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Alcohol and nicotine polygenic scores are associated with the development of alcohol and nicotine use problems from adolescence to young adulthood.

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Title: Alcohol and nicotine polygenic scores are associated with the development of alcohol and nicotine use problems from adolescence to young adulthood.
Authors: Deak, Joseph D. (AUTHOR), Clark, D. Angus (AUTHOR), Liu, Mengzhen (AUTHOR), Schaefer, Jonathan D. (AUTHOR), Jang, Seon Kyeong (AUTHOR), Durbin, C. Emily (AUTHOR), Iacono, William G. (AUTHOR), McGue, Matt (AUTHOR), Vrieze, Scott (AUTHOR), Hicks, Brian M. (AUTHOR)
Source: Addiction. Apr2022, Vol. 117 Issue 4, p1117-1127. 11p. 1 Diagram, 3 Charts, 1 Graph.
Subjects: Substance abuse risk factors, Research, Structural equation modeling, Risk-taking behavior, Genetics, Nicotine, Binge drinking, Molecular biology, Risk assessment, Alcohol drinking, Teenagers' conduct of life, Smoking, Statistical correlation, Adults, Adolescence
Geographic Terms: United States
Abstract: Background and Aims: Molecular genetic studies of alcohol and nicotine use have identified many genome‐wide association study (GWAS) loci. We measured associations between drinking and smoking polygenic scores (PGS) and trajectories of alcohol and nicotine use outcomes from late childhood to early adulthood, substance‐specific versus broader‐liability PGS effects, and if PGS performance varied for consumption versus problematic substance use. Design, setting, participants and measurements: We fitted latent growth curve models with structured residuals to scores on measures of alcohol and nicotine use and problems from ages 14 to 34 years. We then estimated associations between the intercept (initial status) and slope (rate of change) parameters and PGSs for drinks per week (DPW), problematic alcohol use (PAU), cigarettes per day (CPD) and ever being a regular smoker (SMK), controlling for sex and genetic principal components. All data were analyzed in the United States. PGSs were calculated for participants of the Minnesota Twin Family Study (n = 3225) using results from the largest GWAS of alcohol and nicotine consumption and problematic use to date. Findings Each PGS was associated with trajectories of use for their respective substances [i.e. DPW (βmean = 0.08; βrange = 0.02–0.12) and PAU (βmean = 0.12; βrange = −0.02 to 0.31) for alcohol; CPD (βmean = 0.08; βrange = 0.04–0.14) and SMK (βmean = 0.18; βrange = 0.05–0.36) for nicotine]. The PAU and SMK PGSs also exhibited cross‐substance associations (i.e. PAU for nicotine‐specific intercepts and SMK for alcohol intercepts and slope). All identified SMK PGS effects remained as significant predictors of nicotine and alcohol trajectories (βmean = 0.15; βrange = 0.02–0.33), even after adjusting for the respective effects of all other PGSs. Conclusions: Substance use‐related polygenic scores (PGSs) vary in the strength and generality versus specificity of their associations with substance use and problems over time. The regular smoking PGS appears to be a robust predictor of substance use trajectories and seems to measure both nicotine‐specific and non‐specific genetic liability for substance use, and potentially externalizing problems in general. [ABSTRACT FROM AUTHOR]
Copyright of Addiction is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Alcohol and nicotine polygenic scores are associated with the development of alcohol and nicotine use problems from adolescence to young adulthood.
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  Data: <searchLink fieldCode="AR" term="%22Deak%2C+Joseph+D%2E%22">Deak, Joseph D.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Clark%2C+D%2E+Angus%22">Clark, D. Angus</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Liu%2C+Mengzhen%22">Liu, Mengzhen</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Schaefer%2C+Jonathan+D%2E%22">Schaefer, Jonathan D.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Jang%2C+Seon+Kyeong%22">Jang, Seon Kyeong</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Durbin%2C+C%2E+Emily%22">Durbin, C. Emily</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Iacono%2C+William+G%2E%22">Iacono, William G.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22McGue%2C+Matt%22">McGue, Matt</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Vrieze%2C+Scott%22">Vrieze, Scott</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Hicks%2C+Brian+M%2E%22">Hicks, Brian M.</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Addiction%22">Addiction</searchLink>. Apr2022, Vol. 117 Issue 4, p1117-1127. 11p. 1 Diagram, 3 Charts, 1 Graph.
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  Data: <searchLink fieldCode="DE" term="%22Substance+abuse+risk+factors%22">Substance abuse risk factors</searchLink><br /><searchLink fieldCode="DE" term="%22Research%22">Research</searchLink><br /><searchLink fieldCode="DE" term="%22Structural+equation+modeling%22">Structural equation modeling</searchLink><br /><searchLink fieldCode="DE" term="%22Risk-taking+behavior%22">Risk-taking behavior</searchLink><br /><searchLink fieldCode="DE" term="%22Genetics%22">Genetics</searchLink><br /><searchLink fieldCode="DE" term="%22Nicotine%22">Nicotine</searchLink><br /><searchLink fieldCode="DE" term="%22Binge+drinking%22">Binge drinking</searchLink><br /><searchLink fieldCode="DE" term="%22Molecular+biology%22">Molecular biology</searchLink><br /><searchLink fieldCode="DE" term="%22Risk+assessment%22">Risk assessment</searchLink><br /><searchLink fieldCode="DE" term="%22Alcohol+drinking%22">Alcohol drinking</searchLink><br /><searchLink fieldCode="DE" term="%22Teenagers'+conduct+of+life%22">Teenagers' conduct of life</searchLink><br /><searchLink fieldCode="DE" term="%22Smoking%22">Smoking</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+correlation%22">Statistical correlation</searchLink><br /><searchLink fieldCode="DE" term="%22Adults%22">Adults</searchLink><br /><searchLink fieldCode="DE" term="%22Adolescence%22">Adolescence</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22United+States%22">United States</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Background and Aims: Molecular genetic studies of alcohol and nicotine use have identified many genome‐wide association study (GWAS) loci. We measured associations between drinking and smoking polygenic scores (PGS) and trajectories of alcohol and nicotine use outcomes from late childhood to early adulthood, substance‐specific versus broader‐liability PGS effects, and if PGS performance varied for consumption versus problematic substance use. Design, setting, participants and measurements: We fitted latent growth curve models with structured residuals to scores on measures of alcohol and nicotine use and problems from ages 14 to 34 years. We then estimated associations between the intercept (initial status) and slope (rate of change) parameters and PGSs for drinks per week (DPW), problematic alcohol use (PAU), cigarettes per day (CPD) and ever being a regular smoker (SMK), controlling for sex and genetic principal components. All data were analyzed in the United States. PGSs were calculated for participants of the Minnesota Twin Family Study (n = 3225) using results from the largest GWAS of alcohol and nicotine consumption and problematic use to date. Findings Each PGS was associated with trajectories of use for their respective substances [i.e. DPW (βmean = 0.08; βrange = 0.02–0.12) and PAU (βmean = 0.12; βrange = −0.02 to 0.31) for alcohol; CPD (βmean = 0.08; βrange = 0.04–0.14) and SMK (βmean = 0.18; βrange = 0.05–0.36) for nicotine]. The PAU and SMK PGSs also exhibited cross‐substance associations (i.e. PAU for nicotine‐specific intercepts and SMK for alcohol intercepts and slope). All identified SMK PGS effects remained as significant predictors of nicotine and alcohol trajectories (βmean = 0.15; βrange = 0.02–0.33), even after adjusting for the respective effects of all other PGSs. Conclusions: Substance use‐related polygenic scores (PGSs) vary in the strength and generality versus specificity of their associations with substance use and problems over time. The regular smoking PGS appears to be a robust predictor of substance use trajectories and seems to measure both nicotine‐specific and non‐specific genetic liability for substance use, and potentially externalizing problems in general. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Addiction is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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    Identifiers:
      – Type: doi
        Value: 10.1111/add.15697
    Languages:
      – Code: eng
        Text: English
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        PageCount: 11
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    Subjects:
      – SubjectFull: Substance abuse risk factors
        Type: general
      – SubjectFull: Research
        Type: general
      – SubjectFull: Structural equation modeling
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      – SubjectFull: Risk-taking behavior
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      – SubjectFull: Genetics
        Type: general
      – SubjectFull: Nicotine
        Type: general
      – SubjectFull: Binge drinking
        Type: general
      – SubjectFull: Molecular biology
        Type: general
      – SubjectFull: Risk assessment
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      – SubjectFull: Alcohol drinking
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      – SubjectFull: Teenagers' conduct of life
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      – SubjectFull: Smoking
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      – SubjectFull: Adults
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      – SubjectFull: Adolescence
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      – SubjectFull: United States
        Type: general
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      – TitleFull: Alcohol and nicotine polygenic scores are associated with the development of alcohol and nicotine use problems from adolescence to young adulthood.
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              Text: Apr2022
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