Background

This study addresses the strength of associations between trichotillomania (TTM) and other DSM-IV Axis I conditions in a large sample (n = 2606) enriched for familial obsessive-compulsive disorder (OCD), to inform TTM classification.

Methods

We identified participants with TTM in the Johns Hopkins OCD Family Study (153 families) and the OCD Collaborative Genetics Study, a six-site genetic linkage study of OCD (487 families). We used logistic regression (with generalized estimating equations) to assess the strength of associations between TTM and other DSM-IV disorders.

Results

TTM had excess comorbidity with a number of conditions from different DSM-IV chapters, including tic disorders, alcohol dependence, mood disorders, anxiety disorders, impulse-control disorders, and bulimia nervosa. However, association strengths (odds ratios) were highest for kleptomania (6.6), pyromania (5.8), OCD (5.6), skin picking disorder (4.4), bulimia nervosa (3.5), and pathological nail biting (3.4).

Conclusions

TTM is comorbid with a number of psychiatric conditions besides OCD, and it is strongly associated with other conditions involving impaired impulse control. Though DSM-5 includes TTM as an OCD-related disorder, its comorbidity pattern also emphasizes the impulsive, appetitive aspects of this condition that may be relevant to classification.

Objective: The aim of this study was to identify any potential genetic overlap between attention deficit hyperactivity disorder (ADHD) and obsessive compulsive disorder (OCD). We hypothesized that since these disorders share a sub-phenotype, they may share common risk alleles. In this manuscript, we report the overlap found between these two disorders. Methods: A meta-analysis was conducted between ADHD and OCD, and polygenic risk scores (PRS) were calculated for both disorders. In addition, a protein-protein analysis was completed in order to examine the interactions between proteins; p-values for the protein-protein interaction analysis was calculated using permutation. Conclusion: None of the single nucleotide polymorphisms (SNPs) reached genome wide significance and there was little evidence of genetic overlap between ADHD and OCD.

Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.