Equivalence tests for safety assessment of genetically modified crops using plant composition data. (October 2021)

• Record Type: Journal Article
• Authors: Engel, Jasper; van der Voet, Hilko
• Is Part Of: Food and chemical toxicology. Volume 156(2021)
• Publication Date: 2021-10
• Subjects: Food safety -- Equivalence test -- Distribution-wise equivalence -- Linear mixed model -- Generalized pivotal quantity; Toxicology -- Periodicals; Food poisoning -- Periodicals; Food Poisoning -- Periodicals; Toxicology -- Periodicals; Toxicologie -- Périodiques; Intoxications alimentaires -- Périodiques; Food poisoning; Toxicology; Periodicals; Electronic journals; 615.9
• DOI: 10.1016/j.fct.2021.112517
• Languages: English
• ISSNs: 0278-6915

Abstract

Abstract: The evaluation of compositional characteristics of plants harvested from field trials is an important step in the safety assessment of a genetically modified crop and its derived products for food and feed. The European Food Safety Authority (EFSA) evaluates safety by testing for equivalence between the GM genotype and other genotypes, typically with a history of safe use. Here, a new equivalence test is proposed, which addresses issues with the EFSA test. The method is motivated by a recently proposed equivalence test for analysis of data from animal feeding trials. In order to be suitable for practical safety assessment, the new method has a statistical power set to a desired value, e.g. 95%, by construction. In addition, we assess distributions rather than average values. This way, equivalence limits can also be established when there is limited genotypic variation. The original EFSA equivalence test breaks down in this case. The method is illustrated by its application to data from a field study on maize grain. Simulation studies indicate that the proposed test has appropriate performance characteristics and is competitive with respect to recently proposed alternatives, including the EFSA/EU equivalence test. Highlights: An update to the EFSA/EU equivalence test for GMO safety assessment is proposed. The statistical power for specific test genotypes is controlled at a desired value. The proposed method is compared to other methods in simulations. The methods are applied to a maize compositional data set. Results are visualized as equivalence limit scaled differences.