Transcriptomics in type 2 diabetes: Bridging the gap between genotype and phenotype

A ginsenoside G-Rg3 PEGylated long-circulating liposome for hyperglycemia and insulin resistance therapy in streptozotocin-induced type 2 diabetes mice

Ginsenoside (GS), one of the main active components in ginseng, can enhance insulin sensitivity, improve the function of islet β cells, and reduce cell apoptosis in the treatment of diabetes. However, the drawbacks of high lipid solubility, poor water solubility, and low oral availability in Ginsenoside Rg3 (G-Rg3) seriously limit further application of GS. In this work, a G-Rg3 PEGylated long-circulating liposome (PEG-L-Rg3) is designed and developed to improve symptoms in type 2 diabetic mice. The as-prepared PEG-L-Rg3 with a spherical structure shows a particle size of ∼ 140.5 ± 1.4 nm, the zeta potential of -0.10 ± 0.05 mV, and a high encapsulation rate of 99.8 %. Notably, in vivo experimental results demonstrate that PEG-L-Rg3 exhibits efficient ability to improve body weight and food intake in streptozotocin-induced type 2 diabetic mice. Moreover, PEG-L-Rg3 also enhances fasting insulin (FINS) and insulin sensitivity index (ISI). In addition, the glucose tolerance of mice is significantly improved after the treatment of PEG-L-Rg3, indicating that PEG-L-Rg3 can be a potential drug for the treatment of type 2 diabetes, which provides a new way for the treatment of type 2 diabetes using ginsenosides.

Advanced Mass Spectrometry-Based Biomarker Identification for Metabolomics of Diabetes Mellitus and Its Complications

Over the years, there has been notable progress in understanding the pathogenesis and treatment modalities of diabetes and its complications, including the application of metabolomics in the study of diabetes, capturing attention from researchers worldwide. Advanced mass spectrometry, including gas chromatography-tandem mass spectrometry (GC-MS/MS), liquid chromatography-tandem mass spectrometry (LC-MS/MS), and ultra-performance liquid chromatography coupled to electrospray ionization quadrupole time-of-flight mass spectrometry (UPLC-ESI-Q-TOF-MS), etc., has significantly broadened the spectrum of detectable metabolites, even at lower concentrations. Advanced mass spectrometry has emerged as a powerful tool in diabetes research, particularly in the context of metabolomics. By leveraging the precision and sensitivity of advanced mass spectrometry techniques, researchers have unlocked a wealth of information within the metabolome. This technology has enabled the identification and quantification of potential biomarkers associated with diabetes and its complications, providing new ideas and methods for clinical diagnostics and metabolic studies. Moreover, it offers a less invasive, or even non-invasive, means of tracking disease progression, evaluating treatment efficacy, and understanding the underlying metabolic alterations in diabetes. This paper summarizes advanced mass spectrometry for the application of metabolomics in diabetes mellitus, gestational diabetes mellitus, diabetic peripheral neuropathy, diabetic retinopathy, diabetic nephropathy, diabetic encephalopathy, diabetic cardiomyopathy, and diabetic foot ulcers and organizes some of the potential biomarkers of the different complications with the aim of providing ideas and methods for subsequent in-depth metabolic research and searching for new ways of treating the disease.

Overview of Transcriptomic Research on Type 2 Diabetes: Challenges and Perspectives

Type 2 diabetes (T2D) is a common chronic disease whose etiology is known to have a strong genetic component. Standard genetic approaches, although allowing for the detection of a number of gene variants associated with the disease as well as differentially expressed genes, cannot fully explain the hereditary factor in T2D. The explosive growth in the genomic sequencing technologies over the last decades provided an exceptional impetus for transcriptomic studies and new approaches to gene expression measurement, such as RNA-sequencing (RNA-seq) and single-cell technologies. The transcriptomic analysis has the potential to find new biomarkers to identify risk groups for developing T2D and its microvascular and macrovascular complications, which will significantly affect the strategies for early diagnosis, treatment, and preventing the development of complications. In this article, we focused on transcriptomic studies conducted using expression arrays, RNA-seq, and single-cell sequencing to highlight recent findings related to T2D and challenges associated with transcriptome experiments.

AGEomics Biomarkers and Machine Learning-Realizing the Potential of Protein Glycation in Clinical Diagnostics

Protein damage by glycation, oxidation and nitration is a continuous process in the physiological system caused by reactive metabolites associated with dicarbonyl stress, oxidative stress and nitrative stress, respectively. The term AGEomics is defined as multiplexed quantitation of spontaneous modification of proteins damage and other usually low-level modifications associated with a change of structure and function—for example, citrullination and transglutamination. The method of quantitation is stable isotopic dilution analysis liquid chromatography—tandem mass spectrometry (LC-MS/MS). This provides robust quantitation of normal and damaged or modified amino acids concurrently. AGEomics biomarkers have been used in diagnostic algorithms using machine learning methods. In this review, I describe the utility of AGEomics biomarkers and provide evidence why these are close to the phenotype of a condition or disease compared to other metabolites and metabolomic approaches and how to train and test algorithms for clinical diagnostic and screening applications with high accuracy, sensitivity and specificity using machine learning approaches.

A human-based multi-gene signature enables quantitative drug repurposing for metabolic disease

Insulin resistance (IR) contributes to the pathophysiology of diabetes, dementia, viral infection, and cardiovascular disease. Drug repurposing (DR) may identify treatments for IR; however, barriers include uncertainty whether in vitro transcriptomic assays yield quantitative pharmacological data, or how to optimise assay design to best reflect in vivo human disease. We developed a clinical-based human tissue IR signature by combining lifestyle-mediated treatment responses (>500 human adipose and muscle biopsies) with biomarkers of disease status (fasting IR from >1200 biopsies). The assay identified a chemically diverse set of >130 positively acting compounds, highly enriched in true positives, that targeted 73 proteins regulating IR pathways. Our multi-gene RNA assay score reflected the quantitative pharmacological properties of a set of epidermal growth factor receptor-related tyrosine kinase inhibitors, providing insight into drug target specificity; an observation supported by deep learning-based genome-wide predicted pharmacology. Several drugs identified are suitable for evaluation in patients, particularly those with either acute or severe chronic IR.

OUP accepted manuscript

Type 2 diabetes is a complex, systemic disease affected by both genetic and environmental factors. Previous research has identified genetic variants associated with type 2 diabetes risk; however, gene regulatory changes underlying progression to metabolic dysfunction are still largely unknown. We investigated RNA expression changes that occur during diabetes progression using a two-stage approach. In our discovery stage, we compared changes in gene expression using two longitudinally collected blood samples from subjects whose fasting blood glucose transitioned to a level consistent with type 2 diabetes diagnosis between the time points against those who did not with a novel analytical network approach. Our network methodology identified 17 networks, one of which was significantly associated with transition status. This 822-gene network harbors many genes novel to the type 2 diabetes literature but is also significantly enriched for genes previously associated with type 2 diabetes. In the validation stage, we queried associations of genetically determined expression with diabetes-related traits in a large biobank with linked electronic health records. We observed a significant enrichment of genes in our identified network whose genetically determined expression is associated with type 2 diabetes and other metabolic traits and validated 31 genes that are not near previously reported type 2 diabetes loci. Finally, we provide additional functional support, which suggests that the genes in this network are regulated by enhancers that operate in human pancreatic islet cells. We present an innovative and systematic approach that identified and validated key gene expression changes associated with type 2 diabetes transition status and demonstrated their translational relevance in a large clinical resource.

Multi-Omics Comparison of the Spontaneous Diabetes Mellitus and Diet-Induced Prediabetic Macaque Models

The prevalence of diabetes mellitus has been increasing for decades worldwide. To develop safe and potent therapeutics, animal models contribute a lot to the studies of the mechanisms underlying its pathogenesis. Dietary induction using is a well-accepted protocol in generating insulin resistance and diabetes models. In the present study, we reported the multi-omics profiling of the liver and sera from both peripheral blood and hepatic portal vein blood from Macaca fascicularis that spontaneously developed Type-2 diabetes mellitus with a chow diet (sDM). The other two groups of the monkeys fed with chow diet and high-fat high-sugar (HFHS) diet, respectively, were included for comparison. Analyses of various omics datasets revealed the alterations of high consistency. Between the sDM and HFHS monkeys, both the similar and unique alterations in the lipid metabolism have been demonstrated from metabolomic, transcriptomic, and proteomic data repeatedly. The comparison of the proteome and transcriptome confirmed the involvement of fatty acid binding protein 4 (FABP4) in the diet-induced pathogenesis of diabetes in macaques. Furthermore, the commonly changed genes between spontaneous diabetes and HFHS diet-induced prediabetes suggested that the alterations in the intra- and extracellular structural proteins and cell migration in the liver might mediate the HFHS diet induction of diabetes mellitus.

Human type 2 diabetes mellitus-associated transcriptional disturbances in a high-sugar diet long-term exposed Drosophila melanogaster

Type 2 Diabetes mellitus (T2DM) is a multifactorial and polygenic disorder with the molecular bases still idiopathic. Experimental analyses and tests are quite limited upon human samples due to the access, variability of patient's conditions, and the size and complexity of the genome. Therefore, high-sugar diet exposure is commonly used for modeling T2DM in non-human animals, which includes invertebrate organisms like the fruit fly Drosophila melanogaster. Interestingly, high-sugar diet (HSD) induces delayed time for pupation and reduced viability in fruit fly larvae hatched from a 30% sucrose-containing medium (HSD-30%). Here we carried out an mRNA-deep sequencing study to identify differentially transcribed genes in adult fruit fly hatched and reared from an HSD-30%. Seven days after hatching, flies reared on control and HSD-30% were used to glucose and triglyceride level measurements and RNA extraction for sequencing. Remarkably, glucose levels were about 2-fold higher than the control group in fruit flies exposed to HSD-30%, whereas triglycerides levels increased 1.7-fold. After RNA-sequencing, we found that 13.5% of the genes were differentially transcribed in the dyslipidemic and hyperglycaemic insects. HSD-30% up-regulated genes involved in ribosomal biogenesis (e.g. dTOR, ERK and dS6K) and down-regulated genes involved in energetic process (e.g. Pfk, Gapdh1, and Pyk from pyruvate metabolism; kdn, Idh and Mdh2 from the citric acid cycle; ATPsynC and ATPsynẞ from ATP synthesis) and insect development. We found a remarkable down-regulation for Actin (Act88F) that likely impairs muscle development. Moreover, HSD-30% up-regulated both the insulin-like peptides 7 and 8 and down-regulated the insulin receptor substrate p53, isoform A and insulin-like peptide 6 genes, whose functional products are insulin signaling markers. All these features pointed together to a tightly correlation of the T2DM-like phenotype modeled by the D. melanogaster and an intricate array of phenomena, which includes energetic processes, muscle development, and ribosomal synthesis as that observed for the human pathology.

Protein glycation - biomarkers of metabolic dysfunction and early-stage decline in health in the era of precision medicine

Protein glycation provides a biomarker in widespread clinical use, glycated hemoglobin HbA1c (A1C). It is a biomarker for diagnosis of diabetes and prediabetes and of medium-term glycemic control in patients with established diabetes. A1C is an early-stage glycation adduct of hemoglobin with glucose; a fructosamine derivative. Glucose is an amino group-directed glycating agent, modifying N-terminal and lysine sidechain amino groups. A similar fructosamine derivative of serum albumin, glycated albumin (GA), finds use as a biomarker of glycemic control, particularly where there is interference in use of A1C. Later stage adducts, advanced glycation endproducts (AGEs), are formed by the degradation of fructosamines and by the reaction of reactive dicarbonyl metabolites, such as methylglyoxal. Dicarbonyls are arginine-directed glycating agents forming mainly hydroimidazolone AGEs. Glucosepane and pentosidine, an intense fluorophore, are AGE covalent crosslinks. Cellular proteolysis of glycated proteins forms glycated amino acids, which are released into plasma and excreted in urine. Development of diagnostic algorithms by artificial intelligence machine learning is enhancing the applications of glycation biomarkers. Investigational glycation biomarkers are in development for: (i) healthy aging; (ii) risk prediction of vascular complications of diabetes; (iii) diagnosis of autism; and (iv) diagnosis and classification of early-stage arthritis. Protein glycation biomarkers are influenced by heritability, aging, decline in metabolic, vascular, renal and skeletal health, and other factors. They are applicable to populations of differing ethnicities, bridging the gap between genotype and phenotype. They are thereby likely to find continued and expanding clinical use, including in the current era of developing precision medicine, reporting on multiple pathogenic processes and supporting a precision medicine approach.

Further evidence supporting a potential role for ADH1B in obesity

Insulin is an essential hormone that regulates glucose homeostasis and metabolism. Insulin resistance (IR) arises when tissues fail to respond to insulin, and it leads to serious health problems including Type 2 Diabetes (T2D). Obesity is a major contributor to the development of IR and T2D. We previously showed that gene expression of alcohol dehydrogenase 1B (ADH1B) was inversely correlated with obesity and IR in subcutaneous adipose tissue of Mexican Americans. In the current study, a meta-analysis of the relationship between ADH1B expression and BMI in Mexican Americans, African Americans, Europeans, and Pima Indians verified that BMI was increased with decreased ADH1B expression. Using established human subcutaneous pre-adipocyte cell lines derived from lean (BMI < 30 kg m-2) or obese (BMI ≥ 30 kg m-2) donors, we found that ADH1B protein expression increased substantially during differentiation, and overexpression of ADH1B inhibited fatty acid binding protein expression. Mature adipocytes from lean donors expressed ADH1B at higher levels than obese donors. Insulin further induced ADH1B protein expression as well as enzyme activity. Knockdown of ADH1B expression decreased insulin-stimulated glucose uptake. Our findings suggest that ADH1B is involved in the proper development and metabolic activity of adipose tissues and this function is suppressed by obesity.

Cancer Signaling Transcriptome Is Upregulated in Type 2 Diabetes Mellitus

We aimed to explore the differences in the whole transcriptome of peripheral blood mononuclear cells between elderly individuals with and without type 2 diabetes (T2D). We conducted a microarray-based transcriptome analysis of 19 individuals with T2D and 15 without. Differentially expressed genes according to linear models were submitted to the Ingenuity Pathway Analysis system to conduct a functional enrichment analysis. We established that diseases, biological functions, and canonical signaling pathways were significantly associated with T2D patients when their logarithms of Benjamini–Hochberg-adjusted p-value were >1.30 and their absolute z-scores were >2.0 (≥2.0 meant “upregulation” and ≤ −2.0 “downregulation”). Cancer signaling pathways were the most upregulated ones in T2D (z-score = 2.63, −log(p-value) = 32.3; 88.5% (n = 906) of the total differentially expressed genes located in these pathways). In particular, integrin (z-score = 2.52, −log(p-value) = 2.03) and paxillin (z-score = 2.33, −log(p-value) = 1.46) signaling pathways were predicted to be upregulated, whereas the Rho guanosine diphosphate (Rho-GDP) dissociation inhibitor signaling pathway was predicted to be downregulated in T2D individuals (z-score = −2.14, −log(p-value) = 2.41). Our results suggest that, at transcriptional expression level, elderly individuals with T2D present an increased activation of signaling pathways related to neoplastic processes, T-cell activation and migration, and inflammation.

The expression profile and role of non-coding RNAs in obesity

Latest years have experienced a dramatic upsurge in the knowledge about the function of non-coding transcripts in the determination of diverse human phenotypes including obesity. Several miRNAs and lncRNAs participate in the regulation of metabolic pathways leading to obesity. Several lncRNAs such as Mist, lincIRS2, lncRNA-p5549, H19, GAS5 and SNHG9 have been shown to be down-regulated in adipose tissues or other biological samples in the obese human or animal subjects. On the other hand, Meg3, Plnc1, Blnc1, AC092834.1, TINCR and PVT1 are among up-regulated lncRNAs in the obese subjects. Tens of miRNAs have differential expression between obese and non-obese subjects or between mature adipocytes and pre-adipocytes. Understanding the molecular mechanism of involvement of non-coding RNAs in the pathobiology of obesity would simplify design of therapeutic choices for protecting against obesity and its related comorbidities. We explain the available literature on the function of these transcripts in the pathobiology of obesity.

Comparative effectiveness of bariatric surgeries in patients with obesity and type 2 diabetes mellitus: A network meta-analysis of randomized controlled trials

A network meta-analysis of randomized controlled trials (RCTs) was performed to determine the hierarchies of different bariatric surgeries in patients with obesity and type 2 diabetes mellitus (T2DM), in terms of diabetes remission and cardiometabolic outcomes. Seventeen RCTs and six bariatric surgeries, including single anastomosis (mini) gastric bypass (mini-GBP), biliopancreatic diversion without duodenal switch (BPD), laparoscopic-adjustable gastric banding (LAGB), laparoscopic sleeve gastrectomy (LSG), Roux-en-Y gastric bypass (RYGBP), greater curvature plication (GCP) and nonsurgical treatments (NST) were included. Mini-GBP, BPD, LSG, RYGBP and LAGB (from best to worst), as compared with NST, were all significantly associated with the remission of T2DM. For the follow-up period > 3 years, BPD, mini-GBP, RYGBP and LSG (from best to worst) were significantly superior to NST in achieving the remission of T2DM. For secondary outcomes, the overall ranking for bariatric surgeries was RYGBP > BPD > LSG > LAGB after comprehensively weighting glucose, weight, systolic and diastolic pressure, total cholesterol, triglycerides, high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C). Mini-GBP has the greatest probability of achieving diabetes remission in adults with obesity and T2DM, yet BPD was the most effective in long-term diabetes remission. RYGBP appears to be the most favourable alternative treatment to manage patients with cardiometabolic conditions.

Multi-dimensional Transcriptional Remodeling by Physiological Insulin In Vivo

Regulation of gene expression is an important aspect of insulin action but in vivo is intertwined with changing levels of glucose and counter-regulatory hormones. Here we demonstrate that under euglycemic clamp conditions, physiological levels of insulin regulate interrelated networks of more than 1,000 transcripts in muscle and liver. These include expected pathways related to glucose and lipid utilization, mitochondrial function, and autophagy, as well as unexpected pathways, such as chromatin remodeling, mRNA splicing, and Notch signaling. These acutely regulated pathways extend beyond those dysregulated in mice with chronic insulin deficiency or insulin resistance and involve a broad network of transcription factors. More than 150 non-coding RNAs were regulated by insulin, many of which also responded to fasting and refeeding. Pathway analysis and RNAi knockdown revealed a role for lncRNA Gm15441 in regulating fatty acid oxidation in hepatocytes. Altogether, these changes in coding and non-coding RNAs provide an integrated transcriptional network underlying the complexity of insulin action.

The Construction and Analysis of the Aberrant lncRNA-miRNA-mRNA Network in Adipose Tissue from Type 2 Diabetes Individuals with Obesity

BACKGROUND

The prevalence of obesity and type 2 diabetes mellitus (T2DM) has become the most serious global public health issue. In recent years, there has been increasing attention to the role of long noncoding RNAs (lncRNAs) in the occurrence and development of obesity and T2DM. The aim of this work was to find new lncRNAs as potential predictive biomarkers or therapeutic targets for obesity and T2DM.

METHODS

In this study, we identified significant differentially expressed mRNAs (DEmRNAs) and differentially expressed lncRNAs (DElncRNAs) between adipose tissue of individuals with obesity and T2DM and normal adipose tissue (absolute log₂FC ≥ 1 and FDR < 0.05). Then, the lncRNA-miRNA interactions predicted by miRcode were further screened with a threshold of MIC > 0.2. Simultaneously, the mRNA-miRNA interactions were explored by miRWalk 2.0. Finally, a ceRNA network consisting of lncRNAs, miRNAs, and mRNAs was established by integrating lncRNA-miRNA interactions and mRNA-miRNA interactions.

RESULTS

Upon comparing adipose tissue from individuals with obesity and T2DM and normal adipose tissues, 364 significant DEmRNAs, including 140 upregulated and 224 downregulated mRNAs, were identified in GSE104674; in addition, 231 significant DEmRNAs, including 146 upregulated and 85 downregulated mRNAs, were identified in GSE133099. GO and KEGG analyses have shown that downregulated DEmRNAs in GSE104674 and GSE133099 were associated with obesity- and T2DM-related biological pathways, such as lipid metabolism, AMPK signaling, and insulin resistance. Furthermore, 28 significant DElncRNAs, including 14 upregulated and 14 downregulated lncRNAs, were found. Based on the predicted lncRNA-miRNA and mRNA-miRNA relationships, we constructed a competitive endogenous RNA (ceRNA) network, including five lncRNAs, ten miRNAs, and 15 mRNAs. KEGG-GSEA analysis revealed that four lncRNAs (FLG-AS1, SNAI3-AS1, AC008147.0, and LINC02015) in the ceRNA network were related to the biological pathways of metabolic diseases.

CONCLUSIONS

Through ceRNA network analysis, our study identified four new lncRNAs that may be used as potential biomarkers and therapeutic targets of obesity and T2DM, thus laying a foundation for future clinical studies.

Therapeutic Silencing of Centromere Protein X Ameliorates Hyperglycemia in Zebrafish and Mouse Models of Type 2 Diabetes Mellitus

Type 2 diabetes mellitus (T2DM) is characterized by persistent hyperglycemia and is influenced by genetic and environmental factors. Optimum T2DM management involves early diagnosis and effective glucose-lowering therapies. Further research is warranted to improve our understanding of T2DM pathophysiology and reveal potential roles of genetic predisposition. We have previously developed an obesity-induced diabetic zebrafish model that shares common pathological pathways with humans and may be used to identify putative pharmacological targets of diabetes. Additionally, we have previously identified several candidate genes with altered expression in T2DM zebrafish. Here, we performed a small-scale zebrafish screening for these genes and discovered a new therapeutic target, centromere protein X (CENPX), which was further validated in a T2DM mouse model. In zebrafish, cenpx knockdown by morpholino or knockout by CRISPR/Cas9 system ameliorated overfeeding-induced hyperglycemia and upregulated insulin level. In T2DM mice, small-interfering RNA-mediated Cenpx knockdown decreased hyperglycemia and upregulated insulin synthesis in the pancreas. Gene expression analysis revealed insulin, mechanistic target of rapamycin, leptin, and insulin-like growth factor 1 pathway activation following Cenpx silencing in pancreas tissues. Thus, CENPX inhibition exerted antidiabetic effects via increased insulin expression and related pathways. Therefore, T2DM zebrafish may serve as a powerful tool in the discovery of new therapeutic gene targets.

Recent advances and perspectives in next generation sequencing application to the genetic research of type 2 diabetes

Type 2 diabetes (T2D) mellitus is a common complex disease that currently affects more than 400 million people worldwide and has become a global health problem. High-throughput sequencing technologies such as whole-genome and whole-exome sequencing approaches have provided numerous new insights into the molecular bases of T2D. Recent advances in the application of sequencing technologies to T2D research include, but are not limited to: (1) Fine mapping of causal rare and common genetic variants; (2) Identification of confident gene-level associations; (3) Identification of novel candidate genes by specific scoring approaches; (4) Interrogation of disease-relevant genes and pathways by transcriptional profiling and epigenome mapping techniques; and (5) Investigation of microbial community alterations in patients with T2D. In this work we review these advances in application of next-generation sequencing methods for elucidation of T2D pathogenesis, as well as progress and challenges in implementation of this new knowledge about T2D genetics in diagnosis, prevention, and treatment of the disease.

Progress in the discovery of naturally occurring anti-diabetic drugs and in the identification of their molecular targets

Diabetes mellitus (DM), a chronic metabolic disease, severely affects patients' life and intensively increases risks of developing other diseases. It is estimated that 0.4 billion individuals worldwide are subjected to diabetes, especially type 2 diabetes mellitus. At present, although various synthetic drugs for diabetes such as Alogliptin and Rosiglitazone, etc. have been used to manage diabetes, some of them showed severe side effects. Given that the pathogenesis of type 2 diabetes mellitus, natural occurring drugs are beneficial alternatives for diabetes therapy with low adverse effects or toxicity. Recently, more and more plant-derived extracts or compounds were evaluated to have anti-diabetic activities. Their anti-diabetic mechanisms involve certain key targets like α-glucosidase, α-amylase, DPP-4, PPAR γ, PTP1B, and GLUT4, etc. Here, we summarize the newly found anti-diabetic (type 2 diabetes mellitus) natural compounds and extracts from 2011-2017, and give the identification of their molecular targets. This review could provide references for the research of natural agents curing type 2 diabetes mellitus (T2DM).

Overview of genomics and post-genomics research on type 2 diabetes mellitus: Future perspectives and a framework for further studies

In this review, we briefly outlined salient features of pathophysiology and results of the genetic association studies hitherto conducted on type 2 diabetes. Primarily focusing on the current status of genomic research, we briefly discussed the limited progress made during the post-genomic era and tried to identify the limitations of the post-genomic research strategies. We suggested reanalysis of the existing genomic data through advanced statistical and computational methods and recommended integrated genomics-metabolomics approaches for future studies to facilitate understanding of the gene-environment interactions in the manifestation of the disease. We also propose a framework for research that may be apt for determining the effects of urbanization and changing lifestyles in the manifestation of complex genetic disorders like type 2 diabetes in the Indian populations and offset the confounding effects of both genetic and environmental factors in the natural way.

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.

Shared Genetic Control of Brain Activity During Sleep and Insulin Secretion: A Laboratory-Based Family Study

Over the past 20 years, a large body of experimental and epidemiologic evidence has linked sleep duration and quality to glucose homeostasis, although the mechanistic pathways remain unclear. The aim of the current study was to determine whether genetic variation influencing both sleep and glucose regulation could underlie their functional relationship. We hypothesized that the genetic regulation of electroencephalographic (EEG) activity during non-rapid eye movement sleep, a highly heritable trait with fingerprint reproducibility, is correlated with the genetic control of metabolic traits including insulin sensitivity and β-cell function. We tested our hypotheses through univariate and bivariate heritability analyses in a three-generation pedigree with in-depth phenotyping of both sleep EEG and metabolic traits in 48 family members. Our analyses accounted for age, sex, adiposity, and the use of psychoactive medications. In univariate analyses, we found significant heritability for measures of fasting insulin sensitivity and β-cell function, for time spent in slow-wave sleep, and for EEG spectral power in the delta, theta, and sigma ranges. Bivariate heritability analyses provided the first evidence for a shared genetic control of brain activity during deep sleep and fasting insulin secretion rate.

Induced Pluripotent Stem Cells in Disease Modeling and Gene Identification

Experimental modeling of human inherited disorders provides insight into the cellular and molecular mechanisms involved, and the underlying genetic component influencing, the disease phenotype. The breakthrough development of induced pluripotent stem cell (iPSC) technology represents a quantum leap in experimental modeling of human diseases, providing investigators with a self-renewing and, thus, unlimited source of pluripotent cells for targeted differentiation. In principle, the entire range of cell types found in the human body can be interrogated using an iPSC approach. Therefore, iPSC technology, and the increasingly refined abilities to differentiate iPSCs into disease-relevant target cells, has far-reaching implications for understanding disease pathophysiology, identifying disease-causing genes, and developing more precise therapeutics, including advances in regenerative medicine. In this chapter, we discuss the technological perspectives and recent developments in the application of patient-derived iPSC lines for human disease modeling and disease gene identification.

Type 2 diabetes

415 million people live with diabetes worldwide, and an estimated 193 million people have undiagnosed diabetes. Type 2 diabetes accounts for more than 90% of patients with diabetes and leads to microvascular and macrovascular complications that cause profound psychological and physical distress to both patients and carers and put a huge burden on health-care systems. Despite increasing knowledge regarding risk factors for type 2 diabetes and evidence for successful prevention programmes, the incidence and prevalence of the disease continues to rise globally. Early detection through screening programmes and the availability of safe and effective therapies reduces morbidity and mortality by preventing or delaying complications. Increased understanding of specific diabetes phenotypes and genotypes might result in more specific and tailored management of patients with type 2 diabetes, as has been shown in patients with maturity onset diabetes of the young. In this Seminar, we describe recent developments in the diagnosis and management of type 2 diabetes, existing controversies, and future directions of care.