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Assessing genetic association with human survival at multi-allelic loci.

Publication ,  Journal Article
Tan, Q; De Benedictis, G; Yashin, AI; Bathum, L; Christiansen, L; Dahlgaard, J; Frizner, N; Vach, W; Vaupel, JW; Christensen, K; Kruse, TA
Published in: Biogerontology
January 2004

Genetic variation plays an important role in natural selection and population evolution. However, it also presents geneticists interested in aging research with problems in data analysis because of the large number of alleles and their various modes of action. Recently, a new statistical method based on survival analysis (the relative risk model or the RR model) has been introduced to assess gene-longevity associations [Yashin et al. (1999) Am J Hum Genet 65: 1178-1193] which outperforms the traditional gene frequency method. Here we extend the model to deal with polymorphic genes or gene markers. Assuming the Hardy-Weinberg equilibrium at birth, we first introduce an allele-based parameterization on gene frequency which helps to cut down the number of frequency parameters to be estimated. We then propose both the genotype and allele-based parameterizations on risk parameters to estimate genotype and allelic relative risks (the GRR and ARR models). While the GRR model allows us to investigate whether the alleles are recessive, dominant or codominant, the ARR model further minimizes the number of parameters to be estimated. As an example, we apply the methods to empirical data on Renin gene polymorphism and longevity. We show that our models can serve as useful tools in searching for important genetic variations implicated in human aging and longevity.

Duke Scholars

Published In

Biogerontology

DOI

EISSN

1573-6768

ISSN

1389-5729

Publication Date

January 2004

Volume

5

Issue

2

Start / End Page

89 / 97

Related Subject Headings

  • Risk Assessment
  • Renin
  • Models, Genetic
  • Mathematics
  • Longevity
  • Humans
  • Gerontology
  • Genotype
  • Genetic Variation
  • Alleles
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Tan, Q., De Benedictis, G., Yashin, A. I., Bathum, L., Christiansen, L., Dahlgaard, J., … Kruse, T. A. (2004). Assessing genetic association with human survival at multi-allelic loci. Biogerontology, 5(2), 89–97. https://doi.org/10.1023/b:bgen.0000025072.30441.1c
Tan, Qihua, G. De Benedictis, A. I. Yashin, L. Bathum, L. Christiansen, J. Dahlgaard, N. Frizner, et al. “Assessing genetic association with human survival at multi-allelic loci.Biogerontology 5, no. 2 (January 2004): 89–97. https://doi.org/10.1023/b:bgen.0000025072.30441.1c.
Tan Q, De Benedictis G, Yashin AI, Bathum L, Christiansen L, Dahlgaard J, et al. Assessing genetic association with human survival at multi-allelic loci. Biogerontology. 2004 Jan;5(2):89–97.
Tan, Qihua, et al. “Assessing genetic association with human survival at multi-allelic loci.Biogerontology, vol. 5, no. 2, Jan. 2004, pp. 89–97. Epmc, doi:10.1023/b:bgen.0000025072.30441.1c.
Tan Q, De Benedictis G, Yashin AI, Bathum L, Christiansen L, Dahlgaard J, Frizner N, Vach W, Vaupel JW, Christensen K, Kruse TA. Assessing genetic association with human survival at multi-allelic loci. Biogerontology. 2004 Jan;5(2):89–97.
Journal cover image

Published In

Biogerontology

DOI

EISSN

1573-6768

ISSN

1389-5729

Publication Date

January 2004

Volume

5

Issue

2

Start / End Page

89 / 97

Related Subject Headings

  • Risk Assessment
  • Renin
  • Models, Genetic
  • Mathematics
  • Longevity
  • Humans
  • Gerontology
  • Genotype
  • Genetic Variation
  • Alleles