Xiaohua Liu1, John R Kelsoe2, Tiffany A Greenwood3. 1. Department of Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China. 2. Department of Psychiatry, University of California San Diego, La Jolla, CA, USA; San Diego Veterans Affairs Healthcare System, San Diego, CA, USA; Institute for Genomic Medicine, University of California, La Jolla, San Diego, CA, USA. 3. Department of Psychiatry, University of California San Diego, La Jolla, CA, USA.
Abstract
BACKGROUND: Bipolar disorder is a heterogeneous mood disorder associated with several important clinical comorbidities, such as eating disorders. This clinical heterogeneity complicates the identification of genetic variants contributing to bipolar susceptibility. Here we investigate comorbidity of eating disorders as a subphenotype of bipolar disorder to identify genetic variation that is common and unique to both disorders. METHODS: We performed a genome-wide association analysis contrasting 184 bipolar subjects with eating disorder comorbidity against both 1370 controls and 2006 subjects with bipolar disorder only from the Bipolar Genome Study (BiGS). RESULTS: The most significant genome-wide finding was observed bipolar with comorbid eating disorder vs. controls within SOX2-OT (p=8.9×10(-8) for rs4854912) with a secondary peak in the adjacent FXR1 gene (p=1.2×10(-6) for rs1805576) on chromosome 3q26.33. This region was also the most prominent finding in the case-only analysis (p=3.5×10(-7) and 4.3×10(-6), respectively). Several regions of interest containing genes involved in neurodevelopment and neuroprotection processes were also identified. LIMITATIONS: While our primary finding did not quite reach genome-wide significance, likely due to the relatively limited sample size, these results can be viewed as a replication of a recent study of eating disorders in a large cohort. CONCLUSIONS: These findings replicate the prior association of SOX2-OT with eating disorders and broadly support the involvement of neurodevelopmental/neuroprotective mechanisms in the pathophysiology of both disorders. They further suggest that different clinical manifestations of bipolar disorder may reflect differential genetic contributions and argue for the utility of clinical subphenotypes in identifying additional molecular pathways leading to illness.
BACKGROUND:Bipolar disorder is a heterogeneous mood disorder associated with several important clinical comorbidities, such as eating disorders. This clinical heterogeneity complicates the identification of genetic variants contributing to bipolar susceptibility. Here we investigate comorbidity of eating disorders as a subphenotype of bipolar disorder to identify genetic variation that is common and unique to both disorders. METHODS: We performed a genome-wide association analysis contrasting 184 bipolar subjects with eating disorder comorbidity against both 1370 controls and 2006 subjects with bipolar disorder only from the Bipolar Genome Study (BiGS). RESULTS: The most significant genome-wide finding was observed bipolar with comorbid eating disorder vs. controls within SOX2-OT (p=8.9×10(-8) for rs4854912) with a secondary peak in the adjacent FXR1 gene (p=1.2×10(-6) for rs1805576) on chromosome 3q26.33. This region was also the most prominent finding in the case-only analysis (p=3.5×10(-7) and 4.3×10(-6), respectively). Several regions of interest containing genes involved in neurodevelopment and neuroprotection processes were also identified. LIMITATIONS: While our primary finding did not quite reach genome-wide significance, likely due to the relatively limited sample size, these results can be viewed as a replication of a recent study of eating disorders in a large cohort. CONCLUSIONS: These findings replicate the prior association of SOX2-OT with eating disorders and broadly support the involvement of neurodevelopmental/neuroprotective mechanisms in the pathophysiology of both disorders. They further suggest that different clinical manifestations of bipolar disorder may reflect differential genetic contributions and argue for the utility of clinical subphenotypes in identifying additional molecular pathways leading to illness.
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