RESUMO
The paper presents an extension of the regressive logistic models proposed by Bonney [Biometrics 42:611-625, 1986], to address the problems of variable age-of-onset and time-dependent covariates in analysis of familial diseases. This goal is achieved by using failure time data analysis methods, and partitioning the time of follow up in K mutually exclusive intervals. The conditional probability of being affected within the kth interval (k = 1...K) given not affected before represents the hazard function in this discrete formulation. A logistic model is used to specify a regression relationship between this hazard function and a set of explanatory variables including genotype, phenotypes of ancestors, and other covariates which can be time dependent. The probability that a given person either becomes affected within the kth interval (i.e., interval k includes age of onset of the person) or remains unaffected by the end of the kth interval (i.e., interval k includes age at examination of the person) are derived from the general results of failure time data analysis and used for the likelihood formulation. This proposed approach can be used in any genetic segregation and linkage analysis in which a penetrance function needs to be defined. Application of the method to familial leprosy data leads to results consistent with our previous analysis performed using the unified mixed model [Abel and Demenais, Am J Hum Genet 42:256-266, 1988], i.e., the presence of a recessive major gene controlling susceptibility to leprosy. Furthermore, a simulation study shows the capability of the new model to detect major gene effects and to provide accurate parameter estimates in a situation of complete ascertainment.
Assuntos
Fatores Etários , Doenças Genéticas Inatas/epidemiologia , Adolescente , Adulto , Criança , Pré-Escolar , Métodos Epidemiológicos , Humanos , Lactente , Hanseníase/epidemiologia , Hanseníase/genética , Funções Verossimilhança , Modelos Logísticos , Pessoa de Meia-Idade , Análise de Sobrevida , Fatores de Tempo , Índias Ocidentais/epidemiologiaRESUMO
This paper presents an extension of the regressive logistic model proposed by Bonney [Biometrics 42:611-625, 1986], to address the problems of variable age-of-onset and time-dependent covariates in analysis of familial diseases. The goal is achieved by using failure time data analysis methods, and partitioning the time of follow up in K mutually exclusive intervals. The conditional probability of being affected within the Kth interval (K=1...K) given not affected before represents the hazaard function in this discrete formulation. A logistic model is used to specify a regression relationship between this hazard function and a set of explanatory variables including genotype, phenotype of ancestors and other covariates which can be time independent. The probability that a given person either becomes affected within the Kth interval (ie. interval K includes age of onset of the person) or remains unaffected by the end of the Kth interval (ie. interval K includes age at examination of the person) are derived from the general result of failure time data analysis and used for the likelihood formulation. This proposed approach can be used in any genetic segregation and linkage analysis in which a penetrance function needs to be defined. Application of the method to familial leprosy data leads to results consistent with our previous analysis performed using the unified mixed model [Abel and Demenias, Am J Hum Genet 42:256-266, 1988], ie. the presence of a recessive major gene controlling susceptibility to leprosy. Furthermore, a simulation study shows the capability of the new method to detect major gene effects and to provide accurate parameter estimates in a situation of complete ascertainment. (AU)
Assuntos
Humanos , Lactente , Pré-Escolar , Criança , Adolescente , Adulto , Pessoa de Meia-Idade , Fatores Etários , Doenças Genéticas Inatas/epidemiologia , Métodos Epidemiológicos , Hanseníase/epidemiologia , Hanseníase/genética , Funções Verossimilhança , Modelos Logísticos , Análise de Sobrevida , Fatores de Tempo , Índias Ocidentais/epidemiologiaRESUMO
Scientific evidence has accumulated to show that chronic atrophic gastritis (CAG) is a precursor of gastric carcinoma, especially its intestinal histologic type; thus the etiology of CAG is of interest. Data on 110 families (557 individuals) collected as part of a large cohort from the Narino region of Colombia, South America, are analyzed to determine the familiality of CAG as a risk factor, and the possible involvement of a major gene in its etiology. We found that age and having an affected mother are important risk factors. In the sample, 45% are affected; 56% of individuals above 30 are affected, whereas only 28% of those 30 and under are affected; 48% of those with affected mothers are affected, but only 7% of those with unaffected mothers are affected. A positive spouse association was confounded with age. Sex and an affected father are not significant risk factors. The genetic (segregation) analysis showed Mendelian transmission of a recessive autosomal gene with penetrance dependent on age and mother's CAG status. Homozygous recessives account for an estimated 61% of the sampled population and have penetrance reaching 72% at age 30 if the mother is affected, and 41% if the mother is not affected. Carriers and non-carriers, who make up an estimated 39% of the sampled population, have an appreciable estimated risk after age 50. The environment, particularly diet, as the sole determinant of CAG needs reevaluation; some combined action of genes and environment seems more plausible.