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Verma M, Hontecillas R, Tubau-Juni N, Abedi V, Bassaganya-Riera J. Challenges in Personalized Nutrition and Health. Front Nutr 2018; 5:117. [PMID: 30555829 PMCID: PMC6281760 DOI: 10.3389/fnut.2018.00117] [Citation(s) in RCA: 48] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2018] [Accepted: 11/14/2018] [Indexed: 12/11/2022] Open
Affiliation(s)
- Meghna Verma
- Nutritional Immunology and Molecular Medicine Laboratory, Biocomplexity Institute of Virginia Tech, Blacksburg, VA, United States.,Graduate Program in Translational Biology, Medicine and Health, Virginia Tech, Blacksburg, VA, United States
| | - Raquel Hontecillas
- Nutritional Immunology and Molecular Medicine Laboratory, Biocomplexity Institute of Virginia Tech, Blacksburg, VA, United States
| | - Nuria Tubau-Juni
- Nutritional Immunology and Molecular Medicine Laboratory, Biocomplexity Institute of Virginia Tech, Blacksburg, VA, United States
| | - Vida Abedi
- Nutritional Immunology and Molecular Medicine Laboratory, Biocomplexity Institute of Virginia Tech, Blacksburg, VA, United States.,Department of Biomedical and Translational Informatics, Geisinger Health System, Danville, PA, United States
| | - Josep Bassaganya-Riera
- Nutritional Immunology and Molecular Medicine Laboratory, Biocomplexity Institute of Virginia Tech, Blacksburg, VA, United States
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Gao YF, Mao XY, Zhu T, Mao CX, Liu ZX, Wang ZB, Li L, Li X, Yin JY, Zhang W, Zhou HH, Liu ZQ. COL3A1 and SNAP91: novel glioblastoma markers with diagnostic and prognostic value. Oncotarget 2018; 7:70494-70503. [PMID: 27655637 PMCID: PMC5342568 DOI: 10.18632/oncotarget.12038] [Citation(s) in RCA: 49] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2016] [Accepted: 08/26/2016] [Indexed: 01/15/2023] Open
Abstract
Although patients with glioblastoma (GBM) have grave prognosis, significant variability in patient outcome is observed. This study aims to identify novel targets for GBM diagnosis and therapy. Microarray data (GSE4290, GSE7696, and GSE4412) obtained from the Gene Expression Omnibus was used to identify the differentially expressed genes (DEGs) by significant analysis of microarray (SAM). Intersection of the identified DEGs for each profile revealed 46 DEGs in GBM. A subset of common DEGs were validated by real-time reverse transcription quantitative PCR (qPCR). The prognostic value of some of the markers was also studied. We determined that RRM2 and COL3A1 were increased and directly correlated with glioma grade, while SH3GL2 and SNAP91 were decreased in GBM and inversely correlated with glioma grade. Kaplan-Meir analysis of GSE7696 revealed that COL3A1 and SNAP91 correlated with survival, suggesting that COL3A1 and SNAP91 may be suitable biomarkers for diagnostic or therapeutic strategies for GBM.
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Affiliation(s)
- Yuan-Feng Gao
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, P. R. China.,Institute of Clinical Pharmacology, Central South University, Hunan Key Laboratory of Pharmacogenetics, Changsha 410078, P. R. China
| | - Xiao-Yuan Mao
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, P. R. China.,Institute of Clinical Pharmacology, Central South University, Hunan Key Laboratory of Pharmacogenetics, Changsha 410078, P. R. China
| | - Tao Zhu
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, P. R. China.,Institute of Clinical Pharmacology, Central South University, Hunan Key Laboratory of Pharmacogenetics, Changsha 410078, P. R. China
| | - Chen-Xue Mao
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, P. R. China.,Institute of Clinical Pharmacology, Central South University, Hunan Key Laboratory of Pharmacogenetics, Changsha 410078, P. R. China
| | - Zhi-Xiong Liu
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha 410008, P. R. China
| | - Zhi-Bin Wang
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, P. R. China.,Institute of Clinical Pharmacology, Central South University, Hunan Key Laboratory of Pharmacogenetics, Changsha 410078, P. R. China
| | - Ling Li
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, P. R. China.,Institute of Clinical Pharmacology, Central South University, Hunan Key Laboratory of Pharmacogenetics, Changsha 410078, P. R. China
| | - Xi Li
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, P. R. China.,Institute of Clinical Pharmacology, Central South University, Hunan Key Laboratory of Pharmacogenetics, Changsha 410078, P. R. China
| | - Ji-Ye Yin
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, P. R. China.,Institute of Clinical Pharmacology, Central South University, Hunan Key Laboratory of Pharmacogenetics, Changsha 410078, P. R. China
| | - Wei Zhang
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, P. R. China.,Institute of Clinical Pharmacology, Central South University, Hunan Key Laboratory of Pharmacogenetics, Changsha 410078, P. R. China
| | - Hong-Hao Zhou
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, P. R. China.,Institute of Clinical Pharmacology, Central South University, Hunan Key Laboratory of Pharmacogenetics, Changsha 410078, P. R. China
| | - Zhao-Qian Liu
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, P. R. China.,Institute of Clinical Pharmacology, Central South University, Hunan Key Laboratory of Pharmacogenetics, Changsha 410078, P. R. China
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3
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PPIC, EMP3 and CHI3L1 Are Novel Prognostic Markers for High Grade Glioma. Int J Mol Sci 2016; 17:ijms17111808. [PMID: 27801851 PMCID: PMC5133809 DOI: 10.3390/ijms17111808] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2016] [Revised: 10/18/2016] [Accepted: 10/25/2016] [Indexed: 12/20/2022] Open
Abstract
Current treatment methods for patients diagnosed with gliomas have shown limited success. This is partly due to the lack of prognostic genes available to accurately predict disease outcomes. The aim of this study was to investigate novel prognostic genes based on the molecular profile of tumor samples and their correlation with clinical parameters. In the current study, microarray data (GSE4412 and GSE7696) downloaded from Gene Expression Omnibus were used to identify differentially expressed prognostic genes (DEPGs) by significant analysis of microarray (SAM) between long-term survivors (>2 years) and short-term survivors (≤2 years). DEPGs generated from these two datasets were intersected to obtain a list of common DEPGs. The expression of a subset of common DEPGs was then independently validated by real-time reverse transcription quantitative PCR (qPCR). Survival value of the common DEPGs was validated using known survival data from the GSE4412 and TCGA dataset. After intersecting DEPGs generated from the above two datasets, three genes were identified which may potentially be used to determine glioma patient prognosis. Independent validation with glioma patients tissue (n = 70) and normal brain tissue (n = 19) found PPIC, EMP3 and CHI3L1 were up-regulated in glioma tissue. Survival value validation showed that the three genes correlated with patient survival by Kaplan-Meir analysis, including grades, age and therapy.
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Systems view of adipogenesis via novel omics-driven and tissue-specific activity scoring of network functional modules. Sci Rep 2016; 6:28851. [PMID: 27385551 PMCID: PMC4935943 DOI: 10.1038/srep28851] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2015] [Accepted: 06/10/2016] [Indexed: 12/18/2022] Open
Abstract
The investigation of the complex processes involved in cellular differentiation must be based on unbiased, high throughput data processing methods to identify relevant biological pathways. A number of bioinformatics tools are available that can generate lists of pathways ranked by statistical significance (i.e. by p-value), while ideally it would be desirable to functionally score the pathways relative to each other or to other interacting parts of the system or process. We describe a new computational method (Network Activity Score Finder - NASFinder) to identify tissue-specific, omics-determined sub-networks and the connections with their upstream regulator receptors to obtain a systems view of the differentiation of human adipocytes. Adipogenesis of human SBGS pre-adipocyte cells in vitro was monitored with a transcriptomic data set comprising six time points (0, 6, 48, 96, 192, 384 hours). To elucidate the mechanisms of adipogenesis, NASFinder was used to perform time-point analysis by comparing each time point against the control (0 h) and time-lapse analysis by comparing each time point with the previous one. NASFinder identified the coordinated activity of seemingly unrelated processes between each comparison, providing the first systems view of adipogenesis in culture. NASFinder has been implemented into a web-based, freely available resource associated with novel, easy to read visualization of omics data sets and network modules.
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Lacroix S, Lauria M, Scott-Boyer MP, Marchetti L, Priami C, Caberlotto L. Systems biology approaches to study the molecular effects of caloric restriction and polyphenols on aging processes. GENES & NUTRITION 2015; 10:58. [PMID: 26608884 PMCID: PMC4659783 DOI: 10.1007/s12263-015-0508-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/17/2015] [Accepted: 11/13/2015] [Indexed: 12/17/2022]
Abstract
Worldwide population is aging, and a large part of the growing burden associated with age-related conditions can be prevented or delayed by promoting healthy lifestyle and normalizing metabolic risk factors. However, a better understanding of the pleiotropic effects of available nutritional interventions and their influence on the multiple processes affected by aging is needed to select and implement the most promising actions. New methods of analysis are required to tackle the complexity of the interplay between nutritional interventions and aging, and to make sense of a growing amount of -omics data being produced for this purpose. In this paper, we review how various systems biology-inspired methods of analysis can be applied to the study of the molecular basis of nutritional interventions promoting healthy aging, notably caloric restriction and polyphenol supplementation. We specifically focus on the role that different versions of network analysis, molecular signature identification and multi-omics data integration are playing in elucidating the complex mechanisms underlying nutrition, and provide some examples on how to extend the application of these methods using available microarray data.
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Affiliation(s)
- Sébastien Lacroix
- The Microsoft Research, University of Trento Centre for Computational Systems Biology (COSBI), Piazza Manifattura 1, 38068, Rovereto, Italy
| | - Mario Lauria
- The Microsoft Research, University of Trento Centre for Computational Systems Biology (COSBI), Piazza Manifattura 1, 38068, Rovereto, Italy
| | - Marie-Pier Scott-Boyer
- The Microsoft Research, University of Trento Centre for Computational Systems Biology (COSBI), Piazza Manifattura 1, 38068, Rovereto, Italy
| | - Luca Marchetti
- The Microsoft Research, University of Trento Centre for Computational Systems Biology (COSBI), Piazza Manifattura 1, 38068, Rovereto, Italy
| | - Corrado Priami
- The Microsoft Research, University of Trento Centre for Computational Systems Biology (COSBI), Piazza Manifattura 1, 38068, Rovereto, Italy
- Department of Mathematics, University of Trento, Via Sommarive 14, 38123, Povo, Italy
| | - Laura Caberlotto
- The Microsoft Research, University of Trento Centre for Computational Systems Biology (COSBI), Piazza Manifattura 1, 38068, Rovereto, Italy.
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Abstract
Type 2 diabetes (T2D) has become an increasingly challenging health burden due to its high morbidity, mortality, and heightened prevalence worldwide. Although dietary and nutritional imbalances have long been recognized as key risk factors for T2D, the underlying mechanisms remain unclear. The advent of nutritional systems biology, a field that aims to elucidate the interactions between dietary nutrients and endogenous molecular entities in disease-related tissues, offers unique opportunities to unravel the complex mechanisms underlying the health-modifying capacities of nutritional molecules. The recent revolutionary advances in omics technologies have particularly empowered this incipient field. In this review, we discuss the applications of multi-omics approaches toward a systems-level understanding of how dietary patterns and particular nutrients modulate the risk of T2D. We focus on nutritional studies utilizing transcriptomics, epigenomomics, proteomics, metabolomics, and microbiomics, and integration of diverse omics technologies. We also summarize the potential molecular mechanisms through which nutritional imbalances contribute to T2D pathogenesis based on these studies. Finally, we discuss the remaining challenges of nutritional systems biology and how the field can be optimized to further our understanding of T2D and guide disease management via nutritional interventions.
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Affiliation(s)
- Yuqi Zhao
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA 90095 USA
| | - Rio Elizabeth Barrere-Cain
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA 90095 USA
| | - Xia Yang
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA 90095 USA
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Abu Bakar MH, Sarmidi MR, Cheng KK, Ali Khan A, Suan CL, Zaman Huri H, Yaakob H. Metabolomics – the complementary field in systems biology: a review on obesity and type 2 diabetes. MOLECULAR BIOSYSTEMS 2015; 11:1742-74. [DOI: 10.1039/c5mb00158g] [Citation(s) in RCA: 82] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
This paper highlights the metabolomic roles in systems biology towards the elucidation of metabolic mechanisms in obesity and type 2 diabetes.
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Affiliation(s)
- Mohamad Hafizi Abu Bakar
- Department of Bioprocess Engineering
- Faculty of Chemical Engineering
- Universiti Teknologi Malaysia
- 81310 Johor Bahru
- Malaysia
| | - Mohamad Roji Sarmidi
- Institute of Bioproduct Development
- Universiti Teknologi Malaysia
- 81310 Johor Bahru
- Malaysia
- Innovation Centre in Agritechnology for Advanced Bioprocessing (ICA)
| | - Kian-Kai Cheng
- Department of Bioprocess Engineering
- Faculty of Chemical Engineering
- Universiti Teknologi Malaysia
- 81310 Johor Bahru
- Malaysia
| | - Abid Ali Khan
- Institute of Bioproduct Development
- Universiti Teknologi Malaysia
- 81310 Johor Bahru
- Malaysia
- Department of Biosciences
| | - Chua Lee Suan
- Institute of Bioproduct Development
- Universiti Teknologi Malaysia
- 81310 Johor Bahru
- Malaysia
| | - Hasniza Zaman Huri
- Department of Pharmacy
- Faculty of Medicine
- University of Malaya
- 50603 Kuala Lumpur
- Malaysia
| | - Harisun Yaakob
- Institute of Bioproduct Development
- Universiti Teknologi Malaysia
- 81310 Johor Bahru
- Malaysia
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8
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Li G, Pan W, Yang X, Miao J. Gene co-expression network and function modules in three types of glioma. Mol Med Rep 2014; 11:3055-63. [PMID: 25435164 DOI: 10.3892/mmr.2014.3014] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2013] [Accepted: 04/25/2014] [Indexed: 11/06/2022] Open
Abstract
The aim of the present study was to identify the disease‑associated genes and their functions involved in the development of three types of glioma (astrocytoma, glioblastoma and oligodendroglioma) with DNA microarray technology, and to analyze their differences and correlations. First, the gene expression profile GSE4290 was downloaded from the Gene Expression Omnibus database, then the probe‑level data were pre‑processed and the differentially expressed genes (DEGs) were identified with limma package in R language. Gene functions of the selected DEGs were further analyzed with the Database for Annotation, Visualization and Integrated Discovery. After the co‑expression network of DEGs was constructed by Cytoscape, the functional modules were mined and enrichment analysis was performed, and then the similarities and differences between any two types of glioma were compared. A total of 1151 genes between normal and astrocytoma tissues, 684 genes between normal and malignant glioma tissues, and 551 genes between normal and oligodendroglioma tissues were filtered as DEGs, respectively. By constructing co‑expression networks of DEGs, a total of 77232, 455 and 987 interactions were involved in the differentially co‑expressed networks of astrocytoma, oligodendroglioma and glioblastoma, respectively. The functions of DEGs were consistent with the modules in astrocytoma, glioblastoma and oligodendroglioma, which were mainly enriched in neuron signal transmission, immune responses and synthesis of organic acids, respectively. Model functions of astrocytoma and glioblastoma were similar (mainly related with immune response), while the model functions of oligodendroglioma differed markedly from that of the other two types. The identification of the associations among these three types of glioma has potential clinical utility for improving the diagnosis of different types of glioma in the future. In addition, these results have marked significance in studying the underlying mechanisms, distinguishing between normal and cancer tissues, and examining novel therapeutic strategies for patients with glioma.
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Affiliation(s)
- Gang Li
- Department of Neurosurgery, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, P.R. China
| | - Weiran Pan
- Department of Neurosurgery, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, P.R. China
| | - Xiaoxiao Yang
- Department of Neurosurgery, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, P.R. China
| | - Jinming Miao
- Department of Neurosurgery, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, P.R. China
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Morine MJ, Monteiro JP, Wise C, Teitel C, Pence L, Williams A, Ning B, McCabe-Sellers B, Champagne C, Turner J, Shelby B, Bogle M, Beger RD, Priami C, Kaput J. Genetic associations with micronutrient levels identified in immune and gastrointestinal networks. GENES AND NUTRITION 2014; 9:408. [PMID: 24879315 PMCID: PMC4169061 DOI: 10.1007/s12263-014-0408-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/01/2014] [Accepted: 05/12/2014] [Indexed: 01/05/2023]
Abstract
The discovery of vitamins and clarification of their role in preventing frank essential nutrient deficiencies occurred in the early 1900s. Much vitamin research has understandably focused on public health and the effects of single nutrients to alleviate acute conditions. The physiological processes for maintaining health, however, are complex systems that depend upon interactions between multiple nutrients, environmental factors, and genetic makeup. To analyze the relationship between these factors and nutritional health, data were obtained from an observational, community-based participatory research program of children and teens (age 6–14) enrolled in a summer day camp in the Delta region of Arkansas. Assessments of erythrocyte S-adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH), plasma homocysteine (Hcy) and 6 organic micronutrients (retinol, 25-hydroxy vitamin D3, pyridoxal, thiamin, riboflavin, and vitamin E), and 1,129 plasma proteins were performed at 3 time points in each of 2 years. Genetic makeup was analyzed with 1 M SNP genotyping arrays, and nutrient status was assessed with 24-h dietary intake questionnaires. A pattern of metabolites (met_PC1) that included the ratio of erythrocyte SAM/SAH, Hcy, and 5 vitamins were identified by principal component analysis. Met_PC1 levels were significantly associated with (1) single-nucleotide polymorphisms, (2) levels of plasma proteins, and (3) multilocus genotypes coding for gastrointestinal and immune functions, as identified in a global network of metabolic/protein–protein interactions. Subsequent mining of data from curated pathway, network, and genome-wide association studies identified genetic and functional relationships that may be explained by gene–nutrient interactions. The systems nutrition strategy described here has thus associated a multivariate metabolite pattern in blood with genes involved in immune and gastrointestinal functions.
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Affiliation(s)
- Melissa J Morine
- The Microsoft Research - University of Trento Centre for Computational and Systems Biology (COSBI), Rovereto, Italy
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Afman L, Milenkovic D, Roche HM. Nutritional aspects of metabolic inflammation in relation to health--insights from transcriptomic biomarkers in PBMC of fatty acids and polyphenols. Mol Nutr Food Res 2014; 58:1708-20. [PMID: 24449395 DOI: 10.1002/mnfr.201300559] [Citation(s) in RCA: 49] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2013] [Revised: 11/27/2013] [Accepted: 12/03/2013] [Indexed: 11/08/2022]
Abstract
Recent research has highlighted potential important interaction between metabolism and inflammation, within the context of metabolic health and nutrition, with a view to preventing diet-related disease. In addition to this, there is a paucity of evidence in relation to accurate biomarkers that are capable of reflecting this important biological interplay or relationship between metabolism and inflammation, particularly in relation to diet and health. Therefore the objective of this review is to highlight the potential role of transcriptomic approaches as a tool to capture the mechanistic basis of metabolic inflammation. Within this context, this review has focused on the potential of peripheral blood mononuclear cells transcriptomic biomarkers, because they are an accessible tissue that may reflect metabolism and subacute chronic inflammation. Also these pathways are often dysregulated in the common diet-related diseases obesity, type 2 diabetes, and cardiovascular disease, thus may be used as markers of systemic health. The review focuses on fatty acids and polyphenols, two classes of nutrients/nonnutrient food components that modulate metabolism/inflammation, which we have used as an example of a proof-of-concept with a view to understanding the extent to which transcriptomic biomarkers are related to nutritional status and/or sensitive to dietary interventions. We show that both nutritional components modulate inflammatory markers at the transcriptomic level with the capability of profiling pro- and anti-inflammatory mechanisms in a bidirectional fashion; to this end transcriptomic biomarkers may have potential within the context of metabolic inflammation. This transcriptomic biomarker approach may be a sensitive indicator of nutritional status and metabolic health.
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Affiliation(s)
- Lydia Afman
- Nutrition, Metabolism and Genomics Group, Division of Human Nutrition, Wageningen University, The Netherlands
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Kaput J, van Ommen B, Kremer B, Priami C, Monteiro JP, Morine M, Pepping F, Diaz Z, Fenech M, He Y, Albers R, Drevon CA, Evelo CT, Hancock REW, Ijsselmuiden C, Lumey LH, Minihane AM, Muller M, Murgia C, Radonjic M, Sobral B, West KP. Consensus statement understanding health and malnutrition through a systems approach: the ENOUGH program for early life. GENES & NUTRITION 2014; 9:378. [PMID: 24363221 PMCID: PMC3896628 DOI: 10.1007/s12263-013-0378-y] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2013] [Accepted: 12/02/2013] [Indexed: 12/20/2022]
Abstract
Nutrition research, like most biomedical disciplines, adopted and often uses experimental approaches based on Beadle and Tatum's one gene-one polypeptide hypothesis, thereby reducing biological processes to single reactions or pathways. Systems thinking is needed to understand the complexity of health and disease processes requiring measurements of physiological processes, as well as environmental and social factors, which may alter the expression of genetic information. Analysis of physiological processes with omics technologies to assess systems' responses has only become available over the past decade and remains costly. Studies of environmental and social conditions known to alter health are often not connected to biomedical research. While these facts are widely accepted, developing and conducting comprehensive research programs for health are often beyond financial and human resources of single research groups. We propose a new research program on essential nutrients for optimal underpinning of growth and health (ENOUGH) that will use systems approaches with more comprehensive measurements and biostatistical analysis of the many biological and environmental factors that influence undernutrition. Creating a knowledge base for nutrition and health is a necessary first step toward developing solutions targeted to different populations in diverse social and physical environments for the two billion undernourished people in developed and developing economies.
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Affiliation(s)
- Jim Kaput
- Clinical Translation Unit, Nestle Institute of Health Sciences, Lausanne, Switzerland,
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Meng Q, Mäkinen VP, Luk H, Yang X. Systems Biology Approaches and Applications in Obesity, Diabetes, and Cardiovascular Diseases. CURRENT CARDIOVASCULAR RISK REPORTS 2013; 7:73-83. [PMID: 23326608 PMCID: PMC3543610 DOI: 10.1007/s12170-012-0280-y] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
The metabolically connected triad of obesity, diabetes, and cardiovascular diseases is a major public health threat, and is expected to worsen due to the global shift toward energy-rich and sedentary living. Despite decades of intense research, a large part of the molecular pathogenesis behind complex metabolic diseases remains unknown. Recent advances in genetics, epigenomics, transcriptomics, proteomics and metabolomics enable us to obtain large-scale snapshots of the etiological processes in multiple disease-related cells, tissues and organs. These datasets provide us with an opportunity to go beyond conventional reductionist approaches and to pinpoint the specific perturbations in critical biological processes. In this review, we summarize systems biology methodologies such as functional genomics, causality inference, data-driven biological network construction, and higher-level integrative analyses that can produce novel mechanistic insights, identify disease biomarkers, and uncover potential therapeutic targets from a combination of omics datasets. Importantly, we also demonstrate the power of these approaches by application examples in obesity, diabetes, and cardiovascular diseases.
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Affiliation(s)
- Qingying Meng
- Department of Integrative Biology and Physiology, University of California (UCLA), 610 Charles E. Young Dr E., Terasaki Life Sciences Building, Los Angeles, CA 90095 USA
| | - Ville-Petteri Mäkinen
- Department of Integrative Biology and Physiology, University of California (UCLA), 610 Charles E. Young Dr E., Terasaki Life Sciences Building, Los Angeles, CA 90095 USA
| | - Helen Luk
- Department of Integrative Biology and Physiology, University of California (UCLA), 610 Charles E. Young Dr E., Terasaki Life Sciences Building, Los Angeles, CA 90095 USA
| | - Xia Yang
- Department of Integrative Biology and Physiology, University of California (UCLA), 610 Charles E. Young Dr E., Terasaki Life Sciences Building, Los Angeles, CA 90095 USA
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