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. 2011 Dec;35(12):2152-61.
doi: 10.1111/j.1530-0277.2011.01564.x. Epub 2011 Jun 20.

Measures of current alcohol consumption and problems: two independent twin studies suggest a complex genetic architecture

Danielle M Dick  1 , Jacquelyn L Meyers, Richard J Rose, Jaakko Kaprio, Kenneth S Kendler
Affiliations

Measures of current alcohol consumption and problems: two independent twin studies suggest a complex genetic architecture

Danielle M Dick et al. Alcohol Clin Exp Res. 2011 Dec.

Abstract

Background: Twin studies demonstrate that measures of alcohol consumption (AC) show evidence of genetic influence, suggesting they may be useful in gene identification efforts. The extent to which these phenotypes will be informative in identifying susceptibility genes involved in alcohol dependence depends on the extent to which genetic influences are shared across measures of AC and alcohol problems. Previous studies have demonstrated that AC reported for the period of heaviest lifetime drinking shows a large degree of genetic overlap with alcohol dependence; however, many studies with genetic material assess current AC. Further, there are many different aspects of AC that can be assessed (e.g., frequency of use, quantity of use, and frequency of intoxication).

Methods: Here, we use data from 2 large, independent, population-based twin samples, FinnTwin 16 and The Virginia Adult Twin Study of Psychiatric and Substance Use Disorders, to examine the extent to which genetic influences are shared across many different measures of AC and alcohol problems.

Results: Genetic correlations across current AC measures and alcohol problems were high across both samples. However, both samples suggest a complex genetic architecture with many different genetic factors influencing various aspects of current AC and problems.

Conclusions: These results suggest that careful attention must be paid to the phenotype in efforts to "replicate" genetic effects across samples or combine samples for meta-analyses of genetic effects influencing susceptibility to alcohol-related outcomes.

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Figures

Fig. 1
Fig. 1
Full Cholesky model in the FinnTwin16 sample containing 7 latent genetic (A), shared environmental (C), and unique environmental (E) factors each loading onto the 7 measured alcohol variables (frequency, frequency × quantity, frequency of heavy drinking, frequency of intoxication, maximum drinks in a 24-hour period, the MAST, and the RAPI). MAST, Michigan Alcoholism Screening Test; RAPI, Rutgers Alcohol Problem Index.
Fig. 2
Fig. 2
Full Cholesky model in the VATSPSUD sample containing 5 latent genetic (A), shared environmental (C), and unique environmental (E) factors each loading onto the 5 measured alcohol variables (frequency, quantity, frequency of intoxication, maximum drinks in a 24-hour period, DSM-IV alcohol dependence symptoms [AD Sx]). VATSPSUD, Virginia Adult Twin Study of Psychiatric and Substance Use Disorders.
Fig. 3
Fig. 3
FinnTwin16 best-fitting model: additive genetic pathways. MAST, Michigan Alcoholism Screening Test; RAPI, Rutgers Alcohol Problem Index.
Fig. 4
Fig. 4
VATSPSUD best-fitting model: additive genetic pathways. VATSPSUD, Virginia Adult Twin Study of Psychiatric and Substance Use Disorders; AD Sx, alcohol dependence symptoms.
Fig. 5
Fig. 5
FinnTwin16 best-fitting model: unique environmental pathways. MAST, Michigan Alcoholism Screening Test; RAPI, Rutgers Alcohol Problem Index.
Fig. 6
Fig. 6
VATSPSUD best-fitting model: unique environmental pathways. VATSPSUD, Virginia Adult Twin Study of Psychiatric and Substance Use Disorders; AD Sx, alcohol dependence symptoms.
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References

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