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Article ; Online: Expression of Concern: Expression of junctional adhesion molecule-A prevents spontaneous and random motility.

Bazzoni, Gianfranco / Tonetti, Paolo / Manzi, Luca / Cera, Maria R / Balconi, Giovanna / Dejana, Elisabetta

2024 Volume 137, Issue 2

Language	English
Publishing date	2024-01-30
Publishing country	England
Document type	Journal Article ; Expression of Concern
ZDB-ID	2993-2
ISSN	1477-9137 ; 0021-9533
ISSN (online)	1477-9137
ISSN	0021-9533
DOI	10.1242/jcs.261904
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Zs.MG 14: Show issues

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Article ; Online: The similarity of inherited diseases (I): clinical similarity within the phenotypic series.

Gamba, Alessio / Salmona, Mario / Bazzoni, Gianfranco

BMC medical genomics

2021 Volume 14, Issue 1, Page(s) 52

Abstract: Background: Mutations of different genes often result in clinically similar diseases. Among the datasets of similar diseases, we analyzed the 'phenotypic series' from Online Mendelian Inheritance in Man and examined the similarity of the diseases that ... ...

Abstract	Background: Mutations of different genes often result in clinically similar diseases. Among the datasets of similar diseases, we analyzed the 'phenotypic series' from Online Mendelian Inheritance in Man and examined the similarity of the diseases that belong to the same phenotypic series, because we hypothesize that clinical similarity may unveil shared pathogenic mechanisms. Methods: Specifically, for each pair of diseases, we quantified their similarity, based on both number and information content of the shared clinical phenotypes. Then, we assembled the disease similarity network, in which nodes represent diseases and edges represent clinical similarities. Results: On average, diseases have high similarity with other diseases of their own phenotypic series, even though about one third of diseases have their maximal similarity with a disease of another series. Consequently, the network is assortative (i.e., diseases belonging to the same series link preferentially to each other), but the series differ in the way they distribute within the network. Specifically, heterophobic series, which minimize links to other series, form islands at the periphery of the network, whereas heterophilic series, which are highly inter-connected with other series, occupy the center of the network. Conclusions: The finding that the phenotypic series display not only internal similarity (assortativity) but also varying degrees of external similarity (ranging from heterophobicity to heterophilicity) calls for investigation of biological mechanisms that might be shared among different series. The correlation between the clinical and biological similarities of the phenotypic series is analyzed in Part II of this study
MeSH term(s)	Algorithms ; Computational Biology ; Humans ; Phenotype
Language	English
Publishing date	2021-02-23
Publishing country	England
Document type	Journal Article
ISSN	1755-8794
ISSN (online)	1755-8794
DOI	10.1186/s12920-021-00900-7
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Article ; Online: The similarity of inherited diseases (I)

Alessio Gamba / Mario Salmona / Gianfranco Bazzoni

BMC Medical Genomics, Vol 14, Iss 1, Pp 1-

clinical similarity within the phenotypic series

2021 Volume 12

Abstract: Abstract Background Mutations of different genes often result in clinically similar diseases. Among the datasets of similar diseases, we analyzed the ‘phenotypic series’ from Online Mendelian Inheritance in Man and examined the similarity of the diseases ...

Abstract	Abstract Background Mutations of different genes often result in clinically similar diseases. Among the datasets of similar diseases, we analyzed the ‘phenotypic series’ from Online Mendelian Inheritance in Man and examined the similarity of the diseases that belong to the same phenotypic series, because we hypothesize that clinical similarity may unveil shared pathogenic mechanisms. Methods Specifically, for each pair of diseases, we quantified their similarity, based on both number and information content of the shared clinical phenotypes. Then, we assembled the disease similarity network, in which nodes represent diseases and edges represent clinical similarities. Results On average, diseases have high similarity with other diseases of their own phenotypic series, even though about one third of diseases have their maximal similarity with a disease of another series. Consequently, the network is assortative (i.e., diseases belonging to the same series link preferentially to each other), but the series differ in the way they distribute within the network. Specifically, heterophobic series, which minimize links to other series, form islands at the periphery of the network, whereas heterophilic series, which are highly inter-connected with other series, occupy the center of the network. Conclusions The finding that the phenotypic series display not only internal similarity (assortativity) but also varying degrees of external similarity (ranging from heterophobicity to heterophilicity) calls for investigation of biological mechanisms that might be shared among different series. The correlation between the clinical and biological similarities of the phenotypic series is analyzed in Part II of this study1.
Keywords	Gene mutations ; Inherited diseases ; Disease phenotypes ; Differential diagnosis ; Network analysis ; Graph theory ; Internal medicine ; RC31-1245 ; Genetics ; QH426-470
Subject code	610
Language	English
Publishing date	2021-02-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Quantitative analysis of proteins which are members of the same protein complex but cause locus heterogeneity in disease.

Gamba, Alessio / Salmona, Mario / Bazzoni, Gianfranco

Scientific reports

2020 Volume 10, Issue 1, Page(s) 10423

Abstract: It is still largely unknown how mutations in different genes cause similar diseases - a condition known as locus heterogeneity. A likely explanation is that the different proteins encoded by the locus heterogeneity genes participate in the same ... ...

Abstract	It is still largely unknown how mutations in different genes cause similar diseases - a condition known as locus heterogeneity. A likely explanation is that the different proteins encoded by the locus heterogeneity genes participate in the same biological function and, specifically, that they belong to the same protein complex. Here we report that, in up to 30% of the instances of locus heterogeneity, the disease-causing proteins are indeed members of the same protein complex. Moreover, we observed that, in many instances, the diseases and protein complexes only partially intersect. Among the possible explanations, we surmised that some genes that encode proteins in the complex have not yet been reported as causing disease and are therefore candidate disease genes. Mutations of known human disease genes and murine orthologs of candidate disease genes that encode proteins in the same protein complex do in fact often cause similar phenotypes in humans and mice. Furthermore, we found that the disease-complex intersection is not only incomplete but also non-univocal, with many examples of one disease intersecting more than one protein complex or one protein complex intersecting more than one disease. These limits notwithstanding, this study shows that action on proteins in the same complex is a widespread pathogenic mechanism underlying numerous instances of locus heterogeneity.
MeSH term(s)	Animals ; Databases, Genetic ; Databases, Protein ; Genetic Heterogeneity ; Humans ; Mutation ; Phenotype ; Proteins
Chemical Substances	Proteins
Language	English
Publishing date	2020-06-26
Publishing country	England
Document type	Journal Article
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-020-66836-7
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Article ; Online: The similarity of inherited diseases (II): clinical and biological similarity between the phenotypic series.

Gamba, Alessio / Salmona, Mario / Cantù, Laura / Bazzoni, Gianfranco

BMC medical genomics

2020 Volume 13, Issue 1, Page(s) 139

Abstract: Background: Despite being caused by mutations in different genes, diseases in the same phenotypic series are clinically similar, as reported in Part I of this study. Here, in Part II, we hypothesized that the phenotypic series too might be clinically ... ...

Abstract	Background: Despite being caused by mutations in different genes, diseases in the same phenotypic series are clinically similar, as reported in Part I of this study. Here, in Part II, we hypothesized that the phenotypic series too might be clinically similar. Furthermore, on the assumption that gene mutations indirectly cause clinical phenotypes by directly affecting biological functions, we hypothesized that clinically similar phenotypic series might be biologically similar as well. Methods: To test these hypotheses, we generated a clinical similarity network and a set of biological similarity networks. In both types of network, the nodes represent the phenotypic series, and the edges linking the nodes indicate the similarity of the linked phenotypic series. The weight of each edge is proportional to a similarity coefficient, which depends on the clinical phenotypes and the biological features that are shared by the linked phenotypic series, in the clinical and biological similarity networks, respectively. Results: After assembling and analyzing the networks, we raised the threshold for the similarity coefficient, to retain edges of progressively greater weight. This way all the networks were gradually split into fragments, composed of phenotypic series with increasingly greater degrees of similarity. Finally, by comparing the fragments from the two types of network, we defined subsets of phenotypic series with varying types and degrees of clinical and biological correlation. Conclusions: Like the individual diseases, the phenotypic series too are clinically and biologically similar to each other. Furthermore, our findings unveil different modalities of correlation between the clinical manifestations and the biological features of the inherited diseases.
MeSH term(s)	Algorithms ; Computational Biology/methods ; Gene Regulatory Networks ; Genetic Diseases, Inborn/classification ; Genetic Diseases, Inborn/genetics ; Humans ; Phenotype
Language	English
Publishing date	2020-09-24
Publishing country	England
Document type	Journal Article
ISSN	1755-8794
ISSN (online)	1755-8794
DOI	10.1186/s12920-020-00793-y
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Article ; Online: Pathobiology of junctional adhesion molecules.

Bazzoni, Gianfranco

Antioxidants & redox signaling

2011 Volume 15, Issue 5, Page(s) 1221–1234

Abstract: Junctional adhesion molecules are transmembrane proteins that belong to the immunoglobulin superfamily. In addition to their localization in close proximity to the tight junctions in endothelial and epithelial cells, junctional adhesion molecules are ... ...

Abstract	Junctional adhesion molecules are transmembrane proteins that belong to the immunoglobulin superfamily. In addition to their localization in close proximity to the tight junctions in endothelial and epithelial cells, junctional adhesion molecules are also expressed in circulating cells that do not form junctions, such as leukocytes and platelets. As a consequence, these proteins are associated not only with the permeability-regulating barrier function of the tight junctions, but also with other biologic processes, such as inflammatory reactions, responses to vascular injury, and tumor angiogenesis. Furthermore, because of their transmembrane topology, junctional adhesion molecules are poised both for receiving inputs from the cell interior (their expression, localization, and function being regulated in response to inflammatory cytokines and growth factors) and for translating extracellular adhesive events into functional responses. This review focuses on the different roles of junctional adhesion molecules in normal and pathologic conditions, with emphasis on inflammatory reactions and vascular responses to injury.
MeSH term(s)	Animals ; Cell Adhesion Molecules/chemistry ; Cell Adhesion Molecules/metabolism ; Humans ; Inflammation/metabolism ; Junctional Adhesion Molecules ; Leukocytes/metabolism ; Neoplasms/metabolism ; Protein Binding/physiology ; Tight Junctions/metabolism ; Vascular Diseases/metabolism
Chemical Substances	Cell Adhesion Molecules ; Junctional Adhesion Molecules
Language	English
Publishing date	2011-09-01
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Review
ZDB-ID	1483836-9
ISSN	1557-7716 ; 1523-0864
ISSN (online)	1557-7716
ISSN	1523-0864
DOI	10.1089/ars.2010.3867
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Article ; Online: Quantitative analysis of proteins which are members of the same protein complex but cause locus heterogeneity in disease

Alessio Gamba / Mario Salmona / Gianfranco Bazzoni

Scientific Reports, Vol 10, Iss 1, Pp 1-

2020 Volume 10

Abstract: Abstract It is still largely unknown how mutations in different genes cause similar diseases – a condition known as locus heterogeneity. A likely explanation is that the different proteins encoded by the locus heterogeneity genes participate in the same ... ...

Abstract	Abstract It is still largely unknown how mutations in different genes cause similar diseases – a condition known as locus heterogeneity. A likely explanation is that the different proteins encoded by the locus heterogeneity genes participate in the same biological function and, specifically, that they belong to the same protein complex. Here we report that, in up to 30% of the instances of locus heterogeneity, the disease-causing proteins are indeed members of the same protein complex. Moreover, we observed that, in many instances, the diseases and protein complexes only partially intersect. Among the possible explanations, we surmised that some genes that encode proteins in the complex have not yet been reported as causing disease and are therefore candidate disease genes. Mutations of known human disease genes and murine orthologs of candidate disease genes that encode proteins in the same protein complex do in fact often cause similar phenotypes in humans and mice. Furthermore, we found that the disease-complex intersection is not only incomplete but also non-univocal, with many examples of one disease intersecting more than one protein complex or one protein complex intersecting more than one disease. These limits notwithstanding, this study shows that action on proteins in the same complex is a widespread pathogenic mechanism underlying numerous instances of locus heterogeneity.
Keywords	Medicine ; R ; Science ; Q
Subject code	612
Language	English
Publishing date	2020-06-01T00:00:00Z
Publisher	Nature Publishing Group
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: The similarity of inherited diseases (II)

Alessio Gamba / Mario Salmona / Laura Cantù / Gianfranco Bazzoni

BMC Medical Genomics, Vol 13, Iss 1, Pp 1-

clinical and biological similarity between the phenotypic series

2020 Volume 11

Abstract: Abstract Background Despite being caused by mutations in different genes, diseases in the same phenotypic series are clinically similar, as reported in Part I of this study. Here, in Part II, we hypothesized that the phenotypic series too might be ... ...

Abstract	Abstract Background Despite being caused by mutations in different genes, diseases in the same phenotypic series are clinically similar, as reported in Part I of this study. Here, in Part II, we hypothesized that the phenotypic series too might be clinically similar. Furthermore, on the assumption that gene mutations indirectly cause clinical phenotypes by directly affecting biological functions, we hypothesized that clinically similar phenotypic series might be biologically similar as well. Methods To test these hypotheses, we generated a clinical similarity network and a set of biological similarity networks. In both types of network, the nodes represent the phenotypic series, and the edges linking the nodes indicate the similarity of the linked phenotypic series. The weight of each edge is proportional to a similarity coefficient, which depends on the clinical phenotypes and the biological features that are shared by the linked phenotypic series, in the clinical and biological similarity networks, respectively. Results After assembling and analyzing the networks, we raised the threshold for the similarity coefficient, to retain edges of progressively greater weight. This way all the networks were gradually split into fragments, composed of phenotypic series with increasingly greater degrees of similarity. Finally, by comparing the fragments from the two types of network, we defined subsets of phenotypic series with varying types and degrees of clinical and biological correlation. Conclusions Like the individual diseases, the phenotypic series too are clinically and biologically similar to each other. Furthermore, our findings unveil different modalities of correlation between the clinical manifestations and the biological features of the inherited diseases.
Keywords	Gene mutations ; Inherited diseases ; Disease phenotypes ; Biological processes ; Network analysis ; Ontologies ; Internal medicine ; RC31-1245 ; Genetics ; QH426-470
Subject code	610
Language	English
Publishing date	2020-09-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Signalling pathways and adhesion molecules as targets for antiangiogenesis therapy in tumors.

Bazzoni, Gianfranco

Advances in experimental medicine and biology

2008 Volume 610, Page(s) 74–87

MeSH term(s)	Angiogenesis Inhibitors/pharmacology ; Animals ; Cadherins/metabolism ; Cell Adhesion ; Cell Adhesion Molecules/metabolism ; Endothelium/metabolism ; Humans ; Neoplasms/therapy ; Neovascularization, Pathologic ; Signal Transduction ; Vascular Endothelial Growth Factor A/metabolism
Chemical Substances	Angiogenesis Inhibitors ; Cadherins ; Cell Adhesion Molecules ; Vascular Endothelial Growth Factor A
Language	English
Publishing date	2008
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Review
ISSN	2214-8019 ; 0065-2598
ISSN (online)	2214-8019
ISSN	0065-2598
DOI	10.1007/978-0-387-73898-7_6
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Article: Endothelial tight junctions: permeable barriers of the vessel wall.

Bazzoni, Gianfranco

Thrombosis and haemostasis

2006 Volume 95, Issue 1, Page(s) 36–42

Abstract: The endothelial lining of the vessel wall is a permeable barrier, which is located at the interface between the vascular and the perivascular compartments. Although the endothelium acts as an efficient barrier that strictly separates the two compartments, ...

Abstract	The endothelial lining of the vessel wall is a permeable barrier, which is located at the interface between the vascular and the perivascular compartments. Although the endothelium acts as an efficient barrier that strictly separates the two compartments, it may also act as a permeable filter which allows selective exchange of solutes and water between the luminal and abluminal sides of the barrier. Similarly to epithelia, also in the endothelium permeability follows two distinct routes, which have been termed transcellular pathway (across the apical and basolateral membranes of individual cells) and paracellular pathway (through the intercellular junctions and the lateral spaces between contacting cells). After an initial description of the two pathways, the review focuses on the cellular and molecular basis of the paracellular pathway, with emphasis on the role of intercellular tight junctions and tight junction-associated claudins. Finally, the signaling events that regulate paracellular permeability are discussed.
MeSH term(s)	Animals ; Capillary Permeability ; Cell Adhesion ; Cell Adhesion Molecules/chemistry ; Cell Adhesion Molecules/metabolism ; Cell Communication ; Claudin-1 ; Endothelium, Vascular/chemistry ; Endothelium, Vascular/enzymology ; Humans ; Junctional Adhesion Molecules ; Membrane Proteins/chemistry ; Membrane Proteins/metabolism ; Models, Biological ; Occludin ; Protein Conformation ; Protein Kinase C/metabolism ; Protein-Tyrosine Kinases/metabolism ; Signal Transduction ; Tight Junctions/chemistry ; Tight Junctions/enzymology
Chemical Substances	CLDN1 protein, human ; Cell Adhesion Molecules ; Claudin-1 ; Junctional Adhesion Molecules ; Membrane Proteins ; OCLN protein, human ; Occludin ; Protein-Tyrosine Kinases (EC 2.7.10.1) ; Protein Kinase C (EC 2.7.11.13)
Language	English
Publishing date	2006-01
Publishing country	Germany
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Review
ZDB-ID	518294-3
ISSN	0340-6245
ISSN	0340-6245
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Zs.MO 433: Show issues

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