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Shi C, Cheng L, Yu Y, Chen S, Dai Y, Yang J, Zhang H, Chen J, Geng N. Multi-omics Integration Analysis: Tools and Applications in Environmental Toxicology. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024:124675. [PMID: 39103035 DOI: 10.1016/j.envpol.2024.124675] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2024] [Revised: 07/08/2024] [Accepted: 08/03/2024] [Indexed: 08/07/2024]
Abstract
Nowadays, traditional single-omics study is not enough to explain the causality between molecular alterations and toxicity endpoints for environmental pollutants. With the development of high-throughput sequencing technology and high-resolution mass spectrometry technology, the integrative analysis of multi-omics has become an efficient strategy to understand holistic biological mechanisms and to uncover the regulation network in specific biological processes. This review summarized sample preparation methods, integration analysis tools and the application of multi-omics integration analyses in environmental toxicology field. Currently, omics methods have been widely applied being as the sensitivity of early biological response, especially for low-dose and long-term exposure to environmental pollutants. Integrative omics can reveal the overall changes of genes, proteins, and/or metabolites in the cells, tissues or organisms, which provide new insights into revealing the overall toxicity effects, screening the toxic targets, and exploring the underlying molecular mechanism of pollutants.
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Affiliation(s)
- Chengcheng Shi
- CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China; College of Environmental Science and Engineering, Dalian Maritime University, Dalian, 116026, China
| | - Lin Cheng
- CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China
| | - Ying Yu
- College of Environmental Science and Engineering, Dalian Maritime University, Dalian, 116026, China
| | - Shuangshuang Chen
- CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China; College of Environmental Science and Engineering, Dalian Maritime University, Dalian, 116026, China
| | - Yubing Dai
- CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China
| | - Jiajia Yang
- CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China; College of Materials Science and Engineering, Hebei University of Engineering, Handan, 056038, China
| | - Haijun Zhang
- CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China
| | - Jiping Chen
- CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China
| | - Ningbo Geng
- CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China.
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Liu C, Wang Y, Wu Z, Tang X, Wang G, Wang J. Exploration of effective biomarkers for venous thrombosis embolism in Behçet's disease based on comprehensive bioinformatics analysis. Sci Rep 2024; 14:15884. [PMID: 38987624 PMCID: PMC11236978 DOI: 10.1038/s41598-024-66973-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2024] [Accepted: 07/05/2024] [Indexed: 07/12/2024] Open
Abstract
Behçet's disease (BD) is a multifaceted autoimmune disorder affecting multiple organ systems. Vascular complications, such as venous thromboembolism (VTE), are highly prevalent, affecting around 50% of individuals diagnosed with BD. This study aimed to identify potential biomarkers for VTE in BD patients. Three microarray datasets (GSE209567, GSE48000, GSE19151) were retrieved for analysis. Differentially expressed genes (DEGs) associated with VTE in BD were identified using the Limma package and weighted gene co-expression network analysis (WGCNA). Subsequently, potential diagnostic genes were explored through protein-protein interaction (PPI) network analysis and machine learning algorithms. A receiver operating characteristic (ROC) curve and a nomogram were constructed to evaluate the diagnostic performance for VTE in BD patients. Furthermore, immune cell infiltration analyses and single-sample gene set enrichment analysis (ssGSEA) were performed to investigate potential underlying mechanisms. Finally, the efficacy of listed drugs was assessed based on the identified signature genes. The limma package and WGCNA identified 117 DEGs related to VTE in BD. A PPI network analysis then selected 23 candidate hub genes. Four DEGs (E2F1, GATA3, HDAC5, and MSH2) were identified by intersecting gene sets from three machine learning algorithms. ROC analysis and nomogram construction demonstrated high diagnostic accuracy for these four genes (AUC: 0.816, 95% CI: 0.723-0.909). Immune cell infiltration analysis revealed a positive correlation between dysregulated immune cells and the four hub genes. ssGSEA provided insights into potential mechanisms underlying VTE development and progression in BD patients. Additionally, therapeutic agent screening identified potential drugs targeting the four hub genes. This study employed a systematic approach to identify four potential hub genes (E2F1, GATA3, HDAC5, and MSH2) and construct a nomogram for VTE diagnosis in BD. Immune cell infiltration analysis revealed dysregulation, suggesting potential macrophage involvement in VTE development. ssGSEA provided insights into potential mechanisms underlying BD-induced VTE, and potential therapeutic agents were identified.
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Affiliation(s)
- Chunjiang Liu
- Division of Vascular Surgery, Department of General Surgery, Shaoxing People's Hospital, Shaoxing, 312000, China
| | - Yuan Wang
- Department of Intervention Vascular, Hefei Hospital of Anhui Medical University, Hefei, 230000, China
| | - Zhifeng Wu
- Division of Vascular Surgery, Department of General Surgery, Shaoxing People's Hospital, Shaoxing, 312000, China
- Medical College, Shaoxing University, Shaoxing, 312000, China
| | - Xiaoqi Tang
- Division of Vascular Surgery, Department of General Surgery, Shaoxing People's Hospital, Shaoxing, 312000, China
| | - Guohua Wang
- Division of Vascular Surgery, Department of General Surgery, Shaoxing People's Hospital, Shaoxing, 312000, China
| | - Jiajia Wang
- Department of Rheumatology, Shaoxing People's Hospital, 568# Zhongxing North Road, Shaoxing, 312000, China.
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Halema AA, El-Beltagi HS, Al-Dossary O, Alsubaie B, Henawy AR, Rezk AA, Almutairi HH, Mohamed AA, Elarabi NI, Abdelhadi AA. Omics technology draws a comprehensive heavy metal resistance strategy in bacteria. World J Microbiol Biotechnol 2024; 40:193. [PMID: 38709343 DOI: 10.1007/s11274-024-04005-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Accepted: 04/24/2024] [Indexed: 05/07/2024]
Abstract
The rapid industrial revolution significantly increased heavy metal pollution, becoming a major global environmental concern. This pollution is considered as one of the most harmful and toxic threats to all environmental components (air, soil, water, animals, and plants until reaching to human). Therefore, scientists try to find a promising and eco-friendly technique to solve this problem i.e., bacterial bioremediation. Various heavy metal resistance mechanisms were reported. Omics technologies can significantly improve our understanding of heavy metal resistant bacteria and their communities. They are a potent tool for investigating the adaptation processes of microbes in severe conditions. These omics methods provide unique benefits for investigating metabolic alterations, microbial diversity, and mechanisms of resistance of individual strains or communities to harsh conditions. Starting with genome sequencing which provides us with complete and comprehensive insight into the resistance mechanism of heavy metal resistant bacteria. Moreover, genome sequencing facilitates the opportunities to identify specific metal resistance genes, operons, and regulatory elements in the genomes of individual bacteria, understand the genetic mechanisms and variations responsible for heavy metal resistance within and between bacterial species in addition to the transcriptome, proteome that obtain the real expressed genes. Moreover, at the community level, metagenome, meta transcriptome and meta proteome participate in understanding the microbial interactive network potentially novel metabolic pathways, enzymes and gene species can all be found using these methods. This review presents the state of the art and anticipated developments in the use of omics technologies in the investigation of microbes used for heavy metal bioremediation.
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Affiliation(s)
- Asmaa A Halema
- Genetics Department, Faculty of Agriculture, Cairo University, Giza, 12613, Egypt
| | - Hossam S El-Beltagi
- Agricultural Biotechnology Department, College of Agriculture and Food Sciences, King Faisal University, Al-Ahsa, 31982, Saudi Arabia.
- Biochemistry Department, Faculty of Agriculture, Cairo University, Giza, 12613, Egypt.
| | - Othman Al-Dossary
- Agricultural Biotechnology Department, College of Agriculture and Food Sciences, King Faisal University, Al-Ahsa, 31982, Saudi Arabia
| | - Bader Alsubaie
- Agricultural Biotechnology Department, College of Agriculture and Food Sciences, King Faisal University, Al-Ahsa, 31982, Saudi Arabia
| | - Ahmed R Henawy
- Microbiology Department, Faculty of Agriculture, Cairo University, Giza, 12613, Egypt
| | - Adel A Rezk
- Agricultural Biotechnology Department, College of Agriculture and Food Sciences, King Faisal University, Al-Ahsa, 31982, Saudi Arabia
- Plant Virology Department, Plant Pathology Research Institute, Agriculture Research Center, Giza, 12619, Egypt
| | - Hayfa Habes Almutairi
- Chemistry Department, College of Science, King Faisal University, Al-Ahsa, 31982, Saudi Arabia
| | - Amal A Mohamed
- Chemistry Dept, Al-Leith University College, Umm Al-Qura University, P.O. Box 6725- 21955, Makkah, Saudi Arabia
| | - Nagwa I Elarabi
- Genetics Department, Faculty of Agriculture, Cairo University, Giza, 12613, Egypt
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Li X, Xiang S, Li G. Application of artificial intelligence in brain arteriovenous malformations: Angioarchitectures, clinical symptoms and prognosis prediction. Interv Neuroradiol 2024:15910199241238798. [PMID: 38515371 DOI: 10.1177/15910199241238798] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/23/2024] Open
Abstract
BACKGROUND Artificial intelligence (AI) has rapidly advanced in the medical field, leveraging its intelligence and automation for the management of various diseases. Brain arteriovenous malformations (AVM) are particularly noteworthy, experiencing rapid development in recent years and yielding remarkable results. This paper aims to summarize the applications of AI in the management of AVMs management. METHODS Literatures published in PubMed during 1999-2022, discussing AI application in AVMs management were reviewed. RESULTS AI algorithms have been applied in various aspects of AVM management, particularly in machine learning and deep learning models. Automatic lesion segmentation or delineation is a promising application that can be further developed and verified. Prognosis prediction using machine learning algorithms with radiomic-based analysis is another meaningful application. CONCLUSIONS AI has been widely used in AVMs management. This article summarizes the current research progress, limitations and future research directions.
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Affiliation(s)
- Xiangyu Li
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Sishi Xiang
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Guilin Li
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
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Mengelkoch S, Miryam Schüssler-Fiorenza Rose S, Lautman Z, Alley JC, Roos LG, Ehlert B, Moriarity DP, Lancaster S, Snyder MP, Slavich GM. Multi-omics approaches in psychoneuroimmunology and health research: Conceptual considerations and methodological recommendations. Brain Behav Immun 2023; 114:475-487. [PMID: 37543247 PMCID: PMC11195542 DOI: 10.1016/j.bbi.2023.07.022] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 07/04/2023] [Accepted: 07/30/2023] [Indexed: 08/07/2023] Open
Abstract
The field of psychoneuroimmunology (PNI) has grown substantially in both relevance and prominence over the past 40 years. Notwithstanding its impressive trajectory, a majority of PNI studies are still based on a relatively small number of analytes. To advance this work, we suggest that PNI, and health research in general, can benefit greatly from adopting a multi-omics approach, which involves integrating data across multiple biological levels (e.g., the genome, proteome, transcriptome, metabolome, lipidome, and microbiome/metagenome) to more comprehensively profile biological functions and relate these profiles to clinical and behavioral outcomes. To assist investigators in this endeavor, we provide an overview of multi-omics research, highlight recent landmark multi-omics studies investigating human health and disease risk, and discuss how multi-omics can be applied to better elucidate links between psychological, nervous system, and immune system activity. In doing so, we describe how to design high-quality multi-omics studies, decide which biological samples (e.g., blood, stool, urine, saliva, solid tissue) are most relevant, incorporate behavioral and wearable sensing data into multi-omics research, and understand key data quality, integration, analysis, and interpretation issues. PNI researchers are addressing some of the most interesting and important questions at the intersection of psychology, neuroscience, and immunology. Applying a multi-omics approach to this work will greatly expand the horizon of what is possible in PNI and has the potential to revolutionize our understanding of mind-body medicine.
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Affiliation(s)
- Summer Mengelkoch
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, CA, USA.
| | | | - Ziv Lautman
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Jenna C Alley
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, CA, USA
| | - Lydia G Roos
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, CA, USA
| | - Benjamin Ehlert
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Daniel P Moriarity
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, CA, USA
| | | | | | - George M Slavich
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, CA, USA.
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Fiocchi C. Omics and Multi-Omics in IBD: No Integration, No Breakthroughs. Int J Mol Sci 2023; 24:14912. [PMID: 37834360 PMCID: PMC10573814 DOI: 10.3390/ijms241914912] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 09/27/2023] [Accepted: 10/02/2023] [Indexed: 10/15/2023] Open
Abstract
The recent advent of sophisticated technologies like sequencing and mass spectroscopy platforms combined with artificial intelligence-powered analytic tools has initiated a new era of "big data" research in various complex diseases of still-undetermined cause and mechanisms. The investigation of these diseases was, until recently, limited to traditional in vitro and in vivo biological experimentation, but a clear switch to in silico methodologies is now under way. This review tries to provide a comprehensive assessment of state-of-the-art knowledge on omes, omics and multi-omics in inflammatory bowel disease (IBD). The notion and importance of omes, omics and multi-omics in both health and complex diseases like IBD is introduced, followed by a discussion of the various omics believed to be relevant to IBD pathogenesis, and how multi-omics "big data" can generate new insights translatable into useful clinical tools in IBD such as biomarker identification, prediction of remission and relapse, response to therapy, and precision medicine. The pitfalls and limitations of current IBD multi-omics studies are critically analyzed, revealing that, regardless of the types of omes being analyzed, the majority of current reports are still based on simple associations of descriptive retrospective data from cross-sectional patient cohorts rather than more powerful longitudinally collected prospective datasets. Given this limitation, some suggestions are provided on how IBD multi-omics data may be optimized for greater clinical and therapeutic benefit. The review concludes by forecasting the upcoming incorporation of multi-omics analyses in the routine management of IBD.
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Affiliation(s)
- Claudio Fiocchi
- Department of Inflammation & Immunity, Lerner Research Institute, Cleveland, OH 44195, USA;
- Department of Gastroenterology, Hepatology and Nutrition, Digestive Disease and Surgery Institute, Cleveland Clinic, Cleveland, OH 44195, USA
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7
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Corral-Jara KF, Nuthikattu S, Rutledge J, Villablanca A, Fong R, Heiss C, Ottaviani JI, Milenkovic D. Structurally related (-)-epicatechin metabolites and gut microbiota derived metabolites exert genomic modifications via VEGF signaling pathways in brain microvascular endothelial cells under lipotoxic conditions: Integrated multi-omic study. J Proteomics 2022; 263:104603. [PMID: 35568144 DOI: 10.1016/j.jprot.2022.104603] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 04/04/2022] [Accepted: 04/25/2022] [Indexed: 12/12/2022]
Abstract
Dysfunction of blood-brain barrier formed by endothelial cells of cerebral blood vessels, plays a key role in development of neurodegenerative disorders. Epicatechin exerts vasculo-protective effects through genomic modifications, however molecular mechanisms of action, particularly on brain endothelial cells, are largely unknow. This study aimed to use a multi-omic approach (transcriptomics of mRNA, miRNAs and lncRNAs, and proteomics), to provide novel in-depth insights into molecular mechanisms of how metabolites affect brain endothelial cells under lipid-stressed (as a model of BBB dysfunction) at physiological concentrations. We showed that metabolites can simultaneously modulate expression of protein-coding, non-coding genes and proteins. Integrative analysis revealed interactions between different types of RNAs and form functional groups of genes involved in regulation of processing like VEGF-related functions, cell signaling, cell adhesion and permeability. Molecular modeling of genomics data predicted that metabolites decrease endothelial cell permeability, increased by lipotoxic stress. Correlation analysis between genomic modifications observed and genomic signature of patients with vascular dementia and Alzheimer's diseases showed opposite gene expression changes. Taken together, this study describes for the first time a multi-omic mechanism of action by which (-)-epicatechin metabolites could preserve brain vascular endothelial cell integrity and reduce the risk of neurodegenerative diseases. SIGNIFICANCE: Dysfunction of the blood-brain barrier (BBB), characterized by dysfunction of endothelial cells of cerebral blood vessels, result in an increase in permeability and neuroinflammation which constitute a key factor in the development neurodegenerative disorders. Even though it is suggested that polyphenols can prevent or delay the development of these disorders, their impact on brain endothelial cells and underlying mechanisms of actions are unknow. This study aimed to use a multi-omic approach including analysis of expression of mRNA, microRNA, long non-coding RNAs, and proteins to provide novel global in-depth insights into molecular mechanisms of how (-)-epicatechin metabolites affect brain microvascular endothelial cells under lipid-stressed (as a model of BBB dysfunction) at physiological relevant conditions. The results provide basis of knowledge on the capacity of polyphenols to prevent brain endothelial dysfunction and consequently neurodegenerative disorders.
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Affiliation(s)
| | - Saivageethi Nuthikattu
- Division of Cardiovascular Medicine, University of California Davis, 95616 Davis, CA, USA
| | - John Rutledge
- Division of Cardiovascular Medicine, University of California Davis, 95616 Davis, CA, USA
| | - Amparo Villablanca
- Division of Cardiovascular Medicine, University of California Davis, 95616 Davis, CA, USA
| | - Reedmond Fong
- Department of Nutrition, University of California Davis, 95616 Davis, CA, USA
| | - Christian Heiss
- Clinical Medicine Section, Department of Clinical and Experimental Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom; Vascular Department, Surrey and Sussex NHS Healthcare Trust, East Surrey Hospital, Redhill, United Kingdom
| | | | - Dragan Milenkovic
- Department of Nutrition, University of California Davis, 95616 Davis, CA, USA; Université Clermont Auvergne, INRAE, UNH, F-63000 Clermont-Ferrand, France.
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Benevenuto RF, Venter HJ, Zanatta CB, Nodari RO, Agapito-Tenfen SZ. Alterations in genetically modified crops assessed by omics studies: Systematic review and meta-analysis. Trends Food Sci Technol 2022. [DOI: 10.1016/j.tifs.2022.01.002] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
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Williams EG, Pfister N, Roy S, Statzer C, Haverty J, Ingels J, Bohl C, Hasan M, Čuklina J, Bühlmann P, Zamboni N, Lu L, Ewald CY, Williams RW, Aebersold R. Multiomic profiling of the liver across diets and age in a diverse mouse population. Cell Syst 2022; 13:43-57.e6. [PMID: 34666007 PMCID: PMC8776606 DOI: 10.1016/j.cels.2021.09.005] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Revised: 07/12/2021] [Accepted: 09/14/2021] [Indexed: 01/21/2023]
Abstract
We profiled the liver transcriptome, proteome, and metabolome in 347 individuals from 58 isogenic strains of the BXD mouse population across age (7 to 24 months) and diet (low or high fat) to link molecular variations to metabolic traits. Several hundred genes are affected by diet and/or age at the transcript and protein levels. Orthologs of two aging-associated genes, St7 and Ctsd, were knocked down in C. elegans, reducing longevity in wild-type and mutant long-lived strains. The multiomics data were analyzed as segregating gene networks according to each independent variable, providing causal insight into dietary and aging effects. Candidates were cross-examined in an independent diversity outbred mouse liver dataset segregating for similar diets, with ∼80%-90% of diet-related candidate genes found in common across datasets. Together, we have developed a large multiomics resource for multivariate analysis of complex traits and demonstrate a methodology for moving from observational associations to causal connections.
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Affiliation(s)
- Evan G Williams
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg.
| | - Niklas Pfister
- Department of Mathematical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Suheeta Roy
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Cyril Statzer
- Department of Health Sciences and Technology, ETH Zürich, Zurich, Switzerland
| | - Jack Haverty
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Jesse Ingels
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Casey Bohl
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Moaraj Hasan
- Department of Biology, Institute of Molecular Systems Biology, ETH Zürich, Zurich, Switzerland
| | - Jelena Čuklina
- Department of Biology, Institute of Molecular Systems Biology, ETH Zürich, Zurich, Switzerland
| | - Peter Bühlmann
- Department of Mathematics, Seminar for Statistics, ETH Zürich, Zurich, Switzerland
| | - Nicola Zamboni
- Department of Biology, Institute of Molecular Systems Biology, ETH Zürich, Zurich, Switzerland
| | - Lu Lu
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Collin Y Ewald
- Department of Health Sciences and Technology, ETH Zürich, Zurich, Switzerland
| | - Robert W Williams
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Ruedi Aebersold
- Department of Biology, Institute of Molecular Systems Biology, ETH Zürich, Zurich, Switzerland; Faculty of Science, University of Zürich, Zurich, Switzerland
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Hill MM, Gerner C. Integrative Multi-Omics in Biomedical Research. Biomolecules 2021; 11:biom11101527. [PMID: 34680160 PMCID: PMC8534182 DOI: 10.3390/biom11101527] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Accepted: 10/08/2021] [Indexed: 12/01/2022] Open
Affiliation(s)
- Michelle M. Hill
- QIMR Berghofer Medical Research Institute, Herston, Brisbane, QLD 4006, Australia
- UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Herston, Brisbane, QLD 4006, Australia
- Correspondence:
| | - Christopher Gerner
- Department of Analytical Chemistry, University of Vienna, 1090 Vienna, Austria;
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11
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Multi-Omics Analysis to Generate Hypotheses for Mild Health Problems in Monkeys. Metabolites 2021; 11:metabo11100701. [PMID: 34677416 PMCID: PMC8538200 DOI: 10.3390/metabo11100701] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 09/28/2021] [Accepted: 10/09/2021] [Indexed: 11/17/2022] Open
Abstract
Certain symptoms associated with mild sickness and lethargy have not been categorized as definitive diseases. Confirming such symptoms in captive monkeys (Macaca fascicularis, known as cynomolgus monkeys) can be difficult; however, it is possible to observe and analyze their feces. In this study, we investigated the relationship between stool state and various omics data by considering objective and quantitative values of stool water content as a phenotype for analysis. By examining the food intake of the monkeys and assessing their stool, urine, and plasma, we attempted to obtain a comprehensive understanding of the health status of individual monkeys and correlate it with the stool condition. Our metabolomics data strongly suggested that many lipid-related metabolites were correlated with the stool water content. The lipidomic analysis revealed the involvement of saturated and oxidized fatty acids, metallomics revealed the contribution of selenium (a bio-essential trace element), and intestinal microbiota analysis revealed the association of several bacterial species with the stool water content. Based on our results, we hypothesize that the redox imbalance causes minor health problems. However, it is not possible to make a definite conclusion using multi-omics alone, and other hypotheses could be proposed.
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12
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Sanghi A, Gruber JJ, Metwally A, Jiang L, Reynolds W, Sunwoo J, Orloff L, Chang HY, Kasowski M, Snyder MP. Chromatin accessibility associates with protein-RNA correlation in human cancer. Nat Commun 2021; 12:5732. [PMID: 34593797 PMCID: PMC8484618 DOI: 10.1038/s41467-021-25872-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2020] [Accepted: 08/24/2021] [Indexed: 11/19/2022] Open
Abstract
Although alterations in chromatin structure are known to exist in tumors, how these alterations relate to molecular phenotypes in cancer remains to be demonstrated. Multi-omics profiling of human tumors can provide insight into how alterations in chromatin structure are propagated through the pathway of gene expression to result in malignant protein expression. We applied multi-omics profiling of chromatin accessibility, RNA abundance, and protein abundance to 36 human thyroid cancer primary tumors, metastases, and patient-match normal tissue. Through quantification of chromatin accessibility associated with active transcription units and global protein expression, we identify a local chromatin structure that is highly correlated with coordinated RNA and protein expression. In particular, we identify enhancers located within gene-bodies as predictive of correlated RNA and protein expression, that is independent of overall transcriptional activity. To demonstrate the generalizability of these findings we also identify similar results in an independent cohort of human breast cancers. Taken together, these analyses suggest that local enhancers, rather than distal enhancers, are likely most predictive of cancer gene expression phenotypes. This allows for identification of potential targets for cancer therapeutic approaches and reinforces the utility of multi-omics profiling as a methodology to understand human disease.
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Affiliation(s)
- Akshay Sanghi
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Joshua J Gruber
- Department of Genetics, Stanford University, Stanford, CA, USA
- Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Ahmed Metwally
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Lihua Jiang
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Warren Reynolds
- Center for Personal Dynamic Regulomes and HHMI, Stanford University, Stanford, USA
| | - John Sunwoo
- Division of Head and Neck Surgery, Department of Otolaryngology, Stanford University School of Medicine, Stanford, CA, USA
| | - Lisa Orloff
- Division of Head and Neck Surgery, Department of Otolaryngology, Stanford University School of Medicine, Stanford, CA, USA
| | - Howard Y Chang
- Department of Genetics, Stanford University, Stanford, CA, USA
- Center for Personal Dynamic Regulomes and HHMI, Stanford University, Stanford, USA
| | - Maya Kasowski
- Department of Genetics, Stanford University, Stanford, CA, USA
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Sean N. Parker Center for Allergy and Asthma Research at Stanford University, Stanford University, Stanford, CA, USA
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Chen LK. Machine Learning Improves Analysis of Multi-Omics Data in Aging Research and Geroscience. Arch Gerontol Geriatr 2021; 93:104360. [PMID: 33546901 DOI: 10.1016/j.archger.2021.104360] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Affiliation(s)
- Liang-Kung Chen
- Aging and Health Research Center, National Yang Ming University, Taipei, Taiwan; Center for Geriatrics and Gerontology, Taipei Veterans General Hospital, Taipei, Taiwan.
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