The Path To Curing Degenerative Brain Diseases


“We always hope for the easy fix: the one simple change that will erase a problem in a stroke. But few things in life work this way. Instead, success requires making a hundred small steps go right – one after the other, no slipups, no goofs, everyone pitching in.”
― Atul Gawande


For years now I have been trying to answer one question: where would I place my bets on where cures for Parkinson’s diseases will come from?

To date I have toured over 50 academic labs, biotech companies and pharmaceutical giants, formally interviewed 80 experts in the field, and spoken at length with hundreds more, all in a roundabout attempt to answer that one burning question.

Well, I am happy to say that I think I finally found the answer. But before I get to it I ask, what is the most important question facing the future of research into Parkinson’s diseases?

In my opinion it is this, do these diseases look like this…


cluser 2


Or this….


cluster 1


Are they similar enough that we can target most of them as a group? Or are they different diseases that will each require different solutions?

This is certainly not a new question, looking back it seems medical science has been asking this for decades across different diseases. (One of my favorite pieces on this is from Jon Palfreman writing for the Journal of Parkinson’s blog on Hedgehogs vs. Foxes. Though as you will see, we reach very different conclusions.)

For what it is worth, I hope the answer is the first one. It would be a much easier problem to solve. We would just need to keep digging through the biology until we find the common thread that unites them. Many believe we have already found it in certain protein aggregates, we just have not figured out yet how to properly treat them. (And a promising new target supposedly shared by 94% of people with PD just popped up as well.)

However, for reasons stated below, I fear that the second picture is closer to the truth. If it is then we need to rethink what we are doing as almost everyone is looking for converging lines of evidence that point to a small number of biological phenomena. This is largely a function of the way medical science works, boiling down a problem to a single independent variable that we can tweak until we find the right fit.

But how do we know we are dealing with one problem? How can we try to settle this debate?

Well, to start, as best as I can tell here are the arguments for each side… (looking only at evidence we have from humans)


* The Story of Joy Milne


What is clear to me is that there is no decisive winner, we cannot say with certainty if we are dealing with one disease or many. Yet, the vast majority of therapies in development try to tackle Parkinson’s as if it were one problem. It is passed time that at the very least we hedge our bets and ask, if we are dealing with many diseases, what do we need to do to tell them apart and tackle each one?

So far, since we don’t know how to look inside a person’s brain while they are still alive without doing a lot more damage than we would like, we have had to turn to models to try and simulate what is happening. While we have learned a lot from our models and they have been crucial in developing the therapies we have, none have proven useful in helping stop or reverse disease progression.

I believe this is because none of them recapitulate enough of the disease to truly be disease-relevant. I’ve never seen a mouse, fly or even monkey that had even a single symptom that was a good enough proxy for what people diagnosed with Parkinson’s experience. A mouse dragging a hind limb is not analogous to a human shuffling their feet. A contorted spinal column in a fish is not similar to the cramping felt by those with dystonia. Flies fluttering in asymmetric circles is not a good substitute for the motor impairments felt by humans.

At this point some may say, these models are the best we have. We have no choice but to keep plugging away with them and hope we stumble across something.

But there is another option, people.



How do we study people?

Well, by tracking large groups of patients over long periods of time while collecting as much potentially relevant information about them as possible. In just the last decade we have developed an array of powerful new biologic and analytic tools that provide novel insights into what we can glean from humans living with these diseases. I believe these discoveries have allowed us to pass a tipping point where the disadvantages of studying humans (much harder and more expensive to run controlled experiments on and to access tissue) is now outweighed by the advantages (they actually get the diseases). Models still have an important role to play in determining safety and dosage and in advancing basic biology, but they are no longer the best resource for understanding the diseases themselves.

Now, to be fair, none of that is certain because we haven’t done this properly yet. We have taken small, clinically defined groups and used them to answer specific questions, with ideas about what we were looking for and where we might find it. But to do this right we need to blind ourselves not only to what to look for, but to the diseases as well. Biology does not have boundaries between what we call Parkinson’s or Alzheimer’s or any other degenerative brain condition. Each name we have given to these conditions represents a spectrum that bleeds into one another to the point where the same experts that helped give us those definitions frequently misdiagnose them. Yet we continue to lump people together into categories that were made decades before we had the tools and insights needed to accurately define them. For all we know, people with different clinical diagnoses might share underlying biological abnormalities. For example, two people could have the same viral infection that leads to chronic neuroinflammation but due to all the differences in their physiology one could go on to get a form of dementia, the other a form of Parkinson’s. (Or as was just pointed out to me by Prof. Alice Chen-Plotkin, expansion of the gene C9orf72 can manifest as ALS or frontotemporal dementia, in the same family.)

So, what is needed is a giant concerted effort to study large groups of people that have been diagnosed with one of these diseases, separate them from their diagnostic label, mix them all up, study their biology in as much detail as possible for as long as possible, analyze the data, and see who clusters together. In the end we will probably get something that looks like this…





Then we match each cluster to the best therapeutic target we have for that group (or develop their own unique therapy). That will enable us to turn this amorphous blog of a puzzle we now call Parkinson’s disease into discrete disease groups, each with their own tailored solution.





This is certainly not a quick fix, so it will need to be complemented with therapies that help people live better now while we wait for these solutions to emerge, but I believe it is the kind of long term thinking that is needed to enable us to one day develop cures for degenerative brain diseases.

Thankfully, such a program has just begun. It is called the CCBP, the Cincinnati Cohort Biomarker Program. It will launch with enough funding to recruit 5000 people in 5 years and follow them for at least 5 more, with plans in place to greatly increase both figures. There are no guarantees it will find what we are hoping for, but the wider we cast our net, the more we will tilt the odds of finding something in our favor.

It is where I’ll be placing my bets on where cures will come from.


(Note: This was merely a conceptual introduction to the CCBP, more specific details to come…)





Featured Image: The Gambler | Christian Ludwig Bokelmann


Unlabeled images courtesy of Prof. Alberto Espay


  1. There’s nothing not to love about mass data collection. Hopefully, we start immediately and take some of the following into consideration:

    1. This is more than a shot at a cure. It may be equally as much about treatments and best self-care practices.

    2. Collect such data far and wide. Geographic and cultural diversity. There’s almost no limitation to what may result.

    3. There are numerous private companies who would pay significantly for such data. Give them limited access so they can develop more treatments. We should be able to get it funded without having to give up our privacy.

    4. This is a massive source of meaning/purpose for people with PD. Now they’re invested in their own outcomes. People with PD could/should even be hired to collect some of the data or play some role in the project.

    5. Now we won’t have to rely on biased data to tell us what works and doesn’t. We will be able to evaluate every form of treatment objectively, including now having outcome data by physician! Finally, doctors might begin to prioritize patient results over time.

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