Transcription Factor 7-Like 2 (TCF7L2) Gene Polymorphism and Progression From Single to Multiple Autoantibody Positivity in Individuals at Risk for Type 1 Diabetes

Associations of genetic factors with vascular diabetes complications: an umbrella review

Background

To comprehensively assess evidence from published systematic review and meta-analyses (SRMAs) on the genetics of vascular diabetes complications.

Methods

A systematic literature search conducted in Medline and Embase identified 63 non-overlapping SRMAs. We re-conducted meta-analyses to compare diabetes with and without complications using multiple genetic models; evaluated associations using Venice criteria and Bayesian false-discovery probability (BFDP); and graded as highly credible, credible, and not credible. We also contrasted highly credible and credible associations to recent genome-wide association studies (GWASs).

Results

Highly credible evidence was discovered for single nucleotide polymorphisms (SNPs) rs1024611 at MCP-1 gene and SNP rs3025039 at VEGF gene with diabetic retinopathy (DR) in type 2 diabetes; SNP rs2268388 at ACACB gene, insertion/deletion (Ins/Del) variant at ACE gene, SNP rs1801133 at MTHFR gene, and SNP rs7903146 at TCF7L2 gene with diabetic kidney disease (DKD) in type 2 diabetes; and SNP rs4880 at SOD2 gene with diabetic peripheral neuropathy (DPN) in type 1 diabetes. Combining type 1 and 2 diabetes, highly credible evidence was discovered for insertion/deletion variant at ACE gene, SNP rs759853 at AKR1B1 gene, SNP rs1044498 at ENPP1 gene and DKD, and SNP rs1617640 at EPO gene for the combined endpoint of DR and DKD. None of these associations was directly replicated in the latest GWASs for DR and DKD, however, another SNP, rs55853916 at TCF7L2 gene had been detected as a GWAS hit for DKD.

Conclusions

This umbrella review rigorously assessed evidence on the genetics of vascular diabetes complications, complemented findings in recent GWASs and yielded insight into the optimal selection of genetic models for the design of GWASs on vascular diabetes complications. Mechanistic or bioinformatic studies are warranted to further assess the role of these genes in the pathology of vascular diabetes complications and their potential as drug targets.

Registration

PROSPERO: CRD42022384423.

The stage- and subgroup-specific impact of non-HLA polymorphisms on preclinical type 1 diabetes progression

Besides variation within the HLA gene complex determining a major part of genetic susceptibility to Type 1 diabetes, genome-wide association studies have identified over 60 non-HLA loci also contributing to disease risk. While individual single nucleotide polymorphisms (SNPs) have limited predictive power, genetic risk scores (GRS) can identify at-risk individuals. However, current models do not fully capture the heterogeneous progression of asymptomatic islet autoimmunity, especially in autoantibody-positive subjects. In this study, we investigated the additional stage-specific impact of 17 non-HLA loci on previously established prediction models in 448 persistently autoantibody-positive first-degree relatives. Cox regression and Kaplan Meier survival analysis were used to assess their influence on progression from single to multiple autoantibody-positivity, and from there to clinical onset. FUT2 and CTSH significantly accelerated progression of single to multiple autoAb-positivity, but only in presence of insulin autoantibodies and HLA-DQ2/DQ8, respectively. At the stage of multiple autoantibody-positivity, progression to clinical onset was impacted by various non-HLA SNPs either as independent predictors (GLIS3, CENPW, IL2, GSDM, MEG3A, and NRP-1) or through interaction with HLA class I alleles (CLEC16A, NRP-1, TCF7L2), maternal diabetes status (CTSH), or a high-risk autoantibody-profile (CD226). Our data indicate that, unlike for GRS, the weight of distinct non-HLA polymorphisms varies significantly among individuals at risk, depending on disease stage and other stage-specific risk factors. They refine our previous stage-specific prediction models including age, autoantibody-profile, HLA genotype, and other non-HLA SNPs, and emphasize the importance of stratifying accordingly to personalize time-to-event prediction in risk groups, or for preparing or interpreting prevention trials.

Time to reframe the disease staging system for type 1 diabetes

In 2015, introduction of a disease staging system offered a framework for benchmarking progression to clinical type 1 diabetes. This model, based on islet autoantibodies (stage 1) and dysglycaemia (stage 2) before type 1 diabetes diagnosis (stage 3), has facilitated screening and identification of people at risk. Yet, there are many limitations to this model as the stages combine a very heterogeneous group of individuals; do not have high specificity for type 1 diabetes; can occur without persistence (ie, reversion to an earlier risk stage); and exclude age and other influential risk factors. The current staging system also infers that individuals at risk of type 1 diabetes progress linearly from stage 1 to stage 2 and subsequently stage 3, whereas such movements are often more complex. With the approval of teplizumab by the US Food and Drug Administration in 2022 to delay type 1 diabetes in people at stage 2, there is a need to refine the definition and accuracy of type 1 diabetes staging. Theoretically, we propose that a type 1 diabetes risk calculator should incorporate any available demographic, genetic, autoantibody, metabolic, and immune data that could be continuously updated. Additionally, we call to action for the field to increase the breadth of knowledge regarding type 1 diabetes risk in non-relatives, adults, and individuals from minority populations.

Family History of Type 2 Diabetes and Its Association with Beta Cell Function and Lipid Profile in Newly Diagnosed Pediatric Patients with Type 1 Diabetes

OBJECTIVE

The objective of this study was to explore the associations between a family history of type 2 diabetes (T2D) and beta-cell function, as well as lipid profile, in pediatric patients newly diagnosed with type 1 diabetes (T1D).

METHODS

A retrospective analysis was conducted on children under 14 years of age who were newly diagnosed with T1D at the Children's Hospital of Zhejiang University between August 2018 and August 2022. Clinical features, metabolic profiles, beta-cell function, and lipid profile were evaluated.

RESULTS

A total of 316 children were diagnosed with new-onset T1D. Among them, 28.2% had a family history of T2D. Patients with T1D who had a family history of T2D experienced a later onset of the disease (p = 0.016), improved HOMA2-%B levels (p = 0.003), and increased concentrations of HDL-C (p = 0.005). In addition, no statistically significant differences in age at onset, HOMA2-%B levels, or HDL-C were found when assessing the interaction between family history of T2D and type of diabetes mellitus (autoimmune T1D/idiopathic T1D).

CONCLUSION

A family history of T2D may contribute to the heterogeneity of T1D patients in terms of HOMA2-%B levels and lipid profile. This highlights the significance of taking into account T2D-related factors in the diagnosis and treatment of T1D.

Understanding diabetes heterogeneity: key steps towards precision medicine in diabetes

Diabetes is a highly heterogeneous condition; yet, it is diagnosed by measuring a single blood-borne metabolite, glucose, irrespective of aetiology. Although pragmatically helpful, disease classification can become complex and limit advances in research and medical care. Here, we describe diabetes heterogeneity, highlighting recent approaches that could facilitate management by integrating three disease models across all forms of diabetes, namely, the palette model, the threshold model and the gradient model. Once diabetes has developed, further worsening of established diabetes and the subsequent emergence of diabetes complications are kept in check by multiple processes designed to prevent or circumvent metabolic dysfunction. The impact of any given disease risk factor will vary from person-to-person depending on their background, diabetes-related propensity, and environmental exposures. Defining the consequent heterogeneity within diabetes through precision medicine, both in terms of diabetes risk and risk of complications, could improve health outcomes today and shine a light on avenues for novel therapy in the future.

Heterogeneity and endotypes in type 1 diabetes mellitus

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

Lessons and Gaps in the Prediction and Prevention of Type 1 Diabetes

Type 1 diabetes (T1D) is a serious chronic autoimmune condition. Even though the root cause of T1D development has yet to be determined, enough is known about the natural history of T1D pathogenesis to allow study of interventions that may delay or even prevent the onset of hyperglycemia and clinical T1D. Primary prevention aims to prevent the onset of beta cell autoimmunity in asymptomatic people at high genetic risk for T1D. Secondary prevention strategies aim to preserve functional beta cells once autoimmunity is present, and tertiary prevention aims to initiate and extend partial remission of beta cell destruction after the clinical onset of T1D. The approval of teplizumab in the United States to delay the onset of clinical T1D marks an impressive milestone in diabetes care. This treatment opens the door to a paradigm shift in T1D care. People with T1D risk need to be identified early by measuring T1D related islet autoantibodies. Identifying people with T1D before they have symptoms will facilitate better understanding of pre-symptomatic T1D progression and T1D prevention strategies that may be effective.

Clinical signs of type 1 diabetes are associated with type 2 diabetes marker transcription factor 7-like 2 polymorphism

AIMS/INTRODUCTION

We aimed to assess the distribution of transcription factor 7-like 2 gene TCF7L2 (rs7903146) polymorphism and to find possible associations between TCF7L2 and the characteristics of type 1 diabetes.

MATERIALS AND METHODS

We studied 190 newly diagnosed type 1 diabetes patients (median age 12.7 years, range 2.0-72.5) and 246 controls (median age 23.8 years, range 1.4-81.5) for TCF7L2 single nucleotide polymorphism. We determined anti-islet autoantibodies, random C-peptide levels, diabetes associated HLA DR/DQ haplotypes and genotypes in all patients.

RESULTS

There were no differences in the distribution of TCF7L2 single nucleotide polymorphism between patients and controls. However, patients with in type 1 diabetes, after adjusting for age and sex, subjects carrying C allele were at risk for a C-peptide level lower than 0.5 nmol/L (OR 5.65 [95% CI: 1.14-27.92]) and for zinc transporter 8 autoantibody positivity (5.22 [1.34-20.24]). Participants without T allele were associated with a higher level of islet antigen-2 autoantibodies (3.51 [1.49-8.27]) and zinc transporter 8 autoantibodies (2.39 [1.14-4.99]).

CONCLUSIONS

The connection of TCF7L2 polymorphism with zinc transporter 8 and islet antigen-2 autoantibodies and C-peptide levels in patients supports the viewpoint that TCF7L2 is associated with the clinical signs and autoimmune characteristics of type 1 diabetes. The mechanisms of the interaction between the TCF7L2 risk genotype and anti-islet autoantibodies need to be studied further.

Type 1 diabetes in diverse ancestries and the use of genetic risk scores

Over 75 genetic loci within and outside of the HLA region influence type 1 diabetes risk. Genetic risk scores (GRS), which facilitate the integration of complex genetic information, have been developed in type 1 diabetes and incorporated into models and algorithms for classification, prognosis, and prediction of disease and response to preventive and therapeutic interventions. However, the development and validation of GRS across different ancestries is still emerging, as is knowledge on type 1 diabetes genetics in populations of diverse genetic ancestries. In this Review, we provide a summary of the current evidence on the evolutionary genetic variation in type 1 diabetes and the racial and ethnic differences in type 1 diabetes epidemiology, clinical characteristics, and preclinical course. We also discuss the influence of genetics on type 1 diabetes with differences across ancestries and the development and validation of GRS in various populations.

Heterogeneity of Diabetes: β-Cells, Phenotypes, and Precision Medicine: Proceedings of an International Symposium of the Canadian Institutes of Health Research's Institute of Nutrition, Metabolism and Diabetes and the U.S. National Institutes of Health's National Institute of Diabetes and Digestive and Kidney Diseases

One hundred years have passed since the discovery of insulin-an achievement that transformed diabetes from a fatal illness into a manageable chronic condition. The decades since that momentous achievement have brought ever more rapid innovation and advancement in diabetes research and clinical care. To celebrate the important work of the past century and help to chart a course for its continuation into the next, the Canadian Institutes of Health Research's Institute of Nutrition, Metabolism and Diabetes and the U.S. National Institutes of Health's National Institute of Diabetes and Digestive and Kidney Diseases recently held a joint international symposium, bringing together a cohort of researchers with diverse interests and backgrounds from both countries and beyond to discuss their collective quest to better understand the heterogeneity of diabetes and thus gain insights to inform new directions in diabetes treatment and prevention. This article summarizes the proceedings of that symposium, which spanned cutting-edge research into various aspects of islet biology, the heterogeneity of diabetic phenotypes, and the current state of and future prospects for precision medicine in diabetes.

Heterogeneity of Diabetes: β-Cells, Phenotypes, and Precision Medicine: Proceedings of an International Symposium of the Canadian Institutes of Health Research's Institute of Nutrition, Metabolism and Diabetes and the U.S. National Institutes of Health's National Institute of Diabetes and Digestive and Kidney Diseases

One hundred years have passed since the discovery of insulin-an achievement that transformed diabetes from a fatal illness into a manageable chronic condition. The decades since that momentous achievement have brought ever more rapid innovation and advancement in diabetes research and clinical care. To celebrate the important work of the past century and help to chart a course for its continuation into the next, the Canadian Institutes of Health Research's Institute of Nutrition, Metabolism and Diabetes and the U.S. National Institutes of Health's National Institute of Diabetes and Digestive and Kidney Diseases recently held a joint international symposium, bringing together a cohort of researchers with diverse interests and backgrounds from both countries and beyond to discuss their collective quest to better understand the heterogeneity of diabetes and thus gain insights to inform new directions in diabetes treatment and prevention. This article summarizes the proceedings of that symposium, which spanned cutting-edge research into various aspects of islet biology, the heterogeneity of diabetic phenotypes, and the current state of and future prospects for precision medicine in diabetes.

Heterogeneity of Diabetes: β-Cells, Phenotypes, and Precision Medicine: Proceedings of an International Symposium of the Canadian Institutes of Health Research's Institute of Nutrition, Metabolism and Diabetes and the U.S. National Institutes of Health's National Institute of Diabetes and Digestive and Kidney Diseases

One hundred years have passed since the discovery of insulin-an achievement that transformed diabetes from a fatal illness into a manageable chronic condition. The decades since that momentous achievement have brought ever more rapid innovation and advancement in diabetes research and clinical care. To celebrate the important work of the past century and help to chart a course for its continuation into the next, the Canadian Institutes of Health Research's Institute of Nutrition, Metabolism and Diabetes and the U.S. National Institutes of Health's National Institute of Diabetes and Digestive and Kidney Diseases recently held a joint international symposium, bringing together a cohort of researchers with diverse interests and backgrounds from both countries and beyond to discuss their collective quest to better understand the heterogeneity of diabetes and thus gain insights to inform new directions in diabetes treatment and prevention. This article summarizes the proceedings of that symposium, which spanned cutting-edge research into various aspects of islet biology, the heterogeneity of diabetic phenotypes, and the current state of and future prospects for precision medicine in diabetes.

The broad pathogenetic role of TCF7L2 in human diseases beyond type 2 diabetes

The TCF7L2 protein is a key transcriptional effector of the Wnt/β‐catenin signaling pathway, regulating gene expression. It was initially identified in cancer research and embryologic developmental studies. Later, the TCF7L2 gene was linked to type 2 diabetes (T2D), implicating TCF7L2 and Wnt‐signaling in metabolic disorders and homeostasis. In fact, TCF7L2‐T2D variants confer the greatest relative risk for T2D, unquestionably predicting conversion to T2D in individuals with impaired glucose tolerance. We aim to describe the relevance of TCF7L2 in other human disorders. The TCF7L2‐single nucleotide polymorphisms (SNPs) and T2D‐risk association have been replicated in numerous follow‐up studies, and research has now been performed in several other diseases. In this article, we discuss common TCF7L2‐T2D variants within the framework of their association with human diseases. The TCF7L2 functional regions need to be further investigated because the molecular and cellular mechanisms through which TCF7L2 contributes to risk associations with different diseases are still not fully elucidated. In this review, we show the association of common TCF7L2‐T2D variants with many types of diseases. However, the role of rare genetic variations in the TCF7L2 gene in distinct diseases and ethnic groups has not been explored, and understanding their impact on specific phenotypes will be of clinical relevance. This offers an excellent opportunity to gain a clearer picture of the role that the TCF7L2 gene plays in the pathophysiology of human diseases. The potential pleiotropic role of TCF7L2 may underlie a possible pathway for comorbidity in human disorders.

Metabolic syndrome-related SNPs in HLA and TNF7L2 may be risk factors for generalized pustular psoriasis in Chinese Han population

Background

Generalized pustular psoriasis (GPP) is a rare and severe type of psoriasis. Previous studies have reported that metabolic syndrome and its components have been associated with psoriasis.

Objective

To investigate the association of metabolic syndrome‐related single‐nucleotide polymorphisms (SNPs) and GPP in Chinese Han population.

Materials and Methods

One hundred and thirty‐six (136) GPP patients and 965 healthy controls were recruited in the study. Approximately, 4 ml peripheral venous blood was collected from each participant. After collection, second‐generation sequencing was used to detect genetic polymorphism of 15 SNPs. The plink 1.07 software package was used for statistical analysis.

Results

Rs805303 (p = 0.01, OR = 0.70) and rs3177928 (p = 3.18E−07, OR = 2.66) in HLA were significantly different between the two groups. Moreover, rs4506565 (p = 1.41E−03, OR = 2.72) and rs7901695 (p = 9.39E−04, OR = 2.82) in TCF7L2 were significantly associated with GPP in patients without a previous history of PsV. Genotype analysis of rs4506565 and rs7901695 showed that under the recessive model, genotype frequencies of rs4506565 (p = 0.00, OR = 18.52) and rs7901695 (p = 0.00, OR = 18.44) were significantly different between GPP patients and healthy controls.

Conclusion

Rs805303 and rs3177928 in HLA may increase the risk of GPP in the Chinese Han population. TCF7L2 may be a risk factor for GPP in patients without a previous history of PsV.

The role of transcription factor 7-like 2 in metabolic disorders

Transcription factor 7-like 2 (TCF7L2), a member of the T cell factor/lymphoid enhancer factor family, generally forms a complex with β-catenin to regulate the downstream target genes as an effector of the canonical Wnt signalling pathway. TCF7L2 plays a vital role in various biological processes and functions in many organs and tissues, including the liver, islet and adipose tissues. Further, TCF7L2 down-regulates hepatic gluconeogenesis and promotes lipid accumulation. In islets, TCF7L2 not only affects the insulin secretion of the β-cells but also has an impact on other cells. In addition, TCF7L2 influences adipogenesis in adipose tissues. Thus, an out-of-control TCF7L2 expression can result in metabolic disorders. The TCF7L2 gene is composed of 17 exons, generating 13 different transcripts, and has many single-nucleotide polymorphisms (SNPs). The discovery that these SNPs have an impact on the risk of type 2 diabetes (T2D) has attracted thorough investigations in the study of TCF7L2. Apart from T2D, TCF7L2 SNPs are also associated with type 1, posttransplant and other types of diabetes. Furthermore, TCF7L2 variants affect the progression of other disorders, such as obesity, cancers, metabolic syndrome and heart diseases. Finally, the interaction between TCF7L2 variants and diet also needs to be investigated.

Index60 as an additional diagnostic criterion for type 1 diabetes

AIMS/HYPOTHESIS

We aimed to compare characteristics of individuals identified in the peri-diagnostic range by Index60 (composite glucose and C-peptide measure) ≥2.00, 2 h OGTT glucose ≥11.1 mmol/l, or both.

METHODS

We studied autoantibody-positive participants in the Type 1 Diabetes TrialNet Pathway to Prevention study who, at their baseline OGTT, had 2 h blood glucose ≥11.1 mmol/l and/or Index60 ≥2.00 (n = 354, median age = 11.2 years, age range = 1.7-46.6; 49% male, 83% non-Hispanic White). Type 1 diabetes-relevant characteristics (e.g., age, C-peptide, autoantibodies, BMI) were compared among three mutually exclusive groups: 2 h glucose ≥11.1 mmol/l and Index60 <2.00 [Glu(+), n = 76], 2 h glucose <11.1 mmol/l and Index60 ≥2.00 [Ind(+), n = 113], or both 2 h glucose ≥11.1 mmol/l and Index60 ≥2.00 [Glu(+)/Ind(+), n = 165].

RESULTS

Participants in Glu(+), vs those in Ind(+) or Glu(+)/Ind(+), were older (mean ages = 22.9, 11.8 and 14.7 years, respectively), had higher early (30-0 min) C-peptide response (1.0, 0.50 and 0.43 nmol/l), higher AUC C-peptide (2.33, 1.13 and 1.10 nmol/l), higher percentage of overweight/obesity (58%, 16% and 30%) (all comparisons, p < 0.0001), and a lower percentage of multiple autoantibody positivity (72%, 92% and 93%) (p < 0.001). OGTT-stimulated C-peptide and glucose patterns of Glu(+) differed appreciably from Ind(+) and Glu(+)/Ind(+). Progression to diabetes occurred in 61% (46/76) of Glu(+) and 63% (71/113) of Ind(+). Even though Index60 ≥2.00 was not a Pathway to Prevention diagnostic criterion, Ind(+) had a 4 year cumulative diabetes incidence of 95% (95% CI 86%, 98%).

CONCLUSIONS/INTERPRETATION

Participants in the Ind(+) group had more typical characteristics of type 1 diabetes than participants in the Glu(+) did and were as likely to be diagnosed. However, unlike Glu(+) participants, Ind(+) participants were not identified at the baseline OGTT.

Nutrition and Obesity in the Pathogenesis of Youth-Onset Type 1 Diabetes and Its Complications

Since the 1980s, there has been a dramatic rise in the prevalence of overweight and obesity in pediatric populations, in large part driven by sedentary lifestyles and changing dietary patterns with more processed foods. In parallel with the rise in pediatric obesity in the general population, the prevalence of overweight and obesity has increased among children and adolescents with type 1 diabetes. Adiposity has been implicated in a variety of mechanisms both potentiating the risk for type 1 diabetes as well as exacerbating long-term complications, particularly cardiovascular disease. Treatment options targeting the unique needs of obese pediatric patients, both before and after diagnosis of type 1 diabetes, are limited. In this review, we discuss the history of the epidemiology of the obesity epidemic in the context of pediatric type 1 diabetes, highlight the possible role of obesity in type 1 diabetes pathogenesis and review the concept of "double diabetes". The impact of obesity at and after diagnosis will be discussed, including noted differences in clinical and biochemical markers, lipid abnormalities, and long-term cardiovascular complications. Finally, we will review the existing literature on pharmacologic and nutritional interventions as potential treatment strategies for youth with coexisting type 1 diabetes and obesity.

Insights into the Genetic Underpinnings of Endocrine Traits from Large-Scale Genome-Wide Association Studies

Great strides have been made in genetic association studies of endocrine traits and diseases, with hundreds or thousands of variants associated with height, body mass index, bone density, pubertal timing, and diabetes in recent years. The common variants associated with these traits explain up to half of the trait variation owing to genetic factors, and when aggregated into polygenic risk scores, can also impact clinically relevant phenotypes at the tail ends of the trait distributions. However, pediatric studies tend to lag behind, and it is often unclear how adult-associated variants behave across life.

Excess BMI Accelerates Islet Autoimmunity in Older Children and Adolescents

OBJECTIVE

Sustained excess BMI increases the risk of type 1 diabetes (T1D) in autoantibody-positive relatives without diabetes of patients. We tested whether elevated BMI also accelerates the progression of islet autoimmunity before T1D diagnosis.

RESEARCH DESIGN AND METHODS

We studied 706 single autoantibody-positive pediatric TrialNet participants (ages 1.6-18.6 years at baseline). Cumulative excess BMI (ceBMI) was calculated for each participant based on longitudinally accumulated BMI ≥85th age- and sex-adjusted percentile. Recursive partitioning analysis and multivariable modeling defined the age cut point differentiating the risk for progression to multiple positive autoantibodies.

RESULTS

At baseline, 175 children (25%) had a BMI ≥85th percentile. ceBMI range was -9.2 to 15.6 kg/m² (median -1.91), with ceBMI ≥0 kg/m² corresponding to persistently elevated BMI ≥85th percentile. Younger age increased the progression to multiple autoantibodies, with age cutoff of 9 years defined by recursive partitioning analysis. Although ceBMI was not significantly associated with progression from single to multiple autoantibodies overall, there was an interaction with ceBMI ≥0 kg/m², age, and HLA (P = 0.009). Among children ≥9 years old without HLA DR3-DQ2 and DR4-DQ8, ceBMI ≥0 kg/m² increased the rate of progression from single to multiple positive autoantibodies (hazard ratio 7.32, P = 0.004) and conferred a risk similar to that in those with T1D-associated HLA haplotypes. In participants <9 years old, the effect of ceBMI on progression to multiple autoantibodies was not significant regardless of HLA type.

CONCLUSIONS

These data support that elevated BMI may exacerbate islet autoimmunity prior to clinical T1D, particularly in children with lower risk based on age and HLA. Interventions to maintain normal BMI may prevent or delay the progression of islet autoimmunity.

Introducing the Endotype Concept to Address the Challenge of Disease Heterogeneity in Type 1 Diabetes

The clinical diagnosis of new-onset type 1 diabetes has, for many years, been considered relatively straightforward. Recently, however, there is increasing awareness that within this single clinical phenotype exists considerable heterogeneity: disease onset spans the complete age range; genetic susceptibility is complex; rates of progression differ markedly, as does insulin secretory capacity; and complication rates, glycemic control, and therapeutic intervention efficacy vary widely. Mechanistic and immunopathological studies typically show considerable patchiness across subjects, undermining conclusions regarding disease pathways. Without better understanding, type 1 diabetes heterogeneity represents a major barrier both to deciphering pathogenesis and to the translational effort of designing, conducting, and interpreting clinical trials of disease-modifying agents. This realization comes during a period of unprecedented change in clinical medicine, with increasing emphasis on greater individualization and precision. For complex disorders such as type 1 diabetes, the option of maintaining the "single disease" approach appears untenable, as does the notion of individualizing each single patient's care, obliging us to conceptualize type 1 diabetes less in terms of phenotypes (observable characteristics) and more in terms of disease endotypes (underlying biological mechanisms). Here, we provide our view on an approach to dissect heterogeneity in type 1 diabetes. Using lessons from other diseases and the data gathered to date, we aim to delineate a roadmap through which the field can incorporate the endotype concept into laboratory and clinical practice. We predict that such an effort will accelerate the implementation of precision medicine and has the potential for impact on our approach to translational research, trial design, and clinical management.

The Genetic Contribution to Type 1 Diabetes

PURPOSE OF REVIEW

To provide an updated summary of discoveries made to date resulting from genome-wide association study (GWAS) and sequencing studies, and to discuss the latest loci added to the growing repertoire of genetic signals predisposing to type 1 diabetes (T1D).

RECENT FINDINGS

Genetic studies have identified over 60 loci associated with T1D susceptibility. GWAS alone does not specifically inform on underlying mechanisms, but in combination with other sequencing and omics-data, advances are being made in our understanding of T1D genetic etiology and pathogenesis. Current knowledge indicates that genetic variation operating in both pancreatic β cells and in immune cells is central in mediating T1D risk. One of the main challenges is to determine how these recently discovered GWAS-implicated variants affect the expression and function of gene products. Once we understand the mechanism of action for disease-causing variants, we will be well placed to apply targeted genomic approaches to impede the premature activation of the immune system in an effort to ultimately prevent the onset of T1D.

Birth and coming of age of islet autoantibodies

This review takes the reader through 45 years of islet autoantibody research, from the discovery of islet‐cell antibodies in 1974 to today’s population‐based screening for presymptomatic early‐stage type 1 diabetes. The review emphasizes the current practical value of, and factors to be considered in, the measurement of islet autoantibodies.

The TCF7L2 Locus: A Genetic Window Into the Pathogenesis of Type 1 and Type 2 Diabetes

Over the past ∼15 years there has been great progress in our understanding of the genetics of both type 1 diabetes and type 2 diabetes. This has been driven principally by genome-wide association studies (GWAS) in increasingly larger sample sizes, where many distinct loci have now been reported for both traits. One of the loci that dominates these studies is the TCF7L2 locus for type 2 diabetes. This genetic signal has been leveraged to explore multiple aspects of disease risk, including developments in genetic risk scores, genetic commonalities with cancer, and for gaining insights into diabetes-related molecular pathways. Furthermore, the TCF7L2 locus has aided in providing insights into the genetics of both latent autoimmune diabetes in adults and various presentations of type 1 diabetes. This review outlines the knowledge gained to date and highlights how work with this locus leads the way in guiding how many other genetic loci could be similarly used to gain insights into the pathogenesis of diabetes.

The Influence of Type 2 Diabetes-Associated Factors on Type 1 Diabetes

Current efforts to prevent progression from islet autoimmunity to type 1 diabetes largely focus on immunomodulatory approaches. However, emerging data suggest that the development of diabetes in islet autoantibody-positive individuals may also involve factors such as obesity and genetic variants associated with type 2 diabetes, and the influence of these factors increases with age at diagnosis. Although these factors have been linked with metabolic outcomes, particularly through their impact on β-cell function and insulin sensitivity, growing evidence suggests that they might also interact with the immune system to amplify the autoimmune response. The presence of factors shared by both forms of diabetes contributes to disease heterogeneity and thus has important implications. Characteristics that are typically considered to be nonimmune should be incorporated into predictive algorithms that seek to identify at-risk individuals and into the designs of trials for disease prevention. The heterogeneity of diabetes also poses a challenge in diagnostic classification. Finally, after clinically diagnosing type 1 diabetes, addressing nonimmune elements may help to prevent further deterioration of β-cell function and thus improve clinical outcomes. This Perspectives in Care article highlights the role of type 2 diabetes-associated genetic factors (e.g., gene variants at transcription factor 7-like 2 [TCF7L2]) and obesity (via insulin resistance, inflammation, β-cell stress, or all three) in the pathogenesis of type 1 diabetes and their impacts on age at diagnosis. Recognizing that type 1 diabetes might result from the sum of effects from islet autoimmunity and type 2 diabetes-associated factors, their interactions, or both affects disease prediction, prevention, diagnosis, and treatment.

New insights on the genetics of type 1 diabetes

PURPOSE OF REVIEW

The genetic risk for type 1 diabetes has been studied for over half a century, with the strong genetic associations of type 1 diabetes forming critical evidence for the role of the immune system in pathogenesis. In this review, we discuss some of the original research leading to recent developments in type 1 diabetes genetics.

RECENT FINDINGS

We examine the translation of polygenic scores for type 1 diabetes into tools for prediction and diagnosis of type 1 diabetes, in particular, when used in combination with other biomarkers and clinical features, such as age and islet-specific autoantibodies. Furthermore, we review the description of age associations with type 1 diabetes genetic risk, and the investigation of loci linked to type 2 diabetes in progression of type 1 diabetes. Finally, we consider current limitations, including the scarcity of data from racial and ethnic minorities, and future directions.

SUMMARY

The development of polygenic risk scores has allowed the integration of type 1 diabetes genetics into diagnosis and prediction. Emerging information on the role of specific genes in subgroups of individuals with the disease, for example, early-onset, mild autoimmunity, and so forth, is facilitating our understanding of the heterogeneity of type 1 diabetes, with the ultimate goal of using genetic information in research and clinical practice.