u/dan_in_ca

A review of a pilot study that seems to connect rapamycin therapy to increased cerebral blood flow in APOE4 carriers.

Interesting mechanistic insight. I personally noticed this after carrying my 16 month old around in a baby bjorn vest and seeing body composition changes that seemed outsized relative to my dietary changes. Interesting to connect the mechanism.

A review on how SGLT2 inhibitors target ectopic fat (specifically epicardial fat). Ectopic fat is the excess fat that gets stored in organ tissue. The paper outlines the different mechanisms of how it does so. For anyone not familiar with SGLT2 inhibitors, they cause you to urinate 60-80g of glucose, so it can cause a mild caloric deficit. It would be interesting to see a side by side comparison of how SGLT2i's compare to GLP1 reduction in ectopic fat.

For anybody interested in the metabolic hypothesis of Alzheimer's, this is an interesting overview of research on the overabundance of glycan protein modifications and the failure to clear them as contributors to Alzheimer's pathology.

One of the more interesting callouts was glucosamine usage was associated with a 25% higher mortality risk in patients with established Alzheimer's disease-related dementia, and a 25 percent higher rate of progression from mild cognitive impairment to full dementia.

Major caveats are needed to process that finding because it seems like this finding does really translate to healthy people taking glucosamine. The biological mechanism through which it could worsen outcomes in an already hyperglycosylating brain is coherent though.

An analysis of a new biological age model from the Wyss-Coray Lab at Stanford. Bioage models typically give a composite number. This model maps aging at the level of individual cell types, 40+ simultaneously from a single blood draw. It's validated across two proteomics platforms and with blood bank data from 60k people.

The big takeaway is that it has a disease prediction model. Extreme astrocyte aging predicted Alzheimers with a hazard ratio comparable to APOE4 over 15 years. Extreme skeletal myocyte aging predicted ALS 12.7x higher risk years before diagnosis. And people with extreme aging across 20+ cell types had 34% 15 year survival vs 90% for normal agers. Pretty cool if true.

Caveats are real though. The proteomics platforms aren't routine clinical tools yet, cohorts were mostly older and caucasian, and nobody has shown that actually modifying these cellular aging trajectories changes outcomes the way the associations predict. But the idea that you can get cellular resolution biological age from a blood test and meaningfully improve disease prediction over composite scores feels like a step forward. Cautiously excited about where this goes as the tech gets more accessible.