Genome-Wide Meta-analysis Identifies Genetic Variants Associated With Glycemic Response to Sulfonylureas

Investigation of the degree of family history of diabetes in different clusters of newly diagnosed type 2 diabetes in Thailand

AIM

Type 2 diabetes is a heterogeneous disease with strong genetic components. We showed earlier that newly diagnosed type 2 diabetes in Thai patients could be categorized into four clusters. This study aimed to determine the evidence of hereditary factors in these type 2 diabetes clusters.

METHODS

A total of 487 subjects who were diagnosed with type 2 diabetes in two years were enrolled in the Siriraj Diabetes Center, Siriraj Hospital Bangkok, Bangkok, Thailand. They were divided into four clusters as previously described. The associations between patients' characteristics, degree of family history of diabetes (FHD), and type 2 diabetes clusters were tested using multinomial logistic regression.

RESULTS

Among four clusters of newly diagnosed type 2 diabetes, there were significant differences in characteristics at baseline, including age at diagnosis, BMI, waist circumference, blood sugar levels, vital signs, triglyceride, HDL, calculated LDL, creatinine and eGFR (all p < .05). A relatively young age at the time of diabetes diagnosis was associated with having second-degree relatives with diabetes (p < .05) in all clusters when using mild age-related diabetes (MARD) cluster with no FHD as a control. Patients in the severe insulin-deficient diabetes (SIDD) cluster had more first-degree relatives with diabetes (odds ratio = 1.85; p = .0354), while patients in the metabolic syndrome diabetes (MSD) cluster (odds ratio = 10.73; p < .001) and the mild obesity-related diabetes (MOD) group (odds ratio = 6.66; p = .002), had more second-degree relatives with diabetes.

CONCLUSIONS

Genetic factors might have various roles in the pathogenesis of type 2 diabetes, at least in newly diagnosed Thai patients. Our findings supported that genetic heterogeneity contributed to clinical heterogeneity or four different clusters. Further studies are needed in a larger sample size of these patients is needed to identify genetic loci associated with each cluster.

Diabetes in China: epidemiology, pathophysiology and multi-omics

Although diabetes is now a global epidemic, China has the highest number of affected people, presenting profound public health and socioeconomic challenges. In China, rapid ecological and lifestyle shifts have dramatically altered diabetes epidemiology and risk factors. In this Review, we summarize the epidemiological trends and the impact of traditional and emerging risk factors on Chinese diabetes prevalence. We also explore recent genetic, metagenomic and metabolomic studies of diabetes in Chinese, highlighting their role in pathogenesis and clinical management. Although heterogeneity across these multidimensional areas poses major analytic challenges in classifying patterns or features, they have also provided an opportunity to increase the accuracy and specificity of diagnosis for personalized treatment and prevention. National strategies and ongoing research are essential for improving diabetes detection, prevention and control, and for personalizing care to alleviate societal impacts and maintain quality of life.

Exploring early DNA methylation alterations in type 1 diabetes: implications of glycemic control

Background

Prolonged hyperglycemia causes diabetes-related micro- and macrovascular complications, which combined represent a significant burden for individuals living with diabetes. The growing scope of evidence indicates that hyperglycemia affects the development of vascular complications through DNA methylation.

Methods

A genome-wide differential DNA methylation analysis was performed on pooled peripheral blood DNA samples from individuals with type 1 diabetes (T1D) with direct DNA sequencing. Strict selection criteria were used to ensure two age- and sex-matched groups with no clinical signs of chronic complications according to persistent mean glycated hemoglobin (HbA1c) values over 5 years: HbA1c<7% (N=10) and HbA1c>8% (N=10).

Results

Between the two groups, 8385 differentially methylated CpG sites, annotated to 1802 genes, were identified. Genes annotated to hypomethylated CpG sites were enriched in 48 signaling pathways. Further analysis of key CpG sites revealed four specific regions, two of which were hypermethylated and two hypomethylated, associated with long non-coding RNA and processed pseudogenes.

Conclusions

Prolonged hyperglycemia in individuals with T1D, who have no clinical manifestation of diabetes-related complications, is associated with multiple differentially methylated CpG sites in crucial genes and pathways known to be linked to chronic complications in T1D.

Landscape of pharmacogenetic variants associated with non-insulin antidiabetic drugs in the Indian population

INTRODUCTION

Genetic variants contribute to differential responses to non-insulin antidiabetic drugs (NIADs), and consequently to variable plasma glucose control. Optimal control of plasma glucose is paramount to minimizing type 2 diabetes-related long-term complications. India's distinct genetic architecture and its exploding burden of type 2 diabetes warrants a population-specific survey of NIAD-associated pharmacogenetic (PGx) variants. The recent availability of large-scale whole genomes from the Indian population provides a unique opportunity to generate a population-specific map of NIAD-associated PGx variants.

RESEARCH DESIGN AND METHODS

We mined 1029 Indian whole genomes for PGx variants, drug-drug interaction (DDI) and drug-drug-gene interactions (DDGI) associated with 44 NIADs. Population-wise allele frequencies were estimated and compared using Fisher's exact test.

RESULTS

Overall, we found 76 known and 52 predicted deleterious common PGx variants associated with response to type 2 diabetes therapy among Indians. We report remarkable interethnic differences in the relative cumulative counts of decreased and increased response-associated alleles across NIAD classes. Indians and South Asians showed a significant excess of decreased metformin response-associated alleles compared with other global populations. Network analysis of shared PGx genes predicts high DDI risk during coadministration of NIADs with other metabolic disease drugs. We also predict an increased CYP2C19-mediated DDGI risk for CYP3A4/3A5-metabolized NIADs, saxagliptin, linagliptin and glyburide when coadministered with proton-pump inhibitors (PPIs).

CONCLUSIONS

Indians and South Asians have a distinct PGx profile for antidiabetes drugs, marked by an excess of poor treatment response-associated alleles for various NIAD classes. This suggests the possibility of a population-specific reduced drug response in atleast some NIADs. In addition, our findings provide an actionable resource for accelerating future diabetes PGx studies in Indians and South Asians and reconsidering NIAD dosing guidelines to ensure maximum efficacy and safety in the population.

Glucagon-Like Peptide 1 (GLP-1) Receptor Variants and Glycemic Response to Liraglutide: A Pharmacogenetics Study in Iranian People with Type 2 Diabetes Mellitus

INTRODUCTION

Pharmacogenetics studies suggest that genetic variants have a possible influence on the inter-individual differences in therapeutic response to glucagon-like peptide 1 receptor agonists (GLP-1 RAs). We aimed to examine the potential role of genetic variability of glucagon-like peptide 1 receptor (GLP-1R) on glycemic response to GLP-1 RAs in a population of Iranian people with type 2 diabetes mellitus (T2DM).

METHODS

In this study, we analyzed the data from participants in a non-inferiority randomized clinical trial between 2019 and 2020. Patients received liraglutide 1.8 mg/day subcutaneously for 24 weeks. They were stratified by the baseline hemoglobin A1c (HbA1c) into four categories: 7-7.99, 8-8.99, 9-9.99, and ≥ 10%. In each category, subjects with HbA1c reduction greater than the median ΔHbA1c value for that group were defined as optimal responders. The pooled number of optimal/suboptimal responders in the four groups was used for the comparison. We evaluated two genetic variants of GLP-1R, rs6923761 and rs10305420, using Sanger sequencing. Logistic regression analyses were performed to examine the associations of the GLP-1R variants with the glycemic response in different genetic models.

RESULTS

Out of 233 participants, 120 individuals were optimal responders. Median HbA1c reduction was - 2.5% in the optimal responder group compared with - 1.0% in the suboptimal responder group (P < 0.001). In genetic models, rs10305420 T allele homozygosity was associated with optimal glycemic response to liraglutide compared with heterozygous and wild-type homozygous states (recessive model: OR 3.28, 95% CI 1.41-7.65, P = 0.006; codominant model: OR 2.52, 95% CI 1.03-6.13, P = 0.04). No significant association was found between rs6923761 variant and HbA1c reduction.

CONCLUSION

GLP-1R rs10305420 polymorphism can explain some of the inter-individual differences in glycemic response to liraglutide in a population of Iranian people with T2DM.

Genetic risk scores: are they important for diabetes management? results from multiple cross-sectional studies

BACKGROUND

Several genetic risk scores (GRS) for type 2 diabetes (T2DM) have been published, but not replicated. We aimed to 1) replicate previous findings on the association between GRS on prevalence of T2DM and 2) assess the association between GRS and T2DM management in a sample of community-dwelling people from Switzerland.

METHODS

Four waves from a prospective study conducted in Lausanne. Seven GRS related to T2DM were selected, and compared between participants with and without T2DM, and between controlled and uncontrolled participants treated for T2DM.

RESULTS

Data from 5426, 4017, 2873 and 2170 participants from the baseline, first, second and third follow-ups, respectively, was used. In all study periods, participants with T2DM scored higher than participants without T2DM in six out of seven GRS. Data from 367, 437, 285 and 207 participants with T2DM was used. In all study periods, approximately half of participants treated for T2DM did not achieve adequate fasting blood glucose or HbA1c levels, and no difference between controlled and uncontrolled participants was found for all seven GRS. Power analyses showed that most GRS needed a sample size above 1000 to consider the difference between controlled and uncontrolled participants as statistically significant at p = 0.05.

CONCLUSION

In this study, we confirmed the association between most published GRS and diabetes. Conversely, no consistent association between GRS and diabetes control was found. Use of GRS to manage patients with T2DM in clinical practice is not justified.

Helical-Like Assembly of Nateglinide as Coating for Oral Delivery of Insulin and Their Synergistic Prevention of Diabetes Mellitus

Oral delivery of antidiabetic active components promises to free millions of people from daily suffering who require routine injections. However, oral insulin (Ins) and other short-acting compounds such as nateglinide (NG) in harsh gastrointestinal tract still face great challenging, including low bioavailability, and rapid elimination. In this study, inspired by the self-assembly of phenylalanine-based peptides in nature, it is showed that NG a small phenylalanine derivative, assembles into left-handed helical nanofibers in the presence of Ca2+ . These helical NG nanofibers functioned as a coating layer on the surface of Ca2+ -linked alginate (Alg) microgels for the effective encapsulation of Ins. As expected, the sustained release and prolonged circulation of Ins and NG from the Ins-loading Alg/NG microgels (Ins@Alg/NG) in the intestinal tract synergistically maintain a relatively normal blood glucose level in streptozotocin-induced diabetic mice after oral administration of Ins@Alg/NG. This further confirms that Ins@Alg/NG ameliorated Ins resistance mainly through activating Insreceptor substrate 1 (IRS1), protein kinase B (AKT), and AMP-activated protein kinase (AMPK), as well as by repressing glycogen synthase kinase-3β (GSK-3β). The strategy of using the assembly of NG as a coating achieves the oral delivery of insulin and showcases a potential for the treatment of diabetes.

A gene risk score using missense variants in SLCO1B1 is associated with earlier onset statin intolerance

BACKGROUND AND AIMS

The efficacy of statin therapy is hindered by intolerance to the therapy, leading to discontinuation. Variants in SLCO1B1, which encodes the hepatic transporter OATB1B1, influence statin pharmacokinetics, resulting in altered plasma concentrations of the drug and its metabolites. Current pharmacogenetic guidelines require sequencing of the SLCO1B1 gene, which is more expensive and less accessible than genotyping. In this study, we aimed to develop an easy, clinically implementable functional gene risk score (GRS) of common variants in SLCO1B1 to identify patients at risk of statin intolerance.

METHODS AND RESULTS

A GRS was developed from four common variants in SLCO1B1. In statin users from Tayside, Scotland, UK, those with a high-risk GRS had increased odds across three phenotypes of statin intolerance [general statin intolerance (GSI): ORGSI 2.42; 95% confidence interval (CI): 1.29-4.31, P = 0.003; statin-related myopathy: ORSRM 2.51; 95% CI: 1.28-4.53, P = 0.004; statin-related suspected rhabdomyolysis: ORSRSR 2.85; 95% CI: 1.03-6.65, P = 0.02]. In contrast, using the Val174Ala genotype alone or the recommended OATP1B1 functional phenotypes produced weaker and less reliable results. A meta-analysis with results from adjudicated cases of statin-induced myopathy in the PREDICTION-ADR Consortium confirmed these findings (ORVal174Ala 1.99; 95% CI: 1.01-3.95, P = 0.048; ORGRS 1.76; 95% CI: 1.16-2.69, P = 0.008). For those requiring high-dose statin therapy, the high-risk GRS was more consistently associated with the time to onset of statin intolerance amongst the three phenotypes compared with Val174Ala (GSI: HRVal174Ala 2.49; 95% CI: 1.09-5.68, P = 0.03; HRGRS 2.44; 95% CI: 1.46-4.08, P < 0.001). Finally, sequence kernel association testing confirmed that rare variants in SLCO1B1 are associated with the risk of intolerance (P = 0.02).

CONCLUSION

We provide evidence that a GRS based on four common SLCO1B1 variants provides an easily implemented genetic tool that is more reliable than the current recommended practice in estimating the risk and predicting early-onset statin intolerance.

Genome-wide association analysis identifies ancestry-specific genetic variation associated with acute response to metformin and glipizide in SUGAR-MGH

AIMS/HYPOTHESIS

Characterisation of genetic variation that influences the response to glucose-lowering medications is instrumental to precision medicine for treatment of type 2 diabetes. The Study to Understand the Genetics of the Acute Response to Metformin and Glipizide in Humans (SUGAR-MGH) examined the acute response to metformin and glipizide in order to identify new pharmacogenetic associations for the response to common glucose-lowering medications in individuals at risk of type 2 diabetes.

METHODS

One thousand participants at risk for type 2 diabetes from diverse ancestries underwent sequential glipizide and metformin challenges. A genome-wide association study was performed using the Illumina Multi-Ethnic Genotyping Array. Imputation was performed with the TOPMed reference panel. Multiple linear regression using an additive model tested for association between genetic variants and primary endpoints of drug response. In a more focused analysis, we evaluated the influence of 804 unique type 2 diabetes- and glycaemic trait-associated variants on SUGAR-MGH outcomes and performed colocalisation analyses to identify shared genetic signals.

RESULTS

Five genome-wide significant variants were associated with metformin or glipizide response. The strongest association was between an African ancestry-specific variant (minor allele frequency [MAFAfr]=0.0283) at rs149403252 and lower fasting glucose at Visit 2 following metformin (p=1.9×10-9); carriers were found to have a 0.94 mmol/l larger decrease in fasting glucose. rs111770298, another African ancestry-specific variant (MAFAfr=0.0536), was associated with a reduced response to metformin (p=2.4×10-8), where carriers had a 0.29 mmol/l increase in fasting glucose compared with non-carriers, who experienced a 0.15 mmol/l decrease. This finding was validated in the Diabetes Prevention Program, where rs111770298 was associated with a worse glycaemic response to metformin: heterozygous carriers had an increase in HbA1c of 0.08% and non-carriers had an HbA1c increase of 0.01% after 1 year of treatment (p=3.3×10-3). We also identified associations between type 2 diabetes-associated variants and glycaemic response, including the type 2 diabetes-protective C allele of rs703972 near ZMIZ1 and increased levels of active glucagon-like peptide 1 (GLP-1) (p=1.6×10-5), supporting the role of alterations in incretin levels in type 2 diabetes pathophysiology.

CONCLUSIONS/INTERPRETATION

We present a well-phenotyped, densely genotyped, multi-ancestry resource to study gene-drug interactions, uncover novel variation associated with response to common glucose-lowering medications and provide insight into mechanisms of action of type 2 diabetes-related variation.

DATA AVAILABILITY

The complete summary statistics from this study are available at the Common Metabolic Diseases Knowledge Portal ( https://hugeamp.org ) and the GWAS Catalog ( www.ebi.ac.uk/gwas/ , accession IDs: GCST90269867 to GCST90269899).

Effects of CYP2C9 and CYP2C19 genetic polymorphisms on the pharmacokinetics and pharmacodynamics of gliclazide in healthy subjects

Gliclazide metabolism is mediated by genetically polymorphic CYP2C9 and CYP2C19 enzymes. We investigated the effects of CYP2C9 and CYP2C19 genetic polymorphisms on the pharmacokinetics and pharmacodynamics of gliclazide. Twenty-seven Korean healthy volunteers were administered a single oral dose of gliclazide 80 mg. The plasma concentration of gliclazide was quantified for the pharmacokinetic analysis and plasma concentrations of glucose and insulin were measured as pharmacodynamic parameters. The pharmacokinetics of gliclazide showed a significant difference according to the number of defective alleles of combined CYP2C9 and CYP2C19. The two defective alleles group (group 3) and one defective allele group (group 2) showed 2.34- and 1.46-fold higher AUC_0-∞ (P < 0.001), and 57.1 and 32.3% lower CL/F (P < 0.001), compared to those of the no defective allele group (group 1), respectively. The CYP2C9IM-CYP2C19IM group had AUC_0-∞ increase of 1.49-fold (P < 0.05) and CL/F decrease by 29.9% (P < 0.01), compared with the CYP2C9 Normal Metabolizer (CYP2C9NM)-CYP2C19IM group. The CYP2C9NM-CYP2C19PM group and CYP2C9NM-CYP2C19IM group showed 2.41- and 1.51-fold higher AUC_0-∞ (P < 0.001), and 59.6 and 35.4% lower CL/F (P < 0.001), compared to those of the CYP2C9NM-CYP2C19NM group, respectively. The results represented that CYP2C9 and CYP2C19 genetic polymorphisms significantly affected the pharmacokinetics of gliclazide. Although the genetic polymorphism of CYP2C19 had a greater effect on the pharmacokinetics of gliclazide, the genetic polymorphism of CYP2C9 also had a significant effect. On the other hand, plasma glucose and insulin responses to gliclazide were not significantly affected by the CYP2C9-CYP2C19 genotypes, requiring further well-controlled studies with long-term dosing of gliclazide in diabetic patients.

Pharmacogenomics of GLP-1 receptor agonists: a genome-wide analysis of observational data and large randomised controlled trials

BACKGROUND

In the treatment of type 2 diabetes, GLP-1 receptor agonists lower blood glucose concentrations, body weight, and have cardiovascular benefits. The efficacy and side effects of GLP-1 receptor agonists vary between people. Human pharmacogenomic studies of this inter-individual variation can provide both biological insight into drug action and provide biomarkers to inform clinical decision making. We therefore aimed to identify genetic variants associated with glycaemic response to GLP-1 receptor agonist treatment.

METHODS

In this genome-wide analysis we included adults (aged ≥18 years) with type 2 diabetes treated with GLP-1 receptor agonists with baseline HbA_1c of 7% or more (53 mmol/mol) from four prospective observational cohorts (DIRECT, PRIBA, PROMASTER, and GoDARTS) and two randomised clinical trials (HARMONY phase 3 and AWARD). The primary endpoint was HbA_1c reduction at 6 months after starting GLP-1 receptor agonists. We evaluated variants in GLP1R, then did a genome-wide association study and gene-based burden tests.

FINDINGS

4571 adults were included in our analysis, of these, 3339 (73%) were White European, 449 (10%) Hispanic, 312 (7%) American Indian or Alaskan Native, and 471 (10%) were other, and around 2140 (47%) of the participants were women. Variation in HbA_1c reduction with GLP-1 receptor agonists treatment was associated with rs6923761G→A (Gly168Ser) in the GLP1R (0·08% [95% CI 0·04-0·12] or 0·9 mmol/mol lower reduction in HbA_1c per serine, p=6·0 × 10^-5) and low frequency variants in ARRB1 (optimal sequence kernel association test p=6·7 × 10^-8), largely driven by rs140226575G→A (Thr370Met; 0·25% [SE 0·06] or 2·7 mmol/mol  [SE 0·7] greater HbA_1c reduction per methionine, p=5·2 × 10^-6). A similar effect size for the ARRB1 Thr370Met was seen in Hispanic and American Indian or Alaska Native populations who have a higher frequency of this variant (6-11%) than in White European populations. Combining these two genes identified 4% of the population who had a 30% greater reduction in HbA_1c than the 9% of the population with the worse response.

INTERPRETATION

This genome-wide pharmacogenomic study of GLP-1 receptor agonists provides novel biological and clinical insights. Clinically, when genotype is routinely available at the point of prescribing, individuals with ARRB1 variants might benefit from earlier initiation of GLP-1 receptor agonists.

FUNDING

Innovative Medicines Initiative and the Wellcome Trust.

Using Data to Improve the Management of Diabetes: The Tayside Experience

Tayside is a region in the East of Scotland and forms one of nine local government regions in the country. It is home to approximately 416,000 individuals who fall under the National Health Service (NHS) Tayside health board, which provides health care services to the population. In Tayside, Scotland, a comprehensive informatics network for diabetes care and research has been established for over 25 years. This has expanded more recently to a comprehensive Scotland-wide clinical care system, Scottish Care Information - Diabetes (SCI-Diabetes). This has enabled improved diabetes screening and integrated management of diabetic retinopathy, neuropathy, nephropathy, cardiovascular health, and other comorbidities. The regional health informatics network links all of these specialized services with comprehensive laboratory testing, prescribing records, general practitioner records, and hospitalization records. Not only do patients benefit from the seamless interconnectedness of these data, but also the Tayside bioresource has enabled considerable research opportunities and the creation of biobanks. In this article we describe how health informatics has been used to improve care of people with diabetes in Tayside and Scotland and, through anonymized data linkage, our understanding of the phenotypic and genotypic etiology of diabetes and associated complications and comorbidities.

SLCO1B1 c.521T>C gene polymorphism decreases hypoglycemia risk in sulfonylurea-treated type 2 diabetic patients

OBJECTIVES

Pharmacogenomics can explain some of the heterogeneity of sulfonylurea (SU)-related hypoglycemia risk. Recently, a role of OATP1B1, encoded by SLCO1B1 gene, on SU liver transport prior of metabolism has been uncovered. The aim of the present study was to explore the potential association of SLCO1B1 c.521T>C polymorphism, leading to reduced OATP1B1 function, with SU-related hypoglycemia risk.

METHODS

Study cohort consists of 176 type 2 diabetes patients treated with the SUs glimepiride or gliclazide. 92 patients reported SU-related hypoglycemia, while 84 patients had never experienced a hypoglycemic event. Patients were previously genotyped for CYP2C9 *2 and *3 variant alleles that lead to decreased enzyme activity of the SU metabolizing enzyme CYP2C9 and have been associated with increased SU-related hypoglycemia risk. SLCO1B1 c.521T>C polymorphism was genotyped by use of PCR-RFLP analysis.

RESULTS

SLCO1B1 c.521TC genotype frequency was significantly lower in hypoglycemic cases than non-hypoglycemic controls (15.2% vs. 32.1%, p=0.008). In an adjusted model, c.521TC genotype significantly reduced the risk of hypoglycemia (OR 0.371; 95% C.I. 0.167-0.822; p=0.015). In CYP2C9 intermediate metabolizers (n=54) c.521TC genotype frequency was significantly decreased in cases compared to controls (3 out of 36 cases, 8.3% vs. 7 out of 18 controls, 38.9%, p=0.012). A similar albeit not significant difference of SLCO1B1 c.521TC genotype was present in CYP2C9 extensive metabolizers (n=120) (18.2% in cases vs. 30.8% in controls, p=0.113).

CONCLUSIONS

We have found a protective effect of SLCO1B1 c.521C variant on SU-related hypoglycemia risk both independently and in interaction with CYP2C9 phenotypes. Our results suggest a possible linkage of SLCO1B1 c.521T>C polymorphism with variants in other genes impairing OATPs expressed in pancreatic islets that could interfere with SU tissue distribution.

A novel splice-affecting HNF1A variant with large population impact on diabetes in Greenland

Background

The genetic disease architecture of Inuit includes a large number of common high-impact variants. Identification of such variants contributes to our understanding of the genetic aetiology of diseases and improves global equity in genomic personalised medicine. We aimed to identify and characterise novel variants in genes associated with Maturity Onset Diabetes of the Young (MODY) in the Greenlandic population.

Methods

Using combined data from Greenlandic population cohorts of 4497 individuals, including 448 whole genome sequenced individuals, we screened 14 known MODY genes for previously identified and novel variants. We functionally characterised an identified novel variant and assessed its association with diabetes prevalence and cardiometabolic traits and population impact.

Findings

We identified a novel variant in the known MODY gene HNF1A with an allele frequency of 1.9% in the Greenlandic Inuit and absent elsewhere. Functional assays indicate that it prevents normal splicing of the gene. The variant caused lower 30-min insulin (β = -232 pmol/L, β_SD = -0.695, P = 4.43 × 10^-4) and higher 30-min glucose (β = 1.20 mmol/L, β_SD = 0.441, P = 0.0271) during an oral glucose tolerance test. Furthermore, the variant was associated with type 2 diabetes (OR 4.35, P = 7.24 × 10^-6) and HbA1c (β = 0.113 HbA1c%, β_SD = 0.205, P = 7.84 × 10^-3). The variant explained 2.5% of diabetes variance in Greenland.

Interpretation

The reported variant has the largest population impact of any previously reported variant within a MODY gene. Together with the recessive TBC1D4 variant, we show that close to 1 in 5 cases of diabetes (18%) in Greenland are associated with high-impact genetic variants compared to 1-3% in large populations.

Funding

Novo Nordisk Foundation, Independent Research Fund Denmark, and Karen Elise Jensen's Foundation.

Diabetes precision medicine: plenty of potential, pitfalls and perils but not yet ready for prime time

Rapid advances in technology and data science have the potential to improve the precision of preventive and therapeutic interventions, and enable the right treatment to be recommended, at the right time, to the right person. There are well-described examples of successful precision medicine approaches for monogenic conditions such as specific diets for phenylketonuria, and sulfonylurea treatments for certain types of MODY. However, the majority of chronic diseases are polygenic, and it is unlikely that the research strategies used for monogenic diseases will deliver similar changes to practice for polygenic traits. Type 2 diabetes, for example, is a multifactorial, heterogeneous, polygenic palette of metabolic disorders. In this non-systematic review I highlight limitations of the evidence, and the challenges that need to be overcome prior to implementation of precision medicine in the prevention and management of type 2 diabetes. Most precision medicine approaches are spuriously precise, overly complex and too narrowly focused on predicting blood glucose levels with a limited set of characteristics of individuals rather than the whole person and their context. Overall, the evidence to date is insufficient to justify widespread implementation of precision medicine approaches into routine clinical practice for type 2 diabetes. We need to retain a degree of humility and healthy scepticism when evaluating novel strategies, and to demand that existing evidence thresholds are exceeded prior to implementation.

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.

Current Insights into miRNA and lncRNA Dysregulation in Diabetes: Signal Transduction, Clinical Trials and Biomarker Discovery

Diabetes is one of the most frequently occurring metabolic disorders, affecting almost one tenth of the global population. Despite advances in antihyperglycemic therapeutics, the management of diabetes is limited due to its complexity and associated comorbidities, including diabetic neuropathy, diabetic nephropathy and diabetic retinopathy. Noncoding RNAs (ncRNAs), including microRNAs (miRNAs) and long noncoding RNAs (lncRNAs), are involved in the regulation of gene expression as well as various disease pathways in humans. Several ncRNAs are dysregulated in diabetes and are responsible for modulating the expression of various genes that contribute to the 'symptom complex' in diabetes. We review various miRNAs and lncRNAs implicated in diabetes and delineate ncRNA biological networks as well as key ncRNA targets in diabetes. Further, we discuss the spatial regulation of ncRNAs and their role(s) as prognostic markers in diabetes. We also shed light on the molecular mechanisms of signal transduction with diabetes-associated ncRNAs and ncRNA-mediated epigenetic events. Lastly, we summarize clinical trials on diabetes-associated ncRNAs and discuss the functional relevance of the dysregulated ncRNA interactome in diabetes. This knowledge will facilitate the identification of putative biomarkers for the therapeutic management of diabetes and its comorbidities. Taken together, the elucidation of the architecture of signature ncRNA regulatory networks in diabetes may enable the identification of novel biomarkers in the discovery pipeline for diabetes, which may lead to better management of this metabolic disorder.

On the Verge of Precision Medicine in Diabetes

The epidemic of type 2 diabetes (T2D) is a significant global public health challenge and a major cause of morbidity and mortality. Despite the recent proliferation of pharmacological agents for the treatment of T2D, current therapies simply treat the symptom, i.e. hyperglycemia, and do not directly address the underlying disease process or modify the disease course. This article summarizes how genomic discovery has contributed to unraveling the heterogeneity in T2D, reviews relevant discoveries in the pharmacogenetics of five commonly prescribed glucose-lowering agents, presents evidence supporting how pharmacogenetics can be leveraged to advance precision medicine, and calls attention to important research gaps to its implementation to guide treatment choices.

New and Emerging Research on Solute Carrier and ATP Binding Cassette Transporters in Drug Discovery and Development: Outlook From the International Transporter Consortium

Enabled by a plethora of new technologies, research in membrane transporters has exploded in the past decade. The goal of this state-of-the-art article is to describe recent advances in research on membrane transporters that are particularly relevant to drug discovery and development. This review covers advances in basic, translational, and clinical research that has led to an increased understanding of membrane transporters at all levels. At the basic level, we describe the available crystal structures of membrane transporters in both the solute carrier (SLC) and ATP binding cassette superfamilies, which has been enabled by the development of cryogenic electron microscopy methods. Next, we describe new research on lysosomal and mitochondrial transporters as well as recently deorphaned transporters in the SLC superfamily. The translational section includes a summary of proteomic research, which has led to a quantitative understanding of transporter levels in various cell types and tissues and new methods to modulate transporter function, such as allosteric modulators and targeted protein degraders of transporters. The section ends with a review of the effect of the gut microbiome on modulation of transporter function followed by a presentation of 3D cell cultures, which may enable in vivo predictions of transporter function. In the clinical section, we describe new genomic and pharmacogenomic research, highlighting important polymorphisms in transporters that are clinically relevant to many drugs. Finally, we describe new clinical tools, which are becoming increasingly available to enable precision medicine, with the application of tissue-derived small extracellular vesicles and real-world biomarkers.