LEVELS – A Whole New Level

Heart disease is the leading cause of death, but it’s also one of the most preventable. Decades of research have established a strong causal role for LDL and other ApoB-containing particles in atherosclerosis, and we now have multiple proven ways to lower them. The harder question is how to turn that evidence into a decision for an individual person.

Mike Haney talks with Johns Hopkins cardiologist Dr. Seth Martin, a co-author of the new 2026 dyslipidemia guidelines, about what the latest evidence says we should actually measure and act on. The throughline is pragmatic: lower exposure to atherogenic particles earlier and for longer, use additional tests when they can change a decision, and distinguish interesting new measurements from ones that have actually been shown to improve outcomes.

Free course: Improve your metabolic health

Get our free email course on how glucose, nutrition, exercise, sleep, and measurement can help you build habits that support better energy and long-term health: ⁠https://levels.link/wnl

What We Cover:

• Why the evidence that LDL and ApoB-containing particles cause atherosclerosis is so strong
• What “lower for longer” means and how the new LDL and ApoB goals change with cardiovascular risk
• When ApoB adds useful information beyond a standard lipid panel
• Why the guidelines recommend against routine LDL particle-size testing
• How PREVENT risk scores and coronary calcium scans can help decide when treatment makes sense
• What decades of statin research tell us about benefits, muscle symptoms, and diabetes risk
• How much lifestyle changes typically move cholesterol, and when non-statin drugs enter the picture
• Why common heart-health supplements don’t have the evidence behind proven lipid-lowering therapies

🎙️ About the Guest:

Dr. Seth Martin is a professor of medicine and preventive cardiologist at Johns Hopkins, where he directs the Advanced Lipid Disorders Program and Digital Health and AI Lab at the Ciccarone Center for the Prevention of Cardiovascular Disease. He is a co-developer of the widely used Martin-Hopkins LDL cholesterol equation and served on the writing committee for the 2026 ACC/AHA dyslipidemia guideline.

📍What Dr. Seth Martin & Mike Haney discussed:

• 00:04 - LDL and ApoB are causal. Lower for longer
• 07:10 - Guidelines set the standard. Not your doctor
• 11:40 - 2026 shift: earlier treatment, PREVENT, lower goals
• 17:01 - LDL near zero does not eliminate cholesterol
• 19:59 - Hard numbers are back, and lower
• 23:05 - ApoB if a high result changes treatment
• 27:42 - No trial says treat particle size instead of LDL
• 34:51 - PREVENT is for people not already high risk
• 38:52 - Calcium 300 can push the goals. Zero can mean lifestyle first
• 44:29 - The 3% statin line, and the choice just under it
• 51:22 - Muscle symptoms uncommon. Statin can move prediabetes diagnosis earlier
• 56:21 - Lifestyle often lowers LDL about 10%, not the whole benefit
• 59:05 - Other proven drugs when a statin is not enough
• 1:05:31 - Statin beat the supplements. Fish oil can raise AFib risk

🔗 Helpful Links:

• 2026 Guideline on the Management of Dyslipidemia: ⁠Read the guideline and supporting materials⁠
• The New Cholesterol Guideline: What to Know — Johns Hopkins: Read the Johns Hopkins summary
• PREVENT-ASCVD Calculator.: ⁠Use the PREVENT calculator⁠
• Martin-Hopkins LDL Equation: Learn about the Martin-Hopkins method
• SPORT Trial — JACC (2022): Read the SPORT trial

Watch the conversation: https://youtu.be/vRfhof5dOZw

Find us on YouTube: ⁠https://youtube.com/levelshealth?sub_confirmation=1⁠

👋 Who we are:

Levels helps you understand your metabolic health with personalized data, expert guidance, and tools that connect your daily choices to measurable changes in your body. Our goal is to help you make better decisions about food, exercise, sleep, and long-term health.

Look for new shows every month on A Whole New Level, where we have in-depth conversations with thought leaders about metabolic health.

Most of NextLevel starts with a measurement problem: we can see more biology than ever, but we still have to figure out what to do with it. Bioelectronic medicine flips that sequence. We already know how to send electrical signals into the nervous system to change biology, including an FDA-approved vagus nerve treatment for rheumatoid arthritis, even though we still can’t map or read most of the individual nerve fibers carrying those signals.

Mike Haney talks with Dr. Kevin Tracey, a pioneer of neuroimmunology and bioelectronic medicine, about what becomes possible when nerves become a therapeutic target. The opportunity is not simply vagus nerve stimulation, but learning which signals control specific organs, then building systems that can read and write them. That is still some distance away, and Tracey separates it from looser claims about vagal tone and vagus nerve hacks.

Free course: Improve your metabolic health

Get our free email course on how glucose, nutrition, exercise, sleep, and measurement can help you build habits that support better energy and long-term health: https://levels.link/wnl

What We Cover:

• Why the vagus nerve is not one wire
• How one minute a day became an FDA-approved rheumatoid arthritis treatment
• Why a nerve target can be more precise than a drug
• Why mapping the vagus fiber by fiber is only beginning
• Why CRP and cytokines are not a true inflammation readout
• What HRV, breathing, humming, and cold plunges can and cannot show

🎙️ About the Guest:

Dr. Kevin Tracey is a neurosurgeon, scientist, and President and CEO of the Feinstein Institutes for Medical Research. His work helped establish how the vagus nerve regulates inflammation and helped launch bioelectronic medicine. He is also co-founder of SetPoint Medical and author of The Great Nerve.

📍What Dr. Kevin Tracey & Mike Haney discussed:

• 00:00 - A nerve can treat one organ. A pill cannot
• 04:43 - The vagus nerve is 160,000 fibers, not one wire
• 07:53 - Why the first fiber-by-fiber map of the human vagus is only months old
• 10:29 - FDA-approved vagus nerve stimulation for rheumatoid arthritis
• 14:33 - Why one minute a day can quiet inflammation for 12 to 24 hours
• 17:39 - Why it took 30 years to get from the mouse finding to patients
• 31:53 - How one minute of current reaches millions of immune cells
• 41:19 - Why arthritis has a known mechanism and epilepsy and depression do not
• 49:16 - What single fibers could change in diabetes, the liver, the gut, and stroke recovery
• 52:59 - Why CRP and cytokine levels still fall short of a true readout
• 1:04:18 - Resting heart rate, not HRV, is the cleaner vagus signal
• 1:09:55 - Why deep breathing and humming are not vagus nerve stimulation
• 1:16:35 - A cold plunge is fight-or-flight first, vagus second
• 1:20:23 - The spleen signal he would measure if he could

🔗 Helpful Links:

• The Great Nerve - Kevin J. Tracey (2025)
• RESET-RA - Nature Medicine
• SetPoint System - FDA
• The inflammatory reflex - Nature (2002)
• Vagus nerve stimulation in rheumatoid arthritis - PNAS (2016), early human study
• Vagus nerve stimulation after stroke, paired with rehab - The Lancet (2021)

Watch the conversation: https://youtu.be/x_h6Dd_Ap_o

Find us on YouTube: https://youtube.com/levelshealth?sub_confirmation=1

📲 Connect:

Connect with Dr. Kevin Tracey at Feinstein Institutes for Medical Research

👋 Who we are:

Levels helps you understand your metabolic health with personalized data, expert guidance, and tools that connect your daily choices to measurable changes in your body. Our goal is to help you make better decisions about food, exercise, sleep, and long-term health.

Look for new shows every month on A Whole New Level, where we have in-depth conversations with thought leaders about metabolic health.

Most health decisions happen before the science is settled. A study points one way, another points somewhere else, experts disagree about what matters, and even strong population-level evidence may not tell you what will happen to you.

In this episode, Mike Haney talks with physician and economist Dr. Anupam Jena about how to make decisions under that kind of uncertainty. The goal isn’t to find a single hierarchy of evidence or a perfect source to trust. It’s to understand how much weight to put on any one piece of information, when personal experimentation can actually teach you something, and how the potential downside of an intervention should change the amount of evidence you demand before trying it.

Free course: Improve your metabolic health

Get our free email course on how glucose, nutrition, exercise, sleep, and measurement can help you build habits that support better energy and long-term health: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://levels.link/wnl⁠

What We Cover:

• Why even a high-quality study should rarely change your mind by itself
• Why a meta-analysis is only as useful as the studies that go into it
• What randomized trials can establish, and where they can still fail to apply to real life
• How to judge whether a study’s outcome is actually meaningful, not merely statistically significant
• When N-of-1 experiments can help, and how they can fool you
• A practical framework for deciding whether an intervention is worth trying: potential harm, quality of evidence, biological plausibility, and cost

🎙️ About the Guest:

Dr. Anupam Jena is the Joseph P. Newhouse Professor of Health Care Policy at Harvard Medical School, a physician at Massachusetts General Hospital, and an economist whose research uses natural experiments to uncover unexpected influences on health and medical care. He is also the host of Freakonomics, M.D. and co-author of Random Acts of Medicine.

📍What Dr. Anupam Jena & Mike Haney discussed:

• 04:04 - Why taxi and ambulance drivers die least often of Alzheimer's
• 09:20 - Why half of people still skip a free heart medication
• 13:02 - Why the headlines on coffee keep reversing
• 14:55 - Judge the study on its merits, not on who funded it
• 17:43 - Why even a high-quality study should rarely change your mind
• 23:04 - Why a cold plunge trial cannot separate the bath from the belief
• 26:19 - Why a meta-analysis is only as useful as the studies inside it
• 27:15 - What a randomized trial can establish, and where it still fails in real life
• 33:53 - The coin-flip test for whether a study shows cause and effect
• 36:25 - Absolute risk, relative risk, and what "significant" leaves out
• 43:06 - When an N-of-1 experiment can teach you what a trial cannot
• 46:02 - Getting better does not mean the experiment worked
• 53:55 - Harm, evidence, plausibility, cost: is it worth trying?

🔗 Helpful Links:

• Dr. Anupam Jena — Harvard Medical School profile
• Random Acts of Medicine — Anupam B. Jena & Christopher Worsham
• Freakonomics, M.D. https://freakonomics.com/series/bapu
• Alzheimer’s mortality among taxi and ambulance drivers (BMJ, 2024). Hypothesis-generating, not evidence that driving prevents Alzheimer’s: Read the BMJ study
• Marathon road closures and cardiac mortality (NEJM, 2017): New England Journal of Medicine

Watch the conversation: https://youtu.be/k9XI7ym7iP8

Find us on YouTube: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://youtube.com/levelshealth?sub_confirmation=1⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

📲 Connect:

Connect with Dr. Anupam Jena on https://x.com/AnupamBJena

👋 Who we are:

Levels helps you understand your metabolic health with personalized data, expert guidance, and tools that connect your daily choices to measurable changes in your body. Our goal is to help you make better decisions about food, exercise, sleep, and long-term health.

Look for new shows every month on A Whole New Level, where we have in-depth conversations with thought leaders about metabolic health.

Most medical imaging happens after a symptom, injury, or abnormal test gives a clinician a reason to look. But what changes if imaging becomes a more routine measurement, creating a record of the body before something goes wrong?

In this episode of Next Level, Mike Haney talks with Dr. Daniel Durand, chief medical officer at Prenuvo, about whole-body MRI as a test case for a broader shift from episodic medicine toward longitudinal health data. Whole-body MRI is controversial, and Durand is clearly an advocate. The conversation takes the skepticism seriously, then asks a larger question: as measurement gets cheaper, more frequent, and increasingly visible to patients themselves, how should medicine decide what is worth knowing?

Free course: Improve your metabolic health

Get our free email course on how glucose, nutrition, exercise, sleep, and measurement can help you build habits that support better energy and long-term health: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://levels.link/wnl⁠

What We Cover:

• How X-rays, CT scans, ultrasound, and MRI differ, and why radiation matters when you start thinking about repeated imaging
• What whole-body MRI sees well, and where CT, colonoscopy, or blood-based approaches may still be better
• The concerns around incidental findings, overdiagnosis, anxiety, and unnecessary follow-up, and Durand’s response to them
• What the current cancer-detection evidence for whole-body MRI does, and does not, establish
• Why having prior scans could help distinguish a stable abnormality from something genuinely new
• How faster scans and AI interpretation could eventually connect imaging with genomic, proteomic, and other health data

🎙️ About the Guest:

Dr. Daniel Durand is chief medical officer at Prenuvo and president of the Prenuvo Medical Group. He trained at Johns Hopkins, is board-certified in adult and pediatric radiology, and previously served as chief clinical officer and chief innovation officer at LifeBridge Health.

📍What Dr. Daniel Durand & Mike Haney discussed:

• 03:32 - Why imaging belongs in a series about continuous measurement
• 15:32 - Imaging 101: X-rays, CT, ultrasound, and MRI
• 28:57 - How AI is shortening MRI scan times
• 38:52 - Screening versus surveillance
• 40:26 - Which cancers whole-body MRI can miss
• 46:39 - The case against scanning healthy people
• 52:40 - What the cancer-detection data actually shows
• 54:39 - "We're all going to get a body scan"
• 1:03:31 - What would make routine imaging more useful?
• 1:11:49 - Building a baseline of the healthy body
• 1:17:43 - When AI can see more than a radiologist
• 1:21:28 - Is it better to know, even when you can't treat it?

🔗 Helpful Links:

• Dr. Daniel Durand, Prenuvo: Prenuvo medical leadership
• Meta-analysis behind the ~9,000 participants and ~1.6% detection figures. It notes limits, including incidental findings (European Radiology, 2026): PubMed
• Prenuvo-associated study of 1,011 people, 2.2% confirmed cancer detection (Cancer Research/AACR, 2025): AACR abstract
• Incidental findings in whole-body MRI and their psychosocial effects (European Journal of Radiology, 2021): PubMed
• Prenuvo's research overview, including Polaris data (company-reported): Prenuvo clinical research

Watch the conversation: https://youtu.be/rFZVbzUPSaA

Find us on YouTube: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://youtube.com/levelshealth?sub_confirmation=1⁠⁠⁠⁠⁠⁠⁠⁠⁠

📲 Connect:

Connect with Dr. Daniel Durand at LinkedIn

👋 Who we are:

Levels helps you understand your metabolic health with personalized data, expert guidance, and tools that connect your daily choices to measurable changes in your body. Our goal is to help you make better decisions about food, exercise, sleep, and long-term health.

Look for new shows every month on A Whole New Level, where we have in-depth conversations with thought leaders about metabolic health.

Alcohol has spent the last 40 years bouncing between two health narratives: a little is good for your heart, or any amount is dangerous. The science doesn’t really support either slogan.

Dr. Tim Naimi has spent decades studying the health effects of alcohol and, just as importantly, why the research is so difficult to interpret. His read of the evidence is less dramatic but more useful: there’s no good reason to start drinking for your health, very low intake may carry little measurable added risk, and risk rises as consumption does. Understanding why earlier studies made moderate drinking look protective helps explain a lot of the whiplashing headlines.

Free course: Improve your metabolic health

Get our free email course on how glucose, nutrition, exercise, sleep, and measurement can help you build habits that support better energy and long-term health: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://levels.link/wnl⁠

What We Cover:

• Why alcohol is a Group 1 carcinogen causally linked to at least seven cancers
• Whether small amounts of alcohol really protect your heart
• Why researchers still don’t have a definitive randomized trial of drinking and long-term health
• How the “sick quitter” problem, selection bias, and confounding made moderate drinkers look healthier
• Why two major recent reviews of alcohol and health produced such different headlines
• How the risk changes with dose, including Naimi’s estimate of a 1 in 25 lifetime risk of an alcohol-caused death at 14 drinks per week
• Why alcohol consumption is falling, and whether GLP-1 drugs could be contributing

🎙️ About the Guest:

Dr. Tim Naimi is a physician and alcohol epidemiologist who directs the Canadian Institute for Substance Use Research at the University of Victoria, where he is a professor in the Division of Medical Sciences.

📍What Dr. Tim Naimi & Mike Haney discussed:

• 00:45 — Why the science on alcohol is so confusing
• 05:48 — How alcohol damages DNA and raises cancer risk
• 09:43 — Is alcohol actually good for your heart?
• 14:22 — Why we still don't have a definitive randomized trial
• 20:30 — The "sick quitter" problem
• 24:56 — Selection bias and the problem with "healthy" moderate drinkers
• 29:35 — Why two major reports produced different headlines
• 31:37 — How alcohol risk changes as drinks per week increase
• 38:21 — Industry funding and conflicts of interest
• 46:15 — How much alcohol is too much?
• 49:48 — Why younger generations are drinking less
• 51:53 — Health consciousness, GLP-1s, and the decline in drinking

🔗 Helpful Links:

• Alcohol Intake and Health Study: No Protective Effect at Low Levels, With Mortality Increasing to 1 in 25 at 14 Drinks Per Week (Journal of Studies on Alcohol and Drugs, 2026) Paper
• Review of Evidence on Alcohol and Health (National Academies of Sciences, Engineering, and Medicine, 2025) Report
• Association Between Daily Alcohol Intake and Risk of All-Cause Mortality: A Systematic Review and Meta-analyses (JAMA Network Open, 2023) Paper
• Do “Moderate” Drinkers Have Reduced Mortality Risk? (Journal of Studies on Alcohol and Drugs, 2016) Paper
• Alcohol Abstinence in Drinkers with Atrial Fibrillation (New England Journal of Medicine, 2020) Paper
• Canada’s Guidance on Alcohol and Health (2023) Guidance and supporting research
• Alcohol and Cancer (World Health Organization / IARC) WHO overview

Watch the conversation: https://youtu.be/8GNmcjPfg7U

Find us on YouTube: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://youtube.com/levelshealth?sub_confirmation=1⁠⁠⁠⁠⁠⁠⁠⁠

📲 Connect:

Connect with Dr. Tim Naimi at University of Victoria

👋 Who we are:

Levels helps you understand your metabolic health with personalized data, expert guidance, and tools that connect your daily choices to measurable changes in your body. Our goal is to help you make better decisions about food, exercise, sleep, and long-term health.

Look for new shows every month on A Whole New Level, where we have in-depth conversations with thought leaders about metabolic health.

From a single blood sample, new proteomic tools can now measure thousands of proteins at once. Dr. Tony Wyss-Coray’s lab is using that flood of data, together with machine learning, to build a much higher-resolution picture of what’s happening throughout the body and where someone’s health may be headed.

The early signals are striking. In one analysis of people who appeared healthy by conventional measures, every additional 4.1 years of estimated heart age was associated with nearly 2.5 times the risk of heart failure over the following 15 years. Wyss-Coray sees this kind of measurement eventually becoming a “health compass”: something that could show which parts of the body are changing fastest, then help track whether an intervention is actually moving them in the right direction.

Free course: Improve your metabolic health

Get our free email course on how glucose, nutrition, exercise, sleep, and measurement can help you build habits that support better energy and long-term health: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://levels.link/wnl⁠

What We Cover:

• How a drop of blood can now reveal information from thousands of proteins
• Why aging appears to happen in waves rather than at a steady rate
• Why one part of the body may age faster than the rest
• What young-blood experiments in mice taught Wyss-Coray about proteins and brain aging
• How the work is moving from whole organs down to individual cell types
• Why the field’s biggest constraint may now be data collection rather than better AI

🎙️ About the Guest:

Dr. Tony Wyss-Coray is the D.H. Chen Distinguished Professor of Neurology and Neurological Sciences at Stanford University and director of the Phil and Penny Knight Initiative for Brain Resilience.

📍What Dr. Tony Wyss-Coray & Mike Haney discussed:

• 04:03 Proteins 101: the building blocks hiding information about your health
• 05:09 How one blood sample can measure thousands of proteins
• 09:07 Using machine learning to find patterns in the proteome
• 12:17 Can blood reveal what’s happening inside the brain?
• 13:11 What happened when young blood was given to old mice
• 19:45 Why aging may happen in waves rather than at a steady rate
• 29:24 How stable are protein measurements over time?
• 32:37 Can proteins predict disease years before it appears?
• 40:35 Why one part of your body may age faster than the rest
• 46:31 The missing test: does an intervention actually change the measurement?
• 51:04 Going from whole organs to individual cell types
• 54:10 Why more data, not better AI, is the current bottleneck
• 57:18 A future “health compass” for the body

🔗 Helpful Links:

• Organ aging signatures in the plasma proteome track health and disease (Nature, 2023)Paper
  The foundational organ-aging work discussed in the episode, using plasma proteins to estimate aging across 11 organs.
• Plasma proteomic signatures of cellular aging predict human disease (Nature Medicine, 2026)Paper
  The newer study extending the approach to more than 40 cell types using over 7,000 plasma proteins.
• Undulating changes in human plasma proteome profiles across the lifespan (Nature Medicine, 2019)Paper
  
• Young blood reverses age-related impairments in cognitive function and synaptic plasticity in mice (Nature Medicine, 2014)Paper
  

• UK Biobank Research resource
  The large longitudinal cohort used for much of the disease-prediction work discussed in the episode.

Watch the conversation: https://youtu.be/1dfMBAZiP8o

Find us on YouTube: ⁠⁠⁠⁠⁠⁠⁠⁠⁠https://youtube.com/levelshealth?sub_confirmation=1⁠⁠⁠⁠⁠⁠⁠⁠

📲 Connect:

Connect with Dr. Tony Wyss-Coray at Stanford

👋 Who we are:

Levels helps you understand your metabolic health with personalized data, expert guidance, and tools that connect your daily choices to measurable changes in your body. Our goal is to help you make better decisions about food, exercise, sleep, and long-term health.

Look for new shows every month on A Whole New Level, where we have in-depth conversations with thought leaders about metabolic health.

Aging science has gotten much better at describing who appears to be aging faster or slower. What medicine still lacks is a reliable feedback loop: a way to tell whether something we do is actually changing the biology that drives age-related disease.

Dr. Nir Barzilai argues that solving that measurement problem could turn geroscience from an interesting field of research into something doctors can actually use: measure where you are, intervene, measure again, and learn what works.

Free course: Improve your metabolic health

Get our free email course on how glucose, nutrition, exercise, sleep, and measurement can help you build habits that support better energy and long-term health: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://levels.link/wnl⁠

What We Cover:

• What centenarians reveal about living longer and spending less time sick
• Why changing one hallmark of aging can affect several others
• How TAME was designed to test metformin as an anti-aging drug and to convince the FDA to treat aging itself as an endpoint—and why it failed to get off the ground
• Why metformin, SGLT2 inhibitors, GLP-1 agonists, and some osteoporosis drugs are being studied as potential gerotherapeutics, or anti-aging drugs
• How FAST is searching existing clinical trials for biomarkers that change when an intervention affects aging biology
• Whether aging needs continuous monitoring or can be meaningfully tracked a few times a year

🎙️ About the Guest:

Dr. Nir Barzilai is the Ingeborg and Ira Leon Rennert Chair in Aging Research and a professor of medicine and genetics at Albert Einstein College of Medicine, where he directs the Institute for Geroscience.

📍What Dr. Nil Barzilai & Mike Haney discussed:

• 05:10 - Aging is a condition, not just a label
• 05:59 - Why aging is what drives disease
• 08:19 - Should we call aging a disease?
• 10:20 - Why the species may have a ceiling around 115
• 14:34 - Why changing one hallmark of aging changes the others
• 23:08 - Metformin was anti-aging before it was a diabetes drug
• 31:55 - Centenarians live longer and spend less time sick
• 40:12 - How TAME tried to make aging an FDA endpoint
• 48:17 - Metformin, SGLT2s, GLP-1s, and osteoporosis drugs as gerotherapeutics
• 52:26 - FAST: finding biomarkers that actually change with treatment
• 56:49 - Whether aging needs continuous monitoring, or a few checks a year
• 1:01:16 - Where behavior still fits once we have anti-aging drugs

🔗 Helpful Links:

• Hallmarks of Aging: An Expanding Universe (Cell, 2023) Paper
• Compression of Morbidity Is Observed Across Cohorts with Exceptional Longevity (JAGS, 2016) Paper
• Metformin as a Tool to Target Aging (Cell Metabolism, 2016) Paper
• Geroscience-Guided Repurposing of FDA-Approved Drugs to Target Aging (Aging Cell, 2022) Paper
• Biomarkers of Aging for the Identification and Evaluation of Longevity Interventions (Cell, 2023) Paper
• FAST: Finding Aging Biomarkers by Searching Existing Trials FAST Initiative
• ARPA-H PROSPR / FAST award ARPA-H FAST project

Watch the conversation: https://youtu.be/HbeGjwCw6vk

Find us on YouTube: ⁠⁠⁠⁠⁠⁠⁠⁠https://youtube.com/levelshealth?sub_confirmation=1⁠⁠⁠⁠⁠⁠⁠

📲 Connect:

Connect with Dr. Nil Barzilai on X: https://x.com/NirBarzilaiMD

👋 Who we are:

Levels helps you understand your metabolic health with personalized data, expert guidance, and tools that connect your daily choices to measurable changes in your body. Our goal is to help you make better decisions about food, exercise, sleep, and long-term health.

Look for new shows every month on A Whole New Level, where we have in-depth conversations with thought leaders about metabolic health.

Medical AI is already getting good at doing things doctors do. Dr. Ziad Obermeyer thinks the bigger opportunity is using AI to discover things medicine doesn’t yet know.

His work shows both sides of that future: algorithms can amplify bad assumptions when trained on the wrong targets, but they can also uncover signals in medical data that humans miss. Obermeyer argues that as more health data is collected outside the hospital, AI could turn it into a continuous picture of health rather than a series of isolated snapshots.

Free course: Improve your metabolic health

Get our free email course on how glucose, nutrition, exercise, sleep, and measurement can help you build habits that support better energy and long-term health: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://levels.link/wnl⁠

What We Cover:

• Why AI should learn from patients and outcomes, not just doctors
• How an ECG model found hidden risk of sudden cardiac death
• Why medical data access is still a major bottleneck
• How more measurement could actually mean fewer unnecessary tests
• Why healthcare may be entering a “mainframe to PC” transition

🎙️ About the Guest:

Dr. Ziad Obermeyer is an emergency medicine physician and an Associate Professor at the UC Berkeley School of Public Health. He also co-founded Dandelion Health and the non-profit Nightingale Open Science.

📍What Dr. Ziad Obermeyer & Mike Haney discussed:

• 02:43 Why better data is fundamental to medical AI
• 05:54 The problem: There’s no variable called “get sick”
• 09:27 Algorithms optimize exactly what you tell them to
• 23:03 Why teaching AI to copy doctors limits what it can discover
• 26:28 How AI could create a new science of medicine
• 28:40 Could AI predict sudden cardiac death before it happens?
• 34:14 Can an algorithm teach us what it sees?
• 36:50 Medicine’s biggest AI bottleneck: access to data
• 49:00 Healthcare’s “mainframe to PC” transition
• 55:08 Why more measurement could actually mean fewer tests
• 58:46 Why medical AI is aiming too low
• 1:02:13 What the next generation of wearables needs to measure

🔗 Helpful Links:

• Dissecting Racial Bias in an Algorithm Used to Manage the Health of Populations (Science, 2019)https://www.science.org/doi/10.1126/science.aax2342
• An Algorithmic Approach to Reducing Unexplained Pain Disparities in Underserved Populations (Nature Medicine, 2021)https://www.nature.com/articles/s41591-020-01192-7
• An ECG Biomarker for Sudden Cardiac Death Discovered with Deep Learning (Nature, 2026)https://www.nature.com/articles/s41586-026-10674-6
• Predicting the Future — Big Data, Machine Learning, and Clinical Medicine (NEJM, 2016)https://www.nejm.org/doi/full/10.1056/NEJMp1606181
• Nightingale Open Sciencehttps://www.nightingalescience.org/
• Dandelion Healthhttps://dandelionhealth.ai/

Watch the conversation: https://youtu.be/WDo-iL6O5nU

Find us on YouTube: ⁠⁠⁠⁠⁠⁠⁠https://youtube.com/levelshealth?sub_confirmation=1⁠⁠⁠⁠⁠⁠

📲 Connect:

Connect with Dr. Ziad Obermeyer on https://ziadobermeyer.com/

👋 Who we are:

Levels helps you understand your metabolic health with personalized data, expert guidance, and tools that connect your daily choices to measurable changes in your body. Our goal is to help you make better decisions about food, exercise, sleep, and long-term health.

Look for new shows every month on A Whole New Level, where we have in-depth conversations with thought leaders about metabolic health.

Why do we crave some foods the more often we eat them? Are we addicted?

Dr. Dana Small’s research suggests that food craving reaches far beyond taste or willpower, and that “addiction” isn’t a helpful descriptor. Every time we eat, unconscious signals from the body teach the brain which foods deliver useful nutrients, and train us to want more of those. In other words, we don’t eat crave foods because they taste good; foods taste good because our body craves them.

Understanding that means we can rethink overeating. It’s not a matter of addiction or self-control; it’s our body behaving the way nature intended it to, but in the setting of foods not found in the wild, like those high in both fat and carbohydrates. But we may also be able to train our brain away from these cravings.

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What We Cover

• Taste vs. flavor, pleasure, motivation, and food reward
• How gut nutrient signals teach the brain which foods to seek
• Why fat + carbs produce an unusually strong reward response
• What eight weeks of high-fat, high-sugar snacks did to the brain
• How GLP-1s may cut food wanting while preserving pleasure

🎙️ About the Guest:

Dr. Dana Small is the Canada Excellence Research Chair in Metabolism and the Brain and a professor at McGill University, with appointments in Neurology and Neurosurgery and Medicine. She directs the Modern Diet and Physiology Research Center, and her research examines how sensory, metabolic, and neural signals interact to shape food reward, eating behavior, and metabolic health.

📍What Dr. Dana Small & Mike Haney discussed:

• 02:44 - Is food actually addictive?
• 05:02 - Taste and flavor are different senses
• 08:21 - Why “hedonic” vs. “homeostatic” eating is misleading
• 10:42 - The reward from sugar begins after you swallow it
• 22:32 - The “high road” and “low road” of food reward
• 27:41 - How scientists teach the brain to associate a flavor with calories
• 38:30 - Why combining fat and carbohydrates produces more reward
• 47:34 - How beliefs about food can change physiological responses
• 50:02 - Eight weeks of snacks changes how the brain responds to food
• 57:51 - What this science means for people trying to eat differently
• 1:03:50 - How GLP-1 drugs may change food wanting
• 1:07:30 - Can GLP-1s help retrain eating behavior for the long term?

🔗 Helpful Links:

• Habitual Daily Intake of a Sweet and Fatty Snack Modulates Reward Processing in Humans (Cell Metabolism, 2023)https://pubmed.ncbi.nlm.nih.gov/36958330/
• Supra-Additive Effects of Combining Fat and Carbohydrate on Food Reward (Cell Metabolism, 2018)https://www.cell.com/cell-metabolism/fulltext/S1550-4131(18)30325-5
• Integration of Sweet Taste and Metabolism Determines Carbohydrate Reward (Current Biology, 2017)https://pubmed.ncbi.nlm.nih.gov/28803868/
• Rethinking Food Reward (Annual Review of Psychology, 2020)https://pubmed.ncbi.nlm.nih.gov/31561741/
• In Defense of Pleasure: We Need to Rethink Food Reward and Obesity (PLOS Biology, 2025)https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3003497
• Mind Over Milkshakes: Mindsets, Not Just Nutrients, Determine Ghrelin Response (Health Psychology, 2011)https://pubmed.ncbi.nlm.nih.gov/21574706/

Watch the conversation: https://youtu.be/lXlCqNqjgHY

Find us on YouTube: ⁠⁠⁠⁠⁠⁠https://youtube.com/levelshealth?sub_confirmation=1⁠⁠⁠⁠⁠

👋 Who we are:

Levels helps you understand your metabolic health with personalized data, expert guidance, and tools that connect your daily choices to measurable changes in your body. Our goal is to help you make better decisions about food, exercise, sleep, and long-term health.

Look for new shows every month on A Whole New Level, where we have in-depth conversations with thought leaders about metabolic health.

Twenty-five years ago, sequencing the human genome seemed poised to usher in an era of personalized medicine. Dr. Euan Ashley helped turn that promise into an actual clinical experiment, leading one of the first efforts to interpret an entire human genome in the context of a real patient’s health. The challenge quickly became apparent: medicine could suddenly generate billions of data points about one person, but making sense of them was painfully slow.

That history feels newly relevant. Ashley recently gave an AI system his own 15-year-old genome data and watched it reproduce most of an analysis that had originally required months of work by a team, in about 30 minutes. Meanwhile, genomics is being joined by wearables, multi-omics, and other technologies capable of tracking far more of our biology over time.

In this episode of NextLevel, we use the genome revolution as a case study for what happens when our ability to measure the body advances faster than our ability to interpret and use the information. The next leap in personalized medicine may depend less on collecting another mountain of data than on building the tools, reference datasets, and healthcare systems capable of turning that information into decisions.

Free course: Improve your metabolic health

Get our free email course on how glucose, nutrition, exercise, sleep, and measurement can help you build habits that support better energy and long-term health: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://levels.link/wnl⁠

🎙️ About the Guest:

Dr. Euan Ashley is Chair of the Department of Medicine at Stanford University and the Roger and Joelle Burnell Professor of Genomics and Precision Health, with appointments in medicine, genetics, and biomedical data science. He’s also the author of The Genome Odyssey: Medical Mysteries and the Incredible Quest to Solve Them.

📍What Dr. Euan Ashley & Mike Haney discussed:

• 03:33 What happened to the promise of personalized medicine?
• 06:33 The first clinical interpretation of a human genome
• 11:26 AI interprets in 30 minutes what once took months
• 21:25 Why genomics still needs better, more diverse reference data
• 27:41 Building a molecular map of exercise with MoTrPAC
• 32:01 Exercise changed nearly every organ researchers measured
• 39:05 Why your personal baseline can matter more than a "normal" range
• 42:46 How wearables opened a new era of longitudinal health data
• 47:48 The biggest barrier to continuous, personalized healthcare
• 51:39 What medical AI needs to become genuinely useful
• 57:05 How AI can ace medical benchmarks for the wrong reasons
• 58:20 The heart measurement Ashley considers a medical "holy grail"

🔗 Helpful Links:

• Clinical Assessment Incorporating a Personal Genome, The Lancet, 2010. Landmark integrated clinical analysis of a complete human genome.
• Molecular Transducers of Physical Activity Consortium (MoTrPAC), NIH Common Fund. Large-scale project mapping how exercise changes tissues and organs. 
• MoTrPAC: Human Studies Design and Protocol, Journal of Applied Physiology, 2024. Human study of molecular responses to endurance and resistance training.
• The Mitochondrial Multi-Omic Response to Exercise Training Across Rat Tissues, Cell Metabolism, 2024. MoTrPAC study on molecular changes across organs after exercise.
• Harmonizing Standards and Resources for the Medical Genome, Nature, 2026. Ashley et al. on genomic reference standards and clinical-grade sequencing.
  

Watch the conversation: https://youtu.be/bD2YVGdwviE

Find us on YouTube: ⁠⁠⁠⁠⁠https://youtube.com/levelshealth?sub_confirmation=1⁠⁠⁠⁠

👋 Who we are:

Levels helps you understand your metabolic health with personalized data, expert guidance, and tools that connect your daily choices to measurable changes in your body. Our goal is to help you make better decisions about food, exercise, sleep, and long-term health.

Look for new shows every month on A Whole New Level, where we have in-depth conversations with thought leaders about metabolic health.