Open Access

A systems approach to prion disease

Daehee Hwang, Inyoul Y Lee, Hyuntae Yoo, Nils Gehlenborg, Ji‐Hoon Cho, Brianne Petritis, David Baxter, Rose Pitstick, Rebecca Young, Doug Spicer, Nathan D Price, John G Hohmann, Stephen J DeArmond, George A Carlson, Leroy E Hood

Author Affiliations

  1. Daehee Hwang1,2,,
  2. Inyoul Y Lee1,,
  3. Hyuntae Yoo1,,
  4. Nils Gehlenborg1,3,
  5. Ji‐Hoon Cho2,
  6. Brianne Petritis1,
  7. David Baxter1,
  8. Rose Pitstick4,
  9. Rebecca Young4,
  10. Doug Spicer4,
  11. Nathan D Price7,
  12. John G Hohmann5,
  13. Stephen J DeArmond6,
  14. George A Carlson*,4 and
  15. Leroy E Hood*,1
  1. 1 Institute for Systems Biology, Seattle, WA, USA
  2. 2 I‐Bio Program & Department of Chemical Engineering, POSTECH, Pohang, Republic of Korea
  3. 3 Microarray Team, European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge, UK
  4. 4 McLaughlin Research Institute, Great Falls, MT, USA
  5. 5 Allen Brain Institute, Seattle, WA, USA
  6. 6 Department of Pathology, University of California, San Francisco, CA, USA
  7. 7 Department of Chemical and Biomolecular Engineering & Institute for Genomic Biology, University of Illinois, Urbana, IL, USA
  1. *Corresponding authors. McLaughlin Research Institute, 1520 23rd Street South, Great Falls, MT 59405, USA. Tel.: +1 406 454 6044; Fax: +1 406 454 6019; E-mail: gac{at}po.mri.montana.eduInstitute for Systems Biology, 1441 North 34th Street, Seattle, WA 98103, USA. Tel.: +1 206 732 1201; Fax: +1 206 732 1254; E-mail: lhood{at}
  1. These authors contributed equally to this work

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Prions cause transmissible neurodegenerative diseases and replicate by conformational conversion of normal benign forms of prion protein (PrPC) to disease‐causing PrPSc isoforms. A systems approach to disease postulates that disease arises from perturbation of biological networks in the relevant organ. We tracked global gene expression in the brains of eight distinct mouse strain–prion strain combinations throughout the progression of the disease to capture the effects of prion strain, host genetics, and PrP concentration on disease incubation time. Subtractive analyses exploiting various aspects of prion biology and infection identified a core of 333 differentially expressed genes (DEGs) that appeared central to prion disease. DEGs were mapped into functional pathways and networks reflecting defined neuropathological events and PrPSc replication and accumulation, enabling the identification of novel modules and modules that may be involved in genetic effects on incubation time and in prion strain specificity. Our systems analysis provides a comprehensive basis for developing models for prion replication and disease, and suggests some possible therapeutic approaches.

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A systems approach to disease postulates that disease arises from the pathological perturbation (genetic and/or environmental) of one or more biological networks in the relevant organ and hence to understand a disease one must study the dynamical changes in relevant biological networks during disease progression. We applied the systems approach analyzing brain transcriptomes to the experimentally tractable neurodegenerative diseases caused by prion infection of mice. Prions are unique among transmissible, disease‐causing agents in that they replicate by conformational conversion of normal benign forms of prion protein (PrPC) to disease‐specific PrPSc isoforms. Neuropathological features common to all prion diseases in mammals, which include bovine spongiform encephalopathy (BSE) in cows, Creutzfeldt–Jakob disease (CJD) in humans, and scrapie in sheep, can be conveniently subdivided into four well‐defined pathological processes: prion replication and PrPSc accumulation (Prusiner, 2003), synaptic degeneration (Ishikura et al, 2005), microglia and astrocyte activation (Rezaie and Lantos, 2001; Perry et al, 2002), and neuronal cell death (Liberski et al, 2004). Data on pathological changes in prion disease have been derived in multiple laboratories that have viewed prion‐induced neurodegeneration from different perspectives and with different preconceptions. Our comprehensive and independent systems analysis of the brain transcriptomes in normal and prion‐infected mice provides gene expression correlates with pathological information and will aid in organizing the current abundance of data fragments into a coherent pathogenic model of prion disease.

We tracked global gene expression in the brains of eight distinct mouse strain–prion strain combinations at 8–10 time points throughout the incubation periods (60–350 days) to capture the effects of prion strain, host genetics, and PrP concentration on disease incubation time (Figure 1). Approximately 7400 genes were differentially expressed genes (DEGs) in one or more of the combinations. Subtractive analyses using three inbred mouse strains and two prion strains reduced the data dimensionality from 7400 to a core of 333 DEGs that reflected effects of prion strain and Prnp genotype that appeared central to prion disease. Of these, 178 had not previously been reported to change in prion‐infected mice. Gene expression results were combined with temporal patterns of PrPSc accumulation, pathology, gene ontology, protein interactions, and cell‐specific gene expression data to generate hypothetical dynamic protein networks that could be associated with known pathological events in disease progression; 231 DEGs were mapped into these networks. Figure 4 is a snapshot of one of these networks (PrPSc accumulation) in a single mouse strain–prion strain combination at 14 weeks after inoculation, before any clinical signs are apparent. This figure includes a histoblot to track regional deposition of proteinase K‐resistant PrPSc in the brain; histoblots were collected at each time point for each prion strain–mouse strain combination. The previously unidentified DEGs and those that could not be readily assigned to networks likely encode previously unidentified aspects of prion disease and subsets of these may reveal involvement of modules reflecting androgenic steroid, iron, or arachidonate/prostaglandin metabolism. All data and tools used in these studies are available online in a prion disease database (

Grouping mice in the five core prion strain–mouse strain combinations according to differences in incubation time revealed 55 DEGs, the expression of which was significantly enriched only in groups with short incubation times (B6‐RML, B6.I‐301V, and FVB‐RML). Similarly, grouping according to prion strain (RML or 301V) identified 39 DEGs enriched in RML prion‐inoculated mice. Interestingly, the emphasis on pathways such as cholesterol metabolism or glycosaminoglycan biosynthesis as central to prion disease may reflect the widespread use of RML and related prion isolates in short incubation time mice and in cell culture. The five core mouse strain–prion strain combinations emphasize incubation time differences reflecting interactions of PrPSc with PrPC encoded by alternative alleles of Prnp. PrPC concentration can also affect incubation time, and differential gene expression was explored in FVB.129‐Prnptm1Zrch/wt (0/+) mice that express half the normal amount of PrP and have a very long RML incubation time and in FVB‐Tg(PrP‐A)4053 (Tg4053) mice that overexpress PrP and have a very short incubation time. Among the 333 shared DEGs gleaned from five prion–wild‐type mouse strain combinations, 311 DEGs also were changed in Prnp (0/+) mice (summarized in Figure 1). In contrast, Tg4053 mice PrP showed significant changes in only 125 of the 333 DEGs in the shared set. Prominent shared DEGs in most of the key shared modules exhibited patterns in Tg4053 mice that were similar to the core groups, though generally with differentials of smaller magnitude and closer in time to clinical illness than all other combinations of prions and mice. Perplexingly, prion‐infected Tg4053 also had a unique set of highly significant DEGs that were not seen in any other mouse–prion combination.

We have demonstrated here the power of comprehensive, global systems approaches to diseases as complex as prion infection, even when the data sets are restricted to gene expression profiles, and involve whole brain. The efficacy of using several strain combinations, prion and genetic backgrounds as biological filters to identify the network signals that are important for various disease‐related processes is a striking lesson from our study. The new modules that have been connected to the disease, the strong alignment of the specific pathogenic processes with network changes, and the range of novel and sharpened hypotheses illustrate the power of this approach. We have confidence that with the addition of other data types, the attribution of network processes to brain regions, and the specific testing of hypotheses suggested here, that the systems medicine of prion disease (and other neurodegenerative diseases) will advance rapidly. This study also provided new insights into the power of systems approaches to formulate new strategies for blood diagnosis and treatment.

  • A systems approach was applied to neurodegenerative disease caused by prions, which are transmissible agents that replicate by conformational conversion of normal, benign forms of prion protein (PrPC) to disease‐specific PrPSc isoforms.

  • Analysis of brain transcriptomes and regional PrPSc accumulation in eight distinct mouse strain‐prion strain combinations at 8 to 10 time points across their incubation periods captured the effects of prion strain, host genetics, and PrP concentration on pathogenesis and disease incubation time.

  • We constructed hypothetical networks corresponding to four signal features of prion disease‐prion accumulation and replication, microglial and astrocytic activation, degeneration of axons and presynaptic boutons, and neural cell death.

  • A core of 333 genes showing shared dynamic differential expression appeared to encode the heart of prion disease; two‐thirds of these genes encoded known pathological events of prion disease and one third encoded novel, previously unknown, aspects of this disease.

Mol Syst Biol. 5: 252

  • Received November 27, 2008.
  • Accepted January 20, 2009.

This is an open‐access article distributed under the terms of the Creative Commons Attribution License, which permits distribution, and reproduction in any medium, provided the original author and source are credited. This license does not permit commercial exploitation without specific permission.

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