alt Hacker NewsAI helps unravel a cause of Alzheimer’s and identify a therapeutic candidate
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This is an interesting observation:
> With AI, they could visualize the three-dimensional structure of the PHGDH protein. Within that structure, they discovered that the protein has a substructure that is very similar to a known DNA-binding domain in a class of known transcription factors. The similarity is solely in the structure and not in the protein sequence.>
Reminds me of: if you come across a dataset you have no idea of what it is representing, graph it.
Tying this to APOE, specifically e4 which has an increased requirement for choline and when choline levels are low there can be a metabolic push that leads to elevated PHGDH activity and consequently, increased serine synthesis. That is a neat connection and maybe why when we study choline supplements we see positive results.
https://www.sciencedirect.com/science/article/pii/S000291652...
I always believed that the AI/LLM/ML hysteria is misapplied to software engineering... it just happens to be a field adjacent to it, but not one that can very well apply it.
Medicine and Law, OTOH, suffers heavily from a fractal volume of data and a dearth of experts who can deal with the tedium of applying an expert eye to this much data. Imagine we start capturing ultrasound and chest xrays en masse, or giving legal advice for those who needs help. LLMs/ML are more likely to get this right, than writing computer code.
Its good to see them classifying this as for "late onset Alzheimer's".
There is a theory that Alzheimer's as we currently understand it, is not one disease, but multiple diseases that are lumped into one category because we don't have an adequate test.
This is also where some of the controversy surrounding the Amyloid hypothesis comes from.
This is a strong argument for universal healthcare. If we had universal healthcare in the USA, we'd have to have a common charting protocol and a medical chart exchange.
One thing that AI/ML is really good at is taking very large datasets and finding correlations that you wouldn't otherwise. If everyone's medical chart were in one place, you could find things like "four years before presenting symptoms of pancreatic cancer, patients complain of increased nosebleeds", or things like that.
Of course we don't need universal healthcare to have a chart exchange, and the privacy issues are certainly something that needs consideration.
But the point is, I suspect we could find cures and leading indicators for a lot of diseases if everyone's medical records were available for analysis.
The author here is shoehorning "AI" into the headline to boost views. Quite misleading.
"AI" in this case was used to generate a 3D model of a protein. Literally, something you can grab from Wikipedia — https://en.m.wikipedia.org/wiki/Phosphoglycerate_dehydrogena...
The underlying work performed by the researchers is much more interesting — https://linkinghub.elsevier.com/retrieve/pii/S00928674250039...
They identified a possible upstream pathway that could help treat disease and build therapeutic treatments for Alzheimer’s.
I don’t know about you all but I’m tired of the AI-mania. At least author didn’t but "blockchain" in the article.
It's a pity the ridiculous level of LLM overhype from those chasing investment and profit is dragging "AI" through the mud with it
I'm an AI skeptic but this is AI doing its job.
Because there's AI as in "letting ChatGPT do the hard bits of programming or writing for me", for which it is woefully unsuited, and there's AI as in using machine learning as a statistical approach, which it fundamentally is. It's something you can pour data into and let the machine find how the data clump together, so you can investigate potential causative relationships the Mark I eyeball might have missed.
I'm excited for the possibilities these uses of AI might bring.
I wonder if they used the output of alpha fold? Remember that Deepmind published the 3D structure of hundreds of millions of proteins for FREE. Imagine if they walled off that data behind an Elsevier like subscription wall? They shoould credit Deep Mind at least
A little to late for my mom, but maybe it will help me in the future...
This article is trashy trash trash. The only mention of AI in the actual paper is that they used ChatGPT for grammar correction. The article doesn't explain what or how AI was used beyond "three dimensional modeling".
A paper author did quote the use of AI. But without explaining precisely how AI was used and why it was valuable this article is basically clickbait trash. Was AI necessary for their key result? If so how and why? We don't know!
Everything about this screams "just say AI and we'll get more attention".
AI steals credit for unraveling a cause of Alzheimers so the bubble will exist a bit longer
This piece of the puzzle, and its finding, if confirmed, is very neat. But I think we are barking at the wrong tree, because senescence is inherently chaotic. Sometimes we identify a disease with a set of common symptoms because there are many alternative causes that lead to those very symptoms. It's like "convergent symptoms", so to speak.
If I had any funding to work freely in these subjects, I would instead focus on the more fundamental questions of computationally mapping and reversing cellular senescence, starting with something tiny and trivial (but perhaps not tiny nor trivial enough) like a rotifer. My focus wouldn't be the biologists' "we want to understand this rotifer", "or we want to understand senescence", but more "can we create an exact computational framework to map senescence, a framework which can be extended and applied to other organisms"?
Sadly, funding for science is a lost cause, because even where/when it is available, it comes with all sort of political and ideological chains.
The 202x trend of adding AI into every story when is irrelevant is getting tiresome
If AI causes us humans to workout our brains less, maybe it is also causing Alzheimer's. In the words of Homer Simpson: "To alcohol! The cause of--and solution to--all life's problems."
Hell yes! This is where machine learning shines and I’m so happy to see another incredible breakthrough from using it in medical science.
It’s a nice reprieve from “we’re using a chatbot as a therapist and it started telling people to kill themselves” type news.
Curious to see how this line of research evolves, especially once they get into clinical trials
I notice that I have a form of Gell-Mann amnesia for this sort of thing. Do we need a new term, or does that cover it?
Because I find myself nodding along with optimism, having two grandfathers that died from this disease. It’d be great if something could sift through all the data and come up with a novel solution.
Then I remember that this is the same technology that eagerly tries to autocomplete every other line of my code to include two nonexistent variables and a nonexistent function.
I hope this field has some good people to sanity check this stuff.
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Minor nitpick about the headline. AI didn't help, it was used to identify a therapeutic candidate. I dislike personification of AI because people treat it as something religious already. AI doesn't do anything, the people using it do.
It's a hell of a lot more likely to find the primary causes of Alzheimers outside of the human body imo, medicines/pollution/additives/radiation etc.
The human body is a pretty amazing construction, nature doesn't make a lot of mistakes.
It's really a bummer to see this marketed as 'AI Discovers Something New'. The authors in the actual paper carried out an enormous amount of work, the vast majority of which is relatively standard biochemistry and cell biology - nothing to do with computational techniques. The AlphaFold3 analysis (the AI contribution) literally accounts for a few panels in a supplementary figure - it didn't even help guide their choice of small molecule inhibitors since those were already known. AlphaFold (among other related tools) is absolutely a game changer in structural biology and biophysics, but this is a pretty severe case of AI hype overshadowing the real value of the work.