translational modifications, i.e., histone quantitative trait loci (hQTLs), expression QTLs (eQTLs), and variants on systemic lupus erythematosus (SLE) and autoimmune (AI) disease risk haplotypes to modulate regulatory activity in an allele-dependent manner. Our study demonstrates that hQTLs, as a group, are more likely to modulate regulatory activity in an MPRA compared with other variant classes tested, including a set of eQTLs previously shown to interact with hQTLs and tested AI risk variants. In addition, we nominate 17 variants (including 11 previously unreported) as putative causal variants for SLE and another 14 for various other AI diseases, prioritizing these variants for future functional studies in primary and immortalized B cells. Thus, we uncover important insights into the mechanistic relationships among genotype, epigenetics, and gene expression in SLE and AI disease phenotypes.

The casual relationship between autoimmune diseases and multiple myeloma: a Mendelian randomization study

Observational studies showed possible associations between systemic lupus erythematosus and multiple myeloma. However, whether there is a casual relationship between different types of autoimmune diseases (type 1 diabetes mellitus, rheumatoid arthritis, systemic lupus erythematosus, psoriasis, multiple sclerosis, primary sclerosing cholangitis, primary biliary cirrhosis, and juvenile idiopathic arthritis) and multiple myeloma (MM) is not well known. We performed a two-sample Mendelian randomization (MR) study to estimate the casual relationship. Summary-level data of autoimmune diseases were gained from published genome-wide association studies while data of MM was obtained from UKBiobank. The Inverse-Variance Weighted (IVW) method was used as the primary analysis method to interpret the study results, with MR-Egger and weighted median as complementary methods of analysis. There is causal relationship between primary sclerosing cholangitis [OR = 1.00015, 95% CI 1.000048-1.000254, P = 0.004] and MM. Nevertheless, no similar causal relationship was found between the remaining seven autoimmune diseases and MM. Considering the important role of age at recruitment and body mass index (BMI) in MM, we excluded these relevant instrument variables, and similar results were obtained. The accuracy and robustness of these findings were confirmed by sensitivity tests. Overall, MR analysis suggests that genetic liability to primary sclerosing cholangitis could be causally related to the increasing risk of MM. This finding may serve as a guide for clinical attention to patients with autoimmune diseases and their early screening for MM.

Diabetes mellitus and idiopathic pulmonary fibrosis: a Mendelian randomization study

BACKGROUND

The question as to whether or not diabetes mellitus increases the risk of idiopathic pulmonary fibrosis (IPF) remains controversial. This study aimed to investigate the causal association between type 1 diabetes (T1D), type 2 diabetes (T2D), and IPF using Mendelian randomization (MR) analysis.

METHODS

We used two-sample univariate and multivariate MR (MVMR) analyses to investigate the causal relationship between T1D or T2D and IPF. We obtained genome-wide association study (GWAS) data for T1D and T2D from the European Bioinformatics Institute, comprising 29,652 T1D samples and 101,101 T1D single nucleotide polymorphisms (SNPs) and 655,666 T2D samples and 5,030,727 T2D SNPs. We also used IPF GWAS data from the FinnGen Biobank comprising 198,014 IPF samples and 16,380,413 IPF SNPs. All cases and controls in these datasets were derived exclusively from European populations. In the univariate MR analysis, we employed inverse variance-weighted (IVW), weighted median (WM), and MR-Egger regression methods. For the MVMR analysis, we used the multivariate IVW method primarily, and supplemented it with multivariate MR-Egger and multivariate MR- least absolute shrinkage and selection operator methods. Heterogeneity tests were conducted using the MR-IVW and MR-Egger regression methods, whereas pleiotropic effects were assessed using the MR-Egger intercept. The results of MR and sensitivity analyses were visualized using forest, scatter, leave-one-out, and funnel plots.

RESULTS

Univariate MR revealed a significant causal relationship between T1D and IPF (OR = 1.118, 95% CI = 1.021-1.225, P = 0.016); however, no significant causal relationship was found between T2D and IPF (OR = 0.911, 95% CI = 0.796-1.043, P = 0.178). MVMR analysis further confirmed a causal association between T1D and IPF (OR = 1.133, 95% CI = 1.011-1.270, P = 0.032), but no causal relationship between T2D and IPF (OR = 1.009, 95% CI = 0.790-1.288, P = 0.950). Sensitivity analysis results validated the stability and reliability of our findings.

CONCLUSION

Univariate and multivariate analyses demonstrated a causal relationship between T1D and IPF, whereas no evidence was found to support a causal relationship between T2D and IPF. Therefore, in clinical practice, patients with T1D should undergo lung imaging for early detection of IPF.

Rare copy number variation in autoimmune Addison's disease

Autoimmune Addison's disease (AAD) is a rare but life-threatening endocrine disorder caused by an autoimmune destruction of the adrenal cortex. A previous genome-wide association study (GWAS) has shown that common variants near immune-related genes, which mostly encode proteins participating in the immune response, affect the risk of developing this condition. However, little is known about the contribution of copy number variations (CNVs) to AAD susceptibility. We used the genome-wide genotyping data from Norwegian and Swedish individuals (1,182 cases and 3,810 controls) to investigate the putative role of CNVs in the AAD aetiology. Although the frequency of rare CNVs was similar between cases and controls, we observed that larger deletions (>1,000 kb) were more common among patients (OR = 4.23, 95% CI 1.85-9.66, p = 0.0002). Despite this, none of the large case-deletions were conclusively pathogenic, and the clinical presentation and an AAD-polygenic risk score were similar between cases with and without the large CNVs. Among deletions exclusive to individuals with AAD, we highlight two ultra-rare deletions in the genes LRBA and BCL2L11, which we speculate might have contributed to the polygenic risk in these carriers. In conclusion, rare CNVs do not appear to be a major cause of AAD but further studies are needed to ascertain the potential contribution of rare deletions to the polygenic load of AAD susceptibility.

Non-coding autoimmune risk variant defines role for ICOS in T peripheral helper cell development

Fine-mapping and functional studies implicate rs117701653, a non-coding single nucleotide polymorphism in the CD28/CTLA4/ICOS locus, as a risk variant for rheumatoid arthritis and type 1 diabetes. Here, using DNA pulldown, mass spectrometry, genome editing and eQTL analysis, we establish that the disease-associated risk allele is functional, reducing affinity for the inhibitory chromosomal regulator SMCHD1 to enhance expression of inducible T-cell costimulator (ICOS) in memory CD4+ T cells from healthy donors. Higher ICOS expression is paralleled by an increase in circulating T peripheral helper (Tph) cells and, in rheumatoid arthritis patients, of blood and joint fluid Tph cells as well as circulating plasmablasts. Correspondingly, ICOS ligation and carriage of the rs117701653 risk allele accelerate T cell differentiation into CXCR5-PD-1high Tph cells producing IL-21 and CXCL13. Thus, mechanistic dissection of a functional non-coding variant in human autoimmunity discloses a previously undefined pathway through which ICOS regulates Tph development and abundance.

Influence of sphingolipid enzymes on blood glucose levels, development of diabetes, and involvement of pericytes

AIMS

Sulfatide is a chaperone for insulin manufacturing in beta cells. Here we explore whether the blood glucose values normally could be associated with this sphingolipid and especially two of its building enzymes CERS2 and CERS6. Both T1D and T2D have low blood sulfatide levels, and insulin resistance on beta cells at clinical diagnosis. Furthermore, we examined islet pericytes for sulfatide, and beta-cell receptors for GLP-1, both of which are related to the insulin production.

MATERIALS AND METHODS

We examined mRNA levels in islets from the DiViD and nPOD studies, performed genetic association analyses, and histologically investigated pericytes in the islets for sulfatide.

RESULTS

Polymorphisms of the gene encoding the CERS6 enzyme responsible for synthesising dihydroceramide, a precursor to sulfatide, are associated with random blood glucose values in non-diabetic persons. This fits well with our finding of sulfatide in pericytes in the islets, which regulates the capillary blood flow in the islets of Langerhans, which is important for oxygen supply to insulin production. In the islets of newly diagnosed T1D patients, we observed low levels of GLP-1 receptors; this may explain the insulin resistance in their beta cells and their low insulin production. In T2D patients, we identified associated polymorphisms in both CERS2 and CERS6.

CONCLUSIONS

Here, we describe several polymorphisms in sulfatide enzymes related to blood glucose levels and HbA1c in non-diabetic individuals. Islet pericytes from such persons contain sulfatide. Furthermore, low insulin secretion in newly diagnosed T1D may be explained by beta-cell insulin resistance due to low levels of GLP-1 receptors.

Lessons and Applications of Omics Research in Diabetes Epidemiology

PURPOSE OF REVIEW

Recent advances in genomic technology and molecular techniques have greatly facilitated the identification of disease biomarkers, advanced understanding of pathogenesis of different common diseases, and heralded the dawn of precision medicine. Much of these advances in the area of diabetes have been made possible through deep phenotyping of epidemiological cohorts, and analysis of the different omics data in relation to detailed clinical information. In this review, we aim to provide an overview on how omics research could be incorporated into the design of current and future epidemiological studies.

RECENT FINDINGS

We provide an up-to-date review of the current understanding in the area of genetic, epigenetic, proteomic and metabolomic markers for diabetes and related outcomes, including polygenic risk scores. We have drawn on key examples from the literature, as well as our own experience of conducting omics research using the Hong Kong Diabetes Register and Hong Kong Diabetes Biobank, as well as other cohorts, to illustrate the potential of omics research in diabetes. Recent studies highlight the opportunity, as well as potential benefit, to incorporate molecular profiling in the design and set-up of diabetes epidemiology studies, which can also advance understanding on the heterogeneity of diabetes. Learnings from these examples should facilitate other researchers to consider incorporating research on omics technologies into their work to advance the field and our understanding of diabetes and its related co-morbidities. Insights from these studies would be important for future development of precision medicine in diabetes.

Implementation of type 1 diabetes genetic risk screening in children in diverse communities: the Virginia PrIMeD project

BACKGROUND

Population screening for risk of type 1 diabetes (T1D) has been proposed to identify those with islet autoimmunity (presence of islet autoantibodies). As islet autoantibodies can be transient, screening with a genetic risk score has been proposed as an entry into autoantibody testing.

METHODS

Children were recruited from eight general pediatric and specialty clinics across Virginia with diverse community settings. Recruiters in each clinic obtained informed consent/assent, a medical history, and a saliva sample for DNA extraction in children with and without a history of T1D. A custom genotyping panel was used to define T1D genetic risk based upon associated SNPs in European- and African-genetic ancestry. Subjects at "high genetic risk" were offered a separate blood collection for screening four islet autoantibodies. A follow-up contact (email, mail, and telephone) in one half of the participants determined interest and occurrence of subsequent T1D.

RESULTS

A total of 3818 children aged 2-16 years were recruited, with 14.2% (n = 542) having a "high genetic risk." Of children with "high genetic risk" and without pre-existing T1D (n = 494), 7.0% (34/494) consented for autoantibody screening; 82.4% (28/34) who consented also completed the blood collection, and 7.1% (2/28) of them tested positive for multiple autoantibodies. Among children with pre-existing T1D (n = 91), 52% (n = 48) had a "high genetic risk." In the sample of children with existing T1D, there was no relationship between genetic risk and age at T1D onset. A major factor in obtaining islet autoantibody testing was concern over SARS-CoV-2 exposure.

CONCLUSIONS

Minimally invasive saliva sampling implemented using a genetic risk score can identify children at genetic risk of T1D. Consent for autoantibody screening, however, was limited largely due to the SARS-CoV-2 pandemic and need for blood collection.

TYK2 signaling promotes the development of autoreactive CD8+ cytotoxic T lymphocytes and type 1 diabetes

Tyrosine kinase 2 (TYK2), a member of the JAK family, has attracted attention as a potential therapeutic target for autoimmune diseases. However, the role of TYK2 in CD8+ T cells and autoimmune type 1 diabetes (T1D) is poorly understood. In this study, we generate Tyk2 gene knockout non-obese diabetes (NOD) mice and demonstrate that the loss of Tyk2 inhibits the development of autoreactive CD8+ T-BET+ cytotoxic T lymphocytes (CTLs) by impairing IL-12 signaling in CD8+ T cells and the CD8+ resident dendritic cell-driven cross-priming of CTLs in the pancreatic lymph node (PLN). Tyk2-deficient CTLs display reduced cytotoxicity. Increased inflammatory responses in β-cells with aging are dampened by Tyk2 deficiency. Furthermore, treatment with BMS-986165, a selective TYK2 inhibitor, inhibits the expansion of T-BET+ CTLs, inflammation in β-cells and the onset of autoimmune T1D in NOD mice. Thus, our study reveals the diverse roles of TYK2 in driving the pathogenesis of T1D.

Large-scale integrative analysis of juvenile idiopathic arthritis for new insight into its pathogenesis

BACKGROUND

Juvenile idiopathic arthritis (JIA) is one of the most prevalent rheumatic disorders in children and is classified as an autoimmune disease (AID). While a robust genetic contribution to JIA etiology has been established, the exact pathogenesis remains unclear.

METHODS

To prioritize biologically interpretable susceptibility genes and proteins for JIA, we conducted transcriptome-wide and proteome-wide association studies (TWAS/PWAS). Then, to understand the genetic architecture of JIA, we systematically analyzed single-nucleotide polymorphism (SNP)-based heritability, a signature of natural selection, and polygenicity. Next, we conducted HLA typing using multi-ethnicity RNA sequencing data. Additionally, we examined the T cell receptor (TCR) repertoire at a single-cell level to explore the potential links between immunity and JIA risk.

RESULTS

We have identified 19 TWAS genes and two PWAS proteins associated with JIA risks. Furthermore, we observe that the heritability and cell type enrichment analysis of JIA are enriched in T lymphocytes and HLA regions and that JIA shows higher polygenicity compared to other AIDs. In multi-ancestry HLA typing, B*45:01 is more prevalent in African JIA patients than in European JIA patients, whereas DQA1*01:01, DQA1*03:01, and DRB1*04:01 exhibit a higher frequency in European JIA patients. Using single-cell immune repertoire analysis, we identify clonally expanded T cell subpopulations in JIA patients, including CXCL13+BHLHE40+ TH cells which are significantly associated with JIA risks.

CONCLUSION

Our findings shed new light on the pathogenesis of JIA and provide a strong foundation for future mechanistic studies aimed at uncovering the molecular drivers of JIA.

The genetic basis of autoimmunity seen through the lens of T cell functional traits

Autoimmune disease heritability is enriched in T cell-specific regulatory regions of the genome. Modern-day T cell datasets now enable association studies between single nucleotide polymorphisms (SNPs) and a myriad of molecular phenotypes, including chromatin accessibility, gene expression, transcriptional programs, T cell antigen receptor (TCR) amino acid usage, and cell state abundances. Such studies have identified hundreds of quantitative trait loci (QTLs) in T cells that colocalize with genetic risk for autoimmune disease. The key challenge facing immunologists today lies in synthesizing these results toward a unified understanding of the autoimmune T cell: which genes, cell states, and antigens drive tissue destruction?

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.

Gene-environment interaction in the pathophysiology of type 1 diabetes

Type 1 diabetes (T1D) is a complex metabolic autoimmune disorder that affects millions of individuals worldwide and often leads to significant comorbidities. However, the precise trigger of autoimmunity and disease onset remain incompletely elucidated. This integrative perspective article synthesizes the cumulative role of gene-environment interaction in the pathophysiology of T1D. Genetics plays a significant role in T1D susceptibility, particularly at the major histocompatibility complex (MHC) locus and cathepsin H (CTSH) locus. In addition to genetics, environmental factors such as viral infections, pesticide exposure, and changes in the gut microbiome have been associated with the development of T1D. Alterations in the gut microbiome impact mucosal integrity and immune tolerance, increasing gut permeability through molecular mimicry and modulation of the gut immune system, thereby increasing the risk of T1D potentially through the induction of autoimmunity. HLA class II haplotypes with known effects on T1D incidence may directly correlate to changes in the gut microbiome, but precisely how the genes influence changes in the gut microbiome, and how these changes provoke T1D, requires further investigations. These gene-environment interactions are hypothesized to increase susceptibility to T1D through epigenetic changes such as DNA methylation and histone modification, which in turn modify gene expression. There is a need to determine the efficacy of new interventions that target these epigenetic modifications such as "epidrugs", which will provide novel avenues for the effective management of T1D leading to improved quality of life of affected individuals and their families/caregivers.

Secrets and lies of host-microbial interactions: MHC restriction and trans-regulation of T cell trafficking conceal the role of microbial agents on the edge between health and multifactorial/complex diseases

Here we critically discuss data supporting the view that microbial agents (pathogens, pathobionts or commensals alike) play a relevant role in the pathogenesis of multifactorial diseases, but their role is concealed by the rules presiding over T cell antigen recognition and trafficking. These rules make it difficult to associate univocally infectious agents to diseases' pathogenesis using the paradigm developed for canonical infectious diseases. (Cross-)recognition of a variable repertoire of epitopes leads to the possibility that distinct infectious agents can determine the same disease(s). There can be the need for sequential infection/colonization by two or more microorganisms to develop a given disease. Altered spreading of infectious agents can determine an unwanted activation of T cells towards a pro-inflammatory and trafficking phenotype, due to differences in the local microenvironment. Finally, trans-regulation of T cell trafficking allows infectious agents unrelated to the specificity of T cell to modify their homing to target organs, thereby driving flares of disease. The relevant role of microbial agents in largely prevalent diseases provides a conceptual basis for the evaluation of more specific therapeutic approaches, targeted to prevent (vaccine) or cure (antibiotics and/or Biologic Response Modifiers) multifactorial diseases.

PASTRY: achieving balanced power for detecting risk and protective minor alleles in meta-analysis of association studies with overlapping subjects

BACKGROUND

Meta-analysis is a statistical method that combines the results of multiple studies to increase statistical power. When multiple studies participating in a meta-analysis utilize the same public dataset as controls, the summary statistics from these studies become correlated. To solve this challenge, Lin and Sullivan proposed a method to provide an optimal test statistic adjusted for the correlation. This method quickly became the standard practice. However, we identified an unexpected power asymmetry phenomenon in this standard framework. This can lead to unbalanced power for detecting protective minor alleles and risk minor alleles.

RESULTS

We found that the power asymmetry of the current framework is mainly due to the errors in approximating the correlation term. We then developed a meta-analysis method based on an accurate correlation estimator, called PASTRY (A method to avoid Power ASymmeTRY). PASTRY outperformed the standard method on both simulated and real datasets in terms of the power symmetry.

CONCLUSIONS

Our findings suggest that PASTRY can help to alleviate the power asymmetry problem. PASTRY is available at https://github.com/hanlab-SNU/PASTRY .

The rare DRB1*04:08-DQ8 haplotype is the main HLA class II genetic driver and discriminative factor of Early-onset Type 1 diabetes in the Portuguese population

Introduction

Early-onset Type 1 diabetes (EOT1D) is considered a disease subtype with distinctive immunological and clinical features. While both Human Leukocyte Antigen (HLA) and non-HLA variants contribute to age at T1D diagnosis, detailed analyses of EOT1D-specific genetic determinants are still lacking. This study scrutinized the involvement of the HLA class II locus in EOT1D genetic control.

Methods

We conducted genetic association and regularized logistic regression analyses to evaluate genotypic, haplotypic and allelic variants in DRB1, DQA1 and DQB1 genes in children with EOT1D (diagnosed at ≤5 years of age; n=97), individuals with later-onset disease (LaOT1D; diagnosed 8-30 years of age; n=96) and nondiabetic control subjects (n=169), in the Portuguese population.

Results

Allelic association analysis of EOT1D and LaOT1D unrelated patients in comparison with controls, revealed that the rare DRB1*04:08 allele is a distinctive EOT1D susceptibility factor (corrected p-value=7.0x10-7). Conversely, the classical T1D risk allele DRB1*04:05 was absent in EOT1D children while was associated with LaOT1D (corrected p-value=1.4x10-2). In corroboration, HLA class II haplotype analysis showed that the rare DRB1*04:08-DQ8 haplotype is specifically associated with EOT1D (corrected p-value=1.4x10-5) and represents the major HLA class II genetic driver and discriminative factor in the development of early onset disease.

Discussion

This study uncovered that EOT1D holds a distinctive spectrum of HLA class II susceptibility loci, which includes risk factors overlapping with LaOT1D and discriminative genetic configurations. These findings warrant replication studies in larger multicentric settings encompassing other ethnicities and may impact target screening strategies and follow-up of young children with high T1D genetic risk as well as personalized therapeutic approaches.

Increased expression of protein tyrosine phosphatase nonreceptor type 22 alters early T-cell receptor signaling and differentiation of CD4+ T cells in chronic heart failure

CD4+ T-cell counts are increased and activated in patients with chronic heart failure (CHF), whereas regulatory T-cell (Treg) expansion is inhibited, probably due to aberrant T-cell receptor (TCR) signaling. TCR signaling is affected by protein tyrosine phosphatase nonreceptor type 22 (PTPN22) in autoimmune disorders, but whether PTPN22 influences TCR signaling in CHF remains unclear. This observational case-control study included 45 patients with CHF [18 patients with ischemic heart failure versus 27 patients with nonischemic heart failure (NIHF)] and 16 non-CHF controls. We used flow cytometry to detect PTPN22 expression, tyrosine phosphorylation levels, zeta-chain-associated protein kinase, 70 kDa (ZAP-70) inhibitory residue tyrosine 292 and 319 phosphorylation levels, and CD4+ T cell and Treg proportions. We conducted lentivirus-mediated PTPN22 RNA silencing in isolated CD4+ T cells. PTPN22 expression increased in the CD4+ T cells of patients with CHF compared with that in controls. PTPN22 expression was positively correlated with left ventricular end-diastolic diameter and type B natriuretic peptide but negatively correlated with left ventricular ejection fraction in the NIHF group. ZAP-70 tyrosine 292 phosphorylation was decreased, which correlated positively with PTPN22 overexpression in patients with NIHF and promoted early TCR signaling. PTPN22 silencing induced Treg differentiation in CD4+ T cells from patients with CHF, which might account for the reduced frequency of peripheral Tregs in these patients. PTPN22 is a potent immunomodulator in CHF and might play an essential role in the development of CHF by promoting early TCR signaling and impairing Treg differentiation from CD4+ T cells.

Candidate Genetic and Molecular Drivers of Dysregulated Adaptive Immune Responses After Traumatic Brain Injury

Abstract Neuroinflammation is a significant and modifiable cause of secondary injury after traumatic brain injury (TBI), driven by both central and peripheral immune responses. A substantial proportion of outcome after TBI is genetically mediated, with an estimated heritability effect of around 26%, but because of the comparatively small datasets currently available, the individual drivers of this genetic effect have not been well delineated. A hypothesis-driven approach to analyzing genome-wide association study (GWAS) datasets reduces the burden of multiplicity testing and allows variants with a high prior biological probability of effect to be identified where sample size is insufficient to withstand data-driven approaches. Adaptive immune responses show substantial genetically mediated heterogeneity and are well established as a genetic source of risk for numerous disease states; importantly, HLA class II has been specifically identified as a locus of interest in the largest TBI GWAS study to date, highlighting the importance of genetic variance in adaptive immune responses after TBI. In this review article we identify and discuss adaptive immune system genes that are known to confer strong risk effects for human disease, with the dual intentions of drawing attention to this area of immunobiology, which, despite its importance to the field, remains under-investigated in TBI and presenting high-yield testable hypotheses for application to TBI GWAS datasets.

Genetic discovery and risk prediction for type 1 diabetes in individuals without high-risk HLA-DR3/DR4 haplotypes

Over 10% of type 1 diabetes (T1D) cases do not have high-risk HLA-DR3 or DR4 haplotypes with distinct clinical features such as later onset and reduced insulin dependence. To identify genetic drivers of T1D in the absence of DR3/DR4, we performed association and fine-mapping analyses in 12,316 non-DR3/DR4 samples. Risk variants at the MHC and other loci genome-wide had heterogeneity in effects on T1D dependent on DR3/DR4, and non-DR3/DR4 T1D had evidence for a greater polygenic burden. T1D-assocated variants in non-DR3/DR4 were more enriched for loci, regulatory elements, and pathways for antigen presentation, innate immunity, and beta cells, and depleted in T cells, compared to DR3/DR4. Non-DR3/DR4 T1D cases were poorly classified based on an existing genetic risk score GRS2, and we created a new GRS which highly discriminated non-DR3/DR4 T1D from both non-diabetes and T2D. In total we identified heterogeneity in T1D genetic risk and disease mechanisms dependent on high-risk HLA haplotype and which enabled accurate classification of T1D across HLA background.

Exploring the Causality of Type 1 Diabetes and Stroke Risk: A Mendelian Randomization Study and Meta-analysis

Type II diabetes was causally related to stroke, which is a risk factor for stroke. However, the causal relationship between type I diabetes(T1D) and stroke, especially its subtypes, remains unclear. To determine whether T1D has a genetic causal link to stroke and its subtypes, we undertook this mendelian randomization (MR) study. The genome-wide association studies (GWAS) of T1D was the source of exposure. The outcomes were strokes and their subtypes, including ischemic stroke (IS), small vessel stroke (SVS), cardioembolic stroke (CES), large artery atherosclerosis stroke (LAS), intracerebral hemorrhage (ICH), lobar intracerebral hemorrhage (LICH), and non-lobar intracerebral hemorrhage (NLICH). We used outcome GWAS conducted by ISGC consortium for the initial phase and GWAS from MEGASTROKE consortium as the data for the replication phase to confirm the causal association. Besides, we conducted a meta-analysis of the causal association from ISGC and MEGASTROKE databases to confirm robust causality. Inverse-variance weighting (IVW) was utilized as the primary method to estimate the causality between T1D and stroke. The Cochran's Q test and the MR-PRESSO global test were used to examine the sensitivity. We discovered the causal relationship between T1D and SVS (OR = 1.17, 95% CI: 1.07-1.28, p = 6.0 × 10- 4), CES (OR = 1.11, 95%CI: 1.03-1.21, p = 0.0080) in initial stage. The replication phase validated T1D has a causal relationship with SVS (OR = 1.12, 95% CI: 1.06-1.18, p = 4.0 × 10- 5), but not with stroke and other subtypes. The meta-analysis of initial and replication stage again supported the causal link between T1D and SVS (OR = 1.13, 95% CI: 1.08-1.18, p < 0.05). However, no causal relationship was found between T1D and other stroke subtypes. The sensitivity analysis also supported the robust of these results. In conclusion, T1D was causally associated with SVS, but not with other subtypes of stroke. More investigation is needed to understand the underlying biology mechanism.

DNA methylation differences within INS, PTPN22 and IL2RA promoters in lymphocyte subsets in children with type 1 diabetes and controls

We elucidated the effect of four known T1D-susceptibility associated single nucleotide polymorphism (SNP) markers in three genes (rs12722495 and rs2104286 in IL2RA, rs689 in INS and rs2476601 in PTPN22) on CpG site methylation of their proximal promoters in different lymphocyte subsets using pyrosequencing. The study cohort comprised 25 children with newly diagnosed T1D and 25 matched healthy controls. The rs689 SNP was associated with methylation at four CpG sites in INS promoter: -234, -206, -102 and -69. At all four CpG sites, the susceptibility genotype AA was associated with a higher methylation level compared to the other genotypes. We also found an association between rs12722495 and methylation at CpG sites -373 and -356 in IL2RA promoter in B cells, where the risk genotype AA was associated with lower methylation level compared to the AG genotype. The other SNPs analyzed did not demonstrate significant associations with CpG site methylation in the examined genes. Additionally, we compared the methylation between children with T1D and controls, and found statistically significant methylation differences at CpG -135 in INS in CD8+ T cells (p = 0.034), where T1D patients had a slightly higher methylation compared to controls (87.3 ± 7.2 vs. 78.8 ± 8.9). At the other CpG sites analyzed, the methylation was similar. Our results not only confirm the association between INS methylation and rs689 discovered in earlier studies but also report this association in sorted immune cells. We also report an association between rs12722495 and IL2RA promoter methylation in B cells. These results suggest that at least part of the genetic effect of rs689 and rs12722495 on T1D pathogenesis may be conveyed by DNA methylation.

Distinct transcriptomic profiles in children prior to the appearance of type 1 diabetes-linked islet autoantibodies and following enterovirus infection

Although the genetic basis and pathogenesis of type 1 diabetes have been studied extensively, how host responses to environmental factors might contribute to autoantibody development remains largely unknown. Here, we use longitudinal blood transcriptome sequencing data to characterize host responses in children within 12 months prior to the appearance of type 1 diabetes-linked islet autoantibodies, as well as matched control children. We report that children who present with insulin-specific autoantibodies first have distinct transcriptional profiles from those who develop GADA autoantibodies first. In particular, gene dosage-driven expression of GSTM1 is associated with GADA autoantibody positivity. Moreover, compared with controls, we observe increased monocyte and decreased B cell proportions 9-12 months prior to autoantibody positivity, especially in children who developed antibodies against insulin first. Lastly, we show that control children present transcriptional signatures consistent with robust immune responses to enterovirus infection, whereas children who later developed islet autoimmunity do not. These findings highlight distinct immune-related transcriptomic differences between case and control children prior to case progression to islet autoimmunity and uncover deficient antiviral response in children who later develop islet autoimmunity.

eQTL mapping in fetal-like pancreatic progenitor cells reveals early developmental insights into diabetes risk

The impact of genetic regulatory variation active in early pancreatic development on adult pancreatic disease and traits is not well understood. Here, we generate a panel of 107 fetal-like iPSC-derived pancreatic progenitor cells (iPSC-PPCs) from whole genome-sequenced individuals and identify 4065 genes and 4016 isoforms whose expression and/or alternative splicing are affected by regulatory variation. We integrate eQTLs identified in adult islets and whole pancreas samples, which reveal 1805 eQTL associations that are unique to the fetal-like iPSC-PPCs and 1043 eQTLs that exhibit regulatory plasticity across the fetal-like and adult pancreas tissues. Colocalization with GWAS risk loci for pancreatic diseases and traits show that some putative causal regulatory variants are active only in the fetal-like iPSC-PPCs and likely influence disease by modulating expression of disease-associated genes in early development, while others with regulatory plasticity likely exert their effects in both the fetal and adult pancreas by modulating expression of different disease genes in the two developmental stages.