Obesity

Gene expression profile in obesity and type 2 diabetes mellitus: Gene expression in the pathophysiology of type 2 diabetes mellitus

Athos, H. Genes involved in MHC class II receptor activity, structural constituent of ribosome, Hsp70 protein binding, L-tyrosine transporter activity, cyclin binding, arachidonate 5-lipoxygenase activity were downregulated in DNPH1 with respect to H.

At the initial stage, the abnormal accumulation of food intake and adipose tissues triggers the inflammatory cytokine expression and persistent immune reactions of fat cells. Read the winning articles. Lytovchenko et al. Gregor and G. Received 29 Dec GOMyosin complex.

  • Arch Physiol Biochem.

  • Bruning J.

  • The green spots are the differentially expressed outlier genes for diabetic with no parental history [2] vs diabetic with parental history.

  • The role of inflammation and macrophage accumulation in the development of obesity-induced type 2 diabetes mellitus and the possible therapeutic effects of long-chain n-3 PUFA.

Introduction

Additionally, we found in Figure 2 c that the hub genes play critical roles in linking obesity and T2D since the average degree of the shared genes is significantly higher than the remains in the NOT2D network. Thus, for diabetic with no parental This is 0. Thus, for healthy with obesity vs. Thus, weight loss seen in RYGB and diet control groups could be attributed to alterations in the concentrations of specific hypothalamic signaling peptides that regulate appetite, food intake and satiety.

  • Genes involved in MHC class II receptor activity, gamma-aminobutyric acid: hydrogen symporter activity, chemokine receptor activity, interleukin-4 receptor activity, interleukin-7 receptor activity, arachidonate 5-lipoxygenase activity, complement receptor activity were upregulated in DPH vs DNPH1.

  • Genes were ranked based on differential expression in the T2DM and obesity groups.

  • Figure 4.

  • The green spots are the differentially expressed outlier genes when one diabetic with no parental history [1] was compared with another diabetic with no parental history [2]. Multi- mutually exclusive.

  • For instance, the PPAR signaling pathway is enriched in active cluster 2 of obesity, which has a vital function in adipocyte proliferation and differentiation in liver, muscle and adipose tissues [ 9 ].

The optimal cut-off could be obtained programmatically thereby yielding a set of univariate outliers that overlap with a subset of multivariate outliers. Mogensen T. Giddings Jr. Figure 15 shows the thresholds for 2. Thus, weight loss seen in RYGB and diet control groups could be attributed to alterations in the concentrations of specific hypothalamic signaling peptides that regulate appetite, food intake and satiety. Hamosh A. In addition, ACh has a regulatory role on serotonin, dopamine and other neuropeptides [ 2324 ], suggesting that a complex network of interaction exists between these molecules in the regulation of immune response and neurotransmission.

Figure 19 shows the thresholds for 2-fold change, thereby providing the up and down regulated genes. Nat Rev Cancer. Lipids Health Dis 6, 35 Rosen, C.

Journal of Diabetes Research

Genes were ranked based on differential expression in the T2DM and obesity groups. Although genetics expressioj play an important role in the higher prevalence of these diseases, it is not clear how genetic factors interact with environmental and dietary factors to increase their incidence. Pathway Analysis 1. The observations indicated by green spots is the ure as, subset of bivariate outliers, which could have been differ- entially expressed across the samples.

  • Here X 1 is treated as reference, while X 2 is treated as test sample.

  • Early stages of obesity, type 2 diabetes mellitus, hypertension, and metabolic syndrome X are characterized by insulin resistance restricted to muscle tissue [ 16 ]. Abstract Obesity is an important component of metabolic syndrome X and predisposes to the development of type 2 diabetes mellitus.

  • Hum Mol Genet. Article PubMed Google Scholar.

  • View at: Google Scholar J.

Patti, ME. The differentially expressed genes were classified into upregulated and downregulated groups as Cluster A and B respectively, and then the expression pattern of these genes was visualized using the heat-map function in the R base package [64]. E The top 15 fold change genes downregulated or upregulated in diabetic mouse liver. AAR performed the study, and drafted the manuscript. Genomics81 :1—7.

Goran and M. Our analysis of gene expression in various tissues using GEO datasets provides a valuable method to determine novel candidate genes for T2DM and obesity. And the samples from these patients who suffered both obesity and diabetes were excluded. View at: Google Scholar M.

Advanced Computational Approaches for Medical Genetics and Genomics

The authors declare that there is no conflict of interests regarding the publication of this paper. Central nervous system endoplasmic reticulum stress in a murine model of type 2 diabetes By Junguk Hur. Article PubMed Google Scholar.

Anti-inflammatory nature of exercise. Genes involved in immune response, regulation of glycolysis were downregulated in DPH with respect to H. In total, genes in close proximity to T2DM SNPs were reordered based on their differential expression percentages. Cellular Component Genes localized in vesicle hemoglobin complex, perikaryon, Golgi transport complex were upregulated in DPH with respect to O. Page 19 of 19 page number not for citation purposes View publication stats.

Kliewer, B. Von Sivers, and U. Moreover, we found that some genes such as Comt1Osgin1Mup-ps13 and Gm at a relatively high abundance were quantified in this study but not found in the previous microarray data [33]. Mol Endocrinol. Glutamine family amino acid metabolic process. Figure 7 shows the thresholds for 2. The role of hepatic fatty acid oxidation in diabetes is complicate.

MeSH terms

R package. Epigenetic factors have been revealed to be heavily implicated in the complex interplay between environmental signals and intrinsic genetic alterations 7. Circulation—

Genes localized in vacuolar lumen, chromosome, nucleosome, proteasome activator complex were upregulated in DNPH1 with respect to H. Diehl, B. The non-regular observations, described as outliers, represent systematic deviations. Genes involved in inflammatory response that were differentially expressed in subjects with obesity and type 2 diabetes mellitus.

Known SNPs associated with disease typically account for profils a small fraction of overall disease [ 89 ]. Red and gray circles labeled on each gene indicate the genes are upregulated and unaffected in diabetic mouse liver respectively. This is 1. Biebermann, W. We performed gene expression profile in subjects with obesity and type 2 diabetes mellitus with and without family history of these diseases. McGarry JD Banting lecture dysregulation of fatty acid metabolism in the etiology of type 2 diabetes. A vicious circle.

Machine Learning and Network Methods for Biology and Medicine 2020

Genes localized in vacuolar lumen, chromosome, nucleosome, proteasome activator complex were upregulated in DNPH1 with respect to H. Hobbs, and T. Pawitan, S.

In contrast genes involved in cell adhesion molecules, cytokine-cytokine receptor interaction, insulin signaling and immune system pathways are downregulated in obese. Emanuelli, and C. Thus, for diabetic with no parental history [ 2 ] vs. Eur Heart J.

Brabant, and A. Vidal, and L. B, Biological process. Table S1. J Diabetes Complications Postic C, Girard J The role of the lipogenic pathway in the development of hepatic steatosis.

Introduction

Figure 7. Subscription will auto renew annually. The enrichment factor is the ratio of the number of DEGs annotated to the term to the number of all genes annotated to it.

Dixbetes diets and sedentary lifestyles are prominent environmental contributors leading to the development of T2D 6. Published : 14 December Similarly, we also found many immune-related genes were markedly changed in type 2 diabetic mouse liver Table S2. White hexagonal nodes represent the predicted transcription factors. Figure 1. As a result, there are 16 and 12 pathways significantly enriched in these obesity and T2D active clusters with or without the seed genes Figure 4.

In these subjects, a direct correlation between the degree of adiposity and plasma CRP levels was noted. Armugam, S. Healthy reference vs. Abstract The increased prevalence of obesity and type 2 diabetes T2D has become an important factor affecting the health of the human.

A further study also revealed that selective inactivation of insulin to disrupt hepatic glucose release and fatty acid synthesis led to insulin resistance in the liver, further corroborating that the liver is a significant target for the effect of insulin 7. Lloyd A, Sawyer W and Hopkinson P: Impact of long-term complications on quality of life in patients with type 2 diabetes not using insulin. Valle, and V. The associated genes in the top 5 KEGG pathways significantly altered in diabetic mouse liver. Yang, R.

Publication types

Insulin resistance and human disease: a short history. Read the winning articles. Stage II: Univariate outliers detection The univariate outliers detection analysis is performed as follows: Let S denote the original set of observations.

Table V. Diabetes Care23 — Am J Epidemiol — J Biopharm Stat. Functional and pathway enrichment analyses In order to examine the biological functions of abnormal genes in obesity-associated T2D, GO and KEGG enrichment analyses were performed using the previously identified DEGs and the overlapping genes. Figure 3. Genes localized in ferritin complex, proton-transporting ATP synthase complex, coupling factor F oribosome, eukaryotic translation elongation factor 1 complex, ubiquitin conjugating enzyme complex were downregulated in DNPH1 with respect to H.

Genes involved in MHC class II receptor activity, gamma-aminobutyric acid: hydrogen symporter activity, chemokine receptor activity, interleukin-4 receptor activity, rype receptor activity, arachidonate 5-lipoxygenase activity, complement receptor activity were upregulated in DPH vs DNPH1. One of the well-known methods of estimation viz. An atlas of combinatorial transcriptional regulation in mouse and man. Von Sivers, and U. Multivariate outliers can now be defined as the observations having large squared MD values. Methodology of analysis of data Multivariate outlier detection Outlier detection is one of the important tasks in any data analysis, which describes abnormalities in the data.

Journal of Diabetes Research

J Am Coll Surg. Dixbetes, weight loss seen in RYGB and diet control groups could be attributed ceptors or catecholamine-generating enzymes suppressed to alterations in the concentrations of specific hypotha- inflammation [25]. However, the molecular mechanisms of the disease relations are not well discovered yet. Scatter plot of log intensities for healthy vs.

Table 2 Genes involved in inflammatory response that were differentially expressed in subjects with obesity and type 2 diabetes mellitus. Here X 1 is treated as reference, while X 2 is treated as test sample. Goldstein, and T. Dedoussis, A.

Cell adhesion. Figure 2. Expression of 14, genes was analyzed using the above method. However, the role of Vdac2 and A1bg in glucose and lipid metabolism is yet to be elucidated.

Computational and Mathematical Methods in Medicine

Genes involved in oxidative phosphorylation, immune, nervous system, and metabolic disorders pathways are upregulated in those with diabetes with family history of diabetes compared to those with diabetes but with no family history. On similar lines, the analysis was carried out for the remaining fourteen comparisons and the corresponding figures for each comparison are given below. When the results given in Figures 12 and 13 are compared they look very similar. Emanuelli, and C. The cut-off value could be used in equation 2 to obtain the z-value as.

  • McGarry JD Banting lecture dysregulation of fatty acid metabolism in the etiology of type 2 diabetes.

  • Genes involved in cell adhesion molecules CAMscytokine-cytokine receptor interaction, insulin signaling pathway, immune system pathways were downregulated in O vs H.

  • However, no enrichment was observed in these two submodules.

  • Table 2 Genes involved in inflammatory response that were differentially expressed in subjects with obesity expressiin type 2 diabetes mellitus. Even with these challenges, network-based systems biology is increasingly attracting much attention from communities of both experimental and computational biologists and is expected to revolutionize our understanding of complicated disease as a whole.

The univariate outliers detection analysis is performed as follows:. The shape and the size of multivariate data are quantified by the covariance matrix, ih is taken into account in the Mahalanobis distance. Genes involved in establishment of cellular localization, cuticle biosynthetic process, hydrogen peroxide, biosynthetic process, vesicle docking were upregulated in O vs HO. Metabolic syndrome X is characterized by a abdominal obesity, b atherogenic dyslipidemia, c raised blood pressure, d insulin resistance with or without glucose intolerance, e pro-inflammatory state, and f prothrombin state. This is 3. Blood samples were obtained from 6 subjects. Figure 10 shows the thresholds for 2.

Thus, for healthy with overweight vs. The size of ellipse represents the number of genes in the subclusters and the triangle size is proportional to the number of the links with obesity and T2D subclusters. Metrics details. Biological Process Genes involved in polysaccharide metabolic process, regulation of pH, tissue development, and diuresis were upregulated both in diabetes and obesity. Genes localized in CAAX-protein geranylgeranyltransferase complex, intracellular organelle were upregulated in O with respect to H. The observations with RD values greater than the cut-off are declared as outliers.

MeSH terms

PPARs and the complex journey to obesity. Thus, for healthy with overweight vs. Nervous tissues synthesize neuropeptides and cytokines and immune cells serve as the molecular basis of neural-immune interactions. We also found that the different parts in the same pathway are activated in obesity and T2D.

Anal Chem. Genes involved in carbohydrate metabolism pathways, metabolism of cofactors and vitamins pathways, ubiquitin mediated proteolysis, signal transduction pathways, ECM-receptor interaction, neuroactive ligand receptor interaction, regulation of actin cytoskeleton, cell cycle, endocrine system pathways, nervous system pathways, Huntington's disease were upregulated in DNPH1 vs H. Discussion This study provides the gene expression profile data of type 2 diabetic mouse liver by high-throughput sequencing, and demonstrates the main biological processes, pathways, fatty acid and glucose metabolism related key enzyme genes and liver diseases correlated with type 2 diabetes. Figure 16 shows the thresholds for 2. Yazbek, D.

Pedrini, L. Published online Jul This approach provides the fold-change value considering expressiion scatter of observations and thereby provides up and down regulated genes across the samples. Fick, J. Out of 3, outlier genes, were detected as up regulated, while 1, were detected as down-regulated genes with respect to healthy individual with overweight HO. Diabetic with no parental history2 reference vs detected as up regulated, while were detected as Diabetic with parental history test sample [DNPH2 vs down-regulated genes with respect to the individual with DNPH] diabetes and no parental history [1]. BCAT1 has been identified as the optimal marker for weight regain [ 35 ].

Nat Biotechnol14 — Jn was downregulated in adipose tissue, while increased expression was observed in blood. Substances Insulin. For example, Cpt1a and Cpt2 encoding the rate-limiting enzyme carnitine-palmitoyl transferase in fatty acid oxidation were upregulated to 1. Mahalanobis distance The shape and the size of multivariate data are quantified by the covariance matrix, which is taken into account in the Mahalanobis distance. GONuclear envelope.

BioMed Research International

Adan, B. Hess B, Boiteux A Oscillatory phenomena in biochemistry. Some datasets were separated into several groups according to sample phenotype.

  • McGarry JD Banting lecture dysregulation of fatty acid metabolism in the etiology of type 2 diabetes.

  • Genes involved in regulation of hormone biosynthetic process, opsonization were downregulated in diabetes and obesity. The location and the covariance parameters are estimated using robust estimation methods.

  • Probes corresponding to more than one gene were excluded.

  • Type 2 diabetes mellitus without parental history2 vs Normal inhibitor activity, acyl-CoA oxidase activity, phosphati- [DNPH2 vs H] dylinositol transporter activity, acyltransferase activity Molecular Function were downregulated in DPH with respect to H.

For a perfect linear relationship between the two samples, the Z statistic becomes residual following normal expressioon with mean m and variance S e 2'. Von Sivers, and U. However, it has previously been reported that there is no association between the methylation status of CCND1 and its expression J Biopharm Stat. Value Health. These results are in line with the correlation of diabetes with immunity and cancer [30][31][32]. Sign up for eToc alerts.

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By combing the differential expression profiles from multiple datasets and the NOT2D network, the mellitis 5 scoring active modules were identified in the obesity samples as well as in T2D. Linford, D. Asian Pacific Journal of Tropical Biomedicine. Fox et al. Figure 1. One of the well-known methods of estimation viz.

Biebermann, W. The primary objective of the study of gene expression profiles using microarray is to assess the mRNA transcript levels of samples under different experimental conditions and detect significant difference in expression levels of various genes across samples. Impaired insulin-mediated signaling, gene expression, glycogen synthesis, and accumulation of intramyocellular triglycerides have all been linked with insulin resistance, but no specific defect responsible for insulin resistance and DM has been identified in humans. Issue Date : May Romijn, J. Introduction A sedentary life-style coupled with calorie-dense dietary behavior of contemporary human causes the accumulation of body fat. Figure 5.

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In these subjects, a direct vene between the degree of adiposity and plasma CRP levels was noted. Genes involved in ammonia ligase activity, transaldolase activity, 4-alpha-glucanotransferase activity, choline: sodium symporter activity, interleukin-8 receptor activity were downregulated in DPH vs DNPH1. Genes involved 6. Genes localized in Golgi transport complex, vesicle, oncostatin-M receptor complex, perikaryon were downregulated in O vs HO.

Djabetes 20 shows the thresholds for 2-fold change, thereby providing the up and down regulated genes. Genomic data relevant to various diseases are archived in public repositories that are easily accessed to obtain meaningful information and to make novel discoveries DNA methylation is an epigenetic modification most commonly associated with cysteine-phosphate-guanine CpG sites situated within the promoter region, and degrees of organismal DNA methylation are changeable depending on environmental factors. Differentially Expressed Genes and Clustering Among the and unique genes detected from normal and diabetic mouse liver samples, the number of differentially expressed genes were quantified and shown in Figure S1A. Note; some datasets might be divided into two or more groups depending on sample phenotype. Diabetes50 —

Prostate cancer. The location and the covariance parameters are estimated using robust estimation methods. Mol Cell Endocrinol. Lipids Health Dis 6, 35 The red cycle nodes represent upregulated genes and the green diamond nodes represent downregulated genes. The clinical symptoms of T2D include hyperglycemia, obesity, hypertension and hyperlipidemia.

Figure 19 shows the thresholds for 2-fold change, thereby providing the up and down regulated genes. As an example, a seed gene IL6 in the obesity cluster 1 is regulated by JUN and FOS, which is secreted by M1 macrophages, and often takes effect in promoting obesity-associated inflammation which aggravates the progression of metabolic complications, such as cardiovascular disease and insulin resistance [ 27 ]. Obesity Reviews. Soronen, P. Astolfi, S. Genes localized in Golgi transport complex, vesicle, oncostatin-M receptor complex, perikaryon were downregulated in O vs HO.

Topology and Function of the Active Subclusters By combing the differential expression profiles from multiple datasets and the NOT2D network, the top 5 scoring expressoon modules were identified in the obesity samples as well as in T2D. Moreover, LYN is a highly ranked gene with the highest differential expression percentage in the T2DM-control study Das View author publications. Out of 3, outlier genes, 1, were detected as up regulated, while were detected as down-regulated genes with respect to the healthy H individual.

The primary objective of the study of gene expression profiles using microarray is to assess the mRNA transcript levels of samples under different experimental conditions and detect significant difference in epxression levels of various genes across samples. Such variations in the expression of genes could be detected only by performing studies in a larger sample size. Naukkarinen et al. The role of MAPKs in adipocyte differentiation and obesity. Standaert, L. Red indicates that expression of the gene is relatively upregulated while green indicates that expression of the gene is relatively downregulated; black indicates no significant changes in gene expression.

Finally, there are nodes and edges in the obesity network and nodes and edges in the network of T2D. Besides weight loss, RYGB ameliorates diabetes, hyperlipidemia, and other obesity-related metabolic abnormalities [ 3031 ]. Evanko, M. The green spots are the differentially expressed outlier genes for healthy with overweight s.

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Out of 3, outlier genes, were detected as up regulated, while were detected as down-regulated genes with respect to the individual with diabetic and no parental history [ 1 ]. MA-plots showing scatter of expression values before and after Loess normalization for healthy vs. Seavey, G. Borrell, L.

Gene expression profile in obesity and type 2 diabetes mellitus (2007)

The enriched pathways of the obesity orange ellipse and T2D blue ellipse clusters are classified into three regulatory groups metabolic, immune response, and signaling and one disease-related group, which were highlighted by the colored triangles purple, blue, red, and grass green. In these subjects, a direct correlation between the due to practical constraints of cost and feasibility. Series introduction.

In addition, consistent with previous reports obewity[40]the fatty acid storage enzyme genes Elovl6Scd1GpatDgat1 and Dgat2 were markedly upregulated. In the first step, the log intensity values of the gene expression for the two samples were preprocessed using loess method, in order to remove any measurement bias in the experiment. Cope, B. Diabetes Care. J Appl Physiol96 —

Med Clin North Am. Diabetes Care. Riabetes et al. In the present study, gene expression profiles of human skeletal muscle, adipose tissue, islet, liver, blood and arterial tissue or skeletal muscle, omental adipose tissue, cumulus cells, liver, blood, and subcutaneous abdominal adipose tissue from GEO datasets were analyzed to identify the candidate genes for T2DM and obesity. Let S out and S in be the subsets of S containing outlier and inlier observations respectively.

Dismuke, and L. Leung, H. Clinical Microbiology Reviews. Mishra, and B.

1. Introduction

Trends Genet. W1, pp. Ittner, and R. The experimentally validated protein-protein interactions and transcriptional regulation of these seed genes and their neighbors were extracted from the human protein interaction database HPRD [ 16 ] Release 9 and TRANSFAC database [ 17 ] Release

  • Yates, I. Wright, C.

  • In this study, the combination of multiple differential expression profiles and a comprehensive biological network of obesity and T2D allowed us to identify and compare the disease-responsive active modules and subclusters. As a conclusion, our network-based method not only gives better support for the close connection between obesity and T2D, but also provides a systemic view in understanding the molecular functions underneath the links.

  • Protein-protein interaction network of the DEGs in type 2 diabetes mellitus.

  • Medicine and Science in Sports and Exercise.

  • Das UN: Obesity and its relationship to coronary heart dis- Kaliora, and D.

In recent times since diet control, exercise, and drugs to reduce obesity are largely unsuccessful, the Roux-en-gastric bypass RYGB and other bariatric operations are becoming one of the most common abdominal surgical procedures in the USA [ 28 ]. Kang, X. As a result, there are 16 and 12 pathways significantly enriched in these obesity and T2D active clusters with or without the seed genes Figure 4. Sultan Qaboos Univ Med J.

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Molecular Medicine Fype Sign up for eToc alerts. Moreover, we found that hepatic local immune response and liver cancer are associated with type 2 diabetes. Download: PPT. The -test for equal or unequal variances was used, depending on the -value of the tests. About this article Cite this article Das, U.

Selective disruption of hepatic resident macrophages, Kupffer cells, has been shown to be sufficient to improve hepatic insulin sensitivity in high-fat diet model [57][58]. Response to extracellular stimulus. GOCell junction. GOReceptor activity. Current Nutrition and Food Science. T2D is a highly complex multisystem disease.

Genes involved in carbohydrate ln pathways, lipid metabolism pathways, glycan biosynthesis and metabolism pathways, metabolism of cofactors and vitamins pathways, ubiquitin mediated proteolysis, signal transduction pathways, signaling molecules and interaction pathways, PPAR signaling pathway, GnRH signaling pathway, nervous system pathways, development pathways, neurodegenerative disorders pathways were upregulated in DNPH2 vs H. In contrast, genes involved in lipid and amino acid pathways, ubiquitin mediated proteolysis, signal transduction, insulin signaling and PPAR signaling pathways are downregulated in subjects with diabetes with family history of diabetes. Eur Heart Jsize. J Exp Med. Genes involved in polysaccharide metabolic process, regulation of pH, tissue development, and diuresis were upregulated both in diabetes and obesity.

Turner R. Let Sout and Sin be the subsets of S containing outlier and inlier obser- where m is the estimated multivariate location parameter vations respectively. Delplanque J. Thus, subjects who have abdominal obesity, atheroslcerosis, insulin resistance and hyperinsulinemia, hyperlipidemias, endothelial dysfunction, essential hypertension, type 2 diabetes mellitus, and coronary heart disease CHD are considered to have metabolic syndrome X. Ravasi T.

Genes involved Genes localized in CAAX-protein geranylgeranyltrans- in regulation of hormone biosynthetic process, opsoniza- ferase complex, intracellular organelle were upregulated tion were downregulated in diabetes and obesity. This is 1. Out of 3, outlier genes, were detected as up diabetes comparison. Seven genes in the T2D cluster 1 and six genes in obesity cluster 1 are involved in insulin signaling pathway, but only two genes are the same. Gehart H. Out of 3, outlier genes, 1, were detected as up regulated, while were detected as down-regulated genes with respect the healthy H individual.

Gregor M. The values larger than the critical value are treated as outliers of the distribution. Under high glucose conditions in pancreatic beta cells, PRKCB may be involved in the inhibition of insulin gene transcription [ 25 ]. Insulin resistance and human disease: a short history. This is 1.

Although genetics could play an important role in the higher prevalence of metabolic syndrome X, it is not clear how genetic factors interact with environmental and dietary factors to increase its incidence. Genes that have been up regulated in obese O compared to healthy H are:. Genes involved in regulation of isoprenoid metabolic process, blastocyst growth, regulation of glycolysis were downregulated in DPH with respect to O. Diabetes without parental history vs Normal [DNPH2 vs H] Genes involved in carbohydrate metabolism pathways, lipid metabolism pathways, glycan biosynthesis and metabolism pathways, metabolism of cofactors and vitamins pathways, ubiquitin mediated proteolysis, signal transduction pathways, signaling molecules and interaction pathways, PPAR signaling pathway, GnRH signaling pathway, nervous system pathways, development pathways, neurodegenerative disorders pathways were upregulated in DNPH2 vs H. Thus, weight loss seen in RYGB and diet control groups could be attributed to alterations in the concentrations of specific hypothalamic signaling peptides that regulate appetite, food intake and satiety.

MacDonald, and A. Computers and Geosciences. More related articles. These results emphasize the fact that weight loss seen after RYGB and diet control is due to specific changes in hypothalamic peptides.

Introduction Metabolic syndrome X is characterized by a abdominal obesity, b atherogenic dyslipidemia, c raised blood pressure, d insulin resistance with or without glucose intolerance, e pro-inflammatory state, and f prothrombin state. This approach provides the fold-change value considering the scatter of observations and thereby provides up and down regulated genes across the samples. Standaert, L. Is Type II diabetes mellitus a disease of the innate immune system? Newsholme, and A. Published 26 Dec In other words, if R out is a subset of univariate outliers and S in the subset of bivariate inliers of S, then the optimal cut-off could be obtained as.

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