Congenital anomalies from a physics perspective. The key role of “manufacturing” volatility

Abstract

Genetic and environmental factors are traditionaly seen as the sole causes of congenital anomalies. In this paper we introduce a third possible cause, namely random "manufacturing" discrepancies with respect to "design" values. A clear way to demonstrate the existence of this component is to "shut" the two others and to see whether or not there is remaining variability. Perfect clones raised under well controlled laboratory conditions fulfill the conditions for such a test. Carried out for four different species, the test reveals a variability remainder of the order of 10%-20% in terms of coefficient of variation. As an example, the CV of the volume of E.coli bacteria immediately after binary fission is of the order of 10%. In short, "manufacturing" discrepancies occur randomly, even when no harmful mutation or environmental factors are involved. If the pathway is particularly long or requires exceptional accuracy, output dispersion will be high and may lead to malformations. This effect will be referred to as the dispersion effect. We conjecture that it will be particularly significant when major changes occur; this includes the early phase of embryogenesis or the steps leading from stem cells to differentiated (organ-specific) cells. The dispersion effect not only causes malformations but also innocuous variability. For instance monozygotic (MZ) twins resemble each other but are not strictly identical. It is not uncommon to see only one of the twins of a MZ pair showing a congenital defect (see Appendix A). Not surprisingly, there is a strong connection between congenital defects and infant mortality. In the wake of birth there is a gradual elimination of defective units and this screening accounts for the post-natal fall of infant mortality. For reasons which are not yet fully understood, this fall continues until the age of 10 years. Neither do we understand why, as a function of age, the downward trend of human infant mortality follows a power law with an exponent around 1 (whereas for fish it is about 3, see Bois et al. 2019a). Apart from this trend, post-natal death rates also have humps and peaks associated with various inabilities and defects. In short, infant mortality rates convert the case-by-case and mostly qualitative problem of congenital malformations into a global quantitative effect which, so to say, summarizes and registers what goes wrong in the embryonic phase. Based on the natural assumption that for simple organisms (e.g. rotifers) the manufacturing processes are shorter than for more complex organisms (e.g. mammals), fewer congenital anomalies are expected. Somehow, this feature should be visible on the infant mortality rate. How this conjecture can be tested is outlined in our conclusion.3

Physical models of infant mortality: implications for defects in biological systems

“…where we have used Eqn (3). It is in this sense that infant mortality gives us an insight into the internal working of a device or organism.…”

“…As noted at the outset, the major focus of this and previous papers [2,3] is to study the connection between initial abnormalities (whether from manufacturing or congenital anomalies) and subsequent death rates. Of importance is the determination of the delay between introduction of a defect and the resulting failure which may occur after a substantial time lag.…”

“…The age-dependent mortality rates for humans and other animal species have a declining part, corresponding to infant mortality, which is followed by a rising part, corresponding to the ageing process [1][2][3]. Technical systems are said to show a similar pattern, although little published empirical evidence appears to exist to support the point.…”

“…Therefore they are usually limited to crucial devices, such as items destined for the space industry, and the results are not normally made public 2 . An exception appear to be computer hard drives, for which failure data is now available online 3 . In the case of fluorescent light bulbs, which have average lifetimes of about 20,000 hours, rapid on-off switching cycles, which result in a lifetime decrease, provide an alternative testing method [4,5].…”