Recent News & Updates
Jan 20, 2023 - Highlighted in USA Today:
We can now measure thousands of protein, fat and metabolic molecules from a single drop of blood.
Published in Nature Biomedical Engineering:
Multi-omics microsampling for the profiling of lifestyle-associated changes in health:
Current healthcare practices are reactive and use limited physiological and clinical information, often collected months or years apart. Moreover, the discovery and profiling of blood biomarkers in clinical and research settings are constrained by geographical barriers, the cost and inconvenience of in-clinic venepuncture, low sampling frequency and the low depth of molecular measurements.
Current healthcare practices are reactive and use limited physiological and clinical information, often collected months or years apart. Moreover, the discovery and profiling of blood biomarkers in clinical and research settings are constrained by geographical barriers, the cost and inconvenience of in-clinic venepuncture, low sampling frequency and the low depth of molecular measurements.
Here we describe a strategy for the frequent capture and analysis of thousands of metabolites, lipids, cytokines and proteins in 10 μl of blood alongside physiological information from wearable sensors.
January 11, 2023 - Featured in Futurity:
BIOMARKERS CAN POINT TO RIGHT DIET FOR WEIGHT LOSS
Published December 2022 - Cell Press Journal:
A new analysis of data from a yearlong weight-loss study identifies behaviors and biomarkers that contribute to short- and long-term weight loss.
“Weight loss is enigmatic and complicated, but we can predict from the outset with the microbiome and metabolic biomarkers who will lose the most weight and who will keep it off.” -Michael Snyder
Distinct factors associated with short-term and long-term weight loss induced by low-fat or low-carbohydrate diet intervention
Highlights
•Distinct variables are associated with short-term and long-term weight-loss success
•The primary drivers for short-term weight loss are diet adherence and diet quality
•Long-term weight loss is related to personal multi-omics markers at baseline
•Baseline factors (e.g., RQ) can suggest precision approaches to weight loss
Summary
To understand what determines the success of short- and long-term weight loss, we conduct a secondary analysis of dietary, metabolic, and molecular data collected from 609 participants before, during, and after a 1-year weight-loss intervention with either a healthy low-carbohydrate (HLC) or a healthy low-fat (HLF) diet.
2022 Mental Healthcare Innovations Summit
A collaboration with the Tony Blair Institute for Global Change and the Stanford Healthcare Innovation Lab
October 6, 2022
Snyder Lab's Postdoctoral Research Fellow, Ariel Ganz launched this goundbreaking summit to raise awareness of cutting-edge mental health therapies and bringing together stakeholders across government, policy, research, funding, and advocacy.
Keynote speakers and guests included:
- Michael Snyder, PhD
- Surgeon General of California, Diana Ramos, MD, MPH, MBA, FACOG
- Congresswoman Anna G. Eshoo
- Selena Marie Gomez , Singer, songwriter, entrepreneur, and mental health advocate
Artificial Intelligence, Genes and Ethics
September 2022
- What is AI and why is it sometimes biased?
- How will AI affect medicine to help us but also what are theconditions in which it may harm us.
Will Earth one day be populated by beings who are different from us in their cognitiveand physical abilities.
This course will look at the intersection of AI and Genetics to analyze advancesthat could be made but also ethical questions that should be asked.
Research revealing key exposome findings featured on the cover of Cell Systems
Published in the August & September 2022 issue
Highlights
- Machine learning combines GWAS with single-cell omics to discover COVID-19 risk genes
- The discovered severe COVID-19 risk genes account for 77% of the observed heritability
- Genetic risk for severe COVID-19 is focused within NK cells and T cells
- Mendelian randomization and single-cell multiomics highlight CD56bright NK cells
Summary
Sai Zhang, Johnathan Cooper-Knock, Annika K. Weimer, Minyi Shi, Lina Kozhaya, Derya Unutmaz, Calum Harvey, Thomas H.Julian, Simone Furini, Elisa Frullanti, FrancescaFava, Alessandra Renieri, Peng Gao, Xiaotao Shen, Ilia Sarah Timpanaro, Kevin P. Kenna, J. Kenneth Baillie, Mark M. Davis, Michael P. Snyder
Introducing TidyMass: A new solution for reproducibility, traceability and transparency metabolomics data analysis
July 28, 2022
Published today in Nature Communications, a solution for the long-standing issues of reproducibility, traceability and transparency for metabolomics data analysis. Here, the authors present the TidyMass project (https://www.tidymass.org/), a comprehensive R-based computational framework that can achieve the traceable, shareable, and reproducible workflow needs of data processing and analysis for LC-MS-based untargeted metabolomics. TidyMass is an ecosystem of R packages that share an underlying design philosophy, grammar, and data structure, which provides a comprehensive, reproducible, and object-oriented computational framework. Find the full publication here: https://lnkd.in/geYuuyhC Visit the TidyMass website: https://www.tidymass.org/
Groundbreaking research, featured on the cover of Genome Research
Published in the June & July 2022 issue
Featuring the first study integrating external exposures and internal biomolecular profiles together to see how the exposome shaped the human phenotypes leading to thousands of significant associations that are valuable resources for future exposome-phenome interactions studies.
In this issue, thousands of longitudinally measured chemical and biological components along with physical factors in the personal exposome cloud were investigated for their impact on internal -omes, such as the proteome, metabolome, gut microbiome, as well as cytokines and blood markers. On the cover, the dynamic and diverse exposomics profile is depicted as a mixture and its complex interactions with the gut microbiome and internal biomolecules in various organs is illustrated. These potential gene–environment interactions elucidate how the exposome shapes human phenome and impacts precision health. Cover artwork by Lettie McGuire. [For details, see Gao et al., pp. 1199–1214.])
Explore Precision Medicine, Big Data & Artifical Intelligence
July 18-29, 2022
Explore Our Exciting Summer Virtual Workshop
For US & International Students Ages 16+ -
Explore cutting-edge, deep medicine topics including wearable health devices, artificial intelligence, infectious disease detection, cancer genomics, and more.
https://tinyurl.com/5d75bbf7
Dr. Snyder gives a talk at EverythingALS on our new Genomic ML method for deciphering genetics of complex disease. https://www.youtube.com/watch?v=JGjYG4MY64U
Read the research paper: Genome-wide identification of the genetic basis of amyotrophic lateral sclerosis
In this study, we built a real-time smartwatch-based alerting system that detects aberrant physiological and activity signals (heart rates and steps) associated with the onset of early infection and implemented this system in a prospective study. Early detection of infectious diseases is crucial for reducing transmission and facilitating early intervention. In this study, we built a real-time smartwatch-based alerting system that detects aberrant physiological and activity signals (heart rates and steps) associated with the onset of early infection and implemented this system in a prospective study. In a cohort of 3,318 participants, of whom 84 were infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), this system generated alerts for pre-symptomatic and asymptomatic SARS-CoV-2 infection in 67 (80%) of the infected individuals.
Landmark Study Published in Nature Medicine
In this study, we built a real-time smartwatch-based alerting system that detects aberrant physiological and activity signals (heart rates and steps) associated with the onset of early infection and implemented this system in a prospective study. Early detection of infectious diseases is crucial for reducing transmission and facilitating early intervention. In this study, we built a real-time smartwatch-based alerting system that detects aberrant physiological and activity signals (heart rates and steps) associated with the onset of early infection and implemented this system in a prospective study. In a cohort of 3,318 participants, of whom 84 were infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), this system generated alerts for pre-symptomatic and asymptomatic SARS-CoV-2 infection in 67 (80%) of the infected individuals.
Body Count
December 2021 : How Michael Snyder’s self-monitoring project could transform human health
"What Snyder wants everyone—patient and doctor—to grasp is that the biometric signature of health can look different from person to person. The current system, which evaluates whether someone is healthy according to norms averaged from the larger population, fails to account for how much variation exists among humans. The solution he envisions will require better smart wearables, better testing and better algorithms to crunch the vast data from a variety of “omes.” It will require start-ups to innovate technologies and make them accessible. And it will demand an overhaul of health care so that people can be alerted when their biometrics change and a doctor can investigate what has gone awry..."