Cm. Lewis et al., Controlling misdiagnosis errors in preimplantation genetic diagnosis: a comprehensive model encompassing extrinsic and intrinsic sources of error, HUM REPR, 16(1), 2001, pp. 43-50
We have developed a mathematical model to explore accuracy of preimplantati
on genetic diagnosis (PGD) using Single cell polymerase chain reaction (PCR
). The model encompasses both extrinsic technical errors and intrinsic erro
rs related to nuclear and chromosomal abnormalities. Using estimates for th
ese errors, we have calculated the probability of a serious error (affected
embryo diagnosed as unaffected) using a variety of strategies designed to
increase the accuracy of PGD, Additional information from genotyping a link
ed marker or a second biopsied cell reduces the probability of replacing an
affected embryo, while ensuring that sufficient unaffected embryos can be
replaced. For a recessive disease, two genotypes are required to ensure a l
ow probability of replacing an affected embryo (<1%) with a high proportion
of unaffected embryos eligible for replacement (68%), These genotypes may
be from a single cell with linked marker, or disease genotypes from two cel
ls. PGD of a dominant disease is more difficult, as it relies on the amplif
ication of a single copy of the mutation. Genotypes from two biopsied cells
are required to ensure that a high proportion of unaffected embryos are el
igible for replacement, This model can be used as a clinical tool to priori
tize embryos for transfer in a PGD cycle.