Mental data mining

In researching the previous post I came across some other interesting relationships.

The first is that a common food additive might induce gluconeogenesis (GNG) when it's not needed. Propoinic acid (PA) is added to foods like bread and dairy since it cannot be metabolized by fungus, which makes it toxic. However, mammals can metabolize PA via the odd C chain fatty acid degradation pathway with the PA undergoing GNG. The issue might be that when PA is used as a preservative is that it is presented to the body out of proper dietary context and in levels far higher than would naturally seen. GNG is reserved for times when the diet is not providing sufficient glucose, and fats or proteins need to be used as fuel. Metabolizing dietary PA requires GNG activation even when there is more than enough sugar available (PA is used to preserve alot of starchy and sugary foods). GNG suppresses glycogen storage as well as the removal of lipids from the blood since you are consuming you stored energy. It would be interesting to know what happens long term if you are trying to both store excess fuel while running GNG cycle. It could be very confusing since your body would produce insulin and at the same time telling the cells not store energy. This hypothesis might not seem overly compatible with the previous one since the results are the same the mechanism is opposite. My evidence that the increase in consumption of odd C chain fatty acids (which includes PA) can encourage NIDDM is based largely on interpreting the available data. This is the interesting thing about data mining since I can find evidence to support both hypotheses. I am only pointing out an interesting possibility, and this evidence broadens the pool of genes that will need to be studied to determine the cause of NIDDM. If it turns out that PA is not as safe as we think the impact on the world as a whole would be huge!

Now these next two relationships I have the evidence for but this is a place where one publishes the results of large scale expression studies, but if you get the data from the SMADB you too can find these relationships. The second relationship I found is that experimental therapies for certain cancers and congestive heart failure which use histone deacetylase inhibitors (HDAC inhibitors, HDI). HDI’s can alter the chromatin structure of the DNA, which in certain circumstances can reactive genes that have by inappropriately silenced. In cancer this can lead to apoptosis of the defective cells and in congestive heart failure it can reduce the hypertrophy. In NIDDM HDIs could break the feedback loop required to maintain the abnormal state and restore proper metabolic function. The issue with HDIs and a more powerful class of drugs that includes 5 Aza dC, is that their side effects include cancer, and gross metabolic dysfunction, which is why they are normally only used to treat life threatening diseases. If a safer HDI is discovered or ncRNA can be used it is possible that NIDDM could be cured, instead of treated and controlled.

The last relationship I found is that a drug used to treat NIDDM called rosiglitazone could be used to treat certain types of cancer and chemotherapeutic related wasting disorders. Rosiglitazone inhibits the PPARγ inflammatory pathway. This pathway might be involved with innate resistance of certain solid tumors to drugs, and to the immune cascade that can occur with certain classes of chemo drugs. Rosiglitazone would be used in conjunction with chemo, since it has no direct anti-cancer effects. However, rosiglitazone is associated with an increased risk of “cardiac events”, like most non-OTC anti-inflammatory drugs.