Penetrance and expressivity of mitochondrial variants in a large clinically unselected population.

Whole genome sequencing (WGS) from large clinically unselected cohorts provides a unique opportunity to assess the penetrance and expressivity of rare and/or known pathogenic mitochondrial variants in population. Using WGS from 179 862 clinically unselected individuals from the UK Biobank, we performed extensive single and rare variant aggregation association analyses of 15 881 mtDNA variants and 73 known pathogenic variants with 15 mitochondrial disease-relevant phenotypes. We identified 12 homoplasmic and one heteroplasmic variant (m.3243A>G) with genome-wide significant associations in our clinically unselected cohort. Heteroplasmic m.3243A>G (MAF = 0.0002, a known pathogenic variant) was associated with diabetes, deafness and heart failure and 12 homoplasmic variants increased aspartate aminotransferase levels including three low-frequency variants (MAF ~0.002 and beta~0.3 SD). Most pathogenic mitochondrial disease variants (n = 66/74) were rare in the population (<1:9000). Aggregated or single variant analysis of pathogenic variants showed low penetrance in unselected settings for the relevant phenotypes, except m.3243A>G. Multi-system disease risk and penetrance of diabetes, deafness and heart failure greatly increased with m.3243A>G level ≥ 10%. The odds ratio of these traits increased from 5.61, 12.3 and 10.1 to 25.1, 55.0 and 39.5, respectively. Diabetes risk with m.3243A>G was further influenced by type 2 diabetes genetic risk. Our study of mitochondrial variation in a large-unselected population identified novel associations and demonstrated that pathogenic mitochondrial variants have lower penetrance in clinically unselected settings. m.3243A>G was an exception at higher heteroplasmy showing a significant impact on health making it a good candidate for incidental reporting.

Reduced penetrance of MODY-associated HNF1A/HNF4A variants but not GCK variants in clinically unselected cohorts.

The true prevalence and penetrance of monogenic disease variants are often not known because of clinical-referral ascertainment bias. We comprehensively assess the penetrance and prevalence of pathogenic variants in HNF1A, HNF4A, and GCK that account for >80% of monogenic diabetes. We analyzed clinical and genetic data from 1,742 clinically referred probands, 2,194 family members, clinically unselected individuals from a US health system-based cohort (n = 132,194), and a UK population-based cohort (n = 198,748). We show that one in 1,500 individuals harbor a pathogenic variant in one of these genes. The penetrance of diabetes for HNF1A and HNF4A pathogenic variants was substantially lower in the clinically unselected individuals compared to clinically referred probands and was dependent on the setting (32% in the population, 49% in the health system cohort, 86% in a family member, and 98% in probands for HNF1A). The relative risk of diabetes was similar across the clinically unselected cohorts highlighting the role of environment/other genetic factors. Surprisingly, the penetrance of pathogenic GCK variants was similar across all cohorts (89%-97%). We highlight that pathogenic variants in HNF1A, HNF4A, and GCK are not ultra-rare in the population. For HNF1A and HNF4A, we need to tailor genetic interpretation and counseling based on the setting in which a pathogenic monogenic variant was identified. GCK is an exception with near-complete penetrance in all settings. This along with the clinical implication of diagnosis makes it an excellent candidate for the American College of Medical Genetics secondary gene list.

The relationship between islet autoantibody status and the genetic risk of type 1 diabetes in adult-onset type 1 diabetes.

AIMS/HYPOTHESIS: The reason for the observed lower rate of islet autoantibody positivity in clinician-diagnosed adult-onset vs childhood-onset type 1 diabetes is not known. We aimed to explore this by assessing the genetic risk of type 1 diabetes in autoantibody-negative and -positive children and adults. METHODS: We analysed GAD autoantibodies, insulinoma-2 antigen autoantibodies and zinc transporter-8 autoantibodies (ZnT8A) and measured type 1 diabetes genetic risk by genotyping 30 type 1 diabetes-associated variants at diagnosis in 1814 individuals with clinician-diagnosed type 1 diabetes (1112 adult-onset, 702 childhood-onset). We compared the overall type 1 diabetes genetic risk score (T1DGRS) and non-HLA and HLA (DR3-DQ2, DR4-DQ8 and DR15-DQ6) components with autoantibody status in those with adult-onset and childhood-onset diabetes. We also measured the T1DGRS in 1924 individuals with type 2 diabetes from the Wellcome Trust Case Control Consortium to represent non-autoimmune diabetes control participants. RESULTS: The T1DGRS was similar in autoantibody-negative and autoantibody-positive clinician-diagnosed childhood-onset type 1 diabetes (mean [SD] 0.274 [0.034] vs 0.277 [0.026], p=0.4). In contrast, the T1DGRS in autoantibody-negative adult-onset type 1 diabetes was lower than that in autoantibody-positive adult-onset type 1 diabetes (mean [SD] 0.243 [0.036] vs 0.271 [0.026], p<0.0001) but higher than that in type 2 diabetes (mean [SD] 0.229 [0.034], p<0.0001). Autoantibody-negative adults were more likely to have the more protective HLA DR15-DQ6 genotype (15% vs 3%, p<0.0001), were less likely to have the high-risk HLA DR3-DQ2/DR4-DQ8 genotype (6% vs 19%, p<0.0001) and had a lower non-HLA T1DGRS (p<0.0001) than autoantibody-positive adults. In contrast to children, autoantibody-negative adults were more likely to be male (75% vs 59%), had a higher BMI (27 vs 24 kg/m2) and were less likely to have other autoimmune conditions (2% vs 10%) than autoantibody-positive adults (all p<0.0001). In both adults and children, type 1 diabetes genetic risk was unaffected by the number of autoantibodies (p>0.3). These findings, along with the identification of seven misclassified adults with monogenic diabetes among autoantibody-negative adults and the results of a sensitivity analysis with and without measurement of ZnT8A, suggest that the intermediate type 1 diabetes genetic risk in autoantibody-negative adults is more likely to be explained by the inclusion of misclassified non-autoimmune diabetes (estimated to represent 67% of all antibody-negative adults, 95% CI 61%, 73%) than by the presence of unmeasured autoantibodies or by a discrete form of diabetes. When these estimated individuals with non-autoimmune diabetes were adjusted for, the prevalence of autoantibody positivity in adult-onset type 1 diabetes was similar to that in children (93% vs 91%, p=0.4). CONCLUSIONS/INTERPRETATION: The inclusion of non-autoimmune diabetes is the most likely explanation for the observed lower rate of autoantibody positivity in clinician-diagnosed adult-onset type 1 diabetes. Our data support the utility of islet autoantibody measurement in clinician-suspected adult-onset type 1 diabetes in routine clinical practice.

Phenotypic effect of GBA1 variants in individuals with and without Parkinson's disease: The RAPSODI study.

BACKGROUND: Variants in the GBA1 gene cause the lysosomal storage disorder Gaucher disease (GD). They are also risk factors for Parkinson's disease (PD), and modify the expression of the PD phenotype. The penetrance of GBA1 variants in PD is incomplete, and the ability to determine who among GBA1 variant carriers are at higher risk of developing PD, would represent an advantage for prognostic and trial design purposes. OBJECTIVES: To compare the motor and non-motor phenotype of GBA1 carriers and non-carriers. METHODS: We present the cross-sectional results of the baseline assessment from the RAPSODI study, an online assessment tool for PD patients and GBA1 variant carriers. The assessment includes clinically validated questionnaires, a tap-test, the University of Pennsyllvania Smell Identification Test and cognitive tests. Additional, homogeneous data from the PREDICT-PD cohort were included. RESULTS: A total of 379 participants completed all parts of the RAPSODI assessment (89 GBA1-negative controls, 169 GBA1-negative PD, 47 GBA1-positive PD, 47 non-affected GBA1 carriers, 27 GD). Eighty-six participants were recruited through PREDICT-PD (43 non-affected GBA1 carriers and 43 GBA1-negative controls). GBA1-positive PD patients showed worse performance in visual cognitive tasks and olfaction compared to GBA1-negative PD patients. No differences were detected between non-affected GBA1 carriers carriers and GBA1-negative controls. No phenotypic differences were observed between any of the non-PD groups. CONCLUSIONS: Our results support previous evidence that GBA1-positive PD has a specific phenotype with more severe non-motor symptoms. However, we did not reproduce previous findings of more frequent prodromal PD signs in non-affected GBA1 carriers.

Unsupervised Clustering of Missense Variants in HNF1A Using Multidimensional Functional Data Aids Clinical Interpretation.

Exome sequencing in diabetes presents a diagnostic challenge because depending on frequency, functional impact, and genomic and environmental contexts, HNF1A variants can cause maturity-onset diabetes of the young (MODY), increase type 2 diabetes risk, or be benign. A correct diagnosis matters as it informs on treatment, progression, and family risk. We describe a multi-dimensional functional dataset of 73 HNF1A missense variants identified in exomes of 12,940 individuals. Our aim was to develop an analytical framework for stratifying variants along the HNF1A phenotypic continuum to facilitate diagnostic interpretation. HNF1A variant function was determined by four different molecular assays. Structure of the multi-dimensional dataset was explored using principal component analysis, k-means, and hierarchical clustering. Weights for tissue-specific isoform expression and functional domain were integrated. Functionally annotated variant subgroups were used to re-evaluate genetic diagnoses in national MODY diagnostic registries. HNF1A variants demonstrated a range of behaviors across the assays. The structure of the multi-parametric data was shaped primarily by transactivation. Using unsupervised learning methods, we obtained high-resolution functional clusters of the variants that separated known causal MODY variants from benign and type 2 diabetes risk variants and led to reclassification of 4% and 9% of HNF1A variants identified in the UK and Norway MODY diagnostic registries, respectively. Our proof-of-principle analyses facilitated informative stratification of HNF1A variants along the continuum, allowing improved evaluation of clinical significance, management, and precision medicine in diabetes clinics. Transcriptional activity appears a superior readout supporting pursuit of transactivation-centric experimental designs for high-throughput functional screens.

Systematic genetic testing for recessively inherited monogenic diabetes: a cross-sectional study in paediatric diabetes clinics.

AIMS/HYPOTHESIS: Current clinical guidelines for childhood-onset monogenic diabetes outside infancy are mainly focused on identifying and testing for dominantly inherited, predominantly MODY genes. There are no systematic studies of the recessively inherited causes of monogenic diabetes that are likely to be more common in populations with high rates of consanguinity. We aimed to determine the contribution of recessive causes of monogenic diabetes in paediatric diabetes clinics and to identify clinical criteria by which to select individuals for recessive monogenic diabetes testing. METHODS: We conducted a cross-sectional study of 1093 children from seven paediatric diabetes clinics across Turkey (a population with high rates of consanguinity). We undertook genetic testing of 50 known dominant and recessive causes of monogenic diabetes for 236 children at low risk of type 1 diabetes. As a comparison, we used monogenic diabetes cases from UK paediatric diabetes clinics (a population with low rates of consanguinity). RESULTS: Thirty-four children in the Turkish cohort had monogenic diabetes, equating to a minimal prevalence of 3.1%, similar to that in the UK cohort (p = 0.40). Forty-one per cent (14/34) had autosomal recessive causes in contrast to 1.6% (2/122) in the UK monogenic diabetes cohort (p < 0.0001). All conventional criteria for identifying monogenic diabetes (parental diabetes, not requiring insulin treatment, HbA1c ≤ 58 mmol/mol [≤7.5%] and a composite clinical probability of MODY >10%) assisted the identification of the dominant (all p ≤ 0.0003) but not recessive cases (all p ≥ 0.2) in Turkey. The presence of certain non-autoimmune extra-pancreatic features greatly assisted the identification of recessive (p < 0.0001, OR 66.9) but not dominant cases. CONCLUSIONS/INTERPRETATION: Recessively inherited mutations are a common cause of monogenic diabetes in populations with high rates of consanguinity. Present MODY-focused genetic testing strategies do not identify affected individuals. To detect all cases of monogenic paediatric diabetes, it is crucial that recessive genes are included in genetic panels and that children are selected for testing if they have certain non-autoimmune extra-pancreatic features in addition to current criteria.

How do I diagnose Maturity Onset Diabetes of the Young in my patients?

Maturity Onset Diabetes of the Young (MODY) is a monogenic form of diabetes diagnosed in young individuals that lack the typical features of type 1 and type 2 diabetes. The genetic subtype of MODY determines the most effective treatment and this is the driver for MODY genetic testing in diabetes populations. Despite the obvious clinical and health economic benefits, MODY is significantly underdiagnosed with the majority of patients being inappropriately managed as having type 1 or type 2 diabetes. Low detection rates result from the difficulty in identifying patients with a likely diagnosis of MODY from the high background population of young onset type 1 and type 2 diabetes, compounded by the lack of MODY awareness and education in diabetes care physicians. MODY diagnosis can be improved through (1) access to education and training, (2) the use of sensitive and specific selection criteria based on accurate prediction models and biomarkers to identify patients for testing, (3) the development and mainstream implementation of simple criteria-based selection pathways applicable across a range of healthcare settings and ethnicities to select the most appropriate patients for genetic testing and (4) the correct use of next generation sequencing technology to provide accurate and comprehensive testing of all known MODY and monogenic diabetes genes. The creation and public sharing of educational materials, clinical and scientific best practice guidelines and genetic variants will help identify the missing patients so they can benefit from the more effective clinical care that a genetic diagnosis brings.

Evaluation of pregnancy outcomes in women with GCK-MODY.

AIMS: To determine the fetal and maternal outcomes in pregnant women with Glucokinase-Maturity onset diabetes of the young (GCK-MODY). METHODS: We studied the obstetric and perinatal outcomes in 99 pregnancies of 34 women with GCK-MODY. The mutation status of the offspring was known in 29 and presumed in 33. Clinical outcomes were determined and compared between affected (n = 39) and unaffected (n = 23) offspring. RESULTS: 59% of pregnancies were treated with diet alone and 41% received insulin. Birthweight, percentage of large for gestational age (LGA) and caesarean section (CS) in GCK-unaffected offspring was significantly higher than in GCK-affected offspring (4.0 ± 0.7 vs. 3.4 ± 0.4 kg, p = 0.001), 15 (65%) vs. 5(13%) (p = 0.00006) and 17 (74%) vs. 11 (28%) (p = 0.001), respectively. We observed an earlier gestational age at delivery on insulin in unaffected offspring (38.3 ± 1.0 vs. 39.5 ± 1.5 weeks, p = 0.03) with no significant change in LGA (9 (82%) vs. 6 (50%); p = 0.12), and a higher rate of CS (8 [73%] vs. 3 [11%]; p < 0.001), and no change in small for gestational age (0 [0%] vs. 4 [14%]; p = 0.30) in affected offspring. CONCLUSION: Insulin therapy in unaffected offspring did not reduce LGA and was associated with earlier gestational age at delivery. Insulin treatment in GCK-affected offspring was associated with an increased incidence of CS, but did not adversely affect fetal outcome. Fetal genotype determines birthweight rather than treatment. Pre-pregnancy diagnosis of GCK-MODY, use of continuous glucose monitoring and non-invasive fetal genotyping may enable further investigation of targeted therapy in this condition.

Case report: adult onset diabetes with partial pancreatic agenesis and congenital heart disease due to a de novo GATA6 mutation.

BACKGROUND: Mutations in GATA6 are the most frequent cause of pancreatic agenesis. Most cases present with neonatal diabetes mellitus. CASE PRESENTATION: The case was a female born after an uncomplicated pregnancy and delivery in a non-consanguineous family (3.59 kg, 70th percentile). Severe cardiac malformations were diagnosed at two and a half months old. No hyperglycaemic episodes were recorded in the neonatal period. Diabetes was diagnosed at 21 years due to the detection of incidental glycosuria. She had a low but detectable C-peptide level at diagnosis. Anti-GAD and Islet-cell antibodies were negative and she failed oral hypoglycaemic therapy and was started on insulin. Abdominal MRI revealed the absence of most of the neck, body, and tail of pancreas with normal pancreas elastase levels. Criteria for type 1 or type 2 diabetes were not fulfilled, therefore a next generation sequencing (NGS) panel was performed. A novel heterozygous pathogenic GATA6 mutation (p.Tyr235Ter) was identified. The GATA6 variant was not detected in her parents, implying that the mutation had arisen de novo in the proband. CONCLUSION: Rarely GATA6 mutations can cause adult onset diabetes. This report highlights the importance of screening the GATA6 gene in patients with adult-onset diabetes, congenital cardiac defects and pancreatic agenesis with no first-degree family history of diabetes. It also emphasizes the importance of genetic counselling in these patients as future offspring will be at risk of inheriting the variant and developing GATA6 anomalies.

Towards a systematic nationwide screening strategy for MODY.

MODY is an early-onset monogenic form of diabetes. Correctly identifying MODY is of considerable importance as diagnosing the specific genetic subtype can inform the optimal treatment, with many patients being able to discontinue unnecessary insulin treatment. Diagnostic molecular genetic testing to confirm MODY is expensive, so screening strategies are required to identify the most appropriate patients for testing. In this issue of Diabetologia, Johansson and colleagues (DOI 10.1007/s00125-016-4167-1 ) describe a nationwide systematic screening approach to identify individuals with MODY in the paediatric age range. They focused testing on patients negative for both GAD and islet antigen 2 (IA-2) islet autoantibodies, thereby ruling out those with markers of type 1 diabetes, the most common form of diabetes in this age group. This commentary discusses the advantages and limitations of the approach, and the caution required when interpreting variants of uncertain pathogenicity identified from testing whole populations rather than targeting only patients with a strong MODY phenotype.

The prevalence of monogenic diabetes in Australia: the Fremantle Diabetes Study Phase II.

OBJECTIVE: To determine the prevalence of monogenic diabetes in an Australian community. DESIGN: Longitudinal observational study of a cohort recruited between 2008 and 2011. SETTING: Urban population of 157 000 people (Fremantle, Western Australia). PARTICIPANTS: 1668 (of 4639 people with diabetes) who consented to participation (36.0% participation). MAIN OUTCOME MEASURES: Prevalence of maturity-onset diabetes of the young (MODY) and permanent neonatal diabetes in patients under 35 years of age, from European and non-European ethnic backgrounds, who were at risk of MODY according to United Kingdom risk prediction models, and who were then genotyped for relevant mutations. RESULTS: Twelve of 148 young participants with European ethnic backgrounds (8%) were identified by the risk prediction model as likely to have MODY; four had a glucokinase gene mutation. Thirteen of 45 with non-European ethnic backgrounds (28%) were identified as likely to have MODY, but none had a relevant mutation (DNA unavailable for one patient). Two patients with European ethnic backgrounds (one likely to have MODY) had neonatal diabetes. The estimated MODY prevalence among participants with diagnosed diabetes was 0.24% (95% confidence interval [CI], 0.08-0.66%), an overall population prevalence of 89 cases per million; the prevalence of permanent neonatal diabetes was 0.12% (95% CI, 0.02-0.48%) and the population prevalence 45 cases per million. CONCLUSIONS: One in 280 Australians diagnosed with diabetes have a monogenic form; most are of European ethnicity. Diagnosing MODY and neonatal diabetes is important because their management (including family screening) and prognosis can differ significantly from those for types 1 and 2 diabetes.

Phenotypic severity of homozygous GCK mutations causing neonatal or childhood-onset diabetes is primarily mediated through effects on protein stability.

Mutations in glucokinase (GCK) cause a spectrum of glycemic disorders. Heterozygous loss-of-function mutations cause mild fasting hyperglycemia irrespective of mutation severity due to compensation from the unaffected allele. Conversely, homozygous loss-of-function mutations cause permanent neonatal diabetes requiring lifelong insulin treatment. This study aimed to determine the relationship between in vitro mutation severity and clinical phenotype in a large international case series of patients with homozygous GCK mutations. Clinical characteristics for 30 patients with diabetes due to homozygous GCK mutations (19 unique mutations, including 16 missense) were compiled and assigned a clinical severity grade (CSG) based on birth weight and age at diagnosis. The majority (28 of 30) of subjects were diagnosed before 9 months, with the remaining two at 9 and 15 years. These are the first two cases of a homozygous GCK mutation diagnosed outside infancy. Recombinant mutant GCK proteins were analyzed for kinetic and thermostability characteristics and assigned a relative activity index (RAI) or relative stability index (RSI) value. Six of 16 missense mutations exhibited severe kinetic defects (RAI ≤ 0.01). There was no correlation between CSG and RAI (r(2) = 0.05, P = 0.39), indicating that kinetics alone did not explain the phenotype. Eighty percent of the remaining mutations showed reduced thermostability, the exceptions being the two later-onset mutations which exhibited increased thermostability. Comparison of CSG with RSI detected a highly significant correlation (r(2) = 0.74, P = 0.002). We report the largest case series of homozygous GCK mutations to date and demonstrate that they can cause childhood-onset diabetes, with protein instability being the major determinant of mutation severity.

Characteristics of maturity onset diabetes of the young in a large diabetes center.

Maturity onset diabetes of the young (MODY) is a monogenic form of diabetes caused by a mutation in a single gene, often not requiring insulin. The aim of this study was to estimate the frequency and clinical characteristics of MODY at the Barbara Davis Center. A total of 97 subjects with diabetes onset before age 25, a random C-peptide ≥0.1 ng/mL, and negative for all diabetes autoantibodies (GADA, IA-2, ZnT8, and IAA) were enrolled, after excluding 21 subjects with secondary diabetes or refusal to participate. Genetic testing for MODY 1-5 was performed through Athena Diagnostics, and all variants of unknown significance were further analyzed at Exeter, UK. A total of 22 subjects [20 (21%) when excluding two siblings] were found to have a mutation in hepatocyte nuclear factor 4A (n = 4), glucokinase (n = 8), or hepatocyte nuclear factor 1A (n = 10). Of these 22 subjects, 13 had mutations known to be pathogenic and 9 (41%) had novel mutations, predicted to be pathogenic. Only 1 of the 22 subjects had been given the appropriate MODY diagnosis prior to testing. Compared with MODY-negative subjects, the MODY-positive subjects had lower hemoglobin A1c level and no diabetic ketoacidosis at onset; however, these characteristics are not specific for MODY. In summary, this study found a high frequency of MODY mutations with the majority of subjects clinically misdiagnosed. Clinicians should have a high index of suspicion for MODY in youth with antibody-negative diabetes.

Cross-sectional and longitudinal studies suggest pharmacological treatment used in patients with glucokinase mutations does not alter glycaemia.

AIMS/HYPOTHESIS: Heterozygous glucokinase (GCK) mutations cause mild, fasting hyperglycaemia from birth. Although patients are usually asymptomatic and have glycaemia within target ranges, some are put on pharmacological treatment. We aimed to investigate how many patients are on pharmacological treatment and the impact of treatment on glycaemic control. METHODS: Treatment details were ascertained for 799 patients with heterozygous GCK mutations. In a separate, longitudinal study, HbA1c was obtained for 16 consecutive patients receiving insulin (n = 10) or oral hypoglycaemic agents (OHAs) (n = 6) whilst on treatment, and again having discontinued treatment following a genetic diagnosis of GCK-MODY. For comparison, HbA1c before and after genetic testing was studied in a control group (n = 18) not receiving pharmacological therapy. RESULTS: At referral for genetic testing, 168/799 (21%) of patients were on pharmacological treatment (13.5% OHAs, 7.5% insulin). There was no difference in the HbA1c of these patients compared with those receiving no treatment(median [IQR]: 48 [43, 51] vs 46 [43, 50] mmol/mol, respectively; 6.5% [6.1%, 6.8%] vs 6.4% [6.1%, 6.7%]; p = 0.11). Following discontinuation of pharmacological treatment in 16 patients, HbA1c did not change. The mean change in HbA1c was -0.68 mmol/mol (95% CI: -2.97, 1.61) (-0.06% [95% CI: -0.27, 0.15]). CONCLUSIONS/INTERPRETATION: Prior to a genetic diagnosis, 21% of patients were on pharmacological treatment. HbA1c was no higher than in untreated patients and did not change when therapy was discontinued, suggesting no impact on glycaemia. The lack of response to pharmacological therapy is likely to reflect the regulated hyperglycaemia seen in these patients owing to their glucose sensing defect and is an example of pharmacogenetics.

Prevalence of vascular complications among patients with glucokinase mutations and prolonged, mild hyperglycemia.

IMPORTANCE: Glycemic targets in diabetes have been developed to minimize complication risk. Patients with heterozygous, inactivating glucokinase (GCK) mutations have mild fasting hyperglycemia from birth, resulting in an elevated glycated hemoglobin (HbA1c) level that mimics recommended levels for type 1 and type 2 diabetes. OBJECTIVE: To assess the association between chronic, mild hyperglycemia and complication prevalence and severity in patients with GCK mutations. DESIGN, SETTING, AND PARTICIPANTS: Cross-sectional study in the United Kingdom between August 2008 and December 2010. Assessment of microvascular and macrovascular complications in participants 35 years or older was conducted in 99 GCK mutation carriers (median age, 48.6 years), 91 nondiabetic, familial, nonmutation carriers (control) (median age, 52.2 years), and 83 individuals with young-onset type 2 diabetes (YT2D), diagnosed at age 45 years or younger (median age, 54.7 years). MAIN OUTCOMES AND MEASURES: Prevalence and severity of nephropathy, retinopathy, peripheral neuropathy, peripheral vascular disease, and cardiovascular disease. RESULTS: Median HbA1c was 6.9% in patients with the GCK mutation, 5.8% in controls, and 7.8% in patients with YT2D. Patients with GCK had a low prevalence of clinically significant microvascular complications (1% [95% CI, 0%-5%]) that was not significantly different from controls (2% [95% CI, 0.3%-8%], P=.52) and lower than in patients with YT2D (36% [95% CI, 25%-47%], P<.001). Thirty percent of patients with GCK had retinopathy (95% CI, 21%-41%) compared with 14% of controls (95% CI, 7%-23%, P=.007) and 63% of patients with YT2D (95% CI, 51%-73%, P<.001). Neither patients with GCK nor controls required laser therapy for retinopathy compared with 28% (95% CI, 18%-39%) of patients with YT2D (P<.001). Neither patients with GCK patients nor controls had proteinuria and microalbuminuria was rare (GCK, 1% [95% CI, 0.2%-6%]; controls, 2% [95% CI, 0.2%-8%]), whereas 10% (95% CI, 4%-19%) of YT2D patients had proteinuria (P<.001 vs GCK) and 21% (95% CI, 13%-32%) had microalbuminuria (P<.001). Neuropathy was rare in patients with GCK (2% [95% CI, 0.3%-8%]) and controls (95% CI, 0% [0%-4%]) but present in 29% (95% CI, 20%-50%) of YT2D patients (P<.001). Patients with GCK had a low prevalence of clinically significant macrovascular complications (4% [95% CI, 1%-10%]) that was not significantly different from controls (11% [95% CI, 5%-19%]; P=.09), and lower in prevalence than patients with YT2D (30% [95% CI, 21%-41%], P<.001). CONCLUSIONS AND RELEVANCE: Despite a median duration of 48.6 years of hyperglycemia, patients with a GCK mutation had low prevalence of microvascular and macrovascular complications. These findings may provide insights into the risks associated with isolated, mild hyperglycemia.

Identification of monogenic diabetes in an Australian cohort using the Exeter maturity-onset diabetes of the young (MODY) probability calculator and next-generation sequencing gene panel testing.

AIMS: This study aims to describe the prevalence of monogenic diabetes in an Australian referral cohort, in relation to Exeter maturity-onset diabetes of the young (MODY) probability calculator (EMPC) scores and next-generation sequencing with updated testing where relevant. METHODS: State-wide 5-year retrospective cohort study of individuals referred for monogenic diabetes genetic testing. RESULTS: After excluding individuals who had cascade testing for a familial variant (21) or declined research involvement (1), the final cohort comprised 40 probands. Incorporating updated testing, the final genetic result was positive (likely pathogenic/pathogenic variant) in 11/40 (27.5%), uncertain (variant of uncertain significance) in 8/40 (20%) and negative in 21/40 (52.5%) participants. Causative variants were found in GCK, HNF1A, MT-TL1 and HNF4A. Variants of uncertain significance included a novel multi-exonic GCK duplication. Amongst participants with EMPC scores ≥ 25%, a causative variant was identified in 37%. Cascade testing was positive in 9/10 tested relatives with diabetes and 0/6 tested relatives with no history of diabetes. CONCLUSIONS: Contemporary genetic testing produces a high yield of positive results in individuals with clinically suspected monogenic diabetes and their relatives with diabetes, highlighting the value of genetic testing for this condition. An EMPC score cutoff of ≥ 25% correctly yielded a positive predictive value of ≥ 25% in this multiethnic demographic. This is the first Australian study to describe EMPC scores in the Australian clinic setting, albeit a biased referral cohort. Larger studies may help characterise EMPC performance between ethnic subsets, noting differences in the expected probability of monogenic diabetes relative to type 2 diabetes.

Molecular mechanism of HNF-1A-mediated HNF4A gene regulation and promoter-driven HNF4A-MODY diabetes.

Monogenic diabetes is a gateway to precision medicine through molecular mechanistic insight. Hepatocyte nuclear factor 1A (HNF-1A) and HNF-4A are transcription factors that engage in crossregulatory gene transcription networks to maintain glucose-stimulated insulin secretion in pancreatic ß cells. Variants in the HNF1A and HNF4A genes are associated with maturity-onset diabetes of the young (MODY). Here, we explored 4 variants in the P2-HNF4A promoter region: 3 in the HNF-1A binding site and 1 close to the site, which were identified in 63 individuals from 21 families of different MODY disease registries across Europe. Our goal was to study the disease causality for these variants and to investigate diabetes mechanisms on the molecular level. We solved a crystal structure of HNF-1A bound to the P2-HNF4A promoter and established a set of techniques to probe HNF-1A binding and transcriptional activity toward different promoter variants. We used isothermal titration calorimetry, biolayer interferometry, x-ray crystallography, and transactivation assays, which revealed changes in HNF-1A binding or transcriptional activities for all 4 P2-HNF4A variants. Our results suggest distinct disease mechanisms of the promoter variants, which can be correlated with clinical phenotype, such as age of diagnosis of diabetes, and be important tools for clinical utility in precision medicine.

Development of a clinical calculator to aid the identification of MODY in pediatric patients at the time of diabetes diagnosis.

Maturity Onset Diabetes of the Young (MODY) is a young-onset, monogenic form of diabetes without needing insulin treatment. Diagnostic testing is expensive. To aid decisions on who to test, we aimed to develop a MODY probability calculator for paediatric cases at the time of diabetes diagnosis, when the existing "MODY calculator" cannot be used. Firth logistic regression models were developed on data from 3541 paediatric patients from the Swedish 'Better Diabetes Diagnosis' (BDD) population study (n = 46 (1.3%) MODY (HNF1A, HNF4A, GCK)). Model performance was compared to using islet autoantibody testing. HbA1c, parent with diabetes, and absence of polyuria were significant independent predictors of MODY. The model showed excellent discrimination (c-statistic = 0.963) and calibrated well (Brier score = 0.01). MODY probability > 1.3% (ie. above background prevalence) had similar performance to being negative for all 3 antibodies (positive predictive value (PPV) = 10% v 11% respectively i.e. ~ 1 in 10 positive test rate). Probability > 1.3% and negative for 3 islet autoantibodies narrowed down to 4% of the cohort, and detected 96% of MODY cases (PPV = 31%). This MODY calculator for paediatric patients at time of diabetes diagnosis will help target genetic testing to those most likely to benefit, to get the right diagnosis.