Smoking quit success genotype score predicts quit success and distinct patterns of developmental involvement with common addictive substances

Genotype scores that predict relevant clinical outcomes may detect other disease features and help direct prevention efforts. We report data that validate a previously-established v1.0 smoking cessation quit success genotype score and describe striking differences in the score in individuals who dis...

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Main Authors: Uhl, George R, Walther, Donna, Musci, Rashelle, Fisher, Christian, Anthony, James C, Storr, Carla L, Behm, Frederique M., Eaton, William W, Ialongo, Nicholas, Rose, Jed E.
Format: Online
Language:English
Published: 2012
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3922203/
id pubmed-3922203
recordtype oai_dc
spelling pubmed-39222032014-07-01 Smoking quit success genotype score predicts quit success and distinct patterns of developmental involvement with common addictive substances Uhl, George R Walther, Donna Musci, Rashelle Fisher, Christian Anthony, James C Storr, Carla L Behm, Frederique M. Eaton, William W Ialongo, Nicholas Rose, Jed E. Article Genotype scores that predict relevant clinical outcomes may detect other disease features and help direct prevention efforts. We report data that validate a previously-established v1.0 smoking cessation quit success genotype score and describe striking differences in the score in individuals who display differing developmental trajectories of use of common addictive substances. In a cessation study, v1.0 genotype scores predicted ability to quit with p = 0.00056 and area under ROC curve 0.66. About 43 vs 13% quit in the upper vs lower genotype score terciles. Latent class growth analyses of a developmentally-assessed sample identified three latent classes based on substance use. Higher v1.0 scores were associated with a) higher probabilities of participant membership in a latent class that displayed low use of common addictive substances during adolescence (p = 0.0004) and b) lower probabilities of membership in a class that reported escalating use (p = 0.001). These results suggest that: a) we have identified genetic predictors of smoking cessation success, b) genetic influences on quit success overlap with those that influence the rate at which addictive substance use is taken up during adolescence and c) individuals at genetic risk for both escalating use of addictive substances and poor abilities to quit may provide especially urgent focus for prevention efforts. 2012-11-06 2014-01 /pmc/articles/PMC3922203/ /pubmed/23128154 http://dx.doi.org/10.1038/mp.2012.155 Text en Users may view, print, copy, download and text and data- mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms
repository_type Open Access Journal
institution_category Foreign Institution
institution US National Center for Biotechnology Information
building NCBI PubMed
collection Online Access
language English
format Online
author Uhl, George R
Walther, Donna
Musci, Rashelle
Fisher, Christian
Anthony, James C
Storr, Carla L
Behm, Frederique M.
Eaton, William W
Ialongo, Nicholas
Rose, Jed E.
spellingShingle Uhl, George R
Walther, Donna
Musci, Rashelle
Fisher, Christian
Anthony, James C
Storr, Carla L
Behm, Frederique M.
Eaton, William W
Ialongo, Nicholas
Rose, Jed E.
Smoking quit success genotype score predicts quit success and distinct patterns of developmental involvement with common addictive substances
author_facet Uhl, George R
Walther, Donna
Musci, Rashelle
Fisher, Christian
Anthony, James C
Storr, Carla L
Behm, Frederique M.
Eaton, William W
Ialongo, Nicholas
Rose, Jed E.
author_sort Uhl, George R
title Smoking quit success genotype score predicts quit success and distinct patterns of developmental involvement with common addictive substances
title_short Smoking quit success genotype score predicts quit success and distinct patterns of developmental involvement with common addictive substances
title_full Smoking quit success genotype score predicts quit success and distinct patterns of developmental involvement with common addictive substances
title_fullStr Smoking quit success genotype score predicts quit success and distinct patterns of developmental involvement with common addictive substances
title_full_unstemmed Smoking quit success genotype score predicts quit success and distinct patterns of developmental involvement with common addictive substances
title_sort smoking quit success genotype score predicts quit success and distinct patterns of developmental involvement with common addictive substances
description Genotype scores that predict relevant clinical outcomes may detect other disease features and help direct prevention efforts. We report data that validate a previously-established v1.0 smoking cessation quit success genotype score and describe striking differences in the score in individuals who display differing developmental trajectories of use of common addictive substances. In a cessation study, v1.0 genotype scores predicted ability to quit with p = 0.00056 and area under ROC curve 0.66. About 43 vs 13% quit in the upper vs lower genotype score terciles. Latent class growth analyses of a developmentally-assessed sample identified three latent classes based on substance use. Higher v1.0 scores were associated with a) higher probabilities of participant membership in a latent class that displayed low use of common addictive substances during adolescence (p = 0.0004) and b) lower probabilities of membership in a class that reported escalating use (p = 0.001). These results suggest that: a) we have identified genetic predictors of smoking cessation success, b) genetic influences on quit success overlap with those that influence the rate at which addictive substance use is taken up during adolescence and c) individuals at genetic risk for both escalating use of addictive substances and poor abilities to quit may provide especially urgent focus for prevention efforts.
publishDate 2012
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3922203/
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