LifeGene--a large prospective population-based study of global relevance

Catarina Almqvist, Hans-Olov Adami, Paul W Franks, Leif Groop, Erik Ingelsson, Juha Kere, Lauren Lissner, Jan-Eric Litton, Markus Maeurer, Karl Michaëlsson, Juni Palmgren, Göran Pershagen, Alexander Ploner, Patrick F Sullivan, Gunnel Tybring, Nancy L Pedersen, Catarina Almqvist, Hans-Olov Adami, Paul W Franks, Leif Groop, Erik Ingelsson, Juha Kere, Lauren Lissner, Jan-Eric Litton, Markus Maeurer, Karl Michaëlsson, Juni Palmgren, Göran Pershagen, Alexander Ploner, Patrick F Sullivan, Gunnel Tybring, Nancy L Pedersen

Abstract

Studying gene-environment interactions requires that the amount and quality of the lifestyle data is comparable to what is available for the corresponding genomic data. Sweden has several crucial prerequisites for comprehensive longitudinal biomedical research, such as the personal identity number, the universally available national health care system, continuously updated population and health registries and a scientifically motivated population. LifeGene builds on these strengths to bridge the gap between basic research and clinical applications with particular attention to populations, through a unique design in a research-friendly setting. LifeGene is designed both as a prospective cohort study and an infrastructure with repeated contacts of study participants approximately every 5 years. Index persons aged 18-45 years old will be recruited and invited to include their household members (partner and any children). A comprehensive questionnaire addressing cutting-edge research questions will be administered through the web with short follow-ups annually. Biosamples and physical measurements will also be collected at baseline, and re-administered every 5 years thereafter. Event-based sampling will be a key feature of LifeGene. The household-based design will give the opportunity to involve young couples prior to and during pregnancy, allowing for the first study of children born into cohort with complete pre-and perinatal data from both the mother and father. Questions and sampling schemes will be tailored to the participants' age and life events. The target of LifeGene is to enroll 500,000 Swedes and follow them longitudinally for at least 20 years.

Figures

Fig. 1
Fig. 1
Flow chart on the structure of the study. Questionnaires (Q), parental questionnaires (pQ) and In Person Testing (IPT) in adults, adolescents and children
Fig. 2
Fig. 2
Questionnaire modules in adults (a) and children (b)
Fig. 3
Fig. 3
Population distribution of the LifeGene pilot at the end of the recruitment period. Red line median over 100 simulations, dark grey are: 95% for 100 simulations

References

    1. Ollier W, Sprosen T, Peakman T. UK Biobank: from concept to reality. Pharmacogenomics. 2005;6(6):639–646. doi: 10.2217/14622416.6.6.639.
    1. Gulcher J, Stefansson K. Population genomics: laying the groundwork for genetic disease modeling and targeting. Clin Chem Lab Med. 1998;36(8):523–527. doi: 10.1515/CCLM.1998.089.
    1. Nakamura Y. The BioBank Japan project. Clin Adv Hematol Oncol. 2007;5(9):696–697.
    1. Chen Z, Lee L, Chen J, Collins R, Wu F, Guo Y, et al. Cohort profile: the Kadoorie study of chronic disease in China (KSCDC) Int J Epidemiol. 2005;34(6):1243–1249. doi: 10.1093/ije/dyi174.
    1. Naess O, Sogaard AJ, Arnesen E, Beckstrom AC, Bjertness E, Engeland A, et al. Cohort profile: cohort of Norway (CONOR) Int J Epidemiol. 2008;37(3):481–485. doi: 10.1093/ije/dym217.
    1. Stolk RP, Rosmalen JG, Postma DS, de Boer RA, Navis G, Slaets JP, et al. Universal risk factors for multifactorial diseases: LifeLines: a three-generation population-based study. Eur J Epidemiol. 2008;23(1):67–74. doi: 10.1007/s10654-007-9204-4.
    1. Nilsen RM, Vollset SE, Gjessing HK, Skjaerven R, Melve KK, Schreuder P, et al. Self-selection and bias in a large prospective pregnancy cohort in Norway. Paediatr Perinat Epidemiol. 2009;23(6):597–608. doi: 10.1111/j.1365-3016.2009.01062.x.
    1. Golding J, Pembrey M, Jones R. ALSPAC–the Avon longitudinal study of parents and children. I. study methodology. Paediatr Perinat Epidemiol. 2001;15(1):74–87. doi: 10.1046/j.1365-3016.2001.00325.x.
    1. Landrigan PJ, Trasande L, Thorpe LE, Gwynn C, Lioy PJ, D’Alton ME, et al. The National Children’s Study: a 21-year prospective study of 100,000 American children. Pediatrics. 2006;118(5):2173–2186. doi: 10.1542/peds.2006-0360.
    1. Keil T, Kulig M, Simpson A, Custovic A, Wickman M, Kull I, et al. European birth cohort studies on asthma and atopic diseases: II. Comparison of outcomes and exposures-a GA2LEN initiative. Allergy. 2006;61(9):1104–1111. doi: 10.1111/j.1398-9995.2006.01167.x.
    1. Inskip HM, Godfrey KM, Robinson SM, Law CM, Barker DJ, Cooper C. Cohort profile: the Southampton women’s survey. Int J Epidemiol. 2006;35(1):42–48. doi: 10.1093/ije/dyi202.
    1. Lombardi VC, Ruscetti FW, Das Gupta J, Pfost MA, Hagen KS, Peterson DL, et al. Detection of an infectious retrovirus, XMRV, in blood cells of patients with chronic fatigue syndrome. Science. 2009;326(5952):585–589. doi: 10.1126/science.1179052.
    1. Barker DJ. Fetal origins of coronary heart disease. BMJ. 1995;311(6998):171–174.
    1. Brooks PM. The burden of musculoskeletal disease-a global perspective. Clin Rheumatol. 2006;25(6):778–781. doi: 10.1007/s10067-006-0240-3.
    1. The global burden of disease; 2004 update. Available from . Geneva, Switzerland: WHO Press; 2006 [cited 2010, June 14].
    1. Shargorodsky J, Curhan SG, Curhan GC, Eavey R. Change in prevalence of hearing loss in US adolescents. JAMA. 2010;304(7):772–778. doi: 10.1001/jama.2010.1124.
    1. Ekman A, Litton JE. New times, new needs; e-epidemiology. Eur J Epidemiol. 2007;22(5):285–292. doi: 10.1007/s10654-007-9119-0.
    1. Ekman A, Dickman PW, Klint A, Weiderpass E, Litton JE. Feasibility of using web-based questionnaires in large population-based epidemiological studies. Eur J Epidemiol. 2006;21(2):103–111. doi: 10.1007/s10654-005-6030-4.
    1. Ekman A, Klint A, Dickman PW, Adami HO, Litton JE. Optimizing the design of web-based questionnaires—experience from a population-based study among 50,000 women. Eur J Epidemiol. 2007;22(5):293–300. doi: 10.1007/s10654-006-9091-0.
    1. Bexelius C, Honeth L, Ekman A, Eriksson M, Sandin S, Bagger-Sjoback D, et al. Evaluation of an internet-based hearing test—comparison with established methods for detection of hearing loss. J Med Internet Res. 2008;10(4):e32. doi: 10.2196/jmir.1065.
    1. Collins FS. The case for a US prospective cohort study of genes and environment. Nature. 2004;429(6990):475–477. doi: 10.1038/nature02628.
    1. Burton PR, Hansell AL, Fortier I, Manolio TA, Khoury MJ, Little J, et al. Size matters: just how big is BIG?: Quantifying realistic sample size requirements for human genome epidemiology. Int J Epidemiol. 2009;38(1):263–273. doi: 10.1093/ije/dyn147.
    1. Hernán MA, Robins JM. Observational studies analyzed like randomized experiments: best of both worlds. Epidemiology. 2008;19:789–792. doi: 10.1097/EDE.0b013e318188e85f.
    1. Prentice RL, Pettinger M, Anderson GL. Statistical issues arising in the Women’s Health Initiative. Biometrics. 2005;61(4):899–911. doi: 10.1111/j.0006-341X.2005.454_1.x.
    1. Davey Smith G, Ebrahim S. ‘Mendelian randomization’: can genetic epidemiology contribute to understanding environmental determinants of disease? Int J Epidemiol. 2003;32(1):1–22. doi: 10.1093/ije/dyg070.
    1. Ioannidis JP, Adami HO. Nested randomized trials in large cohorts and biobanks: studying the health effects of lifestyle factors. Epidemiology. 2008;19(1):75–82. doi: 10.1097/EDE.0b013e31815be01c.
    1. Collins FS, Manolio TA. Merging and emerging cohorts: necessary but not sufficient. Nature. 2007;445(7125):259. doi: 10.1038/445259a.
    1. Willett WC, Blot WJ, Colditz GA, Folsom AR, Henderson BE, Stampfer MJ. Merging and emerging cohorts: not worth the wait. Nature. 2007;445(7125):257–258. doi: 10.1038/445257a.

Source: PubMed

3
Abonnere