New machine learning algorithm from Stanford team leads to the discovery of hundreds of potential drug targets for ALS

Stanford Healthcare Innovation Team
Feb 3, 2022

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In this study, Dr. Michael Snyder and his team found nearly seven hundred risk genes related to ALS (Amyotrophic Lateral Sclerosis) using a novel machine learning method, leading to a 5-fold increase in recovered heritability. Their findings give light to new potential drug pathways, and open up the possibility of more genes to explore in connection to ALS.

Only fifteen genes have been identified to contribute to the onset of ALS, and a small group of people possesses mutations in those genes. Many more genes are suspected to be involved, but ALS researchers usually only examine one gene at a time. 

RefMap: A new machine learning method for analysis of GWAS summary statistics

The team developed a novel method for examining genes, using a machine learning algorithm named RefMap. RefMap can integrate genome-wide association data with functional genomic data. This method allows them to scour through massive data sets from genomic screens to determine the wide range of genes potentially associated with ALS. The researchers looked for genes common in ALS patients that supported motor neuron function and found 690 candidate genes. Most of the genes were found in the axon of the cell contributing to the hypothesis that axon defects may have a causative relationship with ALS.

RefMap identifies ALS risk genes by integrating ALS GWAS data with the molecular profiling of motor neurons

KANK1: a new ALS gene

KANK1 is a notable gene the researchers found. Through repeated experiments, the team found that defects in KANK1 contributed to the loss of a protein TDP-43 from the nucleus of motor neurons, a major sign of ALS in most people.

While more research remains to be done, this discovery opens exciting new pathways for targeted treatment plans for those with ALS.

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Michael Snyder, PhD, PresidentBiden and Rob Moritz, PhD
Michael Snyder, PhD, President Biden and Rob Moritz, PhD, supporting healthcare, science and genetic research at the highest level

Michael Snyder, PhD, President Biden and Rob Moritz, PhD, supporting healthcare, science and genetic research at the highest level

Supporting Hupo.org, Presdient Biden met with Michael Snyder, PhD and Rob Moritz to support science progress and the life-saving effects of Dr. Michael Snyder's ground breaking research in preventing diseases and key discoveries improving human health.

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Multiomic analysis reveals cell-type-specific molecular determinants of COVID-19 severity

Multiomic analysis reveals cell-type-specific molecular determinants of COVID-19 severity

Featured on this month's August & September 2022 Cover of Cell Systems.

On the cover: Natural killer (NK) cells (pale blue) attacking SARS-CoV-2 viruses (red) with machine learning methodology signified by patterned numerals. In this issue of Cell Systems, Zhang et al. (p. 598) propose a machine learning method that integrates single-cell mult-iomic data with GWAS summary statistics to discover cell-type-specific disease risk genes. Application to severe COVID-19 identifies over 1,000 risk genes in 19 human lung cell types. Genetic risk is found to be enriched within NK cells and CD56 bright cytokine-producing NK cells.

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Snyder Lab Cell Report Journal Cover
Transcriptomic and proteomic data, cell lines, and cell culture resources that may be broadly enabling for non-human primate iPSC research

Transcriptomic and proteomic data, cell lines, and cell culture resources that may be broadly enabling for non-human primate iPSC research

Featured on the cover of Cell Reports journal August 2022: Dr. Michael Snyder and team have released key findings.

This work is a step forward leveraging primate stem cells for future of organ generation. A significant potential of this work is to utilize generation of primates (including human) tissues and organs to reduce, refine and eventually replace the use of animals in biomedical research.

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Michael P. Snyder, PhD Attends the Inauguration of Amrita Hospital
Dr. Michael Snyder delivers Health Innovation keynote at Amrita University and meets India’s Prime Minister Narendra Modi in New Delhi, August 22-25, 2022

Dr. Michael Snyder delivers Health Innovation keynote at Amrita University and meets India’s Prime Minister Narendra Modi in New Delhi, August 22-25, 2022

While in India as a featured distinguished speaker for the International Summit on Health Innovation Grand Challenges & Global Collaborations, Michael P. Snyder, PhD attended the inauguration of Amrita Hospital, Faridabad with Prime Minister Narendra Modi, Spiritual Leader Mata Amritanandamayi (Amma), Dr. Girija V, Dr. Krish Ramachandran and other supporters, ushering in the country’s largest private hospital.

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A cancer-associated RNA polymerase III identity drives robust transcription and expression of snaR-A noncoding RNA

Results from this research support a model in which Pol III identity functions as an important transcriptional regulatory mechanism. Upregulation of POLR3G, which is driven by MYC, identifies a subgroup of patients with unfavorable survival outcomes in specific cancers, further implicating the POLR3G-enhanced transcription repertoire as a potential disease
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Michael Snyder Interviewed by CBS News
CBS News Interviews Michael Snyder About Our Wearables Research Study and Self-Tracking Your Health Data.

CBS News Interviews Michael Snyder About Our Wearables Research Study and Self-Tracking Your Health Data.

"Stanford School of Medicine professor Michael Snyder is conducting several studies to see how far wearables can go in detecting disease. "You don't drive your car around without a dashboard," he said. "Yet, here we are as people. We're more important than cars, but we're running around without any sensors, most people. And we should be wearing these things, in my opinion, because they can alert you to early things."

Media Spotlight News
Illustration of Michael P. Snyder from Body Count Article in Stanford Magazine
Body Count, how Michael Snyder’s self-monitoring project could transform human health

Body Count, how Michael Snyder’s self-monitoring project could transform human health

"You prick your fingertip, put it on a sensor, and more biometrics scroll along the glass, all in blue, none in red to flag an anomaly."

"This is the future that Michael Snyder, director of the Center for Genomics and Personalized Medicine and chair of the department of genetics, wants for everyone on Earth. He’s already cobbling it together for himself. Each morning, he straps on four smartwatches and an Exposometer to measure levels of airborne particles. He has a continuous glucose monitor for his blood sugar and an Oura ring to track his sleep." Read More >

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Stanford’s large-scale, real-time monitoring & alerting system detects 80% of COVID-19 illnesses at or prior to symptom onset

Harnessing wearable data, the first large-scale, real-time monitoring & alerting system from Stanford detects abnormal physiological events, such as COVID-19 and other respiratory illnesses.

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Longitudinal data study shows gut microbiome diversity changes at the subspecies level during antibiotic treatment

Longitudinal data study shows gut microbiome diversity changes at the subspecies level during antibiotic treatment

Published as the August 2021 Genome Research cover publication, a Stanford research team found evolutionary & ecological changes in human gut microbiome subspecies during antibiotic treatment based on longitudinal data.

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A virtual workshop experience from Stanford Medicine featuring topics such as personalized medicine, big data, & AI
Personalized Medicine, Big Data, & AI Explorers, a new virtual summer workshop from Stanford Medicine

Personalized Medicine, Big Data, & AI Explorers, a new virtual summer workshop from Stanford Medicine

A virtual, two-week summer intensive workshop from Stanford Medicine for students 16 and older that transports participants to the forefront of healthcare innovation research featuring topics such as precision health, big data, & AI.

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Dr. Michael Snyder discusses deep profiling for personalized medicine on Rhonda Patrick’s FoundMyFitness Podcast

Dr. Michael Snyder discusses deep profiling for personalized medicine on Rhonda Patrick’s FoundMyFitness Podcast

Dr. Michael Snyder, a pioneer in longitudinal profiling and personalized medicine, speaks with Rhonda Patrick about his team's work at Stanford, covering areas such as CGMs, multiomics, and wearable data.

New Publication
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Real-time alerting system for COVID-19 using wearable data – Stanford preprint available now

Real-time alerting system for COVID-19 using wearable data – Stanford preprint available now

Our preprint for Phase 2 of our COVID-19 wearable study is available now! This is the 1st large-scale real-time monitoring and alerting system for detecting abnormal physiological changes, including COVID-19 and other respiratory illnesses, using smartwatch data.

Research Study
Clinician giving a vaccination
A new research study from Stanford Medicine featuring molecular profiling of COVID-19 vaccine response utilizing at-home microsampling

A new research study from Stanford Medicine featuring molecular profiling of COVID-19 vaccine response utilizing at-home microsampling

A new study from Stanford Medicine aims to understand the differences in individual responses to COVID-19 infection and response to vaccination using microsampling.

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cloud computing
Insights in the future of cloud computing and its impact on healthcare applications

Insights in the future of cloud computing and its impact on healthcare applications

Dr. Amir Bahmani, Director of Science & Technology at our lab, discussed the future of cloud computing and its impact on healthcare applications with Eric Schmidt, co-founder of Schmidt Futures and former CEO of Google, and Mark Russinovich, CTO of Microsoft Azure.

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