Robison, L. L. | Search bioRxiv

bioRxiv2020

Generalizability of "GWAS hits" in clinical populations: Lessons from childhood cancer survivors

With mounting interest in translating GWAS hits from large meta-analyses (meta-GWAS) in diverse clinical settings, evaluating their generalizability in target populations is crucial. Here we consider long-term survivors of childhood cancers from the St. Jude Lifetime Cohort Study and show the limited generalizability of 1,376 robust SNP associations reported in the general population across 12 complex anthropometric and cardiometabolic phenotypes (N=2,231; observed-to-expected replication ratio=0.68, P=2.4x10-9). An examination of five comparable phenotypes in a second independent cohort of survivors from the Childhood Cancer Survivor Study corroborated the overall limited generalizability of meta-GWAS hits to survivors (N=4,212, observed-to-expected replication ratio=0.53, P=1.1x10-16). Meta-GWAS hits were less likely to be replicated in survivors exposed to cancer therapies associated with phenotype risk. Examination of complementary DNA methylation data in a subset of survivors revealed that treatment-related methylation patterns at genomic sites linked to meta-GWAS hits may disrupt established genetic signals in survivors.

genetics↗

bioRxiv2018

Pediatric Cancer Variant Pathogenicity Information Exchange (PeCanPIE): A Cloud-based Platform for Curating and Classifying Germline Variants

Variant interpretation in the era of next-generation sequencing (NGS) is challenging. While many resources and guidelines are available to assist with this task, few integrated end-to-end tools exist. Here we present \"PeCanPIE\" - the Pediatric Cancer Variant Pathogenicity Information Exchange, a web- and cloud-based platform for annotation, identification, and classification of variations in known or putative disease genes. Starting from a set of variants in Variant Call Format (VCF), variants are annotated, ranked by putative pathogenicity, and presented for formal classification using a decision-support interface based on published guidelines from the American College of Medical Genetics and Genomics (ACMG). The system can accept files containing millions of variants and handle single-nucleotide variants (SNVs), simple insertions/deletions (indels), multiple-nucleotide variants (MNVs), and complex substitutions. PeCanPIE has been applied to classify variant pathogenicity in cancer predisposition genes in two large-scale investigations involving >4,000 pediatric cancer patients, and serves as a repository for the expert-reviewed results. While PeCanPIEs web-based interface was designed to be accessible to non-bioinformaticians, its back end pipelines may also be run independently on the cloud, facilitating direct integration and broader adoption. PeCanPIE is publicly available and free for research use.

bioinformatics↗