Identification of SARS-CoV-2 inhibitors using lung and colonic organoids.

There is an urgent need to create novel models using human disease-relevant cells to study severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) biology and to facilitate drug screening. Here, as SARS-CoV-2 primarily infects the respiratory tract, we developed a lung organoid model using human pluripotent stem cells (hPSC-LOs). The hPSC-LOs (particularly alveolar type-II-like cells) are permissive to SARS-CoV-2 infection, and showed robust induction of chemokines following SARS-CoV-2 infection, similar to what is seen in patients with COVID-19. Nearly 25% of these patients also have gastrointestinal manifestations, which are associated with worse COVID-19 outcomes1. We therefore also generated complementary hPSC-derived colonic organoids (hPSC-COs) to explore the response of colonic cells to SARS-CoV-2 infection. We found that multiple colonic cell types, especially enterocytes, express ACE2 and are permissive to SARS-CoV-2 infection. Using hPSC-LOs, we performed a high-throughput screen of drugs approved by the FDA (US Food and Drug Administration) and identified entry inhibitors of SARS-CoV-2, including imatinib, mycophenolic acid and quinacrine dihydrochloride. Treatment at physiologically relevant levels of these drugs significantly inhibited SARS-CoV-2 infection of both hPSC-LOs and hPSC-COs. Together, these data demonstrate that hPSC-LOs and hPSC-COs infected by SARS-CoV-2 can serve as disease models to study SARS-CoV-2 infection and provide a valuable resource for drug screening to identify candidate COVID-19 therapeutics.

Modeling islet enhancers using deep learning identifies candidate causal variants at loci associated with T2D and glycemic traits.

Genetic association studies have identified hundreds of independent signals associated with type 2 diabetes (T2D) and related traits. Despite these successes, the identification of specific causal variants underlying a genetic association signal remains challenging. In this study, we describe a deep learning (DL) method to analyze the impact of sequence variants on enhancers. Focusing on pancreatic islets, a T2D relevant tissue, we show that our model learns islet-specific transcription factor (TF) regulatory patterns and can be used to prioritize candidate causal variants. At 101 genetic signals associated with T2D and related glycemic traits where multiple variants occur in linkage disequilibrium, our method nominates a single causal variant for each association signal, including three variants previously shown to alter reporter activity in islet-relevant cell types. For another signal associated with blood glucose levels, we biochemically test all candidate causal variants from statistical fine-mapping using a pancreatic islet beta cell line and show biochemical evidence of allelic effects on TF binding for the model-prioritized variant. To aid in future research, we publicly distribute our model and islet enhancer perturbation scores across ~67 million genetic variants. We anticipate that DL methods like the one presented in this study will enhance the prioritization of candidate causal variants for functional studies.

Human organoid models to study SARS-CoV-2 infection.

Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is one of the deadliest pandemics in history. SARS-CoV-2 not only infects the respiratory tract, but also causes damage to many organs. Organoids, which can self-renew and recapitulate the various physiology of different organs, serve as powerful platforms to model COVID-19. In this Perspective, we overview the current effort to apply both human pluripotent stem cell-derived organoids and adult organoids to study SARS-CoV-2 tropism, host response and immune cell-mediated host damage, and perform drug discovery and vaccine development. We summarize the technologies used in organoid-based COVID-19 research, discuss the remaining challenges and provide future perspectives in the application of organoid models to study SARS-CoV-2 and future emerging viruses.

Checkpoint kinase 2 controls insulin secretion and glucose homeostasis.

After the discovery of insulin, a century ago, extensive work has been done to unravel the molecular network regulating insulin secretion. Here we performed a chemical screen and identified AZD7762, a compound that potentiates glucose-stimulated insulin secretion (GSIS) of a human ß cell line, healthy and type 2 diabetic (T2D) human islets and primary cynomolgus macaque islets. In vivo studies in diabetic mouse models and cynomolgus macaques demonstrated that AZD7762 enhances GSIS and improves glucose tolerance. Furthermore, genetic manipulation confirmed that ablation of CHEK2 in human ß cells results in increased insulin secretion. Consistently, high-fat-diet-fed Chk2-/- mice show elevated insulin secretion and improved glucose clearance. Finally, untargeted metabolic profiling demonstrated the key role of the CHEK2-PP2A-PLK1-G6PD-PPP pathway in insulin secretion. This study successfully identifies a previously unknown insulin secretion regulating pathway that is conserved across rodents, cynomolgus macaques and human ß cells in both healthy and T2D conditions.

Single-cell transcriptomic profiling of human pancreatic islets reveals genes responsive to glucose exposure over 24 h.

AIMS/HYPOTHESIS: Disruption of pancreatic islet function and glucose homeostasis can lead to the development of sustained hyperglycaemia, beta cell glucotoxicity and subsequently type 2 diabetes. In this study, we explored the effects of in vitro hyperglycaemic conditions on human pancreatic islet gene expression across 24 h in six pancreatic cell types: alpha; beta; gamma; delta; ductal; and acinar. We hypothesised that genes associated with hyperglycaemic conditions may be relevant to the onset and progression of diabetes. METHODS: We exposed human pancreatic islets from two donors to low (2.8 mmol/l) and high (15.0 mmol/l) glucose concentrations over 24 h in vitro. To assess the transcriptome, we performed single-cell RNA-seq (scRNA-seq) at seven time points. We modelled time as both a discrete and continuous variable to determine momentary and longitudinal changes in transcription associated with islet time in culture or glucose exposure. Additionally, we integrated genomic features and genetic summary statistics to nominate candidate effector genes. For three of these genes, we functionally characterised the effect on insulin production and secretion using CRISPR interference to knock down gene expression in EndoC-ßH1 cells, followed by a glucose-stimulated insulin secretion assay. RESULTS: In the discrete time models, we identified 1344 genes associated with time and 668 genes associated with glucose exposure across all cell types and time points. In the continuous time models, we identified 1311 genes associated with time, 345 genes associated with glucose exposure and 418 genes associated with interaction effects between time and glucose across all cell types. By integrating these expression profiles with summary statistics from genetic association studies, we identified 2449 candidate effector genes for type 2 diabetes, HbA1c, random blood glucose and fasting blood glucose. Of these candidate effector genes, we showed that three (ERO1B, HNRNPA2B1 and RHOBTB3) exhibited an effect on glucose-stimulated insulin production and secretion in EndoC-ßH1 cells. CONCLUSIONS/INTERPRETATION: The findings of our study provide an in-depth characterisation of the 24 h transcriptomic response of human pancreatic islets to glucose exposure at a single-cell resolution. By integrating differentially expressed genes with genetic signals for type 2 diabetes and glucose-related traits, we provide insights into the molecular mechanisms underlying glucose homeostasis. Finally, we provide functional evidence to support the role of three candidate effector genes in insulin secretion and production. DATA AVAILABILITY: The scRNA-seq data from the 24 h glucose exposure experiment performed in this study are available in the database of Genotypes and Phenotypes (dbGap; https://www.ncbi.nlm.nih.gov/gap/ ) with accession no. phs001188.v3.p1. Study metadata and summary statistics for the differential expression, gene set enrichment and candidate effector gene prediction analyses are available in the Zenodo data repository ( https://zenodo.org/ ) under accession number 11123248. The code used in this study is publicly available at https://github.com/CollinsLabBioComp/publication-islet_glucose_timecourse .

SARS-CoV-2 Infection Induces Ferroptosis of Sinoatrial Node Pacemaker Cells.

BACKGROUND: Increasing evidence suggests that cardiac arrhythmias are frequent clinical features of coronavirus disease 2019 (COVID-19). Sinus node damage may lead to bradycardia. However, it is challenging to explore human sinoatrial node (SAN) pathophysiology due to difficulty in isolating and culturing human SAN cells. Embryonic stem cells (ESCs) can be a source to derive human SAN-like pacemaker cells for disease modeling. METHODS: We used both a hamster model and human ESC (hESC)-derived SAN-like pacemaker cells to explore the impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection on the pacemaker cells of the heart. In the hamster model, quantitative real-time polymerase chain reaction and immunostaining were used to detect viral RNA and protein, respectively. We then created a dual knock-in SHOX2:GFP;MYH6:mCherry hESC reporter line to establish a highly efficient strategy to derive functional human SAN-like pacemaker cells, which was further characterized by single-cell RNA sequencing. Following exposure to SARS-CoV-2, quantitative real-time polymerase chain reaction, immunostaining, and RNA sequencing were used to confirm infection and determine the host response of hESC-SAN-like pacemaker cells. Finally, a high content chemical screen was performed to identify drugs that can inhibit SARS-CoV-2 infection, and block SARS-CoV-2-induced ferroptosis. RESULTS: Viral RNA and spike protein were detected in SAN cells in the hearts of infected hamsters. We established an efficient strategy to derive from hESCs functional human SAN-like pacemaker cells, which express pacemaker markers and display SAN-like action potentials. Furthermore, SARS-CoV-2 infection causes dysfunction of human SAN-like pacemaker cells and induces ferroptosis. Two drug candidates, deferoxamine and imatinib, were identified from the high content screen, able to block SARS-CoV-2 infection and infection-associated ferroptosis. CONCLUSIONS: Using a hamster model, we showed that primary pacemaker cells in the heart can be infected by SARS-CoV-2. Infection of hESC-derived functional SAN-like pacemaker cells demonstrates ferroptosis as a potential mechanism for causing cardiac arrhythmias in patients with COVID-19. Finally, we identified candidate drugs that can protect the SAN cells from SARS-CoV-2 infection.

Mechanisms of Lung Injury Induced by SARS-CoV-2 Infection.

The lung is the major target organ of SARS-CoV-2 infection, which causes COVID-19. Here, we outline the multistep mechanisms of lung epithelial and endothelial injury induced by SARS-CoV-2: direct viral infection, chemokine/cytokine-mediated damage, and immune cell-mediated lung injury. Finally, we discuss the recent progress in terms of antiviral therapeutics as well as the development of anti-inflammatory or immunomodulatory therapeutic approaches. This review also provides a systematic overview of the models for studying SARS-CoV-2 infection and discusses how an understanding of mechanisms of lung injury will help identify potential targets for future drug development to mitigate lung injury.

An Immuno-Cardiac Model for Macrophage-Mediated Inflammation in COVID-19 Hearts.

[Figure: see text].

Genetic Alterations of NF-κB and Its Regulators: A Rich Platform to Advance Colorectal Cancer Diagnosis and Treatment.

Colorectal cancer (CRC) is the third leading cause of cancer mortality in the United States, with an estimated 52,000 deaths in 2023. Though significant progress has been made in both diagnosis and treatment of CRC in recent years, genetic heterogeneity of CRC-the culprit for possible CRC relapse and drug resistance, is still an insurmountable challenge. Thus, developing more effective therapeutics to overcome this challenge in new CRC treatment strategies is imperative. Genetic and epigenetic changes are well recognized to be responsible for the stepwise development of CRC malignancy. In this review, we focus on detailed genetic alteration information about the nuclear factor (NF)-κB signaling, including both NF-κB family members, and their regulators, such as protein arginine methyltransferase 5 (PRMT5), and outer dynein arm docking complex subunit 2 (ODAD2, also named armadillo repeat-containing 4, ARMC4), etc., in CRC patients. Moreover, we provide deep insight into different CRC research models, with a particular focus on patient-derived xenografts (PDX) and organoid models, and their potential applications in CRC research. Genetic alterations on NF-κB signaling components are estimated to be more than 50% of the overall genetic changes identified in CRC patients collected by cBioportal for Cancer Genomics; thus, emphasizing its paramount importance in CRC progression. Consequently, various genetic alterations on NF-κB signaling may hold great promise for novel therapeutic development in CRC. Future endeavors may focus on utilizing CRC models (e.g., PDX or organoids, or isogenic human embryonic stem cell (hESC)-derived colonic cells, or human pluripotent stem cells (hPSC)-derived colonic organoids, etc.) to further uncover the underpinning mechanism of these genetic alterations in NF-κB signaling in CRC progression. Moreover, establishing platforms for drug discovery in dishes, and developing Biobanks, etc., may further pave the way for the development of innovative personalized medicine to treat CRC in the future.

The small molecule DIPQUO promotes osteogenic differentiation via inhibition of glycogen synthase kinase 3-beta signaling.

Bone fractures are common impact injuries typically resolved through natural processes of osteogenic regeneration and bone remodeling, restoring the biological and mechanical function. However, dysfunctionality in bone healing and repair often arises in the context of aging-related chronic disorders, such as Alzheimer's disease (AD). There is unmet need for effective pharmacological modulators of osteogenic differentiation and an opportunity to probe the complex links between bone biology and cognitive disorders. We previously discovered the small molecule DIPQUO, which promotes osteoblast differentiation and bone mineralization in mouse and human cell culture models, and in zebrafish developmental and regenerative models. Here, we examined the detailed function of this molecule. First, we used kinase profiling, cellular thermal shift assays, and functional studies to identify glycogen synthase kinase 3-beta (GSK3-ß) inhibition as a mechanism of DIPQUO action. Treatment of mouse C2C12 myoblasts with DIPQUO promoted alkaline phosphatase expression and activity, which could be enhanced synergistically by treatment with other GSK3-ß inhibitors. Suppression of the expression or function of GSK3-ß attenuated DIPQUO-dependent osteogenic differentiation. In addition, DIPQUO synergized with GSK3-ß inhibitors to stimulate expression of osteoblast genes in human multipotent progenitors. Accordingly, DIPQUO promoted accumulation and activation of ß-catenin. Moreover, DIPQUO suppressed activation of tau microtubule-associated protein, an AD-related effector of GSK3-ß signaling. Therefore, DIPQUO has potential as both a lead candidate for bone therapeutic development and a pharmacological modulator of GSK3-ß signaling in cell culture and animal models of disorders including AD.

Deriving human ENS lineages for cell therapy and drug discovery in Hirschsprung disease.

The enteric nervous system (ENS) is the largest component of the autonomic nervous system, with neuron numbers surpassing those present in the spinal cord. The ENS has been called the 'second brain' given its autonomy, remarkable neurotransmitter diversity and complex cytoarchitecture. Defects in ENS development are responsible for many human disorders including Hirschsprung disease (HSCR). HSCR is caused by the developmental failure of ENS progenitors to migrate into the gastrointestinal tract, particularly the distal colon. Human ENS development remains poorly understood owing to the lack of an easily accessible model system. Here we demonstrate the efficient derivation and isolation of ENS progenitors from human pluripotent stem (PS) cells, and their further differentiation into functional enteric neurons. ENS precursors derived in vitro are capable of targeted migration in the developing chick embryo and extensive colonization of the adult mouse colon. The in vivo engraftment and migration of human PS-cell-derived ENS precursors rescue disease-related mortality in HSCR mice (Ednrb(s-l/s-l)), although the mechanism of action remains unclear. Finally, EDNRB-null mutant ENS precursors enable modelling of HSCR-related migration defects, and the identification of pepstatin A as a candidate therapeutic target. Our study establishes the first, to our knowledge, human PS-cell-based platform for the study of human ENS development, and presents cell- and drug-based strategies for the treatment of HSCR.

Identifying FDA-approved drugs with multimodal properties against COVID-19 using a data-driven approach and a lung organoid model of SARS-CoV-2 entry.

BACKGROUND: Vaccination programs have been launched worldwide to halt the spread of COVID-19. However, the identification of existing, safe compounds with combined treatment and prophylactic properties would be beneficial to individuals who are waiting to be vaccinated, particularly in less economically developed countries, where vaccine availability may be initially limited. METHODS: We used a data-driven approach, combining results from the screening of a large transcriptomic database (L1000) and molecular docking analyses, with in vitro tests using a lung organoid model of SARS-CoV-2 entry, to identify drugs with putative multimodal properties against COVID-19. RESULTS: Out of thousands of FDA-approved drugs considered, we observed that atorvastatin was the most promising candidate, as its effects negatively correlated with the transcriptional changes associated with infection. Atorvastatin was further predicted to bind to SARS-CoV-2's main protease and RNA-dependent RNA polymerase, and was shown to inhibit viral entry in our lung organoid model. CONCLUSIONS: Small clinical studies reported that general statin use, and specifically, atorvastatin use, are associated with protective effects against COVID-19. Our study corroborrates these findings and supports the investigation of atorvastatin in larger clinical studies. Ultimately, our framework demonstrates one promising way to fast-track the identification of compounds for COVID-19, which could similarly be applied when tackling future pandemics.

Multifunctional in vivo imaging of pancreatic islets during diabetes development.

Pancreatic islet dysfunction leading to insufficient glucose-stimulated insulin secretion triggers the clinical onset of diabetes. How islet dysfunction develops is not well understood at the cellular level, partly owing to the lack of approaches to study single islets longitudinally in vivo Here, we present a noninvasive, high-resolution system to quantitatively image real-time glucose metabolism from single islets in vivo, currently not available with any other method. In addition, this multifunctional system simultaneously reports islet function, proliferation, vasculature and macrophage infiltration in vivo from the same set of images. Applying our method to a longitudinal high-fat diet study revealed changes in islet function as well as alternations in islet microenvironment. More importantly, this label-free system enabled us to image real-time glucose metabolism directly from single human islets in vivo for the first time, opening the door to noninvasive longitudinal in vivo studies of healthy and diabetic human islets.

Dynamic self-organization of microwell-aggregated cellular mixtures.

Cells with different cohesive properties self-assemble in a spatiotemporal and context-dependent manner. Previous studies on cell self-organization mainly focused on the spontaneous structural development within a short period of time during which the cell numbers remained constant. However the effect of cell proliferation over time on the self-organization of cells is largely unexplored. Here, we studied the spatiotemporal dynamics of self-organization of a co-culture of MDA-MB-231 and MCF10A cells seeded in a well defined space (i.e. non-adherent microfabricated wells). When cell-growth was chemically inhibited, high cohesive MCF10A cells formed a core surrounded by low cohesive MDA-MB-231 cells on the periphery, consistent with the differential adhesion hypothesis (DAH). Interestingly, this aggregate morphology was completely inverted when the cells were free to grow. At an initial seeding ratio of 1 : 1 (MDA-MB-231 : MCF10A), the fast growing MCF10A cells segregated in the periphery while the slow growing MDA-MB-231 cells stayed in the core. Another morphology developed at an inequal seeding ratio (4 : 1), that is, the cell mixtures developed a side-by-side aggregate morphology. We conclude that the cell self-organization depends not only on the cell cohesive properties but also on the cell seeding ratio and proliferation. Furthermore, by taking advantage of the cell self-organization, we purified human embryonic stem cells-derived pancreatic progenitors (hESCs-PPs) from co-cultured feeder cells without using any additional tools or labels.

The efficacy of coaxial percutaneous iodine-125 seed implantation combined with arterial infusion chemotherapy for advanced pancreatic cancer: a randomized clinical trial.

BACKGROUND: This study aimed to evaluate the clinical efficacy of coaxial percutaneous Iodine-125 (125I) seed implantation in combination with arterial infusion chemotherapy for the treatment of advanced pancreatic cancer (PC) through a randomized controlled trial. METHODS: A total of 101 patients with advanced PC were randomized into two groups: control group treated with systemic intravenous chemotherapy and experimental group that received 125I seed implantation in combination with arterial infusion chemotherapy. Outcomes, including tumor control, abdominal pain relief, and survival time were compared between these two groups (Trial Registration No. KYKT2018-65). RESULTS: Pretreatment abdominal pain scores were comparable between the two groups, whereas the abdominal pain scores at 1- and 3-month post-treatment were significantly lower in the control group than those in the experimental group (1-month: 3.74 ± 1.54 vs. 4.48 ± 1.46, p = .015; 3-month: 3.64 ± 2.21 vs. 5.40 ± 1.56, p < .001). At 3-month post-treatment, computed tomography (CT) scan revealed a significantly higher disease control rate in the experimental group than that in the control group (94.0% vs. 74.5%, p = .007). The median survival time in the experimental group was significantly longer than that in the control group (15-month vs. 9-month, p < .001). CONCLUSION: The combination of coaxial percutaneous 125I seed implantation with arterial infusion chemotherapy could significantly alleviate abdominal pain, improve tumor control rates, and prolong survival time in patients with advanced PC.

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.

DAXX is associated with early recurrence of pancreatic neuroendocrine tumors after R0 resection.

INTRODUCTION: ATRX, DAXX, MEN1, and PTEN mutations are proposed drivers of pancreatic neuroendocrine tumor tumorigenesis and independent prognostic factors for metastasis and mortality. However, their implications after R0 resection remain debated. Thus, we sought to identify genomic signatures of pancreatic neuroendocrine tumor disease-specific mortality and recurrence after surgery for curative intent. METHODS: Pancreatic neuroendocrine tumor patients who underwent whole exome sequencing with available survival data were identified using cBioPortal. Clinicopathologic variables, genomics, and outcomes were analyzed. RESULTS: Seventy patients who underwent R0 resection were identified. Forty-five of 70 patients were disease free at last follow-up, whereas 25 of 70 patients had disease-specific mortality or recurrent disease and therefore were categorized as part of the recurrent cohort. There were no significant differences in age (P = .245), sex (P = .201), or median follow-up (38.9 vs 33.7 months, P = .122) between groups. Clinicopathologically, the recurrent cohort had significantly greater tumor size (median 5.0 cm vs 3.2 cm, P = .012) and were more likely to have vascular invasion (88% vs 40%, P = .000), positive lymph nodes (68.0% vs 35.6%, P = .013), and metastatic disease (44% vs 4.4%, P < .000). For both cohorts, most tumors were well or moderately differentiated. Tumor mutation burden was greater in the recurrent cohort (median 0.77 vs 0.43 mutations/Mb, P = .004). DAXX mutations were more frequent in the recurrent cohort (36% vs 11%, P = .026) and in those with vascular invasion (51% vs 92%, P = .010). CONCLUSION: Our analysis demonstrated the prognostic significance of DAXX mutations after curative-intent surgery. Future studies investigating DAXX mutations as a biomarker for aggressive features to guide treatment are warranted.

The Precise Basecalling of Short-Read Nanopore Sequencing.

The nanopore sequencing of short sequences, whose lengths are typically less than 0.3kb therefore comparable with Illumina sequencing techniques, has recently gained wide attention. Here, we design a scheme for training nanopore basecallers that are specialized for short biomolecules. With bioengineered RNA (BioRNA) molecules as examples, we demonstrate the superior accuracy of basecallers trained by our scheme.

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.