The influence of the rs6295 gene polymorphism on serotonin-1A receptor distribution investigated with PET in patients with major depression applying machine learning

摘要: Major depressive disorder (MDD) is the most common neuropsychiatric disease and despite extensive research, its genetic substrate still not sufficiently understood. The polymorphism rs6295 of serotonin-1A receptor gene (HTR1A) affecting transcriptional regulation 5-HT1A has been closely linked to MDD. Here, we used positron emission tomography (PET) exploiting advances in data mining statistics by using machine learning 62 healthy subjects 19 patients with MDD, which were scanned PET radioligand [carbonyl-11C]WAY-100635. All genotyped for genotype was grouped GG vs C allele carriers. Mixed model applied a ROI-based (region interest) approach. ROI binding potential (BPND) divided dorsal raphe BPND as specific measure highlight effects (BPDiv). produced an interaction effect patients' group but no controls. Differences BPDiv demonstrated seven ROIs; parahippocampus, hippocampus, fusiform gyrus, gyrus rectus, supplementary motor area, inferior frontal occipital lingual gyrus. For classification genotype, 'RandomForest' Support Vector Machines used, however, sufficient predictive capability could be computed. Our results are line preclinical data, mouse knockout studies well previous clinical analyses, demonstrating two-pronged G on for, believe, first time. Future endeavors should address epigenetic allosteric heteroreceptor complexes. Replication larger samples MDD necessary substantiate our findings.