Commonly used estimates of the genetic contribution to disease are subject to the same fallacies as bad luck estimates.


Journal

European journal of epidemiology
ISSN: 1573-7284
Titre abrégé: Eur J Epidemiol
Pays: Netherlands
ID NLM: 8508062

Informations de publication

Date de publication:
Nov 2019
Historique:
received: 21 05 2019
accepted: 15 10 2019
pubmed: 24 10 2019
medline: 10 4 2020
entrez: 24 10 2019
Statut: ppublish

Résumé

The scientific debate following the initial formulation of the "bad luck" hypothesis in cancer development highlighted how measures based on analysis of variance are inappropriately used for risk communication. The notion of "explained" variance is not only used to quantify randomness, but also to quantify genetic and environmental contribution to disease in heritability coefficients. In this paper, we demonstrate why such quantifications are generally as problematic as bad luck estimates. We stress the differences in calculation and interpretation between the heritability coefficient and the population attributable fraction, the estimated fraction of all disease events that would not occur if an intervention could successfully prevent the excess genetic risk. We recommend using the population attributable fraction when communicating results regarding the genetic contribution to disease, as this measure is both more relevant from a public health perspective and easier to understand.

Identifiants

pubmed: 31641918
doi: 10.1007/s10654-019-00573-8
pii: 10.1007/s10654-019-00573-8
pmc: PMC6861200
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

987-992

Subventions

Organisme : Forskningsrådet om Hälsa, Arbetsliv och Välfärd
ID : 2018-01596
Organisme : Forskningsrådet om Hälsa, Arbetsliv och Välfärd
ID : 2017-00414

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Auteurs

Jonas Björk (J)

Division of Occupational and Environmental Medicine, Lund University, Box 117, 221 00, Lund, Sweden. jonas.bjork@med.lu.se.
Clinical Studies Sweden, Forum South, Skåne University Hospital, Lund, Sweden. jonas.bjork@med.lu.se.

Tomas Andersson (T)

Unit of Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
Center for Occupational and Environmental Medicine, Stockholm County Council, Stockholm, Sweden.

Anders Ahlbom (A)

Unit of Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
Center for Occupational and Environmental Medicine, Stockholm County Council, Stockholm, Sweden.

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Classifications MeSH