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

Análise preditiva das mutações missense da Triptofano Hidroxilase 2 (TPH2)

Authors

  • Gustavo Duarte Bocayuva Tavares
  • Gabriel Rodrigues Coutinho Pereira
  • Gabriela Fontoura Borges
  • Joelma Freire de Mesquita

DOI:

https://doi.org/10.34117/bjdv8n9-101

Keywords:

psychiatric disorders, Tryptophan Hydroxylase 2, in silico analysis

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.

References

AMERICAN PSYCHIATRIC ADZHUBEI, IA et al. PolyPhen-2 : prediction of functional effects of human nsSNPs. Curr Protoc Hum Genet, 2010.

ARDITO, Fatima et al. The crucial role of protein phosphorylation in cell signalingand its use as targeted therapy (Review). International Journal of Molecular Medicine, v. 40, n. 2, p. 271–280, 2017.

ASHKENAZY, Haim et al. ConSurf 2016 : an improved methodology to estimate and visualize evolutionary conservation in macromolecules. Nucleic Acids Research, v. 44, n. May, p. 344–350, 2016.

ASSOCIATION, American Psychiatric. Diagnostic and Statistical Manual of Mental Disorders 5. 5th. ed. Arlington: American Psychiatric Publishing, 2013. E-book.

BENDL, Jaroslav et al. PredictSNP: Robust and Accurate Consensus Classifier for Prediction of Disease-Related Mutations. PLoS Computational Biology, v. 10, n. 1, p. 1–11, 2014.

BROMBERG, Yana; YACHDAV, Guy; ROST, Burkhard. SNAP predicts effect of mutations on protein function. Bioinformatics, v. 24, n. 20, p. 2397–2398, 2008.

CAO, Xiaoyong et al. Identification of metal ion binding sites based on amino acid sequences. PLoS ONE, [S. l.], v. 12, n. 8, p. 1–16, 2017.

CAPRIOTTI, Emidio et al. WS-SNPs&GO: a web server for predicting the deleterious effect of human protein variants using functional annotation. BMC genomics, v. 14, n. Suppl 3, p. S6, 2013.

CAPRIOTTI, Emidio; FARISELLI, Piero. PhD-SNPg: A webserver and lightweight tool for scoring single nucleotide variants. Nucleic Acids Research, v. 45, n. W1, p. W247–W252, 2017.

CAPRIOTTI, Emidio; FARISELLI, Piero; CASADIO, Rita. I-Mutant2.0: Predicting stability changes upon mutation from the protein sequence or structure. Nucleic Acids Research, v. 33, n. Web Server, p. W306–W310, 2005.

CARKACI-SALLI, Nurgul et al. Functional domains of human tryptophan hydroxylase 2 (hTPH2). Journal of Biological Chemistry, v. 281, n. 38, p. 28105–28112, 2006.

CARKACI-SALLI, Nurgul et al. Functional characterization of the S41Y (C2755A) polymorphism of tryptophan hydroxylase 2. Journal of neurochemistry, v. 130, n. 6, p. 748–758, 2014.

CHOI, Yongwook et al. Predicting the Functional Effect of Amino Acid Substitutions and Indels. PLoS ONE, v. 7, n. 10, 2012.

CHOI, Yongwook; CHAN, Agnes P. PROVEAN web server: A tool to predict the functional effect of amino acid substitutions and indels. Bioinformatics, v. 31, n. 16, p. 2745–2747, 2015.

CICHON, Sven et al. Brain-specific tryptophan hydroxylase 2 (TPH2): A functional Pro206Ser substitution and variation in the 5′-region are associated with bipolar affective disorder. Human Molecular Genetics, v. 17, n. 1, p. 87–97, 2008.

DE BAETS, Greet et al. SNPeffect 4.0: On-line prediction of molecular and structural effects of protein-coding variants. Nucleic Acids Research, v. 40, n. Database, p. D935–D939, 2012.

FAROOK, M. Febin et al. Altered serotonin, dopamine and norepinepherine levels in 15q duplication and Angelman syndrome mouse models. PLoS ONE, v. 7, n. 8, p. 1–9, 2012.

JEAN-BAPTISTE, Lamy; BERTHELOT, Hélène; FAVRE, Madeleine. Rainbow boxes: A technique for visualizing overlapping sets and an application to the comparison of drugs properties. Proceedings of the International Conference on Information Visualisation, v. 2016-August, n. July, p. 253–260, 2016.

KESSLER, Ronald C. et al. Lifetime Prevalence and Age-of-Onset Distributions of. Arch Gen Psychiatry, v. 62, n. June, p. 593–602, 2005.

KHAN, Sofia; VIHINEN, Mauno. Spectrum of disease-causing mutations in protein secondary structures. BMC Structural Biology, v. 7, p. 1–18, 2007.

KORTH, Carsten. Aggregated proteins in schizophrenia and other chronic mental diseases: DISC1opathies. Prion, [S. l.], v. 6, n. 2, p. 134–141, 2012.

KUHN, Donald M. et al. Tryptophan hydroxylase 2 aggregates through disulfide cross-linking upon oxidation: Possible link to serotonin deficits and non-motor symptoms in Parkinson’s disease. Journal of Neurochemistry, [S. l.], v. 116, n. 3, p. 426–437, 2011.

KULIKOVA, Elizabeth A.; KULIKOV, Alexander V. Tryptophan hydroxylase 2 as a therapeutic target for psychiatric disorders: focus on animal models. Expert Opinion on Therapeutic Targets, v. 23, n. 8, p. 655–667, 2019.

LANDRUM, Melissa J. et al. ClinVar : improving access to variant interpretations and supporting evidence. Nucleic Acids Research, v. 46, n. Database, p. D1062–D1067, 2018.

LÓPEZ-FERRANDO, Víctor et al. PMut: A web-based tool for the annotation of pathological variants on proteins, 2017 update. Nucleic Acids Research, v. 45, n. W1, p. W222–W228, 2017.

MAKWANA, Mehul V.; MUIMO, Richmond; JACKSON, Richard F. W. Advances in development of new tools for the study of phosphohistidine. Laboratory Investigation, v. 98, n. 3, p. 291–303, 2018.

MCKINNEY, J. et al. A loss-of-function mutation in tryptophan hydroxylase 2 segregating with attention-deficit/hyperactivity disorder. Molecular Psychiatry, v. 13, n. 4, p. 365–367, 2008.

MCKINNEY, Jeffrey A. et al. Functional properties of missense variants of human tryptophan hydroxylase 2. Human Mutation, [S. l.], v. 30, n. 5, p. 787–794, 2009.

MI, Huaiyu et al. PANTHER version 11: Expanded annotation data from Gene Ontology and Reactome pathways, and data analysis tool enhancements. Nucleic Acids Research, v. 45, n. D1, 2017.

MUKHERJEE, Joia S. Global Health and the Global Burden of Disease. Oxford Scholarship Online, n. December, 2016.

NCBI. Database Resources of the National Center for Biotechnology Information. Nucleic Acids Research, v. 45, n. D1, p. D12–D17, 2017.

OLIVEIRA, Clara Carolina Silva De et al. In silico analysis of the V66M variant of human BDNF in psychiatric disorders : An approach to precision medicine. PLoS ONE, v. 14, n. 4, p. e0215508, 2019.

PAIXÃO, Gabriela Miana de Mattos et al. Machine Learning in Medicine: Review and Applicability. Arquivos Brasileiros de Cardiologia, v. 118, n. 1, p. 95–102, 2022.

PANDOLFO, Gianluca et al. Mental illness and amyloid: A scoping review of scientific evidence over the last 10 years (2011 to 2021). Brain Sciences, v. 11, n. 10, 2021.

PEJAVER, Vikas et al. MutPred2: inferring the molecular and phenotypic impact of amino acid variants. bioRxiv, [S. l.], p. 134981, 2017.

PEREIRA, Gabriel Rodrigues Coutinho et al. In silico analysis of the tryptophan hydroxylase 2 (TPH2) protein variants related to psychiatric disorders. PLoS ONE, v. 15, n. 3, p. 1–23, 2020.

PEREIRA, Gabriel Rodrigues Coutinho et al. Analysis of mutations in APP1 protein associated with development and protection against Alzheimer ’ s disease - an In silico approach. Brazilian Journal of Development, [S. l.], v. 8, n. 6, p. 46902–46924, 2022.

PEREIRA, Gabriel Rodrigues Coutinho; DE AZEVEDO ABRAHIM VIEIRA, Bárbara; DE MESQUITA, Joelma Freire. Comprehensive in silico analysis and molecular dynamics of the superoxide dismutase 1 (SOD1) variants related to amyotrophic lateral sclerosis. PLoS ONE, v. 16, n. 2 February, p. 1–27, 2021.

PEREIRA, Gabriel Rodrigues Coutinho; VIEIRA, Barbara de Azevedo Abrahim; MESQUITA, Joelma Freire De. Comprehensive in silico analysis and molecular dynamics of the superoxide dismutase 1 ( SOD1 ) variants related to amyotrophic lateral sclerosis. PLOS ONE, v. 1, n. 0247841, p. 1–27, 2021.

ROSE, Yana et al. RCSB Protein Data Bank: Architectural Advances Towards Integrated Searching and Efficient Access to Macromolecular Structure Data from the PDB Archive. Journal of Molecular Biology, [S. l.], v. 433, n. 11, p. 166704, 2021.

ROY CHOUDHURY, Amrita et al. Supporting precision medicine by data mining across multi-disciplines: An integrative approach for generating comprehensive linkages between single nucleotide variants (SNVs) and drug-binding sites. Bioinformatics, v. 33, n. 11, p. 1621–1629, 2017.

SANAVIA, Tiziana et al. Limitations and challenges in protein stability prediction upon genome variations: towards future applications in precision medicine. Computational and Structural Biotechnology Journal, [S. l.], v. 18, p. 1968–1979, 2020.

SANSONE, Randy A.; SANSONE, Lori A. PSYCHIATRIC DISORDERS : A Global Look at Facts and Figures PREVALENCE OF PSYCHIATRIC. Psychiatry, v. 7, n. 12, p. 16–19, 2010.

SAVOJARDO, Castrense et al. INPS-MD: a web server to predict stability of protein variants from sequence and structure: Table 1. Bioinformatics, v. 32, n. 16, p. 2542–2544, 2016.

SKAWINSKA, Natalia. Allosteric regulation of human tryptophan hydroxylase isoform 2 (hTPH2). 2020. - Technical University of Denmark, 2020.

STANLEY, Susanne et al. A model of integrated care to address the physical health of people with severe mental illness. The Wellness Clinic, n. June, p. 1–46, 2019.

ŠTRAC, Dubravka Švob; PIVAC, Nela; MÜCK-ŠELER, Dorotea. The serotonergic system and cognitive function. Translational Neuroscience, v. 7, n. 1, p. 35–49, 2016.

TIDEMAND, Kasper D. et al. Stabilization of tryptophan hydroxylase 2 by l-phenylalanine-induced dimerization. FEBS Open Bio, v. 6, n. 10, p. 987–999, 2016.

TRAUTMANN, Sebastian; REHM, Jürgen; WITTCHEN, Hans-Ulrich. The economic costs of mental disorders. EMBO reports, v. 17, n. 9, p. 1245–1249, 2016.

UNIPROT CONSORTIUM. UniProt: the universal protein knowledgebase in 2021. Nucleic Acids Research, [S. l.], v. 49, n. D1, p. D480–D489, 2021.

VASER, Robert et al. SIFT missense predictions for genomes. Nature Protocols, v. 4, n. December 2015, p. 1073–1081, 2015.

WEBER, Claudia C.; WHELAN, Simon. Physicochemical amino acid properties better describe substitution rates in large populations. Molecular Biology and Evolution, v. 36, n. 4, p. 679–690, 2019.

WELFORD, Richard W. D. et al. Serotonin biosynthesis as a predictive marker of serotonin pharmacodynamics and disease-induced dysregulation. Scientific Reports, v. 6, n. June, p. 1–10, 2016.

WHO. World Health Organization - Mental Health. 2017.

WINGE, Ingeborg et al. Characterization of wild-type and mutant forms of human tryptophan hydroxylase 2. Journal of Neurochemistry, v. 100, n. 6, p. 1648–1657, 2007.

XU, Chao-Jin et al. Tph2 Genetic Ablation Contributes to Senile Plaque Load and Astrogliosis in APP/PS1 Mice. Curr Alzheimer Res, v. 16, n. 3, p. 219–232, 2019.

YANG, Jiarun et al. The interaction of TPH2 and 5-HT2A polymorphisms on major depressive disorder susceptibility in a Chinese Han population: A case-control study. Frontiers in Psychiatry, v. 10, n. APR, p. 1–7, 2019.

ZHANG, Xiaoyan; WANG, Yiming. TPH2: A Key Gene Risk Factor and Potential Therapy Target in Depression. E3S Web of Conferences, v. 271, p. 03070, 2021.

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Published

2022-09-09

How to Cite

Tavares, G. D. B., Pereira, G. R. C., Borges, G. F., & Mesquita, J. F. de. (2022). Predictive analysis of Tryptophan Hydroxylase 2 (TPH2) missense mutations in psychiatric disorders: Análise preditiva das mutações missense da Triptofano Hidroxilase 2 (TPH2). Brazilian Journal of Development, 8(9), 61944–61970. https://doi.org/10.34117/bjdv8n9-101

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