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Published on: November 9, 2019
Associations between obsessive-compulsive classes and pathological gambling in a national cohort of male twins
Jeffrey F Scherrer1, Hong Xian2, Wendy S Slutske3
1Research Service, Veterans Affairs Medical Center, St Louis, Missouri2Department of Family and Community Medicine, St Louis University School of Medicine, St Louis, Missouri.
Importance:
Because of shared characteristics, pathological gambling (PG) has been variously conceptualized as an obsessive-compulsive (OC) spectrum disorder or as an addictive disorder. Prior community-based studies have not systematically determined the association between PG and OC features and whether common genetic factors contribute to both conditions.
Objective:
To examine the association and genetic correlation between PG and OC features.
Design, Setting, And Participants:
We performed a latent class analysis (LCA) of OC features, cross-sectional tests of association, and classic twin genetic analysis using results of telephone interviews conducted from March 2002 through November 2003. Participants included 1675 male twin pairs from the Vietnam Era Twin Registry, aged 45 to 60 years.
Main Outcomes And Measures:
Ten OC features were queried and used to derive OC classes identified via LCA.
Results:
The best-fitting LCA model identified the following 4 OC classes: unaffected (class 1), ritual/symmetry compulsions (class 2), germ/contamination obsessions (class 3), and severe OC (class 4). All PG symptoms were more common in class 4 OC and 6 of 10 PG symptoms were significantly more common in class 4 OC (P < .01). Participants in the severe class were most likely to have 4 or more DSM-IV or DSM-5 PG diagnostic criteria (odds ratio, 3.8 [95% CI, 1.8-8.2]). The genetic correlation between phenotypes was 0.44 (95% CI, 0.16-0.75).
Conclusions And Relevance:
The association between OC features and diagnostic criteria for PG highlights a role of obsessions and compulsivity in PG, and the lifetime co-occurrence of these disorders results in part from common genetic variance. Phenotypic and genetic overlap between OC features and PG add to our understanding of the most appropriate classification of PG and offers insights for treatment development.
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