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

^*Kontaktforfatter

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › 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.

Originalsprog	Engelsk
Tidsskrift	Clinical Genetics
Vol/bind	60
Sider (fra-til)	463-469
ISSN	0009-9163
DOI	https://doi.org/10.1034/j.1399-0004.2001.600610.x
Status	Udgivet - 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",

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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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