A computational analysis of protein-protein interaction networks in neurodegenerative diseases

<p>Abstract</p> <p>Background</p> <p>Recent developments have meant that network theory is making an important contribution to the topological study of biological networks, such as protein-protein interaction (PPI) networks. The identification of differentially expressed genes in DNA array experiments is a source of information regarding the molecular pathways involved in disease. Thus, considering PPI analysis and gene expression studies together may provide a better understanding of multifactorial neurodegenerative diseases such as Multiple Sclerosis (MS) and Alzheimer disease (AD). The aim of this study was to assess whether the parameters of degree and betweenness, two fundamental measures in network theory, are properties that differentiate between implicated (seed-proteins) and non-implicated nodes (neighbors) in MS and AD. We used experimentally validated PPI information to obtain the neighbors for each seed group and we studied these parameters in four networks: MS-blood network; MS-brain network; AD-blood network; and AD-brain network.</p> <p>Results</p> <p>Specific features of seed-proteins were revealed, whereby they displayed a lower average degree in both diseases and tissues, and a higher betweenness in AD-brain and MS-blood networks. Additionally, the heterogeneity of the processes involved indicate that these findings are not pathway specific but rather that they are spread over different pathways.</p> <p>Conclusion</p> <p>Our findings show differential centrality properties of proteins whose gene expression is impaired in neurodegenerative diseases.</p

Past, present, and future efforts to enhance the efficacy of cord blood hematopoietic cell transplantation

Cord blood (CB) has been used as a viable source of hematopoietic stem cells (HSCs) and hematopoietic progenitor cells (HPCs) in over 35,000 clinical hematopoietic cell transplantation (HCT) efforts to treat the same variety of malignant and non-malignant disorders treated by bone marrow (BM) and mobilized peripheral blood (mPB) using HLA-matched or partially HLA-disparate related or unrelated donor cells for adult and children recipients. This review documents the beginning of this clinical effort that started in the 1980's, the pros and cons of CB HCT compared to BM and mPB HCT, and recent experimental and clinical efforts to enhance the efficacy of CB HCT. These efforts include means for increasing HSC numbers in single CB collections, expanding functional HSCs ex vivo, and improving CB HSC homing and engraftment, all with the goal of clinical translation. Concluding remarks highlight the need for phase I/II clinical trials to test the experimental procedures that are described, either alone or in combination

Modeling the effector - regulatory T cell cross-regulation reveals the intrinsic character of relapses in multiple sclerosis

Background: The relapsing-remitting dynamics is a hallmark of autoimmune diseases such as Multiple Sclerosis (MS). Although current understanding of both cellular and molecular mechanisms involved in the pathogenesis of autoimmune diseases is significant, how their activity generates this prototypical dynamics is not understood yet. In order to gain insight about the mechanisms that drive these relapsing-remitting dynamics, we developed a computational model using such biological knowledge. We hypothesized that the relapsing dynamics in autoimmunity can arise through the failure in the mechanisms controlling cross-regulation between regulatory and effector T cells with the interplay of stochastic events (e.g. failure in central tolerance, activation by pathogens) that are able to trigger the immune system. Results: The model represents five concepts: central tolerance (T-cell generation by the thymus), T-cell activation, T-cell memory, cross-regulation (negative feedback) between regulatory and effector T-cells and tissue damage. We enriched the model with reversible and irreversible tissue damage, which aims to provide a comprehensible link between autoimmune activity and clinical relapses and active lesions in the magnetic resonances studies in patients with Multiple Sclerosis. Our analysis shows that the weakness in this negative feedback between effector and regulatory T-cells, allows the immune system to generate the characteristic relapsing-remitting dynamics of autoimmune diseases, without the need of additional environmental triggers. The simulations show that the timing at which relapses appear is highly unpredictable. We also introduced targeted perturbations into the model that mimicked immunotherapies that modulate effector and regulatory populations. The effects of such therapies happened to be highly dependent on the timing and/or dose, and on the underlying dynamic of the immune system. Conclusion: The relapsing dynamic in MS derives from the emergent properties of the immune system operating in a pathological state, a fact that has implications for predicting disease course and developing new therapies for MS.This work was supported by the European Commission (NEST-Pathfinder program: "ComplexDis" grant, contract number: 043241 and ITNMC program: "UEPHA*MS" grant, contract number: 212877) and the Spanish Ministry of Health (PI060117 and RD07/0060/0000-01) to PV and JGO. NV is a fellow of the Programa de Formación de Investigadores del Departamento de Educación, Universidades e Investigación, Gobierno Vasco (BFI05.9 AE). JB acknowledges the support of the MEC through the grant: FIS2005-06912-C02, DINCARD. JG is a fellow of Government of Navarra. Dr Bagnato's contribution to this work was supported by the Intramural Research Program of the NINDS-NI

Modeling the effector - regulatory T cell cross-regulation reveals the intrinsic character of relapses in multiple sclerosis

Background: The relapsing-remitting dynamics is a hallmark of autoimmune diseases such as Multiple Sclerosis (MS). Although current understanding of both cellular and molecular mechanisms involved in the pathogenesis of autoimmune diseases is significant, how their activity generates this prototypical dynamics is not understood yet. In order to gain insight about the mechanisms that drive these relapsing-remitting dynamics, we developed a computational model using such biological knowledge. We hypothesized that the relapsing dynamics in autoimmunity can arise through the failure in the mechanisms controlling cross-regulation between regulatory and effector T cells with the interplay of stochastic events (e.g. failure in central tolerance, activation by pathogens) that are able to trigger the immune system. Results: The model represents five concepts: central tolerance (T-cell generation by the thymus), T-cell activation, T-cell memory, cross-regulation (negative feedback) between regulatory and effector T-cells and tissue damage. We enriched the model with reversible and irreversible tissue damage, which aims to provide a comprehensible link between autoimmune activity and clinical relapses and active lesions in the magnetic resonances studies in patients with Multiple Sclerosis. Our analysis shows that the weakness in this negative feedback between effector and regulatory T-cells, allows the immune system to generate the characteristic relapsing-remitting dynamics of autoimmune diseases, without the need of additional environmental triggers. The simulations show that the timing at which relapses appear is highly unpredictable. We also introduced targeted perturbations into the model that mimicked immunotherapies that modulate effector and regulatory populations. The effects of such therapies happened to be highly dependent on the timing and/or dose, and on the underlying dynamic of the immune system. Conclusion: The relapsing dynamic in MS derives from the emergent properties of the immune system operating in a pathological state, a fact that has implications for predicting disease course and developing new therapies for MS.This work was supported by the European Commission (NEST-Pathfinder program: "ComplexDis" grant, contract number: 043241 and ITNMC program: "UEPHA*MS" grant, contract number: 212877) and the Spanish Ministry of Health (PI060117 and RD07/0060/0000-01) to PV and JGO. NV is a fellow of the Programa de Formación de Investigadores del Departamento de Educación, Universidades e Investigación, Gobierno Vasco (BFI05.9 AE). JB acknowledges the support of the MEC through the grant: FIS2005-06912-C02, DINCARD. JG is a fellow of Government of Navarra. Dr Bagnato's contribution to this work was supported by the Intramural Research Program of the NINDS-NI