The ASHG Spring Symposium is a digital-only event over two half-days (April 8 and 9 from 9am-12pm Eastern) featuring talks about recent developments in cancer genetics and genomics. If you’re interested in seeing some of the modern approaches to the prediction and evolution of cancer, this symposium is for you. The presentations will cover predicting cancer risk, non-coding variation in cancer, understanding variant function, precision oncology, and new technical innovations. 

Session Descriptions 

April 8, Day One:

Deciphering Noncoding Regulation, 9:00am – 10:00am

Cancer genomics often focuses on the gain and loss of function variants in protein-coding genes. For this session, we’ll look at the role of non-coding DNA as a cancer driver. The featured talks will include mechanisms for non-coding regulatory regions and the function of some intronic variants. 

Genomics-Aided Precision Oncology, 10:00am – 11:00am

Oncology has been at the forefront of taking a “precision medicine” approach to individual patient care and genetic counseling for risk. In this session, we’ll hear about integrating genomics data into the care of patients, with experience ranging from single centers to nationwide cancer programs. 

Refining Variant Classification in Cancer, 11:00am – 12:00pm

In this session, you’ll learn about methods to help classify genetic variants associated with cancer. We will cover methods ranging from mechanistic studies using single-cell RNA-Seq and saturation mutagenesis to more informatic approaches.

April 9, Day Two:

Cancer Versus the Immune System, 9:00am – 10:00am

In this session, hear about advances in our understanding of the immune system's role in cancer control. Talks will include how tumors evade immune surveillance and how to predict response to immune checkpoint therapies based on machine learning assessment of tumor variant pathogenicity. 

Innovations in Cancer Genomics and Prediction, 10:00am – 11:00am

Genomic technologies evolve rapidly. This session will focus on cutting-edge techniques in cancer genomics, such as predicting original tumor anatomical location from their mutational pattern, cell-free DNA applications, and single-cell multiomics. 

Polygenic Models of Cancer Risk, 11:00am – 12:00pm

Single-point variant estimates of cancer risk can help guide care, but these variants act along with an individual’s other genetic variants. This session will take a broader view of risk assessment, including polygenic risk scores in breast cancer, risk integration in health care, and consideration of multiple population-enriched germline variants.

**Registration free for NIH employees. Please email us at digitalprograms@ashg.org for assistance.

In this seminar, Nara Sobreira, PhD, MD will present tools used to prioritize causative variants in the analysis of coding and non-coding variants when analyzing genomic data. The tools include PhenoDB, GeneMatcher, and VariantMatcher. PhenoDB is an accessible, freely available, web-based platform that allows users to store, share, analyze, and interpret their patients' phenotypes and variants from ES/GS data using a wide range of annotations and AI tools that facilitate the connection of causative genes to the phenotypes being investigated. GeneMatcher is accessible to all stakeholders as a web-based tool developed to connect individuals (researchers, clinicians, health care providers, and patients) around the globe with an interest in the same gene(s), variant(s), or phenotype(s). Finally, VariantMatcher was developed to enable public sharing of variant-level data and phenotypic information from individuals sequenced as part of multiple disease gene discovery projects. Dr. Nara Sobreira will explore the GA4GH tools used to connect these databases to others worldwide as part of the Matchmaker Exchange project.

Overview of Presentation:

• Introduce PhenoDB and outline a typical PhenoDB analysis pipeline.
• Describe GeneMatcher and highlight the ways it has facilitated disease gene discovery.
• Discuss VariantMatcher and the benefits of connecting databases that share variant-level and phenotypic information.

The March Journal Club will feature a talk on two recent papers published in the American Journal of Human Genetics:

Prequalification of genome-based newborn screening for severe childhood genetic diseases through federated training based on purifying hyperselection

Genome-based newborn screening for severe childhood genetic diseases has high positive predictive value and sensitivity in a NICU pilot trial

Dr. Gunn will discuss findings from a study leveraging data from Million Veterans Program and All of Us Research Program to compare methods for building polygenic scores (PGS) for multi-ancestry populations across multiple traits. 

Overview of Presentation

• Polygenic scores (PGS) are a promising tool for identifying people at high genetic risk of disease.
• However, PGS performance declines when scores are applied to target populations different from which they were derived, and most PGS were built with data from primarily European ancestry populations. 
• Our study investigates how to best build PGS for diverse, multi-ancestry populations, using GWAS results from the Million Veterans Program (MVP).
• We built polygenic scores (PGS) for ten complex traits using popular single and multi-ancestry Bayesian methods and evaluated these scores in the All of Us Research Program.
• Overall, we conclude that approaches which combine GWAS results from multiple populations produce scores that perform better than single-population approaches. 
• Our results contribute to the growing consensus that leveraging GWAS results from multiple-ancestry groups improves PGS performance in populations historically underrepresented in GWAS. 

Co-first authors Drs. Kullo and Nelson will present an introduction and overview of the NIH-funded PRIMED Consortium, which is working to improve polygenic risk prediction of a range of health outcomes across diverse, global populations. The presentation will cover design and rationale, organization and progress of Consortium activities, methodological innovations, and initial Consortium findings and products. 

Overview of Presentation

• PRIMED is developing new PRS methods with a focus on equitable performance across diverse populations, including those that are admixed 

• PRIMED is exploring different approaches to incorporate genetic ancestry information into PRS development and evaluation  

• PRIMED is developing approaches to integrate non-genetic information such as social determinants of health with PRS to create comprehensive risk prediction models  

• PRIMED is leveraging the AnVIL cloud platform for consortium data sharing and collaborative analysis and is making analysis workflows for PRS methods and related analyses publicly available  

• The PRIMED common data model supports constructing cross-study datasets with harmonized genotype, phenotype, and genomic summary results data

• PRIMED built off of the NASEM report on Population Descriptors in Genetics and Genomics Research to develop recommendations and a data model to support the flexible and ethical use of population descriptors in PRS research 

• Consortium website: https://primedconsortium.org
• Research Highlights: https://primedconsortium.org/research/highlights
• Data Model available on GitHub encoded as JSON: https://github.com/UW-GAC/primed_data_models
• Workflows for data validation and analysis available on Dockstore: https://dockstore.org/organizations/PRIMED
• Follow PRIMED on social media:
  • Twitter/X: https://x.com/PRSdiversity
  • Bluesky: https://bsky.app/profile/prsdiversity.bsky.social
  • LinkedIn: https://www.linkedin.com/company/primed-consortium/

A discussion of "A novel multivariable Mendelian randomization framework to disentangle highly correlated exposures with application to metabolomics"

A discussion of, "Structural and genetic diversity in the secreted mucins MUC5AC and MUC5B"

The NIH’s All of Us Research Program is committed to collecting multiple types of health data from a million or more participants to create a diverse research resource that accelerates precision medicine. The All of Us Researcher Workbench is the free-to-access secure, cloud-based platform where registered researchers from both US-based and international intuitions access and analyze data using Python, R, or SAS coding languages. Currently the program has over 413,000 program participants with >245,000 whole genome sequence (WGS) samples and >314,000 genotyping arrays. Looking forward, we anticipate counts for both WGS and arrays to surpass 400,000 soon. The genomic data is combined with many types of phenotypic and auxiliary data types including electronic health records (EHR), survey data, physical measurements, and mobile health data (Fitbit). This session will 1) provide an interactive, guided demonstration of the public facing genomic tools, including the new PheWAS x GWAS data browser 2) provide an interactive, guided demonstration of our cloud computing platform, the Researcher Workbench 3) provide participants a hands-on opportunity to replicate a research study with new genomic data types including structural variant and long reads data and 4) conduct an interactive Q&A session to engage attendees about the All of Us Researcher Workbench and the novel technology implemented to conduct genomic analyses.

Please note, to participate in the interactive activities included in this workshop, please register for the platform. This process may take a few hours; registrants are strongly encouraged to complete this by November 15. Platform registration is optional but highly recommended.

ASHG's 2024 Annual Meeting was hosted in Denver, Colorado from November 5 - 9.

This package includes the following recordings:

Sessions

• Presidential Welcome & Address
• Featured Plenary Abstract Session I
• Biobank Scale Genetic Data Resources for Studying Complex and Rare Human Diseases
• Multimodal Approaches to Interpreting the Non-Coding Genome: Evolution, Functional Genomics, and Machine Learning
• Novel Aspects of Modeling Genetic Architectures of Complex Traits
• Presidential Symposium: Mendelian Traits: Thinking about Complexity in the World of "Simple" Genetics
• TOPMed 10-Year Anniversary: Ongoing Success and Future Directions
• From Variant to Function: Prediction and Understanding Variants Function
• Computational Methods for Causal Variant Prioritization
• Featured Plenary Abstract Session II
• How Do We Describe and Ascribe Clinical Significance to the Non-coding Genome?
• Complex Traits and Other Omics
• Exploring Omics: From Genomes to Microbiomes
• Featured Plenary Abstract Session III
• The Promise and Payoff of Human Genetics and Genomics: Paths from Bench to Bedside

ASHG Events

• Career Development Panel: How to Set Yourself Apart
• ASHG Policy Forum: The Next Frontier of AI/ML in Human Genetics/Genomics
• Addressing the Challenges of Polygenic Scores in Human Genetic Research

Workshops

• Workshop: Hidden Features of the UCSC Genome Browser
• Workshop: Getting started with biomedical and genomic data in the All of Us Researcher Workbench

A major goal of human genetics and genomics research is to understand, treat, and correct genetic diseases and alleviate patient suffering. However, moving discoveries from the bench to the bedside can be both daunting and lengthy. The 2024 Distinguished Speakers Symposium will feature leaders who have made important basic science discoveries and navigated the journey from discovery to drug development, clinical trials, and implementation of new therapies. Their work has given hope to patients and framed the ethics, policy, and communication around ground-breaking genetics and genomics research.