Statistical considerations for digital approaches to non-invasive fetal genotyping

Abstract

A growing body of literature has demonstrated the potential for non-invasive diagnosis of a variety of human genetic diseases using cell-free DNA extracted from maternal plasma samples in early gestation. Such methods are of great significance to the obstetrics community because of their potential use as clinical standard of care. Proof of concept for such approaches has been established for aneuploidy and paternally inherited dominant traits. Although significant progress has recently been made, the non-invasive diagnosis of monogenic diseases that segregate in a recessive mendelian fashion is more problematic. Recent developments in microfluidic digital PCR and DNA sequencing have resulted in a number of recent advances in this field. These have largely, although not exclusively, been used for the development of diagnostic methods for aneuploidy. However, given their prevalence, it is likely that such methods will be utilized towards the development of non-invasive methods for diagnosing monogenetic disorders. With this in mind, we have undertaken a statistical modeling of three contemporary (digital) analytical methods in the context of prenatal diagnosis using cell free DNA for monogenic diseases that segregate in a recessive mendelian fashion. We provide an experimental framework for the future development of diagnostic methods in this context that should be considered when designing molecular assays that seek to establish proof of concept in this field.