Microarray profiling of skeletal muscle tissues from equally obese, non-diabetic insulin-sensitive and insulin-resistant Pima Indians

The Arylamine N-Acetyltransferases as Therapeutic Targets in Metabolic Diseases Associated with Mitochondrial Dysfunction

In humans, there are two arylamine N-acetyltransferase genes that encode functional enzymes (NAT1 and NAT2) as well as one pseudogene, all of which are located together on chromosome 8. Although they were first identified by their role in the acetylation of drugs and other xenobiotics, recent studies have shown strong associations for both enzymes in a variety of diseases, including cancer, cardiovascular disease, and diabetes. There is growing evidence that this association may be causal. Consistently, NAT1 and NAT2 are shown to be required for healthy mitochondria. This review discusses the current literature on the role of both NAT1 and NAT2 in mitochondrial bioenergetics. It will attempt to relate our understanding of the evolution of the two genes with biologic function and then present evidence that several major metabolic diseases are influenced by NAT1 and NAT2. Finally, it will discuss current and future approaches to inhibit or enhance NAT1 and NAT2 activity/expression using small-molecule drugs. SIGNIFICANCE STATEMENT: The arylamine N-acetyltransferases (NATs) NAT1 and NAT2 share common features in their associations with mitochondrial bioenergetics. This review discusses mitochondrial function as it relates to health and disease, and the importance of NAT in mitochondrial function and dysfunction. It also compares NAT1 and NAT2 to highlight their functional similarities and differences. Both NAT1 and NAT2 are potential drug targets for diseases where mitochondrial dysfunction is a hallmark of onset and progression.

In-depth urinary and exosome proteome profiling analysis identifies novel biomarkers for diabetic kidney disease

Diabetic kidney disease (DKD) is a major microvascular complication of type 2 diabetes mellitus (T2DM). Monitoring the early diagnostic period and disease progression plays a crucial role in treating DKD. In this study, to comprehensively elucidate the molecular characteristics of urinary proteins and urinary exosome proteins in type 2 DKD, we performed large-scale urinary proteomics (n=144) and urinary exosome proteomics (n=44) analyses on T2DM patients with albuminuria in varying degrees. The dynamics analysis of the urinary and exosome proteomes in our study provides a valuable resource for discovering potential urinary biomarkers in patients with DKD. A series of potential biomarkers, such as SERPINA1 and transferrin (TF), were detected and validated to be used for DKD diagnosis or disease monitoring. The results of our study comprehensively elucidated the changes in the urinary proteome and revealed several potential biomarkers reflecting the progression of DKD, which provide a reference for DKD biomarker screening.

Integration of nutrigenomics, melatonin, serotonin and inflammatory cytokines in the pathophysiology of pregnancy-specific urinary incontinence in women with gestational diabetes mellitus

Gestational diabetes mellitus is an important public health problem and has been associated with the development of pregnancy-specific urinary incontinence. The interaction is related to hyperglycemia, and inflammatory and hormonal patterns, which favor functional alterations in different organs and systems. Several genes associated with human diseases have been identified and partially characterized. Most of these genes are known to cause monogenic diseases. However, about 3 % of diseases do not fit the monogenic theory due to the complex interactions between multiple genes and environmental factors, as in chronic metabolic diseases such as diabetes. The nutritional, immunological, and hormonal patterns associated with changes in maternal metabolism may influence and contribute to greater susceptibility to urinary tract disorders. However, early systematic reviews have not yielded consistent findings for these associations. This literature review summarizes important new findings from integrating nutrigenomics, hormones, and cytokines in women with Gestational diabetes mellitus and pregnancy-specific urinary incontinence. Changes in maternal metabolism due to hyperglycemia can generate an inflammatory environment with increased inflammatory cytokines. This environment modulated by inflammation can alter tryptophan uptake through food and thus influence the production of serotonin and melatonin. As these hormones seem to have protective effects against smooth muscle dysfunction and to restore the impaired contractility of the detrusor muscle, it is assumed that these changes may favor the onset of urinary incontinence specific to pregnancy.

DNA methylation and expression profiles of placenta and umbilical cord blood reveal the characteristics of gestational diabetes mellitus patients and offspring

BACKGROUND

Gestational diabetes mellitus (GDM) is a common pregnancy-specific disease and is growing at an alarming rate worldwide, which can negatively affect the health of pregnant women and fetuses. However, most studies are limited to one tissue, placenta or umbilical cord blood, usually with one omics assay. It is thus difficult to systematically reveal the molecular mechanism of GDM and the key influencing factors on pregnant women and offspring.

RESULTS

We recruited a group of 21 pregnant women with GDM and 20 controls without GDM. For each pregnant woman, reduced representation bisulfite sequencing and RNA-seq were performed using the placenta and paired neonatal umbilical cord blood specimens. Differentially methylated regions (DMRs) and differentially expressed genes (DEGs) were identified with body mass index as a covariate. Through the comparison of GDM and control samples, 2779 and 141 DMRs, 1442 and 488 DEGs were identified from placenta and umbilical cord blood, respectively. Functional enrichment analysis showed that the placenta methylation and expression profiles of GDM women mirrored the molecular characteristics of "type II diabetes" and "insulin resistance." Methylation-altered genes in umbilical cord blood were associated with pathways "type II diabetes" and "cholesterol metabolism." Remarkably, both DMRs and DEGs illustrated significant overlaps among placenta and umbilical cord blood samples. The overlapping DMRs were associated with "cholesterol metabolism." The top-ranking pathways enriched in the shared DEGs include "growth hormone synthesis, secretion and action" and "type II diabetes mellitus."

CONCLUSIONS

Our research demonstrated the epigenetic and transcriptomic alternations of GDM women and offspring. Our findings emphasized the importance of epigenetic modifications in the communication between pregnant women with GDM and offspring, and provided a reference for the prevention, control, treatment, and intervention of perinatal deleterious events of GDM and neonatal complications.

Diagnostic significance of serum FGD5-AS1 and its predictive value for the development of cardiovascular diseases in patients with type 2 diabetes

BACKGROUND

As a result of the continuous rise in the incidence of type 2 diabetes mellitus (T2DM), related cardiovascular diseases (CVDs) have been a main healthy burden worldwide. This study aimed to investigate the potential role of FGD5-AS1 as a biomarker for the diagnosis of T2DM and predicting cardiovascular complications in T2DM.

METHODS

Three hundred subjects were recruited in this study, including 100 T2DM patients without CVDs, 100 T2DM patients with CVDs as well as 100 healthy subjects. Plasma FGD5-AS1 level was quantified using RT-qPCR assay. The correlation of FGD5-AS1 level with other key variables was assessed using Pearson correlation analysis. ROC curve analysis was performed to evaluate the diagnostic value of FGD5-AS1 for T2DM and related CVDs. The effect of FGD5-AS1 on AC16 and HA-VSMCs was determined.

RESULTS

FGD5-AS1 level showed a stepwise decrease in individuals with T2DM and CVDs compared to healthy persons. FGD5-AS1 was associated with BMI, systolic blood pressure, diastolic blood pressure, fasting glucose, 2-h postprandial blood glucose, HbA1c, triglycerides, usCRP, and HDL-cholesterol. The ROC analysis indicated FGD5-AS1 had a significant overall predictive ability to diagnose T2DM, T2DM with CVDs, and the combination of both. FGD5-AS1 increases the growth but alleviates apoptosis and fibrosis of high glucose-induced AC16 cells. FGD5-AS1 attenuate the growth and calcification but induced apoptosis of high glucose-treated HA-VSMC cells.

CONCLUSIONS

These results suggest that FGD5-AS1 are associated with T2DM and measuring FGD5-AS1 could potentially contribute to T2DM screening and prediction for risk of cardiovascular complication.

Differences in protein expression, at the basal state and at 2 h of insulin infusion, in muscle biopsies from healthy Arab men with high or low insulin sensitivity measured by hyperinsulinemic euglycemic clamp

BACKGROUND

Skeletal muscle is the main site for insulin-dependent glucose disposal. The hyperinsulinemic euglycemic clamp (HIEC) is the gold standard for the assessment of insulin sensitivity (IS). We have previously shown that insulin sensitivity, measured by HIEC, varied widely among a group of 60 young healthy men with normoglycemia. The aim of this study was to correlate the proteomic profile of skeletal muscles to insulin sensitivity.

METHODS

Muscle biopsies from 16 subjects having the highest (M ≥ 13; n = 8, HIS) and lowest (M ¾ 6, n = 8, LIS) IS were obtained at baseline and during insulin infusion after stabilization of the blood glucose level and glucose infusion rate at the end of the HIEC. The samples were processed using a quantitative proteomic analysis approach.

RESULTS

At baseline, 924 proteins were identified in the HIS and LIS groups. Among the 924 proteins detected in both groups, three were suppressed and three were increased significantly in the LIS subjects compared with the HIS subjects. Following insulin infusion, 835 proteins were detected in both groups. Among the 835 proteins, two showed differential responsiveness to insulin; ATP5F1 protein was decreased, and MYLK2 was higher in the LIS group compared with that in the HIS group. Our data suggest that alteration in mitochondrial proteins and an increased number of proteins involved in fast-twitch fiber correlate to insulin sensitivity in healthy young Arab men.

CONCLUSIONS

These results suggest a change in a small number of differentially expressed proteins. A possible reason for this small change could be our study cohorts representing a homogeneous and healthy population. Additionally, we show differences in protein levels from skeletal muscle in low and high insulin sensitivity groups. Therefore, these differences may represent early events for the development of insulin resistance, pre-diabetes, and type 2 diabetes.

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

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

Potentiation of incretin hormones and modulation of metabolic enzymes as possible mechanisms behind the insulin sensitizing effects of cabbage-metformin treatment

In our study, we treated high fructose diet-induced insulin resistance in rats with any of metformin, cabbage (80%w/w) or combined metformin and cabbage (MetCabb), and observed the activities of glycolysis and gluconeogenesis regulatory enzymes, incretin hormones and other hormones affecting glucose homeostasis. Comparisons were made with normoglycemic noninsulin resistance rats (control) and insulin-resistant untreated rats (INres). Baseline analysis showing elevated fasting blood sugar (>250 mg/dl), insulin (>25 µIU/ml) and HOMA-IR (>10) satisfied the criteria for recruitment into the insulin-resistant groups. Treatment lasted for 12 weeks. HOMA-IR values significantly (P < 0.05) decreased from 24.7 to 5.5 and 10.6 respectively with MetCabb treatment. MetCabb normalized HOMA-IR values and mean β-cell responsiveness of the INres. Cabbage and metCabb normalized the leptin levels relative to control. The mean fasting blood sugar, insulin, and c-peptide levels with MetCabb treatment reverted to control levels. We found a strong positive linear correlation between the glucagon levels (r = 0.9145) and increasing HOMA-IR values while both incretin hormones; GLP-1 and GIP negatively regressed (r = -0.8084 and -0.8488). MetCab treatment produced comparable values of GLP-1 and GIP to the control. A strong positive correlation was found between the HOMA-IR values and the PEPCK (r = 0.9065), F-1,6-BPase (r = 0.7951), and G-6-Pase (r = 0.7893). The hexokinase (r = -0.807), PFK (r = -0.9151), and PK (r = -0.7448) levels regressed as HOMA-IR values increased. The glycolytic and gluconeogenic enzymes except PEPCK reverted to control levels with MetCabb treatment. Combination of metformin and cabbage was more effective than individual treatments.

Hepatic Transcriptome Analysis Revealing the Molecular Pathogenesis of Type 2 Diabetes Mellitus in Zucker Diabetic Fatty Rats

Around 9% of the adult population in the world (463 million) suffer from diabetes mellitus. Most of them (~90%) belong to type 2 diabetes mellitus (T2DM), which is a common chronic metabolic disorder, and the number of cases has been reported to increase each year. Zucker diabetic fatty (ZDF) rat provides a successful animal model to study the pathogenesis of T2DM. Although previous hepatic transcriptome studies revealed some novel genes associated with the occurrence and development of T2DM, there still lacks the comprehensive transcriptomic analysis for the liver tissues of ZDF rats. We performed comparative transcriptome analyses between the liver tissues of ZDF rats and healthy ZCL rats and also evaluated several clinical indices. We could identify 214 and 104 differentially expressed genes (DEGs) and lncRNAs in ZDF rats, respectively. Pathway and biofunction analyses showed a synergistic effect between mRNAs and lncRNAs. By comprehensively analyzing transcriptomic data and clinical indices, we detected some typical features of T2DM in ZDF rats, such as upregulated metabolism (significant increased lipid absorption/transport/utilization, gluconeogenesis, and protein hydrolysis), increased inflammation, liver injury and increased endoplasmic reticulum (ER) stress. In addition, of the 214 DEGs, 114 were known and 100 were putative T2DM-related genes, most of which have been associated with substance metabolism (particularly degradation), inflammation, liver injury and ER stress biofunctions. Our study provides an important reference and improves understanding of molecular pathogenesis of obesity-associated T2DM. Our data can also be used to identify potential diagnostic markers and therapeutic targets, which should strengthen the prevention and treatment of T2DM.

Identification of a Prognostic Signature Based on the Expression of Genes Related to the Insulin Pathway in Early Breast Cancer

Introduction

Insulin and the insulin-like growth factor (IGF) family play a key role in breast cancer (BC).

Objective

In this study, we evaluated on a genomic scale the potential prognostic value of insulin signaling in early BC.

Methods

Candidate genes were selected from the published literature and gene expression profiling experiments. Three publicly available BC datasets, containing gene expression data on 502 cases, were used to test the prognostic ability of the score. The gene signature was developed on GSE1456, containing microarray data from 159 patients, split into a training set (102 breast tumors) and a validation set (n = 57). GSE3494 and GSE2990 (350 patients) were used for external validation. Univariate Mann-Whitney test was used to identify genes differentially expressed between relapsed and nonrelapsed patients. Expression of genes significantly correlated with relapse was combined in a linear score. Patients were classified as low or high risk with respect to the median value.

Results

On the training set, 15 genes turned out to be differentially expressed: 8-year disease-free survival (DFS) was 51 and 91% in the high- and low-risk group (p < 0.001), respectively. In the validation set, DFS was 97 and 54% (p = 0.009), respectively. External validation: 8-year DFS was 72 and 61%, respectively, in GSE3494 (p = 0.03) and 74 and 55% in GSE2990 (p = 0.03). By multivariate analyses, the insulin signature was significantly associated with DFS, independently of age, hormone receptor status, nodal status, and grade.

Conclusions

Our findings indicate that the insulin pathway is involved in BC prognosis at a genomic level and provide a window of selectivity for preventive and treatment strategies targeting the insulin/IGF pathway in BC patients.

Gene Set Analysis: Challenges, Opportunities, and Future Research

Gene set analysis methods are widely used to provide insight into high-throughput gene expression data. There are many gene set analysis methods available. These methods rely on various assumptions and have different requirements, strengths and weaknesses. In this paper, we classify gene set analysis methods based on their components, describe the underlying requirements and assumptions for each class, and provide directions for future research in developing and evaluating gene set analysis methods.

Proteomic and Transcriptomic Changes in Hibernating Grizzly Bears Reveal Metabolic and Signaling Pathways that Protect against Muscle Atrophy

Muscle atrophy is a physiological response to disuse and malnutrition, but hibernating bears are largely resistant to this phenomenon. Unlike other mammals, they efficiently reabsorb amino acids from urine, periodically activate muscle contraction, and their adipocytes differentially responds to insulin. The contribution of myocytes to the reduced atrophy remains largely unknown. Here we show how metabolism and atrophy signaling are regulated in skeletal muscle of hibernating grizzly bear. Metabolic modeling of proteomic changes suggests an autonomous increase of non-essential amino acids (NEAA) in muscle and treatment of differentiated myoblasts with NEAA is sufficient to induce hypertrophy. Our comparison of gene expression in hibernation versus muscle atrophy identified several genes differentially regulated during hibernation, including Pdk4 and Serpinf1. Their trophic effects extend to myoblasts from non-hibernating species (including C. elegans), as documented by a knockdown approach. Together, these changes reflect evolutionary favored adaptations that, once translated to the clinics, could help improve atrophy treatment.

CELA2A mutations predispose to early-onset atherosclerosis and metabolic syndrome and affect plasma insulin and platelet activation

Factors that underlie the clustering of metabolic syndrome traits are not fully known. We performed whole exome sequence analysis in kindreds with extreme phenotypes of early-onset atherosclerosis and metabolic syndrome and identified novel loss-of-function mutations in the gene encoding the pancreatic elastase CELA2A. We further show that CELA2A is a circulating enzyme that reduces platelet hyperactivation, triggers both insulin secretion and degradation, and increases insulin sensitivity. CELA2A plasma levels rise postprandially and parallel insulin levels in humans. Loss of these functions by the mutant proteins provides insight into disease mechanisms and suggests that CELA2A could be an attractive therapeutic target.

Exome sequencing identifies loss-of-function CELA2A mutations in families with early-onset atherosclerosis and metabolic syndrome. Functional studies show that CELA2A is a circulating enzyme that reduces platelet activation, triggers insulin secretion and degradation, and increases insulin sensitivity.

Disuse-induced insulin resistance susceptibility coincides with a dysregulated skeletal muscle metabolic transcriptome

Short-term muscle disuse is characterized by skeletal muscle insulin resistance, although this response is divergent across subjects. The mechanisms regulating inactivity-induced insulin resistance between populations that are more or less susceptible to disuse-induced insulin resistance are not known. RNA sequencing was conducted on vastus lateralis muscle biopsies from subjects before and after bed rest (n = 26) to describe the transcriptome of inactivity-induced insulin resistance. Subjects were separated into Low (n = 14) or High (n = 12) Susceptibility Groups based on the magnitude of change in insulin sensitivity after 5 days of bed rest. Both groups became insulin-resistant after bed rest, and there were no differences between groups in nonmetabolic characteristics (body mass, body mass index, fat mass, and lean mass). The High Susceptibility Group had more genes altered >1.5-fold (426 high versus 391 low) and more than twofold (73 high versus 55 low). Twenty-four genes were altered more than twofold in the High Susceptibility Group that did not change in the Low Susceptibility Group. 95 gene changes correlated with the changes in insulin sensitivity; 6 of these genes changed more than twofold in the High Susceptibility Group. Participants in the High Susceptibility Group were uniquely characterized with muscle gene responses described by a decrease in pathways responsible for lipid uptake and oxidation, decreased capacity for triglyceride export (APOB), increased lipogenesis (i.e., PFKFB3, FASN), and increased amino acid export (SLC43A1). These transcriptomic data provide a comprehensive examination of pathways and genes that may be useful biomarkers, or novel targets to offset muscle disuse-induced insulin resistance. NEW & NOTEWORTHY Short-term muscle disuse results in skeletal muscle insulin resistance through mechanisms that are not fully understood. Following a 5-day bed rest intervention, subjects were divided into High and Low Susceptibility Groups to inactivity-induced insulin resistance. This was followed by a genome-wide transcriptional analysis on muscle biopsy samples to gain insight on divergent insulin sensitivity responses. Our primary finding was that the skeletal muscle of subjects who experienced the most inactivity-induced insulin resistance (high susceptibility) was characterized by a decreased preference for lipid oxidation, increased lipogenesis, and increased amino acid export.

Cysteine- and glycine-rich protein 3 regulates glucose homeostasis in skeletal muscle

Skeletal muscle is the major site of postprandial peripheral glucose uptake, but in obesity-induced insulin-resistant states insulin-stimulated glucose disposal is markedly impaired. Despite the importance of skeletal muscle in regulating glucose homeostasis, the specific transcriptional changes associated with insulin-sensitive vs. -resistant states in muscle remain to be fully elucidated. Herein, using an RNA-seq approach we identified 20 genes differentially expressed in an insulin-resistant state in skeletal muscle, including cysteine- and glycine-rich protein 3 ( Csrp3), which was highly expressed in insulin-sensitive conditions but significantly reduced in the insulin-resistant state. CSRP3 has diverse functional roles including transcriptional regulation, signal transduction, and cytoskeletal organization, but its role in glucose homeostasis has yet to be explored. Thus, we investigated the role of CSRP3 in the development of obesity-induced insulin resistance in vivo. High-fat diet-fed CSRP3 knockout (KO) mice developed impaired glucose tolerance and insulin resistance as well as increased inflammation in skeletal muscle compared with wild-type (WT) mice. CSRP3-KO mice had significantly impaired insulin signaling, decreased GLUT4 translocation to the plasma membrane, and enhanced levels of phospho-PKCα in muscle, which all contributed to reduced insulin-stimulated glucose disposal in muscle in HFD-fed KO mice compared with WT mice. CSRP3 is a highly inducible protein and its expression is acutely increased after fasting. After 24h fasting, glucose tolerance was significantly improved in WT mice, but this effect was blunted in CSRP3-KO mice. In summary, we identify a novel role for Csrp3 expression in skeletal muscle in the development of obesity-induced insulin resistance.

Alpha-linolenic acid and linoleic acid differentially regulate the skeletal muscle secretome of obese Zucker rats

Evidence shows that proteins secreted from skeletal muscle influence a broad range of metabolic signaling pathways. We previously reported that essential polyunsaturated fatty acids (PUFA) improved whole-body glucose homeostasis in obese Zucker rats; however, the mechanisms underlying these benefits remain enigmatic. While PUFA and obesity influence skeletal muscle function, their effects on the secretome are unknown. The aim of this work was to determine if improvements in whole-body glucose homeostasis in obese Zucker rats fed diets supplemented with either linoleic acid (LA) or alpha-linolenic acid (ALA) for 12 wk are related to changes in the skeletal muscle secretome. Secreted proteins were identified with a predictive bioinformatic analysis of microarray gene expression from red tibialis anterior skeletal muscle. Approximately 130 genes were differentially expressed (false discovery rate = 0.05) in obese rats compared with lean controls. The expression of 15 genes encoding secreted proteins was differentially regulated in obese controls, obese LA-supplemented, and obese ALA-supplemented rats compared with lean controls. Five secreted proteins ( Col3a1, Col15a1, Pdgfd, Lyz2, and Angptl4) were differentially regulated by LA and ALA. Most notably, ALA supplementation reduced Angptl4 gene expression compared with obese control and obese-LA supplemented rats and reduced circulating ANGPTL4 serum concentrations. ALA also influenced Angptl4 gene expression and ANGPTL4 secretion from differentiated rat L6 myotubes. Altogether, the present data indicate that obesity has a greater global impact on skeletal muscle gene expression than either essential PUFA; however, LA and ALA may exert their metabolic benefits in part by regulating the skeletal muscle secretome.

A comprehensive transcriptome analysis of skeletal muscles in two Polish pig breeds differing in fat and meat quality traits

Pork is the most popular meat in the world. Unfortunately, the selection pressure focused on high meat content led to a reduction in pork quality. The present study used RNA-seq technology to identify metabolic process genes related to pork quality traits and fat deposition. Differentially expressed genes (DEGs) were identified between pigs of Pulawska and Polish Landrace breeds for two the most important muscles (semimembranosus and longissimus dorsi). A total of 71 significant DEGs were reported: 15 for longissimus dorsi and 56 for semimembranosus muscles. The genes overexpressed in Pulawska pigs were involved in lipid metabolism (APOD, LXRA, LIPE, AP2B1, ENSSSCG00000028753 and OAS2) and proteolysis (CST6, CTSD, ISG15 and UCHL1). In Polish Landrace pigs, genes playing a role in biological adhesion (KIT, VCAN, HES1, SFRP2, CDH11, SSX2IP and PCDH17), actin cytoskeletal organisation (FRMD6, LIMK1, KIF23 and CNN1) and calcium ion binding (PVALB, CIB2, PCDH17, VCAN and CDH11) were transcriptionally more active. The present study allows for better understanding of the physiological processes associated with lipid metabolism and muscle fiber organization. This information could be helpful in further research aiming to estimate the genetic markers.

Regulation of insulin resistance and type II diabetes by hepatitis C virus infection: A driver function of circulating miRNAs

Hepatitis C virus (HCV) infection is a serious worldwide healthcare issue. Its association with various liver diseases including hepatocellular carcinoma (HCC) is well studied. However, the study on the relationship between HCV infection and the development of insulin resistance and diabetes is very limited. Current research has already elucidated some underlying mechanisms, especially on the regulation of metabolism and insulin signalling by viral proteins. More studies have emerged recently on the correlation between HCV infection‐derived miRNAs and diabetes and insulin resistance. However, no studies have been carried out to directly address if these miRNAs, especially circulating miRNAs, have causal effects on the development of insulin resistance and diabetes. Here, we proposed a new perspective that circulating miRNAs can perform regulatory functions to modulate gene expression in peripheral tissues leading to insulin resistance and diabetes, rather than just a passive factor associated with these pathological processes. The detailed rationales were elaborated through comprehensive literature review and bioinformatic analyses. miR‐122 was identified to be one of the most potential circulating miRNAs to cause insulin resistance. This result along with the idea about the driver function of circulating miRNAs will promote further investigations that eventually lead to the development of novel strategies to treat HCV infection‐associated extrahepatic comorbidities.

Mitochondrial H+-ATP synthase in human skeletal muscle: contribution to dyslipidaemia and insulin resistance

AIMS/HYPOTHESIS

Mitochondria are important regulators of the metabolic phenotype in type 2 diabetes. A key factor in mitochondrial physiology is the H⁺-ATP synthase. The expression and activity of its physiological inhibitor, ATPase inhibitory factor 1 (IF1), controls tissue homeostasis, metabolic reprogramming and signalling. We aimed to characterise the putative role of IF1 in mediating skeletal muscle metabolism in obesity and diabetes.

METHODS

We examined the 'mitochondrial signature' of obesity and type 2 diabetes in a cohort of 100 metabolically characterised human skeletal muscle biopsy samples. The expression and activity of H⁺-ATP synthase, IF1 and key mitochondrial proteins were characterised, including their association with BMI, fasting plasma insulin, fasting plasma glucose and HOMA-IR. IF1 was also overexpressed in primary cultures of human myotubes derived from the same biopsies to unveil the possible role played by the pathological inhibition of the H⁺-ATP synthase in skeletal muscle.

RESULTS

The results indicate that type 2 diabetes and obesity act via different mechanisms to impair H⁺-ATP synthase activity in human skeletal muscle (76% reduction in its catalytic subunit vs 280% increase in IF1 expression, respectively) and unveil a new pathway by which IF1 influences lipid metabolism. Mechanistically, IF1 altered cellular levels of α-ketoglutarate and L-carnitine metabolism in the myotubes of obese (84% of control) and diabetic (76% of control) individuals, leading to limited β-oxidation of fatty acids (60% of control) and their cytosolic accumulation (164% of control). These events led to enhanced release of TNF-α (10 ± 2 pg/ml, 27 ± 5 pg/ml and 35 ± 4 pg/ml in control, obese and type 2 diabetic participants, respectively), which probably contributes to an insulin resistant phenotype.

CONCLUSIONS/INTERPRETATION

Overall, our data highlight IF1 as a novel regulator of lipid metabolism and metabolic disorders, and a possible target for therapeutic intervention.

Tissue Non-Specific Genes and Pathways Associated with Diabetes: An Expression Meta-Analysis

We performed expression studies to identify tissue non-specific genes and pathways of diabetes by meta-analysis. We searched curated datasets of the Gene Expression Omnibus (GEO) database and identified 13 and five expression studies of diabetes and insulin responses at various tissues, respectively. We tested differential gene expression by empirical Bayes-based linear method and investigated gene set expression association by knowledge-based enrichment analysis. Meta-analysis by different methods was applied to identify tissue non-specific genes and gene sets. We also proposed pathway mapping analysis to infer functions of the identified gene sets, and correlation and independent analysis to evaluate expression association profile of genes and gene sets between studies and tissues. Our analysis showed that PGRMC1 and HADH genes were significant over diabetes studies, while IRS1 and MPST genes were significant over insulin response studies, and joint analysis showed that HADH and MPST genes were significant over all combined data sets. The pathway analysis identified six significant gene sets over all studies. The KEGG pathway mapping indicated that the significant gene sets are related to diabetes pathogenesis. The results also presented that 12.8% and 59.0% pairwise studies had significantly correlated expression association for genes and gene sets, respectively; moreover, 12.8% pairwise studies had independent expression association for genes, but no studies were observed significantly different for expression association of gene sets. Our analysis indicated that there are both tissue specific and non-specific genes and pathways associated with diabetes pathogenesis. Compared to the gene expression, pathway association tends to be tissue non-specific, and a common pathway influencing diabetes development is activated through different genes at different tissues.

Adrenoceptors promote glucose uptake into adipocytes and muscle by an insulin-independent signaling pathway involving mechanistic target of rapamycin complex 2

Uptake of glucose into skeletal muscle and adipose tissue plays a vital role in metabolism and energy balance. Insulin released from β-islet cells of the pancreas promotes glucose uptake in these target tissues by stimulating translocation of GLUT4 transporters to the cell surface. This process is complex, involving signaling proteins including the mechanistic (or mammalian) target of rapamycin (mTOR) and Akt that intersect with multiple pathways controlling cell survival, growth and proliferation. mTOR exists in two forms, mTOR complex 1 (mTORC1), and mTOR complex 2 (mTORC2). mTORC1 has been intensively studied, acting as a key regulator of protein and lipid synthesis that integrates cellular nutrient availability and energy balance. Studies on mTORC2 have focused largely on its capacity to activate Akt by phosphorylation at Ser473, however recent findings demonstrate a novel role for mTORC2 in cellular glucose uptake. For example, agonists acting at β₂-adrenoceptors (ARs) in skeletal muscle or β₃-ARs in brown adipose tissue increase glucose uptake in vitro and in vivo via mechanisms dependent on mTORC2 but not Akt. In this review, we will focus on the signaling pathways downstream of β-ARs that promote glucose uptake in skeletal muscle and brown adipocytes, and will highlight how the insulin and adrenergic pathways converge and interact in these cells. The identification of insulin-independent mechanisms that promote glucose uptake should facilitate novel treatment strategies for metabolic disease.

Screening for genes involved in antibody response to sheep red blood cells in the chicken, Gallus gallus

Antibody response, an important trait in both agriculture and biomedicine, plays a part in protecting animals from infection. Dissecting molecular basis of antibody response may improve artificial selection for natural disease resistance in livestock and poultry. A number of genetic markers associated with antibody response have been identified in the chicken and mouse by linkage-based association studies, which only define genomic regions by genetic markers but do not pinpoint genes for antibody response. In contrast, global expression profiling has been applied to define the molecular bases of a variety of biological traits through identification of differentially expressed genes (DEGs). Here, we employed Affimetrix GeneChip Chicken Genome Arrays to identify differentially expressed genes for antibody response to sheep red blood cells (SRBC) using chickens challenged with and without SRBC or chickens with high and low anti-SRBC titers. The DEGs include those with known (i.e., MHC class I and IgH genes) or unknown function in antibody response. Classification test of these genes suggested that the response of the chicken to intravenous injection of SRBC involved multiple biological processes, including response to stress or other different stimuli, sugar, carbohydrate or protein binding, and cell or soluble fraction, in addition to antibody response. This preliminary study thus provides an insight into molecular basis of antibody response to SRBC in the chicken.

Global Gene Expression Profiling in Omental Adipose Tissue of Morbidly Obese Diabetic African Americans

BACKGROUND

Adipose tissues play important role in the pathophysiology of obesity-related diseases including type 2 diabetes (T2D). To describe gene expression patterns and functional pathways in obesity-related T2D, we performed global transcript profiling of omental adipose tissue (OAT) in morbidly obese individuals with or without T2D.

METHODS

Twenty morbidly obese (mean BMI: about 54 kg/m²) subjects were studied, including 14 morbidly obese individuals with T2D (cases) and 6 morbidly obese individuals without T2D (reference group). Gene expression profiling was performed using the Affymetrix U133 Plus 2.0 human genome expression array. Analysis of covariance was performed to identify differentially expressed genes (DEGs). Bioinformatics tools including PANTHER and Ingenuity Pathway Analysis (IPA) were applied to the DEGs to determine biological functions, networks and canonical pathways that were overrepresented in these individuals.

RESULTS

At an absolute fold-change threshold of 2 and false discovery rate (FDR) < 0.05, 68 DEGs were identified in cases compared to the reference group. Myosin X (MYO10) and transforming growth factor beta regulator 1 (TBRG1) were upregulated. MYO10 encodes for an actin-based motor protein that has been associated with T2D. Telomere extension by telomerase (HNRNPA1, TNKS2), D-myo-inositol (1, 4, 5)-trisphosphate biosynthesis (PIP5K1A, PIP4K2A), and regulation of actin-based motility by Rho (ARPC3) were the most significant canonical pathways and overlay with T2D signaling pathway. Upstream regulator analysis predicted 5 miRNAs (miR-320b, miR-381-3p, miR-3679-3p, miR-494-3p, and miR-141-3p,) as regulators of the expression changes identified.

CONCLUSION

This study identified a number of transcripts and miRNAs in OAT as candidate novel players in the pathophysiology of T2D in African Americans.

Skeletal muscle tissue transcriptome differences in lean and obese female beagle dogs

Skeletal muscle is a large and insulin-sensitive tissue that is an important contributor to metabolic homeostasis and energy expenditure. Many metabolic processes are altered with obesity, but the contribution of muscle tissue in this regard is unclear. A limited number of studies have compared skeletal muscle gene expression of lean and obese dogs. Using microarray technology, our objective was to identify genes and functional classes differentially expressed in skeletal muscle of obese (14.6 kg; 8.2 body condition score; 44.5% body fat) vs. lean (8.6 kg; 4.1 body condition score; 22.9% body fat) female beagle adult dogs. Alterations in 77 transcripts was observed in genes pertaining to the functional classes of signaling, transport, protein catabolism and proteolysis, protein modification, development, transcription and apoptosis, cell cycle and differentiation. Genes differentially expressed in obese vs. lean dog skeletal muscle indicate oxidative stress and altered skeletal muscle cell differentiation. Many genes traditionally associated with lipid, protein and carbohydrate metabolism were not altered in obese vs. lean dogs, but genes pertaining to endocannabinoid metabolism, insulin signaling, type II diabetes mellitus and carnitine transport were differentially expressed. The relatively small response of skeletal muscle could indicate that changes are occurring at a post-transcriptional level, that other tissues (e.g., adipose tissue) were buffering skeletal muscle from metabolic dysfunction or that obesity-induced changes in skeletal muscle require a longer period of time and that the length of our study was not sufficient to detect them. Although only a limited number of differentially expressed genes were detected, these results highlight genes and functional classes that may be important in determining the etiology of obesity-induced derangement of skeletal muscle function.

Regulation of Phosphatidylethanolamine Homeostasis&#8212;The Critical Role of CTP:Phosphoethanolamine Cytidylyltransferase (Pcyt2)

Phosphatidylethanolamine (PE) is the most abundant lipid on the protoplasmatic leaflet of cellular membranes. It has a pivotal role in cellular processes such as membrane fusion, cell cycle regulation, autophagy, and apoptosis. CTP:phosphoethanolamine cytidylyltransferase (Pcyt2) is the main regulatory enzyme in de novo biosynthesis of PE from ethanolamine and diacylglycerol by the CDP-ethanolamine Kennedy pathway. The following is a summary of the current state of knowledge on Pcyt2 and how splicing and isoform specific differences could lead to variations in functional properties in this family of enzymes. Results from the most recent studies on Pcyt2 transcriptional regulation, promoter function, autophagy, and cell growth regulation are highlighted. Recent data obtained from Pcyt2 knockout mouse models is also presented, demonstrating the essentiality of this gene in embryonic development as well as the major physiological consequences of deletion of one Pcyt2 allele. Those include development of symptoms of the metabolic syndrome such as elevated lipogenesis and lipoprotein secretion, hypertriglyceridemia, liver steatosis, obesity, and insulin resistance. The objective of this review is to elucidate the nature of Pcyt2 regulation by linking its catalytic function with the regulation of lipid and energy homeostasis.

The Ups and Downs of Insulin Resistance and Type 2 Diabetes: Lessons from Genomic Analyses in Humans

We are in the midst of a worldwide epidemic of type 2 diabetes (T2D) and obesity. Understanding the mechanisms underlying these diseases is critical if we are to halt their progression and ultimately prevent their development. The advent and widespread implementation of microarray technology has allowed analysis of small samples of human skeletal muscle, adipose, liver, pancreas and blood. While patterns differ in each tissue, several dominant themes have emerged from these studies, including altered expression of genes indicating increased inflammation and altered lipid and mitochondrial oxidative metabolism and insulin signaling in patients with T2D, and in some cases, in those at risk for disease. Unraveling which changes in gene expression are primary, and which are secondary to an insulin resistant or diabetes metabolic milieu remains a scientific challenge but we are one step closer.

Function-based discovery of significant transcriptional temporal patterns in insulin stimulated muscle cells

Background

Insulin action on protein synthesis (translation of transcripts) and post-translational modifications, especially of those involving the reversible modifications such as phosphorylation of various signaling proteins, are extensively studied but insulin effect on transcription of genes, especially of transcriptional temporal patterns remains to be fully defined.

Methodology/Principal Findings

To identify significant transcriptional temporal patterns we utilized primary differentiated rat skeletal muscle myotubes which were treated with insulin and samples were collected every 20 min for 8 hours. Pooled samples at every hour were analyzed by gene array approach to measure transcript levels. The patterns of transcript levels were analyzed based on a novel method that integrates selection, clustering, and functional annotation to find the main temporal patterns associated to functional groups of differentially expressed genes. 326 genes were found to be differentially expressed in response to in vitro insulin administration in skeletal muscle myotubes. Approximately 20% of the genes that were differentially expressed were identified as belonging to the insulin signaling pathway. Characteristic transcriptional temporal patterns include: (a) a slow and gradual decrease in gene expression, (b) a gradual increase in gene expression reaching a peak at about 5 hours and then reaching a plateau or an initial decrease and other different variable pattern of increase in gene expression over time.

Conclusion/Significance

The new method allows identifying characteristic dynamic responses to insulin stimulus, common to a number of genes and associated to the same functional group. The results demonstrate that insulin treatment elicited different clusters of gene transcript profile supporting a temporal regulation of gene expression by insulin in skeletal muscle cells.

Lepidopteran transcriptome analysis following infection by phylogenetically unrelated polydnaviruses highlights differential and common responses

The Polydnaviridae is a family of double-stranded DNA viruses that are symbionts of parasitoid wasps. The family is currently divided into two genera, the Ichnovirus (IV) and Bracovirus (BV), which are associated with wasps in the families Ichneumonidae and Braconidae, respectively. IVs and BVs have similar immunosuppressive and developmental effects on parasitized hosts but their encapsidated genomes largely encode different genes. To assess whether IV and BV infection has similar or disparate effects on the transcriptome of shared hosts, we characterized the effects of Hyposoter didymator Ichnovirus (HdIV) and Microplitis demolitor Bracovirus (MdBV) on the fat body and hemocyte transcriptome of Spodoptera frugiperda (Lepidoptera: Noctuidae). Our results indicated that HdIV and MdBV infection alters the abundance of a relatively low proportion of S. frugiperda transcripts at 24 h post-infection. A majority of the transcripts affected by infection also differed between MdBV and HdIV. However, we did identify some host transcripts that were similarly affected by both viruses. A majority of these genes were transcribed in the fat body and most belonged to functional classes with roles in immunity, detoxification, or cell structure. Particularly prominent in this suite of transcripts were genes encoding for predicted motor-related and collagen IV-like proteins. Overall, our data suggest that the broadly similar effects that HdIV and MdBV have on host growth and immunity are not due to these viruses inducing profound changes in host gene expression. Given though that IVs and BVs encode few shared genes, the host transcripts that are similarly affected by HdIV and MdBV could indicate convergence by each virus to target a few processes at the level of transcription that are important for successful parasitism of hosts by H. didymator and M. demolitor.

Bimodal distribution of RNA expression levels in human skeletal muscle tissue

Background

Many human diseases and phenotypes are related to RNA expression, levels of which are influenced by a wide spectrum of genetic and exposure-related factors. In a large genome-wide study of muscle tissue expression, we found that some genes exhibited a bimodal distribution of RNA expression, in contrast to what is usually assumed in studies of a single healthy tissue. As bimodality has classically been considered a hallmark of genetic control, we assessed the genome-wide prevalence, cause, and association of this phenomenon with diabetes-related phenotypes in skeletal muscle tissue from 225 healthy Pima Indians using exon array expression chips.

Results

Two independent batches of microarrays were used for bimodal assessment and comparison. Of the 17,881 genes analyzed, eight (GSTM1, HLA-DRB1, ERAP2, HLA-DRB5, MAOA, ACTN3, NR4A2, and THNSL2) were found to have bimodal expression replicated in the separate batch groups, while 24 other genes had evidence of bimodality in only one group. Some bimodally expressed genes had modest associations with pre-diabetic phenotypes, of note ACTN3 with insulin resistance. Most of the other bimodal genes have been reported to be involved with various other diseases and characteristics. Association of expression with cis genetic variation in a subset of 149 individuals found all but one of the confirmed bimodal genes and nearly half of all potential ones to be highly significant expression quantitative trait loci (eQTL). The rare prevalence of these bimodally expressed genes found after controlling for batch effects was much lower than the prevalence reported in other studies. Additional validation in data from separate muscle expression studies confirmed the low prevalence of bimodality we observed.

Conclusions

We conclude that the prevalence of bimodal gene expression is quite rare in healthy muscle tissue (<0.2%), and is much lower than limited reports from other studies. The major cause of these clearly bimodal expression patterns in homogeneous tissue appears to be cis-polymorphisms, indicating that such bimodal genes are, for the most part, eQTL. The high frequency of disease associations reported with these genes gives hope that this unique feature may identify or actually be an underlying factor responsible for disease development.

Microarray evidences the role of pathologic adipose tissue in insulin resistance and their clinical implications

Clustering of insulin resistance and dysmetabolism with obesity is attributed to pathologic adipose tissue. The morphologic hallmarks of this pathology are adipocye hypertrophy and heightened inflammation. However, it's underlying molecular mechanisms remains unknown. Study of gene function in metabolically active tissues like adipose tissue, skeletal muscle and liver is a promising strategy. Microarray is a powerful technique of assessment of gene function by measuring transcription of large number of genes in an array. This technique has several potential applications in understanding pathologic adipose tissue. They are: (1) transcriptomic differences between various depots of adipose tissue, adipose tissue from obese versus lean individuals, high insulin resistant versus low insulin resistance, brown versus white adipose tissue, (2) transcriptomic profiles of various stages of adipogenesis, (3) effect of diet, cytokines, adipokines, hormones, environmental toxins and drugs on transcriptomic profiles, (4) influence of adipokines on transcriptomic profiles in skeletal muscle, hepatocyte, adipose tissue etc., and (5) genetics of gene expression. The microarray evidences of molecular basis of obesity and insulin resistance are presented here. Despite the limitations, microarray has potential clinical applications in finding new molecular targets for treatment of insulin resistance and classification of adipose tissue based on future risk of insulin resistance syndrome.

Insulin resistance at the crossroads of metabolic syndrome: systemic analysis using microarrays

Recently, it has been suggested that insulin resistance is a better predictor of metabolic syndrome than obesity. Numerous studies have been conducted to identify insulin resistance susceptibility genes in various model systems. This review focuses on recent findings in microarray analyses, which have indicated that (i) in the liver, genes involved in lipid synthesis and gluconeogenesis are increased in an animal model of insulin resistance that leads into liver steatosis and hyperglycemia; (ii) in adipose tissues, genes involved in fatty acid synthesis and adipogenesis are down-regulated both in insulin-resistant humans and in animals; and (iii) in muscle, overall gene expression, including genes involved in fatty acid oxidation and biosynthesis, is either decreased or unresponsive compared to that of insulin-sensitive control human subjects or animals. Considering the multifaceted effects of insulin resistance in various tissues, aiming at multi-targets rather than a single target will be a more promising strategy for the prevention or treatment of insulin resistance.

Physiological insights gained from gene expression analysis in obesity and diabetes

Microarray technology permits the interrogation of nearly all expressed genes under a wide range of conditions. Patterns of gene expression in response to obesity and diabetes have yielded important insights into the pathogenesis of diabetes and its relationship to obesity. In muscle, microarray studies have motivated research into mitochondrial function. In adipose tissue, clues have pointed to the importance of inflammation in obesity. New adipocyte-derived hormones involved in insulin resistance have been found; a notable example is retinol binding protein 4. In liver, genes responsive to master regulators of lipid metabolism have been identified. In beta-cells, genes involved in cell survival, cell proliferation, and insulin secretion have been identified. These studies have greatly expanded our understanding of mechanisms underlying the pathogenesis of obesity-induced diabetes. When combined with genetic information, microarray data can be used to construct causal network models linking gene expression with disease.

Transcriptome profiling in response to adiponectin in human cancer-derived cells

The adipocyte-derived hormone adiponectin exerts protective actions in several disorders, including some cancers. However, while growing data suggest that adiponectin could be an effective anticancer agent, its mechanism of action in cancer cells is still poorly known. Here, using microarrays, we identified a set of 1,301 genes commonly modulated in three cancer-derived cell lines in response to short-term stimulation with full-length recombinant human adiponectin. Most of these genes are involved in translation regulation, immune or stress responses, and cell proliferation. Furthermore, among genes linked to disease that were retrieved by functional enrichment tests using text mining based on PubMed analysis, we found that 66% are involved in malignant neoplasms, further supporting the link between adiponectin and cancer mechanisms. Bioinformatic analysis demonstrated the diversity of signaling pathways and transcription factors potentially mediating adiponectin effects on gene expression, illustrating the complexity of adiponectin mechanisms of action in cancer cells.

Mining metabolic pathways through gene expression

MOTIVATION

An observed metabolic response is the result of the coordinated activation and interaction between multiple genetic pathways. However, the complex structure of metabolism has meant that a compete understanding of which pathways are required to produce an observed metabolic response is not fully understood. In this article, we propose an approach that can identify the genetic pathways which dictate the response of metabolic network to specific experimental conditions.

RESULTS

Our approach is a combination of probabilistic models for pathway ranking, clustering and classification. First, we use a non-parametric pathway extraction method to identify the most highly correlated paths through the metabolic network. We then extract the defining structure within these top-ranked pathways using both Markov clustering and classification algorithms. Furthermore, we define detailed node and edge annotations, which enable us to track each pathway, not only with respect to its genetic dependencies, but also allow for an analysis of the interacting reactions, compounds and KEGG sub-networks. We show that our approach identifies biologically meaningful pathways within two microarray expression datasets using entire KEGG metabolic networks.

AVAILABILITY AND IMPLEMENTATION

An R package containing a full implementation of our proposed method is currently available from http://www.bic.kyoto-u.ac.jp/pathway/timhancock.

Metabolic network topology reveals transcriptional regulatory signatures of type 2 diabetes

Type 2 diabetes mellitus (T2DM) is a disorder characterized by both insulin resistance and impaired insulin secretion. Recent transcriptomics studies related to T2DM have revealed changes in expression of a large number of metabolic genes in a variety of tissues. Identification of the molecular mechanisms underlying these transcriptional changes and their impact on the cellular metabolic phenotype is a challenging task due to the complexity of transcriptional regulation and the highly interconnected nature of the metabolic network. In this study we integrate skeletal muscle gene expression datasets with human metabolic network reconstructions to identify key metabolic regulatory features of T2DM. These features include reporter metabolites—metabolites with significant collective transcriptional response in the associated enzyme-coding genes, and transcription factors with significant enrichment of binding sites in the promoter regions of these genes. In addition to metabolites from TCA cycle, oxidative phosphorylation, and lipid metabolism (known to be associated with T2DM), we identified several reporter metabolites representing novel biomarker candidates. For example, the highly connected metabolites NAD+/NADH and ATP/ADP were also identified as reporter metabolites that are potentially contributing to the widespread gene expression changes observed in T2DM. An algorithm based on the analysis of the promoter regions of the genes associated with reporter metabolites revealed a transcription factor regulatory network connecting several parts of metabolism. The identified transcription factors include members of the CREB, NRF1 and PPAR family, among others, and represent regulatory targets for further experimental analysis. Overall, our results provide a holistic picture of key metabolic and regulatory nodes potentially involved in the pathogenesis of T2DM.

Type 2 diabetes mellitus is a complex metabolic disease recognized as one of the main threats to human health in the 21^st century. Recent studies of gene expression levels in human tissue samples have indicated that multiple metabolic pathways are dysregulated in diabetes and in individuals at risk for diabetes; which of these are primary, or central to disease pathogenesis, remains a key question. Cellular metabolic networks are highly interconnected and often tightly regulated; any perturbations at a single node can thus rapidly diffuse to the rest of the network. Such complexity presents a considerable challenge in pinpointing key molecular mechanisms and biomarkers associated with insulin resistance and type 2 diabetes. In this study, we address this problem by using a methodology that integrates gene expression data with the human cellular metabolic network. We demonstrate our approach by analyzing gene expression patterns in skeletal muscle. The analysis identified transcription factors and metabolites that represent potential targets for therapeutic agents and future clinical diagnostics for type 2 diabetes and impaired glucose metabolism. In a broader perspective, the study provides a framework for analysis of gene expression datasets from complex diseases in the context of changes in cellular metabolism.

Integration of microRNA changes in vivo identifies novel molecular features of muscle insulin resistance in type 2 diabetes

Background

Skeletal muscle insulin resistance (IR) is considered a critical component of type II diabetes, yet to date IR has evaded characterization at the global gene expression level in humans. MicroRNAs (miRNAs) are considered fine-scale rheostats of protein-coding gene product abundance. The relative importance and mode of action of miRNAs in human complex diseases remains to be fully elucidated. We produce a global map of coding and non-coding RNAs in human muscle IR with the aim of identifying novel disease biomarkers.

Methods

We profiled >47,000 mRNA sequences and >500 human miRNAs using gene-chips and 118 subjects (n = 71 patients versus n = 47 controls). A tissue-specific gene-ranking system was developed to stratify thousands of miRNA target-genes, removing false positives, yielding a weighted inhibitor score, which integrated the net impact of both up- and down-regulated miRNAs. Both informatic and protein detection validation was used to verify the predictions of in vivo changes.

Results

The muscle mRNA transcriptome is invariant with respect to insulin or glucose homeostasis. In contrast, a third of miRNAs detected in muscle were altered in disease (n = 62), many changing prior to the onset of clinical diabetes. The novel ranking metric identified six canonical pathways with proven links to metabolic disease while the control data demonstrated no enrichment. The Benjamini-Hochberg adjusted Gene Ontology profile of the highest ranked targets was metabolic (P < 7.4 × 10^-8), post-translational modification (P < 9.7 × 10^-5) and developmental (P < 1.3 × 10^-6) processes. Protein profiling of six development-related genes validated the predictions. Brain-derived neurotrophic factor protein was detectable only in muscle satellite cells and was increased in diabetes patients compared with controls, consistent with the observation that global miRNA changes were opposite from those found during myogenic differentiation.

Conclusions

We provide evidence that IR in humans may be related to coordinated changes in multiple microRNAs, which act to target relevant signaling pathways. It would appear that miRNAs can produce marked changes in target protein abundance in vivo by working in a combinatorial manner. Thus, miRNA detection represents a new molecular biomarker strategy for insulin resistance, where micrograms of patient material is needed to monitor efficacy during drug or life-style interventions.

Expression-based network biology identifies alteration in key regulatory pathways of type 2 diabetes and associated risk/complications

Type 2 diabetes mellitus (T2D) is a multifactorial and genetically heterogeneous disease which leads to impaired glucose homeostasis and insulin resistance. The advanced form of disease causes acute cardiovascular, renal, neurological and microvascular complications. Thus there is a constant need to discover new and efficient treatment against the disease by seeking to uncover various novel alternate signalling mechanisms that can lead to diabetes and its associated complications. The present study allows detection of molecular targets by unravelling their role in altered biological pathways during diabetes and its associated risk factors and complications. We have used an integrated functional networks concept by merging co-expression network and interaction network to detect the transcriptionally altered pathways and regulations involved in the disease. Our analysis reports four novel significant networks which could lead to the development of diabetes and other associated dysfunctions. (a) The first network illustrates the up regulation of TGFBRII facilitating oxidative stress and causing the expression of early transcription genes via MAPK pathway leading to cardiovascular and kidney related complications. (b) The second network demonstrates novel interactions between GAPDH and inflammatory and proliferation candidate genes i.e., SUMO4 and EGFR indicating a new link between obesity and diabetes. (c) The third network portrays unique interactions PTPN1 with EGFR and CAV1 which could lead to an impaired vascular function in diabetic nephropathy condition. (d) Lastly, from our fourth network we have inferred that the interaction of β-catenin with CDH5 and TGFBR1 through Smad molecules could contribute to endothelial dysfunction. A probability of emergence of kidney complication might be suggested in T2D condition. An experimental investigation on this aspect may further provide more decisive observation in drug target identification and better understanding of the pathophysiology of T2D and its complications.

Sparse linear discriminant analysis for simultaneous testing for the significance of a gene set/pathway and gene selection

MOTIVATION

Pathway and gene set-based approaches for the analysis of gene expression profiling experiments have become increasingly popular for addressing problems associated with individual gene analysis. Since most genes are not differently expressed, existing gene set tests, which consider all the genes within a gene set, are subject to considerable noise and power loss, a concern exacerbated in studies in which the degree of differential expression is moderate for truly differentially expressed genes. For a significantly differentially expressed pathway, it is also of substantial interest to select important genes that drive the differential expression of the pathway.

METHODS

We develop a unified framework to jointly test the significance of a pathway and to select a subset of genes that drive the significant pathway effect. To achieve dimension reduction and gene selection, we decompose each gene pathway into a single score by using a regularized form of linear discriminant analysis, called sparse linear discriminant analysis (sLDA). Testing for the significance of the pathway effect proceeds via permutation of the sLDA score. The sLDA-based test is compared with competing approaches with simulations and two applications: a study on the effect of metal fume exposure on immune response and a study of gene expression profiles among Type II Diabetes patients.

RESULTS

Our results show that sLDA-based testing provides a powerful approach to test for the significance of a differentially expressed pathway and gene selection.

AVAILABILITY

An implementation of the proposed sLDA-based pathway test in the R statistical computing environment is available at http://www.hsph.harvard.edu/~mwu/software/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Intracellular lipid accumulation in liver and muscle and the insulin resistance syndrome

This article emphasizes intrahepatocellular and intramyocellular lipid accumulation as components of the insulin resistance syndrome. It examines the mechanisms responsible for the interrelationships among ectopic fat deposition, insulin resistance, and associated metabolic traits. These relationships are complex and vary according to diet, exercise, weight loss, and racial identity. Overall, there is a high degree of association of both intrahepatocellular and intramyocellular lipids with insulin resistance and associated cardiometabolic risk factors. It concludes that further research is necessary to determine the orchestrated roles of adipose and nonadipose tissue compartments in the regulation of insulin sensitivity, and mechanisms explaining racial differences in the insulin resistance syndrome-trait cluster.

Mitochondrial dysfunction in type 2 diabetes and obesity

Insulin resistance in skeletal muscle is a major hallmark of type 2 diabetes mellitus (T2D) and obesity that is characterized by impaired insulin-mediated glucose transport and glycogen synthesis and by increased intramyocellular content of lipid metabolites. Several studies have provided evidence for mitochondrial dysfunction in skeletal muscle of type 2 diabetic and prediabetic subjects, primarily due to a lower content of mitochondria (mitochondrial biogenesis) and possibly to a reduced functional capacity per mitochondrion. This article discusses the latest advances in the understanding of the molecular mechanisms underlying insulin resistance in human skeletal muscle in T2D and obesity, with a focus on possible links between insulin resistance and mitochondrial dysfunction.

Effect of acute physiological hyperinsulinemia on gene expression in human skeletal muscle in vivo

This study was undertaken to test the hypothesis that short-term exposure (4 h) to physiological hyperinsulinemia in normal, healthy subjects without a family history of diabetes would induce a low grade inflammatory response independently of glycemic status. Twelve normal glucose tolerant subjects received a 4-h euglycemic hyperinsulinemic clamp with biopsies of the vastus lateralis muscle. Microarray analysis identified 121 probe sets that were significantly altered in response to physiological hyperinsulinemia while maintaining euglycemia. In normal, healthy human subjects insulin increased the mRNAs of a number of inflammatory genes (CCL2, CXCL2 and THBD) and transcription factors (ATF3, BHLHB2, HES1, KLF10, JUNB, FOS, and FOSB). A number of other genes were upregulated in response to insulin, including RRAD, MT, and SGK. CITED2, a known coactivator of PPARalpha, was significantly downregulated. SGK and CITED2 are located at chromosome 6q23, where we previously detected strong linkage to fasting plasma insulin concentrations. We independently validated the mRNA expression changes in an additional five subjects and closely paralleled the results observed in the original 12 subjects. A saline infusion in healthy, normal glucose-tolerant subjects without family history of diabetes demonstrated that the genes altered during the euglycemic hyperinsulinemic clamp were due to hyperinsulinemia and were unrelated to the biopsy procedure per se. The results of the present study demonstrate that insulin acutely regulates the levels of mRNAs involved in inflammation and transcription and identifies several candidate genes, including HES1 and BHLHB2, for further investigation.

Reactome: a knowledge base of biologic pathways and processes

Reactome, an online curated resource for human pathway data, can be used to infer equivalent reactions in non-human species and as a tool to aid in the interpretation of microarrays and other high-throughput data sets.

Reactome http://www.reactome.org, an online curated resource for human pathway data, provides infrastructure for computation across the biologic reaction network. We use Reactome to infer equivalent reactions in multiple nonhuman species, and present data on the reliability of these inferred reactions for the distantly related eukaryote Saccharomyces cerevisiae. Finally, we describe the use of Reactome both as a learning resource and as a computational tool to aid in the interpretation of microarrays and similar large-scale datasets.

Dysregulation of muscle lipid metabolism in rats selectively bred for low aerobic running capacity

As substrate for evaluation of metabolic diseases, we developed novel rat models that contrast for endurance exercise capacity. Through two-way artificial selection, we created rodent phenotypes of intrinsically low-capacity runners (LCR) and high-capacity runners (HCR) that also differed markedly for cardiovascular and metabolic disease risk factors. Here, we determined skeletal muscle proteins with putative roles in lipid and carbohydrate metabolism to better understand the mechanisms underlying differences in whole body substrate handling between phenotypes. Animals (generation 16) differed for endurance running capacity by 295%. LCR animals had higher resting plasma glucose (6.58 +/- 0.45 vs. 6.09 +/- 0.45 mmol/l), insulin (0.48 +/- 0.03 vs. 0.32 +/- 0.02 ng/ml), nonesterified fatty acid (0.57 +/- 0.14 v 0.35 +/- 0.05 mM), and triglyceride (TG; 0.47 +/- 0.11 vs. 0.25 +/- 0.08 mmol/l) concentrations (all P < 0.05). Muscle TG (72.3 +/- 14.7 vs. 38.9 +/- 6.2 mmol/kg dry muscle wt; P < 0.05) and diacylglycerol (96 +/- 28 vs. 42 +/- 8 pmol/mg dry muscle wt; P < 0.05) contents were elevated in LCR vs. HCR rats. Accompanying the greater lipid accretion in LCR was increased fatty acid translocase/CD36 content (1,014 +/- 80 vs. 781 +/- 70 arbitrary units; P < 0.05) and reduced TG lipase activity (0.158 +/- 0.0125 vs. 0.274 +/- 0.018 mmol.min(-1).kg dry muscle wt(-1); P < 0.05). Muscle glycogen, GLUT4 protein, and basal phosphorylation states of AMP-activated protein kinase-alpha1, AMP-activated protein kinase-alpha2, and acetyl-CoA carboxylase were similar in LCR and HCR. In conclusion, rats with low intrinsic aerobic capacity demonstrate abnormalities in lipid-handling capacity. These disruptions may, in part, be responsible for the increased risk of metabolic disorders observed in this phenotype.

Defective mitochondrial biogenesis: a hallmark of the high cardiovascular risk in the metabolic syndrome?

The metabolic syndrome is a group of risk factors of metabolic origin that are accompanied by increased risk for type 2 diabetes mellitus and cardiovascular disease. These risk factors include atherogenic dyslipidemia, elevated blood pressure and plasma glucose, and a prothrombotic and proinflammatory state. The condition is progressive and is exacerbated by physical inactivity, advancing age, hormonal imbalance, and genetic predisposition. The metabolic syndrome is a particularly challenging clinical condition because its complex molecular basis is still largely undefined. Impaired cell metabolism has, however, been suggested as a relevant pathophysiological process underlying several clinical features of the syndrome. In particular, defective oxidative metabolism seems to be involved in visceral fat gain and in the development of insulin resistance in skeletal muscle. This suggests that mitochondrial function may be impaired in the metabolic syndrome and, thus, in the consequent cardiovascular disease. We have recently found that mitochondrial biogenesis and function are enhanced by nitric oxide in various cell types and tissues, including cardiac muscle. Increasing evidence suggests that this mediator acts as a metabolic sensor in cardiomyocytes. This implies that a defective production of nitric oxide might be linked to dysfunction of the cardiomyocyte metabolism. Here we summarize some recent findings and propose a hypothesis for the high cardiovascular risk linked to the metabolic syndrome.

FM-test: a fuzzy-set-theory-based approach to differential gene expression data analysis

Background

Microarray techniques have revolutionized genomic research by making it possible to monitor the expression of thousands of genes in parallel. As the amount of microarray data being produced is increasing at an exponential rate, there is a great demand for efficient and effective expression data analysis tools. Comparison of gene expression profiles of patients against those of normal counterpart people will enhance our understanding of a disease and identify leads for therapeutic intervention.

Results

In this paper, we propose an innovative approach, fuzzy membership test (FM-test), based on fuzzy set theory to identify disease associated genes from microarray gene expression profiles. A new concept of FM d-value is defined to quantify the divergence of two sets of values. We further analyze the asymptotic property of FM-test, and then establish the relationship between FM d-value and p-value. We applied FM-test to a diabetes expression dataset and a lung cancer expression dataset, respectively. Within the 10 significant genes identified in diabetes dataset, six of them have been confirmed to be associated with diabetes in the literature and one has been suggested by other researchers. Within the 10 significantly overexpressed genes identified in lung cancer data, most (eight) of them have been confirmed by the literatures which are related to the lung cancer.

Conclusion

Our experiments on synthetic datasets show that FM-test is effective and robust. The results in diabetes and lung cancer datasets validated the effectiveness of FM-test. FM-test is implemented as a Web-based application and is available for free at .