Approaching Complex Diseases

This volume – for pharmacologists, systems biologists, philosophers and historians of medicine – points to investigate new avenues in pharmacology research, by providing a full assessment of the premises underlying a radical shift in the pharmacology paradigm. The pharmaceutical industry is currently facing unparalleled challenges in developing innovative drugs. While drug-developing scientists in the 1990s mostly welcomed the transformation into a target-based approach, two decades of experience shows that this model is failing to boost both drug discovery and efficiency. Selected targets were often not druggable and with poor disease linkage, leading to either high toxicity or poor efficacy. Therefore, a profound rethinking of the current paradigm is needed. Advances in systems biology are revealing a phenotypic robustness and a network structure that strongly suggest that exquisitely selective compounds, compared with multitarget drugs, may exhibit lower than desired clinical efficacy. This appreciation of the role of polypharmacology has significant implications for tackling the two major sources of attrition in drug development, efficacy and toxicity. Integrating network biology and polypharmacology holds the promise of expanding the current opportunity space for druggable targets.

This volume - for pharmacologists, systems biologists, philosophers and historians of medicine - points to investigate new avenues in pharmacology research, by providing a full assessment of the premises underlying a radical shift in the pharmacology paradigm. The pharmaceutical industry is currently facing unparalleled challenges in developing innovative drugs. While drug-developing scientists in the 1990s mostly welcomed the transformation into a target-based approach, two decades of experience shows that this model is failing to boost both drug discovery and efficiency. Selected targets were often not druggable and with poor disease linkage, leading to either high toxicity or poor efficacy. Therefore, a profound rethinking of the current paradigm is needed. Advances in systems biology are revealing a phenotypic robustness and a network structure that strongly suggest that exquisitely selective compounds, compared with multitarget drugs, may exhibit lower than desired clinical efficacy. This appreciation of the role of polypharmacology has significant implications for tackling the two major sources of attrition in drug development, efficacy and toxicity. Integrating network biology and polypharmacology holds the promise of expanding the current opportunity space for druggable targets.

Big data, genomics, and quantitative approaches to network-based analysis are combining to advance the frontiers of medicine as never before. With contributions from leading experts, Network Medicine introduces this rapidly evolving field of research, which promises to revolutionize the diagnosis and treatment of human diseases.

A collection of highly valuable statistical and computational approaches designed for developing powerful methods to analyze large-scale high-throughput data derived from studies of complex diseases. Such diseases include cancer and cardiovascular disease, and constitute the major health challenges in industrialized countries. They are characterized by the systems properties of gene networks and their interrelations, instead of individual genes, whose malfunctioning manifests in pathological phenotypes, thus making the analysis of the resulting large data sets particularly challenging. This is why novel approaches are needed to tackle this problem efficiently on a systems level. Written by computational biologists and biostatisticians, this book is an invaluable resource for a large number of researchers working on basic but also applied aspects of biomedical data analysis emphasizing the pathway level.

The difficulty in achieving effective translation of basic mechanistic biomedical knowledge into effective therapeutics, is the greatest challenge in biomedical research. Nowhere is this more apparent than in the reductionist approaches to understanding and manipulating the acute inflammatory response in the settings of sepsis, trauma/hemorrhage, wound healing, and related processes. This book discusses complex systems and computational biology methods and approaches that have advanced sufficiently to allow for knowledge generation, knowledge integration, and clinical translation in the settings of complex diseases related to the inflammatory response. Well-regulated, self-resolving inflammation is necessary for the appropriate communication and resolution of infection and trauma, and for maintenance of proper physiology and homeostasis. In contrast, self-sustaining inflammation drives the pathobiology of the aforementioned diseases. It is now increasingly recognized that controlling and reprogramming inflammation in order to reap the benefits of this evolutionarily-conserved process is preferred to simply abolishing indiscriminately.

Second Edition features the latest tools for uncovering thegenetic basis of human disease The Second Edition of this landmark publication bringstogether a team of leading experts in the field to thoroughlyupdate the publication. Readers will discover the tremendousadvances made in human genetics in the seven years that haveelapsed since the First Edition. Once again, the editorshave assembled a comprehensive introduction to the strategies,designs, and methods of analysis for the discovery of genes incommon and genetically complex traits. The growing social, legal,and ethical issues surrounding the field are thoroughly examined aswell. Rather than focusing on technical details or particularmethodologies, the editors take a broader approach that emphasizesconcepts and experimental design. Readers familiar with theFirst Edition will find new and cutting-edge materialincorporated into the text: Updated presentations of bioinformatics, multiple comparisons,sample size requirements, parametric linkage analysis, case-controland family-based approaches, and genomic screening New methods for analysis of gene-gene and gene-environmentinteractions A completely rewritten and updated chapter on determininggenetic components of disease New chapters covering molecular genomic approaches such asmicroarray and SAGE analyses using single nucleotide polymorphism(SNP) and cDNA expression data, as well as quantitative trait loci(QTL) mapping The editors, two of the world's leading genetic epidemiologists,have ensured that each chapter adheres to a consistent and highstandard. Each one includes all-new discussion questions andpractical examples. Chapter summaries highlight key points, and alist of references for each chapter opens the door to furtherinvestigation of specific topics. Molecular biologists, human geneticists, geneticepidemiologists, and clinical and pharmaceutical researchers willfind the Second Edition a helpful guide to understanding thegenetic basis of human disease, with its new tools for detectingrisk factors and discovering treatment strategies.

The sequencing of the human genome has brought human genetics into a new era of study resulting in the generation of an explosive amount of information. Application of genomic, proteomic, and bioinformatics technologies to the study of human genetics has made it possible for human genetic diseases to be studied on an unprecedented scale, both in silico and in the wet lab. This volume provides up-to-date coverage of the broad range of research topics in this fascinating area. In the first part of the book, a whole spectrum of approaches to human genetics research is reviewed for both background and the latest progress. In the second, important topics related to genetic research of various complex human diseases are discussed. The robust content and diverse array of subjects allow the book to serve as both a concise “encyclopedia” that introduces basic and essential concepts of human genetics and an in-depth review of the current understanding of genetic research in human diseases.