Economics of Genetic Testing for Diabetes

Implementing genetic testing in diabetes: Knowledge, perceptions of healthcare professionals, and barriers in a developing country

INTRODUCTION

Maturity-Onset Diabetes of the Young (MODY) is an unusual type of diabetes often missed in clinical practice, especially in Africa. Treatment decisions for MODY depend on a precise diagnosis, only made by genetic testing. We aimed to determine MODY knowledge among Nigerian healthcare professionals (HCPs), their perceptions, and barriers to the implementation of genetic testing in diabetes patients.

METHODS

A cross-sectional survey was conducted among doctors and nurses in three levels of public and private healthcare institutions in Ibadan, Nigeria, from December 2018 to June 2019. In all, 70% and 30% of a total 415 participants were recruited from public and private centers, respectively. HCPs were recruited in a 60:40% ratio, respectively. A 51-item instrument was used to assess MODY knowledge, perceptions of HCPs, and barriers to the implementation of genetic testing in diabetes patients.

RESULTS

In the survey, 43.4% self-rated their current MODY knowledge to be at least moderate. About 68%, 73% and 86%, respectively, correctly answered 3 of 5 questions on basic genetics' knowledge. However, only 1 of 7 MODY-specific questions was answered correctly by 72.7% of the respondents. The mean basic genetics and MODY-specific knowledge scores were 2.6/5 (SD=1.0) and 1.8/9 (SD=1.3), respectively. Multiple linear regression showed higher mean scores among those aged 30-49 years, those with degrees and fellowships (except PhD), and general practitioners; 360 (80.0%) perceived that genetic testing plays a central role in diabetes care. Barriers to genetic testing were lack of access to testing facilities, guidance on the use of and updates/educational materials on genetic testing (82.7%, 62.1% and 50.3%, respectively).

CONCLUSIONS

The level of MODY awareness and knowledge among Nigerian HCPs is unacceptably low with a lack of access to genetic testing facilities. These can hinder the implementation of precision diabetes medicine. Increased awareness, provision of decision support aids, and genetic testing facilities are urgently needed.

Early-onset diabetes in Africa: A mini-review of the current genetic profile

Early-onset diabetes is poorly diagnosed partly due to its heterogeneity and variable presentations. Although several genes have been associated with the disease, these genes are not well studied in Africa. We sought to identify the major neonatal, early childhood, juvenile, or early-onset diabetes genes in Africa; and evaluate the available molecular methods used for investigating these gene variants. A literature search was conducted on PubMed, Scopus, Africa-Wide Information, and Web of Science databases. The retrieved records were screened and analyzed to identify genetic variants associated with early-onset diabetes. Although 319 records were retrieved, 32 were considered for the current review. Most of these records (22/32) were from North Africa. The disease condition was genetically heterogenous with most cases possessing unique gene variants. We identified 22 genes associated with early-onset diabetes, 9 of which had variants (n = 19) classified as pathogenic or likely pathogenic (PLP). Among the PLP variants, IER3IP1: p.(Leu78Pro) was the variant with the highest number of cases. There was limited data from West Africa, hence the contribution of genetic variability to early-onset diabetes in Africa could not be comprehensively evaluated. It is worth mentioning that most studies were focused on natural products as antidiabetics and only a few studies reported on the genetics of the disease. ABCC8 and KCNJ11 were implicated as major contributors to early-onset diabetes gene networks. Gene ontology analysis of the network associated ion channels, impaired glucose tolerance, and decreased insulin secretions to the disease. Our review highlights 9 genes from which PLP variants have been identified and can be considered for the development of an African diagnostic panel. There is a gap in early-onset diabetes genetic research from sub-Saharan Africa which is much needed to develop a comprehensive, efficient, and cost-effective genetic panel that will be useful in clinical practice on the continent and among the African diasporas.

A Review of the Biosynthesis and Structural Implications of Insulin Gene Mutations Linked to Human Disease

The discovery of the insulin hormone over 100 years ago, and its subsequent therapeutic application, marked a key landmark in the history of medicine and medical research. The many roles insulin plays in cell metabolism and growth have been revealed by extensive investigations into the structure and function of insulin, the insulin tyrosine kinase receptor (IR), as well as the signalling cascades, which occur upon insulin binding to the IR. In this review, the insulin gene mutations identified as causing disease and the structural implications of these mutations will be discussed. Over 100 studies were evaluated by one reviewing author, and over 70 insulin gene mutations were identified. Mutations may impair insulin gene transcription and translation, preproinsulin trafficking and proinsulin sorting, or insulin-IR interactions. A better understanding of insulin gene mutations and the resultant pathophysiology can give essential insight into the molecular mechanisms underlying impaired insulin biosynthesis and insulin-IR interaction.

Identification of monogenic variants in more than ten per cent of children without type 1 diabetes-related autoantibodies at diagnosis in the Finnish Pediatric Diabetes Register

AIMS/HYPOTHESIS

Monogenic forms of diabetes (MODY, neonatal diabetes mellitus and syndromic forms) are rare, and affected individuals may be misclassified and treated suboptimally. The prevalence of type 1 diabetes is high in Finnish children but systematic screening for monogenic diabetes has not been conducted. We assessed the prevalence and clinical manifestations of monogenic diabetes in children initially registered with type 1 diabetes in the Finnish Pediatric Diabetes Register (FPDR) but who had no type 1 diabetes-related autoantibodies (AABs) or had only low-titre islet cell autoantibodies (ICAs) at diagnosis.

METHODS

The FPDR, covering approximately 90% of newly diagnosed diabetic individuals aged ≤15 years in Finland starting from 2002, includes data on diabetes-associated HLA genotypes and AAB data (ICA, and autoantibodies against insulin, GAD, islet antigen 2 and zinc transporter 8) at diagnosis. A next generation sequencing gene panel including 42 genes was used to identify monogenic diabetes. We interpreted the variants in HNF1A by using the gene-specific standardised criteria and reported pathogenic and likely pathogenic findings only. For other genes, we also reported variants of unknown significance if an individual's phenotype suggested monogenic diabetes.

RESULTS

Out of 6482 participants, we sequenced DNA for 152 (2.3%) testing negative for all AABs and 49 (0.8%) positive only for low-titre ICAs (ICA_low). A monogenic form of diabetes was revealed in 19 (12.5%) of the AAB-negative patients (14 [9.2%] had pathogenic or likely pathogenic variants) and two (4.1%) of the ICA_low group. None had ketoacidosis at diagnosis or carried HLA genotypes conferring high risk for type 1 diabetes. The affected genes were GCK, HNF1A, HNF4A, HNF1B, INS, KCNJ11, RFX6, LMNA and WFS1. A switch from insulin to oral medication was successful in four of five patients with variants in HNF1A, HNF4A or KCNJ11.

CONCLUSIONS/INTERPRETATION

More than 10% of AAB-negative children with newly diagnosed diabetes had a genetic finding associated with monogenic diabetes. Because the genetic diagnosis can lead to major changes in treatment, we recommend referring all AAB-negative paediatric patients with diabetes for genetic testing. Low-titre ICAs in the absence of other AABs does not always indicate a diagnosis of type 1 diabetes.

Co-segregation analysis and functional trial in vivo of candidate genes for monogenic diabetes

INTRODUCTION

The aim of this study was to perform familial co-segregation analysis and functional trial in vivo during mixed meal tolerance test (MMTT) of novel variants in diabetes candidate genes.

RESEARCH DESIGN AND METHODS

It is a continuation of the project "Genetic diabetes in Lithuania" with the cohort of 1209 patients with diabetes. Prior screening for autoimmune markers confirmed type 1 diabetes (T1D) diagnosis in 88.1% (n=1065) of patients, and targeted next-generation sequencing identified 3.5% (n=42) pathogenic variants in MODY genes. Subsequently, 102 patients were classified as having diabetes of unknown etiology. 12/102 were found to have novel variants in potential diabetes genes (RFX2, RREB1, SLC5A1 (3 patients with variants in this gene), GCKR, MC4R, CASP10, TMPRSS6, HGFAC, DACH1, ZBED3). Co-segregation analysis and MMTT were carried out in order to study beta-cell function in subjects with specific variants.

RESULTS

MMTT analysis showed that probands with variants in MC4R, CASP10, TMPRSS6, HGFAC, and SLC5A1 (c.1415T>C) had sufficient residual beta-cell function with stimulated C-peptide (CP) >200 pmol/L. Seven individuals with variants in RFX2, RREB1, GCKR, DACH1, ZBED3 and SLC5A1 (c.1415T>C, and c.932A>T) presented with complete beta-cell failure. No statistical differences were found between patients with sufficient CP production and those with complete beta-cell failure when comparing age at the onset and duration of diabetes. Nineteen family members were included in co-segregation analysis; no diabetes cases were reported among them. Only in patient with the variant c.1894G>A in RFX2 gene, none of the family members were affected by proband's variant.

CONCLUSIONS

Functional beta-cell study in vivo allowed to select five most probable genes for monogenic diabetes. Familial co-segregation analysis showed that novel variant in RFX2 gene could be a possible cause of diabetes. Future functional analysis in vitro is necessary to support or rule out the genetic background as a cause of diabetes.

MODY probability calculator utility in individuals' selection for genetic testing: Its accuracy and performance

Introduction

MODY probability calculator (MPC) represents an easy‐to‐use tool developed by Exeter University to help clinicians prioritize which individuals should be oriented to genetic testing. We aimed to assess the utility of MPC in a Portuguese cohort with early‐onset monogenic diabetes.

Methods

This single‐centre retrospective study enrolled 132 participants submitted to genetic testing between 2015 and 2020. Automatic sequencing and, in case of initial negative results, generation sequencing were performed. MODY probability was calculated using the probability calculator available online. Positive and negative predictive values (PPV and NPV, respectively), accuracy, sensitivity and specificity of the calculator were determined for this cohort.

Results

Seventy‐three individuals were included according to inclusion criteria: 20 glucokinase (GCK‐MODY); 16 hepatocyte nuclear factor 1A (HNF1A‐MODY); 2 hepatocyte nuclear factor 4A (HNF4A‐MODY) and 35 DM individuals with no monogenic mutations found. The median probability score of MODY was significantly higher in monogenic diabetes‐positive subgroup (75.5% vs. 24.2%, p < .001). The discriminative accuracy of the calculator, as expressed by area under the curve, was 75% (95% CI: 64%–85%). In our cohort, the best cut‐off value for the MODY calculator was found to be 36%, with a PPV of 74.4%, NPV of 73.5% and corresponding sensitivity and specificity of 76.2% and 71.4%, respectively.

Conclusions

In a highly pre‐selected group of probands qualified for genetic testing, the Exeter MODY probability calculator provided a useful tool in individuals' selection for genetic testing, with good discrimination ability under an optimal probability cut‐off of 36%. Further geographical and population adjustments are warranted for general use.

Polygenic autoimmune disease risk alleles impacting B cell tolerance act in concert across shared molecular networks in mouse and in humans

Most B cells produced in the bone marrow have some level of autoreactivity. Despite efforts of central tolerance to eliminate these cells, many escape to periphery, where in healthy individuals, they are rendered functionally non-responsive to restimulation through their antigen receptor via a process termed anergy. Broad repertoire autoreactivity may reflect the chances of generating autoreactivity by stochastic use of germline immunoglobulin gene segments or active mechanisms may select autoreactive cells during egress to the naïve peripheral B cell pool. Likewise, it is unclear why in some individuals autoreactive B cell clones become activated and drive pathophysiologic changes in autoimmune diseases. Both of these remain central questions in the study of the immune system(s). In most individuals, autoimmune diseases arise from complex interplay of genetic risk factors and environmental influences. Advances in genome sequencing and increased statistical power from large autoimmune disease cohorts has led to identification of more than 200 autoimmune disease risk loci. It has been observed that autoantibodies are detectable in the serum years to decades prior to the diagnosis of autoimmune disease. Thus, current models hold that genetic defects in the pathways that control autoreactive B cell tolerance set genetic liability thresholds across multiple autoimmune diseases. Despite the fact these seminal concepts were developed in animal (especially murine) models of autoimmune disease, some perceive a disconnect between human risk alleles and those identified in murine models of autoimmune disease. Here, we synthesize the current state of the art in our understanding of human risk alleles in two prototypical autoimmune diseases – systemic lupus erythematosus (SLE) and type 1 diabetes (T1D) along with spontaneous murine disease models. We compare these risk networks to those reported in murine models of these diseases, focusing on pathways relevant to anergy and central tolerance. We highlight some differences between murine and human environmental and genetic factors that may impact autoimmune disease development and expression and may, in turn, explain some of this discrepancy. Finally, we show that there is substantial overlap between the molecular networks that define these disease states across species. Our synthesis and analysis of the current state of the field are consistent with the idea that the same molecular networks are perturbed in murine and human autoimmune disease. Based on these analyses, we anticipate that murine autoimmune disease models will continue to yield novel insights into how best to diagnose, prognose, prevent and treat human autoimmune diseases.

Prevalence and clinical characteristics of T2DM patients with OTUD3 gene rs78466831 SNP at a single academic center in China

BACKGROUND

A novel, rare OTUD3 c.863G>A (rs78466831) in humans has been reported associated with diabetes, but the prevalence and clinical characteristics of T2DM patients with rs78466831 have not been reported before.

OBJECTIVE

To investigate the prevalence and clinical characteristics of T2DM patients with rs78466831 and provide a basis for clinical diagnosis and treatment.

METHODS

OTUD3 gene rs78466831 SNP was detected by Sanger sequencing in all the collected specimens of laboratory-confirmed T2DM patients and healthy people. Clinical characteristics indexes inconsisting of fasting blood glucose (FBG), glycosylated hemoglobin (HbA1c), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), total cholesterol (TC), triglyceride (TG) and a body mass index (BMI), T2DM-associated chronic complications (myocardial infarction, cerebrovascular disease, retinopathy, arterial plaque, peripheral neuropathy and nephropathy) were obtained from the clinical laboratory information systems and electronic medical record system. Clinical characteristic indicators were compared between the wild-type and variant (rs78466831) patients with T2DM.

RESULTS

The prevalence of rs78466831 in the T2DM patients group was significantly higher than the healthy control in our academic center. The general characteristic indicators were not significantly different between the wild-type and rs78466831 patients with T2DM, except the family history of diabetes. Clinical laboratory indicators including HbA1c, FBG, OGTT, TC, HDL-C, LDL-C and CP had no significant difference between the two groups. The therapeutic drug and target achievement rates were not significantly different between the two groups. The incidence of diabetic retinopathy in the variant group was significantly higher than the wild-type group.

CONCLUSIONS

The OTUD3 gene rs78466831 was associated with T2DM and may be a biological risk factor of diabetes retinopathy.

Genetic Spectrum of Neonatal Diabetes

Neonatal diabetes (ND) appears during the first months of life and is caused by a single gene mutation. It is heterogenous and very different compared to other forms of multi-factorial or polygenic diabetes. Clinically, this form is extremely severe, however, early genetic diagnosis is pivotal for successful therapy. A large palette of genes is demonstrated to be a cause of ND, however, the mechanisms of permanent hyperglycemia are different. This review will give an overview of more frequent genetic mutations causing ND, including the function of the mutated genes and the specific therapy for certain sub-forms.

Monogenic diabetes: a gateway to precision medicine in diabetes

Monogenic diabetes refers to diabetes mellitus (DM) caused by a mutation in a single gene and accounts for approximately 1%-5% of diabetes. Correct diagnosis is clinically critical for certain types of monogenic diabetes, since the appropriate treatment is determined by the etiology of the disease (e.g., oral sulfonylurea treatment of HNF1A/HNF4A-diabetes vs. insulin injections in type 1 diabetes). However, achieving a correct diagnosis requires genetic testing, and the overlapping of the clinical features of monogenic diabetes with those of type 1 and type 2 diabetes has frequently led to misdiagnosis. Improvements in sequencing technology are increasing opportunities to diagnose monogenic diabetes, but challenges remain. In this Review, we describe the types of monogenic diabetes, including common and uncommon types of maturity-onset diabetes of the young, multiple causes of neonatal DM, and syndromic diabetes such as Wolfram syndrome and lipodystrophy. We also review methods of prioritizing patients undergoing genetic testing, and highlight existing challenges facing sequence data interpretation that can be addressed by forming collaborations of expertise and by pooling cases.

Disentangling the heterogeneity of adulthood-onset non-autoimmune diabetes: a little closer but lot more to do

Diabetes diagnosed in adults is a highly heterogeneous disorder. It mostly consists of what is referred to as type 2 diabetes but also comprises other entities (i.e. different diseases), including latent autoimmune diabetes, late onset forms of monogenic diabetes and familial diabetes of the adulthood, which has recently been the source of new diabetogenes discovery. Notably, type 2 diabetes is itself heterogeneous as it includes subtypes with onset at the extremes of age and/or weight distributions characterized by different degree of hyperglycemia and cardiovascular risk as compared to common forms of type 2 diabetes occurring in middle-aged, overweight/obese individuals. Understanding whether these are different presentations of one, highly heterogeneous disease or separate nosological entities with different clinical trajectories and requiring different treatments is essential to effectively pursue the path of precision medicine.

Precision medicine in diabetes: a Consensus Report from the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD)

The convergence of advances in medical science, human biology, data science and technology has enabled the generation of new insights into the phenotype known as 'diabetes'. Increased knowledge of this condition has emerged from populations around the world, illuminating the differences in how diabetes presents, its variable prevalence and how best practice in treatment varies between populations. In parallel, focus has been placed on the development of tools for the application of precision medicine to numerous conditions. This Consensus Report presents the American Diabetes Association (ADA) Precision Medicine in Diabetes Initiative in partnership with the European Association for the Study of Diabetes (EASD), including its mission, the current state of the field and prospects for the future. Expert opinions are presented on areas of precision diagnostics and precision therapeutics (including prevention and treatment) and key barriers to and opportunities for implementation of precision diabetes medicine, with better care and outcomes around the globe, are highlighted. Cases where precision diagnosis is already feasible and effective (i.e. monogenic forms of diabetes) are presented, while the major hurdles to the global implementation of precision diagnosis of complex forms of diabetes are discussed. The situation is similar for precision therapeutics, in which the appropriate therapy will often change over time owing to the manner in which diabetes evolves within individual patients. This Consensus Report describes a foundation for precision diabetes medicine, while highlighting what remains to be done to realise its potential. This, combined with a subsequent, detailed evidence-based review (due 2022), will provide a roadmap for precision medicine in diabetes that helps improve the quality of life for all those with diabetes.

Quality of Life and Treatment Satisfaction in Participants with Maturity-Onset Diabetes of the Young: A Comparison to Other Major Forms of Diabetes

AIMS

We investigated the quality of life (QoL), treatment satisfaction and perception of genetic results in participants with Maturity-Onset Diabetes of the Young (MODY) and compared the results with those of subjects with type 1 (T1D) or type 2 (T2D) diabetes.

METHODS

A total of 162 adults with GCK-MODY, 62 with HNF1A-MODY and 29 with HNF4A-MODY answered the questionnaire Audit of Diabetes Dependent Quality of Life, the Diabetes Treatment Satisfaction Questionnaire and non-validated instrument examining the respondent's perception of the genetic results. Data from GCK-MODY patients were compared with 84 participants with T2D and HNF-MODY subjects were compared with 81 participants having T1D.

RESULTS

Higher age (p=0.004), higher haemoglobin A1c (p=0.026) and medication (p=0.019) were associated with lower general QoL in GCK-MODY patients. In HNF-MODY patients, lower general QoL was associated with a longer time since diagnosis (p=0.005), worse haemoglobin bA1c (p=0.006) and insulin treatment (p=0.019). Similar numbers of participants with GCK- and HNF-MODY considered the genetic diagnosis of MODY to be positive, negative and without significance. The patient with GCK-MODY did not differ from those with T2D in terms of their QoL, but they were less satisfied with their treatment (p<0.001). QoL was better in patients with HNF-MODY compared with patients with T1D (p=0.006), and they did not differ in terms of treatment satisfaction.

CONCLUSIONS

QoL was affected in both GCK-MODY and HNF-MODY subjects. Apprehension of genetic diagnosis was not single-valued in MODY respondents.

Precision Medicine in Diabetes: A Consensus Report From the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD)

The convergence of advances in medical science, human biology, data science, and technology has enabled the generation of new insights into the phenotype known as "diabetes." Increased knowledge of this condition has emerged from populations around the world, illuminating the differences in how diabetes presents, its variable prevalence, and how best practice in treatment varies between populations. In parallel, focus has been placed on the development of tools for the application of precision medicine to numerous conditions. This Consensus Report presents the American Diabetes Association (ADA) Precision Medicine in Diabetes Initiative in partnership with the European Association for the Study of Diabetes (EASD), including its mission, the current state of the field, and prospects for the future. Expert opinions are presented on areas of precision diagnostics and precision therapeutics (including prevention and treatment), and key barriers to and opportunities for implementation of precision diabetes medicine, with better care and outcomes around the globe, are highlighted. Cases where precision diagnosis is already feasible and effective (i.e., monogenic forms of diabetes) are presented, while the major hurdles to the global implementation of precision diagnosis of complex forms of diabetes are discussed. The situation is similar for precision therapeutics, in which the appropriate therapy will often change over time owing to the manner in which diabetes evolves within individual patients. This Consensus Report describes a foundation for precision diabetes medicine, while highlighting what remains to be done to realize its potential. This, combined with a subsequent, detailed evidence-based review (due 2022), will provide a roadmap for precision medicine in diabetes that helps improve the quality of life for all those with diabetes.

Maturity-Onset Diabetes of the Young (MODY) in Portugal: Novel GCK, HNFA1 and HNFA4 Mutations

Maturity-onset diabetes of the young (MODY) is a frequently misdiagnosed type of diabetes, which is characterized by early onset, autosomal dominant inheritance, and absence of insulin dependence. The most frequent subtypes are due to mutations of the GCK (MODY 2), HNF1A (MODY 3), and HNF4A (MODY 1) genes. We undertook the first multicenter genetic study of MODY in the Portuguese population. The GCK, HNF1A, and HNF4A genes were sequenced in 46 unrelated patients that had at least two of the three classical clinical criteria for MODY (age at diagnosis, family history, and clinical presentation). The functional consequences of the mutations were predicted by bioinformatics analysis. Mutations were identified in 23 (50%) families. Twelve families had mutations in the GCK gene, eight in the HNF1A gene, and three in the HNF4A gene. These included seven novel mutations (GCK c.494T>C, GCK c.563C>G, HNF1A c.1623G>A, HNF1A c.1729C>G, HNF4A c.68delG, HNF4A c.422G>C, HNF4A c.602A>C). Mutation-positive patients were younger at the time of diagnosis when compared to mutation-negative patients (14.3 vs. 23.0 years, p = 0.011). This study further expands the spectrum of known mutations associated with MODY, and may contribute to a better understanding of this type of diabetes and a more personalized clinical management of affected individuals.