Petr Houška

Worth noting, no major disease has shown better hard outcomes from outlook or wanting to get better - Cancer - MS - Lupus - RA - Heart disease - HIV - ME/CFS Etc You can recover & credit your mindset. But you didn’t think your way out. That was natural recovery, luck, & placebo

One of the biggest reasons I’ve become theory-agnostic in Long COVID and ME/CFS is how easy it is to become convinced you’ve found the explanation. That is not because people are irrational. It is because the human brain has to simplify problems in order to handle them. When a disease is extremely complex, with many overlapping systems and huge amounts of literature, we naturally latch onto a theory that seems to connect a lot of the dots. I saw that in myself very early on with ROCK1. I came across papers suggesting it may be altered after COVID, and the more I read, the more compelling it seemed. ROCK1 appeared connected to mitochondrial dysfunction, vascular dysfunction, viral persistence, and a range of other features that looked highly relevant. It felt like I might have found something that could explain the disease. Interestingly, in our own data, ROCK1 appears reduced in blood. But even that is not straightforward. Lower circulating ROCK1 may in some contexts reflect cleavage, which could imply increased activity rather than decreased importance. That still needs further research. The same pattern repeated across other pathways. Angiotensin 1-7, ACE2, PINK1, TGFB, NAD+ biology, tryptophan and kynurenine metabolism, T-cell exhaustion, NK-cell exhaustion, and mast-cell biology. Each time, there were mechanisms that looked compelling. There were people who improved when targeting them. But there were also people who worsened from the exact same interventions. At a certain point, the pattern becomes difficult to ignore. Multiple pathways can each look capable of explaining the disease, which means likely none of them do on their own. Finally, we are beginning to see the emergence of systems that may be able to hold the full nuance and scale of biological data in context at once, something the human brain has not been able to achieve. Now the goal is clear. Build the highest-quality datasets to allow those systems to solve these diseases as quickly as possible 💪

Two recent stories suggested AI may help find highly personal treatment routes in cancer, one in Sid Sijbrandij and one in Rosie the dog. There is some nuance here, so I’ll break down what happened in simple language, including cost, and how similar logic could apply to chronic disease.