Dr. Michael Snyder on Continuous Glucose Monitoring and Deep Profiling for Personalized Medicine

Dr. Michael Snyder and Personalized Medicine

• Dr. Michael Snyder is the chairman of the Department of Genetics and director of the center for Genomics and Personalized Medicine at Stanford
• Founder of Cubio and January AI
• Believes in collecting extensive data to better understand health status

Measuring Health Parameters

• Dr. Snyder has measured various parameters in himself, including DNA sequencing, molecular measurements, and wearable devices
• Discovered his risk for type 2 diabetes through genome sequencing

Prevalence of Prediabetes

• 9 out of 10 people with prediabetes are unaware of their condition
• 9% of the US population is diabetic, while 33% are prediabetic
• Continuous glucose monitoring can help identify prediabetes and manage glucose levels

Continuous Glucose Monitors (CGMs)

• CGMs are prescribed under the care of a physician
• Companies like Nutrients, January AI, and Levels make CGMs available to the general public
• Dexcom and Freestyle Libre are well-​​known CGM brands

Personalized Glucose Monitoring

• Different foods cause glucose spikes in different people
• CGMs can help identify which foods cause spikes and allow for personalized dietary habits

• Dr. Snyder believes everyone should wear a CGM to better understand their glucose regulation and prevent diseases
  Diabetes as Multiple Diseases

• Diabetes often thought of as insulin resistance or lack of insulin production

• Different types of diabetes require different treatments 
  • Example: some people don’t release insulin from their pancreas
  • Non-​​metformin responders may benefit from other drugs like Rapinolide
• Understanding individual differences can lead to better health management

Continuous Glucose Monitors

• Help identify foods and lifestyle factors that impact glucose regulation
• Can reveal surprising sources of sugar in seemingly healthy foods
• Exercise can help suppress glucose spikes
• Apps and programs can help teach healthy habits

Big Data in Health

• Current healthcare system measures too little information
• Goal is to create a more complete picture of individual health
• Everyone’s profile is different and relatively stable over time
• Comparing profiles to themselves can help detect shifts in health
• Profiling can reveal important health information before symptoms appear

Transition to Precision Medicine

• Requires changes at multiple levels
• Academics can discover and prove principles, but scaling requires companies and industry involvement
• Need for more personalized and data-​​driven healthcare

• Collaboration between research, industry, and healthcare systems is key
  Qbio and Health Monitoring

• Qbio: a company that offers thorough medical exams with deep molecular measurements and whole-​​body MRIs

  • Costs $3,500, making it inaccessible for many people
  • Aim to make it more affordable in the future
• Current healthcare system is broken 
  • Doctors get paid when patients are ill, not when they’re healthy
  • Need to incentivize keeping people healthy
• Employers could benefit from keeping employees healthy 
  • Healthier workers are more productive
• Insurers need to see proof that new technologies work and save money before implementing them

Wearables and Health Tracking

• Wearables started as fitness trackers but have evolved into powerful physiological monitors 
  • Measure heart rate, skin temperature, blood oxygen, blood pressure, etc.
  • Can take millions of measurements daily
• Example: detecting Lyme disease through a smartwatch and pulse ox 
  • Blood oxygen dropped abnormally low, heart rate increased, and skin temperature increased
  • Detected illness before symptoms appeared

• Algorithm developed to detect illness based on resting heart rate and skin temperature

  • Works retrospectively and in real-time
  • Can detect COVID-​​19 in 81% of cases, often before symptoms appear
  • On average, heart rate jumps up four days before symptoms appear
    Wearable Devices for Health Tracking

• Hour by hour measurement of heart rate and other parameters

  • Can detect illness 70% of the time
  • Detected COVID in 44 out of 63 people in real-time
  • Needs improvement in algorithms and more data
• Heart rate variability 
  • Variable heart rate is a sign of health
  • Can detect atrial fibrillation (AFib) with smartwatches
  • Can measure electrocardiograms with Apple Watch and other devices

Exposome and Environmental Exposure

• Exposome: all the things you’re exposed to 
  • Airborne exposure: pollen, bacteria, fungi, chemicals, etc.
  • Device measures PM 2.5, temperature, humidity, and captures particulates and chemicals
• Environmental exposure contributes to disease risk 
  • Genetics and environment both play a role
  • Air pollution increases risk for age-​​related diseases, Alzheimer’s, respiratory diseases, etc.
• Control over exposure 
  • HEPA filters can help
  • More information can lead to more informed decisions
  • Identifying specific harmful molecules and removing them from the environment

Firefighters and Environmental Exposure

• Measuring exposome of firefighters during wildfires

  • Higher incidence of allergies and asthma in children in polluted areas
  • Identifying harmful elements and finding ways to control exposure or remove them from the body
    Sulforaphane and Detoxification

• Sulforaphane found in cruciferous vegetables, particularly broccoli sprouts

  • Increases excretion of benzene and acrylene found in air pollution and cigarette smoke
  • Activates NRF2 pathway, leading to activation of phase two detoxification enzymes
• Sweat can help excrete heavy metals and other xenobiotics like parabens or BPA 
  • Exercise and sauna bathing can aid in detoxification

Aging and Biomarkers

• People age differently, with some aging more in certain organs or systems 
  • Ageotypes: kidney, liver, immune, metabolic, and cardio aging
  • Can determine ageotype with about five measurements within two years
• Interventions can potentially slow down or reverse aging in specific ageotypes 
  • Exercise, weight loss, and certain supplements may help
• Metformin as a potential anti-​​aging drug 
  • Initial observation: diabetics on metformin seemed to live longer than non-diabetics
  • However, metformin may blunt the benefits of exercise in healthy individuals
  • Exercise is considered the number one factor for longevity, followed by diet

Importance of Exercise for Aging

• Exercise helps maintain muscle mass and prevent sarcopenia
• Encouraging movement and activity in older individuals can lead to better health and longer life

• Exercise induces beneficial effects such as increased myostatins and endorphins
  Benefits of Exercise and Metabolic Changes

• $170 million study on aerobic and resistance training benefits

• Exercise changes half of your molecules, including immune molecules
• VO2 max is an indicator of longevity
• Exercise promotes immune health, beneficial cytokines, and other factors

Genetics vs. Lifestyle in Aging

• Strong genetic component in aging, centenarians run in families
• Strong environmental component, e.g., smoking, living near highways
• Environmental and lifestyle factors can be controlled, unlike genetics

Lifestyle Routine and Diet

• Exercise daily, weight training, and muscle mass gain
• Type 2 diabetic, avoid carbs, eat protein-​​rich foods
• Struggle with vegetable intake, focus on fiber-​​rich foods like carrots and nuts
• Fiber supplementation to reach daily recommended intake
• Omega-​​3s in diet

Microbiome and Health

• Microbiome composition connected to metabolic health, type 2 diabetes, and autoimmune conditions
• Certain fibers can lower cholesterol, e.g., inulin in psyllium husk
• Different people react to different fibers due to their unique microbiomes
• Personal microbiome measurement could help determine optimal diet and immune health

Future of Microbiome Research

• Understanding the microbiome is crucial for determining food intake and immune health
• More immune cells in the gut than anywhere else in the body
• Interplay between immune system, microbiome, and food intake
• Big data is important for understanding the whole health picture

• Better food logging methods needed for comprehensive health analysis
  Big Data Approach in Health Research

• Measuring as much data as possible

  • Unique associations and biomarkers
  • Microbiome, metabolome, genome, proteome
• Exciting time for health research

Following Mike’s Work

• Twitter: @Snydershot
• Studies at Innovations Stanford 
  • Wearables for COVID
  • Other studies available
• Spin-​​off companies 
  • January AI: improving metabolic health using continuous glucose monitoring
  • Cube BIOS: deep data profiling for a complete medical picture