Predictive analysis of Tryptophan Hydroxylase 2 (TPH2) missense mutations in psychiatric disorders

Abstract

Psychiatric disorders are syndromes characterized by cognitive disturbance and behavioral dysfunction, which affect over 800 million people worldwide. It is considered a major public health problem responsible for severe distress with significant impairment in social and working relationships. In the United States and Canada, psychiatric disorders are considered the main cause of disability in young individuals, in addition to being a key factor underlying suicide. Missense mutations in tryptophan hydroxylase 2 enzyme (TPH2) are associated with the development of psychiatric disorders. TPH2 catalyzes the first step of serotonin biosynthesis, a neurotransmitter that plays a central role in the regulation of emotional behavior and cognition. These mutations lead to TPH2 dysfunction with impaired enzymatic activity, which ultimately results in abnormally low levels of serotonin in the brain. Despite the importance of missense mutations in TPH2 to the development of psychiatric disorders, most of them have not yet been characterized, so their effects are still unknown. In this study, we characterized the impact of missense mutations in TPH2 using prediction algorithms and evolutionary conservation analysis. We also used a penalty system to prioritize the most likely harmful mutations of TPH2 by combining the predictive analyses, evolutionary conservation, literature review, and alterations in physicochemical properties upon amino acid substitution. Three hundred and eighty-four missense mutations of TPH2 were compiled from the literature and databases. Our predictive analysis pointed to a high rate of deleterious and destabilizing predictions for the TPH2 mutations. These mutations mainly affect conserved and, possibly, functionally important residues. Among the uncharacterized mutations of TPH2, variants V295E, R441C T311P, Y281C, R441S, S383F, P308S, Y281H, and E363G received the highest penalties, thus, being the most likely deleterious and, consequently, important targets for future investigation. Our findings may guide the design of clinical and laboratory experiments, optimizing time and resources.