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Supplementary Material for: comorbidPGS: an R package assessing shared predisposition between Phenotypes using Polygenic Scores

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posted on 2024-05-11, 07:05 authored by Pascat V., Zudina L., Ulrich A., Maina J.G., Kaakinen M., Pupko I., Bonnefond A., Demirkan A., Balkhiyarova Z., Froguel P., Prokopenko I.
Introduction Polygenic Score (PGS) is a valuable method for assessing the estimated genetic liability to a given outcome or genetic variability contributing to a quantitative trait. While PRSs are widely used for complex traits, their application in uncovering shared genetic predisposition between phenotypes, i.e. when genetic variants influence more than one phenotype, remains limited. Methods We developed an R package, comorbidPGS, which facilitates a systematic evaluation of shared genetic effects among (cor)related phenotypes using PGSs. The comorbidPGS package takes as input a set of Single Nucleotide Polymorphisms (SNPs) along with their established effects on the original phenotype (Po), referred to as Po-PGS. It generates a comprehensive summary of effect(s) of Po-PGS on target phenotype(s) (Pt) with customisable graphical features. Results We applied comorbidPGS to investigate the shared genetic predisposition between phenotypes defining elevated blood pressure (Systolic Blood Pressure, SBP; Diastolic Blood Pressure, DBP; Pulse Pressure, PP) and several cancers (Breast Cancer, BrC; Pancreatic Cancer, PanC; Kidney Cancer, KidC; Prostate Cancer, PrC; Colorectal Cancer, CrC) using the European ancestry UK Biobank individuals and GWAS meta-analyses summary statistics from independent set of European ancestry individuals. We report a significant association between elevated DBP and the genetic risk of PrC (β (SE)=0.066 (0.017), P-value=9.64×10^(-5)), as well as between CrC PGS and both, lower SBP (β (SE)=-0.10 [0.029], P-value=3.83×10^(-4))) and lower DBP (β (SE)=-0.055 [0.017], P-value=1.05×10^(-3)). Our analysis highlights two nominally significant relationships for individuals with genetic predisposition to elevated SBP leading to higher risk of KidC (OR [95%CI]=1.04 [1.0039-1.087], P-value=2.82×10^(-2)) and PrC (OR [95%CI]=1.02 [1.003-1.041], P-value=2.22×10^(-2)). Conclusion Using comorbidPGS, we underscore mechanistic relationships between blood pressure regulation and susceptibility to three comorbid malignancies. This package offers valuable means to evaluate shared genetic susceptibility between (cor)related phenotypes through polygenic scores.

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