Stacey L Kirkpatrick1, Lisa R Goldberg2, Neema Yazdani3, R Keith Babbs1, Jiayi Wu4, Eric R Reed5, David F Jenkins6, Amanda F Bolgioni2, Kelsey I Landaverde1, Kimberly P Luttik1, Karen S Mitchell7, Vivek Kumar8, W Evan Johnson9, Megan K Mulligan10, Pietro Cottone11, Camron D Bryant12. 1. Laboratory of Addiction Genetics, Department of Pharmacology and Experimental Therapeutics and Department of Psychiatry, Boston University, Boston, Massachusetts. 2. Laboratory of Addiction Genetics, Department of Pharmacology and Experimental Therapeutics and Department of Psychiatry, Boston University, Boston, Massachusetts; Graduate Program in Biomolecular Pharmacology, Boston University, Boston, Massachusetts. 3. Laboratory of Addiction Genetics, Department of Pharmacology and Experimental Therapeutics and Department of Psychiatry, Boston University, Boston, Massachusetts; Graduate Program in Biomolecular Pharmacology, Boston University, Boston, Massachusetts; Transformative Training Program in Addiction Science, Boston University, Boston, Massachusetts. 4. Laboratory of Addiction Genetics, Department of Pharmacology and Experimental Therapeutics and Department of Psychiatry, Boston University, Boston, Massachusetts; Ph.D. Program in Biomedical Sciences, Graduate Program in Genetics and Genomics, Boston University, Boston, Massachusetts; Transformative Training Program in Addiction Science, Boston University, Boston, Massachusetts. 5. Laboratory of Addiction Genetics, Department of Pharmacology and Experimental Therapeutics and Department of Psychiatry, Boston University, Boston, Massachusetts; Ph.D. Program in Bioinformatics, Boston University, Boston, Massachusetts. 6. Computational Biomedicine, Boston University, Boston, Massachusetts; Ph.D. Program in Bioinformatics, Boston University, Boston, Massachusetts. 7. Department of Psychiatry, Boston University School of Medicine, Boston University, Boston, Massachusetts. 8. The Jackson Laboratory, Bar Harbor, Maine. 9. Computational Biomedicine, Boston University, Boston, Massachusetts. 10. Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, Tennessee. 11. Laboratory of Addictive Disorders, Department of Pharmacology and Experimental Therapeutics and Department of Psychiatry, Boston University, Boston, Massachusetts. 12. Laboratory of Addiction Genetics, Department of Pharmacology and Experimental Therapeutics and Department of Psychiatry, Boston University, Boston, Massachusetts. Electronic address: camron@bu.edu.
Abstract
BACKGROUND: Eating disorders are lethal and heritable; however, the underlying genetic factors are unknown. Binge eating is a highly heritable trait associated with eating disorders that is comorbid with mood and substance use disorders. Therefore, understanding its genetic basis will inform therapeutic development that could improve several comorbid neuropsychiatric conditions. METHODS: We assessed binge eating in closely related C57BL/6 mouse substrains and in an F2 cross to identify quantitative trait loci associated with binge eating. We used gene targeting to validate candidate genetic factors. Finally, we used transcriptome analysis of the striatum via messenger RNA sequencing to identify the premorbid transcriptome and the binge-induced transcriptome to inform molecular mechanisms mediating binge eating susceptibility and establishment. RESULTS: C57BL/6NJ but not C57BL/6J mice showed rapid and robust escalation in palatable food consumption. We mapped a single genome-wide significant quantitative trait locus on chromosome 11 (logarithm of the odds = 7.4) to a missense mutation in cytoplasmic FMR1-interacting protein 2 (Cyfip2). We validated Cyfip2 as a major genetic factor underlying binge eating in heterozygous knockout mice on a C57BL/6N background that showed reduced binge eating toward a wild-type C57BL/6J-like level. Transcriptome analysis of premorbid genetic risk identified the enrichment terms morphine addiction and retrograde endocannabinoid signaling, whereas binge eating resulted in the downregulation of a gene set enriched for decreased myelination, oligodendrocyte differentiation, and expression. CONCLUSIONS: We identified Cyfip2 as a major significant genetic factor underlying binge eating and provide a behavioral paradigm for future genome-wide association studies in populations with increased genetic complexity.
BACKGROUND:Eating disorders are lethal and heritable; however, the underlying genetic factors are unknown. Binge eating is a highly heritable trait associated with eating disorders that is comorbid with mood and substance use disorders. Therefore, understanding its genetic basis will inform therapeutic development that could improve several comorbid neuropsychiatric conditions. METHODS: We assessed binge eating in closely related C57BL/6 mouse substrains and in an F2 cross to identify quantitative trait loci associated with binge eating. We used gene targeting to validate candidate genetic factors. Finally, we used transcriptome analysis of the striatum via messenger RNA sequencing to identify the premorbid transcriptome and the binge-induced transcriptome to inform molecular mechanisms mediating binge eating susceptibility and establishment. RESULTS: C57BL/6NJ but not C57BL/6J mice showed rapid and robust escalation in palatable food consumption. We mapped a single genome-wide significant quantitative trait locus on chromosome 11 (logarithm of the odds = 7.4) to a missense mutation in cytoplasmic FMR1-interacting protein 2 (Cyfip2). We validated Cyfip2 as a major genetic factor underlying binge eating in heterozygous knockout mice on a C57BL/6N background that showed reduced binge eating toward a wild-type C57BL/6J-like level. Transcriptome analysis of premorbid genetic risk identified the enrichment terms morphine addiction and retrograde endocannabinoid signaling, whereas binge eating resulted in the downregulation of a gene set enriched for decreased myelination, oligodendrocyte differentiation, and expression. CONCLUSIONS: We identified Cyfip2 as a major significant genetic factor underlying binge eating and provide a behavioral paradigm for future genome-wide association studies in populations with increased genetic complexity.
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