Ground Truths

In recent weeks the results (announced by press release) of 2 major placebo-controlled randomized trials—ZEUS, testing an interleukin-6 (IL-6) blocker vs inflammation, and HORIZON, testing a drug to lower Lp(a), indicated failure to achieve their primary endpoint.
Are we maxxed out for new treatments vs heart disease, as this article in the WSJ (←gift link) today asserts?
“Cardiovascular drug development is starting to look a bit like the modern oil industry. The easy wells have been tapped. What’s left is in deep water: expensive, technically perilous and less likely to strike oil.”

Or is it more complicated? Are the trial results and reasons for failure different?
I wrote a recent Ground Truths —The Coronary Artery Inflammation Controversy— on the data (what has been released to date) and my take. But I wanted to vet this with another physician-scientist who is studying atherosclerosis and turned to Prof Marios Georgakis, from the University of Munich, who as I mentioned in the previous piece, wrote a brilliant analysis of ZEUS and is also doing writing about HORIZON.
Many years ago we went through a “CV winter” when the biopharma companies largely shunned doing clinical trials for heart disease. They thought the field had been maxxed out. After a lapse of several years, there have many trials undertaken with positive results and substantial progress for better treatments vs heart disease. Both Marios and I remain optimistic that we are a long way from maxing out, as you’ll learn from the podcast. Heart disease is the number one global killer, for both men and women. That’s despite all the progress that has been made to date.

Thanks for your support of Ground Truths and to Dr. Julie Kellogg, Vau Geha, Ralph Horwitz, Jessica Coffman, Michael G. Levin, MD, and mopre than 400 others for tuning into my live video with Marios Georgakis!
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Ground Truths has 215,000 subscribers from every US state and 214 countries. There are over 310,000 followers of Ground Truths so nearly 100,000 folks who can easily convert to be free subscribers. Please consider doing that…it’s free.
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This podcast is meant to complement my recent Ground Truths post Why Our Memory Slips After Age 50 which has all the relevant links to the 2 papers, key graphics, and other related publications. If you haven’t had a chance to read that, it would be helpful to spend a few minutes to do so before listening to this podcast.
Links to the 2 papers for those who don’t want to look back
Zemke et al in Science https://www.science.org/doi/10.1126/science.adt8307
Belk et al in Nature https://www.nature.com/articles/s41586-026-10939-0

It’s a major and fascinating discovery. We’re talking about a “hostile takeover” of blood monocyte cells that invade the brain and ultimately completely replace the brain microglia. The problem is these new microglia are pro-inflammatory.
A surprising finding is about CHIP (blood stem cells with mutations known as clonal hematopoiesis of indeterminate potential) that was shown to be protective. It’s surprising because CHIP is common with age and until now it has been linked to bad things such as cardiovascular disease, clotting, and cancer. If this pans out, it introduces the concept of immunotherapy of the blood (“brain immunotherapy”).
We discussed recent studies of microglia replacement and ways to keep our brain microglia intact, such as prevention any breakdown of the blood brain barrier.
The role of latent viruses and the mechanism of benefit of the Shingles vaccine were touched on.
Our conversation provides far more color and perspective about why their independent, complementary, and convergent findings are so important, debunking our longstanding belief that the microglia, the immune cells in the brain, are exclusively derived from the brain. Technology driven discovery. And what are the next steps in this line of research.

I hope you found this podcast illuminating and fun. If you did, plus share it with your network. Thanks for supporting Ground Truths and your help in spreading the word.

And thank to jojofinance, Elisabetta Pilotti, Daniel Rench, Dr. Sara Wolfson, Bob Fleischman, and hundreds of others for tuning into the live video with Julia Belk and Nathan Zemke! Join me for my next live video in the app.


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Deb Cohen is an award winning investigative journalist and correspondent who trained as a physician and has worked with the BBC and BMJ. She just published BAD INFLUENCE, a book which takes us deep into the wellness-industrial complex—the confluence of the supplement, testing, tech, and pharma industries, and how they sell health anxiety to healthy people.

Here are some of the points we discussed:
—The big market in healthy, well people. Tests, wearables, imaging, supplements, etc
—Algorithms feed the health anxiety in an amplifying, vicious loop on the social media platforms. When the algorithm knows you better than you.
—The special qualities of influencers, likable, relatable, vulnerable, appearance as friends, certainty, cultivating parasocial relationships. “I understand you, I see you, I hear you.” Often with financial conflicts of interest. Plus hidden financial benefits.
—The inverted pyramid of evidence and displacement of trust. Anecdotes believed and accepted as best evidence instead of rigorous randomized trials. A big flip, doctors losing trust to influencers and the sponsors of influencers.
—The Nocebo effect of harm through expectations
—The epidemic of neurologic tics during the pandemic traced back to TikTok, a viral contagion with 5.8 billion views (Figure made with Notebook LM)

—Potential for regulation of patient/consumers/prosumer influencers
—Celebrity influencers and the recent NEJM paper
—Many ideas for how we can mitigate this mess (Graphic by Notebook LM)

—Many illuminating patient examples: Femtech, silicon breast implant illness (BII), beta blocker experiment, a bogus bioresonance of hair test in a woman with GI symptoms, full-body MRI of brain lesions (transmitted to the patient by an automated message) that were a false positive.
—The term “wellness”
—Concierge physicians

Thank you jojofinance, Vote Against Billionaires, Gretchen Faucett, Mary Powers, Jessica Coffman, and hundreds of others for tuning into my live video with Bad Influence! Join me for my next live video in the app.
Ground Truths has subscribers from every US state and 214 countries. There are over 302,000 followers of Ground Truths so nearly 90,000 folks who can easily convert to be free subscribers.

Your subscription to these free essays and podcasts makes my work in putting them together worthwhile. If you’re not a subscriber, please join!
If you found this interesting PLEASE share it!

A couple of other things to note:
—Thanks to the voluntary paid subscribers who support our summer internship program for high school, college, and grad school students. On August 6th, we had a poster session with our SRTI summer interns (pictured below) which was an extraordinary event with about 100 posters!

—I hit a publication milestone that I had not ever envisioned. More than 400,000 citations with an h-index of 259, as tallied by Google Scholar
Thanks to all for your support of Ground Truths.



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Sarah Urbut is a physician-scientist at Harvard Medical School and the Massachusetts General Research Institute. She and her colleagues published a landmark paper in Nature on patient health journeys for 3 different cohorts—the Mass General Brigham patients, the UK Biobank, and the All of Us research program—with a cumulative 683,000 individuals, 348 diseases, and up to 52 years of follow-up. Integrating electronic medical records and polygenic risk scores (N=36). An AI model was developed and validated called ALADYNOULLI, with each individual represented latent disease signatures (N=21), mathematically and biologically driven. An example of a patient’s dynamic life journey (health arc) is provided in the Figure below (adapted from the paper, made with NotebookLM). The longitudinal story for each individual is key here. Using a Gaussian process, the risk continually shifts like a GPS navigation when you make a wrong turn and you are re-routed. Considerable effort was dedicated to addressing selection bias with inverse probability weighting.

Here are 20 temporal pattern signatures for the UK Biobank cohort, which help to provide the biologic mechanism of a person’s disease, as shown for multiple conditions like heart attack, breast cancer, and depression. That is, the same disease phenotype can link to different genomic pathway underpinnings. An example for breast cancer could be related to signature 8 or signature 7; the latter tied to inflammation and metabolic abnormalities. This biological pattern could also be used to detect likely medication failure (such as SSRI treatment for depression) and predict rare diseases.

In fact, the model was used to discover genomic signatures for different diseases, as shown below.
This model predicted 1 and 10-year risk of diseases at the individual level and far surpassed routinely used clinical prediction calculators such as the pooled cohort equation (PCE) for coronary artery disease (0.89 vs 0.68, respectively, 1-year risk ) and the GAIL model for breast cancer (0.783 vs 0.54, respectively). ALADYNOULLI also surpassed accuracy for precision when compared with the recent Delphi-2M model that I wrote about here
The ALADYNOULLI paper is packed with information and equations and is not easy to get through without a sophisticated math background. That’s why the summary infographic below (made by Notebook LM) may be helpful to grasp its main findings

Prediction of Your Health Trajectory in Context
The new model substantively adds to many other recent reports that include Delphi 2M, APOLLO, and AURORA that predict future health events up to 20 years out. Each of these models were different with respect to inputs, how patient data were represented (tokens, embeddings, or latent states), and prediction outputs as briefly summarized in the Table I made below. Notably, the inputs are complementary and likely additive, such that the deeper and longer (longitudinally) the data re for each individual, the better predictive accuracy will be possible.

Adding to these models are many specific disease prediction (e.g. cancer, asthma, diabetes, neurodegenerative diseases) and sources of data (such as sleep lab, wearables, or high-throughput proteomics).
We are now seeing intense efforts at medical forecasting which will continue to evolve and something that was not previously possible in patient care. What I mean is that we could provide a rough sense of a patient’s risk for, let’s say Alzhiemer’s disease, but could not temporally place when it might occur. Age 65 or 95? It makes a huge difference. And so does the ability to apply counterfactuals, what-if scenarios for the individuals to reduce the risk, markedly defer a condition’s appearance, or even fully prevent it. That’s why ALADYNOULLI adds yet another dimension, different methodology, multiple patient cohorts, and novel findings that further add to a new prediction and prevention dimension of medical practice. It couldn’t have been done with multimodal AI.
Note to readers: I wrote this post entirely. There was no AI used except to generate 3 Figures by Notebook LM (Figure 1,3 and 4) as noted. Figure 2 above is from the Supplemental information of the paper. I have no COI related to this post.

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A big thanks to Ground Truths subscribers from every US state and 212 countries. Your subscription to these free essays and podcasts makes my work in putting them together worthwhile. If you’re not a subscriber, please join!
If you found this interesting PLEASE share it!
Paid subscriptions are voluntary and all proceeds from them go to support Scripps Research. They do allow for posting comments and questions, which I do my best to respond to. Please don’t hesitate to post comments and give me feedback. Let me know topics that you would like to see covered.
Many thanks to those who have contributed—they have greatly helped fund our summer internship programs for the past two years. It enabled us to accept and support a record number of 61 summer interns here with us now! These are high school, college and medical students selected from thousands of applicants. We couldn’t do this expanded program without the funds coming in through Ground Truths.
And thank you Harshi Peiris, Ph.D., DOCTOR KLOVER 🍀, William Joseph Turner, Barry R. Davis, Robert Taylor, and hundreds of others for tuning into my live video with Sarah Urbut, MD PhD! Join me for my next live video or newsletter in the app.


Get full access to Ground Truths at erictopol.substack.com/subscribe

“The future of biology is programmable.”
To give you a sense of how important this topic is, Patrick Hsu is the first guest we’ve had back to Ground Truths since the podcast began a few years ago. Nearly 2 years ago we spoke about digital biology but so much has happened since to help unravel the complexities in the language of life.
Patrick is a co-founder and core investigator at the Arc Institute. His work is at the intersection of biology, engineering, and AI. At the ripe old age of 33, he’s a pioneer of genome editing technologies and my go-to for tracking progress in digital biology. Besides that he’s a great explainer with frequent use of metaphors and simplification of very complicated stuff.

Here’s what we discussed with the relevant links:
—Our recent review in Nature Biotechnology on the large language of life models (LLLMs). GBAI-generalist biological artificial intelligence

—The 2 multi-agent AI Nature papers in May for accelerating drug discovery: Full House (Robin) and Google Deep Mind (Co-Scientist) Multiple drug candidates were described as an outgrowth of multi-agent AI , with a 200-fold decrease in workflow time.
Below Figure from synthesis of the Robin and Co-Scientist papers: “AI devises hypotheses and ways to test them,” Nature News and Views, by Oliver Elemento

—Biomni published in Science 9 July
An infographic by NotebookLM below helps give you a sense of what—a diversity of important tasks— accomplished by Biomni

—New workbench offerings by the AI companies including Anthropic’s Claude Science, Open AI, Google DeepMind and the competition with academic spinoffs
—Spud Cells
—Virtual Cell project, which it’s such a big deal, and the importance of perturbations
—Alzheimer’s disease with OpenAI for finding mechanistic new targets for drug discovery
—The Nature Editorial
—Mid-Journey’s Ultrasound Imaging of the “Whole-Body” (and we’re not imaginative enough, the need to think big)
—Mitigating the worries about humans as lab assistants and nefarious use to produce bioweapons
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A big thanks to Ground Truths subscribers from every US state and 212 countries. Your subscription to these free essays and podcasts makes my work in putting them together worthwhile. If you’re not a subscriber, please join!
If you found this interesting PLEASE share it!
Paid subscriptions are voluntary and all proceeds from them go to support Scripps Research. They do allow for posting comments and questions, which I do my best to respond to. Please don’t hesitate to post comments and give me feedback. Let me know topics that you would like to see covered.
Many thanks to those who have contributed—they have greatly helped fund our summer internship programs for the past two years. It enabled us to accept and support a record number of 61 summer interns here with us now! These are high school, college and medical students selected from thousands of applicants. We couldn’t do this expanded program without the funds coming in through Ground Truths.
Finally, thank you Alan Heldman MD, Bob Fleischman, Jeanie, Maureen Susannah, Mary Powers, and more than 400 others for tuning into my live video with Patrick Hsu! Join me for my next live video in the app.


Get full access to Ground Truths at erictopol.substack.com/subscribe