Limitations and risks of meta-analyses of longevity studies. (July 2017)

• Record Type: Journal Article
• Authors: Sebastiani, Paola; Bae, Harold; Gurinovich, Anastasia; Soerensen, Mette; Puca, Annibale; Perls, Thomas T.
• Is Part Of: Mechanisms of ageing and development. Volume 165:Part B(2017)
• Page Start: 139
• Page End: 146
• Publication Date: 2017-07
• Subjects: Human longevity -- Meta-analysis -- Odds-ratios; Aging -- Periodicals; Developmental biology -- Periodicals; Aging -- Periodicals; Developmental Biology -- Periodicals; Vieillissement -- Périodiques; Biologie du développement -- Périodiques; Aging; Developmental biology; Periodicals; 612.67
• DOI: 10.1016/j.mad.2017.01.008
• Languages: English
• ISSNs: 0047-6374

Abstract

Highlights: Genetic association studies of human longevity have been challenged by the rarity of the phenotype and the need of large sample sizes to have extreme statistical power. Following the principle that "more is always better", meta-analysis has become a popular method to aggregate results from individual studies and increase sample sizes. We show that meta-analysis risk to overlook between studies differences and may inflate the false negative rate of genetic associations. Abstract: Searching for genetic determinants of human longevity has been challenged by the rarity of data sets with large numbers of individuals who have reached extreme old age, inconsistent definitions of the phenotype, and the difficulty of defining appropriate controls. Meta-analysis – a statistical method to summarize results from different studies – has become a common tool in genetic epidemiology to accrue large sample sizes for powerful genetic association studies. In conducting a meta-analysis of studies of human longevity however, particular attention must be made to the definition of cases and controls (including their health status) and on the effect of possible confounders such as sex and ethnicity upon the genetic effect to be estimated. We will show examples of how a meta-analysis can inflate the false negative rates of genetic association studies or it can bias estimates of the association between a genetic variant and extreme longevity.