I’ll put Mike’s videos in this thread when I see them and think they are interesting…
Introduction to Biological Age and Blood Testing
The video discusses the results of a blood test conducted in 2025, indicating a biological age that is significantly younger than the chronological age.
The speaker questions whether the biological age clock, specifically the pheno age, has any blind spots and introduces the nine biomarkers that contribute to this assessment.
These biomarkers include measures related to liver health, kidney function, metabolic health, immune response, and red blood cells, but notably exclude cardiovascular disease biomarkers.
The absence of cardiovascular disease-related biomarkers is emphasized as significant since cardiovascular disease ranks among the top five causes of death.
A younger biological age is correlated with a lower risk of death from cardiovascular disease, suggesting the importance of tracking additional biomarkers related to cardiovascular health.
Cardiovascular Disease Risk Biomarkers
The speaker plans to delve into cardiovascular disease risk biomarkers, beginning with details from the blood test report.
Tests are ordered through ultalabtest.com, allowing for personalized selection of tests, followed by a blood draw at Quest Diagnostics.
Results from a test conducted on July 22nd were received just four days later, highlighting the efficiency of the process.
Lipid Panel Results - HDL
The speaker reviews HDL (high-density lipoprotein) levels from the lipid panel, noting a result of 76 milligrams per deciliter, which is above the reference range of 40 milligrams per deciliter.
While the result is good, the speaker refers to a more stringent optimal range of 50 to 69 milligrams per deciliter based on extensive studies involving millions of participants.
HDL levels tend to decline with age, and the speaker has created a Patreon tier to share data on optimal biomarker ranges as they relate to aging.
The speaker examines HDL data spanning 20 years, revealing fluctuations and a general decline prior to 2015, which coincided with the beginning of a more rigorous dietary tracking approach.
Since adopting a detailed dietary tracking method, the speaker has managed to increase HDL levels significantly, with a recent average of 58 milligrams per deciliter.
APOA1 Levels and Their Significance
APOA1, a component of HDL, is discussed as an important biomarker for cardiovascular disease risk, with the speaker presenting a current test result of 166 milligrams per deciliter.
The reference range for APOA1 is anything over 115 milligrams per deciliter, indicating that the speaker’s result is satisfactory.
The speaker notes that the reference range has not been updated since a 2004 study, despite newer data being available.
The optimal range for APOA1, based on recent studies, is identified as 150 to 180 milligrams per deciliter, suggesting that the speaker’s levels are adequate but could be improved.
The speaker’s average APOA1 levels over six tests are 146 milligrams per deciliter, which is slightly below the optimal range but shows potential for improvement.
Triglyceride Levels and Assessment
The triglyceride level from the latest test is reported at 62 milligrams per deciliter, which is well below the reference threshold of 150 milligrams per deciliter.
However, the speaker aims for an optimal triglyceride level of less than 90 milligrams per deciliter, as studies indicate this range is associated with lower all-cause mortality risk.
In a study involving 4.5 million participants, the lowest coronary heart disease risk was associated with triglyceride levels below 45 milligrams per deciliter, which is the speaker’s long-term goal.
Over 20 years and 71 tests, the speaker has noted a trend of decreasing triglycerides, although recent data shows an upward trend that the speaker hopes to reverse through increased cardio activity.
The speaker reflects on dietary changes, including a brief period of veganism, and the impact of a low-fat diet on triglyceride levels.
LDL Levels and Long-Term Trends
The LDL (low-density lipoprotein) level for the recent test is noted at 86 milligrams per deciliter, which is below the reference range of 100 milligrams per deciliter.
The speaker discusses optimal LDL levels, citing studies that associate the lowest coronary heart disease risk with levels ranging from 65 to 120 milligrams per deciliter.
The speaker acknowledges the complexity of LDL trends, which typically follow an inverse U-shape across the lifespan, peaking in midlife before declining in older age.
Analysis of LDL data from 72 tests over 20 years reveals fluctuations that may relate to dietary changes made since 2015.
The speaker aims to stabilize LDL levels while avoiding age-related increases or decreases, with a long-term average of 82.5 milligrams per deciliter.
Lipoprotein A and Cardiovascular Risk
The speaker’s lipoprotein A level is reported at 91 nanomolar, which exceeds the reference range of 75 nanomolar, raising concerns about cardiovascular risk.
Optimal levels for lipoprotein A, associated with the lowest coronary artery disease risk, are considered to be below 48 nanomolar.
Historical data from 45 tests over 20 years shows a concerning average of 106 nanomolar for the first decade, indicating poor lipoprotein A levels.
The speaker cites a significant improvement in lipoprotein A levels over the past 10 years, achieving an average of 90 nanomolar through dietary changes.
The speaker notes the importance of high-sensitivity C-reactive protein (hsCRP) levels in modifying cardiovascular risk associated with lipoprotein A.
High-Sensitivity C-Reactive Protein and Its Impact
The speaker’s hsCRP level is reported as less than 0.2 milligrams per liter, indicating a low level of inflammation, which is favorable for cardiovascular health.
The speaker has consistently maintained hsCRP levels below the detection limit for 26 tests, suggesting effective management of inflammation over the years.
Despite a higher lipoprotein A level, low hsCRP may mitigate cardiovascular disease risk, particularly given the speaker’s family history of cardiovascular issues.
The relationship between lipoprotein A and cardiovascular disease risk remains complex, especially when factoring in hsCRP levels.
APO B Levels and Future Monitoring
APO B, a protein associated with various lipoproteins, is discussed, with a current level of 71 milligrams per deciliter, which is below the reference range of 90 milligrams per deciliter.
The speaker aims for an optimal APO B level of less than 70 milligrams per deciliter, which is associated with lower cardiovascular disease and all-cause mortality risk.
Over six tests, the speaker has achieved an average APO B level of 67 milligrams per deciliter, indicating that he is within the optimal range.
The speaker plans to continue monitoring APO B to gather more data and assess its relevance compared to other lipoprotein measures.
Conclusion and Future Directions
The video concludes with the acknowledgment that only a portion of the blood test report has been covered, encouraging viewers to seek further information available on Patreon.
The speaker plans to share details regarding the diet, supplements, and medications that correspond to the recent test results in future videos.
Viewers are invited to follow the speaker’s journey in biohacking aging and to access various resources, including affiliate links for testing services.
The speaker emphasizes the importance of understanding one’s health metrics in the context of aging and cardiovascular disease prevention.
Who’s Really Winning At Longevity? (Featuring Unaging Crissman Loomis)
AI Summary:
Here is the summary and analysis of the provided podcast transcript.
A. Executive Summary
This episode features a “Biomarker Throwdown” comparing the physiological data of three individuals: the guest Chrisman Loomis (55), longevity mogul Bryan Johnson (48), and biohacker Siim Land (31). Hosted by Michael, the discussion critiques the claim that extreme financial investment (Johnson’s $2M/year) is necessary for elite biomarkers. Loomis demonstrates that a low-cost, high-effort protocol (walking desk, minimal but heavy lifting) can rival or exceed the results of Johnson’s extensive supplement and medical regime.
Michael provides a rigorous technical analysis of the data, debunking the reliance on single-snapshot biological age clocks and emphasizing raw clinical chemistry (Albumin, RDW, Cystatin C). The analysis reveals potential red flags in Johnson’s data (kidney function, anemia risk) despite his “perfect” branding. The episode concludes with Loomis introducing the “2026 Unaging Challenge,” a free community initiative focused on increasing healthspan through measurable strength and step-count goals.
B. Bullet Summary
Context of Comparison: Comparing biomarkers across vast age gaps (31 vs 48 vs 55) is inherently flawed; the true metric is resistance to age-related decline, not absolute numbers against a younger control.
Strength & Function: Grip strength is a top-tier aging biomarker. While Siim Land (31) dominates absolute strength, maintaining functional range of motion (ROM) is critical to avoid “old person” mobility issues.
Bone Density (BMD): Loomis reversed osteopenia (pre-osteoporosis) through heavy lifting, proving age-related bone loss is reversible.
Kidney Function: Standard eGFR is useless for athletes due to Creatinine/muscle mass skew. Cystatin C is the superior metric. Data suggests Bryan Johnson has suboptimal kidney function (Cystatin C > 0.8) despite his protocol.
Immune Health: Total white blood cell count is insufficient; the lymphocyte breakdown (CD4/CD8 ratio) determines the “Immune Health Grade.”
Red Blood Cells: RDW (Red Cell Distribution Width) is the strongest predictor of mortality in the PhenoAge clock. MCV (size) tends to increase with age; optimal levels should remain lower/youthful.
Lipids & Steps: Loomis has an exceptionally high HDL (113 mg/dL) and ApoA1, attributed to 20,000+ daily steps, lifting, and moderate alcohol. Michael warns of a U-shaped mortality curve where extremely high HDL can indicate liver stress or dysfunction.
Cost vs. Outcome: Loomis achieves elite biomarkers with a $60 gym membership and bananas (potassium), challenging Johnson’s $170,000/month protocol involving 100+ pills.
Biological Clocks: Epigenetic clocks (DunedinPACE) are often weak predictors compared to clinical chemistry clocks (PhenoAge, GrimAge) which track actual organ function (Albumin, Creatinine, CRP).
Blood Pressure Hack: Increasing Potassium intake (approx. 4.7g+) is often three times more effective for lowering BP than sodium restriction alone.
The Unaging Challenge: A community initiative tracking V02 Max, HRV, and strength, aiming to extend average life expectancy by ~20 years through lifestyle modification.
D. Claims & Evidence Table
Claim
Evidence Provided
Assessment
Bryan Johnson has the “best biomarkers in the world.”
Comparison of kidney (Cystatin C), blood (Hemoglobin), and immune data against Loomis/Land.
Weak. Data reveals suboptimal kidney function, potential anemia risk, and lower immune markers compared to peers.
Walking increases HDL cholesterol.
Loomis correlates 20k steps/day with HDL of 113. Michael cites linear correlation data.
Strong. Mechanism exists, though alcohol consumption is a confounding variable in Loomis’s case.
eGFR is inaccurate for high-muscle individuals.
High muscle turnover increases Creatinine, artificially lowering eGFR.
Strong. Standard medical consensus; Cystatin C is the required corrective test.
Potassium lowers blood pressure effectively.
Michael/Chris discuss supplementing Potassium to balance sodium intake.
Strong. Well-supported by physiology (sodium-potassium pump dynamics).
Epigenetic Clocks are the gold standard.
Michael argues they are predictions of biomarkers, whereas PhenoAge uses the actual biomarkers.
Disputed. Michael argues for clinical chemistry (GrimAge/PhenoAge) over pure methylation clocks like DunedinPACE.
E. Actionable Insights
Switch Kidney Metrics: If you lift weights or have high muscle mass, ignore standard eGFR/Creatinine. Demand a Cystatin C test to accurately gauge kidney health (Target: <0.7 mg/L).
Standardize Testing Conditions: Do not train heavily 3–4 days before a blood draw. Exercise-induced inflammation acts as a confounding variable for liver enzymes (ALT/AST) and inflammatory markers (CRP).
Track RDW and MCV: These neglected markers on a CBC panel are powerful aging signals. Rising RDW and MCV indicate aging red blood cells and increased mortality risk.
Prioritize Potassium: To manage blood pressure, focus on increasing Potassium intake (bananas, supplements) to ~4,700mg/day rather than aggressively cutting sodium, provided kidneys are healthy.
Use Clinical “Clocks”: Don’t pay hundreds for epigenetic spit tests if you haven’t optimized the inputs of PhenoAge (Albumin, Glucose, CRP, RDW, etc.), which are available on cheap standard blood panels.
Walking Desk ROI: High-volume low-intensity walking (15k-20k steps) drives massive improvements in lipid profiles (HDL) and inflammation (CRP) without recovery cost.
H. Technical Deep-Dive
1. The “U-Shaped” Curve of HDL & Mortality
While high HDL is generally cardio-protective, the transcript highlights that values >90-100 mg/dL (like Loomis’s 113) can lose their protective status.
Mechanism: Extremely high HDL can be dysfunctional (large, buoyant particles that fail to efflux cholesterol). It is also strongly correlated with alcohol intake. In alcoholics, high HDL co-occurs with liver damage.
Analysis: Loomis must differentiate if his HDL is driven by aerobic volume (steps) or alcohol. Given his low liver enzymes (GGT) and high physical activity, it is likely functional, but the mortality risk plateau at >180 mg/dL ApoA1 suggests diminishing returns.
2. Kidney Function: The Creatinine vs. Cystatin C Delta
Creatinine: A waste product of creatine phosphate in muscle. High muscle mass = high creatinine = low calculated eGFR (false positive for kidney failure).
Cystatin C: A protein produced by all nucleated cells at a constant rate, filtered freely by the glomerulus. It is independent of muscle mass.
Observation: Bryan Johnson’s Cystatin C is 0.87 (suboptimal), and BUN (Blood Urea Nitrogen) is elevated. While high protein intake raises BUN, the combination with elevated Cystatin C suggests legitimate renal stress, potentially from his extensive supplement stack or aggressive protocols.
3. Red Blood Cell Aging (RDW & MCV)
RDW (Red Cell Distribution Width): Measures the variation in RBC volume. Higher variation implies a mix of healthy and unhealthy/dying cells. It is the single strongest weighting factor in the PhenoAge clock.
MCV (Mean Corpuscular Volume): RBCs tend to get larger (macrocytic) with age or B12/Folate deficiency.
Significance: Both Johnson and Loomis show elevations here. Keeping RDW <12% and MCV <90 fL helps minimize “biological age” scores.
I. Fact-Check Important Claims
Claim:High Protein intake causes high BUN.
Verdict:True. Urea is a byproduct of protein metabolism. However, elevated BUN alongside elevated Cystatin C (as seen in Johnson’s data) is more indicative of reduced filtration capacity than dietary intake alone.
Claim:Walking 20,000 steps creates linear HDL increase.
Verdict:Plausible/Supported. Aerobic activity increases Lipoprotein Lipase (LPL) activity, which catabolizes triglycerides and transfers constituents to HDL. However, genetics and alcohol play significant roles in reaching outliers like 113 mg/dL.
Verdict:Nuanced. The transcript claims the creators of DunedinPACE found no benefit from diet/exercise. Correction: Studies generally show DunedinPACE does respond to caloric restriction (CALERIE trial), though it may be less sensitive to short-term exercise changes than clinical markers. Michael prefers GrimAge/PhenoAge for mortality prediction.
Diet Composition that Corresponds To A 15y Younger Biological Age (Blood Test #7 In 2025 Analysis)
Gemini Pro AI Summary:
Here is the summary and analysis of the provided transcript detailing Blood Test #7 in 2025 and the associated dietary interventions.
A. Executive Summary
The video details the results of Blood Test #7 in 2025 following a 41-day specific dietary protocol (September 16 – October 26). The subject reports a PhenoAge biological age 15 years younger than their chronological age (52 years old). Despite this aggregate success, the speaker highlights critical failures in specific biomarker optimization attempts based on previous correlation data.
The core analysis focuses on three “weak spots”: DHEA Sulfate (DHEA-S), Mean Corpuscular Volume (MCV), and Lipoprotein(a). The speaker previously attempted to raise DHEA-S by increasing Omega-3 intake (sardines, flax, walnuts), lower MCV by reducing Brazil nuts, and lower Lipoprotein(a) by increasing monounsaturated fat (avocado). All three experiments failed: DHEA-S reached a four-year low (126 µg/dL), MCV reached a ten-year high (96 fL), and Lipoprotein(a) remained elevated.
The speaker employs a rigorous N=1 methodology involving weighing >99% of food intake, tracking via Cronometer, and calculating Pearson correlations between dietary components and blood biomarkers. Based on the failed experiments, the protocol for Test #8 involves new correlation-based adjustments: re-introducing salt and removing olives to target DHEA-S; reducing lycopene and adding cacao to lower MCV; and doubling chickpea intake to target Lipoprotein(a). The diet remains macronutrient-dense (2302 kcal/day, 39% fat, 22% protein), utilizing a “cheat meal” protocol immediately post-blood draw to mitigate psychological restriction fatigue.
B. Bullet Summary
Biological Age Discrepancy: The subject achieved a PhenoAge 15 years lower than chronological age, despite specific biomarker deterioration.
DHEA-S Decline: DHEA-S levels dropped to 126 µg/dL, significantly below the target of ~300 µg/dL (youth median), despite increased Omega-3 intake intended to boost it.
MCV Deterioration: Mean Corpuscular Volume increased to 96 fL (highest in 10 years), indicating larger, older red blood cells, despite reducing Brazil nut intake.
Lipoprotein(a) Stagnation: Lp(a) remained high at 80 nmol/L despite doubling avocado intake; the goal is to reduce this independent cardiovascular risk factor.
Correlation vs. Causation Failure: The speaker explicitly notes that following statistically significant correlations from previous data sets failed to produce the desired causal result for DHEA-S, MCV, and Lp(a) in this cycle.
Dietary Tracking Precision: Over 99% of food intake has been weighed and logged since 2015, creating a massive longitudinal dataset for personal correlation analysis.
Test #8 DHEA-S Strategy: The new protocol involves increasing added salt and decreasing olives, nutmeg, avocado, and celery based on fresh inverse correlations.
Test #8 MCV Strategy: The subject is reducing tomato intake (lycopene) and re-introducing cacao (10g/day) to attempt to lower red blood cell volume.
Test #8 Lp(a) Strategy: Chickpea intake is being doubled to ~80g/day based on a significant inverse correlation with Lp(a).
Macro Composition: The diet averaged 2302 kcal, 126g protein (22%), 101g fat (39%), and 185g net carbs (32%).
Saturated Fat Constraint: Saturated fat is kept low to manage Cystatin C and Beta-2 Microglobulin (B2M), which are key predictors of GrimAge.
Sodium & Blood Pressure: Sodium was increased to 2700mg/day to test effects on Norepinephrine/HRV, but this negatively impacted blood pressure; sodium will be reduced by 500mg for the next cycle.
Cheat Meal Protocol: A 3-day window of high-sugar/processed foods (Nutella, jelly, cookies) is utilized immediately post-test to prevent long-term binge behavior; the remaining 38 days were 100% “clean.”
Top Calorie Source: Sardines remain the primary caloric staple, consistent with the subject’s long-term pescatarian approach (9 years).
Fructose Management: Total fructose was ~50g/day, a reduction from previous highs, intended to manage general aging biomarkers, though future tests may increase fruit intake (strawberries).
Previous inverse correlation. Experiment: Doubled intake. Result: Lp(a) remained static/high.
Refuted (in N=1)
Sodium lowers Norepinephrine
Hypothesis stated based on literature; attempting to improve HRV/RHR. Result: Blood pressure worsened.
Mixed/Trade-off identified
Cheat days prevent binging
Personal anecdote: “Cold turkey” leads to uncontrolled binging; scheduled cheating maintains 98% compliance.
Subjective/Behavioral
Low Saturated Fat lowers Cystatin C/B2M
Longitudinal data shows low SatFat correlates with lower Cystatin C/B2M. Result: Biomarkers remained low.
Supported (in N=1)
E. Actionable Insights
Establish Baselines: Use tools like Cronometer to weigh and track food intake to generate a dataset capable of revealing personal correlations.
Iterative Testing: Do not assume a general health intervention (e.g., “eat more Brazil nuts”) applies to your specific biology. Test, measure, and pivot.
Correlation Causation: Be prepared for correlation-based interventions to fail. When they do, recalculate correlations and test the next statistically significant variable.
Target DHEA-S: Monitor DHEA-S as a marker of aging; if levels drop below 200-300 µg/dL, investigate adrenal function and dietary precursors, though Omega-3s may not be the lever.
Monitor MCV: As you age, watch for rising Mean Corpuscular Volume (>90 fL). This indicates larger red blood cells and potential issues with B12/Folate methylation or general membrane stiffness.
Scheduled “Refeeds”: If adherence is an issue, consider a structured 24-72 hour window of “cheat” meals immediately following a measurement event to reset psychological satiety signaling.
Sodium Titration: Monitor blood pressure response to sodium closely. Increases to improve HRV may come at the cost of hypertension.
Lp(a) Modulation: While largely genetic, test dietary fiber sources (specifically legumes/chickpeas) as potential modulators for Lipoprotein(a).
H. Technical Deep-Dive
1. DHEA Sulfate (DHEA-S) and Aging
DHEA-S is the sulfated form of Dehydroepiandrosterone, the most abundant steroid hormone in the human circulation. It functions as a reservoir for DHEA, which can be converted into androgens and estrogens (intracrinology).
Mechanism of Decline: DHEA-S production peaks in the 20s and declines by ~10% per decade (adrenopause). This is associated with sarcopenia, immunosenescence, and reduced neuroplasticity.
The Speaker’s Data: The sharp drop to 126 µg/dL suggests a potential suppression of the hypothalamic-pituitary-adrenal (HPA) axis or a diversion of pregnenolone (the precursor) toward cortisol (“pregnenolone steal”) due to stress or inflammation, rather than a lack of dietary fats.
2. Mean Corpuscular Volume (MCV)
MCV measures the average size of red blood cells.
Aging Context: MCV tends to increase with age. Macrocytosis (high MCV) is often linked to B12/Folate deficiency (megaloblastic anemia), hypothyroidism, or alcohol intake. However, in the context of longevity, rising MCV in the absence of deficiency may indicate altered erythropoiesis or changing membrane lipid composition.
Dietary Failure: The failure of reducing Brazil nuts (Selenium) suggests the issue is likely not Selenium toxicity. The shift toward testing Cacao (polyphenols/minerals) implies a search for anti-inflammatory or membrane-stabilizing agents.
3. Lipoprotein(a) [Lp(a)]
Lp(a) consists of an LDL-like particle bound to apolipoprotein(a).
Pathology: It is pro-thrombotic and pro-atherogenic. Unlike standard LDL, it is largely determined by the LPA gene (autosomal dominant inheritance).
Dietary Resistance: Standard lipid-lowering diets often fail to impact Lp(a). The speaker’s failure with Avocado (MUFA) aligns with clinical consensus that diet has minimal impact on Lp(a). Testing chickpeas (soluble fiber) attempts to sequester bile acids, forcing the liver to upregulate LDL receptors, though Lp(a) clearance pathways are distinct and less understood.
I. Fact-Check Important Claims
Claim:Sodium lowers Norepinephrine.
Consensus:Plausible. Sodium restriction stimulates the renin-angiotensin-aldosterone system (RAAS) and sympathetic nervous system (increasing norepinephrine) to maintain blood pressure. Conversely, adequate sodium can suppress this sympathetic drive. However, the trade-off is often increased blood volume and blood pressure in salt-sensitive individuals, which the speaker confirmed occurred.
Reference: Graudal, N. A., et al. (2012). Effects of low-sodium diet vs. high-sodium diet on blood pressure, renin, aldosterone, catecholamines, cholesterol, and triglyceride (Cochrane Review).
Claim:Nutmeg extends lifespan in animal models.
Consensus:Speculative. While macelignan (found in nutmeg) has shown potential antioxidant and anti-inflammatory properties, and some compounds improve metabolic parameters in rodents, robust data supporting lifespan extension in mammals is limited compared to established interventions like Rapamycin or Caloric Restriction.
Context: High doses of nutmeg are hepatotoxic and neurotoxic (myristicin).
Claim:DHEA-S median in youth is 300 µg/dL.
Consensus:True. Reference ranges for men aged 20-29 typically span 280 to 640 µg/dL. 300 µg/dL is a reasonable median target for maintaining a “youthful” profile.
This analysis investigates the role of Beta-Hydroxybutyrate (BHB)—a ketone body—as a central signaling molecule in longevity and healthspan. The core thesis posits that BHB is not merely an alternative fuel source but a critical mediator of the lifespan-extending effects observed in Calorie Restriction (CR) and Ketogenic Diets (KD).
The speaker presents data from mouse models (specifically Roberts et al. and Newman et al.) demonstrating that both CR and KD significantly increase circulating BHB and extend median lifespan (surpassing the “900-day rule” benchmark for murine longevity). Crucially, the analysis highlights a mechanistic dependency: the longevity benefits of CR appear to require intact glucagon signaling, which drives BHB production.
Translating this to humans, the speaker explores the optimal “fasting window” required to spike BHB. While mice see BHB peaks after 12–20 hours of fasting, the speaker’s n=1 self-experimentation suggests that a similar window (16–20 hours) coupled with specific fat intake (avoiding high saturated fat to prevent glucose spikes) is necessary to achieve therapeutic BHB levels (>0.4 mM) without inducing physiological insulin resistance. The presentation concludes with emerging speculation that BHB spikes during sleep may enhance glymphatic clearance, potentially slowing brain aging.
B. Bullet Summary
BHB Structure: BHB is a ketone body synthesized from fatty acids, containing a hydroxyl group at the beta position.
Longevity Link: Elevated BHB is a shared biomarker in two proven lifespan-extending interventions in mice: Calorie Restriction (CR) and Ketogenic Diets (KD).
Mouse Data (Keto): Ketogenic-fed mice (89% fat) showed ~2-fold higher BHB and extended median lifespan to ~1000 days, beating the 900-day control benchmark.
Mouse Data (CR): Calorie-restricted mice also exhibit ~2-fold higher BHB levels compared to ad-libitum fed controls.
Causality (Glucagon): Glucagon signaling is required for BHB production. Glucagon receptor knockout mice do not derive healthspan benefits from CR, suggesting the Glucagon→BHB pathway is essential.
Fasting Dynamics: In CR mice, BHB levels remain low (2mM) for the first 8 hours post-feeding, peaking (6-7mM) at 16 hours fasting.
Translational Gap: Mice metabolism is faster; the 12-20 hour murine fasting window requires careful calibration to translate to human circadian biology.
Self-Experimentation: The speaker targets a 16–20 hour daily fast to elevate BHB from baseline (0.2mM) to therapeutic levels (>0.4mM).
Dietary Composition: High saturated fat intake in the speaker caused elevated glucose (Physiological Insulin Resistance), prompting a switch to MUFA/PUFA (walnuts) to raise BHB without spiking glucose.
Emerging Hypothesis: Elevated BHB during sleep may optimize the glymphatic system (brain waste clearance), theoretically reducing neurodegenerative risk.
Biomarker Context: Raising BHB should not come at the cost of worsening other markers (e.g., ApoB, triglycerides, liver enzymes).
Measurement: Capillary ketone meters are used for tracking, though their accuracy compared to venipuncture is variable.
D. Claims & Evidence Table (Adversarial Peer Review)
Role: rigorous Longevity Scientist. Standard: Human outcomes > Mechanistic speculation.
Claim from Video
Speaker’s Evidence
Scientific Reality (Best Available Data)
Evidence Grade
Verdict
“BHB reduces inflammation & oxidative stress”
General assertion
Mechanistically strong (NLRP3 inhibition). Human trials show mixed results; some show anti-inflammatory effects in T2D, others show acute BHB increases inflammation markers in healthy adults.
C/D (Mechanistic/Mixed Human)
Plausible (Context Dependent)
“Ketogenic Diet extends lifespan”
Cites Roberts et al. (Mice)
Confirmed in mice (Roberts 2017, Newman 2017) reducing midlife mortality. No human RCTs verify longevity extension. Long-term Keto safety in humans is debated (lipid risks).
D (Mouse Only)
Translational Gap
“Glucagon signaling is required for CR benefits”
Cites Glucagon Receptor KO study
Confirmed in mice (Ren et al.). Glucagon receptor signaling is indispensable for the metabolic health effects of CR in aging mice.
D (Mouse Only)
Strong Pre-clinical Support
“Fasting 12–20h raises BHB significantly”
Mouse data & n=1 Human data
Human physiology confirms nutritional ketosis typically begins >12-16h fasting. Levels of 0.2–0.5 mM are standard for this window.
B (Human Physiology)
Strong Support
“High Saturated Fat increases Glucose”
n=1 Self-Experiment
Known phenomenon: “Physiological Insulin Resistance” or “Adaptive Glucose Sparing.” High FFA levels can inhibit glucose uptake in muscle to spare it for the brain.
B (Physiological Mechanism)
Verified Phenomenon
“BHB improves Glymphatic Clearance”
Cites “Emerging Data”
Highly speculative. Sleep drives glymphatic clearance (proven), but the specific role of BHB as a driver is not yet established in human trials.
E (Speculative)
Experimental
E. Actionable Insights (Pragmatic & Prioritized)
Top Tier (High Confidence)
Time-Restricted Feeding (16:8): To replicate the BHB elevation seen in longevity models, a fasting window of 16–18 hours is the minimum effective dose for humans to enter nutritional ketosis (BHB > 0.3-0.5 mM).
Monitor “Physiological Insulin Resistance”: If utilizing a high-fat/low-carb diet, rigorously track HbA1c and Fasting Glucose. If glucose rises despite low carb intake, reduce Saturated Fat and replace with Monounsaturated Fats (Olive Oil, Avocado) or Polyunsaturated Fats (Walnuts/Omega-3).
Experimental (Risk/Reward)
The “BHB-Sleep” Protocol: Attempt to align the peak of the fasting window with sleep to theoretically maximize glymphatic clearance. Protocol: Stop eating 4–6 hours before bed. This ensures the overnight period coincides with the start of ketogenesis.
Targeted Ketosis without “Keto”: Use a moderate fat, high fiber diet with compressed eating windows (e.g., 20h fast) to pulse BHB levels daily without the long-term restrictive burden (and potential lipid issues) of a permanent ketogenic diet.
Avoid (Safety Risks)
“Dirty Keto” for Longevity: Do not chase BHB numbers by consuming unlimited saturated fats (butter/bacon) if it negatively impacts ApoB or Fasting Glucose. The speaker emphasizes that biomarker context matters more than a single metric.
H. Technical Deep-Dive: The Glucagon-Lifespan Axis
The transcript touches on a sophisticated mechanism often overlooked in pop-science: the Glucagon-Autophagy-BHB Axis.
The Mechanism:
During fasting (CR), insulin drops and Glucagon rises.
Glucagon binds to the hepatic GCGR (Glucagon Receptor).
This activates cAMP/PKA signaling pathways.
Downstream Effect 1: Activation of HMGCS2, the rate-limiting enzyme for ketogenesis (producing BHB).
Downstream Effect 2: Stimulation of Autophagy (cellular cleanup) independent of insulin.
The Critical Finding:
The speaker references data (likely Ren et al.) showing that GCGR-/- (Knockout) mice on Calorie Restriction failed to see lifespan extension.
Implication: It is not just “eating less” that extends life; it is the metabolic stress signal (mediated by Glucagon) that triggers repair mechanisms. If you block the signal (Glucagon), you block the benefit.
Human Translation:
This suggests that “snacking” or eating frequencies that perpetually suppress Glucagon (even in a caloric deficit) might blunt the longevity benefits of CR. Fasting duration matters because it is the primary driver of the Glucagon spike.
I. Fact-Check: The “900-Day Rule”
Claim: Control mice must live median ~900 days for a longevity study to be valid.
Verification:Accurate. In high-quality mouse longevity research (e.g., the Interventions Testing Program - ITP), C57BL/6 or HET3 control mice typically have median lifespans of 850–900 days.
Why it matters: Many poor-quality studies use “short-lived” control strains (due to stress, poor housing, or genetic drift) that die at 600–700 days. If a supplement extends their life to 800 days, it looks like a miracle, but it actually just restored them to “normal.” The speaker correctly identifies that true longevity agents must push past the 900-day biological ceiling.
