Genetic cause of hyperglycaemia and response to treatment in diabetes

Management of pregnancy in women with monogenic diabetes due to mutations in GCK, HNF1A and HNF4A genes

Women with maturity-onset diabetes of the young (MODY) need tailored antenatal care and monitoring of their offspring. Each MODY subtype has different implications for glycaemic targets, treatment choices and neonatal management. Hyperglycaemia of MODY is often first diagnosed in adolescence or early adulthood and therefore is clinically relevant to pregnant women. MODY remains an under-recognised and undiagnosed condition. Pregnancy represents an opportune time to make a genetic diagnosis of MODY and provide precision treatment. This review describes the nuance of antenatal care in women with MODY and the implications for pregnancies affected by a positive paternal genotype. Mutations in hepatic nuclear factor 1-alpha (HNF1A) and 4-alpha (HNF4A) genes are associated with progressive β-cell dysfunction resulting in early onset diabetes. Patients are largely managed with sulphonylureas outside of pregnancy. Macrosomia and persistent neonatal hypoglycaemia are reported in 54% and 15% of HNF4A genotype positive offspring respectively with a median increase in birthweight of 790 g. Close observation of foetal growth in utero allows optimal timing of delivery to minimise peri- and postpartum materno-foetal complications. Glucokinase (GCK)-MODY causes mild fasting hyperglycaemia which does not require treatment outside of pregnancy. Birthweight of offspring of maternal carriers is dependent on foetal genotype; heterozygous mutation carriers are usually normal weight while genotype negative offspring are large for gestational age (600 g heavier). Affected offspring of paternal carriers may be small for gestational age (500 g lighter). Serial growth scans with measurement of the abdominal circumference indirectly differentiate foetal genotype. Measurement of cell free foetal DNA in maternal blood from the late first trimester is superior to traditionally used ultrasound to distinguish foetal genotype. Cost and accessibility may limit its use.

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 β 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.

A Woman With HNF1A-Associated Monogenic Diabetes Treated Successfully With Repaglinide Monotherapy

Background/Objective

Monogenic diabetes is a rare type of diabetes that is commonly misdiagnosed as type 1 or 2 diabetes mellitus, which adversely impacts patient care. Such cases are particularly challenging given the heterogeneity in presentation and overlap with other types of diabetes. As the sole use of meglitinides, especially repaglinide, to treat HNF1A-associated monogenic diabetes has been rarely reported in a few other observational studies, we describe a patient who was treated successfully with repaglinide.

Case Report

A 38-year-old woman with type 1 diabetes mellitus, congenital deafness, chronic kidney disease, and retinopathy presented with difficulty controlling her blood glucose levels. Although initially treated with insulin, she had periods of noncompliance with insulin without experiencing diabetic ketoacidosis. Although on insulin therapy, she experienced multiple episodes of hypoglycemia. The laboratory tests showed a hemoglobin A1c level of 10.8%, c-peptide level of 2.7 ng/mL (1.1-4.4 ng/mL), glucose level of 192 mg/dL, creatinine level of 1.23 ng/dL, and severely increased microalbumin-to-creatinine ratio of 638 mg/g (normal range, 0-29 mg/g). Pancreatic autoantibodies were negative. Genetic testing revealed a diagnosis of HNF1A-associated monogenic diabetes (c. 1340C>T (p.P447L)). She was ultimately treated with repaglinide after trials of sulfonylureas and dipeptidyl peptidase 4 inhibitors led to frequent hypoglycemia and a significant increase in the hemoglobin A1c level, respectively.

Discussion

This case highlights the importance of correctly diagnosing monogenic diabetes and reports the successful use of repaglinide to treat HNF1A-associated monogenic diabetes.

Conclusion

Patients with HNF1A-associated monogenic diabetes who do not achieve euglycemia with sulfonylureas and insulin may be successfully treated with repaglinide monotherapy.

Characterisation of HNF1A variants in paediatric diabetes in Norway using functional and clinical investigations to unmask phenotype and monogenic diabetes

AIMS/HYPOTHESIS

Correctly diagnosing MODY is important, as individuals with this diagnosis can discontinue insulin injections; however, many people are misdiagnosed. We aimed to develop a robust approach for determining the pathogenicity of variants of uncertain significance in hepatocyte nuclear factor-1 alpha (HNF1A)-MODY and to obtain an accurate estimate of the prevalence of HNF1A-MODY in paediatric cases of diabetes.

METHODS

We extended our previous screening of the Norwegian Childhood Diabetes Registry by 830 additional samples and comprehensively genotyped HNF1A variants in autoantibody-negative participants using next-generation sequencing. Carriers of pathogenic variants were treated by local healthcare providers, and participants with novel likely pathogenic variants and variants of uncertain significance were enrolled in an investigator-initiated, non-randomised, open-label pilot study (ClinicalTrials.gov registration no. NCT04239586). To identify variants associated with HNF1A-MODY, we functionally characterised their pathogenicity and assessed the carriers' phenotype and treatment response to sulfonylurea.

RESULTS

In total, 615 autoantibody-negative participants among 4712 cases of paediatric diabetes underwent genetic sequencing, revealing 19 with HNF1A variants. We identified nine carriers with novel variants classified as variants of uncertain significance or likely to be pathogenic, while the remaining ten participants carried five pathogenic variants previously reported. Of the nine carriers with novel variants, six responded favourably to sulfonylurea. Functional investigations revealed their variants to be dysfunctional and demonstrated a correlation with the resulting phenotype, providing evidence for reclassifying these variants as pathogenic.

CONCLUSIONS/INTERPRETATION

Based on this robust classification, we estimate that the prevalence of HNF1A-MODY is 0.3% in paediatric diabetes. Clinical phenotyping is challenging and functional investigations provide a strong complementary line of evidence. We demonstrate here that combining clinical phenotyping with functional protein studies provides a powerful tool to obtain a precise diagnosis of HNF1A-MODY.

Epigenetic and transcriptional regulation of the human angiotensinogen gene by high salt

Hypertension is caused by a combination of genetic and environmental factors. Angiotensinogen (AGT) is a component of RAAS, that regulates blood pressure. The human angiotensinogen (hAGT) gene has -6A/-6G polymorphism and -6A variant is associated with human hypertension. In this study, we have investigated the epigenetic regulation of the hAGT. To understand transcriptional regulation of the hAGT, we have made transgenic animals containing -6A. We show that HS affects DNA methylation and modulates transcriptional regulation of this gene in liver and kidney. High salt (HS) increases hAGT gene expression in -6A TG mice. We have observed that the number of CpG sites in the hAGT promoter is decreased after HS treatment. In the liver, seven CpG sites are methylated whereas after HS treatment, only three CpG sites remain methylated. In the kidney, five CpG sites are methylated, whereas after HS treatment, only three CpG sites remain methylated. These results suggest that HS promotes DNA demethylation and increasing AGT gene expression. RT-PCR and immunoblot analysis show that hAGT gene expression is increased by HS. Chip assay has shown that transcription factors bind strongly after HS treatment. RNA-Seq identified differentially expressed genes, novel target genes associated with hypertension, top canonical pathways, upstream regulators. One of the plausible mechanisms for HS induced up-regulation of the hAGT gene is through IL-6/JAK/STAT3/AGT axis.

The use of precision diagnostics for monogenic diabetes: a systematic review and expert opinion

BACKGROUND

Monogenic diabetes presents opportunities for precision medicine but is underdiagnosed. This review systematically assessed the evidence for (1) clinical criteria and (2) methods for genetic testing for monogenic diabetes, summarized resources for (3) considering a gene or (4) variant as causal for monogenic diabetes, provided expert recommendations for (5) reporting of results; and reviewed (6) next steps after monogenic diabetes diagnosis and (7) challenges in precision medicine field.

METHODS

Pubmed and Embase databases were searched (1990-2022) using inclusion/exclusion criteria for studies that sequenced one or more monogenic diabetes genes in at least 100 probands (Question 1), evaluated a non-obsolete genetic testing method to diagnose monogenic diabetes (Question 2). The risk of bias was assessed using the revised QUADAS-2 tool. Existing guidelines were summarized for questions 3-5, and review of studies for questions 6-7, supplemented by expert recommendations. Results were summarized in tables and informed recommendations for clinical practice.

RESULTS

There are 100, 32, 36, and 14 studies included for questions 1, 2, 6, and 7 respectively. On this basis, four recommendations for who to test and five on how to test for monogenic diabetes are provided. Existing guidelines for variant curation and gene-disease validity curation are summarized. Reporting by gene names is recommended as an alternative to the term MODY. Key steps after making a genetic diagnosis and major gaps in our current knowledge are highlighted.

CONCLUSIONS

We provide a synthesis of current evidence and expert opinion on how to use precision diagnostics to identify individuals with monogenic diabetes.

Rare variant association analysis in 51,256 type 2 diabetes cases and 370,487 controls informs the spectrum of pathogenicity of monogenic diabetes genes

We meta-analyzed array data imputed with the TOPMed reference panel and whole-genome sequence (WGS) datasets and performed the largest, rare variant (minor allele frequency as low as 5×10-5) GWAS meta-analysis of type 2 diabetes (T2D) comprising 51,256 cases and 370,487 controls. We identified 52 novel variants at genome-wide significance (p<5 × 10-8), including 8 novel variants that were either rare or ancestry-specific. Among them, we identified a rare missense variant in HNF4A p.Arg114Trp (OR=8.2, 95% confidence interval [CI]=4.6-14.0, p = 1.08×10-13), previously reported as a variant implicated in Maturity Onset Diabetes of the Young (MODY) with incomplete penetrance. We demonstrated that the diabetes risk in carriers of this variant was modulated by a T2D common variant polygenic risk score (cvPRS) (carriers in the top PRS tertile [OR=18.3, 95%CI=7.2-46.9, p=1.2×10-9] vs carriers in the bottom PRS tertile [OR=2.6, 95% CI=0.97-7.09, p = 0.06]. Association results identified eight variants of intermediate penetrance (OR>5) in monogenic diabetes (MD), which in aggregate as a rare variant PRS were associated with T2D in an independent WGS dataset (OR=4.7, 95% CI=1.86-11.77], p = 0.001). Our data also provided support evidence for 21% of the variants reported in ClinVar in these MD genes as benign based on lack of association with T2D. Our work provides a framework for using rare variant imputation and WGS analyses in large-scale population-based association studies to identify large-effect rare variants and provide evidence for informing variant pathogenicity.

Systematic Review of Treatment of Beta-Cell Monogenic Diabetes

Background

Beta-cell monogenic forms of diabetes are the area of diabetes care with the strongest support for precision medicine. We reviewed treatment of hyperglycemia in GCK-related hyperglycemia, HNF1A-HNF4A- and HNF1B-diabetes, Mitochondrial diabetes (MD) due to m.3243A>G variant, 6q24-transient neonatal diabetes (TND) and SLC19A2-diabetes.

Methods

Systematic reviews with data from PubMed, MEDLINE and Embase were performed for the different subtypes. Individual and group level data was extracted for glycemic outcomes in individuals with genetically confirmed monogenic diabetes.

Results

147 studies met inclusion criteria with only six experimental studies and the rest being single case reports or cohort studies. Most studies had moderate or serious risk of bias.For GCK-related hyperglycemia, six studies (N=35) showed no deterioration in HbA1c on discontinuing glucose lowering therapy. A randomized trial (n=18 per group) showed that sulfonylureas (SU) were more effective in HNF1A-diabetes than in type 2 diabetes, and cohort and case studies supported SU effectiveness in lowering HbA1c. Two crossover trials (n=15 and n=16) suggested glinides and GLP-1 receptor agonists might be used in place of SU. Evidence for HNF4A-diabetes was limited. While some patients with HNF1B-diabetes (n=301) and MD (n=250) were treated with oral agents, most were on insulin. There was some support for the use of oral agents after relapse in 6q24-TND, and for thiamine improving glycemic control and reducing insulin requirement in SLC19A2-diabetes (less than half achieved insulin-independency).

Conclusion

There is limited evidence to guide the treatment in monogenic diabetes with most studies being non-randomized and small. The data supports: no treatment in GCK-related hyperglycemia; SU for HNF1A-diabetes. Further evidence is needed to examine the optimum treatment in monogenic subtypes.

Single cell multiomic analysis reveals diabetes-associated β-cell heterogeneity driven by HNF1A

Broad heterogeneity in pancreatic β-cell function and morphology has been widely reported. However, determining which components of this cellular heterogeneity serve a diabetes-relevant function remains challenging. Here, we integrate single-cell transcriptome, single-nuclei chromatin accessibility, and cell-type specific 3D genome profiles from human islets and identify Type II Diabetes (T2D)-associated β-cell heterogeneity at both transcriptomic and epigenomic levels. We develop a computational method to explicitly dissect the intra-donor and inter-donor heterogeneity between single β-cells, which reflect distinct mechanisms of T2D pathogenesis. Integrative transcriptomic and epigenomic analysis identifies HNF1A as a principal driver of intra-donor heterogeneity between β-cells from the same donors; HNF1A expression is also reduced in β-cells from T2D donors. Interestingly, HNF1A activity in single β-cells is significantly associated with lower Na+ currents and we nominate a HNF1A target, FXYD2, as the primary mitigator. Our study demonstrates the value of investigating disease-associated single-cell heterogeneity and provides new insights into the pathogenesis of T2D.

Treatment strategy for maturity-onset diabetes of the young 3 (MODY3): Experience with two sisters and their mother

Maturity onset diabetes of the young (MODY) is a relatively young-onset diabetes mellitus with an autosomal dominant inheritance. Among these phenotypes, MODY3, caused by mutations in HNF1A, is one of the most frequent. Although MODY3 is known to respond markedly to sulfonylureas (SU), many cases require insulin therapy. However, there are no clear guidelines for factors to consider when introducing antidiabetic drugs and insulin. This report describes a familial case in which an older sister was diagnosed with diabetes and subsequently with MODY3, followed by the onset of diabetes in the younger sister and mother. The elder sister initially denied insulin treatment and exhibited a suboptimal response to SU but finally agreed to insulin use. The mother initially selected insulin therapy because of the challenges associated with adherence to strict dietary therapy. Conversely, the younger sister responded positively to SU and maintained effective glycemic control. The management of MODY3, even though they have the same single-gene mutation and similar residual insulin secretion at diagnosis, should be flexibly individualized for each family member to ensure long-term adherence and appropriate glycemic control.

Molecular characterization and re-interpretation of HNF1A variants identified in Indian MODY subjects towards precision medicine

Background

HNF1A is an essential component of the transcription factor network that controls pancreatic β-cell differentiation, maintenance, and glucose stimulated insulin secretion (GSIS). A continuum of protein malfunction is caused by variations in the HNF1A gene, from severe loss-of-function (LOF) variants that cause the highly penetrant Maturity Onset Diabetes of the Young (MODY) to milder LOF variants that are far less penetrant but impart a population-wide risk of type 2 diabetes that is up to five times higher. Before classifying and reporting the discovered variations as relevant in clinical diagnosis, a critical review is required. Functional investigations offer substantial support for classifying a variant as pathogenic, or otherwise as advised by the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) ACMG/AMP criteria for variant interpretation.

Objective

To determine the molecular basis for the variations in the HNF1A gene found in patients with monogenic diabetes in India.

Methods

We performed functional protein analyses such as transactivation, protein expression, DNA binding, nuclear localization, and glucose stimulated insulin secretion (GSIS) assay, along with structural prediction analysis for 14 HNF1A variants found in 20 patients with monogenic diabetes.

Results

Of the 14 variants, 4 (28.6%) were interpreted as pathogenic, 6 (42.8%) as likely pathogenic, 3 (21.4%) as variants of uncertain significance, and 1 (7.14%) as benign. Patients harboring the pathogenic/likely pathogenic variants were able to successfully switch from insulin to sulfonylureas (SU) making these variants clinically actionable.

Conclusion

Our findings are the first to show the need of using additive scores during molecular characterization for accurate pathogenicity evaluations of HNF1A variants in precision medicine.

A Systematic Review of the use of Precision Diagnostics in Monogenic Diabetes

Monogenic forms of diabetes present opportunities for precision medicine as identification of the underlying genetic cause has implications for treatment and prognosis. However, genetic testing remains inconsistent across countries and health providers, often resulting in both missed diagnosis and misclassification of diabetes type. One of the barriers to deploying genetic testing is uncertainty over whom to test as the clinical features for monogenic diabetes overlap with those for both type 1 and type 2 diabetes. In this review, we perform a systematic evaluation of the evidence for the clinical and biochemical criteria used to guide selection of individuals with diabetes for genetic testing and review the evidence for the optimal methods for variant detection in genes involved in monogenic diabetes. In parallel we revisit the current clinical guidelines for genetic testing for monogenic diabetes and provide expert opinion on the interpretation and reporting of genetic tests. We provide a series of recommendations for the field informed by our systematic review, synthesizing evidence, and expert opinion. Finally, we identify major challenges for the field and highlight areas for future research and investment to support wider implementation of precision diagnostics for monogenic diabetes.

Shared peripheral blood biomarkers for Alzheimer’s disease, major depressive disorder, and type 2 diabetes and cognitive risk factor analysis

Background

Alzheimer's disease (AD), type 2 diabetes mellitus (T2DM), and Major Depressive Disorder (MDD) have a higher incidence rate in modern society. Although increasing evidence supports close associations between the three, the mechanisms underlying their interrelationships remain elucidated.

Objective

The primary purpose is to explore the shared pathogenesis and the potential peripheral blood biomarkers for AD, MDD, and T2DM.

Methods

We downloaded the microarray data of AD, MDD, and T2DM from the Gene Expression Omnibus database and constructed co-expression networks by Weighted Gene Co-Expression Network Analysis to identify differentially expressed genes. We took the intersection of differentially expressed genes to obtain co-DEGs. Then, we performed GO and KEGG enrichment analysis on the common genes in the AD, MDD, and T2DM-related modules. Next, we utilized the STRING database to find the hub genes in the protein-protein interaction network. ROC curves were constructed for co-DEGs to obtain the most diagnostic valuable genes and to make drug predictions against the target genes. Finally, we conducted a present condition survey to verify the correlation between T2DM, MDD and AD.

Results

Our findings indicated 127 diff co-DEGs, 19 upregulated co-DEGs, and 25 down-regulated co-DEGs. Functional enrichment analysis showed co-DEGs were mainly enriched in signaling pathways such as metabolic diseases and some neurodegeneration. Protein-protein interaction network construction identified hub genes in AD, MDD and T2DM shared genes. We identified seven hub genes of co-DEGs, namely, SMC4, CDC27, HNF1A, RHOD, CUX1, PDLIM5, and TTR. The current survey results suggest a correlation between T2DM, MDD and dementia. Moreover, logistic regression analysis showed that T2DM and depression increased the risk of dementia.

Conclusion

Our work identified common pathogenesis of AD, T2DM, and MDD. These shared pathways might provide novel ideas for further mechanistic studies and hub genes that may serve as novel therapeutic targets for diagnosing and treating.

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.

Patient stratification for determining optimal second-line and third-line therapy for type 2 diabetes: the TriMaster study

Precision medicine aims to treat an individual based on their clinical characteristics. A differential drug response, critical to using these features for therapy selection, has never been examined directly in type 2 diabetes. In this study, we tested two hypotheses: (1) individuals with body mass index (BMI) > 30 kg/m², compared to BMI ≤ 30 kg/m², have greater glucose lowering with thiazolidinediones than with DPP4 inhibitors, and (2) individuals with estimated glomerular filtration rate (eGFR) 60-90 ml/min/1.73 m², compared to eGFR >90 ml/min/1.73 m², have greater glucose lowering with DPP4 inhibitors than with SGLT2 inhibitors. The primary endpoint for both hypotheses was the achieved HbA1c difference between strata for the two drugs. In total, 525 people with type 2 diabetes participated in this UK-based randomized, double-blind, three-way crossover trial of 16 weeks of treatment with each of sitagliptin 100 mg once daily, canagliflozin 100 mg once daily and pioglitazone 30 mg once daily added to metformin alone or metformin plus sulfonylurea. Overall, the achieved HbA1c was similar for the three drugs: pioglitazone 59.6 mmol/mol, sitagliptin 60.0 mmol/mol and canagliflozin 60.6 mmol/mol (P = 0.2). Participants with BMI > 30 kg/m², compared to BMI ≤ 30 kg/m², had a 2.88 mmol/mol (95% confidence interval (CI): 0.98, 4.79) lower HbA1c on pioglitazone than on sitagliptin (n = 356, P = 0.003). Participants with eGFR 60-90 ml/min/1.73 m², compared to eGFR >90 ml/min/1.73 m², had a 2.90 mmol/mol (95% CI: 1.19, 4.61) lower HbA1c on sitagliptin than on canagliflozin (n = 342, P = 0.001). There were 2,201 adverse events reported, and 447/525 (85%) randomized participants experienced an adverse event on at least one of the study drugs. In this precision medicine trial in type 2 diabetes, our findings support the use of simple, routinely available clinical measures to identify the drug class most likely to deliver the greatest glycemic reduction for a given patient. (ClinicalTrials.gov registration: NCT02653209 ; ISRCTN registration: 12039221 .).

Dorzagliatin, a Dual-Acting Glucokinase Activator, Increases Insulin Secretion and Glucose Sensitivity in Glucokinase Maturity-Onset Diabetes of the Young and Recent-Onset Type 2 Diabetes

Glucokinase (GK, gene symbol GCK) maturity-onset diabetes of the young (MODY) is caused by heterozygous inactivating mutations in GK and impaired glucose sensing. We investigated effects of dorzagliatin, a novel allosteric GK activator, on insulin secretion rates (ISRs) and β-cell glucose sensitivity (βCGS) in GCK-MODY and recent-onset type 2 diabetes. In a double-blind, randomized, crossover study, 8 participants with GCK-MODY and 10 participants with type 2 diabetes underwent 2-h 12 mmol/L hyperglycemic clamps following a single oral dose of dorzagliatin 75 mg or matched placebo. Effects of dorzagliatin on wild-type and mutant GK enzyme activity were investigated using an NADP+-coupled assay with glucose-6-phosphate dehydrogenase in vitro. In GCK-MODY, dorzagliatin significantly increased absolute and incremental second-phase ISRs versus placebo but not the acute insulin response. Dorzagliatin improved βCGS in GCK-MODY with an upward and leftward shift in ISR-glucose response. Dorzagliatin increased basal ISRs in type 2 diabetes, with smaller changes in second-phase ISRs versus GCK-MODY. In vitro, dorzagliatin directly reduced the glucose half saturation concentration of wild-type GK and selected GK mutants to varying degrees. Dorzagliatin directly restored enzyme activity of select GK mutants and enhanced wild-type GK activity, thereby correcting the primary defect of glucose sensing in GCK-MODY.

Pharmacogenomics: current status and future perspectives

Inter-individual variability in drug response, be it efficacy or safety, is common and likely to become an increasing problem globally given the growing elderly population requiring treatment. Reasons for this inter-individual variability include genomic factors, an area of study called pharmacogenomics. With genotyping technologies now widely available and decreasing in cost, implementing pharmacogenomics into clinical practice - widely regarded as one of the initial steps in mainstreaming genomic medicine - is currently a focus in many countries worldwide. However, major challenges of implementation lie at the point of delivery into health-care systems, including the modification of current clinical pathways coupled with a massive knowledge gap in pharmacogenomics in the health-care workforce. Pharmacogenomics can also be used in a broader sense for drug discovery and development, with increasing evidence suggesting that genomically defined targets have an increased success rate during clinical development.

An insulin hypersecretion phenotype precedes pancreatic β cell failure in MODY3 patient-specific cells

MODY3 is a monogenic hereditary form of diabetes caused by mutations in the transcription factor HNF1A. The patients progressively develop hyperglycemia due to perturbed insulin secretion, but the pathogenesis is unknown. Using patient-specific hiPSCs, we recapitulate the insulin secretion sensitivity to the membrane depolarizing agent sulfonylurea commonly observed in MODY3 patients. Unexpectedly, MODY3 patient-specific HNF1A^+/R272C β cells hypersecrete insulin both in vitro and in vivo after transplantation into mice. Consistently, we identified a trend of increased birth weight in human HNF1A mutation carriers compared with healthy siblings. Reduced expression of potassium channels, specifically the K_ATP channel, in MODY3 β cells, increased calcium signaling, and rescue of the insulin hypersecretion phenotype by pharmacological targeting ATP-sensitive potassium channels or low-voltage-activated calcium channels suggest that more efficient membrane depolarization underlies the hypersecretion of insulin in MODY3 β cells. Our findings identify a pathogenic mechanism leading to β cell failure in MODY3.

Precision Medicine in Diabetes

Tailoring treatment or management to groups of individuals based on specific clinical, molecular, and genomic features is the concept of precision medicine. Diabetes is highly heterogenous with respect to clinical manifestations, disease progression, development of complications, and drug response. The current practice for drug treatment is largely based on evidence from clinical trials that report average effects. However, around half of patients with type 2 diabetes do not achieve glycaemic targets despite having a high level of adherence and there are substantial differences in the incidence of adverse outcomes. Therefore, there is a need to identify predictive markers that can inform differential drug responses at the point of prescribing. Recent advances in molecular genetics and increased availability of real-world and randomised trial data have started to increase our understanding of disease heterogeneity and its impact on potential treatments for specific groups. Leveraging information from simple clinical features (age, sex, BMI, ethnicity, and co-prescribed medications) and genomic markers has a potential to identify sub-groups who are likely to benefit from a given drug with minimal adverse effects. In this chapter, we will discuss the state of current evidence in the discovery of clinical and genetic markers that have the potential to optimise drug treatment in type 2 diabetes.

[Other specific types of diabetes and exocrine pancreatic insufficiency (update 2023)]

The heterogenous category "specific types of diabetes due to other causes" encompasses disturbances in glucose metabolism due to other endocrine disorders such as acromegaly or hypercortisolism, drug-induced diabetes (e.g. antipsychotic medications, glucocorticoids, immunosuppressive agents, highly active antiretroviral therapy (HAART), checkpoint inhibitors), genetic forms of diabetes (e.g. Maturity Onset Diabetes of the Young (MODY), neonatal diabetes, Down‑, Klinefelter- and Turner Syndrome), pancreatogenic diabetes (e.g. postoperatively, pancreatitis, pancreatic cancer, haemochromatosis, cystic fibrosis), and some rare autoimmune or infectious forms of diabetes. Diagnosis of specific diabetes types might influence therapeutic considerations. Exocrine pancreatic insufficiency is not only found in patients with pancreatogenic diabetes but is also frequently seen in type 1 and long-standing type 2 diabetes.

Targeted gene panel analysis of Japanese patients with maturity-onset diabetes of the young-like diabetes mellitus: Roles of inactivating variants in the ABCC8 and insulin resistance genes

AIMS/INTRODUCTION

To investigate the genetic background of Japanese patients with suspected maturity-onset diabetes of the young (MODY).

MATERIALS AND METHODS

On 340 proband patients referred from across Japan, genomic variants were analyzed using a targeted multigene panel analysis combined with the multiplex ligation probe amplification (MLPA) analysis, mitochondrial m.3243A > G analysis and methylation-specific polymerase chain reaction of the imprinted 6q24 locus. Pathogenic/likely pathogenic variants were listed according to the 2015 American College of Medical Genetics and Genomics and the Association for Molecular Pathology criteria. Additionally, variants with a population frequency <0.001 and Combined Annotation Dependent Depletion score >20 (CS >20) were listed as rare variants of uncertain significance-CS >20.

RESULTS

A total of 157 pathogenic/likely pathogenic variants and 44 rare variants of uncertain significance-CS >20 were identified. In the pathogenic/likely pathogenic variants, alterations in the GCK gene were the most common (82, 52.2%) followed by HNF1A (29, 18.5%), HNF4A (13, 8.3%) and HNF1B (13, 8.3%). One patient was a 29.5% mosaic with a truncating INSR variant. In the rare variants of uncertain significance-CS >20, 20 (45.5%) were in the genes coding for the adenosine triphosphate-sensitive potassium channel, KCNJ11 or ABCC8, and four were in the genes of the insulin-signaling pathway, INSR and PIK3R1. Four variants in ABCC8 were previously reported in patients with congenital hyperinsulinism, suggesting the inactivating nature of these variants, and at least two of our patients had a history of congenital hyperinsulinism evolving into diabetes. In two patients with INSR or PIK3R1 variants, insulin resistance was evident at diagnosis.

CONCLUSIONS

Causative genomic variants could be identified in at least 46.2% of clinically suspected MODY patients. ABCC8-MODY with inactivating variants could represent a distinct category of MODY. Genes of insulin resistance should be included in the sequencing panel for MODY.

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.

A transcriptional regulatory network of HNF4α and HNF1α involved in human diseases and drug metabolism

HNF4α and HNF1α are core transcription factors involved in the development and progression of a variety of human diseases and drug metabolism. They play critical roles in maintaining the normal growth and function of multiple organs, mainly the liver, and in the metabolism of endogenous and exogenous substances. The twelve isoforms of HNF4α may exhibit different physiological functions, and HNF4α and HNF1α show varying or even opposing effects in different types of diseases, particularly cancer. Additionally, the regulation of CYP450, phase II drug-metabolizing enzymes, and drug transporters is affected by several factors. This article aims to review the role of HNF4α and HNF1α in human diseases and drug metabolism, including their structures and physiological functions, affected diseases, regulated drug metabolism genes, influencing factors, and related mechanisms. We also propose a transcriptional regulatory network of HNF4α and HNF1α that regulates the expression of target genes related to disease and drug metabolism.

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.

Phenotypic and genetic classification of diabetes

The historical subclassification of diabetes into predominantly types 1 and 2 is well appreciated to inadequately capture the heterogeneity seen in patient presentations, disease course, response to therapy and disease complications. This review summarises proposed data-driven approaches to further refine diabetes subtypes using clinical phenotypes and/or genetic information. We highlight the benefits as well as the limitations of these subclassification schemas, including practical barriers to their implementation that would need to be overcome before incorporation into clinical practice.

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.

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.

Report of Prolonged Neonatal Hypoglycemia in Three Infants of Mothers With Variants in HNF1A

Background/Objective

Genetic variants in hepatic nuclear factor 1α (HNF1A) cause maturity-onset diabetes of the young (MODY). We sought to examine whether HNF1A MODY variants also cause neonatal hypoglycemia.

Case Report

We present 3 infants with variants in HNF1A shared with their mothers. The infants experienced neonatal hypoglycemia, 2 extending beyond 1 year and the third resolving by 28 days, and all were large for gestational age (birth weights of >99th percentile). In 2 cases, genetic testing for neonatal hypoglycemia revealed pathogenic variants in HNF1A; 1 mother was previously diagnosed with HNF1A MODY, and the other's genetic testing and ultimate MODY diagnosis were prompted by her child's hypoglycemia workup. In the third case, the infant's persistent hypoglycemia prompted genetic testing, revealing an HNF1A variant of uncertain significance, which was then identified in the mother.

Discussion

Genetic variants causing HNF1A MODY have not been definitively linked to neonatal hypoglycemia or fetal overgrowth in utero. MODY caused by HNF1A is clinically similar to that caused by HNF4A, for which a causal relationship with neonatal hypoglycemia is more certain. Case reports have previously implicated variants in HNF1A in congenital hyperinsulinism; however, these cases have generally not been in families with MODY. The cases presented here suggest that HNF1A variants causing MODY may also cause neonatal hypoglycemia.

Conclusion

Although confounding factors make the assessment of neonatal hypoglycemia challenging, these cases offer potential support for single genetic variants in HNF1A causing both MODY and neonatal hypoglycemia, with associated fetal overgrowth in utero.

Clinical and genetic characterization and long-term evaluation of individuals with maturity-onset diabetes of the young (MODY): The journey towards appropriate treatment

AIMS

To describe the clinical and genetic characteristics and long-term follow-up of a cohort with maturity-onset diabetes of the young (MODY), and to evaluate how molecular diagnosis impacted on treatment.

METHODS

A large observational, retrospective, cohort study included individuals referred to the University of São Paulo's Monogenic Diabetes Unit between 2011 and 2020. Comprehensive clinical and genetic evaluations were performed.

RESULTS

Overall, 228 individuals (190 GCK-MODY and 38 HNF1A-MODY) were enrolled. Sixty-two different GCK gene mutations (5 novel) and 17 HNF1A gene mutations (2 novel) were found. Data were available on treatment status for 76 index individuals with GCK-MODY. Before molecular diagnosis, nutritional intervention alone was used in 41 cases (53.9%). After molecular diagnosis, this number increased to 72 (94.8%). Glycated haemoglobin (HbA_1c) remained stable over the 6-year follow-up period: 6.5% (47 mmol/mol) at the first and 6.3% (45 mmol/mol) at the final visit (p = 0.056). Prior to molecular diagnosis, 7/21 (33.3%) HNF1A-MODY individuals were using sulfonylurea compared to 17/21 (81%) after testing. After a median of 5 years on sulfonylureas, HbA_1c values improved from 7.5% (58 mmol/mol) to 6.5% (48 mmol/mol) (p = 0.006).

CONCLUSIONS

Molecular diagnosis resulted in appropriate adjustment of treatment in approximately 80% of participants with GCK-MODY or HNF1A-MODY.

An intron mutation of HNF1A causes abnormal splicing and impairs its activity as a transcription factor

Mutations in HNF1A are associated with Maturity Onset Diabetes of the Young type 3 (MODY3) and most of them are in the coding region. Herein, we identified an intron mutation at the 6th nucleotide upstream of the end of intron 7 of HNF1A, named IVS7-6G > A, in a patient with early-onset diabetes. The "minigene" assay showed that IVS7-6G > A produced two aberrant mRNA variants translating into two truncated proteins: L502S fs* and G437A fs*, both affecting HNF1A transactivation domain (TAD). To determine functional consequences of IVS7-6G > A mutation, we made plasmids encoding truncated HNF1A containing different portions of HNF1A TAD and found that the TAD of HNF1A is important not only for its regulatory activities, but also for its nuclearization, and the residues 282-501 was more essential than 502-631. Our data suggested IVS7-6G > A impaired HNF1A splicing and may contribute to the pathogenesis of MODY3.

Identification of a novel hepatocyte nuclear factor-1 alpha (HNF1A) variant in maturity onset diabetes of the young type 3 (HNF1A-MODY)

Summary

We identified an adolescent young woman with new-onset diabetes. Due to suspicious family history, she underwent genetic testing for common monogenic diabetes (MODY) genes. We discovered that she and her father carry a novel variant of uncertain significance in the HNF1A gene. She was successfully transitioned from insulin to a sulfonylurea with excellent glycemic control. Based on her family history and successful response to sulfonylurea, we propose that this is a novel pathogenic variant in HNF1A. This case highlights the utility of genetic testing for MODY, which has the potential to help affected patients control their diabetes without insulin.

Learning points

HNF1A mutations are a common cause of monogenic diabetes in patients presenting with early-onset diabetes and significant family history. Genetic testing in suspected patients allows for the identification of mutations causing monogenic diabetes. First-degree relatives of the affected individual should be considered for genetic testing. The use of sulfonylurea agents in patients with HNF1A-MODY can reduce dependence on insulin therapy and provide successful glycemic control.

HNF1A Mutations and Beta Cell Dysfunction in Diabetes

Understanding the genetic factors of diabetes is essential for addressing the global increase in type 2 diabetes. HNF1A mutations cause a monogenic form of diabetes called maturity-onset diabetes of the young (MODY), and HNF1A single-nucleotide polymorphisms are associated with the development of type 2 diabetes. Numerous studies have been conducted, mainly using genetically modified mice, to explore the molecular basis for the development of diabetes caused by HNF1A mutations, and to reveal the roles of HNF1A in multiple organs, including insulin secretion from pancreatic beta cells, lipid metabolism and protein synthesis in the liver, and urinary glucose reabsorption in the kidneys. Recent studies using human stem cells that mimic MODY have provided new insights into beta cell dysfunction. In this article, we discuss the involvement of HNF1A in beta cell dysfunction by reviewing previous studies using genetically modified mice and recent findings in human stem cell-derived beta cells.

Improvements in Awareness and Testing Have Led to a Threefold Increase Over 10 Years in the Identification of Monogenic Diabetes in the U.K

OBJECTIVE

Maturity-onset diabetes of the young (MODY) is a rare monogenic form of diabetes. In 2009, >80% of U.K. cases were estimated to be misdiagnosed. Since then, there have been a number of initiatives to improve the awareness and detection of MODY, including education initiatives (Genetic Diabetes Nurse [GDN] project), the MODY probability calculator, and targeted next-generation sequencing (tNGS). We examined how the estimated prevalence of MODY and other forms of monogenic diabetes diagnosed outside the neonatal period has changed over time and how the initiatives have impacted case finding.

RESEARCH DESIGN AND METHODS

U.K. referrals for genetic testing for monogenic diabetes diagnosed >1 year of age from 1 January 1996 to 31 December 2019 were examined. Positive test rates were compared for referrals reporting GDN involvement/MODY calculator use with those that did not.

RESULTS

A diagnosis of monogenic diabetes was confirmed in 3,860 individuals, more than threefold higher than 2009 (1 January 1996 to 28 February 2009, n = 1,177). Median age at diagnosis in probands was 21 years. GDN involvement was reported in 21% of referrals; these referrals had a higher positive test rate than those without GDN involvement (32% vs. 23%, P < 0.001). MODY calculator usage was indicated in 74% of eligible referrals since 2014; these referrals had a higher positive test rate than those not using the calculator (33% vs. 25%, P = 0.001). Four hundred ten (10.6%) cases were identified through tNGS. Monogenic diabetes prevalence was estimated to be 248 cases/million (double that estimated in 2009 because of increased case finding).

CONCLUSIONS

Since 2009, referral rates and case diagnosis have increased threefold. This is likely to be the consequence of tNGS, GDN education, and use of the MODY calculator.

Low genetic confirmation rate in South Indian subjects with a clinical diagnosis of maturity-onset diabetes of the young (MODY) who underwent targeted next-generation sequencing for 13 genes

PURPOSE

To screen for maturity-onset diabetes of the young (MODY) variants in subjects with an early age of onset and positive family history of diabetes mellitus.

METHODS

60 subjects with onset of diabetes between 3 and 30 years of age and parental history (onset < 35 years) of diabetes were recruited after excluding autoimmune, pancreatic and syndromic forms of diabetes. Detailed pedigree chart and clinical data were recorded. MODY genetic testing (MODY 1-13) was performed and variant classification was done adhering to the ACMG guidelines.

RESULTS

Baseline characteristics of subjects were as follows: mean age of onset of diabetes 19.9 ± 7 years, mean duration of diabetes 6.3 ± 6.8 years, BMI 23.3 ± 3 kg/m² and C-peptide 1.56 ± 1.06 nmol/l. Four out of sixty (6.6%) were positive for variants classifiable as pathogenic/likely pathogenic: one patient with HNF4Ac.691C > T, (p.Arg231Trp), two with HNF 1A c.746C > A(p.Ser249Ter) and c.1340C > T(p.Pro447Leu), and one with ABCC8 c.4544C > T (p.Thr1515Met). MODY 1 and MODY 3 variants were documented in the paediatric age group (< 18 years).

CONCLUSION

A genetic diagnosis of MODY could be confirmed in only 6.6% (4/60) of patients clinically classifiable as MODY. This is less than that reported in clinically diagnosed MODY subjects of European descent. Newly published population data and more stringent criteria for assessment of pathogenicity and younger age of onset of type 2 diabetes in Indians could have contributed to the lower genetic confirmation rate. Apart from variants in the classical genes (HNF1A, HNF4A), a likely pathogenic variant in a non-classical gene (ABCC8) was noted in this study.

Fucosylated AGP glycopeptides as biomarkers of HNF1A-Maturity onset diabetes of the young

AIMS

We previously demonstrated that antennary fucosylated N-glycans on plasma proteins are regulated by HNF1A and can identify cases of Maturity-Onset Diabetes of the Young caused by HNF1A variants (HNF1A-MODY). Based on literature data, we further postulated that N-glycans with best diagnostic value mostly originate from alpha-1-acid glycoprotein (AGP). In this study we analyzed fucosylation of AGP in subjects with HNF1A-MODY and other types of diabetes aiming to evaluate its diagnostic potential.

METHODS

A recently developed LC-MS method for AGP N-glycopeptide analysis was utilized in two independent cohorts: a) 466 subjects with different diabetes subtypes to test the fucosylation differences, b) 98 selected individuals to test the discriminative potential for pathogenic HNF1A variants.

RESULTS

Our results showed significant reduction in AGP fucosylation associated to HNF1A-MODY when compared to other diabetes subtypes. Additionally, ROC curve analysis confirmed significant discriminatory potential of individual fucosylated AGP glycopeptides, where the best performing glycopeptide had an AUC of 0.94 (95% CI 0.90-0.99).

CONCLUSIONS

A glycopeptide based diagnostic tool would be beneficial for patient stratification by providing information about the functionality of HNF1A. It could assist the interpretation of DNA sequencing results and be a useful addition to the differential diagnostic process.

Syndromic Monogenic Diabetes Genes Should Be Tested in Patients With a Clinical Suspicion of Maturity-Onset Diabetes of the Young

At present, outside of infancy, genetic testing for monogenic diabetes is typically for mutations in maturity-onset diabetes of the young (MODY) genes that predominantly result in isolated diabetes. Monogenic diabetes syndromes are usually only tested for when supported by specific syndromic clinical features. How frequently patients with suspected MODY have a mutation in a monogenic syndromic diabetes gene is unknown and thus missed by present testing regimes. We performed genetic testing of 27 monogenic diabetes genes (including 18 associated with syndromic diabetes) for 1,280 patients with a clinical suspicion of MODY who were not suspected of having monogenic syndromic diabetes. We confirmed monogenic diabetes in 297 (23%) patients. Mutations in seven different syndromic diabetes genes accounted for 19% (95% CI 15-24%) of all monogenic diabetes. The mitochondrial m.3243A>G and mutations in HNF1B were responsible for the majority of mutations in syndromic diabetes genes. They were also the 4th and 5th most common causes of monogenic diabetes overall. These patients lacked typical features, and their diabetes phenotypes overlapped with patients with nonsyndromic monogenic diabetes. Syndromic monogenic diabetes genes (particularly m.3243A>G and HNF1B) should be routinely tested in patients with suspected MODY who do not have typical features of a genetic syndrome.

Identification and management of GCK-MODY complicating pregnancy in Chinese patients with gestational diabetes

Precise differentiation of glucokinase (GCK) monogenic diabetes from gestational diabetes mellitus (GDM) is critical for accurate management of the pregnancy outcome. We screened GCK-MODY complicating pregnancies in Chinese GDM patients, explored the pathogenesis of novel GCK mutations, and evaluated the patients' pregnancy outcome and management. The GCK gene from 411 GDM patients was screened with PCR-direct sequencing and multiplex ligation-dependent probe amplification (MLPA) and 15 GCK mutations were identified. We also retrospectively analyzed a total of 65 pregnancies from 21 GCK-MODY families, wherein 41 were from 15 maternal families and 24 were from six paternal families. Bioinformatic analysis and biochemical functional study were conducted to identify novel GCK mutations. In total, we identified 21 GCK mutations: 15 from the 411 GDM patients and six from 24 fathers. Of th Asp78Asn (GAC → AAC), Met87Arg (ATG → AGG), Leu451Val (CTT → GTT), Leu451Pro (CTG → CCG) and 1019 + 20G > A e mutations, five, i.e., were novel and deleterious, with markedly decreased enzyme activity and thermal stability. The unaffected offspring of GCK mutation-affected mothers were heavier than affected offspring (p < 0.001). Of 21 insulin-treated affected mothers, 10 had maternal hypoglycemia (47.6%) and seven had perinatal complications (33.3%), and the affected offspring of the insulin-treated affected mothers had significantly lower birth weights than that of the 20 diet-control affected mothers (p = 0.031). In this study, the prevalence of GCK-MODY complicating pregnancy in Chinese GDM patients was 3.6% (15/411). The defective GCK may contribute to the hyperglycemia in GCK-MODY. Insulin therapy is not beneficial for GCK-MODY complicating pregnancy and therefore should not be recommended.

From biobanking to personalized prevention of obesity, diabetes and metabolic syndrome

The growing prevalence of metabolic disorders creates an increasing demand for novel approaches to their prevention and therapy. Novel genetic diagnostic technologies are developed every year, which makes it possible to identify people who are at the highest genetic risk of diabetes, non-alcoholic fatty liver disease, and metabolic syndrome. Early intervention strategies can be used to prevent metabolic disorders in this group of people. Genetic risk scores (GRSs) are a powerful tool to identify people with a high genetic risk. Millions of genetic variants are analyzed in genome-wide association studies in order to combine them into GRSs. It has become possible to store and process such huge amounts of data with the help of biobanks, where biological samples are stored according to international standards. Genetic studies include more and more people every year that increases the predictive power of GRSs. It has already been demonstrated that the use of GRSs makes future preventive measures more effective. In the near future, GRSs are likely to become part of clinical guidelines so that they can be widely used to identify people at high risk for metabolic syndrome and its components.