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PreprintCited by 5Bioinformatics and Genomic NetworksSchizophrenia research and treatmentGenetic Associations and Epidemiology

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Cell type-specific proteogenomic signal diffusion for integrating multi-omics data predicts novel schizophrenia risk genes

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Torshizi, Abolfazl Doostparast, Duan, Jubao, Wang, Kai·2020·Patterns
DOI 10.1101/2020.05.28.121517PMC PMC7518509

Preprint — published as 10.1016/j.patter.2020.100091 · Paper page

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Abstract

Accumulation of diverse types of omics data on schizophrenia (SCZ) requires a systems approach to jointly modeling the interplay between genome, transcriptome and proteome. Proteome dynamics, as the definitive cellular machinery in human body, has been lagging behind the research on genome/transcriptome in the context of SCZ, both at tissue and single-cell resolution. We introduce a Markov Affinity-based Proteogenomic Signal Diffusion (MAPSD) method to model intra-cellular protein trafficking paradigms and tissue-wise single-cell protein abundances. MAPSD integrates multi-omics data to amplify the signals at SCZ risk loci with small effect sizes, and reveal convergent disease-associated gene modules in the brain interactome as well as more than 130 tissue/cell-type combinations. We predicted a set of high-confidence SCZ risk genes, the majority of which are not directly connected to SCZ susceptibility risk genes. We characterized the subcellular localization of proteins encoded by candidate SCZ risk genes in various brain regions, and illustrated that most are enriched in neuronal and Purkinje cells in cerebral cortex. We demonstrated how the identified gene set may be involved in different developmental stages of the brain, how they alter SCZ-related biological pathways, and how they can be effectively leveraged for drug repurposing. MAPSD can be applied to other polygenic diseases, yet our case study on SCZ signifies how tissue-adjusted protein-protein interaction networks can assist in generating deeper insights into the orchestration of polygenic diseases.

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Metadata

Authors
Torshizi, A. D., Duan, J., & Wang, K.
Affiliations
  • Children's Hospital of Philadelphia (US)
  • Endeavor Health (US)
Corresponding author
Wang, Kai
ORCID
Venue
Patterns
Publisher
openRxiv
Published
2020-05-30
Volume
1
Issue
6
Pages
100091-100091
ISSN
2666-3899 (ISSN-L)
DOI
10.1101/2020.05.28.121517
PMC
PMC7518509
OpenAlex
W3082332970
Cited by
5
References
1
Citations by year
2025: 1 · 2024: 1 · 2022: 1 · 2021: 1 · 2020: 1
FWCI
0.24
Type
journal article
Language
en
Open access
Licence
Locations
  • Patterns (publishedVersion, cc-by)
  • SSRN Electronic Journal (publishedVersion)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • Children's Hospital of Philadelphia
  • National Institutes of Health
  • National Institute on Aging (R01AG063175)
  • National Institute of Mental Health (R01MH116281, R01MH108728, R01MH106575)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
  • Health Sciences › Medicine › Psychiatry and Mental health › Schizophrenia research and treatment
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
Keywords
schizophrenia, risk genes, proteogenomics, multi-omics integration, protein trafficking, subcellular protein localization, single-cell proteomics, gene modules, brain development, drug repurposing, polygenic disease

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