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Chunk #2 — Introduction – what is biological versus statistical interaction?

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Less is more, except when less is less: Studying joint effects.
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Colloquially, people refer to two factors as behaving in a synergistic way if their combined effect is greater than what would be expected based on their individual separate effects. A classic example is retardation due to phenylketonuria (PKU): dietary phenylalanine is innocuous in the absence of the metabolic PKU genetic defect, and the defect does not cause retardation in the absence of dietary phenylalanine. (Hence the importance of neonatal screening for this genetic variant.) Most synergistic interactions are less “pure” than the PKU paradigm, and typically both factors individually cause some increase in risk. Consequently, in order to say that a joint effect exceeds what would be expected based on individual effects, we first need a way to form a reasonable expectation for their joint effect, against which to define interaction, or synergism. Any definition of interaction logically relies on some specification of non-interactive effects.