Systems Biology Approaches and Applications in Obesity, Diabetes, and Cardiovascular Diseases
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DIABETES AND INSULIN RESISTANCE (M RUTTER, SECTION EDITOR)
Systems Biology Approaches and Applications in Obesity, Diabetes, and Cardiovascular Diseases Qingying Meng & Ville-Petteri Mäkinen & Helen Luk & Xia Yang
Published online: 18 October 2012 # The Author(s) 2012. This article is published with open access at Springerlink.com
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 largescale 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. Keywords Metabolic disorders . Obesity . Diabetes . Cardiovascular diseases . Systems biology . Integrative genomics . Functional genomics . Causality inference . Network biology
Q. Meng : V.-P. Mäkinen : H. Luk : X. 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 e-mail: [email protected]
Introduction Common metabolically connected diseases (MetDs) such as cardiovascular disease (CVD), type 2 diabetes (T2D), and obesity impose a substantial health burden worldwide, as demonstrated by the fact that both CVD and T2D are among the top ten leading causes of death in Europe and the United States. As obesity (defined as body mass index (BMI) >30 kg/m2) is a key risk factor for both T2D and CVD, the rapidly growing obesity epidemic has further exacerbated the high morbidity and mortality, making an in-depth understanding of the mechanisms of MetDs and the development of novel therapeutic strategies more pressing. Decades of research on MetDs show that obesity, T2D, and CVD are tightly linked and both genetic and environmental factors contribute to the susceptibility [1]. At the genetic level, hundreds of individual genetic loci are associated with MetDs as shown by recent genome-wide association studies (GWAS) [2•]. It is striking, however, that the genetic loci discovered together only explain a small proportion (typically
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