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  1. 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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  2. 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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  3. 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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  4. Article ; Online: The polarity sub-network in the yeast network of protein-protein interactions

    Luca Paris / Gianfranco Bazzoni

    Network Biology, Vol 1, Iss 3-4, Pp 149-

    2011  Volume 158

    Abstract: Rare, but highly connected, hub proteins subdivide hierarchically global networks of interacting proteins into modular clusters. Most biological research, however, focuses on functionally defined sub-networks. Thus, it is important to know whether the ... ...

    Abstract Rare, but highly connected, hub proteins subdivide hierarchically global networks of interacting proteins into modular clusters. Most biological research, however, focuses on functionally defined sub-networks. Thus, it is important to know whether the sub-networks retain the same topology of the global networks, from which they derive. To address this issue, we have analyzed the protein-protein interaction sub-network that participates in the polarized growth of the budding yeast Saccharomyces cerevisiae and that is derived from the global network of this model organism. We have observed that, in contrast to global networks, the distribution of connectivity k (i.e., the number of interactions per protein) does not follow a power law, but decays exponentially, which reflects the local absence of hub proteins. Nonetheless, far from being randomly organized, the polarity sub-network can be subdivided into functional modules. In addition, most non-hub connector proteins, besides ensuring communications among modules, are linked mutually and contribute to the formation of the polarisome, a structure that coordinates actin assembly with polarized growth. These findings imply that identifying critical proteins within sub-networks (e.g., for the aim of targeted therapy) requires searching not only for hubs but also for key non-hub connectors, which might remain otherwise unnoticed due to their relatively low connectivity.
    Keywords protein interactions ; protein interaction networks ; connectivity ; topological role ; budding yeast ; cell polarity ; Biology (General) ; QH301-705.5
    Subject code 612
    Language English
    Publishing date 2011-12-01T00:00:00Z
    Publisher International Academy of Ecology and Environmental Sciences
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: Amyotrophic lateral sclerosis multiprotein biomarkers in peripheral blood mononuclear cells.

    Giovanni Nardo / Silvia Pozzi / Mauro Pignataro / Eliana Lauranzano / Giorgia Spano / Silvia Garbelli / Stefania Mantovani / Kalliopi Marinou / Laura Papetti / Marta Monteforte / Valter Torri / Luca Paris / Gianfranco Bazzoni / Christian Lunetta / Massimo Corbo / Gabriele Mora / Caterina Bendotti / Valentina Bonetto

    PLoS ONE, Vol 6, Iss 10, p e

    2011  Volume 25545

    Abstract: Amyotrophic lateral sclerosis (ALS) is a fatal progressive motor neuron disease, for which there are still no diagnostic/prognostic test and therapy. Specific molecular biomarkers are urgently needed to facilitate clinical studies and speed up the ... ...

    Abstract Amyotrophic lateral sclerosis (ALS) is a fatal progressive motor neuron disease, for which there are still no diagnostic/prognostic test and therapy. Specific molecular biomarkers are urgently needed to facilitate clinical studies and speed up the development of effective treatments.We used a two-dimensional difference in gel electrophoresis approach to identify in easily accessible clinical samples, peripheral blood mononuclear cells (PBMC), a panel of protein biomarkers that are closely associated with ALS. Validations and a longitudinal study were performed by immunoassays on a selected number of proteins. The same proteins were also measured in PBMC and spinal cord of a G93A SOD1 transgenic rat model. We identified combinations of protein biomarkers that can distinguish, with high discriminatory power, ALS patients from healthy controls (98%), and from patients with neurological disorders that may resemble ALS (91%), between two levels of disease severity (90%), and a number of translational biomarkers, that link responses between human and animal model. We demonstrated that TDP-43, cyclophilin A and ERp57 associate with disease progression in a longitudinal study. Moreover, the protein profile changes detected in peripheral blood mononuclear cells of ALS patients are suggestive of possible intracellular pathogenic mechanisms such as endoplasmic reticulum stress, nitrative stress, disturbances in redox regulation and RNA processing.Our results indicate that PBMC multiprotein biomarkers could contribute to determine amyotrophic lateral sclerosis diagnosis, differential diagnosis, disease severity and progression, and may help to elucidate pathogenic mechanisms.
    Keywords Medicine ; R ; Science ; Q
    Subject code 610
    Language English
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Article: The polarity sub-network in the yeast network of protein-protein interactions

    Luca Paris, Gianfranco Bazzoni

    Network Biology

    Language English
    Document type Article
    ISSN 2220-8879
    Database AGRIS - International Information System for the Agricultural Sciences and Technology

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