Utility of genetic risk scores in type 1 diabetes

Early Detection of Type 1 Diabetes in First-Degree Relatives in Saudi Arabia (VISION-T1D): Protocol for a Pilot Implementation Study

BACKGROUND

Type 1 diabetes (T1D) is a growing global health concern, with a notable rise in incidence in Saudi Arabia. Despite the potential benefits of early detection through screening programs, such initiatives are currently lacking in Saudi Arabia and other Arab countries.

OBJECTIVE

This study aims to evaluate the feasibility, acceptability, and cost-effectiveness of a T1D-screening program targeting high-risk individuals, specifically children with a first-degree relative diagnosed with T1D.

METHODS

The VISION-T1D program is a prospective cohort study focused on the early detection of presymptomatic T1D by screening children aged 2-18 years. The primary screening method involves testing for islet autoantibodies, including insulin autoantibodies, glutamic acid decarboxylase autoantibodies, insulinoma associated-2 autoantibodies, and zinc transporter-8 autoantibodies. Optional genetic testing, including human leukocyte antigen phenotyping and the genetic risk score, is offered. Outcomes include the feasibility of the screening process, prevalence of early-stage T1D, psychological impacts, educational intervention effectiveness, progression rates to stage-3 T1D, and economic viability.

RESULTS

The VISION-T1D program began in May 2024. As of December 2024, a total of 176 families have been enrolled. Data collection will continue until April 2025, with final data analysis projected for mid-2025.

CONCLUSIONS

The VISION-T1D study provides a practical approach to T1D screening tailored to the health care landscape of Saudi Arabia. The insights gained from this pilot program will inform the development of a national, population-based screening initiative designed to reduce diabetic ketoacidosis at diagnosis, improve long-term outcomes, and alleviate the economic burden of T1D. The VISION-T1D initiative could also serve as a scalable and sustainable model that can be adopted internationally, contributing to global efforts to manage and prevent T1D.

TRIAL REGISTRATION

ClinicalTrials.gov NCT06513247; https://clinicaltrials.gov/study/NCT06513247.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/70575.

Immunomodulatory agents and cell therapy for patients with type 1 diabetes

Type 1 diabetes (TID) is a chronic disease caused by autoimmune destruction of pancreatic β-cells, that progresses in three stages: 1) stage 1: β-cell autoimmunity + normoglycemia; 2) stage 2: β-cell autoimmunity + mild dysglycemia; 3) stage 3: symptomatic disease + hyperglycemia. Interventions to prevent or cure T1D in the various stages of the disease have been pursued and may target the prevention of the destruction of β cells, regression of insulitis, preservation or recovery of β cells residual mass. Some therapies show promising results that might change the natural history and the approach to patients with T1D in the next few years. Teplizumab, a humanized monoclonal antibody that binds to CD3, was recently approved in the USA to delay Stage 3 T1D in individuals ≥ 8 years of age. Other non-cellular immunomodulatory therapies, both antigen-specific and non-specific, have shown interesting results either in patients with stage 2 or recent onset stage 3 T1D. Cell therapies such as non-myeloablative transplantation of autologous hematopoietic stem cells, mesenchymal stem cells, and tolerogenic dendritic cells have been also studied in these individuals, aiming immunomodulation. Stem cell-derived islet replacement therapy is promising for patients with long- standing T1D, especially with asymptomatic hypoglycemia not resolved by technology. This review aimed to provide updated information on the main immunomodulatory agents and cell therapy options for type 1 diabetes.

Emerging Immunotherapies for Disease Modification of Type 1 Diabetes

Type 1 diabetes mellitus (T1DM) is characterized by the progressive, autoimmune-mediated destruction of β cells. As such, restoring immunoregulation early in the disease course is sought to retain endogenous insulin production. Nevertheless, in the more than 100 years since the discovery of insulin, treatment of T1DM has focused primarily on hormone replacement and glucose monitoring. That said, immunotherapies are widely used to interdict autoimmune and autoinflammatory diseases and are emerging as potential therapeutics seeking the preservation of β-cell function among those with T1DM. In the past 4 decades of diabetes research, several immunomodulatory therapies have been explored, culminating with the US Food and Drug Administration approval of teplizumab to delay stage 3 (clinical) onset of T1DM. Clinical trials seeking to prevent or reverse T1DM by repurposing immunotherapies approved for other autoimmune conditions and by exploring new therapeutics are ongoing. Collectively, these efforts have the potential to transform the future of diabetes care. We encapsulate the past 40 years of immunotherapy trials, take stock of our successes and failures, and chart paths forward in this new age of clinically available immune therapies for T1DM.

The Role of Killer Ig-like Receptors in Diseases from A to Z

Killer Ig-like Receptors (KIRs) regulate immune responses, maintaining the balance between activation and inhibition of the immune system. KIRs are expressed on natural killer cells and some CD8 T cells and interact with HLA class I molecules, influencing various physiological and pathological processes. KIRs' polymorphism creates a variability in immune responses among individuals. KIRs are involved in autoimmune disorders, cancer, infections, neurological diseases, and other diseases. Specific combinations of KIRs and HLA are linked to several diseases' susceptibility, progression, and outcomes. In particular, the balance between inhibitory and activating KIRs can determine how the immune system responds to pathogens and tumors. An imbalance can lead to an excessive response, contributing to autoimmune diseases, or an inadequate response, allowing immune evasion by pathogens or cancer cells. The increasing number of studies on KIRs highlights their essential role as diagnostic and prognostic biomarkers and potential therapeutic targets. This review provides a comprehensive overview of the role of KIRs in all clinical conditions and diseases, listed alphabetically, where they are analyzed.

New Perspectives in Studying Type 1 Diabetes Susceptibility Biomarkers

Type 1 diabetes (T1D) is generally viewed as an etiologic subtype of diabetes caused by the autoimmune destruction of the insulin-secreting β-cells. It has been known that autoreactive T cells unfortunately destroy healthy β-cells. However, there has been a notion of etiologic heterogeneity around the world implicating a varying incidence of a non-autoimmune subgroup of T1D related to insulin deficiency associated with decreased β cell mass, in which the β-cell is the key contributor to the disease. Beta cell dysfunction, reduced mass, and apoptosis may lead to insufficient insulin secretion and ultimately to the development of T1D. Interestingly, Korean as well as other ethnic genetic results have also suggested that genes related with insulin deficiency, let alone those of immune regulation, were associated with the risk of T1D in the young. Genes related with insulin secretion may influence the phenotype of diabetes differentially and different genes may be working on different steps of T1D development. Although we admit the consensus that islet autoimmunity is an essential component in the pathogenesis of T1D, however, dysfunction might occur not only in the immune system but also in the β-cells, the defect of which may induce further dysfunction of the immune system. These arguments stem from the fact that the β-cell might be the trigger of an autoimmune response. This emergent view has many parallels with the fact that by their nature and function, β-cells are prone to biosynthetic stress with limited measures for self-defense. Beta cell stress may induce an immune attack that has considerable negative effects on the production of a vital hormone, insulin. If then, both β-cell stress and islet autoimmunity can be harnessed as targets for intervention strategies. This also may explain why immunotherapy at best delays the progression of T1D and suggests the use of alternative therapies to expand β-cells, in combination with immune intervention strategies, to reverse the disease. Future research should extend to further investigate β-cell biology, in addition to studies of immunologic areas, to find appropriate biomarkers of T1D susceptibility. This will help to decipher β-cell characteristics and the factors regulating their function to develop novel therapeutic approaches.

Risk Stratification for Endometrial Cancer Reveals Independent Contributions of Polygenic Risk and Body Mass Index

Background

Obesity is a major risk factor for endometrial cancer, but it is unknown whether it impacts the association between genetic risk and endometrial cancer. We incorporated polygenic risk score and epidemiological risk factors in the prediction of and investigated associations of BMI and polygenic risk score with endometrial cancer risk.

Methods

We generated polygenic risk score for endometrial cancer in 129,829 unrelated female participants of European ancestry (including 956 incident cases with endometrial cancer) in the UK Biobank and predicted endometrial cancer using endometrial cancer polygenic risk score and established epidemiological risk factors, including BMI. We evaluated the performance of endometrial cancer prediction models by odds ratios and area under the receiver operating characteristic curves (AUCs) to using logistic regression. Individual and joint associations of BMI and polygenic risk score with endometrial cancer were assessed using Cox proportional hazards models.

Results

An integrated model incorporating both polygenic risk score and epidemiological risk factors achieved a modest, but statistically significant, improvement in predicting endometrial cancer status compared with the model that included epidemiologic risk factors alone (AUC = 0.74 versus 0.73; P = 3.98 × 10 -5 ). Obese participants (BMI ≥ 30 kg/m 2 ) in the top polygenic risk tertile had the highest endometrial cancer risk. We observed independent effects of genetic risk and BMI on endometrial cancer risk.

Conclusion

Integrating polygenic risk score with epidemiological risk factors may offer insights into population stratification for endometrial cancer susceptibility. Higher endometrial cancer polygenic risk is associated with endometrial cancer, irrespective of BMI.

The Current Landscape for Screening and Monitoring of Early-Stage Type 1 Diabetes

Type 1 diabetes (T1D) has two pre-symptomatic phases (stages 1 and 2) with progressive destruction of beta cells which have been identified through longitudinal cohort studies in recent decades. The definition of T1D, with hyperglycaemia that may or may not be symptomatic, is now defined as stage 3. There is growing evidence that screening for stages 1 and 2 reduces rates of diabetic ketoacidosis and prevents long-term complications. These stages can be defined by the presence of islet autoantibodies which are markers of autoimmune beta cell damage. Furthermore, genetic risk scores, which combine a variety of single nucleotide polymorphisms, identify people at high genetic risk of future T1D. Thus, they provide an opportunity to select high-risk individuals for islet autoantibody testing. Individuals identified as having stage 1 or 2 T1D require ongoing monitoring to detect hyperglycaemia and the need for insulin replacement. These individuals may also be eligible for emerging immunotherapies in future to delay progression to stage 3. This review article explores the current evidence for screening and summarises the recommended clinical care for early-stage T1D.

Type 1 Diabetes Genetic Risk Contributes to Phenotypic Presentation in Monogenic Autoimmune Diabetes

ARTICLE HIGHLIGHTS

There is variability in early-onset autoimmune diabetes presentation in individuals with monogenic autoimmunity; the mechanism(s) underlying this is unclear. We examined whether type 1 diabetes (T1D) polygenic risk contributes to clinical phenotype in monogenic autoimmune diabetes. Individuals with monogenic autoimmune diabetes had higher T1D genetic risk scores compared with control cohorts, driven largely by increased presence of T1D-risk DR3-DQ2 haplotype. Established T1D polygenic risk alleles, particularly class II HLA genes, contribute to clinical presentation in monogenic autoimmunity.

Standardized Measurement of Type 1 Diabetes Polygenic Risk Across Multi-Ancestry Population Cohorts

Type 1 diabetes (T1D) polygenic risk scores (PRS) are effective tools for discriminating T1D from other diabetes types and predicting T1D risk, with applications in screening and intervention trials. A previously published T1D Genetic Risk Score 2 (GRS2) is widely adopted, but challenges in standardization and accessibility have hindered broader clinical and research utility. To address this, we introduce GRS2x, a standardized and cross-compatible method for accurate T1D PRS calculation, demonstrating genotyping and reference panel independent performance across diverse datasets. GRS2x as a unified approach facilitates accessible and portable measurement of T1D polygenic risk.

Autoimmune Type 1 Diabetes: An Early Approach Appraisal for Spain by the AGORA Diabetes Collaborative Group

Type 1 diabetes (T1D) is an autoimmune disorder characterized by the destruction of insulin-producing pancreatic beta-cells, leading to lifelong insulin dependence. This review explores the current understanding of T1D pathogenesis, clinical progression, and emerging therapeutic approaches. We examined the complex interplay between genetic predisposition and environmental factors that could trigger the autoimmune response as well as the immunological mechanisms involved in beta-cell destruction. The clinical phases of T1D are discussed from the preclinical stage through diagnosis and long-term management, highlighting the importance of early detection and intervention. Recent advancements in treatment strategies are presented, including immunomodulatory therapies and potential cell-based treatments aimed at preserving or restoring beta-cell function. Additionally, this review critically evaluates the feasibility and potential benefits of implementing a population-wide screening program for T1D in Spain. The epidemiological, economic, and ethical implications of such an initiative were considered by the national expert panel, focusing on the potential of early diagnosis to improve clinical outcomes in the face of the challenges of large-scale implementation. This comprehensive analysis aims to provide healthcare professionals, researchers, and policymakers with valuable insights into the current landscape of T1D management and prospects for enhanced prevention and treatment strategies in the Spanish context.

Screening and care for preclinical stage 1-2 type 1 diabetes in first-degree relatives: French expert position statement

The natural history of type 1 diabetes (T1D) evolves from stage 1 (islet autoimmunity with normoglycemia; ICD-10 diagnostic code E10.A1) to stage 2 (autoimmunity with dysglycemia; E10.A2) and subsequent clinical stage 3 (overt hyperglycemia), which is commonly the first time of referral. Autoantibody testing can diagnose T1D at its preclinical stages 1-2 and lead to earlier initiation of care, particularly for first-degree relatives of people living with T1D, who are at higher genetic risk. Preclinical T1D screening and monitoring aims to avoid inaugural ketoacidosis and prolong preservation of endogenous insulin secretion, thereby improving glycemic control and reducing long-term morbidity. Moreover, early management can help coping with T1D and correct modifiable risk factors (obesity, sedentary lifestyle). New treatments currently under clinical deployment or trials also offer the possibility of delaying clinical progression. All these arguments lead to the proposition of a national screening and care pathway open to interested first-degree relatives. This pathway represents a new expertise to acquire for healthcare professionals. By adapting international consensus guidance to the French specificities, the proposed screening strategy involves testing for ≥ 2 autoantibodies (among IAA, anti-GAD, anti-IA-2) in relatives aged 2-45 years. Negative screening (∼95 % of cases) should be repeated every 4 years until the age of 12. A management workflow is proposed for relatives screening positive (∼5 % of cases), with immuno-metabolic monitoring by autoantibody testing, OGTT, glycemia and/or HbA1c of variable frequency, depending on T1D stage, age, patient preference and available resources, as well as the definition of expert centers for preclinical T1D.

2. Diagnosis and Classification of Diabetes: Standards of Care in Diabetes-2025

The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, an interprofessional expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

The Type 1 Diabetes T Cell Receptor and B Cell Receptor Repository in the AIRR Data Commons: a practical guide for access, use and contributions through the Type 1 Diabetes AIRR Consortium

Human molecular genetics has brought incredible insights into the variants that confer risk for the development of tissue-specific autoimmune diseases, including type 1 diabetes. The hallmark cell-mediated immune destruction that is characteristic of type 1 diabetes is closely linked with risk conferred by the HLA class II gene locus, in combination with a broad array of additional candidate genes influencing islet-resident beta cells within the pancreas, as well as function, phenotype and trafficking of immune cells to tissues. In addition to the well-studied germline SNP variants, there are critical contributions conferred by T cell receptor (TCR) and B cell receptor (BCR) genes that undergo somatic recombination to yield the Adaptive Immune Receptor Repertoire (AIRR) responsible for autoimmunity in type 1 diabetes. We therefore created the T1D TCR/BCR Repository (The Type 1 Diabetes T Cell Receptor and B Cell Receptor Repository) to study these highly variable and dynamic gene rearrangements. In addition to processed TCR and BCR sequences, the T1D TCR/BCR Repository includes detailed metadata (e.g. participant demographics, disease-associated parameters and tissue type). We introduce the Type 1 Diabetes AIRR Consortium goals and outline methods to use and deposit data to this comprehensive repository. Our ultimate goal is to facilitate research community access to rich, carefully annotated immune AIRR datasets to enable new scientific inquiry and insight into the natural history and pathogenesis of type 1 diabetes.

Type 1 diabetes genetic risk score variation across ancestries using whole genome sequencing and array-based approaches

A Type 1 Diabetes Genetic Risk Score (T1DGRS) aids diagnosis and prediction of Type 1 Diabetes (T1D). While traditionally derived from imputed array genotypes, Whole Genome Sequencing (WGS) provides a more direct approach and is now increasingly used in clinical and research studies. We investigated the concordance between WGS-based and array-based T1DGRS across genetic ancestries in 149,265 UK Biobank participants using WGS, TOPMed-imputed, and 1000 Genomes-imputed array genotypes. In the overall cohort, WGS-based T1DGRS demonstrated strong correlation with TOPMed-imputed array-based score (r = 0.996, average WGS-based score 0.0028 standard deviations (SD) lower, p < 10- 31), while showing lower correlation with 1000 Genomes-imputed array-based scores (r = 0.981, 0.043 SD lower in WGS, p < 10- 300). Ancestry-stratified analyses between WGS-based and TOPMed-imputed array-based score showed the highest correlation with European ancestry (r = 0.996, 0.044 SD lower in WGS, p < 10- 300) followed by African ancestry (r = 0.989, 0.0193 SD lower in WGS, p < 10- 14) and South Asian ancestry (r = 0.986, 0.0129 SD lower in WGS, p < 10 - 6). These differences were more pronounced when comparing WGS based score with 1000 Genomes-imputed array-based scores (r = 0.982, 0.975, 0.957 for European, South Asian, African respectively). Population-level analysis using WGS-based T1DGRS revealed significant ancestry-based stratification, with European ancestry individuals showing the highest scores, followed by South Asian (average 0.28 SD lower than Europeans, p < 10- 58) and African ancestry individuals (average 0.89 SD lower than Europeans, p < 10- 300). Notably, when applying the European ancestry-derived 90th centile risk threshold, only 0.71% (95% CI 0.41-1.13) of African ancestry individuals and 6.4% (95% CI 5.6-7.2) of South Asian individuals were identified as high-risk, substantially below the expected 10%. In conclusion, while WGS is viable for generating T1DGRS, with TOPMed-imputed genotypes offering a cost-effective alternative, the persistence of ancestry-based variations in T1DGRS distribution even using whole genome sequencing emphasises the need for ancestry-specific or pan-ancestry standards in clinical practice.

Protocol for the Australian Type 1 Diabetes National Screening Pilot: Assessing the feasibility and acceptability of three general population screening models in children

AIM

One third of Australian children diagnosed with type 1 diabetes present with life-threatening diabetic ketoacidosis (DKA) at diagnosis. Screening for early-stage, presymptomatic type 1 diabetes, with ongoing follow-up, can substantially reduce this risk (<5% risk). Several screening models are being trialled internationally, without consensus on the optimal approach. This pilot study aims to assess three models for a routine, population-wide screening programme in Australia.

METHODS

An implementation science-guided pilot study to evaluate the feasibility, acceptability and costs of three screening models in children will be conducted between July 2022 and June 2024. These models are as follows: (1) Genetic risk-stratified screening using newborn heel prick dried bloodspots, followed by autoantibody testing from 11 months of age; (2) genetic risk-stratified screening of infant (6-12 months) saliva followed by autoantibody testing from 10 months of age; and (3) autoantibody screening using capillary dried bloodspots collected from children aged 2, 6 or 10 years. Cohorts for each model will be recruited from targeted geographic areas across Australia involving ≥2 states per cohort, with a recruitment target of up to 3000 children per cohort (total up to 9000 children). The primary outcome is screening uptake for each cohort. Secondary outcomes include programme feasibility, costs, parental anxiety, risk perception, satisfaction, well-being and quality of life, and health professional attitudes and satisfaction.

CONCLUSIONS

This pilot is the first direct comparison of three screening implementation models for general population screening. Findings will provide evidence to inform a potential national screening programme for Australian children.

TRIAL REGISTRATION

ACTRN12622000381785.

Fifty years of HLA-associated type 1 diabetes risk: history, current knowledge, and future directions

More than 50 years have elapsed since the association of human leukocyte antigens (HLA) with type 1 diabetes (T1D) was first reported. Since then, methods for identification of HLA have progressed from cell based to DNA based, and the number of recognized HLA variants has grown from a few to tens of thousands. Current genotyping methodology allows for exact identification of all HLA-encoding genes in an individual's genome, with statistical analysis methods evolving to digest the enormous amount of data that can be produced at an astonishing rate. The HLA region of the genome has been repeatedly shown to be the most important genetic risk factor for T1D, and the original reported associations have been replicated, refined, and expanded. Even with the remarkable progress through 50 years and over 5,000 reports, a comprehensive understanding of all effects of HLA on T1D remains elusive. This report represents a summary of the field as it evolved and as it stands now, enumerating many past and present challenges, and suggests possible paradigm shifts for moving forward with future studies in hopes of finally understanding all the ways in which HLA influences the pathophysiology of T1D.

Exploring the HLA complex in autoimmunity: From the risk haplotypes to the modulation of expression

The genes mapping at the HLA region show high density, strong linkage disequilibrium and high polymorphism, which affect the association of HLA class I and class II genes with autoimmunity. We focused on the HLA haplotypes, genomic structures consisting of an array of specific alleles showing some degrees of genetic association with different autoimmune disorders. GWASs in many pathologies have identified variants in either the coding loci or the flanking regulatory regions, both in linkage disequilibrium in haplotypes, that are frequently associated with increased risk and may influence gene expression. We discuss the relevance of the HLA gene expression because the level of surface heterodimers determines the number of complexes presenting self-antigen and, thus, the strength of pathogenic autoreactive T cells immune response.

Integrating Omics into Functional Biomarkers of Type 1 Diabetes

Biomarkers are critical to the staging and diagnosis of type 1 diabetes (T1D). Functional biomarkers offer insights into T1D immunopathogenesis and are often revealed using "omics" approaches that integrate multiple measures to identify involved pathways and functions. Application of the omics biomarker discovery may enable personalized medicine approaches to circumvent the more recently appreciated heterogeneity of T1D progression and treatment. Use of omics to define functional biomarkers is still in its early years, yet findings to date emphasize the role of cytokine signaling and adaptive immunity in biomarkers of progression and response to therapy. Here, we share examples of the use of omics to define functional biomarkers focusing on two signatures, T-cell exhaustion and T-cell help, which have been associated with outcomes in both the natural history and treatment contexts.

Comparison of blended learning and traditional lecture method on learning outcomes in the evidence-based medicine course: a comparative study

BACKGROUND

Blended learning comprised with flipped classroom (FC) and "internet plus" is a new learning strategy that reverses the position of teacher and students in class, and provides abundant learning resources before and after class. This study aimed to assess the impact of blended learning on learning outcomes in evidence-based medicine course, and compare with traditional learning method.

METHODS

The participants of the two groups were from two difference cohorts in Air force medical university in China. The two groups toke the same pre-test before class and then were given the teaching of same chapters of evidence-based medicine with two different learning strategy. In the blended learning group, the participants were required to create a debriefing slide about their learning outcomes and the answers of questions given in advance after study the learning material sent by teacher a week before class, and the teacher gave a detailed summary based on the common problems, and distributed multimedia resources for review. After the experiment was carried out, learning outcomes including mastering knowledge, learning satisfaction, and self-evaluation were compared.

RESULTS

37 and 39 participants were enrolled to blended learning and traditional learning groups, respectively, and no statistically significant difference were found in baseline information and pre-test grades. Statistically significant differences were found in learning outcomes including post-test score (t = 2.90, p = 0.005), changes of scores between pre-test and post-test (t = 2.49, p = 0.022), learning satisfaction (t = 12.41, p = 0.001), and self-evaluation of the two groups (t = 7.82, p = 0.001). Especially, the changes of scores between pre-test and post-test of blended learning and traditional learning groups were 4.05 (4.26), and 2.00 (2.85), respectively.

CONCLUSIONS

This study showed that compared with traditional learning strategy, blended learning can effectively enhanced participants' acquisition of knowledge, learning satisfaction, and self-evaluation in evidence-based medicine. Using blended learning method including "internet plus" and flipped classroom is recommended in the teaching of evidence-based medicine course.

Recent advances in polygenic scores: translation, equitability, methods and FAIR tools

Polygenic scores (PGS) can be used for risk stratification by quantifying individuals' genetic predisposition to disease, and many potentially clinically useful applications have been proposed. Here, we review the latest potential benefits of PGS in the clinic and challenges to implementation. PGS could augment risk stratification through combined use with traditional risk factors (demographics, disease-specific risk factors, family history, etc.), to support diagnostic pathways, to predict groups with therapeutic benefits, and to increase the efficiency of clinical trials. However, there exist challenges to maximizing the clinical utility of PGS, including FAIR (Findable, Accessible, Interoperable, and Reusable) use and standardized sharing of the genomic data needed to develop and recalculate PGS, the equitable performance of PGS across populations and ancestries, the generation of robust and reproducible PGS calculations, and the responsible communication and interpretation of results. We outline how these challenges may be overcome analytically and with more diverse data as well as highlight sustained community efforts to achieve equitable, impactful, and responsible use of PGS in healthcare.

Immunological and virological triggers of type 1 diabetes: insights and implications

Type 1 diabetes (T1D) is caused by an autoimmune process which culminates in the destruction of insulin-producing beta cells in the pancreas. It is widely believed that a complex and multifactorial interplay between genetic and environmental factors, such as viruses, play a crucial role in the development of the disease. Research over the past few decades has shown that there is not one single viral culprit, nor one single genetic pathway, causing the disease. Rather, viral infections, most notably enteroviruses (EV), appear to accelerate the autoimmune process leading to T1D and are often seen as a precipitator of clinical diagnosis. In support of this hypothesis, the use of anti-viral drugs has recently shown efficacy in preserving beta cell function after onset of diabetes. In this review, we will discuss the various pathways that viral infections utilize to accelerate the development of T1D. There are three key mechanisms linking viral infections to beta-cell death: One is modulated by the direct infection of islets by viruses, resulting in their impaired function, another occurs in a more indirect fashion, by modulating the immune system, and the third is caused by heightened stress on the beta-cell by interferon-mediated increase of insulin resistance. The first two aspects are surprisingly difficult to study, in the case of the former, because there are still many questions about how viruses might persist for longer time periods. In the latter, indirect/immune case, viruses might impact immunity as a hit-and-run scenario, meaning that many or all direct viral footprints quickly vanish, while changes imprinted upon the immune system and the anti-islet autoimmune response persist. Given the fact that viruses are often associated with the precipitation of clinical autoimmunity, there are concerns regarding the impact of the recent global coronavirus-2019 (COVID-19) pandemic on the development of autoimmune disease. The long-term effects of COVID-19 infection on T1D will therefore be discussed, including the increased development of new cases of T1D. Understanding the interplay between viral infections and autoimmunity is crucial for advancing our knowledge in this field and developing targeted therapeutic interventions. In this review we will examine the intricate relationship between viral infections and autoimmunity and discuss potential considerations for prevention and treatment strategies.

Imaging in Type 1 Diabetes, Current Perspectives and Directions

Type 1 diabetes (T1D) is characterized by the autoimmune-mediated attack of insulin-producing beta cells in the pancreas, leading to reliance on exogenous insulin to control a patient's blood glucose levels. As progress is being made in understanding the pathophysiology of the disease and how to better develop therapies to treat it, there is an increasing need for monitoring technologies to quantify beta cell mass and function throughout T1D progression and beta cell replacement therapy. Molecular imaging techniques offer a possible solution through both radiologic and non-radiologic means including positron emission tomography, magnetic resonance imaging, electron paramagnetic resonance imaging, and spatial omics. This commentary piece outlines the role of molecular imaging in T1D research and highlights the need for further applications of such methodologies in T1D.