Alex Plesa

Can we reverse aging? 7 yrs ago, Ocampo et al. showed that partial reprogramming can ameliorate aging hallmarks. But, OSKM induction has safety limitations & no new factors have emerged since. Here, biorxiv.org/content/10.110… we used 🧬 screens to find new rejuvenation factors🧵1/8

Some thoughts on why it's so hard to find a cure for aging — tarkhov.ae/age-time-rever…

1/ How long do you want to live? For most of human history, aging was inevitable. It's now solvable. Apply for LBF8 cohort program: longbiofellowship dot org /THREAD🧵

I’m excited to launch the Longevity Biotech Atlas, a personal project mapping 700+ organizations across the aging and longevity ecosystem. Longevity biotech is moving fast. A lot of the public narrative has centered on GLP-1s, peptides, biohacking, and consumer health optimization. But beneath that, a much deeper ecosystem is forming: companies, labs, investors, and non-profits working on core technologies that will enable fundamentally new forms of measurement and rejuvenation. The field is growing quickly, but it is still hard to answer basic questions: Who is building what? Which areas are crowded? Which technologies are underexplored? Where should founders, scientists, investors, and operators be paying attention? To help make the space easier to navigate, I synthesized public information on 700+ organizations—ranging from therapeutics developers, diagnostics, investors, and more— into a single database. You can explore the atlas at the link in the comments. This is still an early version, and I’ll be adding more over time: new organizations, personal accounts, bookmarks, and better ways to track how the field is evolving. My hope is to build this out into a core tool for people trying to understand, build, fund, or work in longevity. If you’re interested in aging biology, biotech, investing, company formation, or the future of medicine, follow along. I’ll be sharing updates, maps of different subfields, and analyses of where the biggest opportunities and gaps may be. Let me know what you find useful!

Let’s stay at peak health without limits! 🧬 Vitalist Bay 2026 is T-30 days away in Berkeley, CA from May 14-17. Thanks to our partners, join this week & get: 🩸 Free @rythmhealth blood panel 🩻 Free @BodySpec DEXA scan Full program @ vitalistbay.com (+ a unique benefit ↓)

for a while i've had a slight fear that the bluetooth from my airpods could be frying my brain this weekend i pulled the raw data from a $30m government study of 1,679 mice blasted with cell phone radiation and reanalyzed it what i found was...not what I expected? 🧵

A reminder that cellular rejuvenation ≠ organismal rejuvenation In mice, chemical reprogramming cocktails could be safely administered at lower dosages but with little benefits. At higher dosages, they became toxic and required euthanasia.

🧵 Elon: “Longevity is an extremely solvable problem” At Vitalist Bay (May 14 - May 17), we’re solving it! 1K+ pioneers, 100+ speakers, 50+ workshops, 40+ activities, 5 critical health tests Join us to spark dozens of SpaceXs for longevity!

How could tiny breakthroughs in aging science change U.S. GDP and population growth? What’s the economic value of making 41 the new 40, or 65 the new 60? How many lives could we create or save if we could slow reproductive or brain aging by just 1 year? What would billions of healthier hours be worth to the economy, if we assume no change in the age of retirement? I spent the last two years obsessing over the design, research, and execution of this project. The result is a book upcoming with Harvard University Press, a preprint, and—maybe your favorite part—an interactive simulation tool that lets you input your own timelines and assumptions for specific breakthroughs in aging bio, then see the ROI in terms of US population & GDP growth. From @RickEcon and Jason DeBacker—the economists who co-developed the open-source, macro model that made this project possible—to extensive comments by @tylercowen, @sapinker, Richard Freeman, @NDHendrix, @ebudish, @elidourado, @geochurch, @jasoncrawford as well as interviews with 102 scientists (!) and countless iterations with award-winning designer Giorgia Lupi and the @pentagram team, we built something we hope will be a benchmark for how scientists, economists, designers, philosophers, entrepreneurs and storytellers can come together to paint, fund, and build different flourishing futures for our species. I couldn’t be more excited to share this. It’s the start of an open and evolving project—the labor and product of love, obsession, and unrelenting care. I hope you have fun playing with our simulation tool — and if you do, please share!

Announcing our 2026 Fellows! One is a neuroscientist exploring how the brain computes at a molecular level, another is a bioengineer 3D-printing human tissue. There’s a PhD student working on computational protein design, and an engineer developing robots to build large structures in space – just to name a few of the badasses in our new Fellowship cohort! With this one-year program, we want to support early-career talents advancing important science and tech. We connect them with senior scientists, invite them to our technical workshops, seminars, and Vision Weekends alongside leaders in their fields, and offer platforms for sharing their work. We are incredibly excited to introduce our 2026 Fellows! Longevity Biotechnology • Alex Plesa, Scientist, Harvard University @amplesa • Donnacha Fitzgerald, Founder, Origenity @DN_Fitzgerald • Gianluca Cidonio, Assistant Professor, Sapienza University @gianlucacidonio • Jakub Lála, PhD Student, Imperial College London @jakublala • Léo Lopez, Staff Scientist, Tufts University • Nick Schaum, Postdoc & Co-Founder, University of Cambridge & Covalent.Bio Neurotechnology • Avery Krieger, Founder & CEO, Constellation Systems @Biofall • Constanze Albrecht, Graduate Student, MIT Media Lab • Elisa Kallioniemi, Assistant Professor, New Jersey Institute of Technology • Max Kanwal, PhD Student, Stanford University • Sven Truckenbrodt, Group Leader, MRC Laboratory of Molecular Biology Secure AI • Huixin Zhan, Assistant Professor, New Mexico Tech • Keith Patarroyo, Research Fellow, University of Glasgow @KeithPatarroyo • Mateo Petel, Research Scientist, Stanford University • Tianyi Alex Qiu, Research Fellow, Oxford Human-Centered AI Lab @Tianyi_Alex_Qiu • Vivek Nair, CEO, Multifactor Nanotechnology • Alberto Privitera, Assistant Professor, University of Florence • Kathryn Shelley, Postdoctoral Researcher, University of Washington • Konlin Shen, Research and Development Engineer, University of California San Francisco • Qiancheng Xiong, Senior Scientist, A*STAR Bioprocessing Technology Institute Space • Philip Linden, Space Systems Engineer, Planet Labs PBC • Sidh Sikka, Co-Founder, Manifold Research @SikkaSidh Existential Hope • Abigail Olvera, Research Director, Golden Gate Institute for AI @Abi0lvera • Fin Moorhouse, Researcher, Forethought @finmoorhouse • Mahlaqua Mila Noor, Viral Immunologist, University of Cambridge • Ninon Lizé Masclef, Research Affiliate, MIT Media Lab @ninon_lize • Peggy Yin, PhD Student, Stanford University • Ruairidh Battleday, AI Researchers & Founder, Thinking About Thinking @RMBattleday Learn more about our Fellowship: foresight.org/engage/fellows…

Our new paper is now online in @NatureBiotech. We use gRNA engineering, phage-assisted non-continuous evolution (PANCE), and protein language models to improve the precision of adenine base editing. @harvardmed @geochurch nature.com/articles/s4158…

@jpsenescence It depends on the biological system -Cells can not age (iPSCs, HEKs) and can be rejuvenated (reprogramming) -Tissues can have negligible aging (development), but it’s hard to rejuvenate them without removing or diluting damage -Some animals can not age by continuing to develop

If aging is caused by damage that only occurs when maintenance processes become less effective post-development then I'd argue that: 1) We don't age due to inevitable, passive accumulation of molecular damage but rather aging is driven by programmatic changes during development that allow damage to occur. 2) Our cells have the capacity not to age and - in theory, though in practice it may be technically challenging - we can instruct our cells to prevent aging. 3) Let's figure out 1) and 2) 🚀

What's the most predictive biomarker of mortality? Epigenetic clocks get all the attention (thanks to @bryan_johnson and a certain Harvard professor), but they're NOT the most powerful way to predict future health, disease, or mortality. The answer comes from a different biological data type entirely.

Can you rejuvenate an old brain by giving it young immune cells? 🧠 My lab @calico put it to the test. In our new study, we replaced the brain's immune cells in old mice with young ones. The result? The old brain environment forced the young cells to age RAPIDLY. A 🧵👇

@ArtirKel Pluripotent ground state seems to be characterized by global hypomethylation cell.com/cell-stem-cell…

I just realized there's enzymatic methylation and demethylation but only passive demethylation (demethylated CpG is more stable). I had probably read papers saying this already but never noticed or assumed that it had to be symmetric. I was probably reasoning from information theory intuitions instead of physics.

1/ Can we find more precise and even safer ways to rejuvenate vision? As a step towards this goal, I am excited to share this preprint of my 1st postdoc work from @JswLab with amazing collaborators, esp. @Bruce_Ksander! Using functional genomics, we discovered GSTA4 as a key OSK effector for oxidative resilience—overexpressing it alone rejuvenates RPE & restores vision. A breakdown👇biorxiv.org/content/10.110…

@sofipriors @ArtirKel I think that’s why DNAm clocks were the first to come online. I’d assume there’s an inverse correlation between signal stability and the dynamic nature of a layer of biological information (DNAm>RNA>protein). Looking forward to the post

It seems to me a big flaw of many virtual cells efforts is not including aged cells. Aged cells look similar enough to young cells at steady state in scRNAseq, but after perturbations they react differently (this is easier to see in chromatin)

@ArtirKel Exactly! Cell type clustering is also cleaner with scATAC, despite the data being more sparse. Cell cycle genes make things messier in scRNA

@amplesa Yep. Or this dataset nature.com/articles/s4358… . Right pic: scRNA can't tell them apart. scATAC? Beautiful separation even with mixed cell types

@ArtirKel Really good point! We see this in our multiomic data from HSCs across aging. Gene expression doesn’t change a lot in aging, but some regions of chromatin accessibility do.

Just like an aged person: aged livers are fine and you wouldn't know until alcohol hits

In the past thirty years, the number of deaths from cancer has dropped dramatically, resulting in millions of lives saved. Some of this is due to improvements in oncology treatments, including immunotherapy. But most of the effect has little to do with biopharma at all.

New paper @NatureRevCancer on the evolutionary interplay between ageing and cancer 🚨 These are overlapping yet also antagonistic processes. While cancer involves cell proliferation and growth, ageing often involves cellular degeneration and atrophy. Because natural selection prioritizes cancer resistance, I argue it ultimately shapes the evolution of ageing. As such, selective pressures that mitigate cancer risk in young animals contribute to late-life ageing phenotypes. Tumour suppression mechanisms, such as telomere shortening and cellular senescence, have long been argued as such antagonist mechanisms. However, I think there is a much deeper impact involving growth and developmental mechanisms, like hedgehog signalling, that are down regulated with age to reduce cancer risk yet later contribute to loss of stem cell function and tissue homeostasis. Also, given that many processes are antagonistic between cancer and ageing, some anti-ageing interventions could promote cancer, though I argue that this depends on the biological and evolutionary context of the targeted process. Cancer-ageing trade-offs are thus an important caveat when developing interventions targeting ageing processes and must be accounted for in translational geroscience. nature.com/articles/s4156…