Treat the Cause, Not the Symptoms

So far I’ve spent the summer going through seemingly endless iterations of coding, looking at graphs, adjusting some numbers, looking at slightly different graphs… and so on. Finally this week I got my baseline and disease state models working correctly, and began to research treatment strategies! It was a relief to be able to look at something besides MATLAB code for a little while. So far I have added some known Parkinson’s treatments as well as an experimental Huntington’s disease treatment, an immunosuppressant, some anti-inflammatory drugs, an antidepressant, and an insulin sensitizer, all of which target destructive mechanisms in my model.

Unsurprisingly, a combination of treatments is the most effective at preventing neuron death. Not only does this approach inhibit multiple disease pathways, but also is able to counteract some negative side-effects of individual treatments. For example, mitochondrial membrane depolarization is caused by H+ leaking through the membrane, resulting in decreased mitochondrial function and a release of cytochrome c from the mitochondria triggering apoptosis. This process is actually increased by a treatment targeting reactive oxygen species, but is decreased by other treatments so that the overall effect is an increase in polarization and mitochondrial function and a decrease in cytochrome c release and reactive oxygen species.

Most approved Parkinson’s medications available today only work to alleviate symptoms, not stop the progression of the disease. They usually work by increasing dopamine levels, which are substantially lowered because Parkinson’s kills dopamine-producing neurons. The most well-known, L-DOPA, is a dopamine precursor. These treatments do increase the quality of life for people suffering from Parkinson’s disease, however, a treatment that actually prevented the death of the neurons in the first place would not only lessen the symptoms of the disease, but also increase the lifespan of the patient.

Comments

  1. dfmcpherson says:

    I can only imagine your relief at completing that model! I have spent the entire summer so far trying to get a population model working, and I am eager to begin adding additional variables once it’s up and running.

  2. swnordstrom says:

    I’d be really interested to hear how you’re modeling these pathways. What kind of model you’re using, what your variables are, stuff like that. I’ve seen math models for “simple” things like diffusion of molecules throughout the neuron or different models of receptor-binding (modeling these “simple” things can be really complex the more biologically realistic the model becomes) so I can only wonder how modeling an entire disease pathway has to be.

  3. embraatz says:

    I’ve been working on this particular model all of last summer and through the school year. They definitely take a lot of time. Best of luck with your population model!

    I’m modeling my system using Biochemical Systems Theory, or BST. My model includes 510 species and 343 rate equations per state for a total of 1530 species and 1026 equations being modeled between the three states–baseline, disease, and treatment. Running the entire system generates over 2 million values. Considering the scope of the model, assessing processes like receptor binding and ion channel activity to a high level of detail would be impractical and have little overall effect, so they are absorbed into the rate constants. Many of the pathways I model are not fully understood (that’s why we need the model!) so my variable assignments are relative–an initial value for a gene is much lower than that of its corresponding protein, for example. The final results are also comparative. I subtract the values I get from running the baseline state from those of the disease and treatment states. The goals are to evaluate which species are the most sensitive to treatment, and which treatments return the cell closer to baseline, not to find actual species concentrations. E.O. Voit recently published a fairly comprehensive review article of BST (http://dx.doi.org/10.1155/2013/897658) if you’re interested in learning more. Hope this was helpful, and let me know if you have any questions!

  4. swnordstrom says:

    Jeez that’s a lot of data. Good thing you have a computer that can easily sort/find extremes to help you evaluate the effectiveness of treatments. I like the comparative approach — I’m also doing a project that involves comparing an altered system with a control system, although I doubt it will get higher than 40 species, let alone the 1500 you’re looking at! My model so far runs a little slow with only 12 different rate equations so I can’t imagine how long it takes you to run yours. Good luck with the rest of your work!