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Treccani M, Veschetti L, Patuzzo C, Malerba G, Vaglio A, Martorana D. Genetic and Non-Genetic Contributions to Eosinophilic Granulomatosis with Polyangiitis: Current Knowledge and Future Perspectives. Curr Issues Mol Biol 2024; 46:7516-7529. [PMID: 39057087 PMCID: PMC11275403 DOI: 10.3390/cimb46070446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2024] [Revised: 07/12/2024] [Accepted: 07/15/2024] [Indexed: 07/28/2024] Open
Abstract
In this work, we present a comprehensive overview of the genetic and non-genetic complexity of eosinophilic granulomatosis with polyangiitis (EGPA). EGPA is a rare complex systemic disease that occurs in people presenting with severe asthma and high eosinophilia. After briefly introducing EGPA and its relationship with the anti-neutrophil cytoplasmic autoantibodies (ANCA)-associated vasculitis (AAVs), we delve into the complexity of this disease. At first, the two main biological actors, ANCA and eosinophils, are presented. Biological and clinical phenotypes related to ANCA positivity or negativity are explained, as well as the role of eosinophils and their pathological subtypes, pointing out their intricate relations with EGPA. Then, the genetics of EGPA are described, providing an overview of the research effort to unravel them. Candidate gene studies have investigated biologically relevant candidate genes; the more recent genome-wide association studies and meta-analyses, able to analyze the whole genome, have confirmed previous associations and discovered novel risk loci; in the end, family-based studies have dissected the contribution of rare variants and the heritability of EGPA. Then, we briefly present the environmental contribution to EGPA, reporting seasonal events and pollutants as triggering factors. In the end, the latest omic research is discussed and the most recent epigenomic, transcriptomic and microbiome studies are presented, highlighting the current challenges, open questions and suggesting approaches to unraveling this complex disease.
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Affiliation(s)
- Mirko Treccani
- GM Lab, Department of Surgery, Dentistry, Gynaecology and Paediatrics, University of Verona, 37134 Verona, Italy;
| | - Laura Veschetti
- Infections and Cystic Fibrosis Unit, Division of Immunology, Transplantation and Infectious Diseases, IRCCS San Raffaele Scientific Institute, 20132 Milano, Italy;
- Vita-Salute San Raffaele University, 20132 Milano, Italy
| | - Cristina Patuzzo
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, 37134 Verona, Italy;
| | - Giovanni Malerba
- GM Lab, Department of Surgery, Dentistry, Gynaecology and Paediatrics, University of Verona, 37134 Verona, Italy;
| | - Augusto Vaglio
- Nephrology and Dialysis Unit, Meyer Children’s Hospital IRCCS, 50139 Florence, Italy;
- Department of Biomedical Experimental and Clinical Sciences “Mario Serio”, University of Florence, 50121 Florence, Italy
| | - Davide Martorana
- Medical Genetics Unit, Department of Onco-Hematology, University Hospital of Parma, 43126 Parma, Italy;
- CoreLab Unit, Research Center, University Hospital of Parma, 43126 Parma, Italy
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Cui H, Srinivasan S, Gao Z, Korkin D. The Extent of Edgetic Perturbations in the Human Interactome Caused by Population-Specific Mutations. Biomolecules 2023; 14:40. [PMID: 38254640 PMCID: PMC11154503 DOI: 10.3390/biom14010040] [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: 08/11/2023] [Revised: 11/30/2023] [Accepted: 12/03/2023] [Indexed: 01/24/2024] Open
Abstract
Until recently, efforts in population genetics have been focused primarily on people of European ancestry. To attenuate this bias, global population studies, such as the 1000 Genomes Project, have revealed differences in genetic variation across ethnic groups. How many of these differences can be attributed to population-specific traits? To answer this question, the mutation data must be linked with functional outcomes. A new "edgotype" concept has been proposed, which emphasizes the interaction-specific, "edgetic", perturbations caused by mutations in the interacting proteins. In this work, we performed systematic in silico edgetic profiling of ~50,000 non-synonymous SNVs (nsSNVs) from the 1000 Genomes Project by leveraging our semi-supervised learning approach SNP-IN tool on a comprehensive set of over 10,000 protein interaction complexes. We interrogated the functional roles of the variants and their impact on the human interactome and compared the results with the pathogenic variants disrupting PPIs in the same interactome. Our results demonstrated that a considerable number of nsSNVs from healthy populations could rewire the interactome. We also showed that the proteins enriched with interaction-disrupting mutations were associated with diverse functions and had implications in a broad spectrum of diseases. Further analysis indicated that distinct gene edgetic profiles among major populations could shed light on the molecular mechanisms behind the population phenotypic variances. Finally, the network analysis revealed that the disease-associated modules surprisingly harbored a higher density of interaction-disrupting mutations from healthy populations. The variation in the cumulative network damage within these modules could potentially account for the observed disparities in disease susceptibility, which are distinctly specific to certain populations. Our work demonstrates the feasibility of a large-scale in silico edgetic study, and reveals insights into the orchestrated play of population-specific mutations in the human interactome.
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Affiliation(s)
- Hongzhu Cui
- Bioinformatics and Computational Biology Program, Worcester Polytechnic Institute, Worcester, MA 01609, USA;
- Chromatography and Mass Spectrometry Division, Thermo Fisher Scientific, San Jose, CA 95134, USA
| | - Suhas Srinivasan
- Data Science Program, Worcester Polytechnic Institute, Worcester, MA 01609, USA;
- Program in Epithelial Biology, Stanford School of Medicine, Stanford, CA 94305, USA
- Center for Personal Dynamic Regulomes, Stanford School of Medicine, Stanford, CA 94305, USA
| | - Ziyang Gao
- Bioinformatics and Computational Biology Program, Worcester Polytechnic Institute, Worcester, MA 01609, USA;
| | - Dmitry Korkin
- Bioinformatics and Computational Biology Program, Worcester Polytechnic Institute, Worcester, MA 01609, USA;
- Data Science Program, Worcester Polytechnic Institute, Worcester, MA 01609, USA;
- Computer Science Department, Worcester Polytechnic Institute, Worcester, MA 01609, USA
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3
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Guzmán-Jiménez A, González-Muñoz S, Cerván-Martín M, Rivera-Egea R, Garrido N, Luján S, Santos-Ribeiro S, Castilla JA, Gonzalvo MC, Clavero A, Vicente FJ, Maldonado V, Villegas-Salmerón J, Burgos M, Jiménez R, Pinto MG, Pereira I, Nunes J, Sánchez-Curbelo J, López-Rodrigo O, Pereira-Caetano I, Marques PI, Carvalho F, Barros A, Bassas L, Seixas S, Gonçalves J, Lopes AM, Larriba S, Palomino-Morales RJ, Carmona FD, Bossini-Castillo L. Contribution of TEX15 genetic variants to the risk of developing severe non-obstructive oligozoospermia. Front Cell Dev Biol 2022; 10:1089782. [PMID: 36589743 PMCID: PMC9797780 DOI: 10.3389/fcell.2022.1089782] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Accepted: 11/28/2022] [Indexed: 12/23/2022] Open
Abstract
Background: Severe spermatogenic failure (SPGF) represents one of the most relevant causes of male infertility. This pathological condition can lead to extreme abnormalities in the seminal sperm count, such as severe oligozoospermia (SO) or non-obstructive azoospermia (NOA). Most cases of SPGF have an unknown aetiology, and it is known that this idiopathic form of male infertility represents a complex condition. In this study, we aimed to evaluate whether common genetic variation in TEX15, which encodes a key player in spermatogenesis, is involved in the susceptibility to idiopathic SPGF. Materials and Methods: We designed a genetic association study comprising a total of 727 SPGF cases (including 527 NOA and 200 SO) and 1,058 unaffected men from the Iberian Peninsula. Following a tagging strategy, three tag single-nucleotide polymorphisms (SNPs) of TEX15 (rs1362912, rs323342, and rs323346) were selected for genotyping using TaqMan probes. Case-control association tests were then performed by logistic regression models. In silico analyses were also carried out to shed light into the putative functional implications of the studied variants. Results: A significant increase in TEX15-rs1362912 minor allele frequency (MAF) was observed in the group of SO patients (MAF = 0.0842) compared to either the control cohort (MAF = 0.0468, OR = 1.90, p = 7.47E-03) or the NOA group (MAF = 0.0472, OR = 1.83, p = 1.23E-02). The genotype distribution of the SO population was also different from those of both control (p = 1.14E-02) and NOA groups (p = 4.33-02). The analysis of functional annotations of the human genome suggested that the effect of the SO-associated TEX15 variants is likely exerted by alteration of the binding affinity of crucial transcription factors for spermatogenesis. Conclusion: Our results suggest that common variation in TEX15 is involved in the genetic predisposition to SO, thus supporting the notion of idiopathic SPGF as a complex trait.
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Affiliation(s)
- Andrea Guzmán-Jiménez
- Departamento de Genética e Instituto de Biotecnología, Centro de Investigación Biomédica (CIBM), Universidad de Granada, Granada, Spain,Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain
| | - Sara González-Muñoz
- Departamento de Genética e Instituto de Biotecnología, Centro de Investigación Biomédica (CIBM), Universidad de Granada, Granada, Spain,Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain
| | - Miriam Cerván-Martín
- Departamento de Genética e Instituto de Biotecnología, Centro de Investigación Biomédica (CIBM), Universidad de Granada, Granada, Spain,Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain
| | - Rocío Rivera-Egea
- Andrology Laboratory and Sperm Bank, IVIRMA Valencia, Valencia, Spain,IVI Foundation, Health Research Institute La Fe, Valencia, Spain
| | - Nicolás Garrido
- IVI Foundation, Health Research Institute La Fe, Valencia, Spain,Servicio de Urología. Hospital Universitari i Politecnic La Fe e Instituto de Investigación Sanitaria La Fe (IIS La Fe), Valencia, Spain
| | - Saturnino Luján
- Servicio de Urología. Hospital Universitari i Politecnic La Fe e Instituto de Investigación Sanitaria La Fe (IIS La Fe), Valencia, Spain
| | - Samuel Santos-Ribeiro
- IVI-RMA Lisbon, Lisbon, Portugal,Department of Obstetrics and Gynecology, Faculty of Medicine, University of Lisbon, Lisbon, Portugal
| | - José A. Castilla
- Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain,Unidad de Reproducción, UGC Obstetricia y Ginecología, HU Virgen de Las Nieves, Granada, Spain,CEIFER Biobanco—GAMETIA, Granada, Spain
| | - M. Carmen Gonzalvo
- Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain,Unidad de Reproducción, UGC Obstetricia y Ginecología, HU Virgen de Las Nieves, Granada, Spain
| | - Ana Clavero
- Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain,Unidad de Reproducción, UGC Obstetricia y Ginecología, HU Virgen de Las Nieves, Granada, Spain
| | - F. Javier Vicente
- Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain,UGC de Urología, HU Virgen de las Nieves, Granada, Spain
| | - Vicente Maldonado
- UGC de Obstetricia y Ginecología, Complejo Hospitalario de Jaén, Jaén, Spain
| | - Javier Villegas-Salmerón
- Departamento de Genética e Instituto de Biotecnología, Centro de Investigación Biomédica (CIBM), Universidad de Granada, Granada, Spain
| | - Miguel Burgos
- Departamento de Genética e Instituto de Biotecnología, Centro de Investigación Biomédica (CIBM), Universidad de Granada, Granada, Spain
| | - Rafael Jiménez
- Departamento de Genética e Instituto de Biotecnología, Centro de Investigación Biomédica (CIBM), Universidad de Granada, Granada, Spain
| | - Maria Graça Pinto
- Centro de Medicina Reprodutiva, Maternidade Alfredo da Costa, Centro Hospitalar Universitário de Lisboa Central, Lisboa, Portugal
| | - Isabel Pereira
- Departamento de Obstetrícia, Ginecologia e Medicina da Reprodução, Hospital de Santa Maria, Centro Hospitalar Universitário de Lisboa Norte, Lisboa, Portugal
| | - Joaquim Nunes
- Departamento de Obstetrícia, Ginecologia e Medicina da Reprodução, Hospital de Santa Maria, Centro Hospitalar Universitário de Lisboa Norte, Lisboa, Portugal
| | - Josvany Sánchez-Curbelo
- Laboratory of Seminology and Embryology, Andrology Service-Fundació Puigvert, Barcelona, Spain
| | - Olga López-Rodrigo
- Laboratory of Seminology and Embryology, Andrology Service-Fundació Puigvert, Barcelona, Spain
| | - Iris Pereira-Caetano
- Departamento de Genética Humana, Instituto Nacional de Saúde Dr. Ricardo Jorge, Lisbon, Portugal
| | - Patricia Isabel Marques
- i3S—Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal,Institute of Molecular Pathology and Immunology of the University of Porto (IPATIMUP), Porto, Portugal
| | - Filipa Carvalho
- i3S—Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal,Serviço de Genética, Departamento de Patologia, Faculdade de Medicina da Universidade do Porto, Porto, Portugal
| | - Alberto Barros
- i3S—Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal,Serviço de Genética, Departamento de Patologia, Faculdade de Medicina da Universidade do Porto, Porto, Portugal
| | - Lluís Bassas
- Laboratory of Seminology and Embryology, Andrology Service-Fundació Puigvert, Barcelona, Spain
| | - Susana Seixas
- i3S—Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal,Institute of Molecular Pathology and Immunology of the University of Porto (IPATIMUP), Porto, Portugal
| | - João Gonçalves
- i3S—Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal,ToxOmics—Centro de Toxicogenómica e Saúde Humana, Nova Medical School, Lisbon, Portugal
| | - Alexandra M. Lopes
- i3S—Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal,CGPP-IBMC—Centro de Genética Preditiva e Preventiva, Instituto de Biologia Molecular e Celular, Universidade do Porto, Porto, Portugal
| | - Sara Larriba
- Human Molecular Genetics Group, Bellvitge Biomedical Research Institute (IDIBELL), L’Hospitalet de Llobregat, Barcelona, Spain
| | - Rogelio J. Palomino-Morales
- Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain,Departamento de Bioquímica y Biología Molecular I, Universidad de Granada, Granada, Spain
| | - F. David Carmona
- Departamento de Genética e Instituto de Biotecnología, Centro de Investigación Biomédica (CIBM), Universidad de Granada, Granada, Spain,Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain,*Correspondence: F. David Carmona, ; Lara Bossini-Castillo,
| | - Lara Bossini-Castillo
- Departamento de Genética e Instituto de Biotecnología, Centro de Investigación Biomédica (CIBM), Universidad de Granada, Granada, Spain,Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain,*Correspondence: F. David Carmona, ; Lara Bossini-Castillo,
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4
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Narykov O, Johnson NT, Korkin D. Predicting protein interaction network perturbation by alternative splicing with semi-supervised learning. Cell Rep 2021; 37:110045. [PMID: 34818539 DOI: 10.1016/j.celrep.2021.110045] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Revised: 07/21/2021] [Accepted: 11/02/2021] [Indexed: 10/19/2022] Open
Abstract
Alternative splicing introduces an additional layer of protein diversity and complexity in regulating cellular functions that can be specific to the tissue and cell type, physiological state of a cell, or disease phenotype. Recent high-throughput experimental studies have illuminated the functional role of splicing events through rewiring protein-protein interactions; however, the extent to which the macromolecular interactions are affected by alternative splicing has yet to be fully understood. In silico methods provide a fast and cheap alternative to interrogating functional characteristics of thousands of alternatively spliced isoforms. Here, we develop an accurate feature-based machine learning approach that predicts whether a protein-protein interaction carried out by a reference isoform is perturbed by an alternatively spliced isoform. Our method, called the alternatively spliced interactions prediction (ALT-IN) tool, is compared with the state-of-the-art PPI prediction tools and shows superior performance, achieving 0.92 in precision and recall values.
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Affiliation(s)
- Oleksandr Narykov
- Department of Computer Science, and Bioinformatics and Computational Biology Program, Worcester Polytechnic Institute, Worcester, MA, USA
| | - Nathan T Johnson
- Department of Computer Science, and Bioinformatics and Computational Biology Program, Worcester Polytechnic Institute, Worcester, MA, USA; Harvard Program in Therapeutic Sciences, Harvard Medical School, and Breast Tumor Immunology Laboratory, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Dmitry Korkin
- Department of Computer Science, and Bioinformatics and Computational Biology Program, Worcester Polytechnic Institute, Worcester, MA, USA.
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5
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GAMUT: A genomics big data management tool. J Biosci 2021. [DOI: 10.1007/s12038-021-00213-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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6
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Pandey R, Johnson N, Cooke L, Johnson B, Chen Y, Pandey M, Chandler J, Mahadevan D. TP53 Mutations as a Driver of Metastasis Signaling in Advanced Cancer Patients. Cancers (Basel) 2021; 13:597. [PMID: 33546249 PMCID: PMC7913278 DOI: 10.3390/cancers13040597] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Revised: 01/26/2021] [Accepted: 01/28/2021] [Indexed: 11/16/2022] Open
Abstract
Molecular profiling with next generation sequencing (NGS) delivers key information on mutant gene sequences, copy number alterations, gene-fusions, and with immunohistochemistry (IHC), is a valuable tool in clinical decision making for patients entering investigational agent trials. Our objective was to elucidate mutational profiles from primary versus metastatic sites from advanced cancer patients to guide rational therapy. All phase I patients (n = 203) with advanced cancer were profiled by commercially available NGS platforms. The samples were annotated by histology, primary and metastatic site, biopsy site, gene mutations, mutation count/gene, and mutant TP53. A molecular profile of each patient was categorized into common and unique mutations, signaling pathways for each profile and TP53 mutations mapped to 3D-structure of p53 bound to DNA and pre/post therapy molecular response. Of the 171 patients analyzed, 145 had genetic alterations from primary and metastatic sites. The predominant histology was adenocarcinoma followed by squamous cell carcinoma, carcinoma of unknown primary site (CUPS), and melanoma. Of 790 unique mutations, TP53 is the most common followed by APC, KRAS, PIK3CA, ATM, PTEN, NOTCH1, BRCA2, BRAF, KMT2D, LRP1B, and CDKN2A. TP53 was found in most metastatic sites and appears to be a key driver of acquired drug resistance. We highlight examples of acquired mutational profiles pre-/post- targeted therapy in multiple tumor types with a menu of potential targeted agents. Conclusion: The mutational profiling of primary and metastatic lesions in cancer patients provides an opportunity to identify TP53 driver 'pathways' that may predict for drug sensitivity/resistance and guide rational drug combinations in clinical trials.
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Affiliation(s)
- Ritu Pandey
- Cancer Center, University of Arizona, Tucson, AZ 85724, USA; (L.C.); (Y.C.)
- Department of Cellular and Molecular Medicine, University of Arizona, Tucson, AZ 85724, USA
| | - Nathan Johnson
- School of Medicine, Vanderbilt University, Nashville, TN 37325, USA;
| | - Laurence Cooke
- Cancer Center, University of Arizona, Tucson, AZ 85724, USA; (L.C.); (Y.C.)
| | | | - Yuliang Chen
- Cancer Center, University of Arizona, Tucson, AZ 85724, USA; (L.C.); (Y.C.)
| | - Manjari Pandey
- West Cancer Center, 7945 Wolf River Blvd, Germantown, TN 38138, USA; (M.P.); (J.C.)
| | - Jason Chandler
- West Cancer Center, 7945 Wolf River Blvd, Germantown, TN 38138, USA; (M.P.); (J.C.)
| | - Daruka Mahadevan
- Mays Cancer Center, University of Texas Health San Antonio, San Antonio, TX 78229, USA
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7
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Yan T, Li J, Zhou X, Yang Z, Zhang Y, Zhang J, Xu N, Huang Y, Yang H. Genetic determinants of fracture non-union: A systematic review from the literature. Gene 2020; 751:144766. [PMID: 32413481 DOI: 10.1016/j.gene.2020.144766] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Accepted: 05/11/2020] [Indexed: 12/28/2022]
Abstract
Approximately 10-15% of fracture patients suffer impaired healing, which is either delayed or even results in non-union. We performed a Systematic Review, aiming to examine the types and frequency of specific genetic abnormalities in patients experiencing bone fracture and to ascertain whether a genetic association exists regarding the tendency for some patients to suffer fracture non-union or postoperative non-union events. GO and KEGG analyses were used to identify the likely function of the genes involved. Furthermore, we evaluated the functional significance of single nucleotide polymorphisms using RegulomeDB and GTEx. Seven eligible studies involving 29 genes and 89 SNPs were analyzed in this review. We found that the polymorphisms in gene NOS2, NOG, BMP4, CYR61, IL1β and FGFR1 apparently predisposed patients to fracture non-union, while the polymorphisms in gene MMP13, BMP6 and FAM5C appeared to provide protection from non-union. Bioinformatics analysis suggested that these genes were enriched in inflammatory pathways, suggesting that inflammation may be a potential factor involved in fracture non-union. Three SNPs (rs17563, rs3753793 and rs2853550) had smaller RegulomeDB scores, indicating significant biological function. In conclusion, we have identified a number of genes and their polymorphisms that might contribute to a genetic susceptibility to fracture non-union. Further studies with larger cohorts will enhance our understanding of fracture non-union and may inform and direct early interventions.
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Affiliation(s)
- Ting Yan
- Department of Nursing, The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Changzhou 213000, China
| | - Jin Li
- Department of Orthopedics Surgery, The Second Affiliated Hospital of Jiaxing University, Jiaxing 314000, China
| | - Xindie Zhou
- Department of Orthopedics, The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Changzhou 213000, China
| | - Zhicheng Yang
- Department of Orthopedics, The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Changzhou 213000, China
| | - Yi Zhang
- Department of Orthopedics, The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Changzhou 213000, China
| | - Junjie Zhang
- Department of Orthopedics, The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Changzhou 213000, China
| | - Nanwei Xu
- Department of Orthopedics, The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Changzhou 213000, China
| | - Yong Huang
- Department of Orthopedics, The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Changzhou 213000, China.
| | - Haoyu Yang
- Department of Orthopedics, Wuxi 9th People's Hospital Affiliated to Soochow University, Wuxi 214000, China.
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8
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Narykov O, Bogatov D, Korkin D. DISPOT: a simple knowledge-based protein domain interaction statistical potential. Bioinformatics 2020; 35:5374-5378. [PMID: 31350874 PMCID: PMC6954640 DOI: 10.1093/bioinformatics/btz587] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2019] [Revised: 06/17/2019] [Accepted: 07/22/2019] [Indexed: 01/01/2023] Open
Abstract
MOTIVATION The complexity of protein-protein interactions (PPIs) is further compounded by the fact that an average protein consists of two or more domains, structurally and evolutionary independent subunits. Experimental studies have demonstrated that an interaction between a pair of proteins is not carried out by all domains constituting each protein, but rather by a select subset. However, determining which domains from each protein mediate the corresponding PPI is a challenging task. RESULTS Here, we present domain interaction statistical potential (DISPOT), a simple knowledge-based statistical potential that estimates the propensity of an interaction between a pair of protein domains, given their structural classification of protein (SCOP) family annotations. The statistical potential is derived based on the analysis of >352 000 structurally resolved PPIs obtained from DOMMINO, a comprehensive database of structurally resolved macromolecular interactions. AVAILABILITY AND IMPLEMENTATION DISPOT is implemented in Python 2.7 and packaged as an open-source tool. DISPOT is implemented in two modes, basic and auto-extraction. The source code for both modes is available on GitHub: https://github.com/korkinlab/dispot and standalone docker images on DockerHub: https://hub.docker.com/r/korkinlab/dispot. The web server is freely available at http://dispot.korkinlab.org/. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Oleksandr Narykov
- Department of Computer Science, Worcester Polytechnic Institute, Worcester, MA, USA
| | - Dmytro Bogatov
- Department of Computer Science, Boston University, Boston, MA, USA
| | - Dmitry Korkin
- Department of Computer Science, Worcester Polytechnic Institute, Worcester, MA, USA.,Bioinformatics and Computational Biology Program, Worcester Polytechnic Institute, Worcester, MA, USA
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9
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Cui H, Srinivasan S, Korkin D. Enriching Human Interactome with Functional Mutations to Detect High-Impact Network Modules Underlying Complex Diseases. Genes (Basel) 2019; 10:E933. [PMID: 31731769 PMCID: PMC6895925 DOI: 10.3390/genes10110933] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2019] [Revised: 11/04/2019] [Accepted: 11/11/2019] [Indexed: 11/16/2022] Open
Abstract
Rapid progress in high-throughput -omics technologies moves us one step closer to the datacalypse in life sciences. In spite of the already generated volumes of data, our knowledge of the molecular mechanisms underlying complex genetic diseases remains limited. Increasing evidence shows that biological networks are essential, albeit not sufficient, for the better understanding of these mechanisms. The identification of disease-specific functional modules in the human interactome can provide a more focused insight into the mechanistic nature of the disease. However, carving a disease network module from the whole interactome is a difficult task. In this paper, we propose a computational framework, Discovering most IMpacted SUbnetworks in interactoMe (DIMSUM), which enables the integration of genome-wide association studies (GWAS) and functional effects of mutations into the protein-protein interaction (PPI) network to improve disease module detection. Specifically, our approach incorporates and propagates the functional impact of non-synonymous single nucleotide polymorphisms (nsSNPs) on PPIs to implicate the genes that are most likely influenced by the disruptive mutations, and to identify the module with the greatest functional impact. Comparison against state-of-the-art seed-based module detection methods shows that our approach could yield modules that are biologically more relevant and have stronger association with the studied disease. We expect for our method to become a part of the common toolbox for the disease module analysis, facilitating the discovery of new disease markers.
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Affiliation(s)
- Hongzhu Cui
- Bioinformatics and Computational Biology Program, Worcester Polytechnic Institute, Worcester, MA 01609, USA
| | - Suhas Srinivasan
- Data Science Program, Worcester Polytechnic Institute, Worcester, MA 01609, USA;
| | - Dmitry Korkin
- Bioinformatics and Computational Biology Program, Worcester Polytechnic Institute, Worcester, MA 01609, USA
- Data Science Program, Worcester Polytechnic Institute, Worcester, MA 01609, USA;
- Computer Science Department, Worcester Polytechnic Institute, Worcester, MA 01609, USA
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Genetic and Epigenetic Regulation of Immune Response and Resistance to Infectious Diseases in Domestic Ruminants. Vet Clin North Am Food Anim Pract 2019; 35:405-429. [PMID: 31590895 DOI: 10.1016/j.cvfa.2019.07.002] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Infectious diseases are the outcome of complex interactions between the host, pathogen, and environment. After exposure to a pathogen, the host immune system uses various mechanisms to remove the pathogen. However, environmental factors and characteristics of pathogens can compromise the host immune responses and subsequently alter the outcome of infection. In this article, genetic and epigenetic factors that shape the individual variation in mounting protective responses are reviewed. Different approaches that have been used by researchers to investigate the genetic regulation of immunity in ruminants and various sources of genetic information are discussed.
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11
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Miller JE, Veturi Y, Ritchie MD. Innovative strategies for annotating the "relationSNP" between variants and molecular phenotypes. BioData Min 2019; 12:10. [PMID: 31114635 PMCID: PMC6518798 DOI: 10.1186/s13040-019-0197-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Accepted: 04/18/2019] [Indexed: 11/10/2022] Open
Abstract
Characterizing how variation at the level of individual nucleotides contributes to traits and diseases has been an area of growing interest since the completion of sequencing the first human genome. Our understanding of how a single nucleotide polymorphism (SNP) leads to a pathogenic phenotype on a genome-wide scale is a fruitful endeavor for anyone interested in developing diagnostic tests, therapeutics, or simply wanting to understand the etiology of a disease or trait. To this end, many datasets and algorithms have been developed as resources/tools to annotate SNPs. One of the most common practices is to annotate coding SNPs that affect the protein sequence. Synonymous variants are often grouped as one type of variant, however there are in fact many tools available to dissect their effects on gene expression. More recently, large consortiums like ENCODE and GTEx have made it possible to annotate non-coding regions. Although annotating variants is a common technique among human geneticists, the constant advances in tools and biology surrounding SNPs requires an updated summary of what is known and the trajectory of the field. This review will discuss the history behind SNP annotation, commonly used tools, and newer strategies for SNP annotation. Additionally, we will comment on the caveats that distinguish approaches from one another, along with gaps in the current state of knowledge, and potential future directions. We do not intend for this to be a comprehensive review for any specific area of SNP annotation, but rather it will be an excellent resource for those unfamiliar with computational tools used to functionally characterize SNPs. In summary, this review will help illustrate how each SNP annotation method impacts the way in which the genetic and molecular etiology of a disease is explored in-silico.
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Affiliation(s)
- Jason E. Miller
- Department of Genetics, Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd., Philadelphia, PA 19104 USA
| | - Yogasudha Veturi
- Department of Genetics, Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd., Philadelphia, PA 19104 USA
| | - Marylyn D. Ritchie
- Department of Genetics, Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd., Philadelphia, PA 19104 USA
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12
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Cui H, Zhao N, Korkin D. Multilayer View of Pathogenic SNVs in Human Interactome through In Silico Edgetic Profiling. J Mol Biol 2018; 430:2974-2992. [DOI: 10.1016/j.jmb.2018.07.012] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2018] [Revised: 06/28/2018] [Accepted: 07/09/2018] [Indexed: 12/21/2022]
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13
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Abstract
The emergence of next-generation sequencing (NGS) over the last 10 years has increased the efficiency of DNA sequencing in terms of speed, ease, and price. However, the exact quantification of a NGS library is crucial in order to obtain good data on sequencing platforms developed by the current market leader Illumina. Different approaches for DNA quantification are available currently and the most commonly used are based on analysis of the physical properties of the DNA through spectrophotometric or fluorometric methods. Although these methods are technically simple, they do not allow exact quantification as can be achieved using a real-time quantitative PCR (qPCR) approach. A qPCR protocol for DNA quantification with applications in NGS library preparation studies is presented here. This can be applied in various fields of study such as medical disorders resulting from nutritional programming disturbances.
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14
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Suravajhala P, Benso A. Prioritizing single-nucleotide polymorphisms and variants associated with clinical mastitis. Adv Appl Bioinform Chem 2017; 10:57-64. [PMID: 28652783 PMCID: PMC5473491 DOI: 10.2147/aabc.s123604] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
Next-generation sequencing technology has provided resources to easily explore and identify candidate single-nucleotide polymorphisms (SNPs) and variants. However, there remains a challenge in identifying and inferring the causal SNPs from sequence data. A problem with different methods that predict the effect of mutations is that they produce false positives. In this hypothesis, we provide an overview of methods known for identifying causal variants and discuss the challenges, fallacies, and prospects in discerning candidate SNPs. We then propose a three-point classification strategy, which could be an additional annotation method in identifying causalities.
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Affiliation(s)
- Prashanth Suravajhala
- Department of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark
| | - Alfredo Benso
- Department of Control and Computer Engineering, Politecnico di Torino, Torino, Italy
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15
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Korkin D. Effect-specific analysis of pathogenic SNVs in human interactome: Leveraging edge-based network robustness. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2017; 2016:2929-2932. [PMID: 28268927 DOI: 10.1109/embc.2016.7591343] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Study of genetic variants in the context of molecular networks has recently gained much attention. However, many of these studies suffer from the lack of functional information about the network rewiring effect of genetic variants. After large-scale homology modeling, plus extracting native structure from PDB database, we performed structure-based prediction about the rewiring effect using our SNP-IN tool, and it covers significantly more variants than experimental characterization. The analysis result confirms the widespread perturbations in human interactome and reveals the network rewiring behavior based on edge-based network robustness concept.
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16
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Garagnani P, Terlizzi R, Cevoli S, Capellari S, Pierangeli G, Pirazzini C, Bacalini MG, Franceschi C, Cortelli P. Genomics and epigenomics. J Headache Pain 2017; 16:A7. [PMID: 28132381 PMCID: PMC4759335 DOI: 10.1186/1129-2377-16-s1-a7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/04/2022] Open
Affiliation(s)
- Paolo Garagnani
- Dipartimento di Medicina Specialistica Diagnostica e Sperimentale, Università di Bologna, Bologna, Italy.
| | - Rossana Terlizzi
- IRCCS Istituto delle Scienze Neurologiche, Bologna, Italy.,Dipartimento di Scienze Neurologiche, Università di Bologna, Bologna, Italy
| | - Sabina Cevoli
- IRCCS Istituto delle Scienze Neurologiche, Bologna, Italy.,Dipartimento di Scienze Neurologiche, Università di Bologna, Bologna, Italy
| | - Sabina Capellari
- IRCCS Istituto delle Scienze Neurologiche, Bologna, Italy.,Dipartimento di Scienze Neurologiche, Università di Bologna, Bologna, Italy
| | - Giulia Pierangeli
- IRCCS Istituto delle Scienze Neurologiche, Bologna, Italy.,Dipartimento di Scienze Neurologiche, Università di Bologna, Bologna, Italy
| | - Chiara Pirazzini
- Dipartimento di Medicina Specialistica Diagnostica e Sperimentale, Università di Bologna, Bologna, Italy
| | - Maria Giulia Bacalini
- Dipartimento di Medicina Specialistica Diagnostica e Sperimentale, Università di Bologna, Bologna, Italy
| | - Claudio Franceschi
- Dipartimento di Medicina Specialistica Diagnostica e Sperimentale, Università di Bologna, Bologna, Italy
| | - Pietro Cortelli
- IRCCS Istituto delle Scienze Neurologiche, Bologna, Italy.,Dipartimento di Scienze Neurologiche, Università di Bologna, Bologna, Italy
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17
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Visvikis-Siest S, Stathopoulou MG. Beyond genome-wide association studies: identifying variants using -omics approaches. Per Med 2015; 12:529-531. [PMID: 29750611 DOI: 10.2217/pme.15.34] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Affiliation(s)
- Sophie Visvikis-Siest
- INSERM UMR U1122; IGE-PCV "Interactions Gène-Environnement en Physiopathologie CardioVasculaire", Université de Lorraine, Faculté de Pharmacie, 30 Rue Lionnois, 54000 Nancy, France
| | - Maria G Stathopoulou
- INSERM UMR U1122; IGE-PCV "Interactions Gène-Environnement en Physiopathologie CardioVasculaire", Université de Lorraine, Faculté de Pharmacie, 30 Rue Lionnois, 54000 Nancy, France
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18
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Iourov IY, Vorsanova SG, Korostelev SA, Zelenova MA, Yurov YB. Long contiguous stretches of homozygosity spanning shortly the imprinted loci are associated with intellectual disability, autism and/or epilepsy. Mol Cytogenet 2015; 8:77. [PMID: 26478745 PMCID: PMC4608298 DOI: 10.1186/s13039-015-0182-z] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2015] [Accepted: 09/27/2015] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Long contiguous stretches of homozygosity (LCSH) (regions/runs of homozygosity) are repeatedly detected by single-nucleotide polymorphism (SNP) chromosomal microarrays. Providing important clues regarding parental relatedness (consanguinity), uniparental disomy, chromosomal recombination or rearrangements, LCSH are rarely considered as a possible epigenetic cause of neurodevelopmental disorders. Additionally, despite being relevant to imprinting, LCSH at imprinted loci have not been truly addressed in terms of pathogenicity. In this study, we examined LCSH in children with unexplained intellectual disability, autism, congenital malformations and/or epilepsy focusing on chromosomal regions which harbor imprinted disease genes. RESULTS Out of 267 cases, 14 (5.2 %) were found to have LCSH at imprinted loci associated with a clinical outcome. There were 5 cases of LCSH at 15p11.2, 4 cases of LCSH at 7q31.2, 3 cases of LCSH at 11p15.5, and 2 cases of LCSH at 7q21.3. Apart from a case of LCSH at 7q31.33q32.3 (~4 Mb in size), all causative LCSH were 1-1.5 Mb in size. Clinically, these cases were characterized by a weak resemblance to corresponding imprinting diseases (i.e., Silver-Russell, Beckwith-Wiedemann, and Prader-Willi/Angelman syndromes), exhibiting distinctive intellectual disability, autistic behavior, developmental delay, seizures and/or facial dysmorphisms. Parental consanguinity was detected in 8 cases (3 %), and these cases did not exhibit LCSH at imprinted loci. CONCLUSIONS This study demonstrates that shorter LCSH at chromosomes 7q21.3, 7q31.2, 11p15.5, and 15p11.2 occur with a frequency of about 5 % in the children with intellectual disability, autism, congenital malformations and/or epilepsy. Consequently, this type of epigenetic mutations appears to be the most common one among children with neurodevelopmental diseases. Finally, since LCSH less than 2.5-10 Mb in size are generally ignored in diagnostic SNP microarray studies, one can conclude that an important epigenetic cause of intellectual disability, autism or epilepsy is actually overlooked.
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Affiliation(s)
- Ivan Y Iourov
- Mental Health Research Center, 117152 Moscow, Russia ; Separated Structural Unit "Clinical Research Institute of Pediatrics", Russian National Research Medical University named after N.I. Pirogov, Ministry of Health of Russian Federation, 125412 Moscow, Russia ; Department of Medical Genetics, Russian Medical Academy of Postgraduate Education, 123995 Moscow, Russia
| | - Svetlana G Vorsanova
- Mental Health Research Center, 117152 Moscow, Russia ; Separated Structural Unit "Clinical Research Institute of Pediatrics", Russian National Research Medical University named after N.I. Pirogov, Ministry of Health of Russian Federation, 125412 Moscow, Russia
| | | | - Maria A Zelenova
- Mental Health Research Center, 117152 Moscow, Russia ; Separated Structural Unit "Clinical Research Institute of Pediatrics", Russian National Research Medical University named after N.I. Pirogov, Ministry of Health of Russian Federation, 125412 Moscow, Russia
| | - Yuri B Yurov
- Mental Health Research Center, 117152 Moscow, Russia ; Separated Structural Unit "Clinical Research Institute of Pediatrics", Russian National Research Medical University named after N.I. Pirogov, Ministry of Health of Russian Federation, 125412 Moscow, Russia
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19
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Tang H, Zhao Z. Bioinformatics drives the applications of next-generation sequencing in translational biomedical research. Methods 2015; 79-80:1-2. [PMID: 25982352 DOI: 10.1016/j.ymeth.2015.04.035] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Affiliation(s)
- Haixu Tang
- School of Informatics and Computing, Indiana University, Bloomington, United States
| | - Zhongming Zhao
- Department of Biomedical Informatics, Vanderbilt University Medical Center, United States
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