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Tandon S, Aggarwal P, Sarkar S. Polyglutamine disorders: Pathogenesis and potential drug interventions. Life Sci 2024; 344:122562. [PMID: 38492921 DOI: 10.1016/j.lfs.2024.122562] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 02/27/2024] [Accepted: 03/13/2024] [Indexed: 03/18/2024]
Abstract
Polyglutamine/poly(Q) diseases are a group nine hereditary neurodegenerative disorders caused due to abnormally expanded stretches of CAG trinucleotide in functionally distinct genes. All human poly(Q) diseases are characterized by the formation of microscopically discernable poly(Q) positive aggregates, the inclusion bodies. These toxic inclusion bodies are responsible for the impairment of several cellular pathways such as autophagy, transcription, cell death, etc., that culminate in disease manifestation. Although, these diseases remain largely without treatment, extensive research has generated mounting evidences that various events of poly(Q) pathogenesis can be developed as potential drug targets. The present review article briefly discusses the key events of disease pathogenesis, model system-based investigations that support the development of effective therapeutic interventions against pathogenesis of human poly(Q) disorders, and a comprehensive list of pharmacological and bioactive compounds that have been experimentally shown to alleviate poly(Q)-mediated neurotoxicity. Interestingly, due to the common cause of pathogenesis, all poly(Q) diseases share etiology, thus, findings from one disease can be potentially extrapolated to other poly(Q) diseases as well.
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Affiliation(s)
- Shweta Tandon
- Department of Genetics, University of Delhi South Campus, Benito Juarez Road, New Delhi 110021, India
| | - Prerna Aggarwal
- Department of Genetics, University of Delhi South Campus, Benito Juarez Road, New Delhi 110021, India
| | - Surajit Sarkar
- Department of Genetics, University of Delhi South Campus, Benito Juarez Road, New Delhi 110021, India.
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Sousa A, Rocha S, Vieira J, Reboiro-Jato M, López-Fernández H, Vieira CP. On the identification of potential novel therapeutic targets for spinocerebellar ataxia type 1 (SCA1) neurodegenerative disease using EvoPPI3. J Integr Bioinform 2023; 20:jib-2022-0056. [PMID: 36848492 PMCID: PMC10561075 DOI: 10.1515/jib-2022-0056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Accepted: 11/26/2022] [Indexed: 03/01/2023] Open
Abstract
EvoPPI (http://evoppi.i3s.up.pt), a meta-database for protein-protein interactions (PPI), has been upgraded (EvoPPI3) to accept new types of data, namely, PPI from patients, cell lines, and animal models, as well as data from gene modifier experiments, for nine neurodegenerative polyglutamine (polyQ) diseases caused by an abnormal expansion of the polyQ tract. The integration of the different types of data allows users to easily compare them, as here shown for Ataxin-1, the polyQ protein involved in spinocerebellar ataxia type 1 (SCA1) disease. Using all available datasets and the data here obtained for Drosophila melanogaster wt and exp Ataxin-1 mutants (also available at EvoPPI3), we show that, in humans, the Ataxin-1 network is much larger than previously thought (380 interactors), with at least 909 interactors. The functional profiling of the newly identified interactors is similar to the ones already reported in the main PPI databases. 16 out of 909 interactors are putative novel SCA1 therapeutic targets, and all but one are already being studied in the context of this disease. The 16 proteins are mainly involved in binding and catalytic activity (mainly kinase activity), functional features already thought to be important in the SCA1 disease.
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Affiliation(s)
- André Sousa
- Instituto de Investigação e Inovação em Saúde (I3S), Universidade do Porto, Rua Alfredo Allen, 208, 4200-135Porto, Portugal
| | - Sara Rocha
- Instituto de Investigação e Inovação em Saúde (I3S), Universidade do Porto, Rua Alfredo Allen, 208, 4200-135Porto, Portugal
| | - Jorge Vieira
- Instituto de Investigação e Inovação em Saúde (I3S), Universidade do Porto, Rua Alfredo Allen, 208, 4200-135Porto, Portugal
- Instituto de Biologia Molecular e Celular (IBMC), Rua Alfredo Allen, 208, 4200-135Porto, Portugal
| | - Miguel Reboiro-Jato
- Department of Computer Science, CINBIO, Universidade de Vigo, ESEI – Escuela Superior de Ingeniería Informática, 32004Ourense, Spain
- SING Research Group, Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO, 36213 Vigo, Spain
| | - Hugo López-Fernández
- Department of Computer Science, CINBIO, Universidade de Vigo, ESEI – Escuela Superior de Ingeniería Informática, 32004Ourense, Spain
- SING Research Group, Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO, 36213 Vigo, Spain
| | - Cristina P. Vieira
- Instituto de Investigação e Inovação em Saúde (I3S), Universidade do Porto, Rua Alfredo Allen, 208, 4200-135Porto, Portugal
- Instituto de Biologia Molecular e Celular (IBMC), Rua Alfredo Allen, 208, 4200-135Porto, Portugal
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Meszaros A, Ahmed J, Russo G, Tompa P, Lazar T. The evolution and polymorphism of mono-amino acid repeats in androgen receptor and their regulatory role in health and disease. Front Med (Lausanne) 2022; 9:1019803. [PMID: 36388907 PMCID: PMC9642029 DOI: 10.3389/fmed.2022.1019803] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Accepted: 09/30/2022] [Indexed: 12/24/2022] Open
Abstract
Androgen receptor (AR) is a key member of nuclear hormone receptors with the longest intrinsically disordered N-terminal domain (NTD) in its protein family. There are four mono-amino acid repeats (polyQ1, polyQ2, polyG, and polyP) located within its NTD, of which two are polymorphic (polyQ1 and polyG). The length of both polymorphic repeats shows clinically important correlations with disease, especially with cancer and neurodegenerative diseases, as shorter and longer alleles exhibit significant differences in expression, activity and solubility. Importantly, AR has also been shown to undergo condensation in the nucleus by liquid-liquid phase separation, a process highly sensitive to protein solubility and concentration. Nonetheless, in prostate cancer cells, AR variants also partition into transcriptional condensates, which have been shown to alter the expression of target gene products. In this review, we summarize current knowledge on the link between AR repeat polymorphisms and cancer types, including mechanistic explanations and models comprising the relationship between condensate formation, polyQ1 length and transcriptional activity. Moreover, we outline the evolutionary paths of these recently evolved amino acid repeats across mammalian species, and discuss new research directions with potential breakthroughs and controversies in the literature.
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Affiliation(s)
- Attila Meszaros
- VIB-VUB Center for Structural Biology, Vlaams Instituut voor Biotechnologie (VIB), Brussels, Belgium
- Structural Biology Brussels (SBB), Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Junaid Ahmed
- VIB-VUB Center for Structural Biology, Vlaams Instituut voor Biotechnologie (VIB), Brussels, Belgium
- Structural Biology Brussels (SBB), Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Giorgio Russo
- VIB-VUB Center for Structural Biology, Vlaams Instituut voor Biotechnologie (VIB), Brussels, Belgium
- Structural Biology Brussels (SBB), Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Peter Tompa
- VIB-VUB Center for Structural Biology, Vlaams Instituut voor Biotechnologie (VIB), Brussels, Belgium
- Structural Biology Brussels (SBB), Vrije Universiteit Brussel (VUB), Brussels, Belgium
- Research Centre for Natural Sciences (RCNS), ELKH, Budapest, Hungary
- *Correspondence: Peter Tompa,
| | - Tamas Lazar
- VIB-VUB Center for Structural Biology, Vlaams Instituut voor Biotechnologie (VIB), Brussels, Belgium
- Structural Biology Brussels (SBB), Vrije Universiteit Brussel (VUB), Brussels, Belgium
- Tamas Lazar,
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Ru D, Li J, Xie O, Peng L, Jiang H, Qiu R. Explainable artificial intelligence based on feature optimization for age at onset prediction of spinocerebellar ataxia type 3. Front Neuroinform 2022; 16:978630. [PMID: 36110986 PMCID: PMC9468717 DOI: 10.3389/fninf.2022.978630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2022] [Accepted: 08/09/2022] [Indexed: 11/13/2022] Open
Abstract
Existing treatments can only delay the progression of spinocerebellar ataxia type 3/Machado-Joseph disease (SCA3/MJD) after onset, so the prediction of the age at onset (AAO) can facilitate early intervention and follow-up to improve treatment efficacy. The objective of this study was to develop an explainable artificial intelligence (XAI) based on feature optimization to provide an interpretable and more accurate AAO prediction. A total of 1,008 affected SCA3/MJD subjects from mainland China were analyzed. The expanded cytosine-adenine-guanine (CAG) trinucleotide repeats of 10 polyQ-related genes were genotyped and included in related models as potential AAO modifiers. The performance of 4 feature optimization methods and 10 machine learning (ML) algorithms were compared, followed by building the XAI based on the SHapley Additive exPlanations (SHAP). The model constructed with an artificial neural network (ANN) and feature optimization of Crossing-Correlation-StepSVM performed best and achieved a coefficient of determination (R2) of 0.653 and mean absolute error (MAE), root mean square error (RMSE), and median absolute error (MedianAE) of 4.544, 6.090, and 3.236 years, respectively. The XAI explained the predicted results, which suggests that the factors affecting the AAO were complex and associated with gene interactions. An XAI based on feature optimization can improve the accuracy of AAO prediction and provide interpretable and personalized prediction.
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Affiliation(s)
- Danlei Ru
- School of Computer Science and Engineering, Central South University, Changsha, Hunan, China
| | - Jinchen Li
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Center for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Ouyi Xie
- School of Computer Science and Engineering, Central South University, Changsha, Hunan, China
| | - Linliu Peng
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Hong Jiang
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
- School of Basic Medical Science, Central South University, Changsha, Hunan, China
- Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, Hunan, China
- Hunan International Scientific and Technological Cooperation Base of Neurodegenerative and Neurogenetic Diseases, Changsha, China
| | - Rong Qiu
- School of Computer Science and Engineering, Central South University, Changsha, Hunan, China
- *Correspondence: Rong Qiu
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