The CHRNA5/A3/B4 Gene Cluster and Tobacco, Alcohol, Cannabis, Inhalants and Other Substance Use Initiation: Replication and New Findings Using Mixture Analyses
Abstract Multiple studies have provided evidence for genetic associations between single nucleotide polymorphisms (SNPs) located on the CHRNA5/A3/B4 gene cluster and various phenotypes related to Nicotine Dependence (Greenbaum et al. 2009). Only a few studies have investigated other substances of ab...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Lubke, Gitta H. [verfasserIn] Stephens, Sarah H. [verfasserIn] Lessem, Jeffrey M. [verfasserIn] Hewitt, John K. [verfasserIn] Ehringer, Marissa A. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2012 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Behavior genetics - Dordrecht [u.a.] : Springer Science + Business Media B.V, 1970, 42(2012), 4 vom: 01. März, Seite 636-646 |
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| Übergeordnetes Werk: |
volume:42 ; year:2012 ; number:4 ; day:01 ; month:03 ; pages:636-646 |
| Links: |
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| DOI / URN: |
10.1007/s10519-012-9529-y |
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SPR01077467X |
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| 520 | |a Abstract Multiple studies have provided evidence for genetic associations between single nucleotide polymorphisms (SNPs) located on the CHRNA5/A3/B4 gene cluster and various phenotypes related to Nicotine Dependence (Greenbaum et al. 2009). Only a few studies have investigated other substances of abuse. The current study has two aims, (1) to extend previous findings by focusing on associations between the CHRNA5/A3/B4 gene cluster and age of initiation of several different substances, and (2) to investigate heterogeneity in age of initiation across the different substances. All analyses were conducted with a subset of the Add Health study with available genetic data. The first aim was met by modeling onset of tobacco, alcohol, cannabis, inhalants, and other substance use using survival mixture analysis (SMA). Ten SNPs in CHRNA5/A3/B4 were used to predict phenotypic differences in the risk of onset, and differences between users and non-users. The survival models aim at investigating differences in the risk of initiation across the 5–18 age range for each phenotype separately. Significant or marginally significant genetic effects were found for all phenotypes. The genetic effects were mainly related to the risk of initiation and to a lesser extent to discriminating between users and non-users. To address the second goal, the survival analyses were complemented by a latent class analysis that modeled all phenotypes jointly. One of the ten SNPs was found to predict differences between the early and late onset classes. Taken together, our study provides evidence for a general role of the CHRNA5/A3/B4 gene cluster in substance use initiation that is not limited to nicotine and alcohol. | ||
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| 650 | 4 | |a Nicotine initiation |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Substance use |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a CHRNA5/B3/A4 cluster |7 (dpeaa)DE-He213 | |
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| 700 | 1 | |a Ehringer, Marissa A. |e verfasserin |4 aut | |
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10.1007/s10519-012-9529-y doi (DE-627)SPR01077467X (SPR)s10519-012-9529-y-e DE-627 ger DE-627 rakwb eng 570 ASE 42.00 bkl Lubke, Gitta H. verfasserin aut The CHRNA5/A3/B4 Gene Cluster and Tobacco, Alcohol, Cannabis, Inhalants and Other Substance Use Initiation: Replication and New Findings Using Mixture Analyses 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Multiple studies have provided evidence for genetic associations between single nucleotide polymorphisms (SNPs) located on the CHRNA5/A3/B4 gene cluster and various phenotypes related to Nicotine Dependence (Greenbaum et al. 2009). Only a few studies have investigated other substances of abuse. The current study has two aims, (1) to extend previous findings by focusing on associations between the CHRNA5/A3/B4 gene cluster and age of initiation of several different substances, and (2) to investigate heterogeneity in age of initiation across the different substances. All analyses were conducted with a subset of the Add Health study with available genetic data. The first aim was met by modeling onset of tobacco, alcohol, cannabis, inhalants, and other substance use using survival mixture analysis (SMA). Ten SNPs in CHRNA5/A3/B4 were used to predict phenotypic differences in the risk of onset, and differences between users and non-users. The survival models aim at investigating differences in the risk of initiation across the 5–18 age range for each phenotype separately. Significant or marginally significant genetic effects were found for all phenotypes. The genetic effects were mainly related to the risk of initiation and to a lesser extent to discriminating between users and non-users. To address the second goal, the survival analyses were complemented by a latent class analysis that modeled all phenotypes jointly. One of the ten SNPs was found to predict differences between the early and late onset classes. Taken together, our study provides evidence for a general role of the CHRNA5/A3/B4 gene cluster in substance use initiation that is not limited to nicotine and alcohol. Survival mixture analysis (dpeaa)DE-He213 Nicotine initiation (dpeaa)DE-He213 Substance use (dpeaa)DE-He213 CHRNA5/B3/A4 cluster (dpeaa)DE-He213 Stephens, Sarah H. verfasserin aut Lessem, Jeffrey M. verfasserin aut Hewitt, John K. verfasserin aut Ehringer, Marissa A. verfasserin aut Enthalten in Behavior genetics Dordrecht [u.a.] : Springer Science + Business Media B.V, 1970 42(2012), 4 vom: 01. März, Seite 636-646 (DE-627)320524345 (DE-600)2014974-8 1573-3297 nnns volume:42 year:2012 number:4 day:01 month:03 pages:636-646 https://dx.doi.org/10.1007/s10519-012-9529-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 42.00 ASE AR 42 2012 4 01 03 636-646 |
| spelling |
10.1007/s10519-012-9529-y doi (DE-627)SPR01077467X (SPR)s10519-012-9529-y-e DE-627 ger DE-627 rakwb eng 570 ASE 42.00 bkl Lubke, Gitta H. verfasserin aut The CHRNA5/A3/B4 Gene Cluster and Tobacco, Alcohol, Cannabis, Inhalants and Other Substance Use Initiation: Replication and New Findings Using Mixture Analyses 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Multiple studies have provided evidence for genetic associations between single nucleotide polymorphisms (SNPs) located on the CHRNA5/A3/B4 gene cluster and various phenotypes related to Nicotine Dependence (Greenbaum et al. 2009). Only a few studies have investigated other substances of abuse. The current study has two aims, (1) to extend previous findings by focusing on associations between the CHRNA5/A3/B4 gene cluster and age of initiation of several different substances, and (2) to investigate heterogeneity in age of initiation across the different substances. All analyses were conducted with a subset of the Add Health study with available genetic data. The first aim was met by modeling onset of tobacco, alcohol, cannabis, inhalants, and other substance use using survival mixture analysis (SMA). Ten SNPs in CHRNA5/A3/B4 were used to predict phenotypic differences in the risk of onset, and differences between users and non-users. The survival models aim at investigating differences in the risk of initiation across the 5–18 age range for each phenotype separately. Significant or marginally significant genetic effects were found for all phenotypes. The genetic effects were mainly related to the risk of initiation and to a lesser extent to discriminating between users and non-users. To address the second goal, the survival analyses were complemented by a latent class analysis that modeled all phenotypes jointly. One of the ten SNPs was found to predict differences between the early and late onset classes. Taken together, our study provides evidence for a general role of the CHRNA5/A3/B4 gene cluster in substance use initiation that is not limited to nicotine and alcohol. Survival mixture analysis (dpeaa)DE-He213 Nicotine initiation (dpeaa)DE-He213 Substance use (dpeaa)DE-He213 CHRNA5/B3/A4 cluster (dpeaa)DE-He213 Stephens, Sarah H. verfasserin aut Lessem, Jeffrey M. verfasserin aut Hewitt, John K. verfasserin aut Ehringer, Marissa A. verfasserin aut Enthalten in Behavior genetics Dordrecht [u.a.] : Springer Science + Business Media B.V, 1970 42(2012), 4 vom: 01. März, Seite 636-646 (DE-627)320524345 (DE-600)2014974-8 1573-3297 nnns volume:42 year:2012 number:4 day:01 month:03 pages:636-646 https://dx.doi.org/10.1007/s10519-012-9529-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 42.00 ASE AR 42 2012 4 01 03 636-646 |
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10.1007/s10519-012-9529-y doi (DE-627)SPR01077467X (SPR)s10519-012-9529-y-e DE-627 ger DE-627 rakwb eng 570 ASE 42.00 bkl Lubke, Gitta H. verfasserin aut The CHRNA5/A3/B4 Gene Cluster and Tobacco, Alcohol, Cannabis, Inhalants and Other Substance Use Initiation: Replication and New Findings Using Mixture Analyses 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Multiple studies have provided evidence for genetic associations between single nucleotide polymorphisms (SNPs) located on the CHRNA5/A3/B4 gene cluster and various phenotypes related to Nicotine Dependence (Greenbaum et al. 2009). Only a few studies have investigated other substances of abuse. The current study has two aims, (1) to extend previous findings by focusing on associations between the CHRNA5/A3/B4 gene cluster and age of initiation of several different substances, and (2) to investigate heterogeneity in age of initiation across the different substances. All analyses were conducted with a subset of the Add Health study with available genetic data. The first aim was met by modeling onset of tobacco, alcohol, cannabis, inhalants, and other substance use using survival mixture analysis (SMA). Ten SNPs in CHRNA5/A3/B4 were used to predict phenotypic differences in the risk of onset, and differences between users and non-users. The survival models aim at investigating differences in the risk of initiation across the 5–18 age range for each phenotype separately. Significant or marginally significant genetic effects were found for all phenotypes. The genetic effects were mainly related to the risk of initiation and to a lesser extent to discriminating between users and non-users. To address the second goal, the survival analyses were complemented by a latent class analysis that modeled all phenotypes jointly. One of the ten SNPs was found to predict differences between the early and late onset classes. Taken together, our study provides evidence for a general role of the CHRNA5/A3/B4 gene cluster in substance use initiation that is not limited to nicotine and alcohol. Survival mixture analysis (dpeaa)DE-He213 Nicotine initiation (dpeaa)DE-He213 Substance use (dpeaa)DE-He213 CHRNA5/B3/A4 cluster (dpeaa)DE-He213 Stephens, Sarah H. verfasserin aut Lessem, Jeffrey M. verfasserin aut Hewitt, John K. verfasserin aut Ehringer, Marissa A. verfasserin aut Enthalten in Behavior genetics Dordrecht [u.a.] : Springer Science + Business Media B.V, 1970 42(2012), 4 vom: 01. März, Seite 636-646 (DE-627)320524345 (DE-600)2014974-8 1573-3297 nnns volume:42 year:2012 number:4 day:01 month:03 pages:636-646 https://dx.doi.org/10.1007/s10519-012-9529-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 42.00 ASE AR 42 2012 4 01 03 636-646 |
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10.1007/s10519-012-9529-y doi (DE-627)SPR01077467X (SPR)s10519-012-9529-y-e DE-627 ger DE-627 rakwb eng 570 ASE 42.00 bkl Lubke, Gitta H. verfasserin aut The CHRNA5/A3/B4 Gene Cluster and Tobacco, Alcohol, Cannabis, Inhalants and Other Substance Use Initiation: Replication and New Findings Using Mixture Analyses 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Multiple studies have provided evidence for genetic associations between single nucleotide polymorphisms (SNPs) located on the CHRNA5/A3/B4 gene cluster and various phenotypes related to Nicotine Dependence (Greenbaum et al. 2009). Only a few studies have investigated other substances of abuse. The current study has two aims, (1) to extend previous findings by focusing on associations between the CHRNA5/A3/B4 gene cluster and age of initiation of several different substances, and (2) to investigate heterogeneity in age of initiation across the different substances. All analyses were conducted with a subset of the Add Health study with available genetic data. The first aim was met by modeling onset of tobacco, alcohol, cannabis, inhalants, and other substance use using survival mixture analysis (SMA). Ten SNPs in CHRNA5/A3/B4 were used to predict phenotypic differences in the risk of onset, and differences between users and non-users. The survival models aim at investigating differences in the risk of initiation across the 5–18 age range for each phenotype separately. Significant or marginally significant genetic effects were found for all phenotypes. The genetic effects were mainly related to the risk of initiation and to a lesser extent to discriminating between users and non-users. To address the second goal, the survival analyses were complemented by a latent class analysis that modeled all phenotypes jointly. One of the ten SNPs was found to predict differences between the early and late onset classes. Taken together, our study provides evidence for a general role of the CHRNA5/A3/B4 gene cluster in substance use initiation that is not limited to nicotine and alcohol. Survival mixture analysis (dpeaa)DE-He213 Nicotine initiation (dpeaa)DE-He213 Substance use (dpeaa)DE-He213 CHRNA5/B3/A4 cluster (dpeaa)DE-He213 Stephens, Sarah H. verfasserin aut Lessem, Jeffrey M. verfasserin aut Hewitt, John K. verfasserin aut Ehringer, Marissa A. verfasserin aut Enthalten in Behavior genetics Dordrecht [u.a.] : Springer Science + Business Media B.V, 1970 42(2012), 4 vom: 01. März, Seite 636-646 (DE-627)320524345 (DE-600)2014974-8 1573-3297 nnns volume:42 year:2012 number:4 day:01 month:03 pages:636-646 https://dx.doi.org/10.1007/s10519-012-9529-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 42.00 ASE AR 42 2012 4 01 03 636-646 |
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10.1007/s10519-012-9529-y doi (DE-627)SPR01077467X (SPR)s10519-012-9529-y-e DE-627 ger DE-627 rakwb eng 570 ASE 42.00 bkl Lubke, Gitta H. verfasserin aut The CHRNA5/A3/B4 Gene Cluster and Tobacco, Alcohol, Cannabis, Inhalants and Other Substance Use Initiation: Replication and New Findings Using Mixture Analyses 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Multiple studies have provided evidence for genetic associations between single nucleotide polymorphisms (SNPs) located on the CHRNA5/A3/B4 gene cluster and various phenotypes related to Nicotine Dependence (Greenbaum et al. 2009). Only a few studies have investigated other substances of abuse. The current study has two aims, (1) to extend previous findings by focusing on associations between the CHRNA5/A3/B4 gene cluster and age of initiation of several different substances, and (2) to investigate heterogeneity in age of initiation across the different substances. All analyses were conducted with a subset of the Add Health study with available genetic data. The first aim was met by modeling onset of tobacco, alcohol, cannabis, inhalants, and other substance use using survival mixture analysis (SMA). Ten SNPs in CHRNA5/A3/B4 were used to predict phenotypic differences in the risk of onset, and differences between users and non-users. The survival models aim at investigating differences in the risk of initiation across the 5–18 age range for each phenotype separately. Significant or marginally significant genetic effects were found for all phenotypes. The genetic effects were mainly related to the risk of initiation and to a lesser extent to discriminating between users and non-users. To address the second goal, the survival analyses were complemented by a latent class analysis that modeled all phenotypes jointly. One of the ten SNPs was found to predict differences between the early and late onset classes. Taken together, our study provides evidence for a general role of the CHRNA5/A3/B4 gene cluster in substance use initiation that is not limited to nicotine and alcohol. Survival mixture analysis (dpeaa)DE-He213 Nicotine initiation (dpeaa)DE-He213 Substance use (dpeaa)DE-He213 CHRNA5/B3/A4 cluster (dpeaa)DE-He213 Stephens, Sarah H. verfasserin aut Lessem, Jeffrey M. verfasserin aut Hewitt, John K. verfasserin aut Ehringer, Marissa A. verfasserin aut Enthalten in Behavior genetics Dordrecht [u.a.] : Springer Science + Business Media B.V, 1970 42(2012), 4 vom: 01. März, Seite 636-646 (DE-627)320524345 (DE-600)2014974-8 1573-3297 nnns volume:42 year:2012 number:4 day:01 month:03 pages:636-646 https://dx.doi.org/10.1007/s10519-012-9529-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 42.00 ASE AR 42 2012 4 01 03 636-646 |
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Enthalten in Behavior genetics 42(2012), 4 vom: 01. März, Seite 636-646 volume:42 year:2012 number:4 day:01 month:03 pages:636-646 |
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Enthalten in Behavior genetics 42(2012), 4 vom: 01. März, Seite 636-646 volume:42 year:2012 number:4 day:01 month:03 pages:636-646 |
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Survival mixture analysis Nicotine initiation Substance use CHRNA5/B3/A4 cluster |
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Lubke, Gitta H. @@aut@@ Stephens, Sarah H. @@aut@@ Lessem, Jeffrey M. @@aut@@ Hewitt, John K. @@aut@@ Ehringer, Marissa A. @@aut@@ |
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Only a few studies have investigated other substances of abuse. The current study has two aims, (1) to extend previous findings by focusing on associations between the CHRNA5/A3/B4 gene cluster and age of initiation of several different substances, and (2) to investigate heterogeneity in age of initiation across the different substances. All analyses were conducted with a subset of the Add Health study with available genetic data. The first aim was met by modeling onset of tobacco, alcohol, cannabis, inhalants, and other substance use using survival mixture analysis (SMA). Ten SNPs in CHRNA5/A3/B4 were used to predict phenotypic differences in the risk of onset, and differences between users and non-users. The survival models aim at investigating differences in the risk of initiation across the 5–18 age range for each phenotype separately. Significant or marginally significant genetic effects were found for all phenotypes. The genetic effects were mainly related to the risk of initiation and to a lesser extent to discriminating between users and non-users. To address the second goal, the survival analyses were complemented by a latent class analysis that modeled all phenotypes jointly. One of the ten SNPs was found to predict differences between the early and late onset classes. 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Lubke, Gitta H. |
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Lubke, Gitta H. ddc 570 bkl 42.00 misc Survival mixture analysis misc Nicotine initiation misc Substance use misc CHRNA5/B3/A4 cluster The CHRNA5/A3/B4 Gene Cluster and Tobacco, Alcohol, Cannabis, Inhalants and Other Substance Use Initiation: Replication and New Findings Using Mixture Analyses |
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570 ASE 42.00 bkl The CHRNA5/A3/B4 Gene Cluster and Tobacco, Alcohol, Cannabis, Inhalants and Other Substance Use Initiation: Replication and New Findings Using Mixture Analyses Survival mixture analysis (dpeaa)DE-He213 Nicotine initiation (dpeaa)DE-He213 Substance use (dpeaa)DE-He213 CHRNA5/B3/A4 cluster (dpeaa)DE-He213 |
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ddc 570 bkl 42.00 misc Survival mixture analysis misc Nicotine initiation misc Substance use misc CHRNA5/B3/A4 cluster |
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The CHRNA5/A3/B4 Gene Cluster and Tobacco, Alcohol, Cannabis, Inhalants and Other Substance Use Initiation: Replication and New Findings Using Mixture Analyses |
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The CHRNA5/A3/B4 Gene Cluster and Tobacco, Alcohol, Cannabis, Inhalants and Other Substance Use Initiation: Replication and New Findings Using Mixture Analyses |
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Lubke, Gitta H. Stephens, Sarah H. Lessem, Jeffrey M. Hewitt, John K. Ehringer, Marissa A. |
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Lubke, Gitta H. |
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chrna5/a3/b4 gene cluster and tobacco, alcohol, cannabis, inhalants and other substance use initiation: replication and new findings using mixture analyses |
| title_auth |
The CHRNA5/A3/B4 Gene Cluster and Tobacco, Alcohol, Cannabis, Inhalants and Other Substance Use Initiation: Replication and New Findings Using Mixture Analyses |
| abstract |
Abstract Multiple studies have provided evidence for genetic associations between single nucleotide polymorphisms (SNPs) located on the CHRNA5/A3/B4 gene cluster and various phenotypes related to Nicotine Dependence (Greenbaum et al. 2009). Only a few studies have investigated other substances of abuse. The current study has two aims, (1) to extend previous findings by focusing on associations between the CHRNA5/A3/B4 gene cluster and age of initiation of several different substances, and (2) to investigate heterogeneity in age of initiation across the different substances. All analyses were conducted with a subset of the Add Health study with available genetic data. The first aim was met by modeling onset of tobacco, alcohol, cannabis, inhalants, and other substance use using survival mixture analysis (SMA). Ten SNPs in CHRNA5/A3/B4 were used to predict phenotypic differences in the risk of onset, and differences between users and non-users. The survival models aim at investigating differences in the risk of initiation across the 5–18 age range for each phenotype separately. Significant or marginally significant genetic effects were found for all phenotypes. The genetic effects were mainly related to the risk of initiation and to a lesser extent to discriminating between users and non-users. To address the second goal, the survival analyses were complemented by a latent class analysis that modeled all phenotypes jointly. One of the ten SNPs was found to predict differences between the early and late onset classes. Taken together, our study provides evidence for a general role of the CHRNA5/A3/B4 gene cluster in substance use initiation that is not limited to nicotine and alcohol. |
| abstractGer |
Abstract Multiple studies have provided evidence for genetic associations between single nucleotide polymorphisms (SNPs) located on the CHRNA5/A3/B4 gene cluster and various phenotypes related to Nicotine Dependence (Greenbaum et al. 2009). Only a few studies have investigated other substances of abuse. The current study has two aims, (1) to extend previous findings by focusing on associations between the CHRNA5/A3/B4 gene cluster and age of initiation of several different substances, and (2) to investigate heterogeneity in age of initiation across the different substances. All analyses were conducted with a subset of the Add Health study with available genetic data. The first aim was met by modeling onset of tobacco, alcohol, cannabis, inhalants, and other substance use using survival mixture analysis (SMA). Ten SNPs in CHRNA5/A3/B4 were used to predict phenotypic differences in the risk of onset, and differences between users and non-users. The survival models aim at investigating differences in the risk of initiation across the 5–18 age range for each phenotype separately. Significant or marginally significant genetic effects were found for all phenotypes. The genetic effects were mainly related to the risk of initiation and to a lesser extent to discriminating between users and non-users. To address the second goal, the survival analyses were complemented by a latent class analysis that modeled all phenotypes jointly. One of the ten SNPs was found to predict differences between the early and late onset classes. Taken together, our study provides evidence for a general role of the CHRNA5/A3/B4 gene cluster in substance use initiation that is not limited to nicotine and alcohol. |
| abstract_unstemmed |
Abstract Multiple studies have provided evidence for genetic associations between single nucleotide polymorphisms (SNPs) located on the CHRNA5/A3/B4 gene cluster and various phenotypes related to Nicotine Dependence (Greenbaum et al. 2009). Only a few studies have investigated other substances of abuse. The current study has two aims, (1) to extend previous findings by focusing on associations between the CHRNA5/A3/B4 gene cluster and age of initiation of several different substances, and (2) to investigate heterogeneity in age of initiation across the different substances. All analyses were conducted with a subset of the Add Health study with available genetic data. The first aim was met by modeling onset of tobacco, alcohol, cannabis, inhalants, and other substance use using survival mixture analysis (SMA). Ten SNPs in CHRNA5/A3/B4 were used to predict phenotypic differences in the risk of onset, and differences between users and non-users. The survival models aim at investigating differences in the risk of initiation across the 5–18 age range for each phenotype separately. Significant or marginally significant genetic effects were found for all phenotypes. The genetic effects were mainly related to the risk of initiation and to a lesser extent to discriminating between users and non-users. To address the second goal, the survival analyses were complemented by a latent class analysis that modeled all phenotypes jointly. One of the ten SNPs was found to predict differences between the early and late onset classes. Taken together, our study provides evidence for a general role of the CHRNA5/A3/B4 gene cluster in substance use initiation that is not limited to nicotine and alcohol. |
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The CHRNA5/A3/B4 Gene Cluster and Tobacco, Alcohol, Cannabis, Inhalants and Other Substance Use Initiation: Replication and New Findings Using Mixture Analyses |
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| score |
7.4010315 |