Premium Only Content

New Biologic Age Clock Revealed by Dr. Varun Dwaraka
In this video, Dr. Sanjeev Goel and Dr. Varun Dwaraka, Head of Bioinformatics at TruDiagnostic, discuss biologic age testing, focusing on DNA methylation and epigenetics.
📚 PURCHASE DR. SANJEEV GOEL'S BOOK "The Top 10 Must Do Peak Human Biohacks of 2023"📚
→ iBooks: https://books.apple.com/ca/book/top-10-must-do-peak-human-biohacks-of-2023/id6448680046
→ Kobo: https://www.kobo.com/ca/en/ebook/the-top-10-must-do-peak-human-biohacks-of-2023
→ Amazon - https://www.amazon.com/dp/B0C1J2N1YF
📚 Purchase the Peak Longevity Prediction Pack 📚
→ https://peakhuman.ca/product/peak-longevity-pack/?v=3e8d115eb4b3
********************
Visit our website: https://peakhuman.ca/?v=3e8d115eb4b3
Shop here: https://peakhuman.ca/shop/
SUBSCRIBE TODAY: https://bit.ly/PeakHumanLabs
They explore how epigenetic changes occur with aging, affecting gene expression. The conversation touches on the history of epigenetic clocks, aiming to predict biological age beyond chronological age. They introduce the DunedinPACE Clock, which shows promise in improving accuracy. TruDiagnostic's OM Clock integrates various data layers, providing a comprehensive aging assessment. It predicts health outcomes with higher sensitivity and specificity than existing clocks and undergoes ongoing research for response to interventions. For more details, visit www.trudiagnostic.com or connect with Dr. Varun Dwaraka on LinkedIn or Instagram.
Varun Dwaraka PhD is the Head of Bioinformatics at TruDiagnostic, and an aging and longevity investigator specializing in epigenetics and bioinformatics. He has co-authored numerous publications relating to genetics, epigenetic clocks, DNA methylation, and tissue regeneration. In 2020, Dr. Dwaraka was elected as a full member to the Sigma Xi, The Scientific Research Honor Society, and currently serves as a 2023 Foresight Fellow in Biotechnology and Health Expansion, awarded by the Foresight Institute. He also serves on the Scientific Advisory Board for SRW Labs based in New Zealand, offering insight into the application and interpretation of epigenetic age biomarkers. Dr. Dwaraka is passionate about implementing machine learning methods to advance predictive medicine, identify novel biomarkers, and create algorithms to better understand the biology of aging.
******************
TIMESTAMP
0:00 - Intro
2:08 - Dr. Varun discusses the history of epigenetic clocks.
3:03 - Dr. Varun explains DNA methylation.
5:33 - Discussion about the effects of DNA methylation on gene expression.
8:24 - Dr. Varun talks about changes in methylation patterns with age.
9:00 - Introduction to Dr. Steven Horvath's work on epigenetic clocks.
10:14 - Dr. Horvath's role in the development of epigenetic clocks.
11:03 - The limitation of predicting chronological age accurately.
13:05 - DunedinPace Clock and its significance.
15:17 - Pace of Aging score.
15:33 - Explaining the concept of the Pace of Aging score.
16:10 - Describing the bounds of the Pace of Aging score.
17:00 - Question about the validity and frequency of the Pace of Aging score.
18:05 - Discussing how quickly the Pace of Aging score can change.
19:25 - Speculating on the reduced risk of mortality.
21:02 - Discussing variations in methylation patterns between tissues.
23:11 - Mention of the commonality and differences between aging clocks.
24:04 - Comparison of shared CpGs between different aging clocks.
25:26 - Discussion of differences in CpGs selected by different clocks.
26:06 - Question about similarities in aging CpGs across different species.
27:00 - Mention of a mammal clock that is conserved across species.
28:25 - Introduction to the development of the Omic Clock by True Diagnostic.
29:57 - Partnership with Brigham and Women's Hospital for data collection.
30:14 - Idea of combining different layers for a multi-omic inferred clock.
31:22 - Elastic net regression to identify relevant phenotypes.
31:49 - Training to predict time until death.
32:21 - Identification of factors associated with increasing EMR age.
33:03 - Incorporating additional data such as proteins, clinical values, and metabolites.
33:57 - Mention of generating EMR age.
34:03 - Integration of various data types into the clock.
35:00 - Creation of models to predict proteins, clinical values, and metabolites.
36:02 - Reducing the number of models to focus on relevant features.
37:01 - Explanation of correlation and filtering based on correlation values.
38:01 - Introduction of the "omic age" and its importance.
39:36 - Discussion of the omic age and its association with diseases.
40:00 - Explanation of odds ratios and their significance.
42:15 - Comparison of different clocks in terms of sensitivity and specificity.
43:05 - Mention of future testing of interventions on omic age.
#Epigenetics #BiologicAgeClock #Aging
-
LIVE
Laura Loomer
2 hours agoEP135: Champagne Communism: Zohran Mamdani's Ugandan Compound EXPOSED
971 watching -
28:39
The Why Files
3 days agoCryptids Vol. 4 | Bunyips, Yowie and Australian Nightmare Fuel
18.2K35 -
1:07:06
Mike Rowe
18 days agoThe Fight For America's Heartland | Salena Zito #442 | The Way I Heard It
14.6K44 -
2:43:30
TimcastIRL
3 hours agoSouth Park Goes FULL CHARLIE KIRK, Latest Episode ROASTS Trump Again | Timcast IRL
163K50 -
LIVE
SpartakusLIVE
3 hours agoThe Return of the KING of Content
464 watching -
10:05
MattMorseTV
6 hours ago $2.97 earnedHe actually did it...
22.2K13 -
LIVE
Anthony Rogers
1 day agoEpisode 376 - Todd Schowalter
92 watching -
LIVE
megimu32
2 hours agoOTS: Movie Tie-In Games + Remakes: Let’s Play Memory Lane
138 watching -
Adam Does Movies
10 hours ago $0.18 earnedTalking Movies + Ask Me Anything - LIVE
6.19K -
1:17:18
Glenn Greenwald
1 day agoWhat are CBS News' Billionaire Heirs Doing with Bari Weiss? With Ryan Grim on the Funding Behind It; Europe Capitulates to Trump Again | SYSTEM UPDATE #494
94.4K63