Literature DB >> 20512403

Power assessment for genetic association study of human longevity using offspring of long-lived subjects.

Qihua Tan1, Jing Hua Zhao, Shuxia Li, Torben A Kruse, Kaare Christensen.   

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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Year:  2010        PMID: 20512403      PMCID: PMC2988164          DOI: 10.1007/s10654-010-9465-1

Source DB:  PubMed          Journal:  Eur J Epidemiol        ISSN: 0393-2990            Impact factor:   8.082


  21 in total

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  8 in total

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