scholarly journals Integrated omics analysis reveals sirtuin signaling is central to hepatic response to a high fructose diet

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Laura A. Cox ◽  
Jeannie Chan ◽  
Prahlad Rao ◽  
Zeeshan Hamid ◽  
Jeremy P. Glenn ◽  
...  
Keyword(s):  
Regulatory Network ◽  
Molecular Mechanisms ◽  
Statistical Significance ◽  
Molecular Networks ◽  
Integrated Analysis ◽  
Chow Diet ◽  
Vervet Monkeys ◽  
Omics Data ◽  
Obesity And Diabetes ◽  
High Fructose

Abstract Background Dietary high fructose (HFr) is a known metabolic disruptor contributing to development of obesity and diabetes in Western societies. Initial molecular changes from exposure to HFr on liver metabolism may be essential to understand the perturbations leading to insulin resistance and abnormalities in lipid and carbohydrate metabolism. We studied vervet monkeys (Clorocebus aethiops sabaeus) fed a HFr (n=5) or chow diet (n=5) for 6 weeks, and obtained clinical measures of liver function, blood insulin, cholesterol and triglycerides. In addition, we performed untargeted global transcriptomics, proteomics, and metabolomics analyses on liver biopsies to determine the molecular impact of a HFr diet on coordinated pathways and networks that differed by diet. Results We show that integration of omics data sets improved statistical significance for some pathways and networks, and decreased significance for others, suggesting that multiple omics datasets enhance confidence in relevant pathway and network identification. Specifically, we found that sirtuin signaling and a peroxisome proliferator activated receptor alpha (PPARA) regulatory network were significantly altered in hepatic response to HFr. Integration of metabolomics and miRNAs data further strengthened our findings. Conclusions Our integrated analysis of three types of omics data with pathway and regulatory network analysis demonstrates the usefulness of this approach for discovery of molecular networks central to a biological response. In addition, metabolites aspartic acid and docosahexaenoic acid (DHA), protein ATG3, and genes ATG7, and HMGCS2 link sirtuin signaling and the PPARA network suggesting molecular mechanisms for altered hepatic gluconeogenesis from consumption of a HFr diet.

scholarly journals Integrated Omics Analysis Reveals Sirtuin Signaling is Central to Hepatic Response to a High Fructose Diet

2021 ◽  
Author(s):  
Laura A. Cox ◽  
Jeannie Chan ◽  
Prahlad Rao ◽  
Zeeshan Hamid ◽  
Jeremy P. Glenn ◽  
...  
Keyword(s):  
Regulatory Network ◽  
Molecular Mechanisms ◽  
Statistical Significance ◽  
Molecular Networks ◽  
Integrated Analysis ◽  
Chow Diet ◽  
Vervet Monkeys ◽  
Omics Data ◽  
Obesity And Diabetes ◽  
High Fructose

AbstractBackgroundDietary high fructose (HFr) is a known metabolic disruptor contributing to development of obesity and diabetes in Western societies. Initial molecular changes from exposure to HFr on liver metabolism may be essential to understand the perturbations leading to insulin resistance and abnormalities in lipid and carbohydrate metabolism. We studied vervet monkeys (Clorocebus aethiops sabaeus) fed a HFr (n=5) or chow diet (n=5) for 6 weeks, and obtained clinical measures of liver function, blood insulin, cholesterol and triglycerides. In addition, we performed untargeted global transcriptomics, proteomics, and metabolomics analyses on liver biopsies to determine the molecular impact of a HFr diet on coordinated pathways and networks that differed by diet.ResultsWe show that integration of omics data sets improved statistical significance for some pathways and networks, and decreased significance for others, suggesting that multiple omics datasets enhance confidence in relevant pathway and network identification. Specifically, we found that sirtuin signaling and a peroxisome proliferator activated receptor alpha (PPARA) regulatory network were significantly altered in hepatic response to HFr. Integration of metabolomics and miRNAs data further strengthened our findings.ConclusionsOur integrated analysis of three types of omics data with pathway and regulatory network analysis demonstrates the usefulness of this approach for discovery of molecular networks central to a biological response. In addition, metabolites aspartic acid and docosahexaenoic acid (DHA), protein ATG3, and genes ATG7, HMGCS2 link sirtuin signaling and the PPARA network suggesting molecular mechanisms for altered hepatic gluconeogenesis from consumption of a HFr diet.

scholarly journals A comprehensive database for integrated analysis of omics data in autoimmune diseases

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Jordi Martorell-Marugán ◽  
Raúl López-Domínguez ◽  
Adrián García-Moreno ◽  
Daniel Toro-Domínguez ◽  
Juan Antonio Villatoro-García ◽  
...  
Keyword(s):  
Data Analysis ◽  
Autoimmune Diseases ◽  
Pathway Analysis ◽  
Molecular Mechanisms ◽  
Meta Analysis ◽  
Integrated Analysis ◽  
Omics Data ◽  
Difficult Diagnosis ◽  
Integrative Analyses ◽  
Public Repositories

Abstract Background Autoimmune diseases are heterogeneous pathologies with difficult diagnosis and few therapeutic options. In the last decade, several omics studies have provided significant insights into the molecular mechanisms of these diseases. Nevertheless, data from different cohorts and pathologies are stored independently in public repositories and a unified resource is imperative to assist researchers in this field. Results Here, we present Autoimmune Diseases Explorer (https://adex.genyo.es), a database that integrates 82 curated transcriptomics and methylation studies covering 5609 samples for some of the most common autoimmune diseases. The database provides, in an easy-to-use environment, advanced data analysis and statistical methods for exploring omics datasets, including meta-analysis, differential expression or pathway analysis. Conclusions This is the first omics database focused on autoimmune diseases. This resource incorporates homogeneously processed data to facilitate integrative analyses among studies.

Survey and comparative assessments of computational multi-omics integrative methods with multiple regulatory networks identifying distinct tumor compositions across pan-cancer data sets

2020 ◽  
Author(s):  
Zhuohui Wei ◽  
Yue Zhang ◽  
Wanlin Weng ◽  
Jiazhou Chen ◽  
Hongmin Cai
Keyword(s):  
Molecular Mechanisms ◽  
Genomic Data ◽  
Low Rank ◽  
Integrated Analysis ◽  
Data Sets ◽  
Omics Data ◽  
Data Types ◽  
Cancer Data ◽  
Cancer Types ◽  
Pan Cancer

Abstract The significance of pan-cancer categories has recently been recognized as widespread in cancer research. Pan-cancer categorizes a cancer based on its molecular pathology rather than an organ. The molecular similarities among multi-omics data found in different cancer types can play several roles in both biological processes and therapeutic developments. Therefore, an integrated analysis for various genomic data is frequently used to reveal novel genetic and molecular mechanisms. However, a variety of algorithms for multi-omics clustering have been proposed in different fields. The comparison of different computational clustering methods in pan-cancer analysis performance remains unclear. To increase the utilization of current integrative methods in pan-cancer analysis, we first provide an overview of five popular computational integrative tools: similarity network fusion, integrative clustering of multiple genomic data types (iCluster), cancer integration via multi-kernel learning (CIMLR), perturbation clustering for data integration and disease subtyping (PINS) and low-rank clustering (LRACluster). Then, a priori interactions in multi-omics data were incorporated to detect prominent molecular patterns in pan-cancer data sets. Finally, we present comparative assessments of these methods, with discussion over key issues in applying these algorithms. We found that all five methods can identify distinct tumor compositions. The pan-cancer samples can be reclassified into several groups by different proportions. Interestingly, each method can classify the tumors into categories that are different from original cancer types or subtypes, especially for ovarian serous cystadenocarcinoma (OV) and breast invasive carcinoma (BRCA) tumors. In addition, all clusters of the five computational methods show notable prognostic values. Furthermore, both the 9 recurrent differential genes and the 15 common pathway characteristics were identified across all the methods. The results and discussion can help the community select appropriate integrative tools according to different research tasks or aims in pan-cancer analysis.

scholarly journals P0168FRUCTOSE IS A CAUSE OF CALCIUM PHOSPHATE UROLITHIASIS IN RATS

2020 ◽  
Vol 35 (Supplement_3) ◽  
Author(s):  
Mariusz Flisiński ◽  
Andrzej Brymora ◽  
Natalia Skoczylas-Makowska ◽  
Anna Stefańska ◽  
Jacek Manitius
Keyword(s):  
Uric Acid ◽  
Calcium Phosphate ◽  
Kidney Stones ◽  
Statistical Significance ◽  
Dependent Manner ◽  
Kidney Tubules ◽  
High Fructose Diet ◽  
Regular Diet ◽  
Obesity And Diabetes ◽  
High Fructose

Abstract Background and Aims Excessive consumption of fructose (Fr) leads to obesity, metabolic syndrome and insulin resistance, which are known risk factors for kidney stones. Along with the epidemic of obesity and diabetes there is also a growing incidence of kidney stones in both adults and children. The epidemiological studies have shown that the relative risk of nephrolithiasis significantly increases with fructose intake in diet. The aim of the study was to assess the effect of high-fructose diet on kidney tubules disorders and predisposition to the development of kidney stones. Method Male Wistar rats were assigned for 8 weeks to 3 groups differing in the content of Fr in the diet: RD - regular diet with a fructose content <3%; F10 - regular diet with an addition of 10% Fr in drinking water; F60 - 60% Fr as a solid feed. Serum concentration of Fr, creatinine (Cr), insulin (Ins), triglycerides (Tg), homocysteine (Hcs), uric acid (UA), calcium (Ca), phosphorus (P), magnesium (Mg) were measured. Based on a 24-hour urine collection the following tests were performed: urine pH, proteinuria (PCR), excretion of N-Acetyl-(D)-Glucosaminidase (NAG), monocyte chemoattractant protein (MCP-1), uric acid (UAE), phosphorus (PE), calcium (CaE), magnesium (MgE) and sodium (NaE). The creatinine clearance (CrCl) was calculated. Calcium deposits in kidney sections were examined using H+E and von Kossa staining. Statistical analysis was performed using one-way analysis of variance ANOVA. Statistical significance was considered as p<0,05. Results The results are presented in table as mean ± SD. The rats did not differ in total calories intake in their diet. Conclusion The high-fructose diet, in a dose-dependent manner, exacerbated inflammation and induced damage to the proximal tubules. Both F10 and F60 led to hypouricosuria, hypercalciuria and hyperphosphaturia. Those disturbances, in turn, caused precipitation of calcium phosphate deposits in kidney tubules and parenchyma.

High Altitude hypoxia

2020 ◽  
Vol 17 ◽  
Author(s):  
Asma Babar ◽  
Kifayatullah Mengal ◽  
Abdul Hanan Babar ◽  
Shixin Wu ◽  
Mujahid Ali Shah ◽  
...  
Keyword(s):  
Protein Synthesis ◽  
High Altitude ◽  
Molecular Mechanisms ◽  
Strong Association ◽  
Haemoglobin Concentration ◽  
Metabolic Reprogramming ◽  
Molecular Networks ◽  
Whole Genome ◽  
Gene Expressions ◽  
Transcriptional Responses

: The world highest and largest altitude area is called the Qinghai-Tibetan plateau (QTB), which harbors unique animal and plant species. Mammals that inhabit the higher altitude regions have adapted well to the hypoxic conditions. One of the main stressors at high altitude is hypoxia. Metabolic responses to hypoxia play important roles in cell survival strategies and some diseases. However, the homeostatic alterations that equilibrate variations in the demand and supply of energy to maintain organismal function in a prolonged low O2 environment persist partly understood, making it problematic to differentiate adaptive from maladaptive responses in hypoxia. Tibetans and yaks are two perfect examples innate to the plateau for high altitude adaptation. By the scan of the whole-genome, EPAS1 and EGLN1 were identified as key genes associated with sustained haemoglobin concentration in high altitude mammals for adaptation. The yak is a much more ancient mammal which has existed on QTB longer than humans, it is, therefore, possible that natural selection represented a diverse group of genes/pathways in yaks. Physiological characteristics are extremely informative in revealing molecular networks associated with inherited adaptation, in addition to the whole-genome adaptive changes at the DNA sequence level. Gene-expression can be changed by a variety of signals originating from the environment, and hypoxia is the main factor amongst them. The hypoxia-inducible factors (HIF-1α and EPAS1/HIF-2α) are the main regulators of oxygen in homeostasis which play a role as maestro regulators of adaptation in hypoxic reaction of molecular mechanisms. (Vague) The basis of this review is to present recent information regarding the molecular mechanism involved in hypoxia that regulates candidate genes and proteins. Many transcriptional responses toward hypoxia are facilitated by HIFs that change the number of gene expressions and help in angiogenesis, erythropoiesis, metabolic reprogramming and metastasis. HIFs also activate several signals highlighting a strong association between hypoxia, the misfolded proteins’ accumulation in the endoplasmic reticulum in stress and activation of unfolded protein response (UPR). It was observed that at high-altitude, pregnancies yield a low birth weight ∼100 g per1000 m of the climb. (Vague) It may involve variation in the events of energy-demanding, like protein synthesis. Prolonged hypobaric hypoxia causes placental ER stress, which in turn, moderates protein synthesis and reduces proliferation. Further, Cardiac hypertrophy by cytosolic Ca2+ raises and Ca2+/calmodulin, calcineurin stimulation, NF-AT3 pathway might be caused by an imbalance in Sarcoplasmic reticulum ER Ca2, might be adaptive in beginning but severe later.

scholarly journals A Detailed Catalogue of Multi-Omics Methodologies for Identification of Putative Biomarkers and Causal Molecular Networks in Translational Cancer Research

2021 ◽  
Vol 22 (6) ◽  
pp. 2822
Author(s):  
Efstathios Iason Vlachavas ◽  
Jonas Bohn ◽  
Frank Ückert ◽  
Sylvia Nürnberg
Keyword(s):  
Cancer Research ◽  
Clinical Information ◽  
Disease Diagnosis ◽  
Molecular Data ◽  
Molecular Networks ◽  
Biological Knowledge ◽  
Omics Data ◽  
Translational Cancer Research ◽  
Using Data ◽  
Biological Entities

Recent advances in sequencing and biotechnological methodologies have led to the generation of large volumes of molecular data of different omics layers, such as genomics, transcriptomics, proteomics and metabolomics. Integration of these data with clinical information provides new opportunities to discover how perturbations in biological processes lead to disease. Using data-driven approaches for the integration and interpretation of multi-omics data could stably identify links between structural and functional information and propose causal molecular networks with potential impact on cancer pathophysiology. This knowledge can then be used to improve disease diagnosis, prognosis, prevention, and therapy. This review will summarize and categorize the most current computational methodologies and tools for integration of distinct molecular layers in the context of translational cancer research and personalized therapy. Additionally, the bioinformatics tools Multi-Omics Factor Analysis (MOFA) and netDX will be tested using omics data from public cancer resources, to assess their overall robustness, provide reproducible workflows for gaining biological knowledge from multi-omics data, and to comprehensively understand the significantly perturbed biological entities in distinct cancer types. We show that the performed supervised and unsupervised analyses result in meaningful and novel findings.

scholarly journals Comprehensive Analysis of Transcriptome and Metabolome Reveals the Flavonoid Metabolic Pathway Is Associated with Fruit Peel Coloration of Melon

Molecules ◽  
2021 ◽  
Vol 26 (9) ◽  
pp. 2830
Author(s):  
Aiai Zhang ◽  
Jing Zheng ◽  
Xuemiao Chen ◽  
Xueyin Shi ◽  
Huaisong Wang ◽  
...  
Keyword(s):  
Molecular Mechanisms ◽  
Comprehensive Analysis ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Fruit Peel ◽  
External Quality ◽  
Color Formation ◽  
Peel Color ◽  
Dark Green

The peel color is an important external quality of melon fruit. To explore the mechanisms of melon peel color formation, we performed an integrated analysis of transcriptome and metabolome with three different fruit peel samples (grey-green ‘W’, dark-green ‘B’, and yellow ‘H’). A total of 40 differentially expressed flavonoids were identified. Integrated transcriptomic and metabolomic analyses revealed that flavonoid biosynthesis was associated with the fruit peel coloration of melon. Twelve differentially expressed genes regulated flavonoids synthesis. Among them, nine (two 4CL, F3H, three F3′H, IFS, FNS, and FLS) up-regulated genes were involved in the accumulation of flavones, flavanones, flavonols, and isoflavones, and three (2 ANS and UFGT) down-regulated genes were involved in the accumulation of anthocyanins. This study laid a foundation to understand the molecular mechanisms of melon peel coloration by exploring valuable genes and metabolites.

scholarly journals Early alterations of neurovascular unit in the retina in mouse models of tauopathy

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Fan Xia ◽  
Yonju Ha ◽  
Shuizhen Shi ◽  
Yi Li ◽  
Shengguo Li ◽  
...  
Keyword(s):  
Transgenic Mice ◽  
Mouse Models ◽  
Molecular Mechanisms ◽  
Early Stage ◽  
Leukocyte Adhesion ◽  
Neurovascular Unit ◽  
Integrated Analysis ◽  
Therapeutic Effects ◽  
Retinal Ganglion ◽  
Potential Biomarker

AbstractThe retina, as the only visually accessible tissue in the central nervous system, has attracted significant attention for evaluating it as a biomarker for neurodegenerative diseases. Yet, most of studies focus on characterizing the loss of retinal ganglion cells (RGCs) and degeneration of their axons. There is no integrated analysis addressing temporal alterations of different retinal cells in the neurovascular unit (NVU) in particular retinal vessels. Here we assessed NVU changes in two mouse models of tauopathy, P301S and P301L transgenic mice overexpressing the human tau mutated gene, and evaluated the therapeutic effects of a tau oligomer monoclonal antibody (TOMA). We found that retinal edema and breakdown of blood–retina barrier were observed at the very early stage of tauopathy. Leukocyte adhesion/infiltration, and microglial recruitment/activation were constantly increased in the retinal ganglion cell layer of tau transgenic mice at different ages, while Müller cell gliosis was only detected in relatively older tau mice. Concomitantly, the number and function of RGCs progressively decreased during aging although they were not considerably altered in the very early stage of tauopathy. Moreover, intrinsically photosensitive RGCs appeared more sensitive to tauopathy. Remarkably, TOMA treatment in young tau transgenic mice significantly attenuated vascular leakage, inflammation and RGC loss. Our data provide compelling evidence that abnormal tau accumulation can lead to pathology in the retinal NVU, and vascular alterations occur more manifest and earlier than neurodegeneration in the retina. Oligomeric tau-targeted immunotherapy has the potential to treat tau-induced retinopathies. These data suggest that retinal NVU may serve as a potential biomarker for diagnosis and staging of tauopathy as well as a platform to study the molecular mechanisms of neurodegeneration.

Integrated analysis of miRNA and mRNA transcriptomic reveals antler growth regulatory network

2021 ◽  
Author(s):  
Boyin Jia ◽  
Linlin Zhang ◽  
Yifan Zhang ◽  
Chenxia Ge ◽  
Fuhe Yang ◽  
...  
Keyword(s):  
Regulatory Network ◽  
Integrated Analysis ◽  
Antler Growth
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