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Network Medicine — from Obesity to the “Diseasome” Albert-László Barabási, Ph.D

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Network Medicine — from Obesity to the “Diseasome” Albert-László Barabási, Ph.D T h e new england journal o f medicine vided by the primary physician faced with a young, cal and research approaches. Pediatr Infect Dis J 2003;22:Suppl: S58­S65. distressed infant and anxious parents. Withhold­ 8. Martinez FD. Respiratory syncytial virus bronchiolitis and ing therapy is much more difficult than giving it. the pathogenesis of childhood asthma. Pediatr Infect Dis J 2003; 22:Suppl:S76­S82. No potential conflict of interest relevant to this article was re­ 9. Behrendt CE, Decker MD, Burch DJ, Watson PH. Interna­ ported. tional variation in the management of infants hospitalized with respiratory syncytial virus. Eur J Pediatr 1998;157:215­20. From the Department of Infectious Diseases, University of Roch- 10. Christakis DA, Cowan CA, Garrison MM, Molteni R, Mar­ ester School of Medicine and Dentistry, Rochester, NY. cuse E, Zerr DM. Variation in inpatient diagnostic testing and management of bronchiolitis. Pediatrics 2005;115:878­84. 1. Knapp VJ. Major medical explanations for high infant mor­ 11. Rowe BH, Spooner C, Ducharme FM, Bretzlaff JA, Bota GW. tality in nineteenth­century Europe. Can Bull Med Hist 1998;15: Early emergency department treatment of acute asthma with 317­36. systemic corticosteroids. Cochrane Database Syst Rev 2001;1: 2. Leader S, Kohlhase K. Recent trends in severe respiratory CD002178. syncytial virus (RSV) among US infants, 1997­2000. J Pediatr 12. Corneli HM, Zorc JJ, Majahan P, et al. A multicenter, random­ 2003;143:Suppl:S127­S132. ized, controlled trial of dexamethasone for bronchiolitis. N Engl 3. Shay DK, Holman RC, Newman RD, Liu LL, Stout JW, Ander­ J Med 2007;357:331­9. son LJ. Bronchiolitis­associated hospitalizations among US chil­ 13. Schuh S, Coates AL, Binnie R, et al. Efficacy of oral dexa­ dren, 1980­1996. JAMA 1999;282:1440­6. methasone in outpatients with acute bronchiolitis. J Pediatr 4. Falsey AR, Hennessey PA, Formica MA, Cox C, Walsh EE. 2002;140:27­32. Respiratory syncytial virus infection in elderly and high­risk 14. Parrott RH, Kim HW, Arrobio JO, et al. Epidemiology of adults. N Engl J Med 2005;352:1749­59. respiratory syncytial virus infection in Washington, D.C. II. Infec­ 5. American Academy of Pediatrics Subcommittee on Diagno­ tion and disease with respect to age, immunologic status, race sis and Management of Bronchiolitis. Diagnosis and management and sex. Am J Epidemiol 1973;98:289­300. of bronchiolitis. Pediatrics 2006;118:1774­93. 15. Nicholson KG, McNally T, Silverman M, Simons P, Stockton 6. Management of bronchiolitis in infants and children. Evi­ JD, Zambon MC. Rates of hospitalisation for influenza, respira­ dence report/technology assessment. No. 69. Rockville, MD: tory syncytial virus and human metapneumovirus among infants Agency for Healthcare Research and Quality, January 2003:1­5. and young children. Vaccine 2006;24:102­8. (AHRQ publication no. 03­E009.) 16. Gern JE. Mechanisms of virus­induced asthma. J Pediatr 2003; 7. Openshaw PJ, Dean GS, Culley FJ. Links between respira­ 142:Suppl:S9­S14. tory syncytial virus bronchiolitis and childhood asthma: clini­ Copyright © 2007 Massachusetts Medical Society. Network Medicine — From Obesity to the “Diseasome” Albert-László Barabási, Ph.D. A recent study reported that among people who Study, making use of the fact that the participants carried a single copy of the high­risk allele for had been asked to name their friends to facilitate the FTO gene, which is associated with fat mass follow­up in the study. The authors observed that and obesity, the risk of obesity increased by 30%. when two persons perceived each other as friends, The risk of obesity increased by 67% among peo­ if one friend became obese during a given time ple who carried two alleles, and on average they interval, the other friend’s chances of following gained 3.0 kg (6.6 lb) or more.1 Given that ap­ suit increased by 171%. Among pairs of adult sib­ proximately one sixth of the population of Euro­ lings, if one sibling became obese, the chance pean descent is homozygous for this allele, this that the other would become obese increased by link between the FTO gene and obesity appears 40%. The results of this study also indicate that to be one of the strongest genotype–phenotype obesity is clustered in communities. For example, associations detected by modern genome­screen­ the risk that the friend of a friend of an obese ing techniques. person would be obese was about 20% higher in That obesity has a genetic component is not the observed network than in a random network; surprising: researchers have long known that it this effect vanished only by the fourth degree of often runs in families. In this issue of the Journal, separation. Christakis and Fowler suggest that friends have In the past 7 years, our understanding of net­ an even more important effect on a person’s risk works has undergone a revolution because of the of obesity than genes do.2 The authors recon­ emergence of a new array of theoretical tools structed a social network showing the ties between and techniques for mapping out real networks. friends, neighbors, spouses, and family members These advances have included some surprises in­ among participants of the Framingham Heart dicating that most real networks in technologi­ 404 n engl j med 357;4 www.nejm.org july 26, 2007 Downloaded from www.nejm.org on July 27, 2007 . For personal use only. No other uses without permission. Copyright © 2007 Massachusetts Medical Society. All rights reserved. editorials cal, social, and biologic systems have common gins. Human diseases, therefore, themselves form designs that are governed by simple and quanti­ a network in which two diseases are connected fiable organizing principles.3 The growing inter­ if they share at least one gene.7 In this disease est in interconnectedness has brought into focus network, obesity has links to seven diseases, in­ an often ignored issue: networks pervade all as­ cluding asthma, lipodystrophy, and glioblastoma pects of human health. One example of this trend (Fig. 1). Thus, the network concept reveals a num­ involves social networks and their impact on the ber of surprising connections between diseases, spread of obesity or pathogens — from influenza forcing us to rethink the way in which we classify to the severe acute respiratory syndrome or the hu­ and separate them. man immunodeficiency virus. The role of neural In the long run, networks may affect all as­ networks in various psychiatric and neurodegen­ pects of medical research and practice.8 Indeed, erative diseases is another example. In fact, net­ the fundamental question of where function lies work analysis is poised to play the biggest role within a cell is slowly shifting from a single­ at the cellular level,4 since most cellular compo­ minded focus on genes to the understanding that nents are connected to each other through intri­ behind each cellular function there is a discerni­ cate regulatory, metabolic, and protein–protein ble network module consisting of genes, transcrip­ interactions. Because of these many functional tion factors, RNAs, enzymes, and metabolites. links, the defects of various genes spread through­ This understanding forces us to view diseases as out the intracellular network, affecting the activ­ the breakdown of selected functional modules ity of genes that otherwise carry no defects. rather than as single or small groups of genes. To understand various disease mechanisms, Given the many components of such functional it is not sufficient to know the precise list of modules, there are different paths to disease­ “disease genes”; instead, we should try to map inducing systems failure; this explains why often out the detailed wiring diagram of the various many genes are linked to the same disease pheno­ cellular components that are influenced by type. Similarly, the effects of drugs are not lim­ these genes and gene products. Such network­ ited to the molecules to which they directly bind; based thinking has already provided insights into instead, these effects can spread throughout the the pathogenesis of several diseases. For exam­ cellular network in which they act, causing un­ ple, a recent study suggested that 18 of the 23 wanted side effects. Therefore, drug side effects genes known to be associated with ataxia are are inherently network phenomena. part of a highly interlinked subnetwork5; in an­ Naturally, network­based thinking may account other example, a reverse­engineered subnetwork for the environmental and social influences on indicated that the androgen­receptor gene might disease as well. In this context, we must under­ be used to detect the aggressiveness of primary stand the human interactions encompassing so­ prostate cancer.6 cial and family links, proximity­based contacts, The existence of intricate molecular links be­ and transportation networks.9 For example, recent tween subcellular components and disease genes advances in the study of sexual networks have raises another possibility: that is, diseases may led to new protocols for drug dispersion. These not be as independent of each other as medical protocols are expected to be more efficient in practitioners currently consider them to be. For combating the acquired immunodeficiency syn­ example, could a genetic origin account for the drome in underdeveloped countries than current fact that obesity is a risk factor for diabetes? A protocols that are based on social need.10 quick look at the list of genes associated with The Human Genome Project has revolution­ these two diseases indicates that several genes, ized gene hunting, leading to an explosion in including ectoenzyme nucleotide pyrophosphate the number of detected associations between phosphodiesterase (ENPP1), peroxisome­prolifera­ genes and disease phenotypes. The beauty of ge­ tor–activated receptor γ (PPARγ), and — more re­ nomewide association studies lies in their ability cently — FTO, may be implicated in both diseas­ to quantify their own limitations.
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