Food addiction (FA) has gained more scientific attention but needs deeper understanding. Data indicates that the central melanocortin (MC) system through the MC4 receptor (MC4R) and its polymorphisms Show more
Food addiction (FA) has gained more scientific attention but needs deeper understanding. Data indicates that the central melanocortin (MC) system through the MC4 receptor (MC4R) and its polymorphisms play a crucial role in the regulation of eating behaviour and in the motivation for the rewarding properties of food potentially leading to obesity. This may also contribute to the emergence of altered reward-related behaviors such as FA. The study aims to evaluate the genetic contribution of rs17782313, rs12970134, rs10871777, rs6567160, rs17700144 MC4R polymorphisms to the development of FA and to assess the association between these MC4R variations and clinical features. Eating (EDE-Q, BES, NEQ, GQ) and general psychopathology (BDI-II, STAI-S, DERS) were evaluated in patients with obesity with and without FA. Y-FAS 2.0 was used to assess FA. A blood sample was collected from all patients for the genotyping of MC4R polymorphisms. All the polymorphisms were equally distributed between groups except for rs17782313. A direct association between rs17782313 with FA was evident. Patients with FA and with C allele showed higher risk of FA compared to group without FA. There was a significant effect of rs17782313 on psychopathological variables in patients with FA. Allele C carriers exhibited higher anxiety and depression than T carriers. The rs17782313 of the MC4R showed an association with FA. A significant direct influence of C allele on anxiety and depression emerged in the group with FA but not in patients without FA. Show less
Point mutations are the most common cause of inherited diseases. Bioinformatics tools can help to predict the pathogenicity of mutations found during genetic screening, but they may work less well in Show more
Point mutations are the most common cause of inherited diseases. Bioinformatics tools can help to predict the pathogenicity of mutations found during genetic screening, but they may work less well in determining the effect of point mutations in non-coding regions. In silico analysis of intronic variants can reveal their impact on the splicing process, but the consequence of a given substitution is generally not predictable. The aim of this study was to functionally test five intronic variants ( Show less