期刊论文详细信息
BMC Public Health
Biobanking across the phenome - at the center of chronic disease research
Nicole M Probst-Hensch1  Medea Imboden1 
[1] University of Basel, Basel, Switzerland
关键词: Risk factors;    Public health;    Phenome;    Non-communicable disease;    Genome wide association study;    Cohort;    Comorbidities;   
Others  :  1161533
DOI  :  10.1186/1471-2458-13-1094
 received in 2012-07-27, accepted in 2013-09-25,  发布年份 2013
PDF
【 摘 要 】

Background

Recognized public health relevant risk factors such as obesity, physical inactivity, smoking or air pollution are common to many non-communicable diseases (NCDs). NCDs cluster and co-morbidities increase in parallel to age. Pleiotropic genes and genetic variants have been identified by genome-wide association studies (GWAS) linking NCD entities hitherto thought to be distant in etiology. These different lines of evidence suggest that NCD disease mechanisms are in part shared.

Discussion

Identification of common exogenous and endogenous risk patterns may promote efficient prevention, an urgent need in the light of the global NCD epidemic. The prerequisite to investigate causal risk patterns including biologic, genetic and environmental factors across different NCDs are well characterized cohorts with associated biobanks. Prospectively collected data and biospecimen from subjects of various age, sociodemographic, and cultural groups, both healthy and affected by one or more NCD, are essential for exploring biologic mechanisms and susceptibilities interlinking different environmental and lifestyle exposures, co-morbidities, as well as cellular senescence and aging. A paradigm shift in the research activities can currently be observed, moving from focused investigations on the effect of a single risk factor on an isolated health outcome to a more comprehensive assessment of risk patterns and a broader phenome approach. Though important methodological and analytical challenges need to be resolved, the ongoing international efforts to establish large-scale population-based biobank cohorts are a critical basis for moving NCD disease etiology forward.

Summary

Future epidemiologic and public health research should aim at sustaining a comprehensive systems view on health and disease. The political and public discussions about the utilitarian aspect of investing in and contributing to cohort and biobank research are essential and are indirectly linked to the achievement of public health programs effectively addressing the global NCD epidemic.

【 授权许可】

   
2013 Imboden and Probst-Hensch; licensee BioMed Central Ltd.Probst-Hensch

【 预 览 】
附件列表
Files Size Format View
20150413031810998.pdf 251KB PDF download
【 参考文献 】
  • [1]Murray CJ, Vos T, Lozano R, Naghavi M, Flaxman AD, Michaud C, Ezzati M, Shibuya K, Salomon JA, Abdalla S, et al.: Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990–2010: a systematic analysis for the global burden of disease study 2010. Lancet 2012, 380(9859):2197-2223.
  • [2]Vaught J, Lockhart NC: The evolution of biobanking best practices. Clin Chim Acta 2012, 413(19–20):1569-1575.
  • [3]Myles R, Massett HA, Comey G, Atkinson N, Allsop D, Compton C: Stakeholder research on biospecimen needs and reactions to the development of a national cancer human biobank by the National Cancer Institute. J Natl Cancer Inst Monogr 2011, 2011(42):16-23.
  • [4]Collins R: What makes UK Biobank special? Lancet 2012, 379(9822):1173-1174.
  • [5]Li L, Guo Y, Chen Z, Chen J, Peto R: Epidemiology and the control of disease in China, with emphasis on the Chinese Biobank Study. Public Health 2012, 126(3):210-213.
  • [6]Manolio TA, Weis BK, Cowie CC, Hoover RN, Hudson K, Kramer BS, Berg C, Collins R, Ewart W, Gaziano JM, et al.: New models for large prospective studies: is there a better way? Am J Epidemiol 2012, 175(9):859-866.
  • [7]Nair H, Shu XO, Volmink J, Romieu I, Spiegelman D: Cohort studies around the world: methodologies, research questions and integration to address the emerging global epidemic of chronic diseases. Public Health 2012, 126(3):202-205.
  • [8]Murray CJ, Frenk J, Piot P, Mundel T: GBD 2.0: a continuously updated global resource. Lancet 2013, 382(9886):9-11.
  • [9]Remais JV, Zeng G, Li G, Tian L, Engelgau MM: Convergence of non-communicable and infectious diseases in low- and middle-income countries. Int J Epidemiol 2013, 42(1):221-227.
  • [10]Probst-Hensch N, Kunzli N: Preventing noncommunicable diseases-beyond lifestyle. Epidemiology 2012, 23(2):181-183.
  • [11]Ebrahim S, Pearce N, Smeeth L, Casas JP, Jaffar S, Piot P: Tackling non-communicable diseases in low- and middle-income countries: is the evidence from high-income countries all we need? PLoS Med 2013, 10(1):e1001377.
  • [12]Genomes Project C, Abecasis GR, Auton A, Brooks LD, DePristo MA, Durbin RM, Handsaker RE, Kang HM, Marth GT, McVean GA: An integrated map of genetic variation from 1,092 human genomes. Nature 2012, 491(7422):56-65.
  • [13]Teo K, Lear S, Islam S, Mony P, Dehghan M, Li W, Rosengren A, Lopez-Jaramillo P, Diaz R, Oliveira G, et al.: Prevalence of a healthy lifestyle among individuals with cardiovascular disease in high-, middle- and low-income countries: The Prospective Urban Rural Epidemiology (PURE) study. JAMA 2013, 309(15):1613-1621.
  • [14]Elwell-Sutton TM, Jiang CQ, Zhang WS, Cheng KK, Lam TH, Leung GM, Schooling CM: Inequality and inequity in access to health care and treatment for chronic conditions in China: the Guangzhou Biobank cohort study. Health Policy Plan 2012, 28:467.
  • [15]Rottingen JA, Regmi S, Eide M, Young AJ, Viergever RF, Ardal C, Guzman J, Edwards D, Matlin SA, Terry RF: Mapping of available health research and development data: what’s there, what’s missing, and what role is there for a global observatory? Lancet 2013, 382(9900):1286-1307.
  • [16]Moffatt MF, Gut IG, Demenais F, Strachan DP, Bouzigon E, Heath S, von Mutius E, Farrall M, Lathrop M, Cookson WO: A large-scale, consortium-based genomewide association study of asthma. N Engl J Med 2010, 363(13):1211-1221.
  • [17]Moffatt MF, Kabesch M, Liang L, Dixon AL, Strachan D, Heath S, Depner M, von Berg A, Bufe A, Rietschel E, et al.: Genetic variants regulating ORMDL3 expression contribute to the risk of childhood asthma. Nature 2007, 448(7152):470-473.
  • [18]Siroux V, Basagana X, Boudier A, Pin I, Garcia-Aymerich J, Vesin A, Slama R, Jarvis D, Anto JM, Kauffmann F, et al.: Identifying adult asthma phenotypes using a clustering approach. Eur Respir J 2011, 38(2):310-317.
  • [19]Ioannidis JP, Trikalinos TA, Khoury MJ: Implications of small effect sizes of individual genetic variants on the design and interpretation of genetic association studies of complex diseases. Am J Epidemiol 2006, 164(7):609-614.
  • [20]Maher B: Personal genomes: the case of the missing heritability. Nature 2008, 456(7218):18-21.
  • [21]Manolio TA, Collins FS, Cox NJ, Goldstein DB, Hindorff LA, Hunter DJ, McCarthy MI, Ramos EM, Cardon LR, Chakravarti A, et al.: Finding the missing heritability of complex diseases. Nature 2009, 461(7265):747-753.
  • [22]Freimer N, Sabatti C: The human phenome project. Nat Genet 2003, 34(1):15-21.
  • [23]Oetting WS, Robinson PN, Greenblatt MS, Cotton RG, Beck T, Carey JC, Doelken SC, Girdea M, Groza T, Hamilton CM, et al.: Getting ready for the human phenome project: the 2012 forum of the human variome project. Hum Mutat 2013, 34(4):661-666.
  • [24]Potash JB, Toolan J, Steele J, Miller EB, Pearl J, Zandi PP, Schulze TG, Kassem L, Simpson SG, Lopez V, et al.: The bipolar disorder phenome database: a resource for genetic studies. Am J Psychiatry 2007, 164(8):1229-1237.
  • [25]Nesbitt G, McKenna K, Mays V, Carpenter A, Miller K, Williams M: The Epilepsy Phenome/Genome Project (EPGP) informatics platform. Int J Med Inform 2012, 82:248.
  • [26]Maddatu TP, Grubb SC, Bult CJ, Bogue MA: Mouse Phenome Database (MPD). Nucleic Acids Res 2012, 40(Database issue):D887-D894.
  • [27]Piran S, Liu P, Morales A, Hershberger RE: Where genome meets phenome: rationale for integrating genetic and protein biomarkers in the diagnosis and management of dilated cardiomyopathy and heart failure. J Am Coll Cardiol 2012, 60(4):283-289.
  • [28]Eppsteiner RW, Shearer AE, Hildebrand MS, Taylor KR, Deluca AP, Scherer S, Huygen P, Scheetz TE, Braun TA, Casavant TL, et al.: Using the phenome and genome to improve genetic diagnosis for deafness. Otolaryngol Head Neck Surg 2012, 147(5):975-977.
  • [29]Ritchie MD, Denny JC, Zuvich RL, Crawford DC, Schildcrout JS, Bastarache L, Ramirez AH, Mosley JD, Pulley JM, Basford MA, et al.: Genome- and phenome-wide analyses of cardiac conduction identifies markers of arrhythmia risk. Circulation 2013, 127(13):1377-1385.
  • [30]Groza T, Hunter J, Zankl A: Decomposing phenotype descriptions for the human skeletal phenome. Biomed Inform Insights 2013, 6:1-14.
  • [31]Warner JL, Alterovitz G: Phenome based analysis as a means for discovering context dependent clinical reference ranges. AMIA Symp 2012, 2012:1441-1449.
  • [32]Pathak J, Kiefer RC, Bielinski SJ, Chute CG: Mining the human phenome using semantic web technologies: a case study for type 2 Diabetes. AMIA Symp 2012, 2012:699-708.
  • [33]Pathak J, Kiefer RC, Bielinski SJ, Chute CG: Applying semantic web technologies for phenome-wide scan using an electronic health record linked Biobank. J Biomed Semantics 2012, 3(1):10.
  • [34]Goh KI, Cusick ME, Valle D, Childs B, Vidal M, Barabasi AL: The human disease network. Proc Natl Acad Sci U S A 2007, 104(21):8685-8690.
  • [35]Barabasi AL, Gulbahce N, Loscalzo J: Network medicine: a network-based approach to human disease. Nat Rev Genet 2011, 12(1):56-68.
  • [36]Garcia-Olmos L, Salvador CH, Alberquilla A, Lora D, Carmona M, Garcia-Sagredo P, Pascual M, Munoz A, Monteagudo JL, Garcia-Lopez F: Comorbidity patterns in patients with chronic diseases in general practice. PLoS One 2012, 7(2):e32141.
  • [37]Marengoni A, Angleman S, Melis R, Mangialasche F, Karp A, Garmen A, Meinow B, Fratiglioni L: Aging with multimorbidity: a systematic review of the literature. Ageing Res Rev 2011, 10(4):430-439.
  • [38]Liu YI, Wise PH, Butte AJ: The “etiome”: identification and clustering of human disease etiological factors. BMC Bioinforma 2009, 10(Suppl 2):S14.
  • [39]Rzhetsky A, Wajngurt D, Park N, Zheng T: Probing genetic overlap among complex human phenotypes. Proc Natl Acad Sci U S A 2007, 104(28):11694-11699.
  • [40]Hidalgo CA, Blumm N, Barabasi AL, Christakis NA: A dynamic network approach for the study of human phenotypes. PLoS Comput Biol 2009, 5(4):e1000353.
  • [41]Hwang T, Atluri G, Xie M, Dey S, Hong C, Kumar V, Kuang R: Co-clustering phenome-genome for phenotype classification and disease gene discovery. Nucleic Acids Res 2012, 40(19):e146.
  • [42]Jain P, Vig S, Datta M, Jindel D, Mathur AK, Mathur SK, Sharma A: Systems biology approach reveals genome to phenome correlation in type 2 diabetes. PLoS One 2013, 8(1):e53522.
  • [43]Hebbring SJ, Schrodi SJ, Ye Z, Zhou Z, Page D, Brilliant MH: A PheWAS approach in studying HLA-DRB1*1501. Genes Immun 2013, 14(3):187-191.
  • [44]Wild CP: Complementing the genome with an “exposome”: the outstanding challenge of environmental exposure measurement in molecular epidemiology. Cancer Epidemiol Biomarkers Prev 2005, 14(8):1847-1850.
  • [45]Rappaport SM, Smith MT: Epidemiology. environment and disease risks. Science 2010, 330(6003):460-461.
  • [46]Callaway E: Daily dose of toxics to be tracked. Nature 2012, 491(7426):647.
  • [47]MacNee W: Accelerated lung aging: a novel pathogenic mechanism of chronic obstructive pulmonary disease (COPD). Biochem Soc Trans 2009, 37(Pt 4):819-823.
  • [48]Edwards D: Immunological effects of tobacco smoking in “healthy” smokers. COPD 2009, 6(1):48-58.
  • [49]Leung WC, Harvey I: Is skin ageing in the elderly caused by sun exposure or smoking? Br J Dermatol 2002, 147(6):1187-1191.
  • [50]Bruce-Keller AJ, Keller JN, Morrison CD: Obesity and vulnerability of the CNS. Biochim Biophys Acta 2009, 1792(5):395-400.
  • [51]Monickaraj F, Aravind S, Gokulakrishnan K, Sathishkumar C, Prabu P, Prabu D, Mohan V, Balasubramanyam M: Accelerated aging as evidenced by increased telomere shortening and mitochondrial DNA depletion in patients with type 2 diabete. Mol Cell Biochem 2012, 365(1-2):343-350.
  • [52]Tzanetakou IP, Katsilambros NL, Benetos A, Mikhailidis DP: Perrea DN: “Is obesity linked to aging?” Adipose tissue and the role of telomeres . Ageing Res Rev 2012, 11(2):220-229.
  • [53]Apatzidou DA, Riggio MP, Kinane DF: Impact of smoking on the clinical, microbiological and immunological parameters of adult patients with periodontitis. J Clin Periodontol 2005, 32(9):973-983.
  • [54]Dinas PC, Koutedakis Y, Flouris AD: Effects of active and passive tobacco cigarette smoking on heart rate variability. Int J Cardiol 2011, 163:109.
  • [55]Barnes DE, Yaffe K: The projected effect of risk factor reduction on Alzheimer’s disease prevalence. Lancet Neurol 2011, 10(9):819-828.
  • [56]Kucharska-Newton AM, Couper DJ, Pankow JS, Prineas RJ, Rea TD, Sotoodehnia N, Chakravarti A, Folsom AR, Siscovick DS, Rosamond WD: Hemostasis, inflammation, and fatal and nonfatal coronary heart disease: long-term follow-up of the atherosclerosis risk in communities (ARIC) cohort. Arterioscler Thromb Vasc Biol 2009, 29(12):2182-2190.
  • [57]Green AC, Hughes MC, McBride P, Fourtanier A: Factors associated with premature skin aging (photoaging) before the age of 55: a population-based study. Dermatology 2011, 222(1):74-80.
  • [58]Khoo CC, Woo J, Leung PC, Kwok A, Kwok T: Determinants of bone mineral density in older postmenopausal Chinese women. Climacteric 2011, 14(3):378-383.
  • [59]Sheridan PA, Paich HA, Handy J, Karlsson EA, Hudgens MG, Sammon AB, Holland LA, Weir S, Noah TL, Beck MA: Obesity is associated with impaired immune response to influenza vaccination in humans. Int J Obes 2011, 36:1072-1077.
  • [60]Fardet L, Cabane J, Lebbe C, Morel P, Flahault A: Incidence and risk factors for corticosteroid-induced lipodystrophy: a prospective study. J Am Acad Dermatol 2007, 57(4):604-609.
  • [61]Latchman PL, Mathur M, Bartels MN, Axtell RS, De Meersman RE: Impaired autonomic function in normotensive obese children. Clin Auton Res 2011, 21(5):319-323.
  • [62]Su LH, Chen HH: Androgenetic alopecia in policemen: higher prevalence and different risk factors relative to the general population (KCIS no. 23). Arch Dermatol Res 2011, 303(10):753-761.
  • [63]Martinez Perez JA, Palacios S, Garcia FC, Perez M: Assessing osteoporosis risk factors in Spanish menopausal women. Gynecol Endocrinol 2011, 27(10):807-813.
  • [64]Mohan SV, Liao YJ, Kim JW, Goronzy JJ, Weyand CM: Giant cell arteritis: immune and vascular aging as disease risk factors. Arthritis Res Ther 2011, 13(4):231.
  • [65]Garg A, Agarwal AK: Lipodystrophies: disorders of adipose tissue biology. Biochim Biophys Acta 2009, 1791(6):507-513.
  • [66]Scott D, Blizzard L, Fell J, Jones G: The epidemiology of sarcopenia in community living older adults: what role does lifestyle play? J Cachexia Sarcopenia Muscle 2011, 2(3):125-134.
  • [67]Arai Y, Takayama M, Abe Y, Hirose N: Adipokines and aging. J Atheroscler Thromb 2011, 18(7):545-550.
  • [68]Podtelezhnikov AA, Tanis KQ, Nebozhyn M, Ray WJ, Stone DJ, Loboda AP: Molecular insights into the pathogenesis of Alzheimer’s disease and its relationship to normal aging. PLoS One 2011, 6(12):e29610.
  • [69]Zhang Z, Francisco EM, Holden JK, Dennis RG, Tommerdahl M: Somatosensory information processing in the aging population. Front Aging Neurosci 2011, 3:18.
  • [70]Jeck WR, Siebold AP, Sharpless NE: Review: a meta-analysis of GWAS and age-associated diseases. Aging cell 2012, 11(5):727-731.
  • [71]Sivakumaran S, Agakov F, Theodoratou E, Prendergast JG, Zgaga L, Manolio T, Rudan I, McKeigue P, Wilson JF, Campbell H: Abundant pleiotropy in human complex diseases and traits. Am J Hum Genet 2011, 89(5):607-618.
  • [72]Becker KG: The common variants/multiple disease hypothesis of common complex genetic disorders. Med Hypotheses 2004, 62(2):309-317.
  • [73]Contois JH, Anamani DE, Tsongalis GJ: The underlying molecular mechanism of apolipoprotein E polymorphism: relationships to lipid disorders, cardiovascular disease, and Alzheimer’s disease. Clin Lab Med 1996, 16(1):105-123.
  • [74]Gudmundsson J, Sulem P, Manolescu A, Amundadottir LT, Gudbjartsson D, Helgason A, Rafnar T, Bergthorsson JT, Agnarsson BA, Baker A, et al.: Genome-wide association study identifies a second prostate cancer susceptibility variant at 8q24. Nat Genet 2007, 39(5):631-637.
  • [75]Wolf N, Quaranta M, Prescott NJ, Allen M, Smith R, Burden AD, Worthington J, Griffiths CE, Mathew CG, Barker JN, et al.: Psoriasis is associated with pleiotropic susceptibility loci identified in type II diabetes and Crohn disease. J Med Genet 2008, 45(2):114-116.
  • [76]Wang K, Baldassano R, Zhang H, Qu HQ, Imielinski M, Kugathasan S, Annese V, Dubinsky M, Rotter JI, Russell RK, et al.: Comparative genetic analysis of inflammatory bowel disease and type 1 diabetes implicates multiple loci with opposite effects. Hum Mol Genet 2010, 19(10):2059-2067.
  • [77]Goldberger AL: Giles f. Filley lecture. Complex systems. Proc Am Thorac Soc 2006, 3(6):467-471.
  • [78]Resnicow K, Page SE: Embracing chaos and complexity: a quantum change for public health. Am J Public Health 2008, 98(8):1382-1389.
  • [79]Goldberger AL, Amaral LA, Hausdorff JM, Ivanov P, Peng CK, Stanley HE: Fractal dynamics in physiology: alterations with disease and aging. Proc Natl Acad Sci U S A 2002, 99(Suppl 1):2466-2472.
  • [80]Peng CK, Yang AC, Goldberger AL: Statistical physics approach to categorize biologic signals: from heart rate dynamics to DNA sequences. Chaos 2007, 17(1):015115.
  • [81]Zhang Z, Ye W, Qian Y, Zheng Z, Huang X, Hu G: Chaotic motifs in gene regulatory networks. PLoS One 2012, 7(7):e39355.
  • [82]Kent JW Jr: Analysis of multiple phenotypes. Genet Epidemiol 2009, 33(Suppl 1):S33-S39.
  • [83]Karasik D, Kiel DP: Evidence for pleiotropic factors in genetics of the musculoskeletal system. Bone 2010, 46(5):1226-1237.
  • [84]Keller BJ, Eichinger F, Kretzler M: Formal concept analysis of disease similarity. AMIA Summits on Translational Science proceedings AMIA Summit on Translational Science 2012, 2012:42-51.
  • [85]Pendergrass SA, Dudek S, Crawford DC, Ritchie MD: Visually integrating and exploring high throughput Phenome-Wide Association (PheWAS) results using PheWAS-View. BioData Min 2012, 5(1):5.
  • [86]Kohler S, Doelken SC, Rath A, Ayme S, Robinson PN: Ontological phenotype standards for neurogenetics. Hum Mutat 2012, 33:1333-1339.
  • [87]Oellrich A, Gkoutos GV, Hoehndorf R, Rebholz-Schuhmann D: Quantitative comparison of mapping methods between human and mammalian phenotype ontology. J Biomed Semantics 2012, 3(Suppl 2):S1.
  • [88]Rebholz-Schuhmann D, Oellrich A, Hoehndorf R: Text-mining solutions for biomedical research: enabling integrative biology. Nat Rev Genet 2012, 13(12):829-839.
  • [89]Probst-Hensch NM: Chronic age-related diseases share risk factors: do they share pathophysiological mechanisms and why does that matter? Swiss Med Wkly 2010, 140:w13072.
  • [90]Harvey AE, Lashinger LM, Hursting SD: The growing challenge of obesity and cancer: an inflammatory issue. Ann N Y Acad Sci 2011, 1229:45-52.
  • [91]Aller MA, Arias N, Fuentes-Julian S, Blazquez-Martinez A, Argudo S, Miguel MP, Arias JL, Arias J: Coupling inflammation with evo-devo. Med Hypotheses 2012, 78(6):721-731.
  • [92]Boyer JF, Bongard V, Cantagrel A, Jamard B, Gottenberg JE, Mariette X, Davignon JL, Ferrieres J, Ruidavets JB, Dallongeville J, et al.: Link between traditional cardiovascular risk factors and inflammation in early arthritis patients. Arthritis Care Res (Hoboken) 2012, 64(6):872-880.
  • [93]Knoppers BM, Fortier I, Legault D, Burton P: The Public Population Project in Genomics (P3G): a proof of concept? Eur J Hum Genet 2008, 16(6):664-665.
  • [94]Diederichs C, Berger K, Bartels DB: The measurement of multiple chronic diseases–a systematic review on existing multimorbidity indices. J Gerontol A Biol Sci Med Sci 2011, 66(3):301-311.
  • [95]Cordell S: The biobank as an ethical subject. Health Care Anal 2011, 19(3):282-294.
  • [96]Gottweis H, Chen H, Starkbaum J: Biobanks and the phantom public. Human genetics 2011, 130(3):433-440.
  • [97]Holm S: Withdrawing from research: a rethink in the context of research biobanks. Health Care Anal 2011, 19(3):269-281.
  文献评价指标  
  下载次数:2次 浏览次数:14次