From a Walk Home to a Testable Alzheimer’s Theory

Phase 1 — The Spark (April 2024)

It didn’t start in a lab.
It started on a sidewalk.

I’d been deep in Alzheimer’s research for a while — tracing the disease from the molecular chaos of amyloid-β plaques and tau tangles, to the inflammation, oxidative stress, and clearance failures that slowly dismantle the brain’s default-mode network (DMN).

I wasn’t looking at treatments yet. I was just mapping how the disease works, trying to see the hidden logic behind its progression.

And then, on the way home from the store, it hit me — a cinematic, lightbulb moment:

“LITHIUM.”

I hadn’t read a single paper about lithium in Alzheimer’s — but that would change. That night, I got to work.

That night, I wrote the first version of the theory in an email to my cousin (timestamped April 2024). It was still rough — no polished graphics, no formal predictions — but the seed was there.

Phase 2 — Going Public (May 2024)

In May 2024, I released a suite of papers that dismantled the traditional medical model and replaced it with a multi-node engineering strategy. This established the “Logic” long before the “Physics” of the Ion-Sink was proven.

The “Targeted Synergy” Framework: I formally proposed moving away from the “single-target focus” and “cautious, sequential approach”. I argued that instead of avoiding drug interactions, we should actively leverage synergistic effects to address the complexity of the human body.
The First Operational Stack: I didn’t just suggest lithium; I mapped a specific regimen: Lithium to inhibit GSK-3β (the Switch), Rapamycin to induce autophagy (Clearance), and Bromelain to degrade amyloid-beta. I theorized that this combination would clear the terrain and make neurons more receptive to treatment.
The Distribution Insight: I identified that lithium’s failure in trials was likely a failure of distribution and form. I proposed that its effectiveness was a “hidden variable” tied to how it was combined with other agents—directly predicting the local availability problem (the Sink) I would define in 2025.
Delivery Strategy: I focused on “getting it through” the system by using tools like Piperine to enhance the bioavailability of neuroprotective agents like Curcumin. This ensured the tools actually reached the brain instead of getting lost in the systemic “clog”.
The Systemic “Trunk”: I identified peripheral inflammation and markers like IL-6 and TNF-α as the primary drivers of brain decay. By calling out the flaws in existing animal models, I argued that we were failing because we weren’t treating the systemic “Terrain”.

Phase 3 — The Long Pause (Mid 2024 – Mid 2025)

And then… nothing.

Life pulled me in other directions. The lithium idea sat in my archives, public but dormant. No follow-up papers, no lab work — just a theory waiting for the right spark.

Phase 4 — The Catalyst (August 2025)

The spark came in the form of an unexpected fundraising letter from Hjärnfonden.

It got me thinking about that old OSF post. I pulled it back up, dusted it off, and decided to check what had happened in the Alzheimer’s literature since I’d written it.

That’s when I found it — the Harvard/Nature 2025 paper.

They had shown that:

Amyloid plaques bind lithium.
Tissue immediately around plaques is lithium-depleted.
Low-plaque-binding lithium orotate can restore downstream biomarkers at physiological exposure.

It was the missing piece. A direct, biological mechanism for the “distribution matters” hunch I’d written over a year earlier.

Phase 5 — The Sprint (August 2025)

With Harvard’s findings in hand, I dove back into the theory — this time as a full-blown refinement sprint.

I brought my earlier lithium work into a series of deep, iterative sessions with ChatGPT, layering in:

DMN-first amyloid seeding patterns.
Blood–brain barrier and glymphatic clearance defects.
The role of iron-rich microenvironments in amplifying pathology.

Out of this came DISSAD: Default-mode Network Ion Seed-and-Sink in Alzheimer’s Disease.

The model:

Amyloid plaques form in DMN hubs.
These plaques act as lithium ion sinks, binding lithium and creating local depletion zones.
Depletion disinhibits GSK-3β → tau hyperphosphorylation → microglial activation → network failure.
Severity is modulated by local iron levels and clearance efficiency.

The trial plan:

^7Li-MRI to map lithium distribution.
QSM for iron mapping.
Amyloid/tau PET for pathology.
Fluid p-tau217 slope tracking.
Chemistry-region interventional probes contrasting high- vs low-binding lithium.

For the first time, the theory wasn’t just a clever idea — it was falsifiable.

Default‑mode Network Ion Seed‑and‑Sink in Alzheimer’s Disease (DISSAD)

Phase 6 — The Wait

And now we wait

Cheers
Marcus