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Analysis of Swedish male breast cancer family data : a simple way to incorporate a common sibling effect

Karunaratne, P M; Elston, R C; Loman, N LU ; Olsson, H LU and Ranstam, J LU (1998) In Genetic Epidemiology 15(2). p.12-201
Abstract

Based on a population-based cohort study, Olsson et al. [1993] found significant evidence for elevated incidence of breast and ovarian cancers among female first-degree relatives of men with breast cancer. Using an extension of logistic regressive models we investigate whether, after allowing for multifactorial familial correlations, single locus segregation could be the cause of the elevated incidence in these families. The logit for a given sib in the class D logistic regressive model depends on the order in which affected sibs occur in a sibship. That makes the model less appropriate for the situation where a polygenic component or a common sibling environment may be present, as well as being computationally cumbersome. In this... (More)

Based on a population-based cohort study, Olsson et al. [1993] found significant evidence for elevated incidence of breast and ovarian cancers among female first-degree relatives of men with breast cancer. Using an extension of logistic regressive models we investigate whether, after allowing for multifactorial familial correlations, single locus segregation could be the cause of the elevated incidence in these families. The logit for a given sib in the class D logistic regressive model depends on the order in which affected sibs occur in a sibship. That makes the model less appropriate for the situation where a polygenic component or a common sibling environment may be present, as well as being computationally cumbersome. In this paper, we propose to use the proportion of siblings in a sibship who are affected to quantify a sibling correlation. That not only relaxes the interchangeability problem but also makes the model computationally efficient. We then use this modified class D logistic regressive model for our segregation analysis. Using the proportion of siblings in a sibship who are affected as a covariate resulted in a significantly higher likelihoods in all the models we investigated. We found evidence for a dominant Mendelian gene leading to early age of onset of breast and/or ovarian cancer. This could either be a germline mutation of BRCA2 or a mutation in a gene different from BRCA2.

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organization
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Contribution to journal
publication status
published
subject
keywords
Adult, Aged, Aged, 80 and over, BRCA2 Protein, Breast Neoplasms, Breast Neoplasms, Male, Cohort Studies, Data Interpretation, Statistical, Family Health, Female, Follow-Up Studies, Humans, Incidence, Male, Middle Aged, Models, Genetic, Models, Statistical, Mutation, Neoplasm Proteins, Prevalence, Regression Analysis, Risk Assessment, Sweden, Transcription Factors
in
Genetic Epidemiology
volume
15
issue
2
pages
12 pages
publisher
John Wiley & Sons
external identifiers
  • pmid:9554557
ISSN
0741-0395
DOI
10.1002/(SICI)1098-2272(1998)15:2<201::AID-GEPI8>3.0.CO;2-8http://dx.doi.org/10.1002/(SICI)1098-2272(1998)15:2<201::AID-GEPI8>3.0.CO;2-8
language
English
LU publication?
yes
id
627876f0-b745-42a8-b06c-35895055ba63 (old id 1112797)
date added to LUP
2008-07-11 11:18:58
date last changed
2016-09-20 09:56:01
@article{627876f0-b745-42a8-b06c-35895055ba63,
  abstract     = {<p>Based on a population-based cohort study, Olsson et al. [1993] found significant evidence for elevated incidence of breast and ovarian cancers among female first-degree relatives of men with breast cancer. Using an extension of logistic regressive models we investigate whether, after allowing for multifactorial familial correlations, single locus segregation could be the cause of the elevated incidence in these families. The logit for a given sib in the class D logistic regressive model depends on the order in which affected sibs occur in a sibship. That makes the model less appropriate for the situation where a polygenic component or a common sibling environment may be present, as well as being computationally cumbersome. In this paper, we propose to use the proportion of siblings in a sibship who are affected to quantify a sibling correlation. That not only relaxes the interchangeability problem but also makes the model computationally efficient. We then use this modified class D logistic regressive model for our segregation analysis. Using the proportion of siblings in a sibship who are affected as a covariate resulted in a significantly higher likelihoods in all the models we investigated. We found evidence for a dominant Mendelian gene leading to early age of onset of breast and/or ovarian cancer. This could either be a germline mutation of BRCA2 or a mutation in a gene different from BRCA2.</p>},
  author       = {Karunaratne, P M and Elston, R C and Loman, N and Olsson, H and Ranstam, J},
  issn         = {0741-0395},
  keyword      = {Adult,Aged,Aged, 80 and over,BRCA2 Protein,Breast Neoplasms,Breast Neoplasms, Male,Cohort Studies,Data Interpretation, Statistical,Family Health,Female,Follow-Up Studies,Humans,Incidence,Male,Middle Aged,Models, Genetic,Models, Statistical,Mutation,Neoplasm Proteins,Prevalence,Regression Analysis,Risk Assessment,Sweden,Transcription Factors},
  language     = {eng},
  number       = {2},
  pages        = {12--201},
  publisher    = {John Wiley & Sons},
  series       = {Genetic Epidemiology},
  title        = {Analysis of Swedish male breast cancer family data : a simple way to incorporate a common sibling effect},
  url          = {http://dx.doi.org/10.1002/(SICI)1098-2272(1998)15:2<201::AID-GEPI8>3.0.CO;2-8http://dx.doi.org/10.1002/(SICI)1098-2272(1998)15:2<201::AID-GEPI8>3.0.CO;2-8},
  volume       = {15},
  year         = {1998},
}