title: Power estimation for gene-longevity association analysis using concordant twins.
abstract: Statistical power is one of the major concerns in genetic association studies. Related individuals such as twins are valuable samples for genetic studies because of their genetic relatedness. Phenotype similarity in twin pairs provides evidence of genetic control over the phenotype variation in a population. The genetic association study on human longevity, a complex trait that is under control of both genetic and environmental factors, has been confronted by the small sample sizes of longevity subjects which limit statistical power. Twin pairs concordant for longevity have increased probability for carrying beneficial genes and thus are useful samples for gene-longevity association analysis. We conducted a computer simulation to estimate the power of association study using longevity concordant twin pairs. We observed remarkable power increases in using singletons from longevity concordant twin pairs as cases in comparison with cases of sporadic proband. A similar power would require doubled sample sizes for fraternal twins than for identical twins who are concordant for longevity suggesting that longevity concordant identical twins are more efficient samples than fraternal twins. We also observed an approximate of 2- to 3-fold increase in sample sizes needed for longevity cutoff at age 90 as compared with that at age 95. Overall, our results showed high value of twins in genetic association studies on human longevity.
authors.affiliation: Epidemiology, Biostatistics and Biodemography, Institute of Public Health, University of Southern Denmark, J. B. Winsløws Vej 9B, 5000 Odense C, Denmark ; Department of Clinical Genetics, Odense University Hospital, 5000 Odense C, Denmark.
authors.forename: Qihua
authors.identifier: 0000-0003-3194-0030
authors.initials: Q
authors.lastname: Tan
authors.affiliation: MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge CB2 0QQ, UK.
authors.forename: Jing Hua
authors.identifier: 0000-0003-4930-3582
authors.initials: JH
authors.lastname: Zhao
authors.affiliation: Department of Clinical Genetics, Odense University Hospital, 5000 Odense C, Denmark.
authors.forename: Torben
authors.initials: T
authors.lastname: Kruse
authors.affiliation: Epidemiology, Biostatistics and Biodemography, Institute of Public Health, University of Southern Denmark, J. B. Winsløws Vej 9B, 5000 Odense C, Denmark.
authors.forename: Kaare
authors.initials: K
authors.lastname: Christensen