Cargando…

Variance of age-specific log incidence decomposition (VALID): a unifying model of measured and unmeasured genetic and non-genetic risks

BACKGROUND: The extent to which known and unknown factors explain how much people of the same age differ in disease risk is fundamental to epidemiology. Risk factors can be correlated in relatives, so familial aspects of risk (genetic and non-genetic) must be considered. DEVELOPMENT: We present a un...

Descripción completa

Detalles Bibliográficos
Autores principales: Hopper, John L, Dowty, James G, Nguyen, Tuong L, Li, Shuai, Dite, Gillian S, MacInnis, Robert J, Makalic, Enes, Schmidt, Daniel F, Bui, Minh, Stone, Jennifer, Sung, Joohon, Jenkins, Mark A, Giles, Graham G, Southey, Melissa C, Mathews, John D
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10655167/
https://www.ncbi.nlm.nih.gov/pubmed/37349888
http://dx.doi.org/10.1093/ije/dyad086
_version_ 1785136766142906368
author Hopper, John L
Dowty, James G
Nguyen, Tuong L
Li, Shuai
Dite, Gillian S
MacInnis, Robert J
Makalic, Enes
Schmidt, Daniel F
Bui, Minh
Stone, Jennifer
Sung, Joohon
Jenkins, Mark A
Giles, Graham G
Southey, Melissa C
Mathews, John D
author_facet Hopper, John L
Dowty, James G
Nguyen, Tuong L
Li, Shuai
Dite, Gillian S
MacInnis, Robert J
Makalic, Enes
Schmidt, Daniel F
Bui, Minh
Stone, Jennifer
Sung, Joohon
Jenkins, Mark A
Giles, Graham G
Southey, Melissa C
Mathews, John D
author_sort Hopper, John L
collection PubMed
description BACKGROUND: The extent to which known and unknown factors explain how much people of the same age differ in disease risk is fundamental to epidemiology. Risk factors can be correlated in relatives, so familial aspects of risk (genetic and non-genetic) must be considered. DEVELOPMENT: We present a unifying model (VALID) for variance in risk, with risk defined as log(incidence) or logit(cumulative incidence). Consider a normally distributed risk score with incidence increasing exponentially as the risk increases. VALID’s building block is variance in risk, Δ(2), where Δ = log(OPERA) is the difference in mean between cases and controls and OPERA is the odds ratio per standard deviation. A risk score correlated r between a pair of relatives generates a familial odds ratio of exp(rΔ(2)). Familial risk ratios, therefore, can be converted into variance components of risk, extending Fisher’s classic decomposition of familial variation to binary traits. Under VALID, there is a natural upper limit to variance in risk caused by genetic factors, determined by the familial odds ratio for genetically identical twin pairs, but not to variation caused by non-genetic factors. APPLICATION: For female breast cancer, VALID quantified how much variance in risk is explained—at different ages—by known and unknown major genes and polygenes, non-genomic risk factors correlated in relatives, and known individual-specific factors. CONCLUSION: VALID has shown that, while substantial genetic risk factors have been discovered, much is unknown about genetic and familial aspects of breast cancer risk especially for young women, and little is known about individual-specific variance in risk.
format Online
Article
Text
id pubmed-10655167
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-106551672023-06-22 Variance of age-specific log incidence decomposition (VALID): a unifying model of measured and unmeasured genetic and non-genetic risks Hopper, John L Dowty, James G Nguyen, Tuong L Li, Shuai Dite, Gillian S MacInnis, Robert J Makalic, Enes Schmidt, Daniel F Bui, Minh Stone, Jennifer Sung, Joohon Jenkins, Mark A Giles, Graham G Southey, Melissa C Mathews, John D Int J Epidemiol Methods BACKGROUND: The extent to which known and unknown factors explain how much people of the same age differ in disease risk is fundamental to epidemiology. Risk factors can be correlated in relatives, so familial aspects of risk (genetic and non-genetic) must be considered. DEVELOPMENT: We present a unifying model (VALID) for variance in risk, with risk defined as log(incidence) or logit(cumulative incidence). Consider a normally distributed risk score with incidence increasing exponentially as the risk increases. VALID’s building block is variance in risk, Δ(2), where Δ = log(OPERA) is the difference in mean between cases and controls and OPERA is the odds ratio per standard deviation. A risk score correlated r between a pair of relatives generates a familial odds ratio of exp(rΔ(2)). Familial risk ratios, therefore, can be converted into variance components of risk, extending Fisher’s classic decomposition of familial variation to binary traits. Under VALID, there is a natural upper limit to variance in risk caused by genetic factors, determined by the familial odds ratio for genetically identical twin pairs, but not to variation caused by non-genetic factors. APPLICATION: For female breast cancer, VALID quantified how much variance in risk is explained—at different ages—by known and unknown major genes and polygenes, non-genomic risk factors correlated in relatives, and known individual-specific factors. CONCLUSION: VALID has shown that, while substantial genetic risk factors have been discovered, much is unknown about genetic and familial aspects of breast cancer risk especially for young women, and little is known about individual-specific variance in risk. Oxford University Press 2023-06-22 /pmc/articles/PMC10655167/ /pubmed/37349888 http://dx.doi.org/10.1093/ije/dyad086 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of the International Epidemiological Association. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methods
Hopper, John L
Dowty, James G
Nguyen, Tuong L
Li, Shuai
Dite, Gillian S
MacInnis, Robert J
Makalic, Enes
Schmidt, Daniel F
Bui, Minh
Stone, Jennifer
Sung, Joohon
Jenkins, Mark A
Giles, Graham G
Southey, Melissa C
Mathews, John D
Variance of age-specific log incidence decomposition (VALID): a unifying model of measured and unmeasured genetic and non-genetic risks
title Variance of age-specific log incidence decomposition (VALID): a unifying model of measured and unmeasured genetic and non-genetic risks
title_full Variance of age-specific log incidence decomposition (VALID): a unifying model of measured and unmeasured genetic and non-genetic risks
title_fullStr Variance of age-specific log incidence decomposition (VALID): a unifying model of measured and unmeasured genetic and non-genetic risks
title_full_unstemmed Variance of age-specific log incidence decomposition (VALID): a unifying model of measured and unmeasured genetic and non-genetic risks
title_short Variance of age-specific log incidence decomposition (VALID): a unifying model of measured and unmeasured genetic and non-genetic risks
title_sort variance of age-specific log incidence decomposition (valid): a unifying model of measured and unmeasured genetic and non-genetic risks
topic Methods
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10655167/
https://www.ncbi.nlm.nih.gov/pubmed/37349888
http://dx.doi.org/10.1093/ije/dyad086
work_keys_str_mv AT hopperjohnl varianceofagespecificlogincidencedecompositionvalidaunifyingmodelofmeasuredandunmeasuredgeneticandnongeneticrisks
AT dowtyjamesg varianceofagespecificlogincidencedecompositionvalidaunifyingmodelofmeasuredandunmeasuredgeneticandnongeneticrisks
AT nguyentuongl varianceofagespecificlogincidencedecompositionvalidaunifyingmodelofmeasuredandunmeasuredgeneticandnongeneticrisks
AT lishuai varianceofagespecificlogincidencedecompositionvalidaunifyingmodelofmeasuredandunmeasuredgeneticandnongeneticrisks
AT ditegillians varianceofagespecificlogincidencedecompositionvalidaunifyingmodelofmeasuredandunmeasuredgeneticandnongeneticrisks
AT macinnisrobertj varianceofagespecificlogincidencedecompositionvalidaunifyingmodelofmeasuredandunmeasuredgeneticandnongeneticrisks
AT makalicenes varianceofagespecificlogincidencedecompositionvalidaunifyingmodelofmeasuredandunmeasuredgeneticandnongeneticrisks
AT schmidtdanielf varianceofagespecificlogincidencedecompositionvalidaunifyingmodelofmeasuredandunmeasuredgeneticandnongeneticrisks
AT buiminh varianceofagespecificlogincidencedecompositionvalidaunifyingmodelofmeasuredandunmeasuredgeneticandnongeneticrisks
AT stonejennifer varianceofagespecificlogincidencedecompositionvalidaunifyingmodelofmeasuredandunmeasuredgeneticandnongeneticrisks
AT sungjoohon varianceofagespecificlogincidencedecompositionvalidaunifyingmodelofmeasuredandunmeasuredgeneticandnongeneticrisks
AT jenkinsmarka varianceofagespecificlogincidencedecompositionvalidaunifyingmodelofmeasuredandunmeasuredgeneticandnongeneticrisks
AT gilesgrahamg varianceofagespecificlogincidencedecompositionvalidaunifyingmodelofmeasuredandunmeasuredgeneticandnongeneticrisks
AT southeymelissac varianceofagespecificlogincidencedecompositionvalidaunifyingmodelofmeasuredandunmeasuredgeneticandnongeneticrisks
AT mathewsjohnd varianceofagespecificlogincidencedecompositionvalidaunifyingmodelofmeasuredandunmeasuredgeneticandnongeneticrisks