#370 – AMA #76: Peter evaluates longevity drugs, aspirin for CVD, and strategies to improve muscle mass — promising, proven, fuzzy, noise, or nonsense?

We discuss:

Timestamps: There are two sets of timestamps associated with the topic list below. The first is audio (A), and the second is video (V). If you are listening to this podcast with the audio player on this page or in your favorite podcast player, please refer to the audio timestamps. If you are watching the video version on this page or YouTube, please refer to the video timestamps.

• A framework for evaluating scientific claims: proven, promising, fuzzy, noise, or nonsense [A: 1:30, V: 0:10];
• Strong convictions, loosely held: the mindset that separates great scientists from the rest [A: 7:30, V: 6:30];
• GLP-1 agonists: are there benefits beyond improving metabolic health and promoting weight loss? [A: 12:45, V: 12:25];
• GLP-1 drugs and the brain: exploring the potential cognitive benefits [A: 18:45, V: 18:55];
• GLP-1 drugs and lifespan: examining the evidence for potential geroprotective effects [A: 23:00, V: 23:45];
• Rapamycin and geroprotection: why it remains in the “promising” category [A: 25:45, V: 26:50];
• SGLT2 inhibitors and their potential geroprotective effect [A: 27:30, V: 28:40];
• Methylene blue: examining the evidence of an anti-aging effect [A: 34:45, V: 37:00];
• Methylene blue’s potential neuroprotective effects: limited and inconsistent evidence in humans, and the challenges of dosing and safety [A: 41:15, V: 43:45];
• Telomeres: what they are, how they relate to aging, and why telomere-lengthening supplements lack credible scientific evidence [A: 43:45, V: 47:26];
• Does the idea of targeting telomere length to extend lifespan have scientific merit? [A: 50:15, V: 54:45];
• Low-dose aspirin for cardiovascular disease prevention: weighing its clot-prevention benefits against bleeding risks across different populations [A: 55:00, V: 1:00:05];
• Rethinking the protein RDA: why most people need twice the recommended amount for muscle health [A: 1:00:45, V: 1:06:40];
• Debunking the protein–cancer myth: why higher protein intake doesn’t promote tumor growth [A: 1:06:15, V: 1:12:40];
• The biology of follistatin and myostatin, and why follistatin gene therapy has become an emerging topic of interest for muscle growth [A: 1:13:15, V: 1:20:50];
• Follistatin gene therapy for muscle growth: state of the evidence in animals and humans, and the technical challenges and regulatory barriers [A: 1:17:00, V: 1:25:05];
• Why injectable follistatin is theoretically possible but impractical for real-world use [A: 1:23:15, V: 1:32:30]; and
• More.

Show Notes

A framework for evaluating scientific claims: proven, promising, fuzzy, noise, or nonsense [A: 1:30, V: 0:10]

Overview & Structure of the Episode

• This AMA (Ask Me Anything) departs from typical deep-dive topics.
• Goal: summarize multiple health- and longevity-related interventions through a unified evaluative lens rather than exploring each in isolation.
• Framework: the “Five-Category Scale” — Proven, Promising, Fuzzy, Noise, Nonsense — first introduced in Episode 300 (May 2024).
• Purpose:
  • Compare diverse claims apples-to-apples by level of evidentiary support.
  • Give listeners quick, clear takeaways grounded in data strength.
  • Revisit familiar concepts and introduce new ones under this schema.

Topics to Be Evaluated

• Geroprotective / Longevity-Linked Drugs
  • GLP-1 receptor agonists (e.g., Ozempic).
  • SGLT2 inhibitors
• Emerging or Popularized Agents
  • Methylene blue.
  • Telomere-lengthening supplements.
• Preventive Pharmacology
  • Low-dose aspirin and its evidence in cardiovascular-disease prevention.
• Muscle-Preserving / Building Interventions
  • Protein intake optimization.
  • Follistatin gene therapy and other muscle-mass-enhancing concepts.

The Five-Category Evidence Scale

• Proven – “As close to truth as biology allows.”
  • Supported by high-quality, consistent data replicated across studies.
  • Comparable to well-established scientific claims.
  • Note: in biology, nothing is ever literally proven (not like math with Q.E.D.).
• Promising –
  • Data trend in a positive direction but may lack replication or completeness.
  • “Looks good but not fully confirmed.”
• Fuzzy –
  • Limited or inconsistent evidence.
  • Some possible signal but weak or incomplete data quality.
• Noise –
  • Essentially no meaningful or reproducible results.
  • Not necessarily dismissible forever — could move up if stronger data emerge.
• Nonsense –
  • Existing data refute the claim.
  • As close to disproven as a biological hypothesis gets.

Key Conceptual Notes

• These categories are fluid; interventions can migrate up or down with new evidence.
• The framework encourages critical thinking and ongoing reevaluation rather than fixed judgments.
• Intended outcome: help listeners allocate attention toward interventions most supported by evidence and away from distraction.

Strong convictions, loosely held: the mindset that separates great scientists from the rest [A: 7:30, V: 6:30]

“strong convictions, loosely held”

• In today’s culture—especially in fields like nutrition—people often anchor themselves to rigid beliefs (“camps”) and resist updating them despite new evidence
• This prompts Peter to elaborate on the idea of having “strong convictions, loosely held”
• Foundational Principle:
  • “Strong convictions, loosely held” = maintain confidence in well-reasoned positions but stay willing to revise them when credible new evidence arises.
• Attribute of Great Scientists:
  • Great scientists differ from good ones because they are not “married to being right”; they are “married to knowing what is right.”
  • Their allegiance lies with truth, not ego or past beliefs.
  • Willingness to evolve with data is the mark of intellectual integrity.

Origin of the Phrase

• Peter first heard the expression from a friend who managed a hedge fund (now retired).
• The friend applied the principle in investing:
  • You must hold strong convictions to justify putting real capital at risk.
  • But convictions must be loosely held so you can pivot quickly when new information invalidates your thesis.
  • In investing, rigidity is financially fatal—when you double down on wrong positions, you lose money and clients (“LPs”).

Parallel Between Science and Investing

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