Quantified Health, Wellness & Aging

In this twentieth episode, Polina Mamoshina introduces recently launched Deep Longevity, and its app (young.ai).

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Biomarkers of aging are introduced. She explains that they have taken a superior approach by using deep learning instead of machine learning. Aging clocks in general are covered. Finally, she shares her view that transcriptomic and proteonomic clocks are the likely future.
Topics we discussed in this episode

Personal background: Moscow State University, Oxford University, Insilico Medicine hackathon
Bringing Deep Longevity out of stealth, Young.ai companion app
Deep Longevity introduction including company aims
Description of Young.AI app
Biomarkers of aging as the accelerant of market for aging interventions
Introduction to aging clocks: Horvath, Hannum
Taking a novel and superior technological approach to aging clocks, using deep neural networks, instead of shallow machine learning
Limitations of shallow machine learning models
Ability of neural networks to capture highly non linear dependencies and what that matters for biological age determination
Investing in anticipated payoff from deep learning over the long-term, even if machine learning may be good enough in many cases now
Biological age prediction with Aging.ai
Two approaches to designing aging clocks
Machine learned PhenoAge biological age score
Introducing mortality, with the GrimAge score
Longevity clinics and life insurance as market
Biological age scoring as onboarding tool for life insurance markets
Training datasets
Common blood analytes used in PhenoAge vs Aging.ai
Optimized blood analyte levels for a given individual to get younger
Orthodox medicine uses blood analyte levels that are not specific to the individual and not optimized ranges; designed to detect only late-stage pathologies
Cheapness of regular blood analytes
Emerging market is likely to age score bodily subsystems rather than provide an overall singular biological age score
Goal is to find the fastest ticking clock in your body
Biological age test using a selfie
Providing a library of biological age scores, from free to expensive, so users can upgrade, find out more about themselves
Belief that proteomic and transcriptomic clocks will outperform epigenetic clocks in terms of being actionable with interventions
Epigenetics and aging
Acceleration of the aging rate may show up "late" in terms of being able to intervene, on the epigenome
Youthful blood plasma exchanges and age quantification
Transcriptomic, proteomic, and glycomic clocks
Anticipated rise of longevity clinics

Show links

Deep Longevity (Company Website)
Insilico Medicine (Company Website)
Human Longevity, Inc. (Company Website)
Regent Pacific Group (Company Website)
Young.AI (App from Deep Longevity)
Aging.AI (Biological Age Prediction)
'DNA Methylation Age of Human Tissues and Cell Types' (Paper)
'Assessment of Epigenetic Clocks as Biomarkers of Aging in Basic and Population Research' (Paper)
Steve Horvath (WikiPedia Entry)
'Genome-wide Methylation Profiles Reveal Quantitative Views of Human Aging Rates' (Paper)
Gregory Hannum (LinkedIn)
Morgan Levine (LinkedIn)
'An epigenetic biomarker of aging for lifespan and healthspan' (Paper)
Elysium Health (Company Website)
'DNA Methylation GrimAge Strongly Predicts Lifespan and Healthspan' (Paper)
FOXO BioScience (Company Website)
NHANES III (CDC)
AgeoTypes (Stanford Article)
GlycanAge (Company Website)
GENOS (Company Website)

In this nineteenth episode, Stephen Matlin introduces telomere biology. He details how testing services typically use Q-PCR which provides an average telomere length and why that doesn't really mean anything.

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Instead the percentage of critically-short, measured using Q-FISH, does. Finally he chats about supplements - telomerase inducers - for growth.
Topics we discussed in this episode

Introduction to telomere biology
Hayflick limit, senescent cells, apoptosis
Telomeres and the hallmarks of aging
Quantitative PCR derived average telomere length vs shortest telomeres
Coefficient of variation of lab samples
Role of supplements in supporting our telomeres and overall biological function
Declining nutrition in even vegetables
Telomerase inducers TA-65 and TAM-818
Telomerase enzyme
Henrietta Lacks cells, cancer and the Hayflick limit
Telomerase supplements and cancer
Telomerase inducer Telomere Benefits™
Providing biological age scores using telomere measurements
Telomere length and correlation with healthspan
Improving upon biomarker Prostate Specific Antigen with Prostate Telomere Associate Variance

Show links

LifeLength.com (Company Website)
T.A. Sciences TA-65 (UK/Europe)
T.A. Sciences TA-65 (Amazon.com)
Hayflick, His Limit, and Cellular Ageing (Paper)
The Hayflick Limit (Embryo Project Encyclopedia)
The End-Replication Problem (Paper)
Leucocyte Telomere Length And Risk Of Cardiovascular Disease: Systematic Review And Meta-analysis (Paper)
Association Between Leucocyte Telomere Length And Cardiovascular Disease In A Large General Population In The United States (Paper)
The Hallmarks of Aging (Paper)
Coefficient of Variation (Wikipedia Entry)
A Natural Product Telomerase Activator Lengthens Telomeres in Humans: A Randomized, Double Blind, and Placebo Controlled Study (Paper)
The Telomerase Activator Ta-65 Elongates Short Telomeres And Increases Health Span Of Adult/old Mice Without Increasing Cancer Incidence (Paper)
Discovery Of Potent Telomerase Activators: Unfolding New Therapeutic And Anti-aging Perspectives (Paper)
The Nobel Prize in Physiology or Medicine 2009 (Website)
Defy Time (Website)
Telomere Benefits™ (Product Link)
Mathematical Connection Between Short Telomere Induced Senescence Calculation And Mortality Rate Data (Paper)
Comparison Of Telomere Length Measurement Methods (Paper)
Beyond Average: Potential For Measurement Of Short Telomeres (Paper)

In this eighteenth episode, Alexis Shields explains that blood biomarkers may be obtained directly and the results used to reduce chance of future disease occurrence, as well as remedy any subclinical symptoms.

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She provides a tour of some of the common biomarkers. Along the way she describes her virtual functional medicine practice.
Topics we discussed in this episode

Terms naturopathic, homeopathic, allopathic and functional medicine
Urine biomarkers, DUTCH test
Triglyceride to HDL ratio correlates with cardiovascular disease, heart disease, and diabetes
Thyroid testing and Reverse T3
Thyroid and low mineral status
Hashimoto's disease and hypothyroidism
Hematology testing
Machine learning tool for looking at blood work
Iron vs ferritin
Iron levels
Cholesterol testing
High-resolution lipid analysis
LDL, nor total cholesterol has much predictive power
Apolipoprotein B (ApoB) and Lipoprotein(a)
Cholesterol and immunity
Adrenal testing
Sodium and potassium levels and adrenal dysfunction
Cortisol testing
Urine testing of pH is really tricky
Dietary cholesterol has minimal impact on blood cholesterol levels
Electrolytes and diet
Body acidity and disease
Insulin resistance
Physiological insulin resistance
Glucose and melatonin
Blood tests and supplements with COVID-19 in mind

Show links

DrAlexisShields.com (Website)
Stop Flushing Terabytes of Data Down the Toilet – (EP11: Daniel Maggs, bisu)
Nordic Labs (Website)
TG:HDL – Heart Disease Risk Calculator (Online Tool)
KSM-66 Ashwagandha Extract (Website)
Rhodiola Rosea (Website)
Hormesis (Wikipedia Entry)
Lymphocytes Definition (Article)
Leukocytes Definition (Article)
Neutrophils Definition (Article)
BloodSmart.ai (Website)
C-Reactive Protein (Article)
LIPOPRINT LDL Subfractions Test (Website)
NMR Lipid Profile (Article)
DUTCH Test (Website)
Anion Gap (Wikipedia Entry)
HOMA-IR Calculator (Web Page)

In this seventeenth episode, Gordon Lauc introduces glycobiology. He details GlycanAge®, the world’s first direct-to-consumer glycan-based product.

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He explains that it can quantify how well interventions (e.g. supplements) work for you as an individual, and how much healthy life you’ve got left. Finally he details a potential COVID-19 glycan biomarker to accurately assess your risk.
Topics we discussed in this episode

[coming soon]

Show links

[more links coming soon]
GlycanAge (Website)
Genos (Website)

In this sixteenth episode, Knut Wittkowski shares his expert view that lockdowns were not necessary. That he can’t figure out a single justification for extending them. That there is no “second wave”. That there is no viable option other than herd immunity, and that by prolonging the pandemic, we are putting the vulnerable at greater risk.

In this fifteenth episode, Liz Parrish shares her quest for radical life extension and details her two completed gene therapies.

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She describes the regenerative medical tourism available today for increased lifespan and costs. She relates her company's mission to create a human that regenerates faster than they degenerate. She details her upcoming gene therapies, including upgraded IQ.
Topics we discussed in this episode

Making controversial medical history
Quest for radically increased longevity
Upregulating telomerase, hTERT
Downregulates myostatin, follistatin
Interest in regenerative medicine technologies
Desire to help billions of people
Comany goal to create a human that regenerates faster than they degenerate
PGC-1α
BioViva's DNA methylation kit
Plan to look at multiple aging clocks
Regenerative medical tourism
Childhood ambition
Space travel and gene therapy are intertwined
Personal goals
Morphological freedom
Hope for the future
Being of optimistic nature
Gene therapy - dystopian or utopian?
Gene therapy costs
Societal health stratification
Making humans more malleable like software
What is gene therapy?
Gene delivery and viral vectors
Next personal gene therapy - Klotho
Next personal gene therapy - PGC-1α
Developing New Viral Vectors
Apo-A1 Milano
Adeno-Associated Virus (AVV. AAV-2)

Show links

BioViva (Website)
Integrated Health Systems (Website)
Telomeres and Longevity: A Cause or an Effect? (Paper)
Effects of Myostatin Deletion in Aging Mice (Paper)
Telomeres and Telomerase as Therapeutic Targets to Prevent and Treat Age-Related Diseases (Paper)
Inhibition Of Myostatin With Emphasis On Follistatin As A Therapy For Muscle Disease (Paper)
PGC-1α in Aging and Anti-Aging Interventions (Paper)
TimeKeeper™ DNA Methylation kit (Landing Page)
Longevity (Subreddit)
Maximum Life Foundation (Website)
George Church (Wikipedia Entry)
Factor IX (Wikipedia Entry)
hTERT (Wikipedia Entry)
Hayflick Limit (Wikipedia Entry)
Follistatin (Wikipedia Entry)
The Longevity Hormone Klotho Is a New Player in the Interacion of the Growth Hormone/Insulin-Like Growth Factor 1 Axis (Paper)
rs9536314/Klotho Gene (SNPedia Entry)
PGC-1α in Aging and Anti-Aging Interventions (Paper)
María A. Blasco (University Staff Page)
The Long Saga of Apo-A1 Milano (Article)
Why Most Published Research Findings Are False (Paper)

In this fourteenth episode, Dr. William Davis shares his view that healthcare is not primarily concerned with our health. Instead it is concerned with profit, even at the expense of our health.

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He explains that the best way to protect our health and our finances from healthcare is to take our health under our control. And in doing so we can achieve “magnificent health”.
Topics we discussed in this episode

Healthcare system primary focus on profit, not your health
The more you spend on healthcare, the more the mortality rate goes up
Addressing factors that allow disease to emerge in the first place
Healthcare may make you sicker and fatter
"Magnificent health" is achievable with little to no drugs
A long-term ketogenic diet has negative effects on gut microbiome composition
Vitamin D and magnesium deficiency
Disrupted gut microbiome composition factors
Small Intestinal Bacteria Overgrowth (SIBO)
SIBO link to rheumatoid arthritis, fibromyalgia, polymyalgia rheumatica, Hashimoto’s thyroiditis, Parkinsonism, Alzheimer’s dementia
Lactobacillus reuteri DSM 17938
Lactobacillus reuteri ATCC PTA 6475
Grain elimination to avoid zinc deficiency
Lactobacillus casei
Lactobacillus rhamnosus GG
Bifidobacterium Longum
Akkermansia Muciniphila
Stopping or reversing coronary atherosclerosis
CT heart scanning
NMR lipoprotein testing
What foods cause harmful LDL-Cholesterol particles
Lipoprotein(a)
Thyroid tests
A1C test
LIPOPRINT high-resolution cholesterol test
Corrupt JUPITER study
Magnesium water
Need for iodine; kelp
Vitamin K2

Show links

Wheat Belly Blog (Website)
Undoctored (Website)
AIRE device (Website)
Small Intestinal Bacteria Overgrowth (SIBO) Test (Website)
"Leaky Gut Syndrome" (NHS Article)
Triage Theory of Aging (YouTube Video)
The Unique Probiotic Benefits of L Reuteri Yogurt (YouTube Video)
The Efficacy of Lactobacillus Reuteri DSM 17938 in Infants and Children: a Review of the Current Evidence (Paper)
The Effect of Lactobacillus Reuteri ATCC PTA 6475 on Volumetric Bone Mineral Density in Patients With Osteopenia (Paper)
The Lactobacillus casei Group: History and Health Related Applications (Paper)
Towards a Better Understanding of Lactobacillus Rhamnosus GG - Host Interactions (Paper)
Bifidobacterium Longum Subspecies Infantis: Champion Colonizer of the Infant Gut (Paper)
Strategies to Promote Abundance of Akkermansia Muciniphila, an Emerging Probiotics in the Gut, Evidence From Dietary Intervention Studies (Paper)
Genova GI Effects® Microbial Ecology Profile Test (Website)
Coronary Artery Calcium (CAC) Score Testing Locations (Website)
Coronary Artery Calcium Data And Reporting System: Strengths And Limitations (Paper)
Understanding the NMR LipoProfile Test Report (PDF)
Lipoprotein(a): Biology and Clinical Importance (Paper)
Quantimetrix LIPOPRINT Test (Website)
JUPITER: a Few Words of Caution (Paper)
Magnesium Bicarbonate Water Recipe (Website)
Molecular Hydrogen Tablets (Amazon.com)
In Defense of Vitamin K2 MK-4: Dr. Price’s Activator X (Article)

In this thirteenth episode, Tom Stubbs, Co-Founder/CEO of Chronomics starts with introducing epigenetics. He describes the technology and expertise that he's brought together to create the only company in the world advancing the forefront of epigenetic biomarkers.

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He explains how their A.I. based health biomarker engine will be used to reduce your risk of future illness.
Topics we discussed in this episode

Focus of Chronomics
Epigenetic sequencing
Epigenetic ideal data type for preventive health
Epigenetics ideal for figuring out age-related and chronic conditions
Genomics and epigenetics provide complimentary data
Histone methylation
DNA methylation
MTHFR gene
CpG sites
Chronomics health biomarker engine
Epigenetics and aging
Blood vs saliva as an epigenetic sampling type
Arrays vs next-generation sequencing
Why epigenetics is a fantastic data type
Developing unique epigenetic signatures or biomarkers
Polygenic risk scores
Biological age and epigenetic clocks
Using blood vs saliva for epigenetic clock input
Arrays vs sequencing for epigenetic clock input
Genetics vs epigenetics
Leveraging epigenetics to personalize pharmaceutical agent or drug intervention risk/reward
Leveraging epigenetics to personalize rejuvenation therapy or longevity compound reward decisions
Ending flying blind as to whether things have a positive impact or a negative impact on your health
Providing people with access to their molecular level biological data
Ability to retain that immortality across the human existence
Epigenetics in utero mechanisms
Epigenetics across generations
Epigenetic memory
IPS reprogramming
Dietary interventions on rate of biological aging

Show links

Chronomics (Website)
Tommy Wood on Engineering Sustained Health Using A.I. & Standard Blood Chemistry (Podcast Guest #006)
What is 30x and 0.4x Whole Genome Sequencing? (Article)
Next-Generation Sequencing vs. Microarrays (Article)
100,000 Genomes Project (Wikipedia Entry)
From Metabonomics to Pharmacometabonomics: The Role of Metabolic Profiling in Personalized Medicine (Article)
Homocysteine and MTHFR Mutations (Article)
CpG site (Wikipedia Entry)
Polygenic Score (Wikipedia Entry)
Epigenetic Clock (Wikipedia Entry)
Steve Horvath (Wikipedia Entry)
Jeff Kaditz on Multiscale Digital Models of Human Biology, Turning Health into a Hard Science (Podcast Guest #012)
The Epigenetic Landscape in the Course of Time: Conrad Hal Waddington's Methodological Impact on the Life Sciences (Paper)
Induced Pluripotent Stem Cell (Wikipedia Entry)
Beta Oxidation (Wikipedia Entry)
Cell Potency (Wikipedia Entry)
Steve Horvath (Wikipedia Entry)
Dutch Famine of 1944–45 (Wikipedia Entry)
Gamete (Wikipedia Entry)
From Germline to Soma: Epigenetic Dynamics in the Mouse Preimplantation Embryo (Paper)

In this twelfth episode, Jeff Kaditz, Founder/CEO of Q Bio begins with coronavirus chat. He goes on to explain that most medical knowledge today is probably incorrect or heavily biased. That there’s almost nothing a doctor does that couldn’t have been done 200 years ago in terms of the information. He presents his vision to run ‘search engines for the body’ and turn healthcare into hard science.

The present-day healthcare system (the medical industry) naturally embodies a collection of long established characteristics (e.g. paradigms, practices, tools and philosophical beliefs). These have been been interwoven in a successive patchwork stretching back to Ancient Egypt. Significant improvements have occurred during the past ~200 years; particularly the past ~100. Further acceleration is expected.

However over that same ~200 year period our environment (e.g. chemical exposures) has become increasingly at odds with our health. Our lifestyles (e.g. indoor working) conjoined with the shifting environment has also deteriorated in terms of health sustainment.

Within the past ~40 years our food environment in particular has become sharply more adverse to our health and longevity. Strikingly this been in side-step with the issuance of national nutritional guidelines that were not based upon scientific rigor.

If this was not bad enough, the healthcare system during the past ~60 years has constructed, imbued and propagated financial incentives at odds with health. Sickness has become big business along with sickness inducing food-like-products.

It’s left us in the midst of a skyrocketing obesity and chronic disease crisis. One already of epic proportion and fast approaching a species-level crisis. The majority of which is entirely preventable. It represents human suffering on a scale never before witnessed and a grave threat to our new generation.

The healthcare system has been attempting to manage it using tools that were very successful during the 20th century (largely targeting bacteria and viruses), namely pharmacological drugs and procedures. However this is clearly not working and not likely to work even if broken incentives were corrected. It instead requires a novel 21st century approach. One is starting to appear and must be catalyzed, hence this podcast. It’s being born from an entirely different domain - computer science, and a new relationship between man and machine.

Computing, historically known as “machine-assisted human computation” (as “computer” originally referred to the person, not the machine) has, during the past ~60 years went from something unknown to the average person to devices proximal to, carried on and/or worn on the average person the majority of their lifetime. The devices are now entering a new epoch wherein they will understand humans and human life better than humans. From superior emotion detection to whom we should marry. From accurately reading our body biomarkers real-time to unravelling which lifestyle aspects are most negatively impacting our health span.

As this presently unfolds and our lives are increasingly governed and dependent upon computer algorithms, the opportunity is arising for a new healthcare. Not one to replace existing healthcare, but to emerge and live in parallel. A fork.

Existing healthcare will remain confined to sickness and injury (“sick care”). The new second healthcare on the other hand will be for healthy people who still form the majority of the human population.

Existing healthcare will for the most-part stop attempting to deal with prediction and prevention (aside from viral and bacterial). Instead the new industry will. It will also add a third piece, health optimization (of already “healthy” individuals).
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In this inaugural episode, Brad Perkins speaks of why he left the role of founding Chief Medical Officer for Human Longevity, Inc. to create Sapiens Data Science, Inc. where he is Co-Founder, Director and CEO.

Brad covered a number of topics including the necessity to straddle existing healthcare whilst spearheading the new “healthcare for healthy people”. He spoke of his plans to bring as many clinicians from the world of today with him on that journey as he can,

In this eleventh episode, Daniel Maggs enlightens listeners as to how today we are flushing away our bodily waste daily without first capturing the highly-valuable data it contains.

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He details his companies forthcoming smart urine analyzer that provides personalized health advice. He shares a lot of excitement as to where home and personalized health is going.
Topics we discussed in this episode

The three types of ketone
Blood, urine or saliva as the gold standard/s
Electrolytes and other biomarkers
Balancing electrolytes
Kidney aging and testing
Slowing kidney aging
Advantages of looking at ketones relative to things like magnesium, sodium, potassium
Future of home and personalized health
The passing of Quantified Self
Biohacking future, a mainstream culture of health and wellness
Other companies in the home and personalized health space
More scientific rigor and objectivity in the wellness industry
Collaborations on the Bisu data; oral health, baby health, pet urine testing

Show links

Bisu (Website)

In this tenth episode, Jeremy Malecha discusses his company plans to democratize and scale functional medicine by more effective data processing.

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He discusses the need to consolidate data across hundreds of lab test lab providers, structuring of that data and finally the ability to better leverage the data. He discusses his own personal health journey along the way.
Topics we discussed in this episode

Plan to build a "personalized health engine" to democratize and speed-up functional medicine resolutions to patient symptoms
What functional medicine is
Some common blood biomarkers
Jeremy's personal health journal from sub-optimal to resolution
Other functional medicine tests including microbiome, heavy metals and DUTCH
The overly manual and therefore inefficient nature of functional medicine presently
The need to consolidate the data from all the different labs
Enabling the practitioner understand and process the data faster
Trying to have machine help give meaning over multiple lab provider results
Moving beyond "tribal knowledge" to something more grounded in data and explicit
Food sensitivity testing
Labs are not unlocking value in their data repository
Business model in data collected from all labs

Show links

Biocanic (Website)
International Statistical Classification of Diseases and Related Health Problems (ICD)-10 (Wikipedia Entry)
Microbiome Testing: Wild Goose Chase or Modern Miracle? (Article)
C-Reactive-Protein (Wikipedia Entry)
Precision Analytical DUTCH test (Website)
The MTHR Gene Mutation and How to Rewire Your Genetics (Article)
Dirty Genes: A Breakthrough Program to Treat the Root Cause of Illness and Optimize Your Health by Ben Lynch (Book)
Triglyceride Over HDL Ratio Calculator (Website)
NMR LipoProfile Test (Website)
Heads Up Health (Website)
QuickSilver Scientific (Website)
Diagnostic Solutions GI Map (Website)
Difference Between Classic IgE Food Allergies and Delayed IgG Food Allergies (Article)
SpectraCell (Website)
Viome (Website)
Cyrex Laboratories (Website)
Wellevate (Website)
FullScript (Website)
Alcat Test (Website)
Investors Just Bet $2.4 Billion That Your Gut is the Next Frontier for the Hottest Part of Healthcare (Article)
Oxford Biomedical Technologies (Website)
Quest Diagnostics (Website)
LabCorp (Website)

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In this eighth episode, Ben Hwang, Chairman & CEO of Profusa, provides an overview of injectable biosensors. He explains that the technology enables a model akin to getting a blood test every few seconds of our life (rather than only every few years when sick). He predicts that this “unlocked stream of biochemistry data” will become married to other data (e.g. our voice patterns) to provide a panoramic view of our health and wellbeing.
Topics we discussed in this episode

Continuous, realtime measurement of an individual’s biochemistry
Injectable biosensors
Biosensor components
Solving the 'foreign-body response'
Blood chemistries that can and can't be measured in the interstitial fluid
Three stages of the sensor
Achieving calibration with heterogeneity of tissue
Putting multiple chemistries on one single sensor (multiplexing)
Episodic measurements taken by a clinician every few years vs realtime direct measurements
Changing towards a proactive (forward looking) rather than rear-view looking measurement of blood chemistry
Achieving a product cost similar to the price of a Netflix subscription
Empowering individuals to be able to make healthcare decisions and decisions about their wellbeing
Impacting how insurance companies, healthcare providers etc. think about keeping a population or individual healthy
The extent to which today's medical practitioner will remain as intermediaries
The economic need to move to prevention
Ambition to touch a billion people
Marrying biochemical data to other data such as voice (tones, word pattern), pollen count, activity level etc.
Being able to predict and monitor many more biomarkers than the ones we actually have to measure
Forthcoming CE and FDA approval
Multiyear measurement of glucose in realtime
The majority of the population will one day have implantable biosensors for continuous long-term monitoring of blood chemistries

Show links

Profusa Website
'Fluid compartments' Wikipedia Entry
'Foreign body granuloma' Wikipedia Entry
Bloodcalculator.com Website

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In this sixth episode, Tommy Wood, Chief Scientific Officer of Nourish Balance Thrive, explains that the majority of modern disease is caused by our environment and as such, under our control. He shares his experience that A.I. coupled with ordinary blood tests, can inform us of changes we can make to protect/optimize our health, or when sick, lower the cost by predicting which further tests to conduct.
Topics we discussed in this episode

Most

Read the transcript

In this sixth episode, Tommy Wood, Chief Scientific Officer of Nourish Balance Thrive, explains that the majority of modern disease is caused by our environment and as such, under our control. He shares his experience that A.I. coupled with ordinary blood tests, can inform us of changes we can make to protect/optimize our health, or when sick, lower the cost by predicting which further tests to conduct.
Topics we discussed in this episode

Most chronic disease (e.g. diabetes, Alzheimer's, arthritis, certain cancers) we could eliminate by controlling our environment (e.g. diet, sleep, toxic exposures)
Sustaining long-term health by preventing, or slowing down the aging processes
Predicting chronic disease based upon subjective quality of life questionnaires or with the inclusion of simple blood tests, processed by machine learning algorithms
Prediction of biological age based upon simple blood tests, processed by machine learning algorithms
Personalizing lifestyle interventions to achieve longer health and life spans, using only simple blood chemistry processed with machine learning
Nourish Balance Thrive’s Blood Chemistry Calculator
Nourish Balance Thrive’s Elite Performance Analysis Tool
Laboratory biomarker ranges are averages derived from a sick population rather than a healthy nor optimized health population
Predicting where an individual's health may be further optimized (e.g. nutrient deficiencies, heavy metal loads, hormone levels) using only cheap blood tests processed by machine learning algorithms
Humans (e.g. doctors) would be unable to see valuable patterns in cheap blood test data
Lack of biological data derived from healthy individuals, masses of data derived from sick individuals
Groups working on health optimization as opposed to orthodox healthcare’s focus on sick care
Non-pathological insulin resistance, physiological insulin resistance
Elevated fasting glucose and predicted biological age
Genomics can’t optimize an individual's diet and lifestyle, at least at present
An individual's diet and lifestyle can be optimized today through subjective questionnaires and simple blood chemistry processed by machine learning algorithms
Most chronic disease is a metabolic disease
Ancestral health approach prevents or even reverses chronic disease; advanced technologies not needed
Digital phenotyping
Need to filter tap water and other environmental controls to protect our health span
The likelihood that most of the healthy population is in fact not “healthy”; the bar of “healthy” has been lowered so people don’t know of a “more well”
Gut issues underlie or contribute to many health issues we see today
Building tools that can track underlying trends or patterns in our blood biochemistry so that we can know if lifestyle interventions are working for us
Nutritional epidemiology is a broken science
Democratizing functional medicine
Engineering sustained health

Show links

Nourish Balance Thrive Website
Blood Chemistry Calculator
Elite Performance Analysis Tool
Digital Phenotyping Wikipedia Entry
Insilico Medicine Biological Age Prediction Calculator
Kenneth M. Ford Wikipedia Entry
Bryan Walsh Website
Institute for Human and Machine Cognition (IHMC) Website
Chris Kelly LinkedIn Profile
What is Functional Medicine Article
The Dawn Phenomenon – Why are Blood Sugars High in the Morning Article
DayTwo Website
Quick Silver Mercury Tri-Test

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In this fifth episode, Don Brown, CEO LifeOmic, explains the nomenclature shift from precision medicine to precision health, details the firm footing his company has in precision health, how it’s now extending another foot forwards into hyper wellbeing. Lots of app, lifestyle medicine, lifespan, healthspan and biological age quantification chat.

Topics we discussed in this episode

Precision medicine vs precision health
Storage of panoramic health data/longitudinal datasets
Intermittent fasting
Institutional top-down and emerging bottom-up direct-to-consumer approaches to health
Precision health vs hyper wellbeing
Need to focus on aging itself as root cause of most diseases
Homeostasis
Healthspan vs lifespan
Lifestyles that accelerate aging
Lifestyles that decelerate aging
Biological age quantification
Using an app to decelerate aging, extend lifespan and increase healthspan
High insulin as age accelerator
Evolutionary medicine as age decelerator
Machines as overlords vs machines as health companions
Precision lifestyles guided by machines
Healthcare set for exponential changes ahead
Lack of nutritional training in medical school
Tendency of healthcare institutions to hoard data and doctors trained to limit data gathered
Hormesis
Our biological avatar models running in the cloud
Orthomolecular medicine and triage theory
In app integration of genomics, microbiome and other tests
In app gamification of "healthy living"
Mindfulness
Glucose ketone index
Tying lifestyle changes to rate of biological aging to change behavior
Nicotinamide adenine dinucleotide (NAD) and other supplements

Show links

LifeOmic Website
LifeOmic Fasting Tracker for iOS Download
LIFE: The Socially-Connected Intermittent Fasting App that Leverages Precision Medicine Blog Article
A Vision of LIFE Extend — A Powerful Precision Health Mobile App Blog Article
LIFE Extend - Pre-Registration Web Page
Epigenetic Clock Wikipedia Entry
DNA Methylation Age of Human Tissues and Cell Types Paper
DNA Methylation-Based Biomarkers and the Epigenetic Clock Theory of Ageing Paper
Hormesis Wikipedia Entry
Antagonistic Pleiotropy Hypothesis Wikipedia Entry
myDNAge Website
Life Length Website
Effects of Longevinex (Modified Resveratrol) on Cardioprotection and its Mechanisms of Action Paper
Cancer as a Metabolic Disease: On the Origin, Management, and Prevention of Cancer Book
Warburg Effect Wikipedia Entry
Hyper Wellbeing Episode #002 - L-Nutra’ Joseph Antoun on Fasting Mimicking Diets, Biological Aging and Longevity
Juvenescence: Investing in the Age of Longevity Book
An Epigenetic Biomarker of Aging for Lifespan and Healthspan Paper
Methylation Aging Clock: An Update Blog Article
Steve Horvath Wikipedia Entry
Slowing Ageing by Design: the Rise of NAD+ and Sirtuin-Activating Compounds Paper
Sirtuin Wikipedia Entry
David Sinclair's Beginner's Guide to Anti-Ageing News Article
Triage Theory Paper
Orthomolecular Medicine Wikipedia Entry
What is Glucose Ketone Index Blog Article
Glucose Ketone Index (GKI) Calculator
What is Tokenomics and How it Can Make or Break your ICO
Elysium Health Website
Longevinex Website
Leonard P Guarente Wikipedia Entry

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In this fourth episode, Ardy Arianpour, CEO and Co-Founder of Seqster, shares why the future of your health data is a centralized view, controlled by you, pulled from wearables, genetic tests, logged nutritional intake as well as your medical records even if spread across medical institutions. He relates the unique ability and need to share our lifetime of health data transgenerationally.

Topics we discussed in this episode

Apple's acquisition of Gliimpse in 2016
Google's failed attempt of personal health data storage
Microsoft HealthVault
Apple Medical Records
Why Seqster is different from other services offering to collate your medical records
The consumer value of longitudinally matched data sets, particularly multi-generational
The hijacking of Electronic Medical Records for greater profit rather than patient care
The ability to provide a single unified view of our health data, spanning wearable devices, to lab tests such as genetics, to our electronic medical records even if spread over multiple institutions
The reluctance of orthodox healthcare to liberate our health data
The creation of a new legal framework to share our lifetime of health data with our family and/or society, posthumous

Show links

Seqster Website
Chain of custody Wikipedia Entry
PatientBank Shutdown Notification Blog Post
National Institutes of Health (NIH) — All of Us Research Program Web Page
Gliimpse CrunchBase Entry
Picnic Health Website
Heads Up Health Website
Fast Healthcare Interoperability Resources (FHIR) Wikipedia Entry
Affective Computing Wikipedia Entry
Google Health Wikipedia Entry
Stanford Medicine September 2018 White Paper: The Future of Electronic Health Records PDF
An American Sickness: How Healthcare Became Big Business and How You Can Take It Back by Elisabeth Rosenthal Book
Hyper Wellbeing 2016 Conference Video - Walter De Brouwer: From IA to AI in Healthcare
Microsoft HealthVault Web Page
HumanAPI Website
Apple Health Records Web Page

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In this third episode, Ivor Cummins, Chief Program Manager of Irish Heart Disease Awareness (IHDA), shares why as a top class engineer he’s been decoding the causes of human chronic disease and obesity. He relates why orthodox healthcare is unnecessarily putting our health and lives at risk. He imparts what we can do ourselves to predict and prevent modern disease.

Topics we discussed in this episode

Ivor’s blood chemistry showing high serum ferritin, Gamma-Glutamyl Transferase (GGT) and cholesterol
Ivor’s inability to get answers about the root cause of the high markers, nor any quantification of any increased morbidity or mortality
His search for answers and the answer itself
His serendipitous discovery that the risk markers used by orthodox healthcare are weak let alone optimal, even deeply misleading
Better risk markers for morbidity and mortality prediction
Serendipitously meeting David Bobbett who also had an axe to grind with orthodox healthcare after he discovered using his own efforts that he was very high risk, after being told he was low risk by healthcare
The use of generic risk factor algorithms by orthodox healthcare and why they are not good enough
Medications are often a very weak intervention e.g. little effect on all-cause mortality
Correct diet and lifestyle is a more powerful intervention as it addresses the root cause
Dietary root causes - primarily refined sugars, refined carbohydrates and vegetable oils (the three building blocks of manufactured “food like” products)
Mixture of refined carbohydrates and fats is the least optimum for longevity and healthspan
There is no more important factor in weight loss and longevity than your insulin status
The bar where orthodox healthcare puts diabetes and diabetic physiology is very late in the diabetic journey, whereas it could be caught 15 years earlier
The majority of the American adult population have diabetic physiology; the majority share this single metabolic disease
Most doctors are not aware of insulin resistance outside the context of diabetes nor aware of insulin as a disease cause, only a medication
Diabetic physiology is linked to fatty liver, obesity, heart disease, Alzheimer’s, many cancers; in fact all modern chronic diseases
Orthodox healthcare is using glucose to determine diabetic status, whereas it should be using insulin, particularly post-prandial insulin
Use of HOMA calculation as a cheap yet better measure of diabetic physiology
Use of Kraft-Assay as the gold standard to measure of diabetic physiology
Total cholesterol is a very poor risk marker
LDL, the “bad” cholesterol is a very poor independent risk marker
High resolution LDL analysis (LIPOPRINT/NMR)
Bypassing fuzzy risk markers and guesses by using the Coronary Calcium Score (CAC) to see the disease directly
The four types of people - it’s the metabolically unhealthy, thin outside, fat inside (TOFI) at the four who are most risk
The orthodox intervention, low fat diets and vegetable oils, will probably just hasten your demise.
Nutritional guidelines have been based upon junk science and have only exacerbated chronic disease and obesity

Show links

Irish Heart Disease Awareness (IHDA) Website
Jeffry Gerber, MD Website
Ivor Cummins Website
Eat Rich, Live Long: Mastering the Low-Carb & Keto Spectrum for Weight Loss and Longevity Book
David Bobbett on Independent.ie Rich List Web Page
Coronary Calcium Score Web Page
How Could a fit 51-year-old Have a 25pc Chance of a Massive Heart Attack Within a Year? Article
Atherosclerosis Wikipedia Entry
Framingham Risk Score Wikipedia Entry

Chronological age constitutes the central risk factor for major pathologies that limit healthspan, including cancer, diabetes, cardiovascular diseases, and neurodegenerative diseases.

However reaching an old age does not necessarily though result in a higher degree of age-related disability. In other words there is great heterogeneity in the health outcomes of elders. This is evidenced by long-lived individuals from families expressing extraordinary longevity and with a lower prevalence of age-related diseases. They show “youthful” profiles for many metabolic and immune-related parameters and are considered “decelerated” or “healthy agers”.

The rate of aging is malleable, and poor health in late life is not inevitable. Contrary to the previously held belief that increased risk of diseases and disability with advancing age results from inevitable, as well as genetically determined intrinsic aging processes, more recent studies indicate that many of the usual aging attributes are due to lifestyle and other modifiable factors.

Organ systems throughout the body for example, show age-dependent declines in integrity even among young healthy people in their 20s and 30s. Targeting aging in younger, still healthy individuals should allow earlier intervention and damage avoidance. By the time chronic diseases are diagnosed, much damage is done and undoing it is difficult. It also stands to offset the economic burdens of a skyrocketing aging population blighted by multiple chronic conditions.

Today biomedicine takes on conditions one at a time (e.g. Alzheimer's), rather than attempting to stall incremental cellular damage and changes (caused by unhealthy aging) that lead to multiple conditions. Economic incentives in both biomedical research and healthcare reward treating diseases in isolation more than promoting true health.

For the past three decades reliable indicators of biological age, rather than chronological age, along with determinants of healthy aging, has been pursued. (Chronological age refers to the actual amount of time you’ve been alive. Biological age is therefore a truer measure of age than date of birth. Chronological age does not change, regardless of how healthy a lifestyle).

Only recently has there been success in quantification of biological age. Complimentary, findings that aging can be delayed in mammals have raised the credibility of prolonging human healthspan.

The target to identify aging biomarkers was to improve upon chronological age as a predictive risk factor and to enable earlier, proactive interventions; particularly lifestyle changes (additions, subtractions, modifications).

Methods to quantify biological processes of aging are now showing promise. Biological aging measures are designed to capture subtle, organism-wide shifts in physiological integrity. To be truly useful, such measures need to be able to tell exactly where a person is in their total lifespan (therefore must be predictive of the rate of aging).

While life expectancy has increased remarkably over the last two centuries worldwide (due to hygiene, antibiotics etc.), healthspan is not keeping pace because current disease treatment often decreases mortality without preventing or reversing the decline in overall health. People are now sicker longer, often coping with multiple chronic diseases simultaneously. Thus, there is an urgent need to extend healthspan

Human lifespan variation is mainly determined by environmental factors (with food choices and patterns being primary), whereas the genetic contribution is 25-30% and expected to be polygenic. Therefore personalized diets and fasting strategies offer promise in optimizing human healthspan and lifespan.
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In this second episode, Joseph Antoun, Chairman of the Board and CEO of L-Nutra Incorporated,