Vincent Pascat, Liudmila Zudina, Anna Ulrich, Jared G Maina, Marika Kaakinen, Igor Pupko, Amélie Bonnefond, Ayse Demirkan, Zhanna Balkhiyarova, Philippe Froguel, Inga Prokopenko
{"title":"comorbidPGS：使用多基因评分评估表型之间共同易感性的 R 软件包。","authors":"Vincent Pascat, Liudmila Zudina, Anna Ulrich, Jared G Maina, Marika Kaakinen, Igor Pupko, Amélie Bonnefond, Ayse Demirkan, Zhanna Balkhiyarova, Philippe Froguel, Inga Prokopenko","doi":"10.1159/000539325","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>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 polygenic risk scores 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.</p><p><strong>Methods: </strong>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 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.</p><p><strong>Results: </strong>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) and several cancers (breast cancer; 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).</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":13226,"journal":{"name":"Human Heredity","volume":null,"pages":null},"PeriodicalIF":1.1000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"comorbidPGS: An R Package Assessing Shared Predisposition between Phenotypes Using Polygenic Scores.\",\"authors\":\"Vincent Pascat, Liudmila Zudina, Anna Ulrich, Jared G Maina, Marika Kaakinen, Igor Pupko, Amélie Bonnefond, Ayse Demirkan, Zhanna Balkhiyarova, Philippe Froguel, Inga Prokopenko\",\"doi\":\"10.1159/000539325\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>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 polygenic risk scores 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.</p><p><strong>Methods: </strong>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 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.</p><p><strong>Results: </strong>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) and several cancers (breast cancer; 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).</p><p><strong>Conclusion: </strong>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.</p>\",\"PeriodicalId\":13226,\"journal\":{\"name\":\"Human Heredity\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2024-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Human Heredity\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1159/000539325\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/5/13 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q4\",\"JCRName\":\"GENETICS & HEREDITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Human Heredity","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1159/000539325","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/5/13 0:00:00","PubModel":"Epub","JCR":"Q4","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
comorbidPGS: An R Package Assessing Shared Predisposition between Phenotypes Using Polygenic Scores.
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 polygenic risk scores 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 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) and several cancers (breast cancer; 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.
期刊介绍：
Gathering original research reports and short communications from all over the world, ''Human Heredity'' is devoted to methodological and applied research on the genetics of human populations, association and linkage analysis, genetic mechanisms of disease, and new methods for statistical genetics, for example, analysis of rare variants and results from next generation sequencing. The value of this information to many branches of medicine is shown by the number of citations the journal receives in fields ranging from immunology and hematology to epidemiology and public health planning, and the fact that at least 50% of all ''Human Heredity'' papers are still cited more than 8 years after publication (according to ISI Journal Citation Reports). Special issues on methodological topics (such as ‘Consanguinity and Genomics’ in 2014; ‘Analyzing Rare Variants in Complex Diseases’ in 2012) or reviews of advances in particular fields (‘Genetic Diversity in European Populations: Evolutionary Evidence and Medical Implications’ in 2014; ‘Genes and the Environment in Obesity’ in 2013) are published every year. Renowned experts in the field are invited to contribute to these special issues.
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