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Article: Genetic Susceptibility for Low Testosterone in Men and Its Implications in Biology and Screening: Data from the UK Biobank

TitleGenetic Susceptibility for Low Testosterone in Men and Its Implications in Biology and Screening: Data from the UK Biobank
Authors
KeywordsExpression quantitative trait locus
Genetic risk score
Genome-wide association study
Testosterone
Issue Date2021
Citation
European Urology Open Science, 2021, v. 29, p. 36-46 How to Cite?
AbstractBackground: Despite strong evidence of heritability, few studies have attempted to unveil the genetic underpinnings of testosterone levels. Objective: To identify testosterone-associated loci in a large study and assess their biological and clinical implications. Design, setting, and participants: The participants were men from the UK Biobank. A two-stage genome-wide association study (GWAS) was first used to identify/validate loci for low testosterone (LowT, <8 nmol/l) in 80% of men (N = 148 902). The cumulative effect of independent LowT risk loci was then evaluated in the remaining 20% of men. Outcome measurements and statistical analysis: Associations of single nucleotide polymorphisms (SNPs) with LowT were tested using an additive model. Analyses of the expression quantitative trait loci (eQTLs) were performed to assess the associations between significant SNPs and expression of nearby genes (within 1 Mbp). A genetic risk score (GRS) was used to assess the cumulative effect of multiple independent SNPs on LowT risk. Results and limitations: The two-stage GWAS found SNPs in 141 loci of 41 cytobands that were significantly associated with LowT (p < 5 × 10–8), including 94 novel loci from 38 cytobands. An eQTL analysis of these 141 loci revealed significant associations with RNA expression of 155 genes, including previously implicated (SHBG and JMJD1C) and novel (LIN28B, LCMT2, and ZBTB4) genes. Among the 141 loci, 42 were independently associated with LowT after a multivariable analysis. The GRS based on these 42 loci was significantly associated with LowT risk in independent individuals (N = 37 225, ptrend = 3.16 × 10–162). The risk ratio for LowT between men in the top and those in the bottom GRS deciles was 4.98-fold. Results are limited in generalizability as only Caucasians were studied. Conclusions: Identification of the genetic variants associated with LowT may improve our understanding of its etiology and identify high-risk men for LowT screening. Patient summary: We identified 141 new genetic loci that can be incorporated into a genetic risk score that can potentially identify men with low testosterone.
Persistent Identifierhttp://hdl.handle.net/10722/314410
ISSN
2021 Impact Factor: 3.000
2020 SCImago Journal Rankings: 0.421
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorFantus, Richard J.-
dc.contributor.authorNa, Rong-
dc.contributor.authorWei, Jun-
dc.contributor.authorShi, Zhuqing-
dc.contributor.authorResurreccion, W. Kyle-
dc.contributor.authorHalpern, Joshua A.-
dc.contributor.authorFranco, Omar-
dc.contributor.authorHayward, Simon W.-
dc.contributor.authorIsaacs, William B.-
dc.contributor.authorZheng, S. Lilly-
dc.contributor.authorXu, Jianfeng-
dc.contributor.authorHelfand, Brian T.-
dc.date.accessioned2022-07-20T12:03:59Z-
dc.date.available2022-07-20T12:03:59Z-
dc.date.issued2021-
dc.identifier.citationEuropean Urology Open Science, 2021, v. 29, p. 36-46-
dc.identifier.issn2666-1691-
dc.identifier.urihttp://hdl.handle.net/10722/314410-
dc.description.abstractBackground: Despite strong evidence of heritability, few studies have attempted to unveil the genetic underpinnings of testosterone levels. Objective: To identify testosterone-associated loci in a large study and assess their biological and clinical implications. Design, setting, and participants: The participants were men from the UK Biobank. A two-stage genome-wide association study (GWAS) was first used to identify/validate loci for low testosterone (LowT, <8 nmol/l) in 80% of men (N = 148 902). The cumulative effect of independent LowT risk loci was then evaluated in the remaining 20% of men. Outcome measurements and statistical analysis: Associations of single nucleotide polymorphisms (SNPs) with LowT were tested using an additive model. Analyses of the expression quantitative trait loci (eQTLs) were performed to assess the associations between significant SNPs and expression of nearby genes (within 1 Mbp). A genetic risk score (GRS) was used to assess the cumulative effect of multiple independent SNPs on LowT risk. Results and limitations: The two-stage GWAS found SNPs in 141 loci of 41 cytobands that were significantly associated with LowT (p < 5 × 10–8), including 94 novel loci from 38 cytobands. An eQTL analysis of these 141 loci revealed significant associations with RNA expression of 155 genes, including previously implicated (SHBG and JMJD1C) and novel (LIN28B, LCMT2, and ZBTB4) genes. Among the 141 loci, 42 were independently associated with LowT after a multivariable analysis. The GRS based on these 42 loci was significantly associated with LowT risk in independent individuals (N = 37 225, ptrend = 3.16 × 10–162). The risk ratio for LowT between men in the top and those in the bottom GRS deciles was 4.98-fold. Results are limited in generalizability as only Caucasians were studied. Conclusions: Identification of the genetic variants associated with LowT may improve our understanding of its etiology and identify high-risk men for LowT screening. Patient summary: We identified 141 new genetic loci that can be incorporated into a genetic risk score that can potentially identify men with low testosterone.-
dc.languageeng-
dc.relation.ispartofEuropean Urology Open Science-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectExpression quantitative trait locus-
dc.subjectGenetic risk score-
dc.subjectGenome-wide association study-
dc.subjectTestosterone-
dc.titleGenetic Susceptibility for Low Testosterone in Men and Its Implications in Biology and Screening: Data from the UK Biobank-
dc.typeArticle-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1016/j.euros.2021.04.010-
dc.identifier.scopuseid_2-s2.0-85106530428-
dc.identifier.volume29-
dc.identifier.spage36-
dc.identifier.epage46-
dc.identifier.eissn2666-1683-
dc.identifier.isiWOS:000668351000008-

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