Recent advances in understanding the genetic architecture of type 2 diabetes

Healthy dietary pattern is associated with lower glycemia independently of the genetic risk of type 2 diabetes: a cross-sectional study in Finnish men

PURPOSE

Hyperglycemia is affected by lifestyle and genetic factors. We investigated if dietary patterns associate with glycemia in individuals with high or low genetic risk for type 2 diabetes (T2D).

METHODS

Men (n = 1577, 51-81 years) without T2D from the Metabolic Syndrome in Men (METSIM) cohort filled a food-frequency questionnaire and participated in a 2-hour oral glucose tolerance test. Polygenetic risk score (PRS) including 76 genetic variants was used to stratify participants into low or high T2D risk groups. We established two data-driven dietary patterns, termed healthy and unhealthy, and investigated their association with plasma glucose concentrations and hyperglycemia risk.

RESULTS

Healthy dietary pattern was associated with lower fasting and 2-hour plasma glucose, glucose area under the curve, and better insulin sensitivity (Matsuda insulin sensitivity index) and insulin secretion (disposition index) in unadjusted and adjusted models, whereas the unhealthy pattern was not. No interaction was observed between the patterns and PRS on glycemic measures. Healthy dietary pattern was negatively associated with the risk for hyperglycemia in an adjusted model (OR 0.69, 95% CI 0.51-0.95, in the highest tertile), whereas unhealthy pattern was not (OR 1.08, 95% CI 0.79-1.47, in the highest tertile). No interaction was found between diet and PRS on the risk for hyperglycemia (p = 0.69 for healthy diet, p = 0.54 for unhealthy diet).

CONCLUSION

Our findings suggest that healthy diet is associated with lower glucose concentrations and lower risk for hyperglycemia in men with no interaction with the genetic risk.

A genome-wide association study provides insights into the genetic etiology of 57 essential and non-essential trace elements in humans

Trace elements are important for human health but may exert toxic or adverse effects. Mechanisms of uptake, distribution, metabolism, and excretion are partly under genetic control but have not yet been extensively mapped. Here we report a comprehensive multi-element genome-wide association study of 57 essential and non-essential trace elements. We perform genome-wide association meta-analyses of 14 trace elements in up to 6564 Scandinavian whole blood samples, and genome-wide association studies of 43 trace elements in up to 2819 samples measured only in the Trøndelag Health Study (HUNT). We identify 11 novel genetic loci associated with blood concentrations of arsenic, cadmium, manganese, selenium, and zinc in genome-wide association meta-analyses. In HUNT, several genome-wide significant loci are also indicated for other trace elements. Using two-sample Mendelian randomization, we find several indications of weak to moderate effects on health outcomes, the most precise being a weak harmful effect of increased zinc on prostate cancer. However, independent validation is needed. Our current understanding of trace element-associated genetic variants may help establish consequences of trace elements on human health.

Mapping novel QTL and fine mapping of previously identified QTL associated with glucose tolerance using the collaborative cross mice

A chronic metabolic illness, type 2 diabetes (T2D) is a polygenic and multifactorial complicated disease. With an estimated 463 million persons aged 20 to 79 having diabetes, the number is expected to rise to 700 million by 2045, creating a significant worldwide health burden. Polygenic variants of diabetes are influenced by environmental variables. T2D is regarded as a silent illness that can advance for years before being diagnosed. Finding genetic markers for T2D and metabolic syndrome in groups with similar environmental exposure is therefore essential to understanding the mechanism of such complex characteristic illnesses. So herein, we demonstrated the exclusive use of the collaborative cross (CC) mouse reference population to identify novel quantitative trait loci (QTL) and, subsequently, suggested genes associated with host glucose tolerance in response to a high-fat diet. In this study, we used 539 mice from 60 different CC lines. The diabetogenic effect in response to high-fat dietary challenge was measured by the three-hour intraperitoneal glucose tolerance test (IPGTT) test after 12 weeks of dietary challenge. Data analysis was performed using a statistical software package IBM SPSS Statistic 23. Afterward, blood glucose concentration at the specific and between different time points during the IPGTT assay and the total area under the curve (AUC0-180) of the glucose clearance was computed and utilized as a marker for the presence and severity of diabetes. The observed AUC0-180 averages for males and females were 51,267.5 and 36,537.5 mg/dL, respectively, representing a 1.4-fold difference in favor of females with lower AUC0-180 indicating adequate glucose clearance. The AUC0-180 mean differences between the sexes within each specific CC line varied widely within the CC population. A total of 46 QTL associated with the different studied phenotypes, designated as T2DSL and its number, for Type 2 Diabetes Specific Locus and its number, were identified during our study, among which 19 QTL were not previously mapped. The genomic interval of the remaining 27 QTL previously reported, were fine mapped in our study. The genomic positions of 40 of the mapped QTL overlapped (clustered) on 11 different peaks or close genomic positions, while the remaining 6 QTL were unique. Further, our study showed a complex pattern of haplotype effects of the founders, with the wild-derived strains (mainly PWK) playing a significant role in the increase of AUC values.

Pancreatic β-cell glutaminase 2 maintains glucose homeostasis under the condition of hyperglycaemia

Glutaminase 2 (GLS2), a master regulator of glutaminolysis that is induced by p53 and converts glutamine to glutamate, is abundant in the liver but also exists in pancreatic β-cells. However, the roles of GLS2 in islets associated with glucose metabolism are unknown, presenting a critical issue. To investigate the roles of GLS2 in pancreatic β-cells in vivo, we generated β-cell-specific Gls2 conditional knockout mice (Gls2 CKO), examined their glucose homeostasis, and validated the findings using a human islet single-cell analysis database. GLS2 expression markedly increased along with p53 in β-cells from control (RIP-Cre) mice fed a high-fat diet. Furthermore, Gls2 CKO exhibited significant diabetes mellitus with gluconeogenesis and insulin resistance when fed a high-fat diet. Despite marked hyperglycaemia, impaired insulin secretion and paradoxical glucagon elevation were observed in high-fat diet-fed Gls2 CKO mice. GLS2 silencing in the pancreatic β-cell line MIN6 revealed downregulation of insulin secretion and intracellular ATP levels, which were closely related to glucose-stimulated insulin secretion. Additionally, analysis of single-cell RNA-sequencing data from human pancreatic islet cells also revealed that GLS2 expression was elevated in β-cells from diabetic donors compared to nondiabetic donors. Consistent with the results of Gls2 CKO, downregulated GLS2 expression in human pancreatic β-cells from diabetic donors was associated with significantly lower insulin gene expression as well as lower expression of members of the insulin secretion pathway, including ATPase and several molecules that signal to insulin secretory granules, in β-cells but higher glucagon gene expression in α-cells. Although the exact mechanism by which β-cell-specific GLS2 regulates insulin and glucagon requires further study, our data indicate that GLS2 in pancreatic β-cells maintains glucose homeostasis under the condition of hyperglycaemia.

TXLNG improves insulin resistance in obese subjects in vitro and in vivo by inhibiting ATF4 transcriptional activity

Lipotoxicity contributes to insulin resistance and dysfunction of pancreatic β-cells. Insulin promotes 3T3-L1 preadipocyte differentiation and facilitates glucose entry into muscle, adipose, and other tissues. In this study, differential gene expression was analyzed using four datasets, and taxilin gamma (TXLNG) was the only shared downregulated gene in all four datasets. TXLNG expression was significantly reduced in obese subjects according to online datasets and in high-fat diet (HFD)-induced insulin-resistant (IR) mice according to experimental investigations. TXLNG overexpression significantly improved IR induced by HFD in mouse models by reducing body weight and epididymal adipose weight, decreasing mRNA expression of pro-inflammatory factors interleukin 6 (IL-6) and tumor necrosis factor alpha (TNF-α), and reducing adipocyte size. High-glucose/high-insulin-stimulated adipocytes exhibited decreased TXLNG and increased signal transducer and activator of transcription 3 (STAT3) and activating transcription factor 4 (ATF4). IR significantly decreased glucose uptake, cell surface glucose transporter type 4 (GLUT4) levels, and Akt phosphorylation, while increasing the mRNA expression levels of IL-6 and TNF-α in adipocytes. However, these changes were significantly reversed by TXLNG overexpression, while they were exacerbated by TXLNG knockdown. TXLNG overexpression had no effect on ATF4 protein levels, while ATF4 overexpression increased ATF4 protein levels. Furthermore, ATF4 overexpression notably abolished the improvements in IR adipocyte dysfunction caused by TXLNG overexpression. In conclusion, TXLNG improves IR in obese subjects in vitro and in vivo by inhibiting ATF4 transcriptional activity.

Organ and cell-specific biomarkers of Long-COVID identified with targeted proteomics and machine learning

BACKGROUND

Survivors of acute COVID-19 often suffer prolonged, diffuse symptoms post-infection, referred to as "Long-COVID". A lack of Long-COVID biomarkers and pathophysiological mechanisms limits effective diagnosis, treatment and disease surveillance. We performed targeted proteomics and machine learning analyses to identify novel blood biomarkers of Long-COVID.

METHODS

A case-control study comparing the expression of 2925 unique blood proteins in Long-COVID outpatients versus COVID-19 inpatients and healthy control subjects. Targeted proteomics was accomplished with proximity extension assays, and machine learning was used to identify the most important proteins for identifying Long-COVID patients. Organ system and cell type expression patterns were identified with Natural Language Processing (NLP) of the UniProt Knowledgebase.

RESULTS

Machine learning analysis identified 119 relevant proteins for differentiating Long-COVID outpatients (Bonferonni corrected P < 0.01). Protein combinations were narrowed down to two optimal models, with nine and five proteins each, and with both having excellent sensitivity and specificity for Long-COVID status (AUC = 1.00, F1 = 1.00). NLP expression analysis highlighted the diffuse organ system involvement in Long-COVID, as well as the involved cell types, including leukocytes and platelets, as key components associated with Long-COVID.

CONCLUSIONS

Proteomic analysis of plasma from Long-COVID patients identified 119 highly relevant proteins and two optimal models with nine and five proteins, respectively. The identified proteins reflected widespread organ and cell type expression. Optimal protein models, as well as individual proteins, hold the potential for accurate diagnosis of Long-COVID and targeted therapeutics.

Deubiquitinase OTUD3 regulates metabolism homeostasis in response to nutritional stresses

The ovarian-tumor-domain-containing deubiquitinases (OTUDs) block ubiquitin-dependent protein degradation and are involved in diverse signaling pathways. We discovered a rare OTUD3 c.863G>A mutation in a family with an early age of onset of diabetes. This mutation reduces the stability and catalytic activity of OTUD3. We next constructed an experiment with Otud3^-/- mice and found that they developed worse obesity, dyslipidemia, and insulin resistance than wild-type mice when challenged with a high-fat diet (HFD). We further found that glucose and fatty acids stimulate CREB-binding-protein-dependent OTUD3 acetylation, promoting its nuclear translocation, where OTUD3 regulates various genes involved in glucose and lipid metabolism and oxidative phosphorylation by stabilizing peroxisome-proliferator-activated receptor delta (PPARδ). Moreover, targeting PPARδ using a specific agonist can partially rescue the phenotype of HFD-fed Otud3^-/- mice. We propose that OTUD3 is an important regulator of energy metabolism and that the OTUD3 c.863G>A is associated with obesity and a higher risk of diabetes.

β Cell-specific deletion of Zfp148 improves nutrient-stimulated β cell Ca2+ responses

Insulin secretion from pancreatic β cells is essential for glucose homeostasis. An insufficient response to the demand for insulin results in diabetes. We previously showed that β cell-specific deletion of Zfp148 (β-Zfp148KO) improves glucose tolerance and insulin secretion in mice. Here, we performed Ca2+ imaging of islets from β‑Zfp148KO and control mice fed both a chow and a Western-style diet. β-Zfp148KO islets demonstrated improved sensitivity and sustained Ca2+ oscillations in response to elevated glucose levels. β-Zfp148KO islets also exhibited elevated sensitivity to amino acid-induced Ca2+ influx under low glucose conditions, suggesting enhanced mitochondrial phosphoenolpyruvate-dependent (PEP-dependent), ATP-sensitive K+ channel closure, independent of glycolysis. RNA-Seq and proteomics of β-Zfp148KO islets revealed altered levels of enzymes involved in amino acid metabolism (specifically, SLC3A2, SLC7A8, GLS, GLS2, PSPH, PHGDH, and PSAT1) and intermediary metabolism (namely, GOT1 and PCK2), consistent with altered PEP cycling. In agreement with this, β-Zfp148KO islets displayed enhanced insulin secretion in response to l-glutamine and activation of glutamate dehydrogenase. Understanding pathways controlled by ZFP148 may provide promising strategies for improving β cell function that are robust to the metabolic challenge imposed by a Western diet.

Clinical Role of Serum miR-107 in Type 2 Diabetes and Related Risk Factors

Background: As the diagnostic and treatment options for diabetes improve, more attention nowadays is being paid to the exact identification of the etiopathological mechanism of type 2 diabetes (T2DM). Insulin resistance (IR) is a pathogenetic background for T2DM. Several studies demonstrate that miRNAs play an important role in systemic inflammation and thus in T2DM pathogenesis. Overexpression of miR-107 may cause an imbalance of glucose homeostasis, obesity, and dyslipidemia, by regulating insulin sensitivity through the insulin signaling pathway. Methods: 53 patients with T2DM and 54 nondiabetic patients were involved in the study. This study aimed to examine whether miR-107 expression in the serum of patients with diabetes was different from the control group (non-diabetic) and whether miR-107 expression correlated with lipid levels, BMI, and other factors, and finally, with insulin resistance in general. Results: miR-107 expression was higher in the T2DM group than in the control group (1.33 versus 0.63 (p = 0.016). In general, miR-107 expression was directly and positively associated with BMI (r = 0.3, p = 0.01), age (r = 0.3, p = 0.004), and male gender (p = 0.006). Moreover, miR-107 was related to dyslipidemia: Patients with higher miR-107 levels had lower HDL levels (in the control group: r = −0.262, p = 0.022 vs. diabetic group: r = −0.315, p = 0.007). Finally, the overexpression of miR-107 was associated with higher HOMA-IR in the diabetic group (r = 0.373, p = 0.035). Conclusion: MiR-107 expression is higher among diabetic patients than that of nondiabetic control subjects. Higher miR-107 levels are also related to dyslipidemia (lower HDL levels)—in the general cohort and non-diabetic subjects. Moreover, higher miR-107 expression is related to insulin resistance in the diabetic group. In general, higher miR-107 expression levels are related to a higher BMI, older age, and the male gender.

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.

The Impact of Pro-Inflammatory Cytokines on Alternative Splicing Patterns in Human Islets

Alternative splicing (AS) within the β cell has been proposed as one potential pathway that may exacerbate autoimmunity and unveil novel immunogenic epitopes in type 1 diabetes (T1D). We employed a computational strategy to prioritize pathogenic splicing events in human islets treated with IL-1β + IFN-γ as an ex vivo model of T1D and coupled this analysis with a k-mer based approach to predict RNA binding proteins involved in AS. In total, 969 AS events were identified in cytokine-treated islets, with the majority (44.8%) involving a skipped exon. ExonImpact identified 129 events predicted to impact protein structure. AS occurred with high frequency in MHC Class II-related mRNAs, and targeted qPCR validated reduced inclusion of Exon5 in the MHC Class II gene HLA-DMB. Single molecule RNA FISH confirmed increased HLA-DMB splicing in pancreatic sections from human donors with established T1D and autoantibody positivity. Serine and Arginine Rich Splicing Factor 2 was implicated in 37.2% of potentially pathogenic events, including Exon5 exclusion in HLA-DMB. Together, these data suggest that dynamic control of AS plays a role in the β cell response to inflammatory signals during T1D evolution.

Genome-wide association study identifying novel variant for fasting insulin and allelic heterogeneity in known glycemic loci in Chilean adolescents: The Santiago Longitudinal Study

BACKGROUND

The genetic underpinnings of glycemic traits have been understudied in adolescent and Hispanic/Latino (H/L) populations in comparison to adults and populations of European ancestry.

OBJECTIVE

To identify genetic factors underlying glycemic traits in an adolescent H/L population.

METHODS

We conducted a genome-wide association study (GWAS) of fasting glucose (FG) and fasting insulin (FI) in H/L adolescents from the Santiago Longitudinal Study.

RESULTS

We identified one novel variant positioned in the CSMD1 gene on chromosome 8 (rs77465890, effect allele frequency = 0.10) that was associated with FI (β = -0.299, SE = 0.054, p = 2.72×10-8 ) and was only slightly attenuated after adjusting for body mass index z-scores (β = -0.252, SE = 0.047, p = 1.03×10-7 ). We demonstrated directionally consistent, but not statistically significant results in African and Hispanic adults of the Population Architecture Using Genomics and Epidemiology Consortium. We also identified secondary signals for two FG loci after conditioning on known variants, which demonstrate allelic heterogeneity in well-known glucose loci.

CONCLUSION

Our results exemplify the importance of including populations with diverse ancestral origin and adolescent participants in GWAS of glycemic traits to uncover novel risk loci and expand our understanding of disease aetiology.

Whole Alga, Algal Extracts, and Compounds as Ingredients of Functional Foods: Composition and Action Mechanism Relationships in the Prevention and Treatment of Type-2 Diabetes Mellitus

Type-2 diabetes mellitus (T2DM) is a major systemic disease which involves impaired pancreatic function and currently affects half a billion people worldwide. Diet is considered the cornerstone to reduce incidence and prevalence of this disease. Algae contains fiber, polyphenols, ω-3 PUFAs, and bioactive molecules with potential antidiabetic activity. This review delves into the applications of algae and their components in T2DM, as well as to ascertain the mechanism involved (e.g., glucose absorption, lipids metabolism, antioxidant properties, etc.). PubMed, and Google Scholar databases were used. Papers in which whole alga, algal extracts, or their isolated compounds were studied in in vitro conditions, T2DM experimental models, and humans were selected and discussed. This review also focuses on meat matrices or protein concentrate-based products in which different types of alga were included, aimed to modulate carbohydrate digestion and absorption, blood glucose, gastrointestinal neurohormones secretion, glycosylation products, and insulin resistance. As microbiota dysbiosis in T2DM and metabolic alterations in different organs are related, the review also delves on the effects of several bioactive algal compounds on the colon/microbiota-liver-pancreas-brain axis. As the responses to therapeutic diets vary dramatically among individuals due to genetic components, it seems a priority to identify major gene polymorphisms affecting potential positive effects of algal compounds on T2DM treatment.

Genetic basis and identification of candidate genes for wooden breast and white striping in commercial broiler chickens

Wooden breast (WB) and white striping (WS) are highly prevalent and economically damaging muscle disorders of modern commercial broiler chickens characterized respectively by palpable firmness and fatty white striations running parallel to the muscle fiber. High feed efficiency and rapid growth, especially of the breast muscle, are believed to contribute to development of such muscle defects; however, their etiology remains poorly understood. To gain insight into the genetic basis of these myopathies, a genome-wide association study was conducted using a commercial crossbred broiler population (n = 1193). Heritability was estimated at 0.5 for WB and WS with high genetic correlation between them (0.88). GWAS revealed 28 quantitative trait loci (QTL) on five chromosomes for WB and 6 QTL on one chromosome for WS, with the majority of QTL for both myopathies located in a ~ 8 Mb region of chromosome 5. This region has highly conserved synteny with a portion of human chromosome 11 containing a cluster of imprinted genes associated with growth and metabolic disorders such as type 2 diabetes and Beckwith-Wiedemann syndrome. Candidate genes include potassium voltage-gated channel subfamily Q member 1 (KCNQ1), involved in insulin secretion and cardiac electrical activity, lymphocyte-specific protein 1 (LSP1), involved in inflammation and immune response.

Adipocyte precursor cells from first degree relatives of type 2 diabetic patients feature changes in hsa-mir-23a-5p, -193a-5p, and -193b-5p and insulin-like growth factor 2 expression

First-degree relatives (FDRs) of type 2 diabetics (T2D) feature dysfunction of subcutaneous adipose tissue (SAT) long before T2D onset. miRNAs have a role in adipocyte precursor cells (APC) differentiation and in adipocyte identity. Thus, impaired miRNA expression may contribute to SAT dysfunction in FDRs. In the present work, we have explored changes in miRNA expression associated with T2D family history which may affect gene expression in SAT APCs from FDRs. Small RNA-seq was performed in APCs from healthy FDRs and matched controls and omics data were validated by qPCR. Integrative analyses of APC miRNome and transcriptome from FDRs revealed down-regulated hsa-miR-23a-5p, -193a-5p and -193b-5p accompanied by up-regulated Insulin-like Growth Factor 2 (IGF2) gene which proved to be their direct target. The expression changes in these marks were associated with SAT adipocyte hypertrophy in FDRs. APCs from FDRs further demonstrated reduced capability to differentiate into adipocytes. Treatment with IGF2 protein decreased APC adipogenesis, while over-expression of hsa-miR-23a-5p, -193a-5p and -193b-5p enhanced adipogenesis by IGF2 targeting. Indeed, IGF2 increased the Wnt Family Member 10B gene expression in APCs. Down-regulation of the three miRNAs and IGF2 up-regulation was also observed in Peripheral Blood Leukocytes (PBLs) from FDRs. In conclusion, APCs from FDRs feature a specific miRNA/gene profile, which associates with SAT adipocyte hypertrophy and appears to contribute to impaired adipogenesis. PBL detection of this profile may help in identifying adipocyte hypertrophy in individuals at high risk of T2D.

Multi-Omics Data Analysis Uncovers Molecular Networks and Gene Regulators for Metabolic Biomarkers

The insulin-like growth factors (IGFs)/insulin resistance (IR) axis is the major metabolic hormonal pathway mediating the biologic mechanism of several complex human diseases, including type 2 diabetes (T2DM) and cancers. The genomewide association study (GWAS)-based approach has neither fully characterized the phenotype variation nor provided a comprehensive understanding of the regulatory biologic mechanisms. We applied systematic genomics to integrate our previous GWAS data for IGF-I and IR with multi-omics datasets, e.g., whole-blood expression quantitative loci, molecular pathways, and gene network, to capture the full range of genetic functionalities associated with IGF-I/IR and key drivers (KDs) in gene-regulatory networks. We identified both shared (e.g., T2DM, lipid metabolism, and estimated glomerular filtration signaling) and IR-specific (e.g., mechanistic target of rapamycin, phosphoinositide 3-kinases, and erb-b2 receptor tyrosine kinase 4 signaling) molecular biologic processes of IGF-I/IR axis regulation. Next, by using tissue-specific gene–gene interaction networks, we identified both well-established (e.g., IRS1 and IGF1R) and novel (e.g., AKT1, HRAS, and JAK1) KDs in the IGF-I/IR-associated subnetworks. Our results, if validated in additional genomic studies, may provide robust, comprehensive insights into the mechanisms of IGF-I/IR regulation and highlight potential novel genetic targets as preventive and therapeutic strategies for the associated diseases, e.g., T2DM and cancers.

Identifying Shared Risk Genes between Nonalcoholic Fatty Liver Disease and Metabolic Traits by Cross-Trait Association Analysis

Nonalcoholic fatty liver disease (NAFLD) generally co-occurs with metabolic disorders, but it is unclear which genes have a pleiotripic effect on NAFLD and metabolic traits. We performed a large-scale cross-trait association analysis to identify the overlapping genes between NAFLD and nine metabolic traits. Among all the metabolic traits, we found that obesity and type II diabetes are associated with NAFLD. Then, a multitrait association analysis among NAFLD, obesity and type II diabetes was conducted to improve the overall statistical power. We identified 792 significant variants by a cross-trait meta-analysis involving 100 pleiotripic genes. Moreover, we detected another two common genes by a genome-wide gene test. The results from the pathway enrichment analysis show that the 102 shared risk genes are enriched in cancer, diabetes, insulin secretion, and other related pathways. This study can help us understand the molecular mechanisms underlying comorbid NAFLD and metabolic disorders.

In Vivo Reporter Assays Uncover Changes in Enhancer Activity Caused by Type 2 Diabetes-Associated Single Nucleotide Polymorphisms

Many single nucleotide polymorphisms (SNPs) associated with type 2 diabetes overlap with putative endocrine pancreatic enhancers, suggesting that these SNPs modulate enhancer activity and, consequently, gene expression. We performed in vivo mosaic transgenesis assays in zebrafish to quantitatively test the enhancer activity of type 2 diabetes-associated loci. Six out of 10 tested sequences are endocrine pancreatic enhancers. The risk variant of two sequences decreased enhancer activity, while in another two incremented it. One of the latter (rs13266634) locates in an SLC30A8 exon, encoding a tryptophan-to-arginine substitution that decreases SLC30A8 function, which is the canonical explanation for type 2 diabetes risk association. However, other type 2 diabetes-associated SNPs that truncate SLC30A8 confer protection from this disease, contradicting this explanation. Here, we clarify this incongruence, showing that rs13266634 boosts the activity of an overlapping enhancer and suggesting an SLC30A8 gain of function as the cause for the increased risk for the disease. We further dissected the functionality of this enhancer, finding a single nucleotide mutation sufficient to impair its activity. Overall, this work assesses in vivo the importance of disease-associated SNPs in the activity of endocrine pancreatic enhancers, including a poorly explored case where a coding SNP modulates the activity of an enhancer.

Genetic predisposition in type 2 diabetes: A promising approach toward a personalized management of diabetes

Diabetes mellitus, also known simply as diabetes, has been described as a chronic and complex endocrine metabolic disorder that is a leading cause of death across the globe. It is considered a key public health problem worldwide and one of four important non-communicable diseases prioritized for intervention through world health campaigns by various international foundations. Among its four categories, Type 2 diabetes (T2D) is the commonest form of diabetes accounting for over 90% of worldwide cases. Unlike monogenic inherited disorders that are passed on in a simple pattern, T2D is a multifactorial disease with a complex etiology, where a mixture of genetic and environmental factors are strong candidates for the development of the clinical condition and pathology. The genetic factors are believed to be key predisposing determinants in individual susceptibility to T2D. Therefore, identifying the predisposing genetic variants could be a crucial step in T2D management as it may ameliorate the clinical condition and preclude complications. Through an understanding the unique genetic and environmental factors that influence the development of this chronic disease individuals can benefit from personalized approaches to treatment. We searched the literature published in three electronic databases: PubMed, Scopus and ISI Web of Science for the current status of T2D and its associated genetic risk variants and discus promising approaches toward a personalized management of this chronic, non-communicable disorder.

Multiomic Profiling Identifies cis-Regulatory Networks Underlying Human Pancreatic β Cell Identity and Function

EndoC-βH1 is emerging as a critical human β cell model to study the genetic and environmental etiologies of β cell (dys)function and diabetes. Comprehensive knowledge of its molecular landscape is lacking, yet required, for effective use of this model. Here, we report chromosomal (spectral karyotyping), genetic (genotyping), epigenomic (ChIP-seq and ATAC-seq), chromatin interaction (Hi-C and Pol2 ChIA-PET), and transcriptomic (RNA-seq and miRNA-seq) maps of EndoC-βH1. Analyses of these maps define known (e.g., PDX1 and ISL1) and putative (e.g., PCSK1 and mir-375) β cell-specific transcriptional cis-regulatory networks and identify allelic effects on cis-regulatory element use. Importantly, comparison with maps generated in primary human islets and/or β cells indicates preservation of chromatin looping but also highlights chromosomal aberrations and fetal genomic signatures in EndoC-βH1. Together, these maps, and a web application we created for their exploration, provide important tools for the design of experiments to probe and manipulate the genetic programs governing β cell identity and (dys)function in diabetes.

EndoC-βH1 is becoming an important cellular model to study genes and pathways governing human β cell identity and function, but its (epi)genomic similarity to primary human islets is unknown. Lawlor et al. complete and compare extensive EndoC and primary human islet multiomic maps to identify shared and distinct genomic circuitry.

When does diabetes start? Early detection and intervention in type2 diabetes mellitus

Type 2 diabetes mellitus (DM2) is a progressive disease whose pathophysiological changes occur several years before its detection. An approach based on the pathophysiological development of DM2 and its complications emphasises the importance of early and intensive intervention, not only to prevent beta-cell dysfunction but also to act on the potential associated cardiovascular risk factors before reaching the blood glucose thresholds currently set for diagnosing DM2. In the field of recently diagnosed DM2, the VERIFY study has shown that early treatment combined with metformin-vildagliptin provides relevant improvements in long-term glycaemic control and can positively affect the disease's progression.

Double diabetes: A distinct high-risk group?

The term double diabetes (DD) has been used to refer to individuals with type 1 diabetes (T1D) who are overweight, have a family history of type 2 diabetes and/or clinical features of insulin resistance. Several pieces of evidence indicate that individuals who display features of DD are at higher risk of developing future diabetes complications, independently of average glucose control, measured as glycated haemoglobin (HbA1c) concentration. Given the increased prevalence of individuals with features of DD, pragmatic criteria are urgently required to identify and stratify this group, which will help with subsequent implementation of more effective personalized interventions. In this review, we discuss the potential criteria for the clinical identification of individuals with DD, highlighting the strengths and weaknesses of each definition. We also cover potential mechanisms of DD and how these contribute to increased risk of diabetes complications. Special emphasis is placed on the role of estimated glucose disposal rate (eGDR) in the diagnosis of DD, which can be easily incorporated into clinical practice and is predictive of adverse clinical outcome. In addition to the identification of individuals with DD, eGDR has potential utility in monitoring response to different interventions. T1D is a more heterogeneous condition than initially envisaged, and those with features of DD represent a subgroup at higher risk of complications. Pragmatic criteria for the diagnosis of individuals with DD will help with risk stratification, allowing a more personalized and targeted management strategy to improve outcome and quality of life in this population.

Structural equation modeling for hypertension and type 2 diabetes based on multiple SNPs and multiple phenotypes

Genome-wide association studies (GWAS) have been successful in identifying genetic variants associated with complex diseases. However, association analyses between genotypes and phenotypes are not straightforward due to the complex relationships between genetic and environmental factors. Moreover, multiple correlated phenotypes further complicate such analyses. To resolve this complexity, we present an analysis using structural equation modeling (SEM). Unlike current methods that focus only on identifying direct associations between diseases and genetic variants such as single-nucleotide polymorphisms (SNPs), our method introduces the effects of intermediate phenotypes, which are related phenotypes distinct from the target, into the systematic genetic study of diseases. Moreover, we consider multiple diseases simultaneously in a single model. The procedure can be summarized in four steps: 1) selection of informative SNPs, 2) extraction of latent variables from the selected SNPs, 3) investigation of the relationships among intermediate phenotypes and diseases, and 4) construction of an SEM. As a result, a quantitative map can be drawn that simultaneously shows the relationship among multiple SNPs, phenotypes, and diseases. In this study, we considered two correlated diseases, hypertension and type 2 diabetes (T2D), which are known to have a substantial overlap in their disease mechanism and have significant public health implications. As intermediate phenotypes for these diseases, we considered three obesity-related phenotypes-subscapular skin fold thickness, body mass index, and waist circumference-as traits representing subcutaneous adiposity, overall adiposity, and abdominal adiposity, respectively. Using GWAS data collected from the Korea Association Resource (KARE) project, we applied the proposed SEM process. Among 327,872 SNPs, 24 informative SNPs were selected in the first step (p<1.0E-05). Ten latent variables were generated in step 2. After an exploratory analysis, we established a path diagram among phenotypes and diseases in step 3. Finally, in step 4, we produced a quantitative map with paths moving from specific SNPs to hypertension through intermediate phenotypes and T2D. The resulting model had high goodness-of-fit measures (χ2 = 536.52, NFI = 0.997, CFI = 0.998, GFI = 0.995, AGFI = 0.993, RMSEA = 0.012).

Gene loci associated with insulin secretion in islets from non-diabetic mice

Genetic susceptibility to type 2 diabetes is primarily due to β-cell dysfunction. However, a genetic study to directly interrogate β-cell function ex vivo has never been previously performed. We isolated 233,447 islets from 483 Diversity Outbred (DO) mice maintained on a Western-style diet, and measured insulin secretion in response to a variety of secretagogues. Insulin secretion from DO islets ranged >1,000-fold even though none of the mice were diabetic. The insulin secretory response to each secretagogue had a unique genetic architecture; some of the loci were specific for one condition, whereas others overlapped. Human loci that are syntenic to many of the insulin secretion QTL from mouse are associated with diabetes-related SNPs in human genome-wide association studies. We report on three genes, Ptpn18, Hunk and Zfp148, where the phenotype predictions from the genetic screen were fulfilled in our studies of transgenic mouse models. These three genes encode a non-receptor type protein tyrosine phosphatase, a serine/threonine protein kinase, and a Krϋppel-type zinc-finger transcription factor, respectively. Our results demonstrate that genetic variation in insulin secretion that can lead to type 2 diabetes is discoverable in non-diabetic individuals.

Co-shared genetics and possible risk gene pathway partially explain the comorbidity of schizophrenia, major depressive disorder, type 2 diabetes, and metabolic syndrome

Schizophrenia (SCZ) and major depressive disorder (MDD) in treatment-naive patients are associated with increased risk for type 2 diabetes (T2D) and metabolic syndrome (MetS). SCZ, MDD, T2D, and MetS are often comorbid and their comorbidity increases cardiovascular risk: Some risk genes are likely co-shared by them. For instance, transcription factor 7-like 2 (TCF7L2) and proteasome 26S subunit, non-ATPase 9 (PSMD9) are two genes independently reported as contributing to T2D and SCZ, and PSMD9 to MDD as well. However, there are scarce data on the shared genetic risk among SCZ, MDD, T2D, and/or MetS. Here, we briefly describe T2D, MetS, SCZ, and MDD and their genetic architecture. Next, we report separately about the comorbidity of SCZ and MDD with T2D and MetS, and their respective genetic overlap. We propose a novel hypothesis that genes of the prolactin (PRL)-pathway may be implicated in the comorbidity of these disorders. The inherited predisposition of patients with SCZ and MDD to psychoneuroendocrine dysfunction may confer increased risk of T2D and MetS. We illustrate a strategy to identify risk variants in each disorder and in their comorbid psychoneuroendocrine and mental-metabolic dysfunctions, advocating for studies of genetically homogeneous and phenotype-rich families. The results will guide future studies of the shared predisposition and molecular genetics of new homogeneous endophenotypes of SCZ, MDD, and metabolic impairment.

THE ASSOCIATION BETWEEN FIRST-DEGREE FAMILY HISTORY OF DIABETES AND METABOLIC SYNDROME

Objective: Because they share genetic and environmental factors with patients with diabetes, the first-degree relatives (FDRs) of patients with diabetes exhibit early signs of metabolic abnormalities. The present study aimed to investigate the correlation between family history of diabetes in FDRs and metabolic syndrome (MS), as well as changes in related risk factors. Methods: The present study population was a part of the baseline survey from the REACTION study. FDRs were defined as individuals having one or more FDRs with diabetes. MS and its components were defined according to the 2007 Joint Committee for Developing Chinese Guidelines. Results: A total of 2,692 individuals with an average age of 57.24 ± 8.35 years were enrolled in the present study. The prevalence of MS in FDRs (36.44%) was significantly higher than that in non-FDRs (25.28%; P<.001). FDRs accounted for 13.37%, 14.32%, 16.67%, 22.47%, 23.53%, and 25.58% of subjects with 0 to 5 MS components, showing an increasing trend (P for trend <.001). After adjusting for gender and age, partial correlation analyses showed significant associations of first-degree family history of diabetes with MS-related indexes (all P<.05). After adjusting for gender, age, lifestyle habits, and total metabolic traits, the first-degree family history of diabetes remained an independent factor that was positively associated with MS (odds ratio, 1.765; P<.001). Conclusion: A first-degree family history of diabetes predisposes individuals to developing MS and stands out as an independent risk factor for MS even without considering the subsequent effects of hyperglycemia. Abbreviations: BMI = body mass index; DBP = diastolic blood pressure; FDR = first-degree relative; FPG = fasting plasma glucose; HbA1c = glycated hemoglobin A1c; HDL-c = high-density-lipoprotein cholesterol; LDL-c = low-density-lipoprotein cholesterol; MAP = mean arterial pressure; MS = metabolic syndrome; OR = odds ratio; SBP = systolic blood pressure; TC = total cholesterol; TG = triglyceride; WC = waist circumference; WHR = waist-to-hip ratio; 2hPG = 2-hour plasma glucose.

Sibling Similarity in Metabolic Syndrome: The Portuguese Sibling Study on Growth, Fitness, Lifestyle and Health

This study aims to estimate sibling resemblance in metabolic syndrome (MS) markers, and to investigate the associations of biological and behavioral characteristics with MS. The sample comprises 679 biological siblings (363 females; 316 males) aged 9-20 years. MS markers included waist circumference (WC), high-density lipoprotein cholesterol (HDL-C), triglycerides (TRI), fasting glucose (GLU) and systolic blood pressure (SBP). Body mass index (BMI), biological maturation, muscular, and cardiorespiratory fitness were also assessed. Behavioral characteristics, including dietary intake and physical activity, were self-reported by questionnaire. Multilevel models were used, and sibling resemblance was estimated using the intraclass correlation (ρ). In general, same-sex siblings showed higher resemblance in MS markers than opposite-sex siblings. However, variability in sibling resemblance in MS markers was evident with the inclusion of covariates. Biological characteristics including age, BMI and maturity offset influenced all MS markers except for TRI. Importantly, behavioral characteristics diversely influenced MS markers: fruit and vegetables only influenced SBP, whereas physical activity affected HDL-C. Additionally, muscular fitness impacted significantly on MS Z-score, WC, SBP and GLU, whilst cardiorespiratory fitness only affected WC. In conclusion, biological and behavioral characteristics influenced the expression of MS markers. These results confirmed the importance of considering individual characteristics when designing individualized programs for diminishing the adverse effects of specific MS markers.

Incident Type 2 Diabetes Among Individuals With CKD: Findings From the Chronic Renal Insufficiency Cohort (CRIC) Study

RATIONALE & OBJECTIVE

Few studies have examined incident type 2 diabetes mellitus (T2DM) in chronic kidney disease (CKD). Our objective was to examine rates of and risk factors for T2DM in CKD, using several alternative measures of glycemic control.

STUDY DESIGN

Prospective cohort study.

SETTING & PARTICIPANTS

1,713 participants with reduced glomerular filtration rates and without diabetes at baseline, enrolled in the Chronic Renal Insufficiency Cohort (CRIC) Study.

PREDICTORS

Measures of kidney function and damage, fasting blood glucose, hemoglobin A1c (HbA1c), HOMA-IR (homeostatic model assessment of insulin resistance), demographics, family history of diabetes mellitus (DM), smoking status, medication use, systolic blood pressure, triglyceride level, high-density lipoprotein cholesterol level, body mass index, and physical activity.

OUTCOME

Incident T2DM (defined as fasting blood glucose ≥ 126mg/dL or prescription of insulin or oral hypoglycemic agents).

ANALYTICAL APPROACH

Concordance between fasting blood glucose and HbA1c levels was assessed using κ. Cause-specific hazards modeling, treating death and end-stage kidney disease as competing events, was used to predict incident T2DM.

RESULTS

Overall T2DM incidence rate was 17.81 cases/1,000 person-years. Concordance between fasting blood glucose and HbA1c levels was low (κ for categorical versions of fasting blood glucose and HbA1c = 13%). Unadjusted associations of measures of kidney function and damage with incident T2DM were nonsignificant (P ≥ 0.4). In multivariable models, T2DM was significantly associated with fasting blood glucose level (P = 0.002) and family history of DM (P = 0.03). The adjusted association of HOMA-IR with T2DM was comparable to that of fasting blood glucose level; the association of HbA1c level was nonsignificant (P ≥ 0.1). Harrell's C for the models ranged from 0.62 to 0.68.

LIMITATIONS

Limited number of outcome events; predictors limited to measures taken at baseline.

CONCLUSIONS

The T2DM incidence rate among individuals with CKD is markedly higher than in the general population, supporting the need for greater vigilance in this population. Measures of glycemic control and family history of DM were independently associated with incident T2DM.

Dietary Fatty Acids and the Metabolic Syndrome: A Personalized Nutrition Approach

Dietary fatty acids are present in a wide variety of foods and appear in different forms and lengths. The different fatty acids are known to have various effects on metabolic health. The metabolic syndrome (MetS) is a constellation of risk factors of chronic diseases. The etiology of the MetS is represented by a complex interplay of genetic and environmental factors. Dietary fatty acids can be important contributors of the evolution or in prevention of the MetS; however, great interindividual variability exists in the response to fatty acids. The identification of genetic variants interacting with fatty acids might explain this heterogeneity in metabolic responses. This chapter reviews the mechanisms underlying the interactions between the different components of the MetS, dietary fatty acids and genes. Challenges surrounding the implementation of personalized nutrition are also covered.

Effects of Genetic Variants of Nuclear Receptor Y on the Risk of Type 2 Diabetes Mellitus

Nuclear factor-Y (NF-Y) consists of three evolutionary conserved subunits including NF-YA, NF-YB, and NF-YC; it is a critical transcriptional regulator of lipid and glucose metabolism and adipokine biosynthesis that are associated with type 2 diabetes mellitus (T2DM) occurrence, while the impacts of genetic variants in the NF-Y gene on the risk of T2DM remain to be investigated. In the present study, we screened five single-nucleotide polymorphisms (SNPs) with the SNaPshot method in 427 patients with T2DM and 408 healthy individuals. Subsequently, we analyzed the relationships between genotypes and haplotypes constructed from these SNPs with T2DM under diverse genetic models. Furthermore, we investigated the allele effects on the quantitative metabolic traits. Of the five tagSNPs, we found that three SNPs (rs2268188, rs6918969, and rs28869187) exhibited nominal significant differences in allelic or genotypic frequency between patients with T2DM and healthy individuals. The minor alleles G, C, and C at rs2268188, rs6918969, and rs28869187, respectively, conferred a higher T2DM risk under a dominant genetic model, and the carriers of these risk alleles (either homozygotes of the minor allele or heterozygotes) had statistically higher levels of fasting plasma glucose, cholesterol, and triglycerides. Haplotype analysis showed that SNPs rs2268188, rs6918969, rs28869187, and rs35105472 formed a haplotype block, and haplotype TTAC was protective against T2DM (OR = 0.76, 95% CI = 0.33-0.82, P = 0.004), while haplotype GCCG was associated with an elevated susceptibility to T2DM (OR = 2.33, 95% CI = 1.43-3.57, P = 0.001). This study is the first ever observation to our knowledge that indicates the genetic variants of NF-YA might influence a Chinese Han individual's occurrence of T2DM.

Genome-Wide Meta-analysis of Gene-Environmental Interaction for Insulin Resistance Phenotypes and Breast Cancer Risk in Postmenopausal Women

Insulin resistance (IR)-related genetic variants are possibly associated with breast cancer, and the gene-phenotype-cancer association could be modified by lifestyle factors including obesity, physical inactivity, and high-fat diet. Using data from postmenopausal women, a population highly susceptible to obesity, IR, and increased risk of breast cancer, we implemented a genome-wide association study (GWAS) in two steps: (1) GWAS meta-analysis of gene-environmental (i.e., behavioral) interaction (G*E) for IR phenotypes (hyperglycemia, hyperinsulinemia, and homeostatic model assessment-insulin resistance) and (2) after the G*E GWAS meta-analysis, the identified SNPs were tested for their associations with breast cancer risk in overall or subgroup population, where the SNPs were identified at genome-wide significance. We found 58 loci (55 novel SNPs; 5 index SNPs and 6 SNPs, independent of each other) that are associated with IR phenotypes in women overall or women stratified by obesity, physical activity, and high-fat diet; among those 58 loci, 29 (26 new loci; 2 index SNPs and 2 SNPs, independently) were associated with postmenopausal breast cancer. Our study suggests that a number of newly identified SNPs may have their effects on glucose intolerance by interplaying with obesity and other lifestyle factors, and a substantial proportion of these SNPs' susceptibility can also interact with the lifestyle factors to ultimately influence breast cancer risk. These findings may contribute to improved prediction accuracy for cancer and suggest potential intervention strategies for those women carrying genetic risk that will reduce their breast cancer risk.

Genetic Determinants of Glycemic Traits and the Risk of Gestational Diabetes Mellitus

Many common genetic polymorphisms are associated with glycemic traits and type 2 diabetes (T2D), but knowledge about genetic determinants of glycemic traits in pregnancy is limited. We tested genetic variants known to be associated with glycemic traits and T2D in the general population for associations with glycemic traits in pregnancy and gestational diabetes mellitus (GDM). Participants in two cohorts (Genetics of Glucose regulation in Gestation and Growth [Gen3G] and Hyperglycemia and Adverse Pregnancy Outcome [HAPO]) underwent oral glucose tolerance testing at 24-32 weeks' gestation. We built genetic risk scores (GRSs) for elevated fasting glucose and insulin, reduced insulin secretion and sensitivity, and T2D, using variants discovered in studies of nonpregnant individuals. We tested for associations between these GRSs, glycemic traits in pregnancy, and GDM. In both cohorts, the fasting glucose GRS was strongly associated with fasting glucose. The insulin secretion and sensitivity GRSs were also significantly associated with these traits in Gen3G, where insulin measurements were available. The fasting insulin GRS was weakly associated with fasting insulin (Gen3G) or C-peptide (HAPO). In HAPO (207 GDM case subjects), all five GRSs (T2D, fasting glucose, fasting insulin, insulin secretion, and insulin sensitivity) were significantly associated with GDM. In Gen3G (43 GDM case subjects), both the T2D and insulin secretion GRSs were associated with GDM; effect sizes for the other GRSs were similar to those in HAPO. Thus, despite the profound changes in glycemic physiology during pregnancy, genetic determinants of fasting glucose, fasting insulin, insulin secretion, and insulin sensitivity discovered outside of pregnancy influence GDM risk.

Type 2 Diabetes-Associated Genetic Variants Regulate Chromatin Accessibility in Human Islets

Type 2 diabetes (T2D) is a complex disorder in which both genetic and environmental risk factors contribute to islet dysfunction and failure. Genome-wide association studies (GWAS) have linked single nucleotide polymorphisms (SNPs), most of which are noncoding, in >200 loci to islet dysfunction and T2D. Identification of the putative causal variants and their target genes and whether they lead to gain or loss of function remains challenging. Here, we profiled chromatin accessibility in pancreatic islet samples from 19 genotyped individuals and identified 2,949 SNPs associated with in vivo cis-regulatory element use (i.e., chromatin accessibility quantitative trait loci [caQTL]). Among the caQTLs tested (n = 13) using luciferase reporter assays in MIN6 β-cells, more than half exhibited effects on enhancer activity that were consistent with in vivo chromatin accessibility changes. Importantly, islet caQTL analysis nominated putative causal SNPs in 13 T2D-associated GWAS loci, linking 7 and 6 T2D risk alleles, respectively, to gain or loss of in vivo chromatin accessibility. By investigating the effect of genetic variants on chromatin accessibility in islets, this study is an important step forward in translating T2D-associated GWAS SNP into functional molecular consequences.

Adipose Tissue Transferrin and Insulin Resistance

Context

Excessive body iron stores are a risk factor for decreased insulin sensitivity (SI) and diabetes. We hypothesized that transcriptional dysregulation of genes involved in iron metabolism in adipocytes causes insulin resistance.

Objective and Design

To define the genetic regulation of iron metabolism and its role in SI, we used gene expression, genotype, and SI data from an African American cohort (N = 256). Replication studies were performed in independent European ancestry cohorts. In vitro studies in human adipocytes were performed to define the role of a selected gene in causing insulin resistance.

Results

Among 62 transcripts representing iron homeostasis genes, expression of 30 in adipose tissue were correlated with SI. Transferrin (TF) and ferritin heavy polypeptide were most positively and negatively associated with SI, respectively. These observations were replicated in two independent European ancestry adipose data sets. The strongest cis-regulatory variant for TF expression (rs6785596; P = 7.84 × 10-18) was identified in adipose but not muscle or liver tissue. Variants significantly affected the normal relationship of serum ferritin to insulin resistance. Knockdown of TF in differentiated Simpson-Golabi-Behmel syndrome adipocytes by short hairpin RNA decreased intracellular iron, reduced maximal insulin-stimulated glucose uptake, and reduced Akt phosphorylation. Knockdown of TF caused differential expression of 465 genes, including genes involved in glucose transport, mitochondrial function, Wnt-pathway/ SI, chemokine activity, and obesity. Iron chelation recapitulated key changes in the expression profile induced by TF knockdown.

Conclusion

Genetic regulation of TF expression in adipose tissue plays a novel role in regulating SI.

A coding and non-coding transcriptomic perspective on the genomics of human metabolic disease

Genome-wide association studies (GWAS), relying on hundreds of thousands of individuals, have revealed >200 genomic loci linked to metabolic disease (MD). Loss of insulin sensitivity (IS) is a key component of MD and we hypothesized that discovery of a robust IS transcriptome would help reveal the underlying genomic structure of MD. Using 1,012 human skeletal muscle samples, detailed physiology and a tissue-optimized approach for the quantification of coding (>18,000) and non-coding (>15,000) RNA (ncRNA), we identified 332 fasting IS-related genes (CORE-IS). Over 200 had a proven role in the biochemistry of insulin and/or metabolism or were located at GWAS MD loci. Over 50% of the CORE-IS genes responded to clinical treatment; 16 quantitatively tracking changes in IS across four independent studies (P = 0.0000053: negatively: AGL, G0S2, KPNA2, PGM2, RND3 and TSPAN9 and positively: ALDH6A1, DHTKD1, ECHDC3, MCCC1, OARD1, PCYT2, PRRX1, SGCG, SLC43A1 and SMIM8). A network of ncRNA positively related to IS and interacted with RNA coding for viral response proteins (P < 1 × 10-48), while reduced amino acid catabolic gene expression occurred without a change in expression of oxidative-phosphorylation genes. We illustrate that combining in-depth physiological phenotyping with robust RNA profiling methods, identifies molecular networks which are highly consistent with the genetics and biochemistry of human metabolic disease.

Type 2 diabetes genetic loci informed by multi-trait associations point to disease mechanisms and subtypes: A soft clustering analysis

BACKGROUND

Type 2 diabetes (T2D) is a heterogeneous disease for which (1) disease-causing pathways are incompletely understood and (2) subclassification may improve patient management. Unlike other biomarkers, germline genetic markers do not change with disease progression or treatment. In this paper, we test whether a germline genetic approach informed by physiology can be used to deconstruct T2D heterogeneity. First, we aimed to categorize genetic loci into groups representing likely disease mechanistic pathways. Second, we asked whether the novel clusters of genetic loci we identified have any broad clinical consequence, as assessed in four separate subsets of individuals with T2D.

METHODS AND FINDINGS

In an effort to identify mechanistic pathways driven by established T2D genetic loci, we applied Bayesian nonnegative matrix factorization (bNMF) clustering to genome-wide association study (GWAS) results for 94 independent T2D genetic variants and 47 diabetes-related traits. We identified five robust clusters of T2D loci and traits, each with distinct tissue-specific enhancer enrichment based on analysis of epigenomic data from 28 cell types. Two clusters contained variant-trait associations indicative of reduced beta cell function, differing from each other by high versus low proinsulin levels. The three other clusters displayed features of insulin resistance: obesity mediated (high body mass index [BMI] and waist circumference [WC]), "lipodystrophy-like" fat distribution (low BMI, adiponectin, and high-density lipoprotein [HDL] cholesterol, and high triglycerides), and disrupted liver lipid metabolism (low triglycerides). Increased cluster genetic risk scores were associated with distinct clinical outcomes, including increased blood pressure, coronary artery disease (CAD), and stroke. We evaluated the potential for clinical impact of these clusters in four studies containing individuals with T2D (Metabolic Syndrome in Men Study [METSIM], N = 487; Ashkenazi, N = 509; Partners Biobank, N = 2,065; UK Biobank [UKBB], N = 14,813). Individuals with T2D in the top genetic risk score decile for each cluster reproducibly exhibited the predicted cluster-associated phenotypes, with approximately 30% of all individuals assigned to just one cluster top decile. Limitations of this study include that the genetic variants used in the cluster analysis were restricted to those associated with T2D in populations of European ancestry.

CONCLUSION

Our approach identifies salient T2D genetically anchored and physiologically informed pathways, and supports the use of genetics to deconstruct T2D heterogeneity. Classification of patients by these genetic pathways may offer a step toward genetically informed T2D patient management.

Genome-Wide Association Study of Serum Fructosamine and Glycated Albumin in Adults Without Diagnosed Diabetes: Results From the Atherosclerosis Risk in Communities Study

Fructosamine and glycated albumin are potentially useful alternatives to hemoglobin A1c (HbA1c) as diabetes biomarkers. The genetic determinants of fructosamine and glycated albumin, however, are unknown. We performed genome-wide association studies of fructosamine and glycated albumin among 2,104 black and 7,647 white participants without diabetes in the Atherosclerosis Risk in Communities (ARIC) Study and replicated findings in the Coronary Artery Risk Development in Young Adults (CARDIA) study. Among whites, rs34459162, a novel missense single nucleotide polymorphism (SNP) in RCN3, was associated with fructosamine (P = 5.3 × 10-9) and rs1260236, a known diabetes-related missense mutation in GCKR, was associated with percent glycated albumin (P = 5.9 × 10-9) and replicated in CARDIA. We also found two novel associations among blacks: an intergenic SNP, rs2438321, associated with fructosamine (P = 6.2 × 10-9), and an intronic variant in PRKCA, rs59443763, associated with percent glycated albumin (P = 4.1 × 10-9), but these results did not replicate. Few established fasting glucose or HbA1c SNPs were also associated with fructosamine or glycated albumin. Overall, we found genetic variants associated with the glycemic information captured by fructosamine and glycated albumin as well as with their nonglycemic component. This highlights the importance of examining the genetics of hyperglycemia biomarkers to understand the information they capture, including potential glucose-independent factors.

Whole-exome sequencing identifies a novel INS mutation causative of maturity-onset diabetes of the young 10

Monogenic diabetes is often misdiagnosed with type 2 diabetes due to overlapping characteristics. This study aimed to discover novel causative mutations of monogenic diabetes in patients with clinically diagnosed type 2 diabetes and to explore potential molecular mechanisms. Whole-exome sequencing was performed on 31 individuals clinically diagnosed with type 2 diabetes. One novel heterozygous mutation (p.Ala2Thr) in INS was identified. It was further genotyped in an additional case-control population (6523 cases and 4635 controls), and this variant was observed in 0.09% of cases. Intracellular trafficking of insulin proteins was assessed in INS1-E and HEK293T cells. p.Ala2Thr preproinsulin-GFP was markedly retained in the endoplasmic reticulum (ER) in INS1-E cells. Activation of the PERK-eIF2α-ATF4, IRE1α-XBP1, and ATF6 pathways as well as upregulated ER chaperones were detected in INS1-E cells transfected with the p.Ala2Thr mutant. In conclusion, we identified a causative mutation in INS responsible for maturity-onset diabetes of the young 10 (MODY10) in a Chinese population and demonstrated that this mutation affected β cell function by inducing ER stress.

Sarcopoterium spinosum extract improved insulin sensitivity in mice models of glucose intolerance and diabetes

BACKGROUND

The glucose lowering properties of Sarcopoterium spinosum, a traditional medicinal plant, were previously validated by us using KK-Ay mice as a genetic model for type 2 diabetes (T2D).

OBJECTIVE

To clarify the effects of Sarcopoterium spinosum extract (SSE) on diet-induced glucose intolerance and to investigate SSE effects on carbohydrate and lipid metabolism in target tissues of both high-fat-diet (HFD)-fed and KK-Ay mice.

RESULTS

Mice were given SSE (70 mg/day) for 6 weeks. SSE improved glucose tolerance and insulin sensitivity in HFD-fed mice as was demonstrated previously in KK-Ay mice. Higher insulin sensitivity was validated by lower serum insulin and activation of the insulin signaling cascade in skeletal muscle and liver of SSE-treated mice in both models. H&E staining of the livers demonstrated lower severity of steatosis in SSE-treated mice. Several model-specific effects of SSE were observed-mRNA expression of proinflammatory genes and CD36 was reduced in SSE-treated KK-Ay mice. Hepatic mRNA expression of PEPCK was also reduced in SSE-treated KK-Ay mice, while other genes involved in carbohydrates and lipid metabolism were not affected. HFD-fed mice treated by SSE had elevated hepatic glycogen stores. Gluconeogenic gene expression was not affected, while GCK expression was increased. HFD-induced hepatic steatosis was not affected by SSE. However, while genes involved in lipid metabolism were downregulated by HFD, this was not found in HFD-fed mice given SSE, demonstrating an expression profile which is similar to that of standard diet-fed mice.

CONCLUSION

Our study supports the insulin sensitizing activity of SSE and suggests that this extract might improve other manifestations of the metabolic syndrome.

Insulin promoter in human pancreatic β cells contacts diabetes susceptibility loci and regulates genes affecting insulin metabolism

Both type 1 and type 2 diabetes involve a complex interplay between genetic, epigenetic, and environmental factors. Our laboratory has been interested in the physical interactions, in nuclei of human pancreatic β cells, between the insulin (INS) gene and other genes that are involved in insulin metabolism. We have identified, using Circularized Chromosome Conformation Capture (4C), many physical contacts in a human pancreatic β cell line between the INS promoter on chromosome 11 and sites on most other chromosomes. Many of these contacts are associated with type 1 or type 2 diabetes susceptibility loci. To determine whether physical contact is correlated with an ability of the INS locus to affect expression of these genes, we knock down INS expression by targeting the promoter; 259 genes are either up or down-regulated. Of these, 46 make physical contact with INS We analyze a subset of the contacted genes and show that all are associated with acetylation of histone H3 lysine 27, a marker of actively expressed genes. To demonstrate the usefulness of this approach in revealing regulatory pathways, we identify from among the contacted sites the previously uncharacterized gene SSTR5-AS1 and show that it plays an important role in controlling the effect of somatostatin-28 on insulin secretion. These results are consistent with models in which clustering of genes supports transcriptional activity. This may be a particularly important mechanism in pancreatic β cells and in other cells where a small subset of genes is expressed at high levels.

Identification and functional analysis of glycemic trait loci in the China Health and Nutrition Survey

To identify genetic contributions to type 2 diabetes (T2D) and related glycemic traits (fasting glucose, fasting insulin, and HbA1c), we conducted genome-wide association analyses (GWAS) in up to 7,178 Chinese subjects from nine provinces in the China Health and Nutrition Survey (CHNS). We examined patterns of population structure within CHNS and found that allele frequencies differed across provinces, consistent with genetic drift and population substructure. We further validated 32 previously described T2D- and glycemic trait-loci, including G6PC2 and SIX3-SIX2 associated with fasting glucose. At G6PC2, we replicated a known fasting glucose-associated variant (rs34177044) and identified a second signal (rs2232326), a low-frequency (4%), probably damaging missense variant (S324P). A variant within the lead fasting glucose-associated signal at SIX3-SIX2 co-localized with pancreatic islet expression quantitative trait loci (eQTL) for SIX3, SIX2, and three noncoding transcripts. To identify variants functionally responsible for the fasting glucose association at SIX3-SIX2, we tested five candidate variants for allelic differences in regulatory function. The rs12712928-C allele, associated with higher fasting glucose and lower transcript expression level, showed lower transcriptional activity in reporter assays and increased binding to GABP compared to the rs12712928-G, suggesting that rs12712928-C contributes to elevated fasting glucose levels by disrupting an islet enhancer, resulting in reduced gene expression. Taken together, these analyses identified multiple loci associated with glycemic traits across China, and suggest a regulatory mechanism at the SIX3-SIX2 fasting glucose GWAS locus.

A Common Type 2 Diabetes Risk Variant Potentiates Activity of an Evolutionarily Conserved Islet Stretch Enhancer and Increases C2CD4A and C2CD4B Expression

Genome-wide association studies (GWASs) and functional genomics approaches implicate enhancer disruption in islet dysfunction and type 2 diabetes (T2D) risk. We applied genetic fine-mapping and functional (epi)genomic approaches to a T2D- and proinsulin-associated 15q22.2 locus to identify a most likely causal variant, determine its direction of effect, and elucidate plausible target genes. Fine-mapping and conditional analyses of proinsulin levels of 8,635 non-diabetic individuals from the METSIM study support a single association signal represented by a cluster of 16 strongly associated (p < 10^-17) variants in high linkage disequilibrium (r² > 0.8) with the GWAS index SNP rs7172432. These variants reside in an evolutionarily and functionally conserved islet and β cell stretch or super enhancer; the most strongly associated variant (rs7163757, p = 3 × 10^-19) overlaps a conserved islet open chromatin site. DNA sequence containing the rs7163757 risk allele displayed 2-fold higher enhancer activity than the non-risk allele in reporter assays (p < 0.01) and was differentially bound by β cell nuclear extract proteins. Transcription factor NFAT specifically potentiated risk-allele enhancer activity and altered patterns of nuclear protein binding to the risk allele in vitro, suggesting that it could be a factor mediating risk-allele effects. Finally, the rs7163757 proinsulin-raising and T2D risk allele (C) was associated with increased expression of C2CD4B, and possibly C2CD4A, both of which were induced by inflammatory cytokines, in human islets. Together, these data suggest that rs7163757 contributes to genetic risk of islet dysfunction and T2D by increasing NFAT-mediated islet enhancer activity and modulating C2CD4B, and possibly C2CD4A, expression in (patho)physiologic states.

Genetic Drivers of Pancreatic Islet Function

The majority of gene loci that have been associated with type 2 diabetes play a role in pancreatic islet function. To evaluate the role of islet gene expression in the etiology of diabetes, we sensitized a genetically diverse mouse population with a Western diet high in fat (45% kcal) and sucrose (34%) and carried out genome-wide association mapping of diabetes-related phenotypes. We quantified mRNA abundance in the islets and identified 18,820 expression QTL. We applied mediation analysis to identify candidate causal driver genes at loci that affect the abundance of numerous transcripts. These include two genes previously associated with monogenic diabetes (PDX1 and HNF4A), as well as three genes with nominal association with diabetes-related traits in humans (FAM83E, IL6ST, and SAT2). We grouped transcripts into gene modules and mapped regulatory loci for modules enriched with transcripts specific for α-cells, and another specific for δ-cells. However, no single module enriched for β-cell-specific transcripts, suggesting heterogeneity of gene expression patterns within the β-cell population. A module enriched in transcripts associated with branched-chain amino acid metabolism was the most strongly correlated with physiological traits that reflect insulin resistance. Although the mice in this study were not overtly diabetic, the analysis of pancreatic islet gene expression under dietary-induced stress enabled us to identify correlated variation in groups of genes that are functionally linked to diabetes-associated physiological traits. Our analysis suggests an expected degree of concordance between diabetes-associated loci in the mouse and those found in human populations, and demonstrates how the mouse can provide evidence to support nominal associations found in human genome-wide association mapping.

Lifestyle genomics and the metabolic syndrome: A review of genetic variants that influence response to diet and exercise interventions

Metabolic syndrome (MetS) comprises a cluster of risk factors that includes central obesity, dyslipidemia, impaired glucose homeostasis and hypertension. Individuals with MetS have elevated risk of type 2 diabetes and cardiovascular disease; thus placing significant burdens on social and healthcare systems. Lifestyle interventions (comprised of diet, exercise or a combination of both) are routinely recommended as the first line of treatment for MetS. Only a proportion of people respond, and it has been assumed that psychological and social aspects primarily account for these differences. However, the etiology of MetS is multifactorial and stems, in part, on a person's genetic make-up. Numerous single nucleotide polymorphisms (SNPs) are associated with the various components of MetS, and several of these SNPs have been shown to modify a person's response to lifestyle interventions. Consequently, genetic variants can influence the extent to which a person responds to changes in diet and/or exercise. The goal of this review is to highlight SNPs reported to influence the magnitude of change in body weight, dyslipidemia, glucose homeostasis and blood pressure during lifestyle interventions aimed at improving MetS components. Knowledge regarding these genetic variants and their ability to modulate a person's response will provide additional context for improving the effectiveness of personalized lifestyle interventions that aim to reduce the risks associated with MetS.

The type 2 diabetes-associated HMG20A gene is mandatory for islet beta cell functional maturity

HMG20A (also known as iBRAF) is a chromatin factor involved in neuronal differentiation and maturation. Recently small nucleotide polymorphisms (SNPs) in the HMG20A gene have been linked to type 2 diabetes mellitus (T2DM) yet neither expression nor function of this T2DM candidate gene in islets is known. Herein we demonstrate that HMG20A is expressed in both human and mouse islets and that levels are decreased in islets of T2DM donors as compared to islets from non-diabetic donors. In vitro studies in mouse and human islets demonstrated that glucose transiently increased HMG20A transcript levels, a result also observed in islets of gestating mice. In contrast, HMG20A expression was not altered in islets from diet-induced obese and pre-diabetic mice. The T2DM-associated rs7119 SNP, located in the 3' UTR of the HMG20A transcript reduced the luciferase activity of a reporter construct in the human beta 1.1E7 cell line. Depletion of Hmg20a in the rat INS-1E cell line resulted in decreased expression levels of its neuronal target gene NeuroD whereas Rest and Pax4 were increased. Chromatin immunoprecipitation confirmed the interaction of HMG20A with the Pax4 gene promoter. Expression levels of Mafa, Glucokinase, and Insulin were also inhibited. Furthermore, glucose-induced insulin secretion was blunted in HMG20A-depleted islets. In summary, our data demonstrate that HMG20A expression in islet is essential for metabolism-insulin secretion coupling via the coordinated regulation of key islet-enriched genes such as NeuroD and Mafa and that depletion induces expression of genes such as Pax4 and Rest implicated in beta cell de-differentiation. More importantly we assign to the T2DM-linked rs7119 SNP the functional consequence of reducing HMG20A expression likely translating to impaired beta cell mature function.

Brain insulin resistance in type 2 diabetes and Alzheimer disease: concepts and conundrums

Considerable overlap has been identified in the risk factors, comorbidities and putative pathophysiological mechanisms of Alzheimer disease and related dementias (ADRDs) and type 2 diabetes mellitus (T2DM), two of the most pressing epidemics of our time. Much is known about the biology of each condition, but whether T2DM and ADRDs are parallel phenomena arising from coincidental roots in ageing or synergistic diseases linked by vicious pathophysiological cycles remains unclear. Insulin resistance is a core feature of T2DM and is emerging as a potentially important feature of ADRDs. Here, we review key observations and experimental data on insulin signalling in the brain, highlighting its actions in neurons and glia. In addition, we define the concept of 'brain insulin resistance' and review the growing, although still inconsistent, literature concerning cognitive impairment and neuropathological abnormalities in T2DM, obesity and insulin resistance. Lastly, we review evidence of intrinsic brain insulin resistance in ADRDs. By expanding our understanding of the overlapping mechanisms of these conditions, we hope to accelerate the rational development of preventive, disease-modifying and symptomatic treatments for cognitive dysfunction in T2DM and ADRDs alike.