A logistic regression model for measuring gene-longevity associations

Q. Tan; A.I. Yashin; G. De Benedictis; F. Cintolesi; G. Rose; M. Bonafe; C. Francheschi; W. Vach; J.W. Vaupel

doi:10.1034/j.1399-0004.2001.600610.x

A logistic regression model for measuring gene-longevity associations

Q. Tan^*, A.I. Yashin, G. De Benedictis, F. Cintolesi, G. Rose, M. Bonafe, C. Francheschi, W. Vach, J.W. Vaupel

^*Corresponding author for this work

Research output: Contribution to journal › Journal article › Research › peer-review

Abstract

The logistic regression model is a popular model for data analysis in epidemiological research. In this paper, we use this model to analyze genetic data collected from gene–longevity association studies. This new approach models the probability of observing one genotype as a function of the age of investigated individuals. Applying the model to genotype data on the TH and 3′ApoB‐VNTR loci collected from an Italian centenarian study, we show how it can be used to model the different ways that genes affect survival, including sex‐ and age‐specific influences. We highlight the advantages of this application over other available models. The application of the model to empirical data indicates that it is an efficient and easily applicable approach for determining the influences of genes on human longevity.

Original language	English
Journal	Clinical Genetics
Volume	60
Pages (from-to)	463-469
ISSN	0009-9163
DOIs	https://doi.org/10.1034/j.1399-0004.2001.600610.x
Publication status	Published - 2001

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10.1034/j.1399-0004.2001.600610.x

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title = "A logistic regression model for measuring gene-longevity associations",

abstract = "The logistic regression model is a popular model for data analysis in epidemiological research. In this paper, we use this model to analyze genetic data collected from gene–longevity association studies. This new approach models the probability of observing one genotype as a function of the age of investigated individuals. Applying the model to genotype data on the TH and 3′ApoB‐VNTR loci collected from an Italian centenarian study, we show how it can be used to model the different ways that genes affect survival, including sex‐ and age‐specific influences. We highlight the advantages of this application over other available models. The application of the model to empirical data indicates that it is an efficient and easily applicable approach for determining the influences of genes on human longevity.",

author = "Q. Tan and A.I. Yashin and {De Benedictis}, G. and F. Cintolesi and G. Rose and M. Bonafe and C. Francheschi and W. Vach and J.W. Vaupel",

year = "2001",

doi = "10.1034/j.1399-0004.2001.600610.x",

language = "English",

volume = "60",

pages = "463--469",

journal = "Clinical Genetics",

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T1 - A logistic regression model for measuring gene-longevity associations

AU - Tan, Q.

AU - Yashin, A.I.

AU - De Benedictis, G.

AU - Cintolesi, F.

AU - Rose, G.

AU - Bonafe, M.

AU - Francheschi, C.

AU - Vach, W.

AU - Vaupel, J.W.

PY - 2001

Y1 - 2001

N2 - The logistic regression model is a popular model for data analysis in epidemiological research. In this paper, we use this model to analyze genetic data collected from gene–longevity association studies. This new approach models the probability of observing one genotype as a function of the age of investigated individuals. Applying the model to genotype data on the TH and 3′ApoB‐VNTR loci collected from an Italian centenarian study, we show how it can be used to model the different ways that genes affect survival, including sex‐ and age‐specific influences. We highlight the advantages of this application over other available models. The application of the model to empirical data indicates that it is an efficient and easily applicable approach for determining the influences of genes on human longevity.

AB - The logistic regression model is a popular model for data analysis in epidemiological research. In this paper, we use this model to analyze genetic data collected from gene–longevity association studies. This new approach models the probability of observing one genotype as a function of the age of investigated individuals. Applying the model to genotype data on the TH and 3′ApoB‐VNTR loci collected from an Italian centenarian study, we show how it can be used to model the different ways that genes affect survival, including sex‐ and age‐specific influences. We highlight the advantages of this application over other available models. The application of the model to empirical data indicates that it is an efficient and easily applicable approach for determining the influences of genes on human longevity.

U2 - 10.1034/j.1399-0004.2001.600610.x

DO - 10.1034/j.1399-0004.2001.600610.x

M3 - Journal article

SN - 0009-9163

VL - 60

SP - 463

EP - 469

JO - Clinical Genetics

JF - Clinical Genetics

ER -

A logistic regression model for measuring gene-longevity associations

Abstract

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