Sex dependent genetic architecture of biochemically verified tobacco use

IF 4.2 2区医学 Q1 PSYCHIATRY

Psychiatry Research Pub Date : 2025-03-26 DOI:10.1016/j.psychres.2025.116465

Meghan J. Chenoweth , Caryn Lerman , Jo Knight , Rachel F. Tyndale

{"title":"Sex dependent genetic architecture of biochemically verified tobacco use","authors":"Meghan J. Chenoweth , Caryn Lerman , Jo Knight , Rachel F. Tyndale","doi":"10.1016/j.psychres.2025.116465","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>Tobacco 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.</div></div><div><h3>Methods</h3><div>We conducted a genome-wide genotype-by-sex (GxS) interaction analysis of COT and COT+3HC measured from blood in European treatment-seeking smokers (<em>n</em> = 541 males, <em>n</em> = 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.</div></div><div><h3>Results</h3><div>For COT, five suggestive (<em>P</em> < 5 × 10<sup>–6</sup>) loci on chr 4, 15, 19, 12, and 1 were identified; the top variant was rs11520555 (5′ of <em>SPOCK3</em>; beta=0.38, se=0.08, GxS <em>P</em> = 7.39 × 10<sup>–7</sup>). 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 <em>HSPA13</em>; beta=0.33, se=0.06, GxS <em>P</em> = 3.48 × 10<sup>–7</sup>). 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.</div></div><div><h3>Conclusions</h3><div>Our 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.</div></div><div><h3>Implications</h3><div>This 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.</div></div>","PeriodicalId":20819,"journal":{"name":"Psychiatry Research","volume":"348 ","pages":"Article 116465"},"PeriodicalIF":4.2000,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Psychiatry Research","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0165178125001131","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHIATRY","Score":null,"Total":0}

引用次数: 0

Abstract

Background

Tobacco 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.

Methods

We 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.

Results

For 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.

Conclusions

Our 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.

Implications

This 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.

查看原文本刊更多论文

求助全文

约1分钟内获得全文求助全文

来源期刊

Psychiatry Research 医学-精神病学

CiteScore

17.40

自引率

1.80%

发文量

527

审稿时长

57 days

期刊介绍： Psychiatry Research offers swift publication of comprehensive research reports and reviews within the field of psychiatry. The scope of the journal encompasses: Biochemical, physiological, neuroanatomic, genetic, neurocognitive, and psychosocial determinants of psychiatric disorders. Diagnostic assessments of psychiatric disorders. Evaluations that pursue hypotheses about the cause or causes of psychiatric diseases. Evaluations of pharmacologic and non-pharmacologic psychiatric treatments. Basic neuroscience studies related to animal or neurochemical models for psychiatric disorders. Methodological advances, such as instrumentation, clinical scales, and assays directly applicable to psychiatric research.