COMPARATIVE STUDY
JOURNAL ARTICLE

Shared genetic contributions to pathological gambling and major depression in men

Marc N Potenza, Hong Xian, Kamini Shah, Jeffrey F Scherrer, Seth A Eisen
Archives of General Psychiatry 2005, 62 (9): 1015-21
16143733

CONTEXT: Although pathological gambling (PG) and major depression (MD) frequently co-occur, little is known regarding the relative contributions of environmental and genetic factors to the codevelopment of the disorders.

OBJECTIVES: To estimate environmental and genetic contributions to PG and MD as defined in DSM-III-R and the lifetime co-occurrence of PG and MD.

DESIGN: Survey data from the Vietnam Era Twin Registry were examined in biometric models.

SETTING: Telephone interview.

PARTICIPANTS: Of 10, 253 eligible participants, 7869 were successfully interviewed.

MAIN OUTCOME MEASURES: Estimated genetic, shared environmental, and unique environmental contributions to PG and MD and their lifetime co-occurrence in bivariate models.

RESULTS: Elevated odds ratios for MD were associated with those of PG (4.06; 95% confidence interval, 2.68-6.13), and the association remained significant following adjustment for sociodemographic and other psychiatric variables (odds ratio = 1.98; 95% confidence interval, 1.14-3.45). The best-fitting bivariate model indicated that 66% of the variance in PG and 41% of the variance in MD were owing to genetic factors, and 34% of the variance in PG and 59% of the variance in MD were owing to unique environmental factors. There was a substantial correlation between the genetic components of PG and MD (r(A) = 0.58), with 34% of the genetic variance for each disorder also contributing to that of the other. The best-fitting model estimated that 100% of the total overlap between PG and MD was genetic.

CONCLUSIONS: The correlation between PG and MD in middle-aged men appears to be largely influenced by overlapping genetic factors. Future research is needed to determine the extent to which these findings extend to other groups (eg, women), identify specific genes, and generate improved prevention and treatment strategies.

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