| Title |
Genetic and Neurophysiological Correlates of the Age of Onset of Alcohol Use Disorders in Adolescents and Young Adults
|
|---|---|
| Published in |
Behavior Genetics, August 2013
|
| DOI | 10.1007/s10519-013-9604-z |
| Pubmed ID | |
| Authors |
David B. Chorlian, Madhavi Rangaswamy, Niklas Manz, Jen-Chyong Wang, Danielle Dick, Laura Almasy, Lance Bauer, Kathleen Bucholz, Tatiana Foroud, Victor Hesselbrock, Sun J. Kang, John Kramer, Sam Kuperman, John Nurnberger, John Rice, Marc Schuckit, Jay Tischfield, Howard J. Edenberg, Alison Goate, Laura Bierut, Bernice Porjesz |
| Abstract |
Discrete time survival analysis was used to assess the age-specific association of event-related oscillations (EROs) and CHRM2 gene variants on the onset of regular alcohol use and alcohol dependence. The subjects were 2,938 adolescents and young adults ages 12-25. Results showed that the CHRM2 gene variants and ERO risk factors had hazards which varied considerably with age. The bulk of the significant age-specific associations occurred in those whose age of onset was under 16. These associations were concentrated in those subjects who at some time took an illicit drug. These results are consistent with studies which associate greater rates of alcohol dependence among those who begin drinking at an early age. The age specificity of the genetic and neurophysiological factors is consistent with recent studies of adolescent brain development, which locate an interval of heightened vulnerability to substance use disorders in the early to mid teens. |
Mendeley readers
The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| New Zealand | 1 | 2% |
| United States | 1 | 2% |
| Argentina | 1 | 2% |
| Unknown | 49 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 15% |
| Student > Ph. D. Student | 7 | 13% |
| Professor | 6 | 12% |
| Student > Bachelor | 6 | 12% |
| Student > Doctoral Student | 4 | 8% |
| Other | 13 | 25% |
| Unknown | 8 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 16 | 31% |
| Neuroscience | 5 | 10% |
| Medicine and Dentistry | 4 | 8% |
| Agricultural and Biological Sciences | 4 | 8% |
| Social Sciences | 4 | 8% |
| Other | 9 | 17% |
| Unknown | 10 | 19% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 26 August 2013.
All research outputs
#5,696,319
of 22,719,618 outputs
Outputs from Behavior Genetics
#272
of 907 outputs
Outputs of similar age
#48,386
of 198,818 outputs
Outputs of similar age from Behavior Genetics
#6
of 13 outputs
Altmetric has tracked 22,719,618 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 907 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.8. This one has gotten more attention than average, scoring higher than 69% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 198,818 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 75% of its contemporaries.
We're also able to compare this research output to 13 others from the same source and published within six weeks on either side of this one. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.