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Review
. 2009 Jan;64(1):47-60.
doi: 10.1093/gerona/gln021. Epub 2009 Jan 23.

Genetic epidemiology in aging research

M Daniele Fallin  1 , Amy Matteini
Affiliations
Review

Genetic epidemiology in aging research

M Daniele Fallin et al. J Gerontol A Biol Sci Med Sci. 2009 Jan.

Abstract

Over the last two decades, aging research has expanded to include not only age-related disease models, and conversely, longevity and disease-free models, but also focuses on biological mechanisms related to the aging process. By viewing aging on multiple research frontiers, we are rapidly expanding knowledge as a whole and mapping connections between biological processes and particular age-related diseases that emerge. This is perhaps most true in the field of genetics, where variation across individuals has improved our understanding of aging mechanisms, etiology of age-related disease, and prediction of therapeutic responses. A close partnership between gerontologists, epidemiologists, and geneticists is needed to take full advantage of emerging genome information and technology and bring about a new age for biological aging research. Here we review current genetic findings for aging across both disease-specific and aging process domains. We then highlight the limitations of most work to date in terms of study design, genomic information, and trait modeling and focus on emerging technology and future directions that can partner genetic epidemiology and aging research fields to best take advantage of the rapid discoveries in each.

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Figures

Figure 1.
Figure 1.
Direct versus indirect genetic association tests.
Figure 2.
Figure 2.
Coverage comparison between a custom-made single nucleotide polymorphism (SNP) panel for 92 candidate genes and current genomewide association panels. The y axis shows the ratio of coverage for the custom panel versus either the Illumina 650 panel or the Affymetrix 6.0 panel. Coverage is defined as the percent of common (>5%) Yoruban HapMap Phase II SNPs that are in high linkage disequilibrium with genotyped SNPs on the panel (r2 ≥ .8) and thus are “covered” by the panel even if they are not genotyped. Points falling under 1 indicated that genomewide association studies have better coverage at that particular gene, whereas points falling above 1 indicate that the custom-made panel yields better coverage at that gene.
Figure 3.
Figure 3.
Possible phenotype definitions for an underlying continuous trait.
See this image and copyright information in PMC

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Publication types