| Title |
Genetic and Environmental Contributions to the Relationships Between Brain Structure and Average Lifetime Cigarette Use
|
|---|---|
| Published in |
Behavior Genetics, February 2015
|
| DOI | 10.1007/s10519-014-9704-4 |
| Pubmed ID | |
| Authors |
Elizabeth Prom-Wormley, Hermine H. M. Maes, J. Eric Schmitt, Matthew S. Panizzon, Hong Xian, Lisa T. Eyler, Carol E. Franz, Michael J. Lyons, Ming T. Tsuang, Anders M. Dale, Christine Fennema-Notestine, William S. Kremen, Michael C. Neale |
| Abstract |
Chronic cigarette use has been consistently associated with differences in the neuroanatomy of smokers relative to nonsmokers in case-control studies. However, the etiology underlying the relationships between brain structure and cigarette use is unclear. A community-based sample of male twin pairs ages 51-59 (110 monozygotic pairs, 92 dizygotic pairs) was used to determine the extent to which there are common genetic and environmental influences between brain structure and average lifetime cigarette use. Brain structure was measured by high-resolution structural magnetic resonance imaging, from which subcortical volume and cortical volume, thickness and surface area were derived. Bivariate genetic models were fitted between these measures and average lifetime cigarette use measured as cigarette pack-years. Widespread, negative phenotypic correlations were detected between cigarette pack-years and several cortical as well as subcortical structures. Shared genetic and unique environmental factors contributed to the phenotypic correlations shared between cigarette pack-years and subcortical volume as well as cortical volume and surface area. Brain structures involved in many of the correlations were previously reported to play a role in specific aspects of networks of smoking-related behaviors. These results provide evidence for conducting future research on the etiology of smoking-related behaviors using measures of brain morphology. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 27 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Professor | 6 | 22% |
| Student > Ph. D. Student | 5 | 19% |
| Other | 4 | 15% |
| Professor > Associate Professor | 3 | 11% |
| Student > Bachelor | 2 | 7% |
| Other | 6 | 22% |
| Unknown | 1 | 4% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 6 | 22% |
| Biochemistry, Genetics and Molecular Biology | 4 | 15% |
| Psychology | 4 | 15% |
| Neuroscience | 4 | 15% |
| Agricultural and Biological Sciences | 2 | 7% |
| Other | 2 | 7% |
| Unknown | 5 | 19% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 February 2015.
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#20,262,276
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Outputs from Behavior Genetics
#795
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#214,868
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Outputs of similar age from Behavior Genetics
#10
of 11 outputs
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