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Evolution of Risk Assessment Strategies for Food and Feed Uses of Stacked GM Events

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Specialties Biology
Biotechnology
Date 2016 Feb 26
PMID 26914314
Citations 6
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Abstract

Data requirements are not harmonized globally for the regulation of food and feed derived from stacked genetically modified (GM) events, produced by combining individual GM events through conventional breeding. The data required by some regulatory agencies have increased despite the absence of substantiated adverse effects to animals or humans from the consumption of GM crops. Data from studies conducted over a 15-year period for several stacked GM event maize (Zea mays L.) products (Bt11 ×  GA21, Bt11 ×  MIR604, MIR604 ×  GA21, Bt11 ×  MIR604 ×  GA21, Bt11 ×  MIR162 ×  GA21 and Bt11 ×  MIR604 ×  MIR162 ×  GA21), together with their component single events, are presented. These data provide evidence that no substantial changes in composition, protein expression or insert stability have occurred after combining the single events through conventional breeding. An alternative food and feed risk assessment strategy for stacked GM events is suggested based on a problem formulation approach that utilizes (i) the outcome of the single event risk assessments, and (ii) the potential for interactions in the stack, based on an understanding of the mode of action of the transgenes and their products.

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References
1.
Klumper W, Qaim M . A meta-analysis of the impacts of genetically modified crops. PLoS One. 2014; 9(11):e111629. PMC: 4218791. DOI: 10.1371/journal.pone.0111629. View

2.
Kok E, Kuiper H . Comparative safety assessment for biotech crops. Trends Biotechnol. 2003; 21(10):439-44. DOI: 10.1016/j.tibtech.2003.08.003. View

3.
Steiner H, Halpin C, Jez J, Kough J, Parrott W, Underhill L . Editor's choice: Evaluating the potential for adverse interactions within genetically engineered breeding stacks. Plant Physiol. 2013; 161(4):1587-94. PMC: 3613440. DOI: 10.1104/pp.112.209817. View

4.
Raybould A . Problem formulation and hypothesis testing for environmental risk assessments of genetically modified crops. Environ Biosafety Res. 2007; 5(3):119-25. DOI: 10.1051/ebr:2007004. View

5.
Harrigan G, Stork L, Riordan S, Reynolds T, Ridley W, Masucci J . Impact of genetics and environment on nutritional and metabolite components of maize grain. J Agric Food Chem. 2007; 55(15):6177-85. DOI: 10.1021/jf070494k. View