Nathan Youlton

ORCID: 0000-0002-3427-8743
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About
Contact & Profiles
Research Areas
  • CRISPR and Genetic Engineering
  • RNA and protein synthesis mechanisms
  • Genetic Associations and Epidemiology
  • Cardiomyopathy and Myosin Studies
  • Congenital heart defects research
  • SARS-CoV-2 and COVID-19 Research
  • Cardiac Fibrosis and Remodeling
  • Immune responses and vaccinations
  • Respiratory viral infections research
  • RNA regulation and disease
  • Virology and Viral Diseases
  • Viral Infections and Immunology Research
  • Liver Disease Diagnosis and Treatment
  • Animal Virus Infections Studies

United States Nuclear Regulatory Commission
2024

Stanford University
2021-2023

Stanford Medicine
2022

The SARS-CoV-2 pandemic has differentially impacted populations across race and ethnicity. A multi-omic approach represents a powerful tool to examine risk multi-ancestry genomes. We leverage tracking strategy in which we sequence viral host genomes transcriptomes from nasopharyngeal swabs of 1049 individuals (736 positive 313 negative) integrate them with digital phenotypes electronic health records diverse catchment area Northern California. Genome-wide association disaggregated by...

10.1038/s41467-022-32397-8 article EN cc-by Nature Communications 2022-08-30

Abstract The combinatorial effect of genetic variants is often assumed to be additive. Although variation can clearly interact non-additively, methods uncover epistatic relationships remain in their infancy. We develop low-signal signed iterative random forests elucidate the complex architecture cardiac hypertrophy. derive deep learning-based estimates left ventricular mass from MRI scans 29,661 individuals enrolled UK Biobank. report including close CCDC141 , IGF1R TTN and TNKS. Several...

10.1101/2023.11.06.23297858 preprint EN cc-by-nc-nd medRxiv (Cold Spring Harbor Laboratory) 2023-11-09

The combinatorial effect of genetic variants is often assumed to be additive. Although variation can clearly interact non-additively, methods uncover epistatic relationships remain in their infancy. We develop low-signal signed iterative random forests elucidate the complex architecture cardiac hypertrophy. derive deep learning-based estimates left ventricular mass from MRI scans 29,661 individuals enrolled UK Biobank. report including close

10.21203/rs.3.rs-3509208/v1 preprint EN cc-by Research Square (Research Square) 2023-11-20

To realize the potential of genome engineering therapeutics, tractable strategies must be identified that balance personalized therapy with need for off-the-shelf availability. We hypothesized regional clustering pathogenic variants can inform design rational prime editing therapeutics to treat majority genetic cardiovascular diseases a limited number reagents.

10.1161/circgen.123.004370 article EN Circulation Genomic and Precision Medicine 2024-03-20

ABSTRACT The SARS-CoV-2 pandemic has differentially impacted populations of varied race, ethnicity and socioeconomic status. Admixture mapping local ancestry inference represent powerful tools to examine genetic risk within multi-ancestry genomes independent these confounding social constructs. Here, we leverage a tracking strategy in which sequence viral host transcriptomes from 1,327 nasopharyngeal swab residuals integrate them with digital phenotypes electronic health records. We...

10.1101/2021.08.04.21261547 preprint EN medRxiv (Cold Spring Harbor Laboratory) 2021-08-08

This protocol outlines the induction and correction of mutagenesis in HEK293T cells using CRISPR-X prime editing.

10.17504/protocols.io.b5jrq4m6 preprint EN 2022-02-24

Abstract Recent rise in the number and therapeutic potential of genome engineering technologies has generated excitement cardiovascular genetics. One significant barrier to their implementation is costly time consuming reagent development for novel unique variants. Prior data have illuminated regional clustering disease-causing genetic variants known functional protein domains. We hypothesized that most disease-relevant genes ClinVar would display variant clustering, multiple within a...

10.1101/2022.03.03.22271786 preprint EN medRxiv (Cold Spring Harbor Laboratory) 2022-03-08

Recent rise in the number and therapeutic potential of genome engineering technologies has generated excitement cardiovascular genetics. One significant barrier to their implementation is costly time consuming reagent development for novel unique variants. Prior data have illuminated regional clustering disease-causing genetic variants known functional protein domains. We hypothesized that most disease-relevant genes ClinVar would display variant clustering, multiple within a hotspot could...

10.1161/circ.146.suppl_1.11527 article EN Circulation 2022-11-08
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