Jonathan Judd, Jeffrey P Spence, Jonathan K Pritchard, Linda Kachuri, John S Witte
{"title":"Investigating the Role of Neighborhood Socioeconomic Status and Germline Genetics on Prostate Cancer Risk","authors":"Jonathan Judd, Jeffrey P Spence, Jonathan K Pritchard, Linda Kachuri, John S Witte","doi":"10.1101/2024.07.31.24311312","DOIUrl":null,"url":null,"abstract":"Background: Genetic factors play an important role in prostate cancer (PCa)\ndevelopment with polygenic risk scores (PRS) predicting disease risk across genetic\nancestries. However, there are few convincing modifiable factors for PCa and little is\nknown about their potential interaction with genetic risk. We analyzed incident PCa\ncases (n=6,155) and controls (n=98,257) of European and African ancestry from the\nUK Biobank (UKB) cohort to evaluate the role of neighborhood socioeconomic status\n(nSES)-and how it may interact with PRS-on PCa risk. Methods: We evaluated a multi-ancestry PCa PRS containing 269 genetic variants to\nunderstand the association of germline genetics with PCa in UKB. Using the English\nIndices of Deprivation, a set of validated metrics that quantify lack of resources within\ngeographical areas, we performed logistic regression to investigate the main effects\nand interactions between nSES deprivation, PCa PRS, and PCa. Results: The PCa PRS was strongly associated with PCa (OR=2.04;\n95%CI=2.00-2.09; P<0.001). Additionally, nSES deprivation indices were inversely\nassociated with PCa: employment (OR=0.91; 95%CI=0.86-0.96; P<0.001), education\n(OR=0.94; 95%CI=0.83-0.98; P<0.001), health (OR=0.91; 95%CI=0.86-0.96;\nP<0.001), and income (OR=0.91; 95%CI=0.86-0.96; P<0.001). The PRS effects\nshowed little heterogeneity across nSES deprivation indices, except for the Townsend\nIndex (P=0.03) Conclusions: We reaffirmed genetics as a risk factor for PCa and identified nSES\ndeprivation domains that influence PCa detection and are potentially correlated with\nenvironmental exposures that are a risk factor for PCa. These findings also suggest\nthat nSES and genetic risk factors for PCa act independently.","PeriodicalId":501071,"journal":{"name":"medRxiv - Epidemiology","volume":"57 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"medRxiv - Epidemiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.07.31.24311312","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Genetic factors play an important role in prostate cancer (PCa)
development with polygenic risk scores (PRS) predicting disease risk across genetic
ancestries. However, there are few convincing modifiable factors for PCa and little is
known about their potential interaction with genetic risk. We analyzed incident PCa
cases (n=6,155) and controls (n=98,257) of European and African ancestry from the
UK Biobank (UKB) cohort to evaluate the role of neighborhood socioeconomic status
(nSES)-and how it may interact with PRS-on PCa risk. Methods: We evaluated a multi-ancestry PCa PRS containing 269 genetic variants to
understand the association of germline genetics with PCa in UKB. Using the English
Indices of Deprivation, a set of validated metrics that quantify lack of resources within
geographical areas, we performed logistic regression to investigate the main effects
and interactions between nSES deprivation, PCa PRS, and PCa. Results: The PCa PRS was strongly associated with PCa (OR=2.04;
95%CI=2.00-2.09; P<0.001). Additionally, nSES deprivation indices were inversely
associated with PCa: employment (OR=0.91; 95%CI=0.86-0.96; P<0.001), education
(OR=0.94; 95%CI=0.83-0.98; P<0.001), health (OR=0.91; 95%CI=0.86-0.96;
P<0.001), and income (OR=0.91; 95%CI=0.86-0.96; P<0.001). The PRS effects
showed little heterogeneity across nSES deprivation indices, except for the Townsend
Index (P=0.03) Conclusions: We reaffirmed genetics as a risk factor for PCa and identified nSES
deprivation domains that influence PCa detection and are potentially correlated with
environmental exposures that are a risk factor for PCa. These findings also suggest
that nSES and genetic risk factors for PCa act independently.