2026 Sequencing Strategies for Population and Cancer Epidemiology Studies (SeqSPACE) : Submission #7
Submission information
Submission Number: 7
Submission ID: 182460
Submission UUID: 6b89bd0a-e6a0-4af8-9d53-7f14071a7844
Submission URI: /egrp/seqspaceabstracts
Submission View: /node/2144/webform/submissions/182460?token=4p5k0qt0K_qXYvoXvWsPHnxpaTWw090EZguczB66Wtg
Submission Update: /egrp/seqspaceabstracts?token=4p5k0qt0K_qXYvoXvWsPHnxpaTWw090EZguczB66Wtg
Created: Thu, 06/04/2026 - 03:01
Completed: Thu, 06/04/2026 - 03:01
Changed: Thu, 06/04/2026 - 03:01
Remote IP address: 10.208.28.22
Submitted by: Anonymous
Language: English
Is draft: No
Webform: seqspace (Abstracts)
Presenter Information
Julia
{Empty}
Steinberg
Ph.D
Genomics and Precision Health team lead and Adjunct Associate Professor [early-career faculty]
The Daffodil Centre, The University of Sydney, and Cancer Council NSW, Australia
Abstract Information
Low-coverage whole-genome-sequencing data for >7,400 Australians integrated with large-scale longitudinal health, socioeconomic, behaviour and linked medical data within the 45 and Up Study
Large-scale studies linking genomic and longitudinal health/medical data are highly valuable for population and cancer epidemiology research. In particular, the 45 and Up Study includes 267,357 participants age 45+ years recruited in 2005-2009, with extensive information on health and sociodemographic characteristics. As part of the Australian Cancer Risk Study, we invited 30,541 participants to provide a DNA sample, including a randomly selected sub-cohort (n=9,986), and all participants diagnosed with prostate, breast, melanoma and colorectal cancer who were alive in October 2021 (identified via linked NSW Cancer Registry data).
Overall, 8,311 participants consented (27%), and new genomic data were generated for 7,408 participants using low-coverage whole-genome sequencing (lcWGS; minimum=0.4X, median coverage=0.8X) and genotype imputation (GLIMPSE2, using well-established Gencove analysis pipeline).
Following in-depth sample- and variant-level quality checks (QC), we retained a final high-quality genomic dataset of 6,827 participants, including 6,631 unrelated European-ancestry individuals.
Supporting quality of post-QC data, we found excellent genotype concordance between lcWGS duplicates (n=85 individuals; r2>0.97), and of imputed lcWGS with additional new dense genotype array data (n=170 individuals; r2>0.9 for minor allele frequency ≥0.01).
In an illustrative analysis of leading cancer polygenic risk scores (PGS) for breast, prostate, melanoma, and colorectal cancers, 62-76% of PGS variants passed QC and were generally imputed with high confidence. The risk prediction performance of these PGS in our new data was comparable to previous studies for prostate, breast and melanoma (area-under-the-ROC-curve 0.66-0.68, 0.62, 0.64, respectively), but slightly reduced for colorectal cancer (~0.57 vs ~0.62). No PGS was significantly associated with cancer spread at diagnosis, and only prostate cancer PGS were significantly associated with younger age at diagnosis.
In conclusion, we present a major new high-quality genomics resource generated using low-coverage whole-genome-sequencing, readily integrated with longitudinal linked health data from the 45 and Up Study to support population and cancer epidemiology research.
Overall, 8,311 participants consented (27%), and new genomic data were generated for 7,408 participants using low-coverage whole-genome sequencing (lcWGS; minimum=0.4X, median coverage=0.8X) and genotype imputation (GLIMPSE2, using well-established Gencove analysis pipeline).
Following in-depth sample- and variant-level quality checks (QC), we retained a final high-quality genomic dataset of 6,827 participants, including 6,631 unrelated European-ancestry individuals.
Supporting quality of post-QC data, we found excellent genotype concordance between lcWGS duplicates (n=85 individuals; r2>0.97), and of imputed lcWGS with additional new dense genotype array data (n=170 individuals; r2>0.9 for minor allele frequency ≥0.01).
In an illustrative analysis of leading cancer polygenic risk scores (PGS) for breast, prostate, melanoma, and colorectal cancers, 62-76% of PGS variants passed QC and were generally imputed with high confidence. The risk prediction performance of these PGS in our new data was comparable to previous studies for prostate, breast and melanoma (area-under-the-ROC-curve 0.66-0.68, 0.62, 0.64, respectively), but slightly reduced for colorectal cancer (~0.57 vs ~0.62). No PGS was significantly associated with cancer spread at diagnosis, and only prostate cancer PGS were significantly associated with younger age at diagnosis.
In conclusion, we present a major new high-quality genomics resource generated using low-coverage whole-genome-sequencing, readily integrated with longitudinal linked health data from the 45 and Up Study to support population and cancer epidemiology research.