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

• Published in: European journal of epidemiology Vol. 34; no. 11; pp. 987 - 992
• Main Authors: Björk, Jonas, Andersson, Tomas, Ahlbom, Anders
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Science + Business Media 01.11.2019; Springer Netherlands; Springer Nature B.V
• Subjects: Cancer; Cardiology; Environment; Environmental factors; Environmental health; Epidemiology; ESSAY; Estimates; Etiologic fraction; Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi; Genetic Predisposition to Disease; Genetic studies; Genetic Variation; Genomes; Genotype; Genotype & phenotype; Health risk assessment; Health Sciences; Heritability; Humans; Hypotheses; Hälsovetenskap; Infectious Diseases; Liability; Medical and Health Sciences; Medicin och hälsovetenskap; Medicine; Medicine & Public Health; Models, Genetic; Neoplasms - genetics; Oncology; Phenotype; Population; Public Health; Public Health, Global Health, Social Medicine and Epidemiology; Risk communication; Risk Factors; Variance analysis; Genetic studies; Etiologic fraction; Epidemiology; Public health
• ISSN: 0393-2990; 1573-7284; 1573-7284
• DOI: 10.1007/s10654-019-00573-8

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.