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The accuracy of statistical estimates in genetic studies of aging can be significantly improved

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Abstract

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.

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Abbreviations

AD:

Alzheimer’s disease

AIC:

the Akaike information criterion

APOE :

apolipoprotein E

ICD-9-CM:

International Classification of Diseases, 9th Revision, Clinical Modification

NLTCS:

the National Long Term Care Survey

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Acknowledgements

This research was supported by NIH/NIA grants PO1 AG08761-01, U01 AG023712 and 5UO1-AG-007198-18. The authors thank V. Lewis for help in preparing this manuscript for publication.

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Authors and Affiliations

  1. Center for Demographic Studies, Duke University, 2117 Campus Drive, Box 90408, Durham, NC, 27708-0408, USA

    Anatoli I. Yashin, Konstantin G. Arbeev & Svetlana V. Ukraintseva

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  1. Anatoli I. Yashin
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  2. Konstantin G. Arbeev
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  3. Svetlana V. Ukraintseva
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Correspondence to Anatoli I. Yashin.

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Yashin, A.I., Arbeev, K.G. & Ukraintseva, S.V. The accuracy of statistical estimates in genetic studies of aging can be significantly improved. Biogerontology 8, 243–255 (2007). https://doi.org/10.1007/s10522-006-9072-4

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  • DOI: https://doi.org/10.1007/s10522-006-9072-4

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