The cost-effectiveness of personalized genetic medicine: the case of genetic testing in neonatal diabetes

Exploring the Diagnostic Complexity of Diabetes Subtypes in Pediatric Obesity: A Case Report of an Adolescent With Prader-Willi Phenotype and Literature Review

Obesity among adolescents poses a significant global health concern with profound short- and long-term impact on physical and mental well-being. The intricate relationship between obesity and the onset of diabetes remains ambiguous, particularly in cases where the manifestation may differ from that observed in individuals with uncomplicated obesity. Herein, we present the case of a 14-year-old male adolescent with Prader-Willi phenotype and subsequent obesity, exhibiting symptoms of polyuria and polydipsia over a 10-day period, indicative of potential diabetes mellitus (DM). Laboratory assessments revealed a hemoglobin A1c level of 10%, confirming the suspected diagnosis. Notably, despite the absence of ketosis, elevated C-peptide levels and the presence of slightly positive islet-cell antibodies warranted further investigation. While the presence of antibodies typically aligns with a diagnosis of type 1 DM, recent research has highlighted the occurrence of anti-insulin pancreatic cell antibodies in type 2 DM cases. This article aims to delve into the multifaceted issues surrounding adolescent obesity, atypical presentations of DM with positive antibodies, and the long-term management of patients with genetic syndromes.

Current practices and challenges in genetic testing and counseling for women with breast and ovarian cancer in Asia

AIM

This study assesses current practices and challenges in genetic testing and counseling (GT and C) for breast cancer gene (BRCA)1/2 mutations in Asia, considering the increased risk of ovarian cancer (OC) and breast cancer (BC) in women carrying these mutations.

METHODS

Insights were gathered through a questionnaire from breast surgeons, gynecologists, oncologists, and genetic clinicians in 10 Asian countries: Thailand, Hong Kong, South Korea, India, Vietnam, Malaysia, the Philippines, Taiwan, Singapore, and Indonesia. The questionnaire covered their knowledge, attitudes, and practices in GT and C for BRCA1/2 mutations, along with information on perceived gaps and unmet needs in the region.

RESULTS

A total of 61 specialists participated in the survey. GT and C for BRCA1/2 mutations were less frequently offered in Asia compared to Western countries. Among the guidelines used, the National Comprehensive Cancer Network (NCCN) guidelines alone or in combination with other guidelines (American Society of Clinical Oncology [ASCO], National Institute for Health and Clinical Excellence [NICE], and European Society for Medical Oncology [ESMO]) were preferred for both BC and OC. Limited access to genetic counselors posed a significant challenge, resulting in delayed or no GT. Pretest genetic counseling was provided by the respondents themselves. Germline testing was preferred for BC, whereas both germline and somatic testing were preferred for OC, with the most preferred option being a multipanel germline test.

CONCLUSION

Disparities exist in GT and C practices between Asian and Western countries. To address this, steps, such as patient and doctor education, increased accessibility and affordability of GT and C services, and improved infrastructure for identifying gene mutations, should be taken.

Cost-Effectiveness of Whole-Genome vs Whole-Exome Sequencing Among Children With Suspected Genetic Disorders

Importance

The diagnosis of rare diseases and other genetic conditions can be daunting due to vague or poorly defined clinical features that are not recognized even by experienced clinicians. Next-generation sequencing technologies, such as whole-genome sequencing (WGS) and whole-exome sequencing (WES), have greatly enhanced the diagnosis of genetic diseases by expanding the ability to sequence a large part of the genome, rendering a cost-effectiveness comparison between them necessary.

Objective

To assess the cost-effectiveness of WGS compared with WES and conventional testing in children with suspected genetic disorders.

Design, Setting, and Participants

In this economic evaluation, a bayesian Markov model was implemented from January 1 to June 30, 2023. The model was developed using data from a cohort of 870 pediatric patients with suspected genetic disorders who were enrolled and underwent testing in the Ospedale Pediatrico Bambino Gesù, Rome, Italy, from January 1, 2015, to December 31, 2022. The robustness of the model was assessed through probabilistic sensitivity analysis and value of information analysis.

Main Outcomes and Measures

Overall costs, number of definitive diagnoses, and incremental cost-effectiveness ratios per diagnosis were measured. The cost-effectiveness analyses involved 4 comparisons: first-tier WGS with standard of care; first-tier WGS with first-tier WES; first-tier WGS with second-tier WES; and first-tier WGS with second-tier WGS.

Results

The ages of the 870 participants ranged from 0 to 18 years (539 [62%] girls). The results of the analysis suggested that adopting WGS as a first-tier strategy would be cost-effective compared with all other explored options. For all threshold levels above €29 800 (US $32 408) per diagnosis that were tested up to €50 000 (US $54 375) per diagnosis, first-line WGS vs second-line WES strategy (ie, 54.6%) had the highest probability of being cost-effective, followed by first-line vs second-line WGS (ie, 54.3%), first-line WGS vs the standard of care alternative (ie, 53.2%), and first-line WGS vs first-line WES (ie, 51.1%). Based on sensitivity analyses, these estimates remained robust to assumptions and parameter uncertainty.

Conclusions and Relevance

The findings of this economic evaluation encourage the development of policy changes at various levels (ie, macro, meso, and micro) of international health systems to ensure an efficient adoption of WGS in clinical practice and its equitable access.

Genetic perspectives on childhood monogenic diabetes: Diagnosis, management, and future directions

Monogenic diabetes is caused by one or even more genetic variations, which may be uncommon yet have a significant influence and cause diabetes at an early age. Monogenic diabetes affects 1 to 5% of children, and early detection and gene-tically focused treatment of neonatal diabetes and maturity-onset diabetes of the young can significantly improve long-term health and well-being. The etiology of monogenic diabetes in childhood is primarily attributed to genetic variations affecting the regulatory genes responsible for beta-cell activity. In rare instances, mutations leading to severe insulin resistance can also result in the development of diabetes. Individuals diagnosed with specific types of monogenic diabetes, which are commonly found, can transition from insulin therapy to sulfonylureas, provided they maintain consistent regulation of their blood glucose levels. Scientists have successfully devised materials and methodologies to distinguish individuals with type 1 or 2 diabetes from those more prone to monogenic diabetes. Genetic screening with appropriate findings and interpretations is essential to establish a prognosis and to guide the choice of therapies and management of these interrelated ailments. This review aims to design a comprehensive literature summarizing genetic insights into monogenetic diabetes in children and adolescents as well as summarizing their diagnosis and mana-gement.

Management of Neonatal Diabetes due to a KCNJ11 Mutation with Automated Insulin Delivery System and Remote Patient Monitoring

Neonatal diabetes mellitus (NDM) is a monogenic form of diabetes. Management of hyperglycemia in neonates with subcutaneous insulin is challenging because of frequent feeding, variable quantity of milk intake with each feed, low insulin dose requirements, and high risk for hypoglycemia and associated complications in this population. We present a case of NDM in a proband initially presenting with focal seizures and diabetic ketoacidosis due to a pathologic mutation in the beta cell potassium ATP channel gene KCNJ11 c.679G > A (p.E227K). We describe the use of continuous glucose monitoring (CGM), insulin pump, automated insulin delivery system, and remote patient monitoring technologies to facilitate rapid and safe outpatient cross-titration from insulin to oral sulfonylurea. Our case highlights the safety and efficacy of these technologies for infants with diabetes, including improvements in glycemia, quality of life, and cost-effectiveness by shortening hospital stay.

Monogenic diabetes

Monogenic diabetes includes several clinical conditions generally characterized by early-onset diabetes, such as neonatal diabetes, maturity-onset diabetes of the young (MODY) and various diabetes-associated syndromes. However, patients with apparent type 2 diabetes mellitus may actually have monogenic diabetes. Indeed, the same monogenic diabetes gene can contribute to different forms of diabetes with early or late onset, depending on the functional impact of the variant, and the same pathogenic variant can produce variable diabetes phenotypes, even in the same family. Monogenic diabetes is mostly caused by impaired function or development of pancreatic islets, with defective insulin secretion in the absence of obesity. The most prevalent form of monogenic diabetes is MODY, which may account for 0.5-5% of patients diagnosed with non-autoimmune diabetes but is probably underdiagnosed owing to insufficient genetic testing. Most patients with neonatal diabetes or MODY have autosomal dominant diabetes. More than 40 subtypes of monogenic diabetes have been identified to date, the most prevalent being deficiencies of GCK and HNF1A. Precision medicine approaches (including specific treatments for hyperglycaemia, monitoring associated extra-pancreatic phenotypes and/or following up clinical trajectories, especially during pregnancy) are available for some forms of monogenic diabetes (including GCK- and HNF1A-diabetes) and increase patients' quality of life. Next-generation sequencing has made genetic diagnosis affordable, enabling effective genomic medicine in monogenic diabetes.

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.

Monogenic diabetes in New Zealand - An audit based revision of the monogenic diabetes genetic testing pathway in New Zealand

AIMS

To evaluate (a) the diagnostic yield of genetic testing for monogenic diabetes when using single gene and gene panel-based testing approaches in the New Zealand (NZ) population, (b) whether the MODY (Maturity Onset Diabetes of the Young) pre-test probability calculator can be used to guide referrals for testing in NZ, (c) the number of referrals for testing for Māori/Pacific ethnicities compared to NZ European, and (d) the volume of proband vs cascade tests being requested.

METHODS

A retrospective audit of 495 referrals, from NZ, for testing of monogenic diabetes genes was performed. Referrals sent to LabPlus (Auckland) laboratory for single gene testing or small multi-gene panel testing, or to the Exeter Genomics Laboratory, UK, for a large gene panel, received from January 2014 - December 2021 were included. Detection rates of single gene, small multi-gene and large gene panels (neonatal and non-neonatal), and cascade testing were analysed. Pre-test probability was calculated using the Exeter MODY probability calculator and ethnicity data was also collected.

RESULTS

The diagnostic detection rate varied across genes, from 32% in GCK, to 2% in HNF4A, with single gene or small gene panel testing averaging a 12% detection rate. Detection rate by type of panel was 9% for small gene panel, 23% for non-neonatal monogenic diabetes large gene panel and 40% for neonatal monogenic diabetes large gene panel. 45% (67/147) of patients aged 1-35 years at diabetes diagnosis scored <20% on MODY pre-test probability, of whom 3 had class 4/5 variants in HNF1A, HNF4A or HNF1B. Ethnicity data of those selected for genetic testing correlated with population diabetes prevalence for Māori (15% vs 16%), but Pacific People appeared under-represented (8% vs 14%). Only 1 in 6 probands generated a cascade test.

CONCLUSIONS

A new monogenic diabetes testing algorithm for NZ is proposed, which directs clinicians to choose a large gene panel in patients without syndromic features who score a pre-test MODY probability of above 20%.

A roadmap to achieve pharmacological precision medicine in diabetes

Current pharmacological treatment of diabetes is largely algorithmic. Other than for cardiovascular disease or renal disease, where sodium-glucose cotransporter 2 inhibitors and/or glucagon-like peptide-1 receptor agonists are indicated, the choice of treatment is based upon overall risks of harm or side effect and cost, and not on probable benefit. Here we argue that a more precise approach to treatment choice is necessary to maximise benefit and minimise harm from existing diabetes therapies. We propose a roadmap to achieve precision medicine as standard of care, to discuss current progress in relation to monogenic diabetes and type 2 diabetes, and to determine what additional work is required. The first step is to identify robust and reliable genetic predictors of response, recognising that genotype is static over time and provides the skeleton upon which modifiers such as clinical phenotype and metabolic biomarkers can be overlaid. The second step is to identify these metabolic biomarkers (e.g. beta cell function, insulin sensitivity, BMI, liver fat, metabolite profile), which capture the metabolic state at the point of prescribing and may have a large impact on drug response. Third, we need to show that predictions that utilise these genetic and metabolic biomarkers improve therapeutic outcomes for patients, and fourth, that this is cost-effective. Finally, these biomarkers and prediction models need to be embedded in clinical care systems to enable effective and equitable clinical implementation. Whilst this roadmap is largely complete for monogenic diabetes, we still have considerable work to do to implement this for type 2 diabetes. Increasing collaborations, including with industry, and access to clinical trial data should enable progress to implementation of precision treatment in type 2 diabetes in the near future.

Achievements, prospects and challenges in precision care for monogenic insulin-deficient and insulin-resistant diabetes

Integration of genomic and other data has begun to stratify type 2 diabetes in prognostically meaningful ways, but this has yet to impact on mainstream diabetes practice. The subgroup of diabetes caused by single gene defects thus provides the best example to date of the vision of 'precision diabetes'. Monogenic diabetes may be divided into primary pancreatic beta cell failure, and primary insulin resistance. In both groups, clear examples of genotype-selective responses to therapy have been advanced. The benign trajectory of diabetes due to pathogenic GCK mutations, and the sulfonylurea-hyperresponsiveness conferred by activating KCNJ11 or ABCC8 mutations, or loss-of-function HNF1A or HNF4A mutations, often decisively guide clinical management. In monogenic insulin-resistant diabetes, subcutaneous leptin therapy is beneficial in some severe lipodystrophy. Increasing evidence also supports use of 'obesity therapies' in lipodystrophic people even without obesity. In beta cell diabetes the main challenge is now implementation of the precision diabetes vision at scale. In monogenic insulin-resistant diabetes genotype-specific benefits are proven in far fewer patients to date, although further genotype-targeted therapies are being evaluated. The conceptual paradigm established by the insulin-resistant subgroup with 'adipose failure' may have a wider influence on precision therapy for common type 2 diabetes, however. For all forms of monogenic diabetes, population-wide genome sequencing is currently forcing reappraisal of the importance assigned to pathogenic mutations when gene sequencing is uncoupled from prior suspicion of monogenic diabetes.

The Net Benefit of Personalized Medicine: A Systematic Literature Review and Regression Analysis

OBJECTIVES

Amidst conflicting expectations about the benefits of personalized medicine (PM) and the potentially high implementation costs, we reviewed the available evidence on the cost-effectiveness of PM relative to non-PM.

METHODS

We conducted a systematic literature review of economic evaluations of PM and extracted data, including incremental quality-adjusted life-years (ΔQALYs) and incremental costs (Δcosts). ΔQALYs and Δcosts were combined with estimates of national cost-effectiveness thresholds to calculate incremental net monetary benefit (ΔNMB). Regression analyses were performed with these variables as dependent variables and PM intervention characteristics as independent variables. Random intercepts were used to cluster studies according to country.

RESULTS

Of 4774 studies reviewed, 128 were selected, providing cost-effectiveness data for 279 PM interventions. Most studies were set in the United States (48%) and the United Kingdom (16%) and adopted a healthcare perspective (82%). Cancer treatments (60%) and pharmaceutical interventions (72%) occurred frequently. Prognostic tests (19%) and tests to identify (non)responders (37%) were least and most common, respectively. Industry sponsorship occurred in 32%. Median ΔQALYs, Δcosts, and ΔNMB per individual were 0.03, Int$575, and Int$18, respectively. We found large heterogeneity in cost-effectiveness. Regression analysis showed that gene therapies were associated with higher ΔQALYs than other interventions. PM interventions for neoplasms brought higher ΔNMB than PM interventions for other conditions. Nonetheless, average ΔNMB in the 'neoplasm' group was found to be negative.

CONCLUSIONS

PM brings improvements in health but often at a high cost, resulting in 0 to negative ΔNMB on average. Pricing policies may be needed to reduce the costs of interventions with negative ΔNMB.

The role of sulfonylureas in the treatment of type 2 diabetes

INTRODUCTION

Type 2 diabetes (T2D) is increasingly prevalent and associated with increased risk for cardiovascular and renal disease. After lifestyle modification, metformin is usually the first-line pharmacotherapy and sulfonylureas are traditionally added after metformin failure. However, with newer glucose lowering drugs that may have less risk of hypoglycemia or that may reduce cardiovascular and renal events, the position of sulfonylureas is being reevaluated.

AREAS COVERED

In this article, the authors review relevant publications related to the use of sulfonylureas.

EXPERT OPINION

Sulfonylureas are potent glucose lowering drugs. The risk of hypoglycemia varies with different drugs within the class and can be minimized by using the safer drugs, possibly in lower doses. Cardiovascular events do not appear to be increased with some of the newer generation drugs. The durability of glycemic control also appears comparable to other newer agents. Sulfonylureas are the preferred treatment for some types of monogenic diabetes and selection of T2D patients who may have greater benefit from sulfonylureas based on certain phenotypes and genotypes is likely to be refined further by precision medicine. Sulfonylureas are inexpensive and readily available everywhere and they are still the most frequently used second-line treatment for T2D in many parts of the world.

Assessing the Effect of Including Social Costs in Economic Evaluations of Diabetes-Related Interventions: A Systematic Review

Background

The economic burden of diabetes from a societal perspective is well documented in the cost-of-illness literature. However, the effect of considering social costs in the results and conclusions of economic evaluations of diabetes-related interventions remains unknown.

Objective

To investigate whether the inclusion of social costs (productivity losses and/or informal care) might change the results and conclusions of economic evaluations of diabetes-related interventions.

Methods

A systematic review was designed and launched on Medline and the Cost-Effectiveness Analysis Registry from the University of Tufts, from the year 2000 until 2018. Included studies had to fulfil the following criteria: i) being an original study published in a scientific journal, ii) being an economic evaluation of an intervention on diabetes, iii) including social costs, iv) being written in English, v) using quality-adjusted life years as outcome, and vi) separating the results according to the perspective applied.

Results

From the 691 records identified, 47 studies (6.8%) were selected. Productivity losses were included in 45 of the selected articles (73% used the human capital approach) whereas informal care costs in only 13 (when stated, the opportunity cost method was used in seven studies and the replacement cost in one). The 47 studies resulted in 110 economic evaluation estimations. The inclusion of social costs changed the conclusions in 8 estimations (17%), 6 of them switching from not cost-effective from the healthcare perspective to cost-effective or dominant from the societal perspective. Considering social costs altered the results from cost-effective to dominant in 9 estimations (19%).

Conclusion

When social costs are considered, the results and conclusions of economic evaluations performed in diabetes-related interventions can alter. Wide methodological variations have been observed, which limit the comparability of studies and advocate for the inclusion of a wider perspective via the consideration of social costs in economic evaluations and methodological guidelines relating to their estimation and valuation.

Diabetes and Genetics: A Relationship Between Genetic Risk Alleles, Clinical Phenotypes and Therapeutic Approaches

Unveiling human genome through successful completion of Human Genome Project and International HapMap Projects with the advent of state of art technologies has shed light on diseases associated genetic determinants. Identification of mutational landscapes such as copy number variation, single nucleotide polymorphisms or variants in different genes and loci have revealed not only genetic risk factors responsible for diseases but also region(s) playing protective roles. Diabetes is a global health concern with two major types - type 1 diabetes (T1D) and type 2 diabetes (T2D). Great progress in understanding the underlying genetic predisposition to T1D and T2D have been made by candidate gene studies, genetic linkage studies, genome wide association studies with substantial number of samples. Genetic information has importance in predicting clinical outcomes. In this review, we focus on recent advancement regarding candidate gene(s) associated with these two traits along with their clinical parameters as well as therapeutic approaches perceived. Understanding genetic architecture of these disease traits relating clinical phenotypes would certainly facilitate population stratification in diagnosing and treating T1D/T2D considering the doses and toxicity of specific drugs.

Monogenic Diabetes: From Genetic Insights to Population-Based Precision in Care. Reflections From a Diabetes Care Editors' Expert Forum

Individualization of therapy based on a person's specific type of diabetes is one key element of a "precision medicine" approach to diabetes care. However, applying such an approach remains difficult because of barriers such as disease heterogeneity, difficulties in accurately diagnosing different types of diabetes, multiple genetic influences, incomplete understanding of pathophysiology, limitations of current therapies, and environmental, social, and psychological factors. Monogenic diabetes, for which single gene mutations are causal, is the category most suited to a precision approach. The pathophysiological mechanisms of monogenic diabetes are understood better than those of any other form of diabetes. Thus, this category offers the advantage of accurate diagnosis of nonoverlapping etiological subgroups for which specific interventions can be applied. Although representing a small proportion of all diabetes cases, monogenic forms present an opportunity to demonstrate the feasibility of precision medicine strategies. In June 2019, the editors of Diabetes Care convened a panel of experts to discuss this opportunity. This article summarizes the major themes that arose at that forum. It presents an overview of the common causes of monogenic diabetes, describes some challenges in identifying and treating these disorders, and reports experience with various approaches to screening, diagnosis, and management. This article complements a larger American Diabetes Association effort supporting implementation of precision medicine for monogenic diabetes, which could serve as a platform for a broader initiative to apply more precise tactics to treating the more common forms of diabetes.

Emerging technologies in pediatrics: the paradigm of neonatal diabetes mellitus

In the era of precision medicine, the tremendous progress in next-generation sequencing technologies has allowed the identification of an ever-increasing number of genes associated with known Mendelian disorders. Neonatal diabetes mellitus is a rare, genetically heterogeneous endocrine disorder diagnosed before 6 months of age. It may occur alone or in the context of genetic syndromes. Neonatal diabetes mellitus has been linked with genetic defects in at least 26 genes to date. Novel mutations in these disease-causing genes are being reported, giving us a better knowledge of the molecular events that occur upon insulin biosynthesis and secretion from the pancreatic β-cell. Of great importance, some of the identified genes encode proteins that can be therapeutically targeted by drugs per os, leading to transitioning from insulin to sulfonylureas. In this review, we provide an overview of pancreatic β-cell physiology, present the clinical manifestations and the genetic causes of the different forms of neonatal diabetes, and discuss the application of next-generation sequencing methods in the diagnosis and therapeutic management of neonatal diabetes and on research in this area.

Uncommon Presentations of Diabetes: Zebras in the Herd

The majority of patients with diabetes are diagnosed as having either type 1 or type 2 diabetes. However, when encountered in clinical practice, some patients may not match the classic diagnostic criteria or expected clinical presentation for either type of the disease. Latent autoimmune, ketosis-prone, and monogenic diabetes are nonclassical forms of diabetes that are often misdiagnosed as either type 1 or type 2 diabetes. Recognizing the distinguishing clinical characteristics and understanding the diagnostic criteria for each will lead to appropriate treatment, facilitate personalized medicine, and improve patient outcomes.

Genetic Counseling Status and Perspectives Based on a 2018 Professional Survey in Korea

BACKGROUND

Genetic counseling (GC) provides many benefits, including the identification of patients appropriate for testing, patient education, and medical management. We evaluated the current status of and challenges faced by GC practitioners in Korean hospitals.

METHODS

An electronic survey was designed and conducted in 52 certified laboratory physicians belonging to the Korean Society of Laboratory Medicine, from August to September 2018. The questionnaires addressed three main categories of information: (1) current status of GC in hospitals; (2) essential qualifications of GC practitioners; and (3) challenges and perspectives for GC. Fisher's exact test was applied to analyze categorical data.

RESULTS

Among a total of 52 participants who initially responded, 12 (23.1%) were performing GC either by direct or indirect care. GC clinics were opened regularly for one (33.3%) or more than three sessions (25.0%) per week; most respondents spent more time for pre-visit activities than in-person visits, both for a initial visit patient and for a follow-up visit patient. All laboratory physicians provided genetic information to their patients. Most recommended family genetic testing when indicated (91.7%), discussed disease management (75.0%), and/or ordered additional genetic testing (58.3%), and some referred patients to other specialists (8.3%).

CONCLUSIONS

Both patients and laboratory physicians concede the advantage of GC performed by clinical geneticists; however, the practice of GC involves several challenges and raises some concerns. The cost and support required to implement GC need to be addressed in order to provide qualified GC in Korea.

The Impact of Biomarker Screening and Cascade Genetic Testing on the Cost-Effectiveness of MODY Genetic Testing

OBJECTIVE

In the U.S., genetic testing for maturity-onset diabetes of the young (MODY) is frequently delayed because of difficulty with insurance coverage. Understanding the economic implications of clinical genetic testing is imperative to advance precision medicine for diabetes. The objective of this article is to assess the cost-effectiveness of genetic testing, preceded by biomarker screening and followed by cascade genetic testing of first-degree relatives, for subtypes of MODY in U.S. pediatric patients with diabetes.

RESEARCH DESIGN AND METHODS

We used simulation models of distinct forms of diabetes to forecast the clinical and economic consequences of a systematic genetic testing strategy compared with usual care over a 30-year time horizon. In the genetic testing arm, patients with MODY received treatment changes (sulfonylureas for HNF1A- and HNF4A-MODY associated with a 1.0% reduction in HbA_1c; no treatment for GCK-MODY). Study outcomes included costs, life expectancy (LE), and quality-adjusted life years (QALY).

RESULTS

The strategy of biomarker screening and genetic testing was cost-saving as it increased average quality of life (+0.0052 QALY) and decreased costs (-$191) per simulated patient relative to the control arm. Adding cascade genetic testing increased quality-of-life benefits (+0.0081 QALY) and lowered costs further (-$735).

CONCLUSIONS

A combined strategy of biomarker screening and genetic testing for MODY in the U.S. pediatric diabetes population is cost-saving compared with usual care, and the addition of cascade genetic testing accentuates the strategy's benefits. Widespread implementation of this strategy could improve the lives of patients with MODY while saving the health system money, illustrating the potential population health benefits of personalized medicine.

From Biology to Genes and Back Again: Gene Discovery for Monogenic Forms of Beta-Cell Dysfunction in Diabetes

This review focuses on gene discovery strategies used to identify monogenic forms of diabetes caused by reduced pancreatic beta-cell number (due to destruction or defective development) or impaired beta-cell function. Gene discovery efforts in monogenic diabetes have identified 36 genes so far. These genetic causes have been identified using four main approaches: linkage analysis, candidate gene sequencing and most recently, exome and genome sequencing. The advent of next-generation sequencing has allowed researchers to move away from linkage analysis (relying on large pedigrees and/or multiple families with the same genetic condition) and candidate gene (relying on previous knowledge on the gene's role) strategies to use a gene agnostic approach, utilizing genetic evidence (such as variant frequency, predicted variant effect on protein function, and predicted mode of inheritance) to identify the causative mutation. This approach led to the identification of seven novel genetic causes of monogenic diabetes, six by exome sequencing and one by genome sequencing. In many of these cases, the disease-causing gene was not known to be important for beta-cell function prior to the gene discovery study. These novel findings highlight a new role for gene discovery studies in furthering our understanding of beta-cell function and dysfunction in diabetes. While many gene discovery studies in the past were led by knowledge in the field (through the candidate gene strategy), now they often lead the scientific advances in the field by identifying new important biological players to be further characterized by in vitro and in vivo studies.

Pediatric Monogenic Diabetes: A Unique Challenge and Opportunity

Monogenic diabetes affects approximately 120,000 people in the United States but continues to be misdiagnosed. Within the pediatric population, 1% to 3% of diabetes is monogenic, and early diagnosis and genetically targeted management of congenital diabetes and maturity onset diabetes of the young (MODY) can have a tremendous impact on future health outcomes and quality of life. In some of the more common monogenic diabetes types, patients can switch from insulin therapy to sulfonylureas or even discontinue glucose-lowering therapy with stable glycemic control. Advancements in the field have identified tools and resources to aid in distinguishing patients likely to have monogenic diabetes from the more common forms of type 1 and type 2 diabetes. However, genetic testing with accurate interpretation of results is necessary to confirm a diagnosis and direct treatment selection and disease management. This article discusses challenges and opportunities in monogenic diabetes in the pediatric population. [Pediatr Ann. 2019;48(8):e319-e325.].

Phenotypic variability in two siblings with monogenic diabetes due to the same ABCC8 gene mutation

ABCC8 gene mutations with different inheritance patterns have been well described to cause transient and permanent forms of neonatal diabetes with onset of hyperglycemia commonly before the age of 6 months, and rare cases between 6 and 12 months. However, recent analyses have also demonstrated ABCC8 gene mutations in patients with monogenic diabetes (maturity onset diabetes of the young, MODY), with milder clinical phenotypes and later onset of hyperglycemia. We report two siblings with diabetes mellitus due to a novel homozygous p.(Phe1068Ile) (c.3202T>A) missense mutation of the ABCC8 gene, but significantly different phenotypes. The index case was diagnosed with diabetes due to an incidental finding of hyperglycemia at the age of 3 years, while her younger sibling presented with severe hyperglycemia and hyperosmolar dehydration at the age of 10 weeks. The possibility of a significant discordance in the correlation between genotype and phenotype needs to be taken into account when ABCC8 mutation dependent diabetes occurs within the same family. Genetic screening in children with diabetes from consanguineous family needs consideration, especially in case of negative autoantibodies and early onset of hyperglycemia.

Economics of Genetic Testing for Diabetes

PURPOSE OF REVIEW

Monogenic diabetes is an uncommon but important form of diabetes, with the most common causes benefitting from management that accounts for the genetic mutation. This often results in decreased costs and treatment burden for affected individuals. Misdiagnosis as type 1 and type 2 diabetes is common. Given the significant burden of diabetes costs to the healthcare system, it is important to assess the economic impact of incorporating genetic testing for monogenic diabetes into clinical care through formal cost-effectiveness analyses (CEAs). This article briefly summarizes the barriers to timely monogenic diabetes diagnosis and then summarizes findings from CEAs on genetic testing for monogenic diabetes.

RECENT FINDINGS

CEAs have shown that routine genetic testing of all patients with a clinical diagnosis of type 1 diabetes can be cost-saving when applied to the scenarios of neonatal diabetes or in a pediatric population. Routine screening has not been shown to be cost-effective in adult populations. However, next-generation sequencing strategies and applying biomarkers to identify and limit genetic testing to people most likely to have monogenic diabetes are promising ways to make testing strategies cost-effective. CEAs have shown that genetic testing for monogenic diabetes diagnosis can be cost-effective or cost-saving and should guide insurers to consider broader coverage of these tests, which would lead to accurate and timely diagnosis and impact treatment and clinical outcomes.

Cost-effectiveness Analysis of Routine Screening Using Massively Parallel Sequencing for Maturity-Onset Diabetes of the Young in a Pediatric Diabetes Cohort: Reduced Health System Costs and Improved Patient Quality of Life

OBJECTIVE

Maturity-onset diabetes of the young (MODY) is an autosomal dominant form of diabetes, with multiple causative genes. Some MODY subtypes can be treated with sulfonylureas instead of insulin, improving glycemic control, complication rates, quality of life (QoL), and costs. Using massively parallel sequencing (MPS), we recently determined the prevalence of pathogenic/likely pathogenic MODY variants in an Australian pediatric diabetes cohort. Here, these data are used to estimate cost-effectiveness of using MPS for MODY in all pediatric diabetes cases compared with standard practice (sequencing limited to individuals with specific clinical features).

RESEARCH DESIGN AND METHODS

A Markov decision model was developed to estimate incremental costs and quality-adjusted life-years (QALYs) of MPS screening, modeled over 30 years. We used our observed prevalence of 2.14% compared with 0.7% for standard practice, based on published data. The probabilities and utility weightings of long-term diabetes complications were based on HbA_1c and estimated from published data. A series of one-way sensitivity analyses were performed using the net monetary benefit framework.

RESULTS

Routine MPS screening for MODY was more effective and less costly than standard care screening, with 26 QALYs gained and 1,016,000 AUD (782,000 USD) saved per 1,000 patients. Cost of screening was fully offset within 10 years. Routine MPS screening remained dominant until MODY prevalence fell to <1.1%.

CONCLUSIONS

Routine MPS screening for MODY in the pediatric population with diabetes could reduce health system costs and improve patient QoL. Our results make a compelling argument for routine genetic screening in all children with presumed type 1 diabetes mellitus.

A Global Overview of Precision Medicine in Type 2 Diabetes

The detailed characterization of human biology and behaviors is now possible at scale owing to innovations in biomarkers, bioimaging, and wearable technologies; "big data" from electronic medical records, health insurance databases, and other platforms becoming increasingly accessible; and rapidly evolving computational power and bioinformatics methods. Collectively, these advances are creating unprecedented opportunities to better understand diabetes and many other complex traits. Identifying hidden structures within these complex data sets and linking these structures to outcome data may yield unique insights into the risk factors and natural history of diabetes, which in turn may help optimize the prevention and management of the disease. This emerging area is broadly termed "precision medicine." In this Perspective, we give an overview of the evidence and barriers to the development and implementation of precision medicine in type 2 diabetes. We also discuss recently presented paradigms through which complex data might enhance our understanding of diabetes and ultimately our ability to tackle the disease more effectively than ever before.

Monogenic diabetes: the impact of making the right diagnosis

PURPOSE OF REVIEW

Monogenic forms of diabetes have received increased attention and genetic testing is more widely available; however, many patients are still misdiagnosed as having type 1 (T1D) or type 2 diabetes. This review will address updates to monogenic diabetes prevalence, identification, treatment, and genetic testing.

RECENT FINDINGS

The creation of a T1D genetic risk score and the use of noninvasive urinary C-peptide creatinine ratios have provided new tools to aid in the discrimination of possible monogenic diabetes from likely T1D. Early, high-dose sulfonylurea treatment in infants with a KCNJ11 or ABCC8 mutation continues to be well tolerated and effective. As the field moves towards more comprehensive genetic testing methods, there is an increased opportunity to identify novel genetic causes. Genetic testing results continue to allow for personalized treatment but should provide patient information at an appropriate health literacy level.

SUMMARY

Although there have been clinical and genetic advances in monogenic diabetes, patients are still misdiagnosed. Improved insurance coverage of genetic testing is needed. The majority of data on monogenic diabetes has been collected from Caucasian populations, therefore, research studies should endeavor to include broader ethnic and racial diversity to provide comprehensive information for all populations.

Monogenic Diabetes in Children and Adolescents: Recognition and Treatment Options

PURPOSE OF REVIEW

We provide a review of monogenic diabetes in young children and adolescents with a focus on recognition, management, and pharmacological treatment.

RECENT FINDINGS

Monogenic forms of diabetes account for approximately 1-2% of diabetes in children and adolescents, and its incidence has increased in recent years due to greater awareness and wider availability of genetic testing. Monogenic diabetes is due to single gene defects that primarily affect beta cell function with more than 30 different genes reported. Children with antibody-negative, C-peptide-positive diabetes should be evaluated and genetically tested for monogenic diabetes. Accurate genetic diagnosis impacts treatment in the most common types of monogenic diabetes, including the use of sulfonylureas in place of insulin or other glucose-lowering agents or discontinuing pharmacologic treatment altogether. Diagnosis of monogenic diabetes can significantly improve patient care by enabling prediction of the disease course and guiding appropriate management and treatment.

Congenital Diabetes: Comprehensive Genetic Testing Allows for Improved Diagnosis and Treatment of Diabetes and Other Associated Features

PURPOSE OF REVIEW

The goal of this review is to provide updates on congenital (neonatal) diabetes from 2011 to present, with an emphasis on publications from 2015 to present.

RECENT FINDINGS

There has been continued worldwide progress in uncovering the genetic causes of diabetes presenting within the first year of life, including the recognition of nine new causes since 2011. Management has continued to be refined based on underlying molecular cause, and longer-term experience has provided better understanding of the effectiveness, safety, and sustainability of treatment. Associated conditions have been further clarified, such as neurodevelopmental delays and pancreatic insufficiency, including a better appreciation for how these "secondary" conditions impact quality of life for patients and their families. While continued research is essential to understand all forms of congenital diabetes, these cases remain a compelling example of personalized genetic medicine.

Whole-exome sequencing for mutation detection in pediatric disorders of insulin secretion: Maturity onset diabetes of the young and congenital hyperinsulinism

BACKGROUND

To assess the utility of whole-exome sequencing (WES) for mutation detection in maturity-onset diabetes of the young (MODY) and congenital hyperinsulinism (CHI). MODY and CHI are the two commonest monogenic disorders of glucose-regulated insulin secretion in childhood, with 13 causative genes known for MODY and 10 causative genes identified for CHI. The large number of potential genes makes comprehensive screening using traditional methods expensive and time-consuming.

METHODS

Ten subjects with MODY and five with CHI with known mutations underwent WES using two different exome capture kits (Nimblegen SeqCap EZ Human v3.0 Exome Enrichment Kit, Nextera Rapid Capture Exome Kit). Analysis was blinded to previously identified mutations, and included assessment for large deletions. The target capture of five exome capture technologies was also analyzed using sequencing data from >2800 unrelated samples.

RESULTS

Four of five MODY mutations were identified using Nimblegen (including a large deletion in HNF1B). Although targeted, one mutation (in INS) had insufficient coverage for detection. Eleven of eleven mutations (six MODY, five CHI) were identified using Nextera Rapid (including the previously missed mutation). On reconciliation, all mutations concorded with previous data and no additional variants in MODY genes were detected. There were marked differences in the performance of the capture technologies.

CONCLUSIONS

WES can be useful for screening for MODY/CHI mutations, detecting both point mutations and large deletions. However, capture technologies require careful selection.

Neonatal Diabetes Mellitus: An Update on Diagnosis and Management

Neonatal diabetes mellitus is likely to be due to an underlying monogenic defect when it occurs at less than 6 months of age. Early recognition and urgent genetic testing are important for predicting the clinical course and raising awareness of possible additional features. Early treatment of sulfonylurea-responsive types of neonatal diabetes may improve neurologic outcomes. It is important to distinguish neonatal diabetes mellitus from other causes of hyperglycemia in newborns. Other causes include infection, stress, inadequate pancreatic insulin production in preterm infants, among others. This review explores the diagnostic approach, mutation types, management, and clinical course of neonatal diabetes.

Congenital forms of diabetes: the beta-cell and beyond

The majority of patients diagnosed with diabetes less than 6 months of age, and many cases diagnosed between 6 and 12 months of age, have a gene mutation that causes permanent or transient hyperglycemia. Recent research advances have allowed for the discovery of new causes of congenital diabetes, including genes involved in pancreatic development (GATA4, NKX2-2, MNX1) and monogenic causes of autoimmune dysregulation (STAT3, LRBA). Ongoing follow-up of patients with KCNJ11 and ABCC8 mutations has supported the safety and efficacy of sulfonylureas, as well as the use of insulin pumps and continuous glucose monitors in infants with insulin-requiring forms of monogenic diabetes. Future studies are needed to improve clinical care and outcomes for these patients and their families.

Precision diabetes: learning from monogenic diabetes

The precision medicine approach of tailoring treatment to the individual characteristics of each patient or subgroup has been a great success in monogenic diabetes subtypes, MODY and neonatal diabetes. This review examines what has led to the success of a precision medicine approach in monogenic diabetes (precision diabetes) and outlines possible implications for type 2 diabetes. For monogenic diabetes, the molecular genetics can define discrete aetiological subtypes that have profound implications on diabetes treatment and can predict future development of associated clinical features, allowing early preventative or supportive treatment. In contrast, type 2 diabetes has overlapping polygenic susceptibility and underlying aetiologies, making it difficult to define discrete clinical subtypes with a dramatic implication for treatment. The implementation of precision medicine in neonatal diabetes was simple and rapid as it was based on single clinical criteria (diagnosed <6 months of age). In contrast, in MODY it was more complex and slow because of the lack of single criteria to identify patients, but it was greatly assisted by the development of a diagnostic probability calculator and associated smartphone app. Experience in monogenic diabetes suggests that successful adoption of a precision diabetes approach in type 2 diabetes will require simple, quick, easily accessible stratification that is based on a combination of routine clinical data, rather than relying on newer technologies. Analysing existing clinical data from routine clinical practice and trials may provide early success for precision medicine in type 2 diabetes.

Neonatal Diabetes: Case Report of a 9-Week-Old Presenting Diabetic Ketoacidosis Due to an Activating ABCC8 Gene Mutation

Context: Neonatal diabetes mellitus, a rare condition occurring in approximately 1 in 500 000 live births, is defined as insulin-requiring hyperglycemia presenting in the first months of life. Neonatal diabetes can be transient or permanent, with studies characterizing the condition as a monogenic disorder. Case Report: We describe a case of a 9-week-old infant with neonatal diabetes who presented in diabetic ketoacidosis due to a mutation affecting the ABCC8 gene that encodes the SUR1 subunit of the potassium ATP channel. Conclusion: This genetic diagnosis has therapeutic implications regarding the initiation of sulfonylurea administration as 85% of patients with neonatal diabetes due to ABCC8 gene mutations can be successfully treated with oral sulfonylurea treatment.

A systematic review and checklist presenting the main challenges for health economic modeling in personalized medicine: towards implementing patient-level models

INTRODUCTION

The ongoing development of genomic medicine and the use of molecular and imaging markers in personalized medicine (PM) has arguably challenged the field of health economic modeling (HEM). This study aims to provide detailed insights into the current status of HEM in PM, in order to identify if and how modeling methods are used to address the challenges described in literature. Areas covered: A review was performed on studies that simulate health economic outcomes for personalized clinical pathways. Decision tree modeling and Markov modeling were the most observed methods. Not all identified challenges were frequently found, challenges regarding companion diagnostics, diagnostic performance, and evidence gaps were most often found. However, the extent to which challenges were addressed varied considerably between studies. Expert commentary: Challenges for HEM in PM are not yet routinely addressed which may indicate that either (1) their impact is less severe than expected, (2) they are hard to address and therefore not managed appropriately, or (3) HEM in PM is still in an early stage. As evidence on the impact of these challenges is still lacking, we believe that more concrete examples are needed to illustrate the identified challenges and to demonstrate methods to handle them.

Implementing personalized medicine with asymmetric information on prevalence rates

Although personalized medicine is becoming the new paradigm to manage some diseases, the economics of personalized medicine have only focused on assessing the efficiency of specific treatments, lacking a theoretical framework analyzing the interactions between pharmaceutical firms and healthcare systems leading to the implementation of personalized treatments. We model the interaction between the hospitals and the manufacturer of a new treatment as an adverse selection problem where the firm does not have perfect information on the prevalence across hospitals of the genetic characteristics of the patients making them eligible to receive a new treatment. As a result of the model, hospitals with high prevalence rates benefit from the information asymmetry only when the standard treatment is inefficient when applied to the patients eligible to receive the new treatment. Otherwise, information asymmetry has no value. Personalized medicine may be fully or partially implemented depending on the proportion of high prevalence hospitals.

Identification of insulin gene variants in neonatal diabetes

OBJECTIVES

Permanent neonatal diabetes (PNDM) is caused by mutations in the genes responsible for the synthesis of different proteins that are important for the normal behavior of beta cells in the pancreas. Mutations in the insulin gene (INS) are considered as one of the causes of diabetes in neonates. This study aimed to investigate the genetic variations in the INS gene in a group of Egyptian infants diagnosed with PNDM.

METHODS

We screened exons 2 and 3 with intronic boundaries of the INS gene by direct gene sequencing in 30 PNDM patients and 20 healthy controls. A detailed clinical phenotyping of the patients was carried out to specify the diabetes features in those found to carry an INS variant.

RESULTS

We identified five variants (four SNPs and one synonymous variant), c(0).187 + 11T > C, c.-17-6T > A, c.*22A > C, c.*9C > T, and c.36G > A (p.A12A), with allelic frequencies of 96.7%, 80%, 75%, 5%, and 1.7%, respectively. All showed no statistically significance difference compared with the controls, with the exception of c.*22A > C.

CONCLUSION

Genetic screening for the INS gene did not reveal an evident role in the diagnosis of PNDM.

Economic Evaluations of Pharmacogenetic and Pharmacogenomic Screening Tests: A Systematic Review. Second Update of the Literature

Objective

Due to extended application of pharmacogenetic and pharmacogenomic screening (PGx) tests it is important to assess whether they provide good value for money. This review provides an update of the literature.

Methods

A literature search was performed in PubMed and papers published between August 2010 and September 2014, investigating the cost-effectiveness of PGx screening tests, were included. Papers from 2000 until July 2010 were included via two previous systematic reviews. Studies’ overall quality was assessed with the Quality of Health Economic Studies (QHES) instrument.

Results

We found 38 studies, which combined with the previous 42 studies resulted in a total of 80 included studies. An average QHES score of 76 was found. Since 2010, more studies were funded by pharmaceutical companies. Most recent studies performed cost-utility analysis, univariate and probabilistic sensitivity analyses, and discussed limitations of their economic evaluations. Most studies indicated favorable cost-effectiveness. Majority of evaluations did not provide information regarding the intrinsic value of the PGx test. There were considerable differences in the costs for PGx testing. Reporting of the direction and magnitude of bias on the cost-effectiveness estimates as well as motivation for the chosen economic model and perspective were frequently missing.

Conclusions

Application of PGx tests was mostly found to be a cost-effective or cost-saving strategy. We found that only the minority of recent pharmacoeconomic evaluations assessed the intrinsic value of the PGx tests. There was an increase in the number of studies and in the reporting of quality associated characteristics. To improve future evaluations, scenario analysis including a broad range of PGx tests costs and equal costs of comparator drugs to assess the intrinsic value of the PGx tests, are recommended. In addition, robust clinical evidence regarding PGx tests’ efficacy remains of utmost importance.

Some economics on personalized and predictive medicine

OBJECTIVE

To contribute to the theoretical literature on personalized medicine, analyzing and integrating in an economic model, the decision a health authority faces when it must decide on the implementation of personalized medicine in a context of uncertainty.

METHODS

We carry out a stylized model to analyze the decision health authorities face when they do not have perfect information about the best treatment for a population of patients with a given disease. The health authorities decide whether to use a test to match patients with treatments (personalized medicine) to maximize health outcomes. Our model characterizes the situations under which personalized medicine dominates the alternative option of business-as-usual (treatment without previous test). We apply the model to the KRAS test for colorectal cancer, the PCA3 test for prostate cancer and the PCR test for the X-fragile syndrome, to illustrate how the parameters and variables of the model interact.

RESULTS

Implementation of personalized medicine requires, as a necessary condition, having some tests with high discriminatory power. This is not a sufficient condition and expected health outcomes must be taken into account to make a decision. When the specificity and the sensitivity of the test are low, the health authority prefers to apply a treatment to all patients without using the test. When both characteristic of the test are high, the health authorities prefer to personalize the treatments when expected health outcomes are better than those under the standard treatment. When we applied the model to the three aforementioned tests, the results illustrate how decisions are adopted in real world.

CONCLUSIONS

Although promising, the use of personalized medicine is still under scrutiny as there are important issues demanding a response. Personalized medicine may have an impact in the drug development processes, and contribute to the efficiency and effectiveness of health care delivery. Nevertheless, more accurate statistical and economic information related to tests results and treatment costs as well as additional medical information on the efficacy of the treatments are needed to adopt decisions that incorporate economic rationality.

What Is the Best NGS Enrichment Method for the Molecular Diagnosis of Monogenic Diabetes and Obesity?

Molecular diagnosis of monogenic diabetes and obesity is of paramount importance for both the patient and society, as it can result in personalized medicine associated with a better life and it eventually saves health care spending. Genetic clinical laboratories are currently switching from Sanger sequencing to next-generation sequencing (NGS) approaches but choosing the optimal protocols is not easy. Here, we compared the sequencing coverage of 43 genes involved in monogenic forms of diabetes and obesity, and variant detection rates, resulting from four enrichment methods based on the sonication of DNA (Agilent SureSelect, RainDance technologies), or using enzymes for DNA fragmentation (Illumina Nextera, Agilent HaloPlex). We analyzed coding exons and untranslated regions of the 43 genes involved in monogenic diabetes and obesity. We found that none of the methods achieves yet full sequencing of the gene targets. Nonetheless, the RainDance, SureSelect and HaloPlex enrichment methods led to the best sequencing coverage of the targets; while the Nextera method resulted in the poorest sequencing coverage. Although the sequencing coverage was high, we unexpectedly found that the HaloPlex method missed 20% of variants detected by the three other methods and Nextera missed 10%. The question of which NGS technique for genetic diagnosis yields the highest diagnosis rate is frequently discussed in the literature and the response is still unclear. Here, we showed that the RainDance enrichment method as well as SureSelect, which are both based on the sonication of DNA, resulted in a good sequencing quality and variant detection, while the use of enzymes to fragment DNA (HaloPlex or Nextera) might not be the best strategy to get an accurate sequencing.

Age at the time of sulfonylurea initiation influences treatment outcomes in KCNJ11-related neonatal diabetes

AIMS/HYPOTHESIS

Individuals with heterozygous activating mutations of the KCNJ11 gene encoding a subunit of the ATP-sensitive potassium channel (KATP) can usually be treated with oral sulfonylurea (SU) pills in lieu of insulin injections. The aim of this study was to test our hypothesis that younger age at the time of initiation of SU therapy is correlated with lower required doses of SU therapy, shorter transition time and decreased likelihood of requiring additional diabetes medications.

METHODS

We performed a retrospective cohort study using data on 58 individuals with neonatal diabetes due to KCNJ11 mutations identified through the University of Chicago Monogenic Diabetes Registry ( http://monogenicdiabetes.uchicago.edu/registry ). We assessed the influence of age at initiation of SU therapy on treatment outcomes.

RESULTS

HbA1c fell from an average of 8.5% (69 mmol/mol) before transition to 6.2% (44 mmol/mol) after SU therapy (p < 0.001). Age of initiation of SU correlated with the dose (mg kg(-1) day(-1)) of SU required at follow-up (r = 0.80, p < 0.001). Similar associations were observed across mutation subtypes. Ten participants required additional glucose-lowering medications and all had initiated SU at age 13 years or older. No serious adverse events were reported.

CONCLUSIONS/INTERPRETATION

Earlier age at initiation of SU treatment is associated with improved response to SU therapy. Declining sensitivity to SU may be due to loss of beta cell mass over time in those treated with insulin. Our data support the need for early genetic diagnosis and appropriate personalised treatment in all cases of neonatal diabetes.

Sulfonylurea treatment before genetic testing in neonatal diabetes: pros and cons

CONTEXT

Diabetes in neonates nearly always has a monogenic etiology. Earlier sulfonylurea therapy can improve glycemic control and potential neurodevelopmental outcomes in children with KCNJ11 or ABCC8 mutations, the most common gene causes.

OBJECTIVE

Assess the risks and benefits of initiating sulfonylurea therapy before genetic testing results become available.

DESIGN, SETTING, AND PATIENTS

Observational retrospective study of subjects with neonatal diabetes within the University of Chicago Monogenic Diabetes Registry.

MAIN OUTCOME MEASURES

Response to sulfonylurea (determined by whether insulin could be discontinued) and treatment side effects in those treated empirically.

RESULTS

A total of 154 subjects were diagnosed with diabetes before 6 months of age. A genetic diagnosis had been determined in 118 (77%), with 73 (47%) having a mutation in KCNJ11 or ABCC8. The median time from clinical diagnosis to genetic diagnosis was 10.4 weeks (range, 1.6 to 58.2 wk). In nine probands, an empiric sulfonylurea trial was initiated within 28 days of diabetes diagnosis. A genetic cause was subsequently found in eight cases, and insulin was discontinued within 14 days of sulfonylurea initiation in all of these cases.

CONCLUSIONS

Sulfonylurea therapy appears to be safe and often successful in neonatal diabetes patients before genetic testing results are available; however, larger numbers of cases must be studied. Given the potential beneficial effect on neurodevelopmental outcome, glycemic control, and the current barriers to expeditious acquisition of genetic testing, an empiric inpatient trial of sulfonylurea can be considered. However, obtaining a genetic diagnosis remains imperative to inform long-term management and prognosis.