Interpreting type 1 diabetes risk with genetics and single-cell epigenomics

Where AIRE we now? Where AIRE we going?

PURPOSE OF REVIEW

The purpose of the review is to describe the most recent advancement in understanding of the pivotal role of autoimmune regulator ( AIRE ) gene expression in central and peripheral tolerance, and the implications of its impairment in the genetic and pathogenesis of autoimmune polyendocrinopathy-candidiasis-ectodermal dystrophy (APECED) manifestations with insight into possible treatment options.

RECENT FINDINGS

AIRE gene expression has an important role of central and peripheral tolerance. Different AIRE gene mutations cause APECED, whereas polymorphisms and some variants may be implicated in development of other more frequently autoimmune diseases. Impaired negative T cell selection, reduction of T regulatory function, altered germinal center response, activated B cells and production of autoantibodies explain the development of autoimmunity in APECED. Recent data suggest that an excessive interferon-γ response may be the primer driver of the associated organ damage. Therefore, Janus kinase (JAK)-inhibitors may be promising therapies for treatment of broad spectrum of manifestations.

SUMMARY

AIRE has a pivotal role in immune tolerance. Disruption of this delicate equilibrium results in complex immune perturbation, ranging from severe autoimmunity, like APECED, to more common organ-specific disorders. Therefore, a deeper understanding of the correlation between AIRE function and clinical phenotype is warranted given the potential translational implication in clinical practice.

Multi-omic human pancreatic islet endoplasmic reticulum and cytokine stress response mapping provides type 2 diabetes genetic insights

Endoplasmic reticulum (ER) and inflammatory stress responses contribute to islet dysfunction in type 2 diabetes (T2D). Comprehensive genomic understanding of these human islet stress responses and whether T2D-associated genetic variants modulate them is lacking. Here, comparative transcriptome and epigenome analyses of human islets exposed ex vivo to these stressors revealed 30% of expressed genes and 14% of islet cis-regulatory elements (CREs) as stress responsive, modulated largely in an ER- or cytokine-specific fashion. T2D variants overlapped 86 stress-responsive CREs, including 21 induced by ER stress. We linked the rs6917676-T T2D risk allele to increased islet ER-stress-responsive CRE accessibility and allele-specific β cell nuclear factor binding. MAP3K5, the ER-stress-responsive putative rs6917676 T2D effector gene, promoted stress-induced β cell apoptosis. Supporting its pro-diabetogenic role, MAP3K5 expression correlated inversely with human islet β cell abundance and was elevated in T2D β cells. This study provides genome-wide insights into human islet stress responses and context-specific T2D variant effects.

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.

Examining the liver-pancreas crosstalk reveals a role for the molybdenum cofactor in β-cell regeneration

Regeneration of insulin-producing β-cells is an alternative avenue to manage diabetes, and it is crucial to unravel this process in vivo during physiological responses to the lack of β-cells. Here, we aimed to characterize how hepatocytes can contribute to β-cell regeneration, either directly or indirectly via secreted proteins or metabolites, in a zebrafish model of β-cell loss. Using lineage tracing, we show that hepatocytes do not directly convert into β-cells even under extreme β-cell ablation conditions. A transcriptomic analysis of isolated hepatocytes after β-cell ablation displayed altered lipid- and glucose-related processes. Based on the transcriptomics, we performed a genetic screen that uncovers a potential role of the molybdenum cofactor (Moco) biosynthetic pathway in β-cell regeneration and glucose metabolism in zebrafish. Consistently, molybdenum cofactor synthesis 2 (Mocs2) haploinsufficiency in mice indicated dysregulated glucose metabolism and liver function. Together, our study sheds light on the liver-pancreas crosstalk and suggests that the molybdenum cofactor biosynthesis pathway should be further studied in relation to glucose metabolism and diabetes.

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.

Spatially resolved epigenome sequencing via Tn5 transposition and deterministic DNA barcoding in tissue

Spatial epigenetic mapping of tissues enables the study of gene regulation programs and cellular functions with the dependency on their local tissue environment. Here we outline a complete procedure for two spatial epigenomic profiling methods: spatially resolved genome-wide profiling of histone modifications using in situ cleavage under targets and tagmentation (CUT&Tag) chemistry (spatial-CUT&Tag) and transposase-accessible chromatin sequencing (spatial-ATAC-sequencing) for chromatin accessibility. Both assays utilize in-tissue Tn5 transposition to recognize genomic DNA loci followed by microfluidic deterministic barcoding to incorporate spatial address codes. Furthermore, these two methods do not necessitate prior knowledge of the transcription or epigenetic markers for a given tissue or cell type but permit genome-wide unbiased profiling pixel-by-pixel at the 10 μm pixel size level and single-base resolution. To support the widespread adaptation of these methods, details are provided in five general steps: (1) sample preparation; (2) Tn5 transposition in spatial-ATAC-sequencing or antibody-controlled pA-Tn5 tagmentation in CUT&Tag; (3) library preparation; (4) next-generation sequencing; and (5) data analysis using our customed pipelines available at: https://github.com/dyxmvp/Spatial_ATAC-seq and https://github.com/dyxmvp/spatial-CUT-Tag . The whole procedure can be completed on four samples in 2-3 days. Familiarity with basic molecular biology and bioinformatics skills with access to a high-performance computing environment are required. A rudimentary understanding of pathology and specimen sectioning, as well as deterministic barcoding in tissue-specific skills (e.g., design of a multiparameter barcode panel and creation of microfluidic devices), are also advantageous. In this protocol, we mainly focus on spatial profiling of tissue region-specific epigenetic landscapes in mouse embryos and mouse brains using spatial-ATAC-sequencing and spatial-CUT&Tag, but these methods can be used for other species with no need for species-specific probe design.

Autoimmune Diseases and Risk of Non-Hodgkin Lymphoma: A Mendelian Randomisation Study

BACKGROUND

Non-Hodgkin lymphoma (NHL) is one of the most common haematologic malignancies in the world. Despite substantial efforts to identify causes and risk factors for NHL, its aetiology is largely unclear. Autoimmune diseases have long been considered potential risk factors for NHL. We carried out Mendelian randomisation (MR) analyses to examine whether genetically predicted susceptibility to ten autoimmune diseases (Behçet's disease, coeliac disease, dermatitis herpetiformis, lupus, psoriasis, rheumatoid arthritis, sarcoidosis, Sjögren's syndrome, systemic sclerosis, and type 1 diabetes) is associated with risk of NHL.

METHODS

Two-sample MR was performed using publicly available summary statistics from cohorts of European ancestry. For NHL and four NHL subtypes, we used data from UK Biobank, Kaiser Permanente cohorts, and FinnGen studies.

RESULTS

Negative associations between type 1 diabetes and sarcoidosis and the risk of NHL were observed (odds ratio [OR] 0.95, 95% confidence interval [CI]: 0.92-0.98, p = 5 × 10-3, and OR 0.92, 95% CI: 0.85-0.99, p = 2.8 × 10-2, respectively). These findings were supported by the sensitivity analyses accounting for potential pleiotropy and weak instrument bias. No significant associations were found between the other eight autoimmune diseases and NHL risk.

CONCLUSION

These findings suggest that genetically predicted susceptibility to type 1 diabetes, and to some extent sarcoidosis, might reduce the risk of NHL. However, future studies with different datasets, approaches, and populations are warranted to further examine the potential associations between these autoimmune diseases and the risk of NHL.

Uncovering genetic loci and biological pathways associated with age-related cataracts through GWAS meta-analysis

Age-related cataracts is a highly prevalent eye disorder that results in the clouding of the crystalline lens and is one of the leading causes of visual impairment and blindness. The disease is influenced by multiple factors including genetics, prolonged exposure to ultraviolet radiation, and a history of diabetes. However, the extent to which each of these factors contributes to the development of cataracts remains unclear. Our study identified 101 independent genome-wide significant loci, 57 of which are novel. We identified multiple genes and biological pathways associated with the cataracts, including four drug-gene interactions. Our results suggest a causal association between type 1 diabetes and cataracts. Also, we highlighted a surrogate measure of UV light exposure as a marker of cataract risk in adults.

A ONECUT1 regulatory, non-coding region in pancreatic development and diabetes

In a patient with permanent neonatal syndromic diabetes clinically similar to cases with ONECUT1 biallelic mutations, we identified a disease-causing deletion located upstream of ONECUT1. Through genetic, genomic, and functional studies, we identified a crucial regulatory region acting as an enhancer of ONECUT1 specifically during pancreatic development. This enhancer region contains a low-frequency variant showing a strong association with type 2 diabetes and other glycemic traits, thus extending the contribution of this region to common forms of diabetes. Clinical relevance is provided by experimentally tailored therapy options for patients carrying ONECUT1 coding or regulatory mutations.

A regulatory variant rs9379874 in T1D risk region 6p22.2 affects BTN3A1 expression regulating T cell function

OBJECTIVE

Genome-wide association studies (GWAS) have identified that 6p22.2 region is associated with type 1 diabetes (T1D) risk in the Chinese Han population. This study aims to reveal associations between this risk region and T1D subgroups and related clinical features, and further identify causal variant(s) and target gene(s) in this region.

METHODS

2608 T1D and 4814 healthy controls were recruited from East, Central, and South China. Baseline data and genotyping for rs4320356 were collected. The most likely causal variant and gene were identified by bioinformatics analysis, dual-luciferase reporter assays, expression quantitative trait loci (eQTL), and functional annotation of the non-coding region within the 6p22.2 region.

RESULTS

The leading variant rs4320356 in the 6p22.2 region was associated with T1D risk in the Chinese and Europeans. However, this variant was not significantly associated with islet function or autoimmunity. In silico analysis suggested rs9379874 was the most potential causal variant for T1D risk among thymus, spleen, and T cells, overlapping with the enhancer-related histone mark in multiple T cell subsets. Dual luciferase reporter assay and eQTL showed that the T allele of rs9379874 increased BTN3A1 expression by binding to FOXA1. Public single-cell RNA sequencing analysis indicated that BTN3A1 was related to T-cell activation, ATP metabolism, and cytokine metabolism pathways, which might contribute to T1D development.

CONCLUSION

This study indicates that a functional variant rs9379874 regulates BTN3A1 expression, expanding the genomic landscape of T1D risk and offering a potential target for developing novel therapies.

Genetics of type-1 diabetes

Type-1 diabetes is a multifactorial disease characterized by genetic and environmental factors that contribute to its development and progression. Despite progress in the management of type-1 diabetes, the final goal of curing the disease is yet to be achieved. To establish effective methods for the prevention, intervention, and cure of the disease, the molecular mechanisms and pathways involved in its development and progression should be clarified. One effective approach is to identify genes responsible for disease susceptibility and apply information obtained from the function of genes in disease etiology for the protection, intervention, and cure of type-1 diabetes. In this review, we discuss the genetic basis of type-1 diabetes, along with prospects for its prevention, intervention, and cure for type-1 diabetes.

Identifying genetic variants that influence the abundance of cell states in single-cell data

Disease risk alleles influence the composition of cells present in the body, but modeling genetic effects on the cell states revealed by single-cell profiling is difficult because variant-associated states may reflect diverse combinations of the profiled cell features that are challenging to predefine. We introduce Genotype-Neighborhood Associations (GeNA), a statistical tool to identify cell-state abundance quantitative trait loci (csaQTLs) in high-dimensional single-cell datasets. Instead of testing associations to predefined cell states, GeNA flexibly identifies the cell states whose abundance is most associated with genetic variants. In a genome-wide survey of single-cell RNA sequencing peripheral blood profiling from 969 individuals, GeNA identifies five independent loci associated with shifts in the relative abundance of immune cell states. For example, rs3003-T (P = 1.96 × 10-11) associates with increased abundance of natural killer cells expressing tumor necrosis factor response programs. This csaQTL colocalizes with increased risk for psoriasis, an autoimmune disease that responds to anti-tumor necrosis factor treatments. Flexibly characterizing csaQTLs for granular cell states may help illuminate how genetic background alters cellular composition to confer disease risk.

Thyroid Function, Diabetes, and Common Age-Related Eye Diseases: A Mendelian Randomization Study

Background: Previous Mendelian randomization (MR) studies showed an association between hypothyroidism and cataract and between high-normal free thyroxine (FT4) and late age-related macular degeneration (AMD), but not between FT4, thyroid stimulating hormone (TSH), or hyperthyroidism and diabetic retinopathy or cataract. These studies included a limited number of genetic variants for thyroid function and did not investigate autoimmune thyroid disease (AITD) or glaucoma, include bidirectional and multivariable MR (MVMR), and examine sex differences or potential mediation effects of diabetes. We aimed to address this knowledge gap. Methods: We examined the causality and directionality of the associations of AITD, and FT4 and TSH within the reference range with common age-related eye diseases (diabetic retinopathy, cataract, early and late AMD, and primary open-angle glaucoma). We conducted a bidirectional two-sample MR study utilizing publicly available genome-wide association study (GWAS) summary statistics from international consortia (ThyroidOmics, International AMD Genetics Consortium, deCODE, UK Biobank, FinnGen, and DIAGRAM). Bidirectional MR tested directionality, whereas MVMR estimated independent causal effects. Furthermore, we investigated type 1 diabetes (T1D) and type 2 diabetes (T2D) as potential mediators. Results: Genetic predisposition to AITD was associated with increased risk of diabetic retinopathy (p = 3 × 10-4), cataract (p = 3 × 10-3), and T1D (p = 1 × 10-3), but less likely T2D (p = 0.01). MVMR showed attenuated estimates for diabetic retinopathy and cataract when adjusting for T1D, but not T2D. We found pairwise bidirectional associations between AITD, T1D, and diabetic retinopathy. Genetic predisposition to both T1D and T2D increased the risk of diabetic retinopathy and cataract (p < 4 × 10-4). Moreover, genetically predicted higher FT4 within the reference range was associated with an increased risk of late AMD (p = 0.01), particularly in women (p = 7 × 10-3). However, we neither found any association between FT4 and early AMD nor between TSH and early and late AMD. No other associations were observed. Conclusions: Genetic predisposition to AITD is associated with risk of diabetic retinopathy and cataract, mostly mediated through increased T1D risk. Reciprocal associations between AITD, diabetic retinopathy, and T1D imply a shared autoimmune origin. The role of FT4 in AMD and potential sex discrepancies needs further investigation.

A cell type-aware framework for nominating non-coding variants in Mendelian regulatory disorders

Unsolved Mendelian cases often lack obvious pathogenic coding variants, suggesting potential non-coding etiologies. Here, we present a single cell multi-omic framework integrating embryonic mouse chromatin accessibility, histone modification, and gene expression assays to discover cranial motor neuron (cMN) cis-regulatory elements and subsequently nominate candidate non-coding variants in the congenital cranial dysinnervation disorders (CCDDs), a set of Mendelian disorders altering cMN development. We generate single cell epigenomic profiles for ~86,000 cMNs and related cell types, identifying ~250,000 accessible regulatory elements with cognate gene predictions for ~145,000 putative enhancers. We evaluate enhancer activity for 59 elements using an in vivo transgenic assay and validate 44 (75%), demonstrating that single cell accessibility can be a strong predictor of enhancer activity. Applying our cMN atlas to 899 whole genome sequences from 270 genetically unsolved CCDD pedigrees, we achieve significant reduction in our variant search space and nominate candidate variants predicted to regulate known CCDD disease genes MAFB, PHOX2A, CHN1, and EBF3 - as well as candidates in recurrently mutated enhancers through peak- and gene-centric allelic aggregation. This work delivers non-coding variant discoveries of relevance to CCDDs and a generalizable framework for nominating non-coding variants of potentially high functional impact in other Mendelian disorders.

Unveiling the influence of circulating immune cells count on type 1 diabetes: Insight from bidirectional Mendelian randomization

Observational studies have demonstrated an association between circulating immune cell and type 1 diabetes (T1D) risk. However, it is unknown whether this relationship is causal. Herein, we adopted a 2-sample bidirectional Mendelian randomization study to figure out whether circulating immune cell profiles causally impact T1D liability. Summary statistical data were obtained from genome-wide association study (GWAS) to investigate the causal relationship between white cell (WBC) count, 5 specific WBC count, and lymphocyte subtypes cell count and T1D risk. After false discovery rate (FDR) correction, the results indicated that lower lymphocyte cell count (odds ratio [OR] per 1 standard deviation [SD] decrease = 0.746, 95% confidence interval (CI): 0.673-0.828, PFDR = 0.036), and basophil cell count (OR per 1 SD decrease = 0.808, 95% CI: 0.700-0.932, PFDR = 0.010) were causally associated with T1D susceptibility. However, the absolute count of WBC, monocyte, neutrophil, eosinophil, and lymphocyte subtypes cell had no statistically significant effect on T1D risk. Taken together, this study indicates suggestive association between circulating immune cell count and T1D. Moreover, lower numbers of circulating lymphocyte and basophil cell were associated with the increased risk of T1D, which confirmed the immunity predisposition for T1D.

Variance quantitative trait loci reveal gene-gene interactions which alter blood traits

Gene-gene (GxG) interactions play an important role in human genetics, potentially explaining part of the "missing heritability" of polygenic traits and the variable expressivity of monogenic traits. Many GxG interactions have been identified in model organisms through experimental breeding studies, but they have been difficult to identify in human populations. To address this challenge, we applied two complementary variance QTL (vQTL)-based approaches to identify GxG interactions that contribute to human blood traits and blood-related disease risk. First, we used the previously validated genome-wide scale test for each trait in ~450,000 people in the UK Biobank and identified 4 vQTLs. Genome-wide GxG interaction testing of these vQTLs enabled discovery of novel interactions between (1) CCL24 and CCL26 for eosinophil count and plasma CCL24 and CCL26 protein levels and (2) HLA-DQA1 and HLA-DQB1 for lymphocyte count and risk of celiac disease, both of which replicated in ~140,000 NIH All of Us and ~70,000 Vanderbilt BioVU participants. Second, we used a biologically informed approach to search for vQTL in disease-relevant genes. This approach identified (1) a known interaction for hemoglobin between two pathogenic variants in HFE which cause hereditary hemochromatosis and alters risk of cirrhosis and (2) a novel interaction between the JAK2 46/1 haplotype and a variant on chromosome 14 which modifies platelet count, JAK2 V617F clonal hematopoiesis, and risk of polycythemia vera. This work identifies novel disease-relevant GxG interactions and demonstrates the utility of vQTL-based approaches in identifying GxG interactions relevant to human health at scale.

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.

Predictive Prioritization of Enhancers Associated with Pancreas Disease Risk

Genetic and epigenetic variations in regulatory enhancer elements increase susceptibility to a range of pathologies. Despite recent advances, linking enhancer elements to target genes and predicting transcriptional outcomes of enhancer dysfunction remain significant challenges. Using 3D chromatin conformation assays, we generated an extensive enhancer interaction dataset for the human pancreas, encompassing more than 20 donors and five major cell types, including both exocrine and endocrine compartments. We employed a network approach to parse chromatin interactions into enhancer-promoter tree models, facilitating a quantitative, genome-wide analysis of enhancer connectivity. With these tree models, we developed a machine learning algorithm to estimate the impact of enhancer perturbations on cell type-specific gene expression in the human pancreas. Orthogonal to our computational approach, we perturbed enhancer function in primary human pancreas cells using CRISPR interference and quantified the effects at the single-cell level through RNA FISH coupled with high-throughput imaging. Our enhancer tree models enabled the annotation of common germline risk variants associated with pancreas diseases, linking them to putative target genes in specific cell types. For pancreatic ductal adenocarcinoma, we found a stronger enrichment of disease susceptibility variants within acinar cell regulatory elements, despite ductal cells historically being assumed as the primary cell-of-origin. Our integrative approach-combining cell type-specific enhancer-promoter interaction mapping, computational models, and single-cell enhancer perturbation assays-produced a robust resource for studying the genetic basis of pancreas disorders.

Exocrine pancreatic inflammation in canine diabetes mellitus - An active offender?

The purpose of this review is to examine the current scientific literature regarding the interplay between the exocrine and endocrine pancreas, specifically the role of the exocrine pancreas in the pathogenesis of canine diabetes mellitus. β-cell death caused by exocrine pancreatic inflammation is thought to be an under-recognised contributor to diabetes mellitus in dogs, with up to 30 % of canine diabetic patients with concurrent evidence of pancreatitis at post-mortem examination. Current diagnostics for pancreatitis are imprecise, and treatments for both diseases individually have their own limitations: diabetes through daily insulin injections, which has both welfare and financial implications for the stakeholders, and pancreatitis through treatment of clinical signs, such as analgesia and anti-emetics, rather than targeted treatment of the underlying cause. This review will consider the evidence for exocrine pancreatic inflammation making an active contribution to pancreatic β-cell loss and insulin-deficiency diabetes in the dog and explore current and potential future diagnostic and treatment avenues to improve outcomes for these patients.

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.

Association and causality between diabetes and activin A: a two-sample Mendelian randomization study

Activin A, a cytokine belonging to the transforming growth factor-beta (TGF-β) superfamily, mediates a multifunctional signaling pathway that is essential for embryonic development, cell differentiation, metabolic regulation, and physiological equilibrium. Biomedical research using diabetes-based model organisms and cellular cultures reports evidence of different activin A levels between diabetic and control groups. Activin A is highly conserved across species and universally expressed among disparate tissues. A systematic review of published literatures on human populations reveals association of plasma activin A levels with diabetic patients in some (7) but not in others (5) of the studies. With summarized data from publicly available genome-wide association studies (GWASs), a two-sample Mendelian randomization (TSMR) analysis is conducted on the causality between the exposure and the outcome. Wald ratio estimates from single instruments are predominantly non-significant. In contrast to positive controls between diabetes and plasma cholesterol levels, inverse-variance-weighted (IVW), Egger, weighted median, and weighted mode MR methods all lead to no observed causal link between diabetes (type 1 and type 2) and plasma activin A levels. Unavailability of strong instruments prevents the reversal MR analysis of activin A on diabetes. In summary, further research is needed to confirm or deny the potential association between diabetes and plasma activin A, and to elucidate the temporal incidence of these traits in human populations. At this stage, no causality has been found between diabetes and plasma activin A based on TSMR analysis.

Postpartum depression and autoimmune disease: a bidirectional Mendelian randomization study

Purpose

The rising prevalence of postpartum depression (PPD) is harmful to women and families. While there is a growing body of evidence suggesting an association between PPD and autoimmune diseases (ADs), the direction of causality remains uncertain. Therefore, Mendelian randomization (MR) study was employed to investigate the potential causal relationship between the two.

Methods

This study utilized large-scale genome-wide association study genetic pooled data from two major databases: the IEU OpenGWAS project and the FinnGen databases. The causal analysis methods used inverse variance weighting (IVW). The weighted median, MR-Egger method, MR-PRESSO test, and the leave-one-out sensitivity test have been used to examine the results' robustness, heterogeneity, and horizontal pleiotropy.

Results

A total of 23 ADs were investigated in this study. In the IVW model, the MR study showed that PPD increased the risk of type 1 diabetes (OR , = 1.15 (1.05-1.26),p<0.01),Hashimoto's thyroiditis((OR) = 1.21 (1.09-1.34),p<0.0001),encephalitis((OR) = 1.66 (1.06-2.60),p<0.05). Reverse analysis showed that ADs could not genetically PPD. There was no significant heterogeneity or horizontal pleiotropy bias in this result.

Conclusion

Our study suggests that PPD is a risk factor for type 1 diabetes, Hashimoto's thyroiditis, and encephalitis from a gene perspective, while ADs are not a risk factor for PPD. This finding may provide new insights into prevention and intervention strategies for ADs according to PPD patients.

3D chromatin-based variant-to-gene maps across 57 human cell types reveal the cellular and genetic architecture of autoimmune disease susceptibility

A portion of the genetic basis for many common autoimmune disorders has been uncovered by genome-wide association studies (GWAS), but GWAS do not reveal causal variants, effector genes, or the cell types impacted by disease-associated variation. We have generated 3D genomic datasets consisting of promoter-focused Capture-C, Hi-C, ATAC-seq, and RNA-seq and integrated these data with GWAS of 16 autoimmune traits to physically map disease-associated variants to the effector genes they likely regulate in 57 human cell types. These 3D maps of gene cis-regulatory architecture are highly powered to identify the cell types most likely impacted by disease-associated genetic variation compared to 1D genomic features, and tend to implicate different effector genes than eQTL approaches in the same cell types. Most of the variants implicated by these cis-regulatory architectures are highly trait-specific, but nearly half of the target genes connected to these variants are shared across multiple autoimmune disorders in multiple cell types, suggesting a high level of genetic diversity and complexity among autoimmune diseases that nonetheless converge at the level of target gene and cell type. Substantial effector gene sharing led to the common enrichment of similar biological networks across disease and cell types. However, trait-specific pathways representing potential areas for disease-specific intervention were identified. To test this, we pharmacologically validated squalene synthase, a cholesterol biosynthetic enzyme encoded by the FDFT1 gene implicated by our approach in MS and SLE, as a novel immunomodulatory drug target controlling inflammatory cytokine production by human T cells. These data represent a comprehensive resource for basic discovery of gene cis-regulatory mechanisms, and the analyses reported reveal mechanisms by which autoimmune-associated variants act to regulate gene expression, function, and pathology across multiple, distinct tissues and cell types.

Circulating pancreatic enzyme levels are a causal biomarker of type 1 diabetes

Novel biomarkers of type 1 diabetes (T1D) are needed for earlier detection of disease and identifying therapeutic targets. We identified biomarkers of T1D by combining plasma cis and trans protein QTLs (pQTLs) for 2,922 proteins in the UK Biobank with a T1D genome-wide association study (GWAS) in 157k samples. T1D risk variants at over 20% of known loci colocalized with cis or trans pQTLs, and distinct sets of T1D loci colocalized with immune, pancreatic secretion, or gut-related proteins. We identified 23 proteins with evidence for a causal role in using pQTLs as genetic instruments in Mendelian Randomization which included multiple sensitivity analyses. Proteins increasing T1D risk were involved in immune processes (e.g. HLA-DRA) and, more surprisingly, T1D protective proteins were enriched in pancreatic secretions (e.g. CPA1), cholesterol metabolism (e.g. APOA1), and gut homeostasis. Genetic variants associated with plasma levels of T1D-protective pancreatic enzymes such as CPA1 were enriched in cis-regulatory elements in pancreatic exocrine and gut enteroendocrine cells, and the protective effects of CPA1 and other enzymes on T1D were consistent when using instruments specific to acinar cells. Finally, pancreatic enzymes had decreased acinar expression in T1D, including CPA1 which was altered prior to onset. Together, these results reveal causal biomarkers and highlight processes in the exocrine pancreas, immune system, and gut that modulate T1D risk.

Single cell multiome profiling of pancreatic islets reveals physiological changes in cell type-specific regulation associated with diabetes risk

Physiological variability in pancreatic cell type gene regulation and the impact on diabetes risk is poorly understood. In this study we mapped gene regulation in pancreatic cell types using single cell multiomic (joint RNA-seq and ATAC-seq) profiling in 28 non-diabetic donors in combination with single cell data from 35 non-diabetic donors in the Human Pancreas Analysis Program. We identified widespread associations with age, sex, BMI, and HbA1c, where gene regulatory responses were highly cell type- and phenotype-specific. In beta cells, donor age associated with hypoxia, apoptosis, unfolded protein response, and external signal-dependent transcriptional regulators, while HbA1c associated with inflammatory responses and gender with chromatin organization. We identified 10.8K loci where genetic variants were QTLs for cis regulatory element (cRE) accessibility, including 20% with lineage- or cell type-specific effects which disrupted distinct transcription factor motifs. Type 2 diabetes and glycemic trait associated variants were enriched in both phenotype- and QTL-associated beta cell cREs, whereas type 1 diabetes showed limited enrichment. Variants at 226 diabetes and glycemic trait loci were QTLs in beta and other cell types, including 40 that were statistically colocalized, and annotating target genes of colocalized QTLs revealed genes with putatively novel roles in disease. Our findings reveal diverse responses of pancreatic cell types to phenotype and genotype in physiology, and identify pathways, networks, and genes through which physiology impacts diabetes risk.

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.

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.

From genetic associations to genes: methods, applications, and challenges

Genome-wide association studies (GWASs) have identified numerous genetic loci associated with human traits and diseases. However, pinpointing the causal genes remains a challenge, which impedes the translation of GWAS findings into biological insights and medical applications. In this review, we provide an in-depth overview of the methods and technologies used for prioritizing genes from GWAS loci, including gene-based association tests, integrative analysis of GWAS and molecular quantitative trait loci (xQTL) data, linking GWAS variants to target genes through enhancer-gene connection maps, and network-based prioritization. We also outline strategies for generating context-dependent xQTL data and their applications in gene prioritization. We further highlight the potential of gene prioritization in drug repurposing. Lastly, we discuss future challenges and opportunities in this field.

Patterns of Immune Dysregulation in Bipolar Disorder

Background

Bipolar disorder is a debilitating mood disorder associated with a high risk of suicide and characterized by immune dysregulation. In this study, we used a multi-faceted approach to better distinguish the pattern of dysregulation of immune profiles in individuals with BD.

Methods

We analyzed peripheral blood mononuclear cells (bipolar disorder N=39, control N=30), serum cytokines (bipolar disorder N=86, control N=58), whole blood RNA (bipolar disorder N=25, control N=25), and whole blood DNA (bipolar disorder N=104, control N=66) to identify immune-related differences in participants diagnosed with bipolar disorder compared to controls.

Results

Flow cytometry revealed a higher proportion of monocytes in participants with bipolar disorder together with a lower proportion of T helper cells. Additionally, the levels of 18 cytokines were significantly elevated, while two were reduced in participants with bipolar disorder. Most of the cytokines altered in individuals with bipolar disorder were proinflammatory. Forty-nine genes were differentially expressed in our bipolar disorder cohort and further analyses uncovered several immune-related pathways altered in these individuals. Genetic analysis indicated variants associated with inflammatory bowel disease also influences bipolar disorder risk.

Discussion

Our findings indicate a significant immune component to bipolar disorder pathophysiology and genetic overlap with inflammatory bowel disease. This comprehensive study supports existing literature, whilst also highlighting novel immune targets altered in individuals with bipolar disorder. Specifically, multiple lines of evidence indicate differences in the peripheral representation of monocytes and T cells are hallmarks of bipolar disorder.

Diabetes mellitus-Progress and opportunities in the evolving epidemic

Diabetes, a complex multisystem metabolic disorder characterized by hyperglycemia, leads to complications that reduce quality of life and increase mortality. Diabetes pathophysiology includes dysfunction of beta cells, adipose tissue, skeletal muscle, and liver. Type 1 diabetes (T1D) results from immune-mediated beta cell destruction. The more prevalent type 2 diabetes (T2D) is a heterogeneous disorder characterized by varying degrees of beta cell dysfunction in concert with insulin resistance. The strong association between obesity and T2D involves pathways regulated by the central nervous system governing food intake and energy expenditure, integrating inputs from peripheral organs and the environment. The risk of developing diabetes or its complications represents interactions between genetic susceptibility and environmental factors, including the availability of nutritious food and other social determinants of health. This perspective reviews recent advances in understanding the pathophysiology and treatment of diabetes and its complications, which could alter the course of this prevalent disorder.

Coxsackievirus B infection invokes unique cell-type specific responses in primary human pancreatic islets

Coxsackievirus B (CVB) infection has long been considered an environmental factor precipitating Type 1 diabetes (T1D), an autoimmune disease marked by loss of insulin-producing β cells within pancreatic islets. Previous studies have shown CVB infection negatively impacts islet function and viability but do not report on how virus infection individually affects the multiple cell types present in human primary islets. Therefore, we hypothesized that the various islet cell populations have unique transcriptional responses to CVB infection. Here, we performed single-cell RNA sequencing on human cadaveric islets treated with either CVB or poly(I:C), a viral mimic, for 24 and 48 hours. Our global analysis reveals CVB differentially induces dynamic transcriptional changes associated with multiple cell processes and functions over time whereas poly(I:C) promotes an immune response that progressively increases with treatment duration. At the single-cell resolution, we find CVB infects all islet cell types at similar rates yet induces unique cell-type specific transcriptional responses with β, α, and ductal cells having the strongest response. Sequencing and functional data suggest that CVB negatively impacts mitochondrial respiration and morphology in distinct ways in β and α cells, while also promoting the generation of reactive oxygen species. We also observe an increase in the expression of the long-noncoding RNA MIR7-3HG in β cells with high viral titers and reveal its knockdown reduces gene expression of viral proteins as well as apoptosis in stem cell-derived islets. Together, these findings demonstrate a cell-specific transcriptional, temporal, and functional response to CVB infection and provide new insights into the relationship between CVB infection and T1D.

Inhibition of CD226 Co-Stimulation Suppresses Diabetes Development in the NOD Mouse by Augmenting Tregs and Diminishing Effector T Cell Function

Aims/hypothesis

Immunotherapeutics targeting T cells are crucial for inhibiting autoimmune disease progression proximal to disease onset in type 1 diabetes. A growing number of T cell-directed therapeutics have demonstrated partial therapeutic efficacy, with anti-CD3 (α-CD3) representing the only regulatory agency-approved drug capable of slowing disease progression through a mechanism involving the induction of partial T cell exhaustion. There is an outstanding need to augment the durability and effectiveness of T cell targeting by directly restraining proinflammatory T helper type 1 (Th1) and type 1 cytotoxic CD8+ T cell (Tc1) subsets, while simultaneously augmenting regulatory T cell (Treg) activity. Here, we present a novel strategy for reducing diabetes incidence in the NOD mouse model using a blocking monoclonal antibody targeting the type 1 diabetes-risk associated T cell co-stimulatory receptor, CD226.

Methods

Female NOD mice were treated with anti-CD226 between 7-8 weeks of age and then monitored for diabetes incidence and therapeutic mechanism of action.

Results

Compared to isotype-treated controls, anti-CD226 treated NOD mice showed reduced insulitis severity at 12 weeks and decreased disease incidence at 30 weeks. Flow cytometric analysis performed five weeks post-treatment demonstrated reduced proliferation of CD4+ and CD8+ effector memory T cells in spleens of anti-CD226 treated mice. Phenotyping of pancreatic Tregs revealed increased CD25 expression and STAT5 phosphorylation following anti-CD226, with splenic Tregs displaying augmented suppression of CD4+ T cell responders in vitro. Anti-CD226 treated mice exhibited reduced frequencies of islet-specific glucose-6-phosphatase catalytic subunit related protein (IGRP)-reactive CD8+ T cells in the pancreas, using both ex vivo tetramer staining and single-cell T cell receptor sequencing (scTCR-seq) approaches. 51Cr-release assays demonstrated reduced cell-mediated lysis of beta-cells by anti-CD226-treated autoreactive cytotoxic T lymphocytes.

Conclusions/interpretation

CD226 blockade reduces T cell cytotoxicity and improves Treg function, representing a targeted and rational approach for restoring immune regulation in type 1 diabetes.

Examining the Genetic Links between Clusters of Immune-mediated Diseases and Psychiatric Disorders

Importance

Autoimmune and autoinflammatory diseases have been linked to psychiatric disorders in the phenotypic and genetic literature. However, a comprehensive model that investigates the association between a broad range of psychiatric disorders and immune-mediated disease in a multivariate framework is lacking.

Objective

This study aims to establish a factor structure based on the genetic correlations of immune-mediated diseases and investigate their genetic relationships with clusters of psychiatric disorders.

Design Setting and Participants

We utilized Genomic Structural Equation Modeling (Genomic SEM) to establish a factor structure of 11 immune-mediated diseases. Genetic correlations between these immune factors were examined with five established factors across 13 psychiatric disorders representing compulsive, schizophrenia/bipolar, neurodevelopmental, internalizing, and substance use disorders. We included GWAS summary statistics of individuals of European ancestry with sample sizes from 1,223 cases for Addison's disease to 170,756 cases for major depressive disorder.

Main Outcomes and Measures

Genetic correlations between psychiatric and immune-mediated disease factors and traits to determine genetic overlap. We develop and validate a new heterogeneity metric, Q Factor , that quantifies the degree to which factor correlations are driven by more specific pairwise associations. We also estimate residual genetic correlations between pairs of psychiatric disorders and immune-mediated diseases.

Results

A four-factor model of immune-mediated diseases fit the data well and described a continuum from autoimmune to autoinflammatory diseases. The four factors reflected autoimmune, celiac, mixed pattern, and autoinflammatory diseases. Analyses revealed seven significant factor correlations between the immune and psychiatric factors, including autoimmune and mixed pattern diseases with the internalizing and substance use factors, and autoinflammatory diseases with the compulsive, schizophrenia/bipolar, and internalizing factors. Additionally, we find evidence of divergence in associations within factors as indicated by Q Factor . This is further supported by 14 significant residual genetic correlations between individual psychiatric disorders and immune-mediated diseases.

Conclusion and Relevance

Our results revealed genetic links between clusters of immune-mediated diseases and psychiatric disorders. Current analyses indicate that previously described relationships between specific psychiatric disorders and immune-mediated diseases often capture broader pathways of risk sharing indexed by our genomic factors, yet are more specific than a general association across all psychiatric disorders and immune-mediated diseases.

Non-coding variants impact cis-regulatory coordination in a cell type-specific manner

BACKGROUND

Interactions among cis-regulatory elements (CREs) play a crucial role in gene regulation. Various approaches have been developed to map these interactions genome-wide, including those relying on interindividual epigenomic variation to identify groups of covariable regulatory elements, referred to as chromatin modules (CMs). While CM mapping allows to investigate the relationship between chromatin modularity and gene expression, the computational principles used for CM identification vary in their application and outcomes.

RESULTS

We comprehensively evaluate and streamline existing CM mapping tools and present guidelines for optimal utilization of epigenome data from a diverse population of individuals to assess regulatory coordination across the human genome. We showcase the effectiveness of our recommended practices by analyzing distinct cell types and demonstrate cell type specificity of CRE interactions in CMs and their relevance for gene expression. Integration of genotype information revealed that many non-coding disease-associated variants affect the activity of CMs in a cell type-specific manner by affecting the binding of cell type-specific transcription factors. We provide example cases that illustrate in detail how CMs can be used to deconstruct GWAS loci, assess variable expression of cell surface receptors in immune cells, and reveal how genetic variation can impact the expression of prognostic markers in chronic lymphocytic leukemia.

CONCLUSIONS

Our study presents an optimal strategy for CM mapping and reveals how CMs capture the coordination of CREs and its impact on gene expression. Non-coding genetic variants can disrupt this coordination, and we highlight how this may lead to disease predisposition in a cell type-specific manner.

Causal effects of autoimmune diseases on temporomandibular disorders and the mediating pathways: a Mendelian randomization study

Background

The role of autoimmune diseases (ADs) in temporomandibular disorders (TMDs) has been emphasized in observational studies. However, whether the causation exists is unclear, and controversy remains about which specific disorder is destructive in TMDs. This Mendelian randomization (MR) study aims to estimate the causal effect of common ADs on TMDs.

Methods

Genetic data from published genome-wide association studies for fourteen common ADs, specifically multiple sclerosis (MS, N = 15,283), ankylosing spondylitis (AS, N = 22,647), asthma (N = 408,422), celiac disease (N = 15,283), Graves' disease (N = 458,620), Hashimoto thyroiditis (N = 395,640), primary biliary cirrhosis (PBC, N = 11,375), primary sclerosing cholangitis (PSC, N = 14,890), psoriasis vulgaris (N = 483,174), rheumatoid arthritis (RA, N = 417,256), systemic lupus erythematosus (SLE, N = 23,210), Type 1 diabetes (T1D, N = 520,580), inflammatory bowel disease (IBD, N = 34,652), and Sjogren's syndrome (SS, N = 407,746) were collected. Additionally, the latest summary-level data for TMDs (N = 228,812) were extracted from the FinnGen database. The overall effects of each immune traits were assessed via inverse-variance weighted (IVW), weighted median, and MR-Egger methods, and performed extensive sensitivity analyses. Finally, 731 immune cell phenotypes (N = 3,757) were analyzed for their mediating role in the significant causality.

Results

Univariable MR analyses revealed that genetically predicted RA (IVW OR: 1.12, 95% CI: 1.05-1.19, p < 0.001) and MS (IVW OR: 1.06, 95% CI: 1.03-1.10, p = 0.001) were associated with increased risk of TMDs. Two out of 731 immune cell phenotypes were identified as causal mediators in the associations of RA with TMDs, including "CD25++ CD8+ T cell % CD8+ T cell" (mediation proportion: 6.2%) and "CD3 on activated CD4 regulatory T cell" (5.4%). Additionally, "CD127 on granulocyte" mediated 10.6% of the total effect of MS on TMDs. No reverse directions, heterogeneity, and pleiotropy were detected in the analyses (p > 0.05).

Conclusion

This MR study provides new evidence regarding the causal impact of genetic predisposition to RA or MS on the increased risk of TMDs, potentially mediated by the modulation of immune cells. These findings highlight the importance for clinicians to pay more attention to patients with RA or MS when consulting for temporomandibular discomfort. The mediating role of specific immune cells is proposed but needs further investigation.

An atlas of transcribed enhancers across helper T cell diversity for decoding human diseases

Transcribed enhancer maps can reveal nuclear interactions underpinning each cell type and connect specific cell types to diseases. Using a 5' single-cell RNA sequencing approach, we defined transcription start sites of enhancer RNAs and other classes of coding and noncoding RNAs in human CD4+ T cells, revealing cellular heterogeneity and differentiation trajectories. Integration of these datasets with single-cell chromatin profiles showed that active enhancers with bidirectional RNA transcription are highly cell type-specific and that disease heritability is strongly enriched in these enhancers. The resulting cell type-resolved multimodal atlas of bidirectionally transcribed enhancers, which we linked with promoters using fine-scale chromatin contact maps, enabled us to systematically interpret genetic variants associated with a range of immune-mediated diseases.

Identification of unique cell type responses in pancreatic islets to stress

Diabetes involves the death or dysfunction of pancreatic β-cells. Analysis of bulk sequencing from human samples and studies using in vitro and in vivo models suggest that endoplasmic reticulum and inflammatory signaling play an important role in diabetes progression. To better characterize cell type-specific stress response, we perform multiplexed single-cell RNA sequencing to define the transcriptional signature of primary human islet cells exposed to endoplasmic reticulum and inflammatory stress. Through comprehensive pair-wise analysis of stress responses across pancreatic endocrine and exocrine cell types, we define changes in gene expression for each cell type under different diabetes-associated stressors. We find that β-, α-, and ductal cells have the greatest transcriptional response. We utilize stem cell-derived islets to study islet health through the candidate gene CIB1, which was upregulated under stress in primary human islets. Our findings provide insights into cell type-specific responses to diabetes-associated stress and establish a resource to identify targets for diabetes therapeutics.

Establishing evidence for immune surveillance of β-cell senescence

Cellular senescence is a programmed state of cell cycle arrest that involves a complex immunogenic secretome, eliciting immune surveillance and senescent cell clearance. Recent work has shown that a subpopulation of pancreatic β-cells becomes senescent in the context of diabetes; however, it is not known whether these cells are normally subject to immune surveillance. In this opinion article, we advance the hypothesis that immune surveillance of β-cells undergoing a senescence stress response normally limits their accumulation during aging and that the breakdown of these mechanisms is a driver of senescent β-cell accumulation in diabetes. Elucidation and therapeutic activation of immune surveillance mechanisms in the pancreas holds promise for the improvement of approaches to target stressed senescent β-cells in the treatment of diabetes.

Exocrine Pancreas in Type 1 and Type 2 Diabetes: Different Patterns of Fibrosis, Metaplasia, Angiopathy, and Adiposity

The endocrine and exocrine compartments of the pancreas are spatially related but functionally distinct. Multiple diseases affect both compartments, including type 1 diabetes (T1D), pancreatitis, cystic fibrosis, and pancreatic cancer. To better understand how the exocrine pancreas changes with age, obesity, and diabetes, we performed a systematic analysis of well-preserved tissue sections from the pancreatic head, body, and tail of organ donors with T1D (n = 20) or type 2 diabetes (T2D) (n = 25) and donors with no diabetes (ND; n = 74). Among ND donors, we found that the incidence of acinar-to-ductal metaplasia (ADM), angiopathy, and pancreatic adiposity increased with age, and ADM and adiposity incidence also increased with BMI. Compared with age- and sex-matched ND organs, T1D pancreata had greater rates of acinar atrophy and angiopathy, with fewer intralobular adipocytes. T2D pancreata had greater rates of ADM and angiopathy and a higher total number of T lymphocytes, but no difference in adipocyte number, compared with ND organs. Although total pancreatic fibrosis was increased in both T1D and T2D, the patterns were different, with periductal and perivascular fibrosis occurring more frequently in T1D pancreata and lobular and parenchymal fibrosis occurring more frequently in T2D. Thus, the exocrine pancreas undergoes distinct changes as individuals age or develop T1D or T2D.

ARTICLE HIGHLIGHTS

Oral and non-oral lichen planus show genetic heterogeneity and differential risk for autoimmune disease and oral cancer

Lichen planus (LP) is a T-cell-mediated inflammatory disease affecting squamous epithelia in many parts of the body, most often the skin and oral mucosa. Cutaneous LP is usually transient and oral LP (OLP) is most often chronic, so we performed a large-scale genetic and epidemiological study of LP to address whether the oral and non-oral subgroups have shared or distinct underlying pathologies and their overlap with autoimmune disease. Using lifelong records covering diagnoses, procedures, and clinic identity from 473,580 individuals in the FinnGen study, genome-wide association analyses were conducted on carefully constructed subcategories of OLP (n = 3,323) and non-oral LP (n = 4,356) and on the combined group. We identified 15 genome-wide significant associations in FinnGen and an additional 12 when meta-analyzed with UKBB (27 independent associations at 25 distinct genomic locations), most of which are shared between oral and non-oral LP. Many associations coincide with known autoimmune disease loci, consistent with the epidemiologic enrichment of LP with hypothyroidism and other autoimmune diseases. Notably, a third of the FinnGen associations demonstrate significant differences between OLP and non-OLP. We also observed a 13.6-fold risk for tongue cancer and an elevated risk for other oral cancers in OLP, in agreement with earlier reports that connect LP with higher cancer incidence. In addition to a large-scale dissection of LP genetics and comorbidities, our study demonstrates the use of comprehensive, multidimensional health registry data to address outstanding clinical questions and reveal underlying biological mechanisms in common but understudied diseases.

Assessment of bidirectional relationships between autoimmune diseases and primary ovarian insufficiency: insights from a bidirectional two-sample Mendelian randomization analysis

PURPOSE

The simultaneous occurrence of primary ovarian insufficiency (POI) and autoimmune diseases has been noted and debated in some epidemiological research. This bidirectional two-sample Mendelian randomization (MR) study aimed to investigate the causal relationships between autoimmune diseases and POI.

METHODS

We obtained summary-level data for ten autoimmune diseases and POI from published large-scale genome-wide association studies and the FinnGen consortium of European ancestry. A series of filtering steps was performed to discern independent genetic variants. Causal estimates were mainly calculated by the inverse variance weighting method and verified through multiple sensitivity analyses.

RESULTS

Of the ten autoimmune diseases, genetically predicted Addison's disease (odds ratio [OR] = 1.26, 95% confidence interval [CI]: 1.09-1.47, P = 0.003) and systemic lupus erythematosus (OR = 1.12, 95% CI 1.02-1.24, P = 0.021) were associated with an increased risk of POI, and sensitivity analyses confirmed the robustness of the results. In addition, there were weak associations between liability to POI and elevated risks of type 1 diabetes (OR = 1.05, 95% CI 1.00-1.10, P = 0.046) and autoimmune thyroid disease (OR = 1.03, 95% CI 1.01-1.05, P = 0.015).

CONCLUSION

This study revealed that Addison's disease and systemic lupus erythematosus are potential risk factors for POI, underscoring the necessity to consider the impact of autoimmune factors in the diagnosis and treatment of POI.

Genetically identified mediators associated with increased risk of stroke and cardiovascular disease in individuals with autism spectrum disorder

Growing evidence suggested that individuals with autism spectrum disorder (ASD) associated with stroke and cardiovascular disease (CVD). However, the causal association between ASD and the risk of stroke and CVD remains unclear. To validate this, we performed two-sample Mendelian randomization (MR) and two-step mediation MR analyses, using relevant genetic variants sourced from the largest genome-wide association studies (GWASs). Two-sample MR evidence indicated causal relationships between ASD and any stroke (OR = 1.1184, 95% CI: 1.0302-1.2142, P < 0.01), ischemic stroke (IS) (OR = 1.1157, 95% CI: 1.0237-1.2160, P = 0.01), large-artery atherosclerotic stroke (LAS) (OR = 1.2902, 95% CI: 1.0395-1.6013, P = 0.02), atrial fibrillation (AF) (OR = 1.0820, 95% CI: 1.0019-1.1684, P = 0.04), and heart failure (HF) (OR = 1.1018, 95% CI: 1.0007-1.2132, P = 0.05). Additionally, two-step mediation MR suggested that type 2 diabetes mellitus (T2DM) partially mediated this effect (OR = 1.14, 95%CI: 1.02-1.28, P = 0.03). The mediated proportion were 10.96% (95% CI: 0.58%-12.10%) for any stroke, 11.77% (95% CI: 10.58%-12.97%) for IS, 10.62% (95% CI: 8.04%-13.20%) for LAS, and 7.57% (95% CI: 6.79%-8.36%) for HF. However, no mediated effect was observed between ASD and AF risk. These findings have implications for the development of prevention strategies and interventions for stroke and CVD in patients with ASD.

Modeling type 1 diabetes progression using machine learning and single-cell transcriptomic measurements in human islets

Type 1 diabetes (T1D) is a chronic condition in which beta cells are destroyed by immune cells. Despite progress in immunotherapies that could delay T1D onset, early detection of autoimmunity remains challenging. Here, we evaluate the utility of machine learning for early prediction of T1D using single-cell analysis of islets. Using gradient-boosting algorithms, we model changes in gene expression of single cells from pancreatic tissues in T1D and non-diabetic organ donors. We assess if mathematical modeling could predict the likelihood of T1D development in non-diabetic autoantibody-positive donors. While most autoantibody-positive donors are predicted to be non-diabetic, select donors with unique gene signatures are classified as T1D. Our strategy also reveals a shared gene signature in distinct T1D-associated models across cell types, suggesting a common effect of the disease on transcriptional outputs of these cells. Our study establishes a precedent for using machine learning in early detection of T1D.

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.

Inferring causal cell types of human diseases and risk variants from candidate regulatory elements

The heritability of human diseases is extremely enriched in candidate regulatory elements (cRE) from disease-relevant cell types. Critical next steps are to infer which and how many cell types are truly causal for a disease (after accounting for co-regulation across cell types), and to understand how individual variants impact disease risk through single or multiple causal cell types. Here, we propose CT-FM and CT-FM-SNP, two methods that leverage cell-type-specific cREs to fine-map causal cell types for a trait and for its candidate causal variants, respectively. We applied CT-FM to 63 GWAS summary statistics (average N = 417K) using nearly one thousand cRE annotations, primarily coming from ENCODE4. CT-FM inferred 81 causal cell types with corresponding SNP-annotations explaining a high fraction of trait SNP-heritability (~2/3 of the SNP-heritability explained by existing cREs), identified 16 traits with multiple causal cell types, highlighted cell-disease relationships consistent with known biology, and uncovered previously unexplored cellular mechanisms in psychiatric and immune-related diseases. Finally, we applied CT-FM-SNP to 39 UK Biobank traits and predicted high confidence causal cell types for 2,798 candidate causal non-coding SNPs. Our results suggest that most SNPs impact a phenotype through a single cell type, and that pleiotropic SNPs target different cell types depending on the phenotype context. Altogether, CT-FM and CT-FM-SNP shed light on how genetic variants act collectively and individually at the cellular level to impact disease risk.

Deconvolution of polygenic risk score in single cells unravels cellular and molecular heterogeneity of complex human diseases

Polygenic risk scores (PRSs) are commonly used for predicting an individual's genetic risk of complex diseases. Yet, their implication for disease pathogenesis remains largely limited. Here, we introduce scPRS, a geometric deep learning model that constructs single-cell-resolved PRS leveraging reference single-cell chromatin accessibility profiling data to enhance biological discovery as well as disease prediction. Real-world applications across multiple complex diseases, including type 2 diabetes (T2D), hypertrophic cardiomyopathy (HCM), and Alzheimer's disease (AD), showcase the superior prediction power of scPRS compared to traditional PRS methods. Importantly, scPRS not only predicts disease risk but also uncovers disease-relevant cells, such as hormone-high alpha and beta cells for T2D, cardiomyocytes and pericytes for HCM, and astrocytes, microglia and oligodendrocyte progenitor cells for AD. Facilitated by a layered multi-omic analysis, scPRS further identifies cell-type-specific genetic underpinnings, linking disease-associated genetic variants to gene regulation within corresponding cell types. We substantiate the disease relevance of scPRS-prioritized HCM genes and demonstrate that the suppression of these genes in HCM cardiomyocytes is rescued by Mavacamten treatment. Additionally, we establish a novel microglia-specific regulatory relationship between the AD risk variant rs7922621 and its target genes ANXA11 and TSPAN14. We further illustrate the detrimental effects of suppressing these two genes on microglia phagocytosis. Our work provides a multi-tasking, interpretable framework for precise disease prediction and systematic investigation of the genetic, cellular, and molecular basis of complex diseases, laying the methodological foundation for single-cell genetics.

Autoimmune CD8+ T cells in type 1 diabetes: from single-cell RNA sequencing to T-cell receptor redirection

Type 1 diabetes (T1D) is an organ-specific autoimmune disease caused by pancreatic β cell destruction and mediated primarily by autoreactive CD8+ T cells. It has been shown that only a small number of stem cell-like β cell-specific CD8+ T cells are needed to convert normal mice into T1D mice; thus, it is likely that T1D can be cured or significantly improved by modulating or altering self-reactive CD8+ T cells. However, stem cell-type, effector and exhausted CD8+ T cells play intricate and important roles in T1D. The highly diverse T-cell receptors (TCRs) also make precise and stable targeted therapy more difficult. Therefore, this review will investigate the mechanisms of autoimmune CD8+ T cells and TCRs in T1D, as well as the related single-cell RNA sequencing (ScRNA-Seq), CRISPR/Cas9, chimeric antigen receptor T-cell (CAR-T) and T-cell receptor-gene engineered T cells (TCR-T), for a detailed and clear overview. This review highlights that targeting CD8+ T cells and their TCRs may be a potential strategy for predicting or treating T1D.

From genomic insights to clinical hope: Targeting NEU1 in IgA nephropathy

BACKGROUND

IgA Nephropathy (IgAN), the primary form of glomerulonephritis, presents significant clinical challenges due to its obscure pathogenesis and lack of targeted treatments. We conducted a proteome-wide Mendelian randomization (MR) study to identify therapeutic targets for IgAN.

METHODS

Utilizing a plasma proteome dataset comprising 4907 blood plasma proteins as the exposure variable, and renal biopsy-confirmed IgAN cases as the outcome, this study employed MR to pinpoint proteins potentially pathogenic to IgAN. The robustness of our findings was affirmed through external dataset validation, reverse causation testing, and Bayesian colocalization analysis. Additionally, we conducted phenotypic scanning and analyzed downstream metabolites to investigate candidate proteins's biological function.

RESULTS

In our study, a significant association was identified between an increase in neuraminidase 1 (NEU1) expression and the risk of IgAN. Specifically, a one standard deviation increase in NEU1 expression was associated with an odds ratio of 11.80 for the development of IgAN (95% confidence interval: 4.03-34.54). This association was substantiated across various statistical models and external validations. Colocalization analysis indicated a shared causal variant between NEU1 expression and IgAN. Furthermore, an increased influenza risk associated with NEU1 was observed, supporting the therapeutic potential of NEU1 inhibitors for IgAN. However, our study found no significant role for neuraminic acid-related metabolites in IgAN's development, suggesting an independent pathway for NEU1's influence.

CONCLUSION

This study identifies NEU1 as a promising therapeutic target for IgAN, backed by robust genetic evidence. Future research should explore NEU1's therapeutic potential in diverse populations and clinical scenarios, further establishing its role in IgAN.

Unveiling potential therapeutic targets for diabetes-induced frozen shoulder through Mendelian randomization analysis of the human plasma proteome

INTRODUCTION

This study aimed to assess the causal relationship between diabetes and frozen shoulder by investigating the target proteins associated with diabetes and frozen shoulder in the human plasma proteome through Mendelian randomization (MR) and to reveal the corresponding pathological mechanisms.

RESEARCH DESIGN AND METHODS

We employed the MR approach for the purposes of establishing: (1) the causal link between diabetes and frozen shoulder; (2) the plasma causal proteins associated with frozen shoulder; (3) the plasma target proteins associated with diabetes; and (4) the causal relationship between diabetes target proteins and frozen shoulder causal proteins. The MR results were validated and consolidated through colocalization analysis and protein-protein interaction network.

RESULTS

Our MR analysis demonstrated a significant causal relationship between diabetes and frozen shoulder. We found that the plasma levels of four proteins were correlated with frozen shoulder at the Bonferroni significance level (p<3.03E-5). According to colocalization analysis, parathyroid hormone-related protein (PTHLH) was moderately correlated with the genetic variance of frozen shoulder (posterior probability=0.68), while secreted frizzled-related protein 4 was highly correlated with the genetic variance of frozen shoulder (posterior probability=0.97). Additionally, nine plasma proteins were activated during diabetes-associated pathologies. Subsequent MR analysis of nine diabetic target proteins with four frozen shoulder causal proteins indicated that insulin receptor subunit alpha, interleukin-6 receptor subunit alpha, interleukin-1 receptor accessory protein, glutathione peroxidase 7, and PTHLH might contribute to the onset and progression of frozen shoulder induced by diabetes.

CONCLUSIONS

Our study identified a causal relationship between diabetes and frozen shoulder, highlighting the pathological pathways through which diabetes influences frozen shoulder.

Unveiling cell subpopulations in T1D mouse islets using single-cell RNA sequencing

Type 1 diabetes (T1D) is an autoimmune disease characterized by the destruction of beta cells by immune cells. The interactions among cells within the islets may be closely linked to the pathogenesis of T1D. In this study, we used single-cell RNA sequencing (scRNA-Seq) to analyze the cellular heterogeneity within the islets of a T1D mouse model. We established a T1D mouse model induced by streptozotocin and identified cell subpopulations using scRNA-Seq technology. Our results revealed 11 major cell types in the pancreatic islets of T1D mice, with heterogeneity observed in the alpha and beta cell subgroups, which may play a crucial role in the progression of T1D. Flow cytometry further confirmed a mature alpha and beta cell reduction in T1D mice. Overall, our scRNA-Seq analysis provided insights into the cellular heterogeneity of T1D islet tissue and highlighted the potential importance of alpha and beta cells in developing T1D.NEW & NOTEWORTHY In this study, we created a comprehensive single-cell atlas of pancreatic islets in a T1D mouse model using scRNA-Seq and identified 11 major cell types in the islets, highlighting the role of alpha and beta cells in T1D. This study revealed a significant reduction in the maturity alpha and beta cells in T1D mice through flow cytometry. It also demonstrated the heterogeneity of alpha and beta cells, potentially crucial for T1D progression. Overall, our scRNA-Seq analysis provided new insights for understanding and treating T1D by studying cell subtype changes and functions.