Big Data and Human Health & Longevity (Prof. Michael Snyder — Stanford Medicine)

Professor Michael Snyder is the Chair of Genetics at Stanford School of Medicine, where his research group develops and uses technologies to study biological regulatory networks and applies these approaches to understand human variation and health. He's founded multiple biotech startups and has authored a book titled Genomics and Personalized Medicine: What Everyone Needs to Know.

Today, Professor Snyder joins host Bob Hughes to discuss the impact of big data on human health. He reviews the results of his research, carried out on 109 people including himself, which entails collecting numerous types of health data and building an informative data profile, as opposed to the traditional approach of collecting just a few pieces of information. He goes on to share his personal story of how collecting deep data on himself helped him change his lifestyle after being diagnosed as a type two diabetic - using precision medicine to control diabetes. Professor Snyder also explores how DNA methylation can be used to track aging patterns and ageotypes, as well as the relationship between aging and Big Data collection, and also discusses health and longevity from his viewpoint, particularly from the standpoint of boosting the immune system.

In this episode, you’ll learn how Big Data can influence our health, and why Professor Snyder believes that the transformation of healthcare begins with deep-diving into data.

Episode Highlights:

●  Understanding precision medicine and personalized medicine

●  How Big Data influences individual health

●  Professor Snyder’s research results on 109 people

●  The impacts of deep data profiles

●  How Professor Snyder changed his lifestyle after deep-diving into his data

●  Using precision medicine to control diabetes

●  DNA Methylation and tracking aging patterns

●  Selection criteria for the 109 research subjects

●  Professor Snyder’s growth over the years from yeast biology

●  Human health and longevity from Professor Snyder’s viewpoint

Quotes:

“We're actually much more focused, I would say, on precision health, trying to keep people healthy at an individualized level, and trying to use big data to do just that.”

“We're in a world now where you can just collect so much deeper data on people.”

“I liken it to a jigsaw puzzle. If I want to see what the picture is in a puzzle, looking at one or two pieces of a 1000 person puzzle isn't going to tell me the picture, even 15 pieces probably won't do it. But I want to look at as many pieces as possible. And that's what big data is all about.”

“One aspect is to collect data, the other is to do it over time.”

“A lot of people who survived the COVID infections wind up being type two diabetics on a 4% increase, which is a pretty large number of people.”

“Everybody has different aging patterns, and so the way we think about this is like a car. Your car as a whole gets older over time, but some parts wear out first. ”

“Having good biomarkers for aging, we think, is a big deal.”

“Why are we measuring 15 things? We should be measuring thousands.”

“There's a ton of investment going into longevity these days - billions of dollars now into these new startups.”

“Your immune system starts plummeting in your 60s, as I say, and that just leaves you more and more vulnerable anytime after that.”

“I think we can transform healthcare. I think you'll see big changes in the next 10 years in terms of home testing, all this sort of...

Professor Michael Snyder is the Chair of Genetics at Stanford School of Medicine, where his research group develops and uses technologies to study biological regulatory networks and applies these approaches to understand human variation and health. He's founded multiple biotech startups and has authored a book titled Genomics and Personalized Medicine: What Everyone Needs to Know.

Today, Professor Snyder joins host Bob Hughes to discuss the impact of big data on human health. He reviews the results of his research, carried out on 109 people including himself, which entails collecting numerous types of health data and building an informative data profile, as opposed to the traditional approach of collecting just a few pieces of information. He goes on to share his personal story of how collecting deep data on himself helped him change his lifestyle after being diagnosed as a type two diabetic - using precision medicine to control diabetes. Professor Snyder also explores how DNA methylation can be used to track aging patterns and ageotypes, as well as the relationship between aging and Big Data collection, and also discusses health and longevity from his viewpoint, particularly from the standpoint of boosting the immune system.

In this episode, you’ll learn how Big Data can influence our health, and why Professor Snyder believes that the transformation of healthcare begins with deep-diving into data.

Episode Highlights:

●  Understanding precision medicine and personalized medicine

●  How Big Data influences individual health

●  Professor Snyder’s research results on 109 people

●  The impacts of deep data profiles

●  How Professor Snyder changed his lifestyle after deep-diving into his data

●  Using precision medicine to control diabetes

●  DNA Methylation and tracking aging patterns

●  Selection criteria for the 109 research subjects

●  Professor Snyder’s growth over the years from yeast biology

●  Human health and longevity from Professor Snyder’s viewpoint

Quotes:

“We're actually much more focused, I would say, on precision health, trying to keep people healthy at an individualized level, and trying to use big data to do just that.”

“We're in a world now where you can just collect so much deeper data on people.”

“I liken it to a jigsaw puzzle. If I want to see what the picture is in a puzzle, looking at one or two pieces of a 1000 person puzzle isn't going to tell me the picture, even 15 pieces probably won't do it. But I want to look at as many pieces as possible. And that's what big data is all about.”

“One aspect is to collect data, the other is to do it over time.”

“A lot of people who survived the COVID infections wind up being type two diabetics on a 4% increase, which is a pretty large number of people.”

“Everybody has different aging patterns, and so the way we think about this is like a car. Your car as a whole gets older over time, but some parts wear out first. ”

“Having good biomarkers for aging, we think, is a big deal.”

“Why are we measuring 15 things? We should be measuring thousands.”

“There's a ton of investment going into longevity these days - billions of dollars now into these new startups.”

“Your immune system starts plummeting in your 60s, as I say, and that just leaves you more and more vulnerable anytime after that.”

“I think we can transform healthcare. I think you'll see big changes in the next 10 years in terms of home testing, all this sort of stuff.”

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Genomics and Personalized Medicine: What Everyone Needs to Know