TABLE 4-3C Locus-Specific Rates for Radiation-Induced Mutations in Mice Estimated from Data Tables 4-3A and 4-3B

Searle 1967), the rate for chronic low-LET radiation conditions becomes (0.36 ± 0.10) × 10^{−5} per locus per gray.

It is worth reiterating here that this is the first time an attempt has been made to use the mutation data coming not only from the 7 specific loci but also from all loci for which there are published data (a total of 34 loci; see Table 4-3C) taking into account interlaboratory and interexperimental variations in induced rates. Unfortunately, all of the data from biochemical loci and for dominant visibles were from experiments involving acute X- or fractionated X-irradiation experiments. In trying to put together all of these data, there was no alternative but to use the correction factors suggested by the authors of the respective papers to estimate the rate for chronic radiation conditions from the available data. The committee feels that the procedures adopted in estimating an induced rate of (0.36 ± 0.10) × 10^{−5} per gray are sound and that it is justifiable to use a single estimate for the induced rate of mutations.

With the estimates of (2.95 ± 0.64) × 10^{−6} per locus for the rate of origin of spontaneous mutations in humans and (0.36 ± 0.10) × 10^{−5} per locus per gray for induced mutations in mice, the DD becomes 0.82 ± 0.29 Gy. This new estimate is not very different from 1 Gy that has been used thus far and was based entirely on mouse data. The conceptual basis and the database used for estimating the average spontaneous and induced rates of mutations, however, are now different. The committee suggests retaining the use of 1 Gy for the DD estimate.

As noted earlier, the MC is one of the quantities in the equation used to estimate risk of genetic disease using the doubling dose method (*i.e.*, risk per unit dose = *P* × [1/DD] × MC, where *P* = baseline disease prevalence, 1/DD = the relative mutation risk per unit dose, and MC = the mutation component). The rationale for including MC in the risk equation is that the relationship between mutation and disease varies between different classes of genetic diseases—simple for autosomal dominant and X-linked diseases, slightly complex for autosomal recessive diseases, and very complex for multifactorial diseases—and the use of disease class-specific MC makes it possible to predict the impact of an increase in mutation rate on the frequencies of all classes of genetic diseases (Chakraborty and others 1998b; Denniston and others 1998; ICRP 1999).

Let *P* be the disease prevalence before an increase in mutation rate and Δ*P* its change due to a Δ*m* change in spontaneous mutation rate, *m*. The mathematical identity

(4-4)

formalizes the definition of MC. In this equation, since Δ*P*/*P* is the relative change in disease prevalence and Δ*m*/*m* is the