The accuracy of statistical estimates in genetic studies of aging can be significantly improved.
The sample size of the data used in genetic studies is often a factor limiting the accuracy of statistical estimates. In this paper we suggest a new approach to evaluation of genetic influence on risk of development of aging-related health disorders. The approach results in substantial improvement of the accuracy of statistical estimates without an increase in the size of the genetic sample. The approach is based on the joint analysis of data from the genetic samples and easily accessible non-genetic data, such as data collected in epidemiological, demographic, and longitudinal studies of human aging and aging-related pathologies.
Yashin
Anatoli I
AI
Center for Demographic Studies, Duke University, 2117 Campus Drive, Box 90408, Durham, NC 27708-0408, USA. yashin@cds.duke.edu
Arbeev
Konstantin G
KG
Ukraintseva
Svetlana V
SV
D000375:Aging / Q000235:genetics*; D000483:Alleles; D003627:Data Interpretation, Statistical; D005838:Genotype; D006801:Humans; D008137:Longitudinal Studies; D015233:Models, Statistical; D018401:Sample Size