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Jin L, Zhang X, Wang J, Wang Y, Wang K, Wang Z, Wang P, Sun X, Hao J, Jin R, Lu D, Ge Q. Epigenetic Regulation of CD8 + Effector T Cell Differentiation by PDCD5. Eur J Immunol 2025; 55:e202451388. [PMID: 40111008 PMCID: PMC11924876 DOI: 10.1002/eji.202451388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2024] [Revised: 03/06/2025] [Accepted: 03/06/2025] [Indexed: 03/22/2025]
Abstract
Epigenetic modification plays a crucial role in establishing the transcriptional program that governs the differentiation of CD8+ effector T cells. However, the mechanisms by which this process is regulated at an early stage, prior to the expression of master transcription factors, are not yet fully understood. In this study, we have identified PDCD5 as an activation-induced molecule that is necessary for the proper differentiation and expansion of antigen-specific CD8+ effector T cells in a mouse model of chronic viral infection. The genetic deletion of Pdcd5 resulted in impaired differentiation and function of effector T cells, while T-cell activation, metabolic reprogramming, and the differentiation of memory/exhausted T cells were largely unaffected. At the molecular level, we observed reduced chromatin accessibility and transcriptional activity of Tbx21 and its regulated genes in Pdcd5-/- CD8+ T cells. We further identified that PRDM9 facilitates the H3K4me3 modification of genes associated with the effector phenotype in CD8+ T cells. The interaction between PDCD5 and PRDM9 promotes the nuclear translocation and lysine methyltransferase activity of PRDM9. Collectively, these findings highlight the crucial role of the PDCD5/PRDM9 axis in epigenetic reprogramming during the early stages of fate determination for effector CD8+ T cell fate.
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Affiliation(s)
- Lixue Jin
- Department of Immunology, School of Basic Medical Sciences, NHC Key Laboratory of Medical Immunology, Beijing Key Laboratory of Tumor Systems Biology, Institute of Systems Biomedicine, Peking University Health Science CenterPeking UniversityBeijingChina
| | - Xin Zhang
- Department of ImmunologySchool of Basic Medical SciencesNHC Key Laboratory of Medical ImmunologyBeijing Key Laboratory of Tumor Systems BiologyInstitute of Systems BiomedicinePeking University Health Science CenterBeijingChina
| | - Jingyi Wang
- Department of Immunology, School of Basic Medical Sciences, NHC Key Laboratory of Medical Immunology, Beijing Key Laboratory of Tumor Systems Biology, Institute of Systems Biomedicine, Peking University Health Science CenterPeking UniversityBeijingChina
| | - Yujia Wang
- Department of Immunology, School of Basic Medical Sciences, NHC Key Laboratory of Medical Immunology, Beijing Key Laboratory of Tumor Systems Biology, Institute of Systems Biomedicine, Peking University Health Science CenterPeking UniversityBeijingChina
| | - Ke Wang
- Department of Immunology, School of Basic Medical Sciences, NHC Key Laboratory of Medical Immunology, Beijing Key Laboratory of Tumor Systems Biology, Institute of Systems Biomedicine, Peking University Health Science CenterPeking UniversityBeijingChina
| | - Zhuolin Wang
- Department of Immunology, School of Basic Medical Sciences, NHC Key Laboratory of Medical Immunology, Beijing Key Laboratory of Tumor Systems Biology, Institute of Systems Biomedicine, Peking University Health Science CenterPeking UniversityBeijingChina
| | - Pingzhang Wang
- Department of Immunology, School of Basic Medical Sciences, NHC Key Laboratory of Medical Immunology, Beijing Key Laboratory of Tumor Systems Biology, Institute of Systems Biomedicine, Peking University Health Science CenterPeking UniversityBeijingChina
| | - Xiuyuan Sun
- Department of Immunology, School of Basic Medical Sciences, NHC Key Laboratory of Medical Immunology, Beijing Key Laboratory of Tumor Systems Biology, Institute of Systems Biomedicine, Peking University Health Science CenterPeking UniversityBeijingChina
| | - Jie Hao
- Department of Immunology, School of Basic Medical Sciences, NHC Key Laboratory of Medical Immunology, Beijing Key Laboratory of Tumor Systems Biology, Institute of Systems Biomedicine, Peking University Health Science CenterPeking UniversityBeijingChina
| | - Rong Jin
- Department of Immunology, School of Basic Medical Sciences, NHC Key Laboratory of Medical Immunology, Beijing Key Laboratory of Tumor Systems Biology, Institute of Systems Biomedicine, Peking University Health Science CenterPeking UniversityBeijingChina
| | - Dan Lu
- Department of ImmunologySchool of Basic Medical SciencesNHC Key Laboratory of Medical ImmunologyBeijing Key Laboratory of Tumor Systems BiologyInstitute of Systems BiomedicinePeking University Health Science CenterBeijingChina
| | - Qing Ge
- Department of Immunology, School of Basic Medical Sciences, NHC Key Laboratory of Medical Immunology, Beijing Key Laboratory of Tumor Systems Biology, Institute of Systems Biomedicine, Peking University Health Science CenterPeking UniversityBeijingChina
- Department of Integration of Chinese and Western MedicineSchool of Basic Medical SciencesPeking UniversityBeijingChina
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2
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Angelo M, Zhang W, Vilseck J, Aoki S. In silico λ-dynamics predicts protein binding specificities to modified RNAs. Nucleic Acids Res 2025; 53:gkaf166. [PMID: 40066880 PMCID: PMC11894534 DOI: 10.1093/nar/gkaf166] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2024] [Revised: 02/19/2025] [Accepted: 02/20/2025] [Indexed: 03/15/2025] Open
Abstract
RNA modifications shape gene expression through a variety of chemical changes to canonical RNA bases. Although numbering in the hundreds, only a few RNA modifications are well characterized, in part due to the absence of methods to identify modification sites. Antibodies remain a common tool to identify modified RNA and infer modification sites through straightforward applications. However, specificity issues can result in off-target binding and confound conclusions. This work utilizes in silico λ-dynamics to efficiently estimate binding free energy differences of modification-targeting antibodies between a variety of naturally occurring RNA modifications. Crystal structures of inosine and N6-methyladenosine (m6A) targeting antibodies bound to their modified ribonucleosides were determined and served as structural starting points. λ-Dynamics was utilized to predict RNA modifications that permit or inhibit binding to these antibodies. In vitro RNA-antibody binding assays supported the accuracy of these in silico results. High agreement between experimental and computed binding propensities demonstrated that λ-dynamics can serve as a predictive screen for antibody specificity against libraries of RNA modifications. More importantly, this strategy is an innovative way to elucidate how hundreds of known RNA modifications interact with biological molecules without the limitations imposed by in vitro or in vivo methodologies.
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Affiliation(s)
- Murphy Angelo
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, 635 Barnhill Drive, Indianapolis, IN 46202, United States
| | - Wen Zhang
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, 635 Barnhill Drive, Indianapolis, IN 46202, United States
- Melvin and Bren Simon Cancer Center, 535 Barnhill Drive, Indianapolis, IN 46202, United States
| | - Jonah Z Vilseck
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, 635 Barnhill Drive, Indianapolis, IN 46202, United States
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN 46202, United States
| | - Scott T Aoki
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, 635 Barnhill Drive, Indianapolis, IN 46202, United States
- Melvin and Bren Simon Cancer Center, 535 Barnhill Drive, Indianapolis, IN 46202, United States
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3
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Meng Y, Huang R. Decoding the protein methylome: Identification, validation, and functional insights. Bioorg Med Chem 2025; 118:118056. [PMID: 39754853 PMCID: PMC11735303 DOI: 10.1016/j.bmc.2024.118056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2024] [Revised: 12/24/2024] [Accepted: 12/24/2024] [Indexed: 01/06/2025]
Abstract
Protein methylation regulates diverse cellular processes including gene expression and DNA repair. This review discusses the methods of identifying and validating substrates for protein methyltransferases (MTases), as well as the biological roles of methylation. Meanwhile, we outline continued efforts necessary to fully map MTase-substrate pairs and uncover the complex regulatory roles of protein methylation in cellular function.
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Affiliation(s)
- Ying Meng
- Borch Department of Medicinal Chemistry and Molecular Pharmacology, Purdue Institute for Drug Discovery, Purdue University Center for Cancer Research, Purdue University, West Lafayette, IN 47907, United States
| | - Rong Huang
- Borch Department of Medicinal Chemistry and Molecular Pharmacology, Purdue Institute for Drug Discovery, Purdue University Center for Cancer Research, Purdue University, West Lafayette, IN 47907, United States.
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Dai W, Qiao X, Fang Y, Guo R, Bai P, Liu S, Li T, Jiang Y, Wei S, Na Z, Xiao X, Li D. Epigenetics-targeted drugs: current paradigms and future challenges. Signal Transduct Target Ther 2024; 9:332. [PMID: 39592582 PMCID: PMC11627502 DOI: 10.1038/s41392-024-02039-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2024] [Revised: 10/14/2024] [Accepted: 10/29/2024] [Indexed: 11/28/2024] Open
Abstract
Epigenetics governs a chromatin state regulatory system through five key mechanisms: DNA modification, histone modification, RNA modification, chromatin remodeling, and non-coding RNA regulation. These mechanisms and their associated enzymes convey genetic information independently of DNA base sequences, playing essential roles in organismal development and homeostasis. Conversely, disruptions in epigenetic landscapes critically influence the pathogenesis of various human diseases. This understanding has laid a robust theoretical groundwork for developing drugs that target epigenetics-modifying enzymes in pathological conditions. Over the past two decades, a growing array of small molecule drugs targeting epigenetic enzymes such as DNA methyltransferase, histone deacetylase, isocitrate dehydrogenase, and enhancer of zeste homolog 2, have been thoroughly investigated and implemented as therapeutic options, particularly in oncology. Additionally, numerous epigenetics-targeted drugs are undergoing clinical trials, offering promising prospects for clinical benefits. This review delineates the roles of epigenetics in physiological and pathological contexts and underscores pioneering studies on the discovery and clinical implementation of epigenetics-targeted drugs. These include inhibitors, agonists, degraders, and multitarget agents, aiming to identify practical challenges and promising avenues for future research. Ultimately, this review aims to deepen the understanding of epigenetics-oriented therapeutic strategies and their further application in clinical settings.
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Affiliation(s)
- Wanlin Dai
- Center of Reproductive Medicine, Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Xinbo Qiao
- Department of Orthopedics, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yuanyuan Fang
- Center of Reproductive Medicine, Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Renhao Guo
- Center of Reproductive Medicine, Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Peng Bai
- Department of Forensic Genetics, West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, China
| | - Shuang Liu
- Shenyang Maternity and Child Health Hospital, Shenyang, China
| | - Tingting Li
- Department of General Internal Medicine VIP Ward, Liaoning Cancer Hospital & Institute, Shenyang, China
| | - Yutao Jiang
- Center of Reproductive Medicine, Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Shuang Wei
- Center of Reproductive Medicine, Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Zhijing Na
- Center of Reproductive Medicine, Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China.
- NHC Key Laboratory of Advanced Reproductive Medicine and Fertility (China Medical University), National Health Commission, Shenyang, China.
| | - Xue Xiao
- Department of Gynecology and Obstetrics, West China Second Hospital, Sichuan University, Chengdu, China.
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second Hospital, Sichuan University, Chengdu, China.
| | - Da Li
- Center of Reproductive Medicine, Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China.
- NHC Key Laboratory of Advanced Reproductive Medicine and Fertility (China Medical University), National Health Commission, Shenyang, China.
- Key Laboratory of Reproductive Dysfunction Diseases and Fertility Remodeling of Liaoning Province, Shenyang, China.
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5
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Barron MP, Vilseck JZ. A λ-Dynamics Investigation of Insulin Wakayama and Other A3 Variant Binding Affinities to the Insulin Receptor. J Chem Inf Model 2024; 64:5657-5670. [PMID: 38963805 PMCID: PMC11268370 DOI: 10.1021/acs.jcim.4c00662] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2024] [Revised: 06/21/2024] [Accepted: 06/24/2024] [Indexed: 07/06/2024]
Abstract
Insulin Wakayama is a clinical insulin variant where a conserved valine at the third residue on insulin's A chain (ValA3) is replaced with a leucine (LeuA3), weakening insulin receptor (IR) binding by 140-500-fold. This severe impact on binding from a subtle modification has posed an intriguing problem for decades. Although experimental investigations of natural and unnatural A3 mutations have highlighted the sensitivity of insulin-IR binding at this site, atomistic explanations of these binding trends have remained elusive. We investigate this problem computationally using λ-dynamics free energy calculations to model structural changes in response to perturbations of the ValA3 side chain and to calculate associated relative changes in binding free energy (ΔΔGbind). The Wakayama LeuA3 mutation and seven other A3 substitutions were studied in this work. The calculated ΔΔGbind results showed high agreement compared to experimental binding potencies with a Pearson correlation of 0.88 and a mean unsigned error of 0.68 kcal/mol. Extensive structural analyses of λ-dynamics trajectories revealed that critical interactions were disrupted between insulin and the insulin receptor as a result of the A3 mutations. This investigation also quantifies the effect that adding an A3 Cδ atom or losing an A3 Cγ atom has on insulin's binding affinity to the IR. Thus, λ-dynamics was able to successfully model the effects of mutations to insulin's A3 side chain on its protein-protein interactions with the IR and shed new light on a decades-old mystery: the exquisite sensitivity of hormone-receptor binding to a subtle modification of an invariant insulin residue.
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Affiliation(s)
- Monica P Barron
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana 46202, United States
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana 46202, United States
| | - Jonah Z Vilseck
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana 46202, United States
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana 46202, United States
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6
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Barron MP, Vilseck JZ. A λ-dynamics investigation of insulin Wakayama and other A3 variant binding affinities to the insulin receptor. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.15.585233. [PMID: 38559010 PMCID: PMC10979964 DOI: 10.1101/2024.03.15.585233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Insulin Wakayama is a clinical insulin variant where a conserved valine at the third residue on insulin's A chain (ValA3) is replaced with a leucine (LeuA3), impairing insulin receptor (IR) binding by 140-500 fold. This severe impact on binding from such a subtle modification has posed an intriguing problem for decades. Although experimental investigations of natural and unnatural A3 mutations have highlighted the sensitivity of insulin-IR binding to minor changes at this site, an atomistic explanation of these binding trends has remained elusive. We investigate this problem computationally using λ-dynamics free energy calculations to model structural changes in response to perturbations of the ValA3 side chain and to calculate associated relative changes in binding free energy (ΔΔGbind). The Wakayama LeuA3 mutation and seven other A3 substitutions were studied in this work. The calculated ΔΔGbind results showed high agreement compared to experimental binding potencies with a Pearson correlation of 0.88 and a mean unsigned error of 0.68 kcal/mol. Extensive structural analyses of λ-dynamics trajectories revealed that critical interactions were disrupted between insulin and the insulin receptor as a result of the A3 mutations. This investigation also quantifies the effect that adding an A3 Cδ atom or losing an A3 Cγ atom has on insulin's binding affinity to the IR. Thus, λ-dynamics was able to successfully model the effects of subtle modifications to insulin's A3 side chain on its protein-protein interactions with the IR and shed new light on a decades-old mystery: the exquisite sensitivity of hormone-receptor binding to a subtle modification of an invariant insulin residue.
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Affiliation(s)
- Monica P. Barron
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana 46202, United States
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana 46202, United States
| | - Jonah Z. Vilseck
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana 46202, United States
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana 46202, United States
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7
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Angelo M, Zhang W, Vilseck JZ, Aoki ST. In silico λ-dynamics predicts protein binding specificities to modified RNAs. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.26.577511. [PMID: 38328125 PMCID: PMC10849657 DOI: 10.1101/2024.01.26.577511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Abstract
RNA modifications shape gene expression through a smorgasbord of chemical changes to canonical RNA bases. Although numbering in the hundreds, only a few RNA modifications are well characterized, in part due to the absence of methods to identify modification sites. Antibodies remain a common tool to identify modified RNA and infer modification sites through straightforward applications. However, specificity issues can result in off-target binding and confound conclusions. This work utilizes in silico λ-dynamics to efficiently estimate binding free energy differences of modification-targeting antibodies between a variety of naturally occurring RNA modifications. Crystal structures of inosine and N6-methyladenosine (m6A) targeting antibodies bound to their modified ribonucleosides were determined and served as structural starting points. λ-Dynamics was utilized to predict RNA modifications that permit or inhibit binding to these antibodies. In vitro RNA-antibody binding assays supported the accuracy of these in silico results. High agreement between experimental and computed binding propensities demonstrated that λ-dynamics can serve as a predictive screen for antibody specificity against libraries of RNA modifications. More importantly, this strategy is an innovative way to elucidate how hundreds of known RNA modifications interact with biological molecules without the limitations imposed by in vitro or in vivo methodologies.
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Affiliation(s)
- Murphy Angelo
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, 635 Barnhill Drive, Indianapolis, IN 46202, USA
| | - Wen Zhang
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, 635 Barnhill Drive, Indianapolis, IN 46202, USA
- Melvin and Bren Simon Cancer Center, 535 Barnhill Drive, Indianapolis, IN 46202, USA
| | - Jonah Z. Vilseck
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, 635 Barnhill Drive, Indianapolis, IN 46202, USA
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Scott T. Aoki
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, 635 Barnhill Drive, Indianapolis, IN 46202, USA
- Melvin and Bren Simon Cancer Center, 535 Barnhill Drive, Indianapolis, IN 46202, USA
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Ladias P, Markopoulos GS, Kostoulas C, Bouba I, Markoula S, Georgiou I. Cancer Associated PRDM9: Implications for Linking Genomic Instability and Meiotic Recombination. Int J Mol Sci 2023; 24:16522. [PMID: 38003713 PMCID: PMC10671843 DOI: 10.3390/ijms242216522] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2023] [Revised: 11/10/2023] [Accepted: 11/11/2023] [Indexed: 11/26/2023] Open
Abstract
The PR domain-containing 9 or PRDM9 is a gene recognized for its fundamental role in meiosis, a process essential for forming reproductive cells. Recent findings have implicated alterations in the PRDM9, particularly its zinc finger motifs, in the onset and progression of cancer. This association is manifested through genomic instability and the misregulation of genes critical to cell growth, proliferation, and differentiation. In our comprehensive study, we harnessed advanced bioinformatic mining tools to delve deep into the intricate relationship between PRDM9F and cancer. We analyzed 136,752 breakpoints and found an undeniable association between specific PRDM9 motifs and the occurrence of double-strand breaks, a phenomenon evidenced in every cancer profile examined. Utilizing R statistical querying and the Regioner package, 55 unique sequence variations of PRDM9 were statistically correlated with cancer, from a pool of 1024 variations. A robust analysis using the Enrichr tool revealed prominent associations with various cancer types. Moreover, connections were noted with specific phenotypic conditions and molecular functions, underlining the pervasive influence of PRDM9 variations in the biological spectrum. The Reactome tool identified 25 significant pathways associated with cancer, offering insights into the mechanistic underpinnings linking PRDM9 to cancer progression. This detailed analysis not only confirms the pivotal role of PRDM9 in cancer development, but also unveils a complex network of biological processes influenced by its variations. The insights gained lay a solid foundation for future research aimed at deciphering the mechanistic pathways of PRDM9, offering prospects for targeted interventions and innovative therapeutic approaches in cancer management.
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Affiliation(s)
- Paris Ladias
- Laboratory of Medical Genetics in Clinical Practice, Faculty of Medicine, School of Health Sciences, University of Ioannina, 45 110 Ioannina, Greece; (P.L.); (C.K.); (I.B.)
| | - Georgios S. Markopoulos
- Neurosurgical Institute, Faculty of Medicine, School of Health Sciences, University of Ioannina, 45 110 Ioannina, Greece;
| | - Charilaos Kostoulas
- Laboratory of Medical Genetics in Clinical Practice, Faculty of Medicine, School of Health Sciences, University of Ioannina, 45 110 Ioannina, Greece; (P.L.); (C.K.); (I.B.)
| | - Ioanna Bouba
- Laboratory of Medical Genetics in Clinical Practice, Faculty of Medicine, School of Health Sciences, University of Ioannina, 45 110 Ioannina, Greece; (P.L.); (C.K.); (I.B.)
| | - Sofia Markoula
- Department of Neurology, Faculty of Medicine, School of Health Sciences, University of Ioannina, 45 110 Ioannina, Greece;
| | - Ioannis Georgiou
- Laboratory of Medical Genetics in Clinical Practice, Faculty of Medicine, School of Health Sciences, University of Ioannina, 45 110 Ioannina, Greece; (P.L.); (C.K.); (I.B.)
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