“In the most revealing test of this hypothesis, the researchers were able to correct many of the autism-like behaviors in the offspring of immune-activated mothers by giving the offspring a bone-marrow transplant from typical mice. The normal stem cells in the transplanted bone marrow not only replenished the immune system of the host animals but altered their autism-like behavioral impairments.”

…the researchers injected pregnant mothers with a viral mimic that triggered the same type of immune response a viral infection would.

“In mice, this single insult to the mother translates into autism-related behavioral abnormalities and neuropathologies in the offspring,” says Elaine Hsiao, a graduate student in Patterson’s lab and lead author of the PNAS paper.

“Psychoactive medications in water affect the gene expression profiles of fathead minnows in a way that mimics the gene expression patterns associated with autism spectrum disorder in genetically susceptible humans, according to research published June 6 in the open access journal PLoS ONE”

“Another recent study based on CHARGE data found that mothers who were obese or diabetic had a higher likelihood of having children with autism.”

“Since an inflammatory state in the body accompanies obesity and diabetes as well as fever,” said Hertz-Picciotto, “the natural question is: Could inflammatory factors play a role in autism?”

“Our study provides strong evidence that controlling fevers while pregnant may be effective in modifying the risk of having a child with autism or developmental delay,”

I believe it’s less “components” than “parameters” one should be looking at. The parameters against whose variation the system will be least robust, are those that represent trade-offs between competing modes or subsystems that are, individually, highly complex and self-reinforcing under particular conditions.

To use an analogy from political systems, the majority of bad policy arises from excessive influence by one or more special interest groups. In and of themselves, each of these interest groups serves a function helpful to the overall well-being of the population, but what is good for each of these groups is not always best for the whole.

So, back in the world of biology, the key parameters (e.g. expression levels) to suspect for disease should be those that vary bimodally with the global state of the organism, or that act as markers for the relative growth rate or activity of a particular sub-system of the organism. If an enzyme concentration or activity has high predictive value for, as an example, distinguishing an energy-replete/fed state from an energy-deficient/starved state, or distinguishing a childhood state from an adult state, or even a state of child-rearing vs. having no children, etc., then it’s a good candidate. This is because if a perturbation pushes the system toward one extreme, the robustness of THAT state will tend to AMPLIFY rather than dampen the change.

Ironically, it’s thus the parameters that participate in the most fundamental adaptive changes, that would be most vulnerable to causing MALadaptation. Thus it may be seen as a biological form of the fluctuation-dissipation theorem: http://en.wikipedia.org/wiki/Fluctuation-dissipation_theorem

“Lifestyle and genes are not the only factors that shape disease risk, and factors and exposures before, during and after birth can help pre-program much of our adult health,” said investigator Robert Yolken, M.D., a neuro-virologist at Johns Hopkins Children’s Center.

Maternal infections and other inflammatory disorders during pregnancy have long been linked to greater risk for schizophrenia in the offspring but, the Swedish and U.S. investigators say, this is the first study that points to maternal food sensitivity as a possible culprit in the development of such disorders.

Two words: environmental damage

See:

(1) Whitacre, J.M. and A. Bender, Degeneracy: a design principle for achieving robustness and evolvability. Journal of Theoretical Biology, 2010. 263(1): p. 143-53.

(2) Mason, P.H., Degeneracy at Multiple Levels of Complexity. Biological Theory, 2010. 5(3): p. 277-288.