Translatable pathways classification (TransPath-C) for inferring processes germane to human biology from animal studies data: example application in neurobiology
<jats:title>Abstract</jats:title> <jats:p>How to translate insights gained from studies in one organismal species for what is most likely to be germane in another species, such as from mice to humans, is a ubiquitous challenge in basic biology as well as biomedicine...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Oxford University Press (OUP)
2023
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| Online Access: | https://hdl.handle.net/1721.1/147870 |
| _version_ | 1826194387744325632 |
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| author | Carroll, Molly J Garcia-Reyero, Natàlia Perkins, Edward J Lauffenburger, Douglas A |
| author2 | Massachusetts Institute of Technology. Department of Biological Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Biological Engineering Carroll, Molly J Garcia-Reyero, Natàlia Perkins, Edward J Lauffenburger, Douglas A |
| author_sort | Carroll, Molly J |
| collection | MIT |
| description | <jats:title>Abstract</jats:title>
<jats:p>How to translate insights gained from studies in one organismal species for what is most likely to be germane in another species, such as from mice to humans, is a ubiquitous challenge in basic biology as well as biomedicine. This is an especially difficult problem when there are few molecular features that are obviously important in both species for a given phenotype of interest. Neuropathologies are a prominent realm of this complication. Schizophrenia is complex psychiatric disorder that affects 1% of the population. Many genetic factors have been proposed to drive the development of schizophrenia, and the 22q11 microdeletion (MD) syndrome has been shown to dramatically increase this risk. Due to heterogeneity of presentation of symptoms, diagnosis and formulation of treatment options for patients can often be delayed, and there is an urgent need for novel therapeutics directed toward the treatment of schizophrenia. Here, we present a novel computational approach, Translational Pathways Classification (TransPath-C), that can be used to identify shared pathway dysregulation between mouse models and human schizophrenia cohorts. This method uses variation of pathway activation in the mouse model to predict both mouse and human disease phenotype. Analysis of shared dysregulated pathways called out by both the mouse and human classifiers of TransPath-C can identify pathways that can be targeted in both preclinical and human cohorts of schizophrenia. In application to the 22q11 MD mouse model, our findings suggest that PAR1 pathway activation found upregulated in this mouse phenotype is germane for the corresponding human schizophrenia cohort such that inhibition of PAR1 may offer a novel therapeutic target.</jats:p> |
| first_indexed | 2024-09-23T09:55:20Z |
| format | Article |
| id | mit-1721.1/147870 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T09:55:20Z |
| publishDate | 2023 |
| publisher | Oxford University Press (OUP) |
| record_format | dspace |
| spelling | mit-1721.1/1478702023-02-04T03:39:27Z Translatable pathways classification (TransPath-C) for inferring processes germane to human biology from animal studies data: example application in neurobiology Carroll, Molly J Garcia-Reyero, Natàlia Perkins, Edward J Lauffenburger, Douglas A Massachusetts Institute of Technology. Department of Biological Engineering <jats:title>Abstract</jats:title> <jats:p>How to translate insights gained from studies in one organismal species for what is most likely to be germane in another species, such as from mice to humans, is a ubiquitous challenge in basic biology as well as biomedicine. This is an especially difficult problem when there are few molecular features that are obviously important in both species for a given phenotype of interest. Neuropathologies are a prominent realm of this complication. Schizophrenia is complex psychiatric disorder that affects 1% of the population. Many genetic factors have been proposed to drive the development of schizophrenia, and the 22q11 microdeletion (MD) syndrome has been shown to dramatically increase this risk. Due to heterogeneity of presentation of symptoms, diagnosis and formulation of treatment options for patients can often be delayed, and there is an urgent need for novel therapeutics directed toward the treatment of schizophrenia. Here, we present a novel computational approach, Translational Pathways Classification (TransPath-C), that can be used to identify shared pathway dysregulation between mouse models and human schizophrenia cohorts. This method uses variation of pathway activation in the mouse model to predict both mouse and human disease phenotype. Analysis of shared dysregulated pathways called out by both the mouse and human classifiers of TransPath-C can identify pathways that can be targeted in both preclinical and human cohorts of schizophrenia. In application to the 22q11 MD mouse model, our findings suggest that PAR1 pathway activation found upregulated in this mouse phenotype is germane for the corresponding human schizophrenia cohort such that inhibition of PAR1 may offer a novel therapeutic target.</jats:p> 2023-02-03T18:35:00Z 2023-02-03T18:35:00Z 2021 2023-02-03T18:23:32Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/147870 Carroll, Molly J, Garcia-Reyero, Natàlia, Perkins, Edward J and Lauffenburger, Douglas A. 2021. "Translatable pathways classification (TransPath-C) for inferring processes germane to human biology from animal studies data: example application in neurobiology." Integrative Biology, 13 (10). en 10.1093/INTBIO/ZYAB016 Integrative Biology Creative Commons Attribution NonCommercial License 4.0 https://creativecommons.org/licenses/by-nc/4.0/ application/pdf Oxford University Press (OUP) Oxford University Press |
| spellingShingle | Carroll, Molly J Garcia-Reyero, Natàlia Perkins, Edward J Lauffenburger, Douglas A Translatable pathways classification (TransPath-C) for inferring processes germane to human biology from animal studies data: example application in neurobiology |
| title | Translatable pathways classification (TransPath-C) for inferring processes germane to human biology from animal studies data: example application in neurobiology |
| title_full | Translatable pathways classification (TransPath-C) for inferring processes germane to human biology from animal studies data: example application in neurobiology |
| title_fullStr | Translatable pathways classification (TransPath-C) for inferring processes germane to human biology from animal studies data: example application in neurobiology |
| title_full_unstemmed | Translatable pathways classification (TransPath-C) for inferring processes germane to human biology from animal studies data: example application in neurobiology |
| title_short | Translatable pathways classification (TransPath-C) for inferring processes germane to human biology from animal studies data: example application in neurobiology |
| title_sort | translatable pathways classification transpath c for inferring processes germane to human biology from animal studies data example application in neurobiology |
| url | https://hdl.handle.net/1721.1/147870 |
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