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Sex dependent genetic architecture of biochemically verified tobacco use

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Sex dependent genetic architecture of biochemically verified tobacco use. / Chenoweth, M.J.; Lerman, C.; Knight, J. et al.
In: Psychiatry Research, Vol. 348, 116465, 30.06.2025.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Chenoweth, MJ, Lerman, C, Knight, J & Tyndale, RF 2025, 'Sex dependent genetic architecture of biochemically verified tobacco use', Psychiatry Research, vol. 348, 116465. https://doi.org/10.1016/j.psychres.2025.116465

APA

Chenoweth, M. J., Lerman, C., Knight, J., & Tyndale, R. F. (2025). Sex dependent genetic architecture of biochemically verified tobacco use. Psychiatry Research, 348, Article 116465. Advance online publication. https://doi.org/10.1016/j.psychres.2025.116465

Vancouver

Chenoweth MJ, Lerman C, Knight J, Tyndale RF. Sex dependent genetic architecture of biochemically verified tobacco use. Psychiatry Research. 2025 Jun 30;348:116465. Epub 2025 Apr 1. doi: 10.1016/j.psychres.2025.116465

Author

Chenoweth, M.J. ; Lerman, C. ; Knight, J. et al. / Sex dependent genetic architecture of biochemically verified tobacco use. In: Psychiatry Research. 2025 ; Vol. 348.

Bibtex

@article{c8414b290e5c466b8e4e66e7a937afda,
title = "Sex dependent genetic architecture of biochemically verified tobacco use",
abstract = "BackgroundTobacco use differs by genetics and sex, and dose-dependently increases the risk for numerous diseases. Nicotine is metabolized to cotinine (COT) which is further metabolized to 3′hydroxycotinine (3HC). COT and COT+3HC are biomarkers which capture tobacco intake more accurately than self-reported measures such as cigarettes/day. It is currently not known whether genetic risk factors for heavier tobacco intake, measured using these biomarkers, differ by sex.MethodsWe conducted a genome-wide genotype-by-sex (GxS) interaction analysis of COT and COT+3HC measured from blood in European treatment-seeking smokers (n = 541 males, n = 389 females) (NCT01314001). Linear regression models included Genotypes (coded additively), Sex, a GxS interaction term, covariates, and all covariate-by-genotype and covariate-by-sex interaction terms.ResultsFor COT, five suggestive (P < 5 × 10–6) loci on chr 4, 15, 19, 12, and 1 were identified; the top variant was rs11520555 (5′ of SPOCK3; beta=0.38, se=0.08, GxS P = 7.39 × 10–7). For COT+3HC, eight suggestive loci on chr 21, 18, 17 (2 loci), 13, 5, 8, and 19 were identified; the top variant was rs73157714 (3′ of HSPA13; beta=0.33, se=0.06, GxS P = 3.48 × 10–7). Overall, 26 genes were mapped, with 9 showing moderate to high expression in brain, and 5 showing prior associations with psychiatric traits in the GWAS Catalog.ConclusionsOur findings suggest that the genetic architecture of tobacco intake, measured accurately using biomarkers, differs between women and men. A more granular understanding of factors influencing tobacco intake in women versus men may identify risk factors for heavier use and sex-specific opportunities to promote smoking cessation and mitigate disease risk.ImplicationsThis genome-wide interaction study suggested that some of the genetic influences on tobacco intake, measured accurately using biomarkers, differ by sex. The loci identified in our study could be a starting point for developing new genetic biomarkers that predict sex-specific differences in tobacco intake and disease risk.",
author = "M.J. Chenoweth and C. Lerman and J. Knight and R.F. Tyndale",
year = "2025",
month = apr,
day = "1",
doi = "10.1016/j.psychres.2025.116465",
language = "English",
volume = "348",
journal = "Psychiatry Research",
issn = "0165-1781",
publisher = "Elsevier Ireland Ltd",

}

RIS

TY - JOUR

T1 - Sex dependent genetic architecture of biochemically verified tobacco use

AU - Chenoweth, M.J.

AU - Lerman, C.

AU - Knight, J.

AU - Tyndale, R.F.

PY - 2025/4/1

Y1 - 2025/4/1

N2 - BackgroundTobacco use differs by genetics and sex, and dose-dependently increases the risk for numerous diseases. Nicotine is metabolized to cotinine (COT) which is further metabolized to 3′hydroxycotinine (3HC). COT and COT+3HC are biomarkers which capture tobacco intake more accurately than self-reported measures such as cigarettes/day. It is currently not known whether genetic risk factors for heavier tobacco intake, measured using these biomarkers, differ by sex.MethodsWe conducted a genome-wide genotype-by-sex (GxS) interaction analysis of COT and COT+3HC measured from blood in European treatment-seeking smokers (n = 541 males, n = 389 females) (NCT01314001). Linear regression models included Genotypes (coded additively), Sex, a GxS interaction term, covariates, and all covariate-by-genotype and covariate-by-sex interaction terms.ResultsFor COT, five suggestive (P < 5 × 10–6) loci on chr 4, 15, 19, 12, and 1 were identified; the top variant was rs11520555 (5′ of SPOCK3; beta=0.38, se=0.08, GxS P = 7.39 × 10–7). For COT+3HC, eight suggestive loci on chr 21, 18, 17 (2 loci), 13, 5, 8, and 19 were identified; the top variant was rs73157714 (3′ of HSPA13; beta=0.33, se=0.06, GxS P = 3.48 × 10–7). Overall, 26 genes were mapped, with 9 showing moderate to high expression in brain, and 5 showing prior associations with psychiatric traits in the GWAS Catalog.ConclusionsOur findings suggest that the genetic architecture of tobacco intake, measured accurately using biomarkers, differs between women and men. A more granular understanding of factors influencing tobacco intake in women versus men may identify risk factors for heavier use and sex-specific opportunities to promote smoking cessation and mitigate disease risk.ImplicationsThis genome-wide interaction study suggested that some of the genetic influences on tobacco intake, measured accurately using biomarkers, differ by sex. The loci identified in our study could be a starting point for developing new genetic biomarkers that predict sex-specific differences in tobacco intake and disease risk.

AB - BackgroundTobacco use differs by genetics and sex, and dose-dependently increases the risk for numerous diseases. Nicotine is metabolized to cotinine (COT) which is further metabolized to 3′hydroxycotinine (3HC). COT and COT+3HC are biomarkers which capture tobacco intake more accurately than self-reported measures such as cigarettes/day. It is currently not known whether genetic risk factors for heavier tobacco intake, measured using these biomarkers, differ by sex.MethodsWe conducted a genome-wide genotype-by-sex (GxS) interaction analysis of COT and COT+3HC measured from blood in European treatment-seeking smokers (n = 541 males, n = 389 females) (NCT01314001). Linear regression models included Genotypes (coded additively), Sex, a GxS interaction term, covariates, and all covariate-by-genotype and covariate-by-sex interaction terms.ResultsFor COT, five suggestive (P < 5 × 10–6) loci on chr 4, 15, 19, 12, and 1 were identified; the top variant was rs11520555 (5′ of SPOCK3; beta=0.38, se=0.08, GxS P = 7.39 × 10–7). For COT+3HC, eight suggestive loci on chr 21, 18, 17 (2 loci), 13, 5, 8, and 19 were identified; the top variant was rs73157714 (3′ of HSPA13; beta=0.33, se=0.06, GxS P = 3.48 × 10–7). Overall, 26 genes were mapped, with 9 showing moderate to high expression in brain, and 5 showing prior associations with psychiatric traits in the GWAS Catalog.ConclusionsOur findings suggest that the genetic architecture of tobacco intake, measured accurately using biomarkers, differs between women and men. A more granular understanding of factors influencing tobacco intake in women versus men may identify risk factors for heavier use and sex-specific opportunities to promote smoking cessation and mitigate disease risk.ImplicationsThis genome-wide interaction study suggested that some of the genetic influences on tobacco intake, measured accurately using biomarkers, differ by sex. The loci identified in our study could be a starting point for developing new genetic biomarkers that predict sex-specific differences in tobacco intake and disease risk.

U2 - 10.1016/j.psychres.2025.116465

DO - 10.1016/j.psychres.2025.116465

M3 - Journal article

VL - 348

JO - Psychiatry Research

JF - Psychiatry Research

SN - 0165-1781

M1 - 116465

ER -