124
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      scite_
       
      • Record: found
      • Abstract: found
      • Conference Proceedings: found
      Is Open Access

      The systemic complexity of a monogenic disease: how interactomes help to understand molecular disease networks

      Published
      conference-abstract
      1 , 1 , 1 ,   1 ,
      RExPO24 Conference
      REPO4EU
      RExPO24
      3-5 July 2024
      Multi-omics, Spinal Muscular Atrophy, Systems disease, Network-biology
      Bookmark

            Abstract

            Models of monogenic diseases are paradigms for the causal analyses of molecular alterations. Spinal Muscular Atrophy (SMA) is a monogenic disease caused by mutations or deletions of the Survival of Motoneuron 1 ( SMN1) gene (Lefebvre et al., 1995). Current available drugs for SMA increase SMN protein levels resulting in a prolonged survival of patients. However, individual pathomechanisms remain altered (Butterfield, 2021; Hensel et al., 2020). Known pathomechanisms include splicing, cytoskeletal regulation or translation (Hensel & Claus, 2018; Lauria et al., 2020; Pellizzoni et al., 1998). Single mechanisms have been well studied but represent specific aspects of SMA only. The connectivity of these single pathways within a network remains largely unknown. We aimed to analyze the systemic character of SMA by combining proteome, phosphoproteome and translatome data from two SMA mouse models. This network biology-based analyses revealed subnetworks and proteins overlapping between models, but also protein communities defining separate entities. Different disease severities known in patients, here represented by the different animal models, hold common upstream regulators and kinases. Such regulators can affect several changes simultaneously, an important characteristic for the development of one drug for all types of SMA. In addition, the identified regulators are known genes involved in neurodegenerative diseases. Additional inclusion of SMN-interactome data with the proteome network elucidated disease hubs and bottlenecks between the disease-causing protein and altered proteins, which created a comprehensive representation of SMA. We could translate the identification of a common dysregulation in purine metabolism between models to treatment naïve patient samples which showed an increase in associated urine metabolites before and after neuromuscular symptom onset. We highlight that SMA is a system disease only representable by different experimental models and omics levels. This study combines different molecular levels and methods to describe SMA on a systems level and enables the interpretation of single protein changes in the disease context.

            Content

            Author and article information

            Conference
            RExPO24 Conference
            REPO4EU
            2 May 2024
            Affiliations
            [1 ] SMATHERIA gGmbH – Non-Profit Biomedical Research Institute;
            Author notes
            Author information
            https://orcid.org/0000-0002-2358-0031
            https://orcid.org/0009-0000-7947-509X
            https://orcid.org/0009-0009-1772-4316
            https://orcid.org/0000-0003-3824-9445
            Article
            10.58647/REXPO.24000045.v1
            b94e9f2c-2cc9-4290-9436-1b42d15c4c8f

            This work has been published open access under Creative Commons Attribution License CC BY 4.0 , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com .

            RExPO24
            3
            Munich, Germany
            3-5 July 2024
            History
            : 2 May 2024
            Funding
            Funded by: funder-id , Deutsche Muskelstiftung;
            Categories

            The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.
            Molecular medicine,Life sciences
            Multi-omics, Spinal Muscular Atrophy, Systems disease, Network-biology

            Comments

            Comment on this article