Substantial equivalence

One important concept that is used in most countries to regulate products of genetic engineering is substantial equivalence. The way to determine substantial equivalence is comparative assessment. What do substantial equivalence and comparative assessment mean? Depending on the source we use, we might find different definitions and different opinions of how useful they are in determining the safety of products of genetic engineering. The USDA provides information on Food Safety Assessment and Considerations as part of their Focus on Food Biotechnologypage at the Food Safety Research Information Office.

What substantial equivalence can do is give us a starting point.

We know that there is variation in amounts and types of proteins and metabolites, gene expression, and other parameters from variety to variety, from environment to environment, and from plant to plant. For example, if I use a microarray to find similarly and differently expressed genes in two genetically identical plants grown in slightly different environments, such as different temperatures, I will find some genes that have significantly different expression. Similarly, plants of different varieties grown in the same environment will have different gene expression profiles and even two identical plants in the same environment will have some differences.

The first step in a comparative assessment is to test and compare the genetically engineered variety to a genetically similar variety that doesn’t have the trans- or cis-gene. Tests can include gene expression, metabolic profiles, feeding studies, and more. If differences aren’t found in a reasonably wide panel of tests, then the genetically engineered variety can be called substantially equivalent to the genetically similar variety.

If differences are found, two questions need to be asked. First, does the change fall within the natural variation found among different varieties of the same species? For example, some varieties of corn with the Bt gene have been found to contain more lignin than genetically similar varieties without the Bt gene, but the amount of lignin falls within the normal range of lignin content for corn plants. Second, is there a scientific explanation for each change? For example, a transgene that causes higher calcium uptake from the soil is expected to result in higher amounts of calcium.

If there is a change that doesn’t fall within the natural variation for that species, especially if there isn’t an obvious scientific explanation for the change, then more testing needs to be done to determine safety with regard to environment and human health.

What substantial equivalence does not do is give license to make assumptions. The process of genetic engineering does have the potential to cause unintended changes in the resulting organism. That’s why a comparative assessment needs to be conducted before a plant, animal or microbe that has been genetically engineered can be deemed substantially equivalent to a non-genetically engineered but genetically similar organism.

One major problem with determining substantial equivalence is that it is hard to know which tests are appropriate. This problem has improved greatly as “omics” type tests have become more widely used. Tests for macronutrient content could be expected to miss small but significant changes but wide screens for changes in the transcriptome, proteome, or metabolome could be expected to find those small changes.

The metabolome seems to hold the most promise because it effectively tests the end product of gene expression and enzyme activity. Owen Hoekenga presented metabolomics in an excellent 2008 paper as a method that could be used to help determine substantial equivalence.

ResearchBlogging.orgHoekenga OA (2008). Using metabolomics to estimate unintended effects in transgenic crop plants: problems, promises, and opportunities. Journal of biomolecular techniques : JBT, 19 (3), 159-66 PMID: 19137102.

Abstract:  Transgenic crops are widespread in some countries and sectors of the agro-economy, but are also highly contentious. Proponents of transgenic crop improvement often cite the “substantial equivalence” of transgenic crops to the their nontransgenic parents and sibling varieties. Opponents of transgenic crop improvement dismiss the substantial equivalence standard as being without statistical basis and emphasize the possible unintended effects to food quality and composition due to genetic transformation. Systems biology approaches should help consumers, regulators, and other stakeholders make better decisions regarding transgenic crop improvement by characterizing the composition of conventional and transgenically improved crop species and products. In particular, metabolomic profiling via mass spectrometry and nuclear magnetic resonance can make broad and deep assessments of food quality and content. The metabolome observed in a transgenic variety can then be assessed relative to the consumer and regulator accepted phenotypic range observed among conventional varieties. I briefly discuss both targeted (closed architecture) and nontargeted (open architecture) metabolomics with respect to the transgenic crop debate and highlight several challenges to the field. While most experimental examples come from tomato (Solanum lycoperiscum), analytical methods from all of systems biology are discussed.

“Omics” studies that have been conducted on the substantial equivalence of genetically engineered plants to their non-genetically engineered counterparts have found that there are differences but those differences fall within the range of differences found within different varieties of the same species. Below are some such studies.

Kogel KH, Voll LM, Schäfer P, Jansen C, Wu Y, Langen G, Imani J, Hofmann J, Schmiedl A, Sonnewald S, von Wettstein D, Cook RJ, & Sonnewald U (2010). Transcriptome and metabolome profiling of field-grown transgenic barley lack induced differences but show cultivar-specific variances. PNAS, 107 (14), 6198-203 PMID: 20308540

Baker JM, Hawkins ND, Ward JL, Lovegrove A, Napier JA, Shewry PR, & Beale MH (2006). A metabolomic study of substantial equivalence of field-grown genetically modified wheat. Plant biotechnology journal, 4 (4), 381-92 PMID: 17177804

Coll A, Nadal A, Collado R, Capellades G, Messeguer J, Melé E, Palaudelmàs M, & Pla M (2009). Gene expression profiles of MON810 and comparable non-GM maize varieties cultured in the field are more similar than are those of conventional lines. Transgenic research, 18 (5), 801-8 PMID: 19396622

Lehesranta SJ, Davies HV, Shepherd LV, Nunan N, McNicol JW, Auriola S, Koistinen KM, Suomalainen S, Kokko HI, & Kärenlampi SO (2005). Comparison of tuber proteomes of potato varieties, landraces, and genetically modified lines. Plant physiology, 138 (3), 1690-9 PMID: 15951487

Gregersen PL, Brinch-Pedersen H, & Holm PB (2005). A microarray-based comparative analysis of gene expression profiles during grain development in transgenic and wild type wheat. Transgenic research, 14 (6), 887-905 PMID: 16315094

Another problem with comparative assessments is that each genetically engineered trait may require different types of testing, depending on what the trait is. For example, a drought tolerant crop may need to be tested under wet and dry conditions while a nutritional trait may not need to be tested under different environmental conditions.

An alternative view to substantial equivalence and comparative assessment is the precautionary principle. Instead of starting  by looking for differences between a genetically engineered organism and a non-genetically engineered but genetically similar organism as we find in a comparative assessment, the precautionary principle requires us to start with the assumption that there are differences and enough studies must be conducted to determine that something is completely safe before release. The precautionary principle is an important enough idea that it deserves its own post, but I will say here that it has some problems, the biggest of which is that the amount of testing that is deemed to be “enough” is rarely defined, so the amount of tests that “need” to be conducted can always be made larger, which may actually be the point.

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