Are HOMA-IR and HOMA-B good predictors for diabetes and pre-diabetes subtypes?

BACKGROUND: To investigate the association between the Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) and Homeostasis Model Assessment of Beta-cell function (HOMA-B) with the incidence of diabetes and pre-diabetes subtypes. METHODS: A total of 3101 normoglycemic people aged 20-70 years were included in the 6-year follow-up study. Multinomial logistic regression was used to calculate the incidence possibility of isolated Impaired Fasting Glucose (iIFG), isolated Impaired Glucose Tolerance (iIGT), Combined impaired fasting glucose & impaired glucose tolerance (CGI), and Diabetes Mellitus (DM) per standard deviation (SD) increment in HOMA-IR and HOMA-B in the crude and multivariable model. RESULTS: In the multivariate model, an increase in one SD change in HOMA-IR was associated with a 43, 42, 75, and 92% increased risk of iIFG, iIGT, CGI, and DM, respectively. There was a positive correlation between the increase in HOMA-B and the incidence of iIGT; however, after adjusting the results for metabolic syndrome components, it was inversely correlated with the incidence of iIFG [Odds Ratio = 0.86(0.75-0.99)]. CONCLUSIONS: HOMA-IR is positively correlated with diabetes and pre-diabetes subtypes' incidence, and HOMA-B is inversely correlated with the incidence of iIFG but positively correlated with iIGT incidence. However, none of these alone is a good criterion for predicting diabetes and pre-diabetes.

Association of Dietary Diabetes Risk Reduction Score With Risk of Cardiovascular Diseases in the Iranian Population: Tehran Lipid and Glucose Study.

BACKGROUND: There are no data available regarding the association of dietary diabetes risk reduction score (DDRRS) and risk of cardiovascular disease (CVD) worldwide. We aimed to investigate the association of the DDRRS with the risk of CVD outcomes in a prospective population-based study. METHOD: Individuals without CVD (n=2,195) were recruited from participants of the Tehran Lipid and Glucose Study (2006-2008) and followed for a mean of 6.7 years. The DDRRS was determined on the basis of eight components using a validated 168-item food frequency questionnaire. Cox proportional hazard regression models, adjusted for potential confounders, were used to estimate the hazard ratios and 95% confidence interval (CI) of CVD across quartiles of DDRRS. RESULTS: The mean ± standard deviation age of participants (44.8% male) was 38.8±13.0 years at baseline. Median DDRRS for all patients was 23 (intequartile range 20-26). During follow-up, 77 (3.5%) new cases of CVD were identified. After adjustment for confounding variables, including age, sex, body mass index, physical activity, smoking, energy intake, diabetes, and hypertension, no association was found between DDRRS and risk of CVD (odds ratio, 0.70; 95% CI, 0.36-1.37 [p-value for trend=0.351]). CONCLUSIONS: The findings of this study showed that higher DDRRS is not associated with risk of CVD events.

Introducing a panel for early detection of lung adenocarcinoma by using data integration of genomics, epigenomics, transcriptomics and proteomics.

Lung Adenocarcinoma is one of the most leading causes of death worldwide. Early detection of this cancer could enhance the survival chance of patients and even lead to better and more effective treatment. One of the approaches to find out more about biological malfunctions is using "omics" data. Among diverse computational procedures, data integration is becoming a striking tool to deal with complicated diseases such as cancer, considering the defective and informative nature of each kind of "omics" data. Data integration as relates to lung adenocarcinoma can lead to finding molecular biomarkers that could solve early-stage detection and progression prediction alongside other screening technologies like low-dose spiral computed tomography. In the present study, we hypothesized that genes with multiple variations are essential to provoke lung adenocarcinoma and one may use them to predict tumor formation or even cancer development. We integrated the genomic, epigenomic, transcriptomic and proteomic data. Consequently, five genes were introduced and validated by different analyses including classification of patients and survival analysis. Furthermore, we constructed a bipartite mRNA-miRNA network to identify a set of miRNAs for further experimental analyses. Finally, a sensitive and specific diagnostic panel comprising CDKN2A, CX3CR1, COX4I2, SLC15A2 and TFRC genes were identified for early detection of Lung Adenocarcinoma.

BAMSE: Bayesian model selection for tumor phylogeny inference among multiple samples.

BACKGROUND: Intra-tumor heterogeneity is known to contribute to cancer complexity and drug resistance. Understanding the number of distinct subclones and the evolutionary relationships between them is scientifically and clinically very important and still a challenging problem. RESULTS: In this paper, we present BAMSE (BAyesian Model Selection for tumor Evolution), a new probabilistic method for inferring subclonal history and lineage tree reconstruction of heterogeneous tumor samples. BAMSE uses somatic mutation read counts as input and can leverage multiple tumor samples accurately and efficiently. In the first step, possible clusterings of mutations into subclones are scored and a user defined number are selected for further analysis. In the next step, for each of these candidates, a list of trees describing the evolutionary relationships between the subclones is generated. These trees are sorted by their posterior probability. The posterior probability is calculated using a Bayesian model that integrates prior belief about the number of subclones, the composition of the tumor and the process of subclonal evolution. BAMSE also takes the sequencing error into account. We benchmarked BAMSE against state of the art software using simulated datasets. CONCLUSIONS: In this work we developed a flexible and fast software to reconstruct the history of a tumor's subclonal evolution using somatic mutation read counts across multiple samples. BAMSE software is implemented in Python and is available open source under GNU GLPv3 at https://github.com/HoseinT/BAMSE .

Red meat and dietary iron intakes are associated with some components of metabolic syndrome: Tehran Lipid and Glucose Study.

BACKGROUND: This study was conducted to investigate whether the daily consumption of haem, non-haem, total iron and red meat can affect the occurrence of metabolic syndrome (MetS) and its components. METHODS: Eligible adults (n = 4654) were selected from among participants of the Tehran Lipid and Glucose Study with an average follow-up of 3.8 years. Dietary intakes were assessed using a valid and reliable semi-quantitative food frequency questionnaire. Anthropometrics and biochemical variables were evaluated at baseline and follow-up examinations. The occurrence of MetS and its components were assessed in relation to haem, non-haem, total iron and red meat intakes. RESULTS: There was no relationship between different types of dietary iron and red meat intakes and the incidence of MetS in the Tehranian population. Risk of hypertension decreased from quartiles 1 to 4 for haem iron (HR: 1.00, 0.92, 0.81, 0.80, Ptrend < 0.01) and red meat intake (HR: 1.00, 0.89, 0.84, 0.77, Ptrend < 0.01). The association between hyperglycemia and the fourth quartile of total iron intake was significant (HR = 1.98, 95% CI 1.08-3.63); and the risk of high triglyceride appeared to increase in higher quartiles of total iron intake (HR: 1.00, 1.17, 1.49, 1.75, Ptrend = 0.01) compared to lower quartiles. CONCLUSION: Our study suggests a potentially protective relationship of haem and moderate red meat intake against development of high blood pressure; and higher intake of total iron is related to hyperglycemia and high triglyceride.

Risk factors for cardiovascular disease and mortality events in adults with type 2 diabetes - a 10-year follow-up: Tehran Lipid and Glucose Study.

BACKGROUND: To identify risk factors for cardiovascular disease (CVD) and mortality events in patients with type 2 diabetes and to calculate their population attributable fraction among a representative Iranian population. METHODS: A total of 1198 patients with type 2 diabetes (504 men and 694 women), aged ≥30 years, without prevalent CVD, with a median follow-up of 10 years were included in current study. To examine the association between risk factors and their outcomes, multivariate sex-adjusted Cox proportional hazard regression models were used. RESULTS: During the study, 281 and 172 participants experienced CVD and all-cause mortality events, respectively. Regarding CVD events, fasting plasma glucose (FPG) level of 7.22-<10 mmol/L [hazard ratio (HR): 1.46, 95% CI 1.12-1.96], FPG level ≥10 mmol/L (HR 2.04, 1.53-2.72), hypertension (HR 1.65, 1.28-2.13), hypercholesterolaemia (HR 1.96, 1.40-2.75) and high waist to hip ratio (HR 1.30, 0.99-1.70; p = 0.051) were significant predictors, and corresponding population attributable fractions were 9.76, 17.84, 23.26, 41.63 and 14.76%, respectively. Considering all-cause mortality events, hypertension (HR 1.70, 1.23-2.36), FPG level ≥10 mmol/L (HR 2.31, 1.55-3.20) and smoking (HR 1.45, 1.03-2.04) were significant predictors, and corresponding population attributable fractions were 25.81, 20.88 and 11.18%, respectively. Meanwhile, being overweight or obese was associated with lower all-cause and CVD mortality events. CONCLUSIONS: Among modifiable risk factors in patients with type 2 diabetes, hypercholesterolaemia and central adiposity for CVD, smoking for mortality events and hypertension and poor glycaemic control for both outcomes need to be paid most attention by healthcare professionals. Copyright © 2016 John Wiley & Sons, Ltd.

Discovering dominant pathways and signal-response relationships in signaling networks through nonparametric approaches.

A signaling pathway is a sequence of proteins and passenger molecules that transmits information from the cell surface to target molecules. Understanding signal transduction process requires detailed description of the involved pathways. Several methods and tools resolved this problem by incorporating genomic and proteomic data. However, the difficulty of obtaining prior knowledge of complex signaling networks limited the applicability of these tools. In this study, based on the simulation of signal flow in signaling network, we introduce a method for determining dominant pathways and signal response to stimulations. The model uses topology-weighted transit compartment approach and comprises four main steps which include weighting the edges, simulating signal transduction in the network (weighting the nodes), finding paths between initial and target nodes, and assigning a significance score to each path. We applied the proposed model to eighty-three signaling networks by using biologically derived source and sink molecules. The recovered dominant paths matched many known signaling pathways and suggesting a promising index to analyze the phenotype essentiality of molecule encoding paths. We also modeled the stimulus-response relations in long and short-term synaptic plasticity based on the dominant signaling pathway concept. We showed that the proposed method not only accurately determines dominant signaling pathways, but also identifies effective points of intervention in signal transduction.

Long-term thionamide antithyroid treatment of Graves' disease.

Thionamide antithyroid drugs (ATD) are the treatment of choice for Graves' hyperthyroidism. The major drawback of ATD treatment for 1-2 years is the relapse of hyperthyroidism in about 50% of patients. Recently, it has been shown that ATD treatment for more than five years is accompanied by long-term remission in majority of patients without additional major side effects in both adults and children. Compared to radioactive iodine therapy, long-term ATD results in more favorable outcomes. This review summarizes the evidence on long-term ATD therapy regarding the remission rate of hyperthyroidism, efficacy and safety, indications and mode of therapy in patients with hyperthyroidism.

Parallel molecular alteration between Alzheimer's disease and major depressive disorder in the human brain dorsolateral prefrontal cortex: an insight from gene expression and methylation profile analyses.

Alzheimer's disease (AD) and major depressive disorder (MDD) are comorbid neuropsychiatric disorders that are among the leading causes of long-term disability worldwide. Recent research has indicated the existence of parallel molecular mechanisms between AD and MDD in the dorsolateral prefrontal cortex (DLPFC). However, the premorbid history and molecular mechanisms have not yet been well characterized. In this study, differentially expressed gene (DEG), differentially co-expressed gene and protein-protein interaction (PPI) network propagation analyses were applied to gene expression data of postmortem DLPFC samples from human individuals diagnosed with and without AD or MDD (AD: cases = 310, control = 157; MDD: cases = 75, control = 161) to identify the main genes in the two disorders' specific and shared biological pathways. Subsequently, the results were evaluated using another four assessment datasets (n1 = 230, n2 = 65, n3 = 58, n4 = 48). Moreover, the postmortem DLPFC methylation status of human subjects with AD or MDD was compared using 68 and 608 samples for AD and MDD, respectively. Eight genes (XIST, RPS4Y1, DDX3Y, USP9Y, DDX3X, TMSB4Y, ZFY and E1FAY) were common DEGs in DLPFC of subjects with AD or MDD. These genes play important roles in the nervous system and the innate immune system. Furthermore, we found HSPG2, DAB2IP, ARHGAP22, TXNRD1, MYO10, SDK1 and KRT82 as common differentially methylated genes in the DLPFC of cases with AD or MDD. Finally, as evidence of shared molecular mechanisms behind this comorbidity, we propose some genes as candidate biomarkers for both AD and MDD. However, more research is required to clarify the molecular mechanisms underlying the co-existence of these two important neuropsychiatric disorders.

Idiopathic Hirsutism and Metabolic Status: A Population-based Prospective Cohort Study.

BACKGROUND: A limited number of studies have investigated the impact of idiopathic hirsutism (IH) on cardiometabolic parameters with contradictory and inconclusive results. This study aimed to explore the effect of IH on metabolic outcomes. METHOD: In this population-based prospective study, 334 women with IH and 1226 women as healthy controls were selected from Tehran Lipid and Glucose Study. The generalized estimation equations method was applied to investigate the secular longitudinal trends of metabolic indices, including fasting blood sugar (FBS), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL), non-HDL, triglyceride (TG), systolic blood pressure (SBP), diastolic blood pressure (DBP), and waist circumference (WC) in both groups. Unadjusted and adjusted Cox regression models were applied to assess the hazard ratios (HR) and 95% CIs for the association between IH and metabolic disorders. Potential confounding factors such as age, body mass index, smoking, physical activity, history of hypertension (HTN), and family history of diabetes were included in the adjusted model. RESULTS: This study showed that compared with healthy controls, women with IH had lower SHBG and higher total testosterone (median [interquartile ratio; IQR]: 0.37 [0.16-0.70] vs 0.33 [0.14-0.58]; P = 0.01), free androgen index (median [IQR]: 0.85 [0.38-1.54] vs 0.54 [0.26-0.97]; P = 0.001), androstenedione (median [IQR]: 1.60 [1.00-2.25] vs 1.10 [0.90-1.70]; P = 0.001), and dehydroepiandrosterone sulfate (median [IQR]: 168.5 [91.1-227.8] vs 125.2 [66.3-181]; P = 0.001). Over time, mean changes of FBS, HDL-C, LDL-C, non-HDL-C, TG, SBP, DBP, and WC were not significantly different in women with IH, compared with healthy controls. According to the unadjusted Cox regression model, except for type 2 diabetes mellitus (T2DM) (HR [95% CI]: 1.45 [1.00-2.11]) P = 0.05; there was no statistically significant difference in hazard of metabolic disorders (ie, HTN, pre-HTN, pre-T2DM, and metabolic syndrome) in IH, compared with healthy controls. Besides, the adjusted Cox regression model showed no significant differences in the hazard of these outcomes. CONCLUSION: This study showed no significant difference in overtime mean changes of metabolic risk factors and cardiometabolic outcomes in women with IH, compared with the healthy control group, except marginally significant difference on T2DM, which disappeared after further adjustment for potential confounders. Accordingly, routine screening of women for these metabolic outcomes should not recommend.

Effect of family history of diabetes and obesity status on lifetime risk of type 2 diabetes in the Iranian population.

Background: Data are scarce for the lifetime risk of diabetes in the Middle East and North Africa region countries. We estimated the lifetime risk of type 2 diabetes among Iranian adults at age 20 and 40 years, and their variation by family history of diabetes and body mass index (BMI). Methods: The data from 8435 diabetes-free participants from the Tehran Lipid and Glucose study were used in this analysis. We estimated the lifetime risk of diabetes stratified by sex, and quantified the impact of family history of diabetes and BMI status on the lifetime risks, singly and jointly. Results: At age 20 years, the overall lifetime risk of diabetes was 57.8% (95% CI = 54.0%-61.8%) for men and 61.3% (57.2%-65.4%) for women. Having both family history of diabetes and increased level of BMI, alone, increased the lifetime risk of diabetes in both sexes. Moreover, the simultaneous presence of family history of diabetes and overweigh/obesity increased the lifetime risk of diabetes in both sexes. So that, at age 20 years the lifetime risk in obese men with positive family history of diabetes was about 54% higher, compared to normal weight men without family history of diabetes; the corresponding value for women was 42%. Also, normal weight men without family history of diabetes lived 24 years longer free of diabetes, compared with obese men with family history of diabetes. In women, the corresponding value was 20 years. Conclusion: Our study shows the alarming lifetime risk of diabetes across the strata of BMI, which emphasizes the need for more effective interventions to reduce incidence, particularly, among individuals with positive family history of diabetes.

Determinants of the progression to type 2 diabetes and regression to normoglycemia in people with pre-diabetes: A population-based cohort study over ten years.

AIMS: To determine the rates and predictors of the regression to normoglycemia and progression to diabetes among subjects with pre-diabetes. METHODS: A 10-year longitudinal population-based study was conducted among 1329 participants with pre-diabetes in the Tehran Lipid and Glucose Study. Pre-diabetes was divided into isolated IFG (iIFG), isolated IGT (iIGT), and combined IFG/IGT. Univariate and stepwise multivariable Cox regression was used to evaluate predictors of glycemic conversions. RESULTS: The cumulative incidences of normoglycemia and diabetes were 43.7% (95%CI 40.9-46.4) and 40.1% (37.3-42.7), respectively. Isolated IGT returned to normoglycemia more than iIFG (HR:1.26, 1.05-1.51), but there was no difference in how quickly they progressed to diabetes. Regression to normoglycemia was associated with younger age, female sex, lower BMI, no familial history of diabetes, higher HDL-C, and ex-smoking. Older age, higher BMI, diastolic blood pressure, total cholesterol, lower HDL-C, and familial history for diabetes were associated with progression to diabetes. The influence of BMI on glycemic status conversions diminished with age. At approximately above 60 years old, the hazards of BMI for any conversions faded out. CONCLUSIONS: The modifiable predictors of regression to normoglycemia and progression to diabetes are roughly the same. The importance of BMI attenuates in elderly subjects.

Dietary differences between elderly Iranians living in Sweden and Iran a cross-sectional comparative study.

BACKGROUND: During the last decades, global migration has increased and many immigrant groups have a higher prevalence than the native born population of several cardiovascular disease risk factors, including poor dietary habits. However, it is uncertain if dietary habits in immigrant populations reflect dietary habits in their country of origin or if the current diet is a consequence of the migration and possible change of dietary habits. The aim of this study was to examine possible dietary differences between elderly Iranians living in Stockholm, Sweden with elderly Iranians living in Tehran, Iran, taking into account sex, age, marital status, and education. METHODS: Dietary intakes were assessed by semi--quantitative food frequency questionnaire in a cross-sectional study of 121 Iranians living in Stockholm and 52 Iranians living in Tehran, aged 60-80. Differences in dietary habits between the two groups was analysed by bootstrapped regression analyses with 1000 replications. RESULTS: Iranians living in Sweden had significantly higher intake of protein, total fat, fiber than Iranians living in Iran, but lower consumption of carbohydrates. The observed differences in intake of macronutrients were reflected in consumed amount of all food items, which were higher among Iranians living in Iran with the exception of bread and grain consumption which was lower. CONCLUSIONS: There are general differences in dietary habits between Iranians living in Iran and Iranians living in Sweden. Parts of observed differences in dietary habits may reflect a favourable adoption process to the Swedish dietary habits after migration. Meanwhile other differences are point of concern in light of the high prevalence of overweight, among Iranians living in Sweden and can have unfavourable impact in particular in the context of cardiovascular health.

National trends in cardiovascular health metrics among Iranian adults using results of three cross-sectional STEPwise approaches to surveillance surveys.

To examine the trends of 7 cardiovascular health metrics (CVH metrics) incorporate of smoking, physical activity, diet, body mass index (BMI), fasting plasma glucose (FPG), total cholesterol (TC), and blood pressure (BP) level during three cross-sectional STEPwise approaches to surveillance (STEPS), 2007-2016, among Iranian adults. The study population consisted of 19,841 women and 17,243 men, aged 20-65 years. The CVH metrics were categorized as 'ideal', 'intermediate', and 'poor'. The sex-stratified weighted prevalence rate of each CVH metrics was reported. The conditional probability of each poor versus combined intermediate and ideal metric was analyzed using logistic regression. In 2016 compared to 2007, the prevalence of poor BP level (20.4% vs. 23.7%), smoking (13.7% vs. 23.8%), TC ≥ 240 mg/dl (2.4% vs. 11.2%) and FPG < 100 mg/dl (75.6% vs. 82.3%) declined, whereas poor physical activity level (49.7% vs. 30%), poor healthy diet score (38.1% vs. 4.1%), BMI levels ≥ 25 kg/m2 (62.8% vs. 57.8%) increased. Despite a high prevalence of obesity among women, it remained constant in women but showed an increasing trend in men; moreover, the trends of low physical activity and current smoking were better for women. Despite some improvement in CVH metrics, < 4% of Iranian adults meet ≥ 6 CVH metrics in 2016; this issue needs intervention at the public health level using a multi-component strategy.

Detection of novel biomarkers for early detection of Non-Muscle-Invasive Bladder Cancer using Competing Endogenous RNA network analysis.

Bladder Cancer (BC) is one of the most common cancers in the world. Recent studies show that non-coding RNAs such as lncRNAs and circRNAs play critical roles in the progression of this cancer, but their regulatory relationships and functions are still largely unknown. As a new regulatory process within the cell, the coding and non-coding RNAs compete with each other to sponge their target miRNAs. This mechanism is described as "the competing endogenous RNA (ceRNA) hypothesis" which provides a new perspective to understand the regulation of gene expression in health and diseases such as cancer. In this study, to investigate the role of non-coding RNAs in BC, a new approach was used to reconstruct the ceRNA network for Non-Muscle Invasive Bladder Cancer (NMIBC) based on the expression data of coding and non-coding genes. Analysis of ceRNA networks in the early stage of BC led to the detection of an important module containing the lncRNA MEG3 as the central gene. The results show that the lncRNAs CARMN, FENDRR and ADAMTS9-AS2 may regulate MEG3 in NMIBC through sponging some important miRNAs such as miR-143-3p, miR-106a-5p and miR-34a-3p. Also, the lncRNA AC007608.2 is shown to be a potential BC related lncRNA for the first time based on ceRNA stage-specific network analysis. Furthermore, hub and altered genes in stage-specific and between stage networks led to the detection of hsa_circ_0017586 and hsa_circ_0001741 as novel potential circRNAs related to NMIBC. Finally, the hub genes in the networks were shown to be valuable candidates as biomarkers for the early stage diagnosis of BC.

Sequence-based 5-mers highly correlated to epigenetic modifications in genes interactions.

One of the main concerns in biology is extracting sophisticated features from DNA sequence for gene interaction determination, receiving a great deal of researchers' attention. The epigenetic modifications along with their patterns have been intensely recognized as dominant features affecting on gene expression. However, studying sequenced-based features highly correlated to this key element has remained limited. The main objective in this research was to propose a new feature highly correlated to epigenetic modifications capable of classification of genes. In this paper, classification of 34 genes in PPAR signaling pathway associated with muscle fat tissue in human was performed. Using different statistical outlier detection methods, we proposed that 5-mers highly correlated to epigenetic modifications can correctly categorize the genes involved in the same biological pathway or process. Thirty-four genes in PPAR signaling pathway were classified via applying a proposed feature, 5-mers strongly associated to 17 different epigenetic modifications. For this, diverse statistical outlier detection methods were applied to specify the group of thoroughly correlated genes. The results indicated that these 5-mers can appropriately identify correlated genes. In addition, our results corresponded to GeneMania interaction information, leading to support the suggested method. The appealing findings imply that not only epigenetic modifications but also their highly correlated 5-mers can be applied for reconstructing gene regulatory networks as supplementary data as well as other applications like physical interaction, genes prioritization, indicating some sort of data fusion in this analysis.

Evaluation of the Effectiveness of the Iralvex Gel on the Recurrent Aphthous Stomatitis Management.

Introduction. As there is no definitive treatment for the recurrent aphthous stomatitis (RAS), most of the available therapies aim at decreasing pain and discomfort. The aim of this study was to investigate the effectiveness of the Iralvex gel on the RAS management. Material and Methods. In this double-blind and placebo-controlled clinical trial study, twenty patients were treated with the Iralvex gel and the other twenty patients were treated with placebo. In every participant complete healing of lesions, pain duration, and intensity were evaluated. Data were analyzed by independent t-test and analysis of variance. Results. Pain was relieved after 6.10 ± 0.29 days in the Iralvex group in comparison to 8.00 ± 0.33 days in the placebo group (P value ≤0.001). Complete remission in the Iralvex group was after 6.80 ± 0.27 days and 10.20 ± 0.42 days in the placebo group (P value ≤ 0.001). Furthermore, significant differences in the pain intensity between Iralvex and placebo group measured on days 1, 3, and 5 were obtained (P value ≤ 0.01). Conclusion. The results of this study show that Iralvex gel is effective and cheap remedy for treatment of RAS without side effects. This trial is registered with IRCT201207253251N3.

Pathway reconstruction of airway remodeling in chronic lung diseases: a systems biology approach.

Airway remodeling is a pathophysiologic process at the clinical, cellular, and molecular level relating to chronic obstructive airway diseases such as chronic obstructive pulmonary disease (COPD), asthma and mustard lung. These diseases are associated with the dysregulation of multiple molecular pathways in the airway cells. Little progress has so far been made in discovering the molecular causes of complex disease in a holistic systems manner. Therefore, pathway and network reconstruction is an essential part of a systems biology approach to solve this challenging problem. In this paper, multiple data sources were used to construct the molecular process of airway remodeling pathway in mustard lung as a model of airway disease. We first compiled a master list of genes that change with airway remodeling in the mustard lung disease and then reconstructed the pathway by generating and merging the protein-protein interaction and the gene regulatory networks. Experimental observations and literature mining were used to identify and validate the master list. The outcome of this paper can provide valuable information about closely related chronic obstructive airway diseases which are of great importance for biologists and their future research. Reconstructing the airway remodeling interactome provides a starting point and reference for the future experimental study of mustard lung, and further analysis and development of these maps will be critical to understanding airway diseases in patients.

Reconstruction of an integrated genome-scale co-expression network reveals key modules involved in lung adenocarcinoma.

Our goal of this study was to reconstruct a "genome-scale co-expression network" and find important modules in lung adenocarcinoma so that we could identify the genes involved in lung adenocarcinoma. We integrated gene mutation, GWAS, CGH, array-CGH and SNP array data in order to identify important genes and loci in genome-scale. Afterwards, on the basis of the identified genes a co-expression network was reconstructed from the co-expression data. The reconstructed network was named "genome-scale co-expression network". As the next step, 23 key modules were disclosed through clustering. In this study a number of genes have been identified for the first time to be implicated in lung adenocarcinoma by analyzing the modules. The genes EGFR, PIK3CA, TAF15, XIAP, VAPB, Appl1, Rab5a, ARF4, CLPTM1L, SP4, ZNF124, LPP, FOXP1, SOX18, MSX2, NFE2L2, SMARCC1, TRA2B, CBX3, PRPF6, ATP6V1C1, MYBBP1A, MACF1, GRM2, TBXA2R, PRKAR2A, PTK2, PGF and MYO10 are among the genes that belong to modules 1 and 22. All these genes, being implicated in at least one of the phenomena, namely cell survival, proliferation and metastasis, have an over-expression pattern similar to that of EGFR. In few modules, the genes such as CCNA2 (Cyclin A2), CCNB2 (Cyclin B2), CDK1, CDK5, CDC27, CDCA5, CDCA8, ASPM, BUB1, KIF15, KIF2C, NEK2, NUSAP1, PRC1, SMC4, SYCE2, TFDP1, CDC42 and ARHGEF9 are present that play a crucial role in cell cycle progression. In addition to the mentioned genes, there are some other genes (i.e. DLGAP5, BIRC5, PSMD2, Src, TTK, SENP2, PSMD2, DOK2, FUS and etc.) in the modules.

The effect of community-based education for lifestyle intervention on the prevalence of metabolic syndrome and its components: tehran lipid and glucose study.

BACKGROUND: It has been shown that life style modification may decrease the prevalence of metabolic syndrome, but this intervention has not been reported in community setting. OBJECTIVES: Effect of lifestyle modification on prevalence of metabolic syndrome and its components were assessed in an urban population. MATERIALS AND METHODS: In 6870 participants of Tehran Lipid and Glucose Study aged 20-74 years, the prevalence of metabolic syndrome and its components were measured before and after a 3.6 years interval. Lifestyle intervention was employed at a community level including 2961 individuals and also 3909 subjects which were recruited as controls. Logistic regression analysis was adjusted for age, sex and medications. RESULTS: After 3.6 years, the rise in the prevalence of metabolic syndrome was less prominent in intervention than control group (P < 0.002 for increase of metabolic syndrome prevalence between groups), with an OR of 0.84 (confidence interval 0.75-0.95). After intervention the prevalence of abdominal obesity, elevated fasting glucose levels, elevated triglyceride and low HDL cholesterol were more prominent in control group, as compared to intervention group. CONCLUSIONS: Community based lifestyle modifications in Tehranian adults delayed rise in the prevalence of metabolic syndrome and some of its components.