Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci

The Effect of Diabetes-Associated Variation in TCF7L2 on Postprandial Glucose Metabolism When Glucagon and Insulin Concentrations Are Matched

Background: The rs7903146 variant in the TCF7L2 gene is associated with defects in postprandial insulin and glucagon secretion and increased risk of type 2 diabetes. However, it is unclear if this variant has effects on glucose metabolism that are independent of islet function. Methods: We studied 54 nondiabetic subjects on two occasions where endogenous hormone secretion was inhibited by somatostatin. Twenty-nine subjects were homozygous for the diabetes-associated allele (TT) and 25 for the diabetes-protective allele (CC) at rs7903146, but otherwise matched for anthropometric characteristics. On 1 day, glucagon infused at a rate of 0.65 ng/kg/min, and at 0 min prevented a fall in glucagon (nonsuppressed day). On the contrary, infusion commenced at 120 min to create a transient fall in glucagon (suppressed day). Subjects received glucose (labeled with [3-3H]-glucose) infused to mimic the systemic appearance of oral glucose. Insulin was infused to mimic a prandial insulin response. Endogenous glucose production (EGP) was measured using the tracer dilution technique. Results: Lack of glucagon suppression increased postchallenge glucose concentrations and impaired EGP suppression. However, in the presence of matched insulin and glucagon concentrations, genetic variation in TCF7L2 did not alter glucose metabolism. Conclusion: These data suggest that genetic variation in TCF7L2 alters glucose metabolism through changes in islet hormone secretion.

Three months of melatonin treatment reduces insulin sensitivity in patients with type 2 diabetes-A randomized placebo-controlled crossover trial

The use of the sleep-promoting hormone melatonin is rapidly increasing as an assumed safe sleep aid. During the last decade, accumulating observations suggest that melatonin affects glucose homeostasis, but the precise role remains to be defined. We investigated the metabolic effects of long-term melatonin treatment in patients with type 2 diabetes including determinations of insulin sensitivity and glucose-stimulated insulin secretion. We used a double-blinded, randomized, placebo-controlled, crossover design. Seventeen male participants with type 2 diabetes completed (1) 3 months of daily melatonin treatment (10 mg) 1 h before bedtime (M) and (2) 3 months of placebo treatment 1 h before bedtime (P). At the end of each treatment period, insulin secretion was assessed by an intravenous glucose tolerance test (0.3 g/kg) (IVGTT) and insulin sensitivity was assessed by a hyperinsulinemic-euglycemic clamp (insulin infusion rate 1.5 mU/kg/min) (primary endpoints). Insulin sensitivity decreased after melatonin (3.6 [2.9-4.4] vs. 4.1 [3.2-5.2] mg/(kg × min), p = .016). During the IVGTT, the second-phase insulin response was increased after melatonin (p = .03). In conclusion, melatonin treatment of male patients with type 2 diabetes for 3 months decreased insulin sensitivity by 12%. Clinical use of melatonin treatment in dosages of 10 mg should be reserved for conditions where the benefits will outweigh the potential negative impact on insulin sensitivity.

LncRNA-Associated Genetic Etiologies Are Shared between Type 2 Diabetes and Cancers in the UAE Population

Numerous epidemiological studies place patients with T2D at a higher risk for cancer. Many risk factors, such as obesity, ageing, poor diet and low physical activity, are shared between T2D and cancer; however, the biological mechanisms linking the two diseases remain largely unknown. The advent of genome wide association studies (GWAS) revealed large numbers of genetic variants associated with both T2D and cancer. Most significant disease-associated variants reside in non-coding regions of the genome. Several studies show that single nucleotide polymorphisms (SNPs) at or near long non-coding RNA (lncRNA) genes may impact the susceptibility to T2D and cancer. Therefore, the identification of genetic variants predisposing individuals to both T2D and cancer may help explain the increased risk of cancer in T2D patients. We aim to investigate whether lncRNA genetic variants with significant diabetes and cancer associations overlap in the UAE population. We first performed an annotation-based analysis of UAE T2D GWAS, confirming the high prevalence of variants at or near non-coding RNA genes. We then explored whether these T2D SNPs in lncRNAs were relevant to cancer. We highlighted six non-coding genetic variants, jointly reaching statistical significance in T2D and cancer, implicating a shared genetic architecture between the two diseases in the UAE population.

Cardiorespiratory fitness, genetic susceptibility, inflammation and risk of incident type 2 diabetes: A population-based longitudinal study

OBJECTIVE

To examine whether the association between cardiorespiratory fitness (CRF) and type 2 diabetes (T2D) is modified by genetic susceptibility and inflammation.

PARTICIPANTS

The prospective study included 57,185 participants (40-70 years) who were free from T2D and received the CRF assessment at enrollment (2006-2010) in the UK biobank. CRF was examined through a submaximal cycle ergometer test and expressed in metabolic equivalent of tasks (METs), genetic susceptibility was quantified using a genetic risk score, and inflammation was assessed according to the concentration of C-reactive protein. All these three factors were categorized into tertiles.

RESULTS

During a median follow-up of 10.4 years, 5477 (7.0%) cases of T2D were ascertained. CRF was inversely associated with the risk of T2D in a dose-response manner. The hazard ratio (HR) was 0.85 (95% confidence interval [CI]: 0.79-0.92) per 1 MET increment of CRF. There was a significant interaction between CRF and genetic susceptibility to T2D in relation to the risk of T2D (P for interaction = 0.03). Compared with participants with high CRF and low genetic susceptibility, the HR was 4.98 (95% CI: 3.17-7.82) for those with low CRF and high genetic susceptibility. A similar pattern was observed in participants with low CRF and high inflammation compared with those who had high CRF and low inflammation (HR = 2.53; 95% CI: 1.83-3.48), though the interaction between CRF and inflammation did not reach statistical significance. T2D risk declined progressively with increased CRF among different inflammation categories.

CONCLUSION

Our study reveals that genetic susceptibility may modify the association between CRF and T2D, highlighting that risk of T2D associated with genetics could benefit most from interventions on improving CRF.

Multi-staged gene expression profiling reveals potential genes and the critical pathways in kidney cancer

Cancer is among the highly complex disease and renal cell carcinoma is the sixth-leading cause of cancer death. In order to understand complex diseases such as cancer, diabetes and kidney diseases, high-throughput data are generated at large scale and it has helped in the research and diagnostic advancement. However, to unravel the meaningful information from such large datasets for comprehensive and minute understanding of cell phenotypes and disease pathophysiology remains a trivial challenge and also the molecular events leading to disease onset and progression are not well understood. With this goal, we have collected gene expression datasets from publicly available dataset which are for two different stages (I and II) for renal cell carcinoma and furthermore, the TCGA and cBioPortal database have been utilized for clinical relevance understanding. In this work, we have applied computational approach to unravel the differentially expressed genes, their networks for the enriched pathways. Based on our results, we conclude that among the most dominantly altered pathways for renal cell carcinoma, are PI3K-Akt, Foxo, endocytosis, MAPK, Tight junction, cytokine-cytokine receptor interaction pathways and the major source of alteration for these pathways are MAP3K13, CHAF1A, FDX1, ARHGAP26, ITGBL1, C10orf118, MTO1, LAMP2, STAMBP, DLC1, NSMAF, YY1, TPGS2, SCARB2, PRSS23, SYNJ1, CNPPD1, PPP2R5E. In terms of clinical significance, there are large number of differentially expressed genes which appears to be playing critical roles in survival.

Persistent organic pollutants and β-cell toxicity: a comprehensive review

Persistent organic pollutants (POPs) are a diverse family of contaminants that show widespread global dispersion and bioaccumulation. Humans are continuously exposed to POPs through diet, air particles, and household and commercial products; POPs are consistently detected in human tissues, including the pancreas. Epidemiological studies show a modest but consistent correlation between exposure to POPs and increased diabetes risk. The goal of this review is to provide an overview of epidemiological evidence and an in-depth evaluation of the in vivo and in vitro evidence that POPs cause β-cell toxicity. We review evidence for six classes of POPs: dioxins, polychlorinated biphenyls (PCBs), organochlorine pesticides (OCPs), organophosphate pesticides (OPPs), flame retardants, and per- and polyfluoroalkyl substances (PFAS). The available data provide convincing evidence implicating POPs as a contributing factor driving impaired glucose homeostasis, β-cell dysfunction, and altered metabolic and oxidative stress pathways in islets. These findings support epidemiological data showing that POPs increase diabetes risk and emphasize the need to consider the endocrine pancreas in toxicity assessments. Our review also highlights significant gaps in the literature assessing islet-specific endpoints after both in vivo and in vitro POP exposure. In addition, most rodent studies do not consider the impact of biological sex or secondary metabolic stressors in mediating the effects of POPs on glucose homeostasis and β-cell function. We discuss key gaps and limitations that should be assessed in future studies.

Integration of Omics and Phenotypic Data for Precision Medicine

Over the past two decades, biomedical research is moving toward a big-data-driven approach. The underlying causes of this transition include the ability to gather genetic or molecular profiles of humans faster, the increasing adoption of electronic health record (EHR) system, and the growing interest in linking omics and phenotypic data for analysis. The integration of individual's biology data (e.g., genomics, proteomics, metabolomics), and health-care data has created unprecedented opportunities for precision medicine, that is, a medical model that uses a patient's unique information, mainly genetic, to prevent, diagnose, or treat disease. This chapter reviewed the research opportunities and applications of integrating omics and phenotypic data for precision medicine, such as understanding the relationship between genotype and phenotype, disease subtyping, and diagnosis or prediction of adverse outcomes. We reviewed the recent advanced methods, particularly the machine learning and deep learning-based approaches used for harnessing and harmonizing the multiomics and phenotypic data to address these applications. We finally discussed the challenges and future directions.

The landscape of GWAS validation; systematic review identifying 309 validated non-coding variants across 130 human diseases

Background

The remarkable growth of genome-wide association studies (GWAS) has created a critical need to experimentally validate the disease-associated variants, 90% of which involve non-coding variants.

Methods

To determine how the field is addressing this urgent need, we performed a comprehensive literature review identifying 36,676 articles. These were reduced to 1454 articles through a set of filters using natural language processing and ontology-based text-mining. This was followed by manual curation and cross-referencing against the GWAS catalog, yielding a final set of 286 articles.

Results

We identified 309 experimentally validated non-coding GWAS variants, regulating 252 genes across 130 human disease traits. These variants covered a variety of regulatory mechanisms. Interestingly, 70% (215/309) acted through cis-regulatory elements, with the remaining through promoters (22%, 70/309) or non-coding RNAs (8%, 24/309). Several validation approaches were utilized in these studies, including gene expression (n = 272), transcription factor binding (n = 175), reporter assays (n = 171), in vivo models (n = 104), genome editing (n = 96) and chromatin interaction (n = 33).

Conclusions

This review of the literature is the first to systematically evaluate the status and the landscape of experimentation being used to validate non-coding GWAS-identified variants. Our results clearly underscore the multifaceted approach needed for experimental validation, have practical implications on variant prioritization and considerations of target gene nomination. While the field has a long way to go to validate the thousands of GWAS associations, we show that progress is being made and provide exemplars of validation studies covering a wide variety of mechanisms, target genes, and disease areas.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01216-w.

Genomic diversity and post-admixture adaptation in the Uyghurs

Population admixture results in genome-wide combinations of genetic variants derived from different ancestral populations of distinct ancestry, thus providing a unique opportunity for understanding the genetic determinants of phenotypic variation in humans. Here, we used whole-genome sequencing of 92 individuals with high coverage (30–60×) to systematically investigate genomic diversity in the Uyghurs living in Xinjiang, China (XJU), an admixed population of both European-like and East-Asian-like ancestry. The XJU population shows greater genetic diversity, especially a higher proportion of rare variants, compared with their ancestral source populations, corresponding to greater phenotypic diversity of XJU. Admixture-induced functional variants in EDAR were associated with the diversity of facial morphology in XJU. Interestingly, the interaction of functional variants between SLC24A5 and OCA2 likely influences the diversity of skin pigmentation. Notably, selection has seemingly been relaxed or canceled in several genes with significantly biased ancestry, such as HERC2–OCA2. Moreover, signatures of post-admixture adaptation in XJU were identified, including genes related to metabolism (e.g. CYP2D6), digestion (e.g. COL11A1), olfactory perception (e.g. ANO2) and immunity (e.g. HLA). Our results demonstrated population admixture as a driving force, locally or globally, in shaping human genetic and phenotypic diversity as well as in adaptive evolution.

Fine-mapping of Parkinson's disease susceptibility loci identifies putative causal variants

Recent genome-wide association studies have identified 78 loci associated with Parkinson's disease susceptibility but the underlying mechanisms remain largely unclear. To identify likely causal variants for disease risk, we fine-mapped these Parkinson's-associated loci using four different fine-mapping methods. We then integrated multi-assay cell type-specific epigenomic profiles to pinpoint the likely mechanism of action of each variant, allowing us to identify Consensus single nucleotide polymorphism (SNPs) that disrupt LRRK2 and FCGR2A regulatory elements in microglia, an MBNL2 enhancer in oligodendrocytes, and a DYRK1A enhancer in neurons. This genome-wide functional fine-mapping investigation of Parkinson's disease substantially advances our understanding of the causal mechanisms underlying this complex disease while avoiding focus on spurious, non-causal mechanisms. Together, these results provide a robust, comprehensive list of the likely causal variants, genes and cell-types underlying Parkinson's disease risk as demonstrated by consistently greater enrichment of our fine-mapped SNPs relative to lead GWAS SNPs across independent functional impact annotations. In addition, our approach prioritized an average of 3/85 variants per locus as putatively causal, making downstream experimental studies both more tractable and more likely to yield disease-relevant, actionable results. Large-scale studies comparing individuals with Parkinson's disease to age-matched controls have identified many regions of the genome associated with the disease. However, there is widespread correlation between different parts of the genome, making it difficult to tell which genetic variants cause Parkinson's and which are simply co-inherited with causal variants. We therefore applied a suite of statistical models to identify the most likely causal genetic variants (i.e. fine-mapping). We then linked these genetic variants with epigenomic and gene expression signatures across a wide variety of tissues and cell types to identify how these variants cause disease. Therefore, this study provides a comprehensive and robust list of cellular and molecular mechanisms that may serve as targets in the development of more effective Parkinson's therapeutics.

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.

Physiological Functions, Biophysical Properties, and Regulation of KCNQ1 (KV7.1) Potassium Channels

KCNQ1 (K_V7.1) K⁺ channels are expressed in multiple tissues, including the heart, pancreas, colon, and inner ear. The gene encoding the KCNQ1 protein was discovered by a positional cloning effort to determine the genetic basis of long QT syndrome, an inherited ventricular arrhythmia that can cause sudden death. Mutations in KCNQ1 can also cause other types of arrhythmia (i.e., short QT syndrome, atrial fibrillation) and the gene may also have a role in diabetes and certain cancers. KCNQ1 α-subunits can partner with accessory β-subunits (KCNE1-KCNE5) to form K⁺-selective channels that have divergent biophysical properties. In the heart, KCNQ1 α-subunits coassemble with KCNE1 β-subunits to form channels that conduct I_Ks, a very slowly activating delayed rectifier K⁺ current. K_V7.1 channels are highly regulated by PIP₂, calmodulin, and phosphorylation, and rich pharmacology includes blockers and gating modulators. Recent biophysical studies and a cryo-EM structure of the KCNQ1-calmodulin complex have provided new insights into K_V7.1 channel function, and how interactions between KCNQ1 and KCNE subunits alter the gating properties of heteromultimeric channels.

Deep Resequencing of 9 Candidate Genes Identifies a Role for ARAP1 and IGF2BP2 in Modulating Insulin Secretion Adjusted for Insulin Resistance in Obese Southern Europeans

Type 2 diabetes is characterized by impairment in insulin secretion, with an established genetic contribution. We aimed to evaluate common and low-frequency (1–5%) variants in nine genes strongly associated with insulin secretion by targeted sequencing in subjects selected from the extremes of insulin release measured by the disposition index. Collapsing data by gene and/or function, the association between disposition index and nonsense variants were significant, also after adjustment for confounding factors (OR = 0.25, 95% CI = 0.11–0.59, p = 0.001). Evaluating variants individually, three novel variants in ARAP1, IGF2BP2 and GCK, out of eight reaching significance singularly, remained associated after adjustment. Constructing a genetic risk model combining the effects of the three variants, only carriers of the ARAP1 and IGF2BP2 variants were significantly associated with a reduced probability to be in the lower, worst, extreme of insulin secretion (OR = 0.223, 95% CI = 0.105–0.473, p < 0.001). Observing a high number of normal glucose tolerance between carriers, a regression posthoc analysis was performed. Carriers of genetic risk model variants had higher probability to be normoglycemic, also after adjustment (OR = 2.411, 95% CI = 1.136–5.116, p = 0.022). Thus, in our southern European cohort, nonsense variants in all nine candidate genes showed association with better insulin secretion adjusted for insulin resistance, and we established the role of ARAP1 and IGF2BP2 in modulating insulin secretion.

Diabetes mellitus and melatonin: Where are we?

Diabetes mellitus (DM) and diabetes-related complications are amongst the leading causes of mortality worldwide. The international diabetes federation (IDF) has estimated 592 million people to suffer from DM by 2035. Hence, finding a novel biomolecule that can effectively aid diabetes management is vital, as other existing drugs have numerous side effects. Melatonin, a pineal hormone having antioxidative and anti-inflammatory properties, has been implicated in circadian dysrhythmia-linked DM. Reduced levels of melatonin and a functional link between melatonin and insulin are implicated in the pathogenesis of type 2 diabetes (T2D) Additionally, genomic studies revealed that rare variants in melatonin receptor 1b (MTNR1B) are also associated with impaired glucose tolerance and increased risk of T2D. Moreover, exogenous melatonin treatment in cell lines, rodent models, and diabetic patients has shown a potent effect in alleviating diabetes and other related complications. This highlights the role of melatonin in glucose homeostasis. However, there are also contradictory reports on the effects of melatonin supplementation. Thus, it is essential to explore if melatonin can be taken from bench to bedside for diabetes management. This review summarizes the therapeutic potential of melatonin in various diabetic models and whether it can be considered a safe drug for managing diabetic complications and diabetic manifestations like oxidative stress, inflammation, ER stress, mitochondrial dysfunction, metabolic dysregulation, etc.

echolocatoR: an automated end-to-end statistical and functional genomic fine-mapping pipeline

SUMMARY

echolocatoR integrates a diverse suite of statistical and functional fine-mapping tools to identify, test enrichment in, and visualize high-confidence causal consensus variants in any phenotype. It requires minimal input from users (a summary statistics file), can be run in a single R function, and provides extensive access to relevant datasets (e.g. reference linkage disequilibrium panels, quantitative trait loci, genome-wide annotations, cell-type-specific epigenomics), thereby enabling rapid, robust and scalable end-to-end fine-mapping investigations.

AVAILABILITY AND IMPLEMENTATION

echolocatoR is an open-source R package available through GitHub under the GNU General Public License (Version 3) license: https://github.com/RajLabMSSM/echolocatoR.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Stem Cell-Derived β Cells: A Versatile Research Platform to Interrogate the Genetic Basis of β Cell Dysfunction

Pancreatic β cell dysfunction is a central component of diabetes progression. During the last decades, the genetic basis of several monogenic forms of diabetes has been recognized. Genome-wide association studies (GWAS) have also facilitated the identification of common genetic variants associated with an increased risk of diabetes. These studies highlight the importance of impaired β cell function in all forms of diabetes. However, how most of these risk variants confer disease risk, remains unanswered. Understanding the specific contribution of genetic variants and the precise role of their molecular effectors is the next step toward developing treatments that target β cell dysfunction in the era of personalized medicine. Protocols that allow derivation of β cells from pluripotent stem cells, represent a powerful research tool that allows modeling of human development and versatile experimental designs that can be used to shed some light on diabetes pathophysiology. This article reviews different models to study the genetic basis of β cell dysfunction, focusing on the recent advances made possible by stem cell applications in the field of diabetes research.

The rs10830963 Polymorphism of the MTNR1B Gene: Association With Abnormal Glucose, Insulin and C-peptide Kinetics

BACKGROUND

The MTNR1B gene encodes a receptor for melatonin, a hormone regulating biorhythms. Disruptions in biorhythms contribute to the development of type 2 diabetes mellitus (T2DM). Genetic studies suggest that variability in the MTNR1B gene affects T2DM development. Our aim was to compare the distribution of the genetic variant rs10830963 between persons differing in glucose tolerance in a sample of the Czech population (N=1206). We also evaluated possible associations of the polymorphism with insulin sensitivity, beta cell function, with the shape of glucose, insulin and C-peptide trajectories measured 7 times during a 3-hour oral glucose tolerance test (OGTT) and with glucagon response. In a subgroup of 268 volunteers we also evaluated sleep patterns and biorhythm.

RESULTS

13 persons were diagnosed with T2DM, 119 had impaired fasting blood glucose (IFG) and/or impaired glucose tolerance (IGT). 1074 participants showed normal results and formed a control group. A higher frequency of minor allele G was found in the IFG/IGT group in comparison with controls. The GG constellation was present in 23% of diabetics, in 17% of IFG/IGT probands and in 11% of controls. Compared to CC and CG genotypes, GG homozygotes showed higher stimulated glycemia levels during the OGTT. Homozygous as well as heterozygous carriers of the G allele showed lower very early phase of insulin and C-peptide secretion with unchanged insulin sensitivity. These differences remained significant after excluding diabetics and the IFG/IGT group from the analysis. No associations of the genotype with the shape of OGTT-based trajectories, with glucagon or with chronobiological patterns were observed. However, the shape of the trajectories differed significantly between men and women.

CONCLUSION

In a representative sample of the Czech population, the G allele of the rs10830963 polymorphism is associated with impaired early phase of beta cell function, and this is evident even in healthy individuals.

Generating human papillomavirus (HPV) reference databases to maximize genomic mapping

Genomic experiments analyzing human papillomaviruses (HPVs) require a carefully selected list of sequences as a reference database to map millions of reads. The available sources, such as the Papillomavirus Episteme (PaVE), are organized based on variations in the L1 gene rather than the whole HPV sequence. Moreover, the PaVE process uses complex multiple sequence alignments containing hundreds or thousands of sequences. These issues complicate the generation of a reference database for genomics, leading to the generation of per-analysis-defined databases. Here, we propose a de novo strategy considering all HPV sequences reported in the NCBI database to define a subset of highly representative HPV sequences. The strategy is based on oligonucleotide frequency profiling of the whole sequence followed by hierarchical clustering. Using data from HPV capture experiments, we demonstrate that this strategy selects suitable sequences as a reference database to map most mappable reads unambiguously. We provide some recommendations to improve HPV mapping. The generated .fasta files can be accessed at https://github.com/vtrevino/HPV-Ref-Genomes .

A Genome-Wide Association Study of Prediabetes Status Change

We conducted the first genome-wide association study of prediabetes status change (to diabetes or normal glycaemia) among 900 White participants of the Atherosclerosis Risk in Communities (ARIC) study. Single nucleotide polymorphism (SNP)-based analysis was performed by logistic regression models, controlling for age, gender, body mass index, and the first 3 genetic principal components. Gene-based analysis was conducted by combining SNP-based p values using effective Chi-square test method. Promising SNPs (p < 1×10-5) and genes (p < 1×10-4) were further evaluated for replication among 514 White participants of the Framingham Heart Study (FHS). To accommodate familial correlations, generalized estimation equation models were applied for SNP-based analyses in the FHS. Analysis results across ARIC and FHS were combined using inverse-variance-weighted meta-analysis method for SNPs and Fisher's method for genes. We robustly identified 5 novel genes that are associated with prediabetes status change using gene-based analyses, including SGCZ (ARIC p = 9.93×10-6, FHS p = 2.00×10-3, Meta p = 3.72×10-7) at 8p22, HPSE2 (ARIC p = 8.26×10-19, FHS p = 5.85×10-3, Meta p < 8.26×10-19) at 10q24.2, ADGRA1 (ARIC p = 1.34×10-5, FHS p = 1.13×10-3, Meta p = 2.88×10-7) at 10q26.3, GLB1L3 (ARIC p = 3.71×10-6, FHS p = 4.51×10-3, Meta p = 3.16×10-7) at 11q25, and PCSK6 (ARIC p = 6.51×10-6, FHS p = 1.10×10-2, Meta p = 1.25×10-6) at 15q26.3. eQTL analysis indicated that these genes were highly expressed in tissues related to diabetes development. However, we were not able to identify any novel locus in single SNP-based analysis. Future large scale genomic studies of prediabetes status change are warranted.

Association of ACE2 gene functional variants with gestational diabetes mellitus risk in a southern Chinese population

OBJECTIVE

To explore the relationship between angiotensin-converting enzyme 2 (ACE2) genetic variants and gestational diabetes mellitus (GDM) in a southern Chinese population.

METHODS

Potential functional variants (rs2106809, rs6632677, and rs2074192) of ACE2 were selected and genotyped in 566 GDM patients and 710 normal pregnaõncies in Guilin, China. The odds ratio (OR) and its corresponding 95% confidence interval (CI) were used to evaluate the association between genetic variant and GDM risk, and then the false positive report probability, multifactor dimensional reduction (MDR), and bioinformatics tools were used to confirm the significant association in the study.

RESULTS

After adjusting for age and prepregnancy body mass index, logistic regression analysis showed that ACE2 rs6632677 was significantly associated with a decreased risk of GDM (CC vs. GG: adjusted OR = 0.09, 95% CI: 0.01 - 0.71, P = .023; GC/CC vs. GG: adjusted OR = 0.68, 95% CI = 0.46 - 0.99, P = .048; and CC vs. GG/GC: adjusted OR = 0.09, 95% CI = 0.01 - 0.72, P = .024), whereas rs2074192 was associated with increased GDM risk (TT vs. CC/CT: adjusted OR = 1.38, 95% CI = 1.08 - 1.75, P = .009). Furthermore, we found that rs6632677 interacted with SBP (P _interaction = .043) and FPG (P _interaction = .021) and rs2074192 interacted with HDL-c (P _interaction = .029) and LDL-c (P _interaction = .035) to influence the GDM risk of the individual. In the MDR analysis, the rs6632677 was the best one-locus model, and the three-loci model was the best interaction model to predict GDM risk. In addition, functional analysis confirmed that rs2074192 may regulate the splicing process of ACE2 gene.

CONCLUSION

ACE2 gene variants are significantly associated with the risk of GDM via gene-gene and gene-environment combinations. The rs2074192 C > T affects the splicing of the ACE2 gene, which may be a potential mechanism leading to the changed susceptibility of an individual female during pregnancy to GDM.

Melatonin Receptor 1B Genetic Variants on Susceptibility to Gestational Diabetes Mellitus: A Hospital-Based Case-Control Study in Wuhan, Central China

PURPOSE

The aim of the study was to find out the associations of Melatonin receptor 1B (MTNR1B) genetic variants with gestational diabetes mellitus (GDM) in Wuhan of central China.

PATIENTS AND METHODS

A hospital-based case-control study that included 1679 women was carried out to explore the associations of MTNR1B single nucleotide polymorphisms (SNPs) with GDM risk, which were analyzed through logistic regression analysis by adjusting age, pre-pregnancy BMI and family history of diabetes. Multifactor dimensionality reduction was applied to determine gene-gene interactions between SNPs.

RESULTS

MTNR1B SNPs rs10830962, rs10830963, rs1387153, rs7936247 and rs4753426 were significantly associated with GDM risk (P<0.05). The rs10830962/G, rs10830963/G, rs1387153/T, and rs7936247/T were risk variants, whereas rs4753426/T was protective variant for GDM development. Fasting plasma glucose (FPG) and 1h-plasma glucose (PG) were significantly different among genotypes at rs10830962 and rs10830963, whereas 2h-PG levels were not. Gene-gene interactions were not found among the five SNPs on GDM risk.

CONCLUSION

MTNR1B genetic variants have significant associations but no gene-gene interactions with GDM risk in central Chinese population. Furthermore, MTNR1B SNPs have significant relationships with glycemic traits.

Membrane Melatonin Receptors Activated Cell Signaling in Physiology and Disease

The pineal hormone melatonin has attracted great scientific interest since its discovery in 1958. Despite the enormous number of basic and clinical studies the exact role of melatonin in respect to human physiology remains elusive. In humans, two high-affinity receptors for melatonin, MT1 and MT2, belonging to the family of G protein-coupled receptors (GPCRs) have been cloned and identified. The two receptor types activate Gi proteins and MT2 couples additionally to Gq proteins to modulate intracellular events. The individual effects of MT1 and MT2 receptor activation in a variety of cells are complemented by their ability to form homo- and heterodimers, the functional relevance of which is yet to be confirmed. Recently, several melatonin receptor genetic polymorphisms were discovered and implicated in pathology-for instance in type 2 diabetes, autoimmune disease, and cancer. The circadian patterns of melatonin secretion, its pleiotropic effects depending on cell type and condition, and the already demonstrated cross-talks of melatonin receptors with other signal transduction pathways further contribute to the perplexity of research on the role of the pineal hormone in humans. In this review we try to summarize the current knowledge on the membrane melatonin receptor activated cell signaling in physiology and pathology and their relevance to certain disease conditions including cancer.

Diabetes, cigarette smoking and transcription factor 7-like 2 (Tcf7L2) in the UK Biobank cohort

Background —

Smokers are 30 to 40 percent more likely to develop type 2 diabetes than non-smokers. A type 2 diabetes gene, Tcf7L2, which had lost activity, caused rats to consume more nicotine. In the present study, we used data from the UK Biobank to examine the relationship of smoking, type 2 diabetes, and Tcf7L2 in human subjects.

Methods —

The Tcf7L2 gene has two SNPs, rs7903146 and rs4506565, reported to be associated with type 2 diabetes. They have approximately equal power to estimate risk for type 2 diabetes, and the results from one correlate 92% with the other. We examined the genotypes of these SNPs and cigarette consumption.

Results —

Genotype TT, linked to type 2 diabetes, smoked the least. But because of the large sample size (approximately 111,000 subjects) the tiny difference in cigarettes smoked daily by each genotype group (effect size), while statistically significant, is probably clinically meaningless. The average subject smoked 19 cigarettes daily, with a difference of 0.12 cigarette between each genotype group.

Conclusion —

The fact that Tcf7L2 is involved in nicotine addiction in rats but not in humans, as UKBB data suggest, is hardly surprising. Humans and rodents descended from a common ancestor about 80 million years ago, with rats and mice diverging between 12 and 24 million years ago. Thus, over millions of years Tcf7L2 may have developed vastly different functions in rodents and humans. Genome Wide Association Studies have revealed at least 65 different loci linked to type 2 diabetes. Genes associated with type 2 diabetes include Tcf7L2, PPARG, FTO, KCNJ11, NOTCH2, WFS1, IGF2BP2, SLC30A8, JAZF1, HHEX, DGKB, CDKN2A, CDKN2B, KCNQ1, HNF1A, HNF1B MC4R, GIPR, HNF4A, MTNR1B, PARG6, ZBED3, SLC30A8, CDKAL1, GLIS3, GCK, GCKR, among others. Perhaps one or more of these genes might be the intermediary between type 2 diabetes and cigarette smoking. Further studies are warranted.

Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits

Skeletal muscle accounts for the largest proportion of human body mass, on average, and is a key tissue in complex diseases and mobility. It is composed of several different cell and muscle fiber types. Here, we optimize single-nucleus ATAC-seq (snATAC-seq) to map skeletal muscle cell-specific chromatin accessibility landscapes in frozen human and rat samples, and single-nucleus RNA-seq (snRNA-seq) to map cell-specific transcriptomes in human. We additionally perform multi-omics profiling (gene expression and chromatin accessibility) on human and rat muscle samples. We capture type I and type II muscle fiber signatures, which are generally missed by existing single-cell RNA-seq methods. We perform cross-modality and cross-species integrative analyses on 33,862 nuclei and identify seven cell types ranging in abundance from 59.6% to 1.0% of all nuclei. We introduce a regression-based approach to infer cell types by comparing transcription start site-distal ATAC-seq peaks to reference enhancer maps and show consistency with RNA-based marker gene cell type assignments. We find heterogeneity in enrichment of genetic variants linked to complex phenotypes from the UK Biobank and diabetes genome-wide association studies in cell-specific ATAC-seq peaks, with the most striking enrichment patterns in muscle mesenchymal stem cells (∼3.5% of nuclei). Finally, we overlay these chromatin accessibility maps on GWAS data to nominate causal cell types, SNPs, transcription factor motifs, and target genes for type 2 diabetes signals. These chromatin accessibility profiles for human and rat skeletal muscle cell types are a useful resource for nominating causal GWAS SNPs and cell types.

Predicting protein interaction network perturbation by alternative splicing with semi-supervised learning

Alternative splicing introduces an additional layer of protein diversity and complexity in regulating cellular functions that can be specific to the tissue and cell type, physiological state of a cell, or disease phenotype. Recent high-throughput experimental studies have illuminated the functional role of splicing events through rewiring protein-protein interactions; however, the extent to which the macromolecular interactions are affected by alternative splicing has yet to be fully understood. In silico methods provide a fast and cheap alternative to interrogating functional characteristics of thousands of alternatively spliced isoforms. Here, we develop an accurate feature-based machine learning approach that predicts whether a protein-protein interaction carried out by a reference isoform is perturbed by an alternatively spliced isoform. Our method, called the alternatively spliced interactions prediction (ALT-IN) tool, is compared with the state-of-the-art PPI prediction tools and shows superior performance, achieving 0.92 in precision and recall values.

Identification of direct transcriptional targets of NFATC2 that promote β cell proliferation

The transcription factor NFATC2 induces β cell proliferation in mouse and human islets. However, the genomic targets that mediate these effects have not been identified. We expressed active forms of Nfatc2 and Nfatc1 in human islets. By integrating changes in gene expression with genomic binding sites for NFATC2, we identified approximately 2200 transcriptional targets of NFATC2. Genes induced by NFATC2 were enriched for transcripts that regulate the cell cycle and for DNA motifs associated with the transcription factor FOXP. Islets from an endocrine-specific Foxp1, Foxp2, and Foxp4 triple-knockout mouse were less responsive to NFATC2-induced β cell proliferation, suggesting the FOXP family works to regulate β cell proliferation in concert with NFATC2. NFATC2 induced β cell proliferation in both mouse and human islets, whereas NFATC1 did so only in human islets. Exploiting this species difference, we identified approximately 250 direct transcriptional targets of NFAT in human islets. This gene set enriches for cell cycle-associated transcripts and includes Nr4a1. Deletion of Nr4a1 reduced the capacity of NFATC2 to induce β cell proliferation, suggesting that much of the effect of NFATC2 occurs through its induction of Nr4a1. Integration of noncoding RNA expression, chromatin accessibility, and NFATC2 binding sites enabled us to identify NFATC2-dependent enhancer loci that mediate β cell proliferation.

Association between functional genetic variants in retinoid X receptor-α/γ and the risk of gestational diabetes mellitus in a southern Chinese population

To clarify the effect of retinoid X receptor-α/γ (RXR-α/γ) genes functional genetic variants (RXR-α rs4842194 G>A, RXR-γ rs100537 A>G and rs2134095 T>C) on the risk of gestational diabetes mellitus (GDM), a case–control study with 573 GDM patients and 740 pregnant women with normal glucose tolerance was performed in Guangxi area of China. An odds ratio (OR) with its corresponding 95% confidence interval (CI) was used to assess the strengths of the association between genetic variation and GDM. After adjustment of age and pre-BMI, the logistic regression analysis showed that the rs2134095 was significantly associated with GDM risk (CC vs. TT/TC: adjusted OR = 0.71, 95% CI = 0.56–0.90) in all subjects, and this result remained highly significant after Bonferroni’s correction for multiple testing (P=0.004). The stratified analysis showed that rs2134095 was significantly associated with the risk of GDM among age > 30 years (adjusted OR = 0.61, 95% CI = 0.39–0.97), BMI > 22 kg/m² (adjusted OR = 0.46, 95% CI = 0.30–0.70), systolic blood pressure (SBP) > 120 mmHg (adjusted OR = 1.96, 95% CI = 1.14–3.36), glycosylated hemoglobin A1c (HbA1c) < 6.5% (adjusted OR = 1.41, 95% CI = 1.11–1.78), TG ≤ 1.7 mmol/l (adjusted OR = 2.57, 95% CI = 1.45–4.53), TC ≤ 5.18 mmol/l (adjusted OR = 1.58, 95% CI = 1.13–2.22), high-density lipoprotein cholesterol (HDL-c) ≤ 1.5 mmol/l (adjusted OR = 1.70, 95% CI = 1.16–2.49) and low-density lipoprotein cholesterol (LDL-c) > 3.12 mmol/l (adjusted OR = 1.47, 95% CI = 1.08–2.00) subjects, under the recessive genetic model. We also found that rs2134095 interacted with age (P_interaction=0.039), pre-BMI (P_interaction=0.040) and TG (P_interaction=0.025) influencing individual’s genetic susceptibility to GDM. The rs2134095 T>C is significantly associated with the risk of GDM by effect of a single locus and/or complex joint gene–gene and gene–environment interactions. Larger sample-size and different population studies are required to confirm the findings.

Functional characterization of T2D-associated SNP effects on baseline and ER stress-responsive β cell transcriptional activation

Genome-wide association studies (GWAS) have linked single nucleotide polymorphisms (SNPs) at >250 loci in the human genome to type 2 diabetes (T2D) risk. For each locus, identifying the functional variant(s) among multiple SNPs in high linkage disequilibrium is critical to understand molecular mechanisms underlying T2D genetic risk. Using massively parallel reporter assays (MPRA), we test the cis-regulatory effects of SNPs associated with T2D and altered in vivo islet chromatin accessibility in MIN6 β cells under steady state and pathophysiologic endoplasmic reticulum (ER) stress conditions. We identify 1,982/6,621 (29.9%) SNP-containing elements that activate transcription in MIN6 and 879 SNP alleles that modulate MPRA activity. Multiple T2D-associated SNPs alter the activity of short interspersed nuclear element (SINE)-containing elements that are strongly induced by ER stress. We identify 220 functional variants at 104 T2D association signals, narrowing 54 signals to a single candidate SNP. Together, this study identifies elements driving β cell steady state and ER stress-responsive transcriptional activation, nominates causal T2D SNPs, and uncovers potential roles for repetitive elements in β cell transcriptional stress response and T2D genetics.

Genetics of Type 2 Diabetes: Opportunities for Precision Medicine: JACC Focus Seminar

Type 2 diabetes (T2D) is highly prevalent and is a strong contributor for cardiovascular disease. However, there is significant heterogeneity in disease pathogenesis and the risk of complications. Enormous progress has been made in our ability to catalog genetic variation associated with T2D risk and variation in disease-relevant quantitative traits. These discoveries hold the potential to shed light on tractable targets and pathways for safe and effective therapeutic development, but the promise of precision medicine has been slow to be realized. Recent studies have identified subgroups of individuals with differential risk for intermediate phenotypes (eg, lipid levels, fasting insulin, body mass index) that contribute to T2D risk, helping to account for the observed clinical heterogeneity. These "partitioned genetic risk scores" not only have the potential to identify patients at greatest risk of cardiovascular disease and rapid disease progression, but also could aid patient stratification bridging the gap toward precision medicine for T2D.

Druggable genome in attention deficit/hyperactivity disorder and its co-morbid conditions. New avenues for treatment

Attention-Deficit/Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder with only symptomatic care available. Genome-wide association (GWA) studies can provide a starting point in the search for novel drug targets and possibilities of drug repurposing. Here, we explored the druggable genome in ADHD by utilising GWA studies on ADHD and its co-morbid conditions. First, we explored whether the genes targeted by current ADHD drugs show association with the disorder and/or its co-morbidities. Second, we aimed to identify genes and pathways involved in the biological processes underlying ADHD that can be targeted by pharmacological agents. These ADHD-associated druggable genes and pathways were also examined in co-morbidities of ADHD, as commonalities in their aetiology and management may lead to novel pharmacological insights. Strikingly, none of the genes encoding targets of first-line pharmacotherapeutics for ADHD were significantly associated with the disorder, suggesting that FDA-approved ADHD drugs may act through different mechanisms than those underlying ADHD. In the examined druggable genome, three loci on chromosomes 1, 4 and 12 revealed significant association with ADHD and contained nine druggable genes, five of which encode established drug targets for malignancies, autoimmune and neurodevelopmental disorders. To conclude, we present a framework to assess the druggable genome in a disorder, exemplified by ADHD. We highlight signal transduction and cell adhesion as potential novel avenues for ADHD treatment. Our findings add to knowledge on known ADHD drugs and present the exploration of druggable genome associated with ADHD, which may offer interventions at the aetiological level of the disorder.

HLA Alleles Cw12 and DQ4 in Kidney Transplant Recipients Are Independent Risk Factors for the Development of Posttransplantation Diabetes

Supplemental Digital Content is available in the text.

The association between specific HLA alleles and risk for posttransplantation diabetes (PTDM) in a contemporary and multiethnic kidney transplant recipient cohort is not clear.

Genome engineering and disease modeling via programmable nucleases for insulin gene therapy; promises of CRISPR/Cas9 technology

Targeted genome editing is a continually evolving technology employing programmable nucleases to specifically change, insert, or remove a genomic sequence of interest. These advanced molecular tools include meganucleases, zinc finger nucleases, transcription activator-like effector nucleases and RNA-guided engineered nucleases (RGENs), which create double-strand breaks at specific target sites in the genome, and repair DNA either by homologous recombination in the presence of donor DNA or via the error-prone non-homologous end-joining mechanism. A recently discovered group of RGENs known as CRISPR/Cas9 gene-editing systems allowed precise genome manipulation revealing a causal association between disease genotype and phenotype, without the need for the reengineering of the specific enzyme when targeting different sequences. CRISPR/Cas9 has been successfully employed as an ex vivo gene-editing tool in embryonic stem cells and patient-derived stem cells to understand pancreatic beta-cell development and function. RNA-guided nucleases also open the way for the generation of novel animal models for diabetes and allow testing the efficiency of various therapeutic approaches in diabetes, as summarized and exemplified in this manuscript.

Type 2 diabetes is associated with the MTNR1B gene, a genetic bridge between circadian rhythm and glucose metabolism, in a Turkish population

Type 2 diabetes (T2D) is a complicated public health problem in Turkey as well as worldwide. Genome-wide approaches have been guiding in very challenging situations, such as the elucidation of genetic variations underlying complex diseases such as T2D. Despite intensive studies worldwide, few studies have determined the genetic susceptibility to T2D in Turkish populations. In this study, we investigated the effect of genes that are strongly associated with T2D in genome-wide association (GWA) studies, including MTNR1B, CDKAL1, THADA, ADAMTS9 and ENPP1, on T2D and its characteristic traits in a Turkish population. In 824 nonobese individuals (454 T2D patients and 370 healthy individuals), prominent variants of these GWA genes were genotyped by real-time PCR using the LightSNiP Genotyping Assay System. The SNP rs1387153 C/T, which is located 28 kb upstream of the MTNR1B gene, was significantly associated with T2D and fasting blood glucose levels (P < 0.05). The intronic SNP rs10830963 C/G in the MTNR1B gene was not associated with T2D, but it was associated with fasting blood glucose, HbA1C and LDL levels (P < 0.05). The other important GWA loci investigated in our study were not found to be associated with T2D or its traits. Only the SNP rs1044498 (A/C variation) in the ENPP1 gene was determined to be related to fasting blood glucose (P < 0.05). Our study suggests, consistent with the literature, that the MTNR1B locus, which has a prominent role in glucose regulation, is associated with T2D development by affecting blood glucose levels in our population.

Comparison of genetic risk prediction models to improve prediction of coronary heart disease in two large cohorts of the MONICA/KORA study

It is still unclear how genetic information, provided as single-nucleotide polymorphisms (SNPs), can be most effectively integrated into risk prediction models for coronary heart disease (CHD) to add significant predictive value beyond clinical risk models. For the present study, a population-based case-cohort was used as a trainingset (451 incident cases, 1488 noncases) and an independent cohort as testset (160 incident cases, 2749 noncases). The following strategies to quantify genetic information were compared: A weighted genetic risk score including Metabochip SNPs associated with CHD in the literature (GRS_Metabo ); selection of the most predictive SNPs among these literature-confirmed variants using priority-Lasso (PL_Metabo ); validation of two comprehensive polygenic risk scores: GRS_Gola based on Metabochip data, and GRS_Khera (available in the testset only) based on cross-validated genome-wide genotyping data. We used Cox regression to assess associations with incident CHD. C-index, category-free net reclassification index (cfNRI) and relative integrated discrimination improvement (IDI_rel ) were used to quantify the predictive performance of genetic information beyond Framingham risk score variables. In contrast to GRS_Metabo and PL_Metabo , GRS_Gola significantly improved the prediction (delta C-index [95% confidence interval]: 0.0087 [0.0044, 0.0130]; IDI_rel : 0.0509 [0.0131, 0.0894]; cfNRI improved only in cases: 0.1761 [0.0253, 0.3219]). GRS_Khera yielded slightly worse prediction results than GRS_Gola .

The trans-ancestral genomic architecture of glycemic traits

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 × 10-8), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution.

Pharmacogenetic association of diabetes-associated genetic risk score with rapid progression of coronary artery calcification following treatment with HMG-CoA-reductase inhibitors -results of the Heinz Nixdorf Recall Study

HMG-CoA-Reductase inhibitors (HMGRIs) are currently the most widely used group of drugs in patients with coronary artery disease (CAD) and are given preemptively to patients with high levels of cholesterol, including those with diabetes mellitus (DM). However, intake of HMGRIs also increases the progression of coronary artery calcification (CAC) and the risk of developing DM. This study aimed to investigate whether HMGRI intake interacts with the diabetes-associated genetic risk score (GRS) to affect CAC progression using data from the population-based Heinz Nixdorf Recall (HNR) study. CAC was measured in 3157 participants using electron-beam computed tomography twice, at baseline (CAC_b) and 5 years later (CAC_5y). CAC progression was classified as slow, expected, or rapid based on predicted values. Weighted DM GRS was constructed using 100 diabetes mellitus-associated single nucleotide polymorphisms (SNPs). We used log-linear regression to evaluate the interaction of HMGRI intake with diabetes-associated GRS and individual SNPs on CAC progression (rapid vs. expected/slow), adjusting for age, sex, and log(CAC_b + 1). The prevalence of rapid CAC progression in the HNR study was 19.6%. We did not observe any association of the weighted diabetes mellitus GRS with the rapid progression of CAC (relative risk (RR) [95% confidence interval (95% CI)]: 1.01 [0.94; 1.10]). Furthermore, no indication of an interaction between GRS and HMGRI intake was observed (1.08 [0.83; 1.41]). Our analyses showed no indication that the impact of HMGRIs on CAC progression is significantly more severe in patients with a high genetic risk of developing DM than in those with a low GRS.

Dysregulation of the Pdx1/Ovol2/Zeb2 axis in dedifferentiated β-cells triggers the induction of genes associated with epithelial-mesenchymal transition in diabetes

OBJECTIVE

β-cell dedifferentiation has been revealed as a pathological mechanism underlying pancreatic dysfunction in diabetes. We previously showed that increased miR-7 levels trigger β-cell dedifferentiation and diabetes. We used β-cell-specific miR-7 overexpressing mice (Tg7) to test the hypothesis that loss of β-cell identity triggered by miR-7 overexpression alters islet gene expression and islet microenvironment in diabetes.

METHODS

We performed bulk and single-cell RNA sequencing (RNA-seq) in islets obtained from β-cell-specific miR-7 overexpressing mice (Tg7). We carried out loss- and gain-of-function experiments in MIN6 and EndoC-bH1 cell lines. We analysed previously published mouse and human T2D data sets.

RESULTS

Bulk RNA-seq revealed that β-cell dedifferentiation is associated with the induction of genes associated with epithelial-to-mesenchymal transition (EMT) in prediabetic (2-week-old) and diabetic (12-week-old) Tg7 mice. Single-cell RNA-seq (scRNA-seq) indicated that this EMT signature is enriched specifically in β-cells. These molecular changes are associated with a weakening of β-cell: β-cell contacts, increased extracellular matrix (ECM) deposition, and TGFβ-dependent islet fibrosis. We found that the mesenchymal reprogramming of β-cells is explained in part by the downregulation of Pdx1 and its inability to regulate a myriad of epithelial-specific genes expressed in β-cells. Notable among genes transactivated by Pdx1 is Ovol2, which encodes a transcriptional repressor of the EMT transcription factor Zeb2. Following compromised β-cell identity, the reduction in Pdx1 gene expression causes a decrease in Ovol2 protein, triggering mesenchymal reprogramming of β-cells through the induction of Zeb2. We provided evidence that EMT signalling associated with the upregulation of Zeb2 expression is a molecular feature of islets in T2D subjects.

CONCLUSIONS

Our study indicates that miR-7-mediated β-cell dedifferentiation induces EMT signalling and a chronic response to tissue injury, which alters the islet microenvironment and predisposes to fibrosis. This research suggests that regulators of EMT signalling may represent novel therapeutic targets for treating β-cell dysfunction and fibrosis in T2D.

Glucocorticoid signaling in pancreatic islets modulates gene regulatory programs and genetic risk of type 2 diabetes

Glucocorticoids are key regulators of glucose homeostasis and pancreatic islet function, but the gene regulatory programs driving responses to glucocorticoid signaling in islets and the contribution of these programs to diabetes risk are unknown. In this study we used ATAC-seq and RNA-seq to map chromatin accessibility and gene expression from eleven primary human islet samples cultured in vitro with the glucocorticoid dexamethasone at multiple doses and durations. We identified thousands of accessible chromatin sites and genes with significant changes in activity in response to glucocorticoids. Chromatin sites up-regulated in glucocorticoid signaling were prominently enriched for glucocorticoid receptor binding sites and up-regulated genes were enriched for ion transport and lipid metabolism, whereas down-regulated chromatin sites and genes were enriched for inflammatory, stress response and proliferative processes. Genetic variants associated with glucose levels and T2D risk were enriched in glucocorticoid-responsive chromatin sites, including fine-mapped variants at 51 known signals. Among fine-mapped variants in glucocorticoid-responsive chromatin, a likely casual variant at the 2p21 locus had glucocorticoid-dependent allelic effects on beta cell enhancer activity and affected SIX2 and SIX3 expression. Our results provide a comprehensive map of islet regulatory programs in response to glucocorticoids through which we uncover a role for islet glucocorticoid signaling in mediating genetic risk of T2D.

CRISPR-based genome editing in primary human pancreatic islet cells

Gene targeting studies in primary human islets could advance our understanding of mechanisms driving diabetes pathogenesis. Here, we demonstrate successful genome editing in primary human islets using clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated protein 9 (Cas9). CRISPR-based targeting efficiently mutated protein-coding exons, resulting in acute loss of islet β-cell regulators, like the transcription factor PDX1 and the KATP channel subunit KIR6.2, accompanied by impaired β-cell regulation and function. CRISPR targeting of non-coding DNA harboring type 2 diabetes (T2D) risk variants revealed changes in ABCC8, SIX2 and SIX3 expression, and impaired β-cell function, thereby linking regulatory elements in these target genes to T2D genetic susceptibility. Advances here establish a paradigm for genetic studies in human islet cells, and reveal regulatory and genetic mechanisms linking non-coding variants to human diabetes risk.

Genetic Variants in Transcription Factor Binding Sites in Humans: Triggered by Natural Selection and Triggers of Diseases

Variants of transcription factor binding sites (TFBSs) constitute an important part of the human genome. Current evidence demonstrates close links between nucleotides within TFBSs and gene expression. There are multiple pathways through which genomic sequences located in TFBSs regulate gene expression, and recent genome-wide association studies have shown the biological significance of TFBS variation in human phenotypes. However, numerous challenges remain in the study of TFBS polymorphisms. This article aims to cover the current state of understanding as regards the genomic features of TFBSs and TFBS variants; the mechanisms through which TFBS variants regulate gene expression; the approaches to studying the effects of nucleotide changes that create or disrupt TFBSs; the challenges faced in studies of TFBS sequence variations; the effects of natural selection on collections of TFBSs; in addition to the insights gained from the study of TFBS alleles related to gout, its associated comorbidities (increased body mass index, chronic kidney disease, diabetes, dyslipidemia, coronary artery disease, ischemic heart disease, hypertension, hyperuricemia, osteoporosis, and prostate cancer), and the treatment responses of patients.

In-Silico Study of Immune System Associated Genes in Case of Type-2 Diabetes With Insulin Action and Resistance, and/or Obesity

Type-2 diabetes and obesity are among the leading human diseases and highly complex in terms of diagnostic and therapeutic approaches and are among the most frequent and highly complex and heterogeneous in nature. Based on epidemiological evidence, it is known that the patients suffering from obesity are considered to be at a significantly higher risk of type-2 diabetes. There are several pieces of evidence that support the hypothesis that these diseases interlinked and obesity may aggravate the risk(s) of type-2 diabetes. Multi-level unwanted alterations such as (epi-) genetic alterations, changes at the transcriptional level, and altered signaling pathways (receptor, cytoplasmic, and nuclear level) are the major sources that promote several complex diseases, and such a heterogeneous level of complexity is considered as a major barrier in the development of therapeutics. With so many known challenges, it is critical to understand the relationships and the shared causes between type-2 diabetes and obesity, and these are difficult to unravel and understand. For this purpose, we have selected publicly available datasets of gene expression for obesity and type-2 diabetes, have unraveled the genes and the pathways associated with the immune system, and have also focused on the T-cell signaling pathway and its components. We have applied a simplified computational approach to understanding differential gene expression and patterns and the enriched pathways for obesity and type-2 diabetes. Furthermore, we have also analyzed genes by using network-level understanding. In the analysis, we observe that there are fewer genes that are commonly differentially expressed while a comparatively higher number of pathways are shared between them. There are only 4 pathways that are associated with the immune system in case of obesity and 10 immune-associated pathways in case of type-2 diabetes, and, among them, only 2 pathways are commonly altered. Furthermore, we have presented SPNS1, PTPN6, CD247, FOS, and PIK3R5 as the overexpressed genes, which are the direct components of TCR signaling.

Genome-wide Association Studies Reveal Novel Locus With Sex-/Therapy-Specific Fracture Risk Effects in Childhood Cancer Survivors

Childhood cancer survivors treated with radiation therapy (RT) and osteotoxic chemotherapies are at increased risk for fractures. However, understanding of how genetic and clinical susceptibility factors jointly contribute to fracture risk among survivors is limited. To address this gap, we conducted genome-wide association studies of fracture risk after cancer diagnosis in 2453 participants of European ancestry from the Childhood Cancer Survivor Study (CCSS) with 930 incident fractures using Cox regression models (ie, time-to-event analysis) and prioritized sex- and treatment-stratified genetic associations. We performed replication analyses in 1417 survivors of European ancestry with 652 incident fractures from the St. Jude Lifetime Cohort Study (SJLIFE). In discovery, we identified a genome-wide significant (p < 5 × 10^-8 ) fracture risk locus, 16p13.3 (HAGHL), among female CCSS survivors (n = 1289) with strong evidence of sex-specific effects (p_{sex-heterogeneity}  < 7 × 10^-6 ). Combining discovery and replication data, rs1406815 showed the strongest association (hazard ratio [HR] = 1.43, p = 8.2 × 10^-9 ; n = 1935 women) at this locus. In treatment-stratified analyses in the discovery cohort, the association between rs1406815 and fracture risk among female survivors with no RT exposures was weak (HR = 1.22, 95% confidence interval [CI] 0.95-1.57, p = 0.11) but increased substantially among those with greater head/neck RT doses (any RT: HR = 1.88, 95% CI 1.54-2.28, p = 2.4 × 10^-10 ; >36 Gray only: HR = 3.79, 95% CI 1.95-7.34, p = 8.2 × 10^-5 ). These head/neck RT-specific HAGHL single-nucleotide polymorphism (SNP) effects were replicated in female SJLIFE survivors. In silico bioinformatics analyses suggest these fracture risk alleles regulate HAGHL gene expression and related bone resorption pathways. Genetic risk profiles integrating this locus may help identify female survivors who would benefit from targeted interventions to reduce fracture risk. © 2020 American Society for Bone and Mineral Research (ASBMR).

Single-cell chromatin accessibility identifies pancreatic islet cell type- and state-specific regulatory programs of diabetes risk

Single-nucleus assay for transposase-accessible chromatin using sequencing (snATAC-seq) creates new opportunities to dissect cell type-specific mechanisms of complex diseases. Since pancreatic islets are central to type 2 diabetes (T2D), we profiled 15,298 islet cells by using combinatorial barcoding snATAC-seq and identified 12 clusters, including multiple alpha, beta and delta cell states. We cataloged 228,873 accessible chromatin sites and identified transcription factors underlying lineage- and state-specific regulation. We observed state-specific enrichment of fasting glucose and T2D genome-wide association studies for beta cells and enrichment for other endocrine cell types. At T2D signals localized to islet-accessible chromatin, we prioritized variants with predicted regulatory function and co-accessibility with target genes. A causal T2D variant rs231361 at the KCNQ1 locus had predicted effects on a beta cell enhancer co-accessible with INS and genome editing in embryonic stem cell-derived beta cells affected INS levels. Together our findings demonstrate the power of single-cell epigenomics for interpreting complex disease genetics.

Investigating the molecular guts of endoderm formation using zebrafish

The vertebrate endoderm makes major contributions to the respiratory and gastrointestinal tracts and all associated organs. Zebrafish and humans share a high degree of genetic homology and strikingly similar endodermal organ systems. Combined with a multitude of experimental advantages, zebrafish are an attractive model organism to study endoderm development and disease. Recent functional genomics studies have shed considerable light on the gene regulatory programs governing early zebrafish endoderm development, while advances in biological and technological approaches stand to further revolutionize our ability to investigate endoderm formation, function and disease. Here, we discuss the present understanding of endoderm specification in zebrafish compared to other vertebrates, how current and emerging methods will allow refined and enhanced analysis of endoderm formation, and how integration with human data will allow modeling of the link between non-coding sequence variants and human disease.

Cystic Fibrosis-Related Diabetes (CFRD): Overview of Associated Genetic Factors

Cystic fibrosis (CF) is the most common autosomal recessive disease in the Caucasian population and is caused by mutations in the CF transmembrane conductance regulator (CFTR) gene that encodes for a chloride/bicarbonate channel expressed on the membrane of epithelial cells of the airways and of the intestine, as well as in cells with exocrine and endocrine functions. A common nonpulmonary complication of CF is cystic fibrosis-related diabetes (CFRD), a distinct form of diabetes due to insulin insufficiency or malfunction secondary to destruction/derangement of pancreatic betacells, as well as to other factors that affect their function. The prevalence of CFRD increases with age, and 40–50% of CF adults develop the disease. Several proposed hypotheses on how CFRD develops have emerged, including exocrine-driven fibrosis and destruction of the entire pancreas, as well as contrasting theories on the direct or indirect impact of CFTR mutation on islet function. Among contributors to the development of CFRD, in addition to CFTR genotype, there are other genetic factors related and not related to type 2 diabetes. This review presents an overview of the current understanding on genetic factors associated with glucose metabolism abnormalities in CF.

A Genetic Risk Score Improves the Prediction of Type 2 Diabetes Mellitus in Mexican Youths but Has Lower Predictive Utility Compared With Non-Genetic Factors

Background

Type 2 diabetes (T2D) is a multifactorial disease caused by a complex interplay between environmental risk factors and genetic predisposition. To date, a total of 10 single nucleotide polymorphism (SNPs) have been associated with pediatric-onset T2D in Mexicans, with a small individual effect size. A genetic risk score (GRS) that combines these SNPs could serve as a predictor of the risk for pediatric-onset T2D.

Objective

To assess the clinical utility of a GRS that combines 10 SNPs to improve risk prediction of pediatric-onset T2D in Mexicans.

Methods

This case-control study included 97 individuals with pediatric-onset T2D and 84 controls below 18 years old without T2D. Information regarding family history of T2D, demographics, perinatal risk factors, anthropometric measurements, biochemical variables, lifestyle, and fitness scores were then obtained. Moreover, 10 single nucleotide polymorphisms (SNPs) previously associated with pediatric-onset T2D in Mexicans were genotyped. The GRS was calculated by summing the 10 risk alleles. Pediatric-onset T2D risk variance was assessed using multivariable logistic regression models and the area under the receiver operating characteristic curve (AUC).

Results

The body mass index Z-score (Z-BMI) [odds ratio (OR) = 1.7; p = 0.009] and maternal history of T2D (OR = 7.1; p < 0.001) were found to be independently associated with pediatric-onset T2D. No association with other clinical risk factors was observed. The GRS also showed a significant association with pediatric-onset T2D (OR = 1.3 per risk allele; p = 0.006). The GRS, clinical risk factors, and GRS plus clinical risk factors had an AUC of 0.66 (95% CI 0.56-0.75), 0.72 (95% CI 0.62-0.81), and 0.78 (95% CI 0.70-0.87), respectively (p < 0.01).

Conclusion

The GRS based on 10 SNPs was associated with pediatric-onset T2D in Mexicans and improved its prediction with modest significance. However, clinical factors, such the Z-BMI and family history of T2D, continue to have the highest predictive utility in this population.

Analysis of Evolution and Ethnic Diversity at Glucose-Associated SNPs of Circadian Clock-Related Loci with Cryptochrome 1, Cryptochrome 2, and Melatonin receptor 1B

Diabetes shows high heritability and, worldwide, causes significant health problems including cardiovascular disease and stroke. There is significant variation in the frequency of diabetes between different populations. Both Cryptochromes and Melatonin have a major role to regulate the circadian clock. Circadian clock failure causes metabolic dysfunctions including diabetes and obesity. Variations in the Cryptochrome 1, the Cryptochrome 2, and the Melatonin receptor 1B (MTNR1B) genes show associations with fasting glucose, and are also related to circadian clock. Here, we analyzed evidence for genetic selection and ethnic diversity at circadian clock- and glucose-related gene loci associated with Cryptochrome 1, Cryptochrome 2, and MTNR1B. We carried out a 3-step genetic method to investigate genetic selection at the Cryptochrome 1, Cryptochrome 2, and MTNR1B on four populations from the 1000 Genomes Project and HapMap. First we used F-statistics to quantify genetic population differences and find ethnic diversity. Then we applied a long-range haplotype test to detect significant extreme long haplotypes, and then the integrated haplotype score (iHS) to find genetic selection at Cryptochrome 1, Cryptochrome 2, and MTNR1B. We observed genetic population differences and ethnic diversity at one glucose-associated Cryptochrome 1 single-nucleotide polymorphism (SNP) (rs8192440), one glucose-associated Cryptochrome 2 SNP (rs11605924), and one glucose-associated MTNR1B SNP (rs10830963) by F-statistics. Both Cryptochrome 1 and MTNR1B also showed selection by the iHS. These observations show new evidence for evolution at Cryptochrome 1, Cryptochrome 2 and MTNR1B. Further investigation should continue to examine the evolution of circadian clock- and glucose-related genes.

Acute metabolic effects of melatonin-A randomized crossover study in healthy young men

Melatonin regulates circadian rhythm, but may also have effects on glucose homeostasis. A common G-allele in the MTNR1B locus has been associated with an increased risk of type 2 diabetes (T2DM). We aimed to examine acute effects of high doses of melatonin on glucose metabolism with attention to MTNR1B genotype. Twenty men were examined in a double-blinded, randomized crossover study on two nonconsecutive days with four doses of 10 mg oral melatonin or placebo. Insulin sensitivity and insulin secretion were assessed by an intravenous glucose tolerance test (IVGTT) and a hyperinsulinaemic-euglycaemic clamp (HEC). Blood samples were drawn to determine the metabolic profile and MTNR1B rs10830963 genotype. Indirect calorimetry and blood pressure measurements were also performed. Insulin sensitivity index was significantly reduced on the melatonin day (P = .028) in the whole group and in homozygous carriers of the rs10830963 C-allele (P = .041). Glucose during the IVGTT was unaffected, but there was a tendency towards lower insulin and C-peptide levels in the first minutes after glucose administration in G-allele carriers. Systolic blood pressure decreased and lipid oxidation increased significantly on the melatonin day in rs10830963 G-allele carriers. Overall, our study reports that acute administration of melatonin in supra-physiological doses may have a negative impact on insulin sensitivity. Clinical trial registration number (clinicaltrial.gov): NCT03204877.