No abstract

Eating disorders and substance use disorders frequently co-occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa and problem alcohol use (genetic correlation [r g ], twin-based = 0.23-0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome-wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge eating, AN without binge eating,

Eating disorders and substance use disorders frequently co-occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa (BN) and problem alcohol use (genetic correlation [r g ], twin-based=0.23-0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome-wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge-eating, AN without binge-eating, and a BN factor score), and eight substance-use-related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder (MDD). Total sample sizes per phenotype ranged from ~2,400 to ~537,000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism-based genetic correlations between eating disorder and substance-userelated phenotypes. Significant positive genetic associations emerged between AUD and AN (r g =0.18; false discovery rate q=0.0006), cannabis initiation and AN (r g =0.23; q<0.0001), and cannabis initiation and AN with binge-eating (r g =0.27; q=0.0016). Conversely, significant negative genetic correlations were observed between three non-diagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge-eating (r gs =-0.19 to -0.23; qs<0.04). The genetic correlation between AUD and AN was no longer significant after co-varying for MDD loci. The patterns of association between eating disorder-and substance-use-related phenotypes highlights the potentially complex and substance-specific relationships between these behaviors.Eating and Substance Use 12 A well-established phenotypic association exists between eating disorder and substance use phenotypes, with evidence for specific relations between particular types of eating disorders and substance use disorders. The prevalence of an alcohol use disorder (AUD) is greater among individuals with bulimia nervosa (BN) and binge-eating disorder (BED) than individuals with anorexia nervosa (AN) or healthy controls (Gadalla and Piran, 2007, Root et al., 2010).Similarly, individuals with BN or BED are at increased risk for smoking, nicotine dependence (ND) (Solmi et al., 2016, Wiederman andPryor, 1996), and cannabis use (Krug et al., 2008, Wiederman andPryor, 1996) compared with individuals with AN or healthy controls, though these results are not consistent (Root et al., 2010). Importantly, women with the bingeeating/purging subtype of AN report a higher prevalence of AUD, smoking, ND, and cannabis use than women with the restricting subtype of AN (Anzengruber et al., 2006, Krug et al., 2008, Root et al., 2010. Thus, binge eating-a transdiagnostic sy...

Objective: We aimed to determine the effect of human SH2B1 variants on leptin and insulin signaling, major regulators of energy homeostasis, on the RNA level. Methods: We analyzed the expression of infrequent alleles of seven SH2B1 variants (Arg67Cys, Lys150Arg, Thr175Ala, Thr343Met, Thr484Ala, Ser616Pro and Pro689Leu) in response to insulin or leptin cell stimulation. Two of these were identified in own mutation screens, the others were predicted to be deleterious or to serve as controls. The variants were analyzed in a homologous system of mouse hypothalamic cells. Changes in expression of downstream genes were measured. Student’s t-test for independent samples was applied and effect sizes using Cohen’s d were calculated. Results: In 34 of 54 analyzed genes involved in leptin (JAK/STAT or AKT) signaling, variants nominally changed expression. The expression of three genes was considerably increased (p values ≤ 0.001: Gbp2b (67Cys; d = 25.11), Irf9 (689Leu; d = 44.65) and Isg15 (150Arg; d = 20.35)). Of 32 analyzed genes in the insulin signaling pathway, the expression of 10 genes nominally changed (p ≤ 0.05), three resulted in p values ≤ 0.01 (Cap1 (150Arg; d = 7.48), Mapk1(343Met; d = –6.80) and Sorbs1 (689Leu; d = 7.82)). Conclusion: The increased expression of genes in leptin (JAK/STAT or AKT) signaling implies that the main mode of action for human SH2B1 mutations might affect leptin signaling rather than insulin signaling.

Mutations leading to a reduced function of the melanocortin-4 receptor (MC4R) exert a major gene effect on extreme obesity. Recently it was shown that the bone derived hormone lipocalin 2 (LCN2) binds to the MC4R and activates a MC4R dependent anorexigenic pathway. We identified mutations in both genes and screened the effects of MC4R and LCN2 mutations on eating behavior and weight change after a lifestyle intervention. One hundred and twelve children (11.24 ± 2.6 years, BMI-SDS 2.91 ± 1.07) with abdominal obesity participated in a lifestyle intervention. MC4R and LCN2 coding regions were screened by Sanger sequencing. Eating behavior was assessed at baseline with the Children Eating Behavior Questionnaire (CEBQ). We detected three previously described non-synonymous MC4R variants (Glu42Lys, Thr150Ile, and Arg305Gln) and one non-synonymous polymorphism (Ile251Leu). Regarding LCN2, one known non-synonymous variant (Thr124Met) was detected. Eating behavior was described in carriers of the MC4R and LCN2 mutation and in non-carriers. MC4R and LCN2 mutations were detected in 2.42% and 0.84%, respectively, of Spanish children with abdominal obesity. A number of subjects with functional mutation variants in MC4R and LCN2 were able to achieve a reduction in BMI-SDS after a lifestyle intervention.