Pathway Polygenic Risk Scores (pPRS) for the Analysis of Gene-environment Interaction

Gauderman, W. J.; Fu, Y.; Quem, B.; Kawaguchi, E.; Wang, Y.; Morrison, J.; Brenner, H.; Chan, A.; Gruber, S.; Temitope, K.; Li, L.; Moreno, V.; Pellatt, A.; Peters, U.; Samadder, N. J.; Schmit, S.; Ulrich, C.; Um, C.; Wu, A.; Lewinger, J. P.; Mi, H.; Drew, D.

doi:10.1101/2024.12.16.628610

Home/Archive/bioRxiv

bioRxiv · 10.1101/2024.12.16.628610

Pathway Polygenic Risk Scores (pPRS) for the Analysis of Gene-environment Interaction

View original source ↗Export metadata ↓

Abstract

A polygenic risk score (PRS) is used to quantify the combined disease risk of many genetic variants. For complex human traits there is interest in determining whether the PRS modifies, i.e. interacts with, important environmental (E) risk factors. Detection of a PRS by environment (PRS x E) interaction may provide clues to underlying biology and can be useful in developing targeted prevention strategies for modifiable risk factors. The standard PRS may include a subset of variants that interact with E but a much larger subset of variants that affect disease without regard to E. This latter subset will water down the underlying signal in former subset, leading to reduced power to detect PRS x E interaction. We explore the use of pathway-defined PRS (pPRS) scores, using state of the art tools to annotate subsets of variants to genomic pathways. We demonstrate via simulation that testing targeted pPRS x E interaction can yield substantially greater power than testing overall PRS x E interaction. We also analyze a large study (N=78,253) of colorectal cancer (CRC) where E = non-steroidal anti-inflammatory drugs (NSAIDs), a well-established protective exposure. While no evidence of overall PRS x NSAIDs interaction (p=0.41) is observed, a significant pPRS x NSAIDs interaction (p=0.0003) is identified based on SNPs within the TGF-{beta} / gonadotropin releasing hormone receptor (GRHR) pathway. NSAIDS is protective (OR=0.84) for those at the 5th percentile of the TGF-{beta}/GRHR pPRS (low genetic risk, OR), but significantly more protective (OR=0.70) for those at the 95th percentile (high genetic risk). From a biological perspective, this suggests that NSAIDs may act to reduce CRC risk specifically through genes in these pathways. From a population health perspective, our result suggests that focusing on genes within these pathways may be effective at identifying those for whom NSAIDs-based CRC-prevention efforts may be most effective. Author SummaryThe identification of polygenic risk score (PRS) by environment (PRSxE) interactions may provide clues to underlying biology and facilitate targeted disease prevention strategies. The standard approach to computing a PRS likely includes many variants that affect disease without regard to E, reducing power to detect PRS x E interactions. We utilize gene annotation tools to develop pathway-based PRS (pPRS) scores and show by simulation studies that testing pPRS x E interaction can yield substantially greater power than testing PRS x E, while also integrating biological knowledge into the analysis. We apply our method to a large study of colorectal cancer to identify a significant pPRS x NSAIDs interaction (p=0.0003) based on SNPs within the TGF-{beta} / gonadotropin releasing hormone receptor (GRHR) pathway. Our findings suggest that focusing on genetic susceptibility within biologically informed pathways may be more sensitive for identifying exposures that can be considered as part of a precision prevention approach.

Explore related subjects

genetics Preprint

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Gauderman, W. J., Fu, Y., Quem, B., Kawaguchi, E., Wang, Y., Morrison, J., Brenner, H., Chan, A., Gruber, S., Temitope, K., Li, L., Moreno, V., Pellatt, A., Peters, U., Samadder, N. J., Schmit, S., Ulrich, C., Um, C., Wu, A., Lewinger, J. P., Mi, H., Drew, D.. 2024-12-20. Pathway Polygenic Risk Scores (pPRS) for the Analysis of Gene-environment Interaction. https://doi.org/10.1101/2024.12.16.628610

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Pangenome Discoveries from Clinical Long-Read Genomes in Underrepresented Populations with Neurodevelopmental Disorders

Genetic diagnoses remain elusive for many individuals with neurodevelopmental disorders (NDDs), and the gap is wider in populations poorly represented in genomic reference resources. To demonstrate the equitable advantage of long-read whole genome sequencing (LR-WGS) and pangenomes in terms of clinical utility, we analyzed 211 NDD cases and 107 unaffected relatives from 24 populations, integrating their assemblies, resulting in a total of 1204 haplotypes with the Human Pangenome Reference Consortium Release 2 (HPRC_r2) and the Arab Pangenome Reference (APR) datasets. Clinical interpretation of small variants and structural variants (SVs) revealed pathogenic or likely pathogenic findings in 38.9% of the cases (82/211), and our workflow further detected pathogenic repeat expansions in 3.8% of the cases and runs of homozygosity (ROHs) exceeding 300 Mb in 4.7% of the cases, revealing substantial autozygosity suggestive of strong inbreeding. Beyond these clinical assessments, pangenome analysis revealed 3.9 million population-level novel small variants, 39,782 SVs and an average of 2.17 Mb of novel sequence per individual absent from linear references and global pangenomes. We identified 85.9 kb of case-unique nonreference sequences in exonic segments overlapping with curated NDD gene sets. Graph-based tertiary analysis further identified rare exonic complex homozygous rearrangements in the NDD associated genes for 2.4% of the cases. Together, these findings emphasize how diverse genome assemblies extend variant discovery beyond established linear reference-based clinical interpretation.

genetics↗

bioRxiv2026

Integrated exome-transcriptome analysis of a schizophrenia case with an exceptionally low polygenic risk score

Schizophrenia liability reflects both common polygenic variation and rarer variants of larger effect. We investigated a post-mortem schizophrenia case (SZ07) with a schizophrenia polygenic risk score below the first percentile among ancestry-matched cases, asking whether individual-level genomic and transcriptomic analyses could help identify potentially novel schizophrenia-relevant variants. We used exome analysis with multiple variant-prediction tools to generate a panel of variants and corresponding candidate genes potentially implicated in the pathological process in SZ07. The prioritised variants were then assessed using RNA sequencing of three cortical regions. Of these, only an IZUMO4 splice-acceptor variant showed direct RNA-level support. Beyond variant-specific analyses, we characterised broader transcriptomic abnormalities in the SZ07 brain. Pathway analysis of gene-level expression deviations implicated innate immune processes, calcium signalling, synaptic biology, and axon remodelling. Notably, compared with conventional single-sample biological pathway analysis, the analysis we used showed only a weak association with neuronal specificity, suggesting their reduced sensitivity to the main axis of variation related to cellular composition in bulk brain tissue gene expression data. Although the candidate genes showed no significant pathway-level convergence, the broader transcriptomic profile revealed coherent biological alterations largely compatible with the documented history of cerebrovascular disease in SZ07. These results demonstrate how the integration of exome and transcriptome data at the individual level enables the formulation and constraint of hypotheses regarding patient-specific genetic features and their molecular consequences, while highlighting important limitations related to tissue composition, comorbidity, and the choice of reference cohort.

genetics↗

bioRxiv2026

A genetic screen to identify host factors required for commensal bacterial adherence to the gut epithelia

Bacterial adherence to gut epithelial cells likely involves host genetic components. We isolated a gut commensal bacterium, Lelliottia jeotgali, that can robustly colonize C. elegans through attachment to intestinal epithelial cells. Here, we developed a novel screen in C. elegans to identify host genes required for microbiome bacterial colonization. Using transgenic L. jeotgali strain expressing tdTomato, we conducted forward genetic screens in C. elegans to select for mutants that completely lost colonization. We identified multiple allelic mutations in five different C. elegans genes, termed knockout of Lelliottia adherence (kola) mutants, with a near complete loss of adherence. Each of kola-1-5 is uncharacterized and predicted to encode for a secreted or membrane-bound protein. We also identified gly-5, a GalNAc transferase that initiates O-linked glycosylation. Overall, we describe the first C. elegans screen to identify host factors that control microbiome bacterial colonization in the gut.

genetics↗