Abstract
Recently, an indirect genetic association approach that compares genotype frequencies in offspring of long-lived subjects and offspring from random families has been introduced to study gene-longevity associations. Although the indirect genetic association has certain advantages over the direct association approach that compares genotype frequency between centenarians and young controls, the power has been of concern. This paper reports a power study performed on the indirect approach using computer simulation. We perform our simulation study by introducing the current Danish population life table and the proportional hazard model for generating individual lifespan. Family genotype data is generated using a genetic linkage program for given SNP allele frequency. Power is estimated by setting the type I error rate at 0.05 and by calculating the Armitage’s chi-squared test statistic for 200 replicate samples for each setting of the specified allele risk and frequency parameters under different modes of inheritance and for different sample sizes. The indirect genetic association analysis is a valid approach for studying gene-longevity association, but the sample size requirement is about 3–4 time larger than the direct approach. It also has low power in detecting non-additive effect genes. Indirect genetic association using offspring from families with both parents as nonagenarians is nearly as powerful as using offspring from families with one centenarian parent. In conclusion, the indirect design can be a good choice for studying longevity in comparison with other alternatives, when relatively large sample size is available.
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References
Tan Q, Kruse TA, Christensen K. Design and analysis in genetic studies of human aging and longevity. Ageing Res Rev. 2006;5:371–6.
Vaupel JW, Carey JR, Christensen K, et al. Biodemographic trajectories of longevity. Science. 1998;280:855–60.
Barzilai N, Atzmon G, Schechter C, et al. Unique lipoprotein phenotype and genotype associated with exceptional longevity. JAMA. 2003;290:2030–40.
Adams ER, Nolan VG, Andersen SL, Perls TT, Terry DF. Centenarian offspring: start healthier and stay healthier. J Am Geriatr Soc. 2008;56:2089–92.
Suh Y, Atzmon G, Cho MO, et al. Functionally significant insulin-like growth factor I receptor mutations in centenarians. Proc Natl Acad Sci USA. 2008;105:3438–42.
Puca AA, Andrew P, Novelli V, et al. Fatty acid profile of erythrocyte membranes as possible biomarker of longevity. Rejuvenation Res. 2008;11:63–72.
Terry DF, Evans JC, Pencina MJ, et al. Characteristics of Framingham offspring participants with long-lived parents. Arch Intern Med. 2007;167:438–44.
Atzmon G, Pollin TI, Crandall J, et al. Adiponectin levels and genotype: a potential regulator of life span in humans. J Gerontol A Biol Sci Med Sci. 2008;63:447–53.
De Rango F, Dato S, Bellizzi D, et al. A novel sampling design to explore gene-longevity associations: the ECHA study. Eur J Hum Genet. 2008;16:236–42.
Terry DF, Wyszynski DF, Nolan VG, et al. Serum heat shock protein 70 level as a biomarker of exceptional longevity. Mech Ageing Dev. 2006;127:862–8.
Atzmon G, Glyde S, Greiner W, Davidson D, Rennert G, Barzilai N. Clinical phenotype of families with longevity. J Am Geriatr Soc. 2004;52:274–7.
Rose G, Passarino G, Scornaienchi V, et al. The mitochondrial DNA control region shows genetically correlated levels of heteroplasmy in leukocytes of centenarians and their offspring. BMC Genomics. 2007;8:293.
Willems JM, Trompet S, Eline Slagboom P, de Craen AJ, Westendorp RG. Hematopoietic capacity and exceptional survival: the leiden longevity study. J Am Geriatr Soc. 2008;56:1013–2009.
Tan Q, Zhao JH, Zhang D, Kruse TA, Christensen K. Power for genetic association study of human longevity using the case-control design. Am J Epidemiol. 2008;168:890–6.
Gerdes LU, Jeune B, Ranberg KA, Nybo H, Vaupel JW. Estimation of apolipoprotein E genotype-specific relative mortality risks from the distribution of genotypes in centenarians and middle-aged men: apolipoprotein E gene is a “frailty gene”, not a “longevity gene”. Genet Epidemiol. 2000;19:202–10.
Vaupel JW, Manton KG, Stallard E. The impact of heterogeneity in individual frailty on dynamics of mortality. Demography. 1979;16:439–54.
Tan Q. How genes affect longevity in heterogeneous populations: binomial frailty models and applications. PhD thesis. 2000; University of Southern Denmark.
Tan Q, De Benedictis G, Yashi AI, et al. Measuring the genetic influence on human lifespan: gene-environment interaction and sex-specific genetic effects. Biogerontology. 2001;2:141–53.
Abecasis GR, Cherny SS, Cookson WO, Cardon LR. Merlin–rapid analysis of dense genetic maps using sparse gene flow trees. Nat Genet. 2002;30:97–101.
Sasieni PD. From genotypes to genes: doubling the sample size. Biometrics. 1997;53:1253–61.
Hjelmborg VBJ, Iachine I, Skytthe A, et al. Genetic influence on human lifespan and longevity. Hum Genet. 2006;119:312–21.
Tan Q, Christiansen L, Christensen K, Kruse TA, Bathum L. Apolipoprotein E genotype frequency patterns in aged Danes as revealed by logistic regression models. Eur J Epidemiol. 2004;19:651–6.
Acknowledgments
This work was supported by the National Institutes of Health [U01AG023712]; and the National Institute of Aging [P01-AG08761].
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Tan, Q., Zhao, J.H., Li, S. et al. Power assessment for genetic association study of human longevity using offspring of long-lived subjects. Eur J Epidemiol 25, 501–506 (2010). https://doi.org/10.1007/s10654-010-9465-1
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DOI: https://doi.org/10.1007/s10654-010-9465-1