Individualized identification of disturbed pathways in sickle cell disease

Background: Sickle cell disease (SCD) is one of the most common genetic blood disorders. Identifying pathway aberrance in an individual SCD contributes to the understanding of disease pathogenesis and the promotion of personalized therapy. Here we proposed an individualized pathway aberrance method to identify the disturbed pathways in SCD. Methods: Based on the transcriptome data and pathway data, an individualized pathway aberrance method was implemented to identify the altered pathways in SCD, which contained four steps: data preprocessing, gene-level statistics, pathway-level statistics, and significant analysis. The changed percentage of altered pathways in SCD individuals was calculated, and a differentially expressed gene (DEG)-based pathway enrichment analysis was performed to validate the results. Results: We identified 618 disturbed pathways between normal and SCD conditions. Among them, 6 pathways were altered in > 80% SCD individuals. Meanwhile, forty-six DEGs were identified between normal and SCD conditions, and were enriched in heme biosynthesis. Relative to DEG-based pathway analysis, the new method presented richer results and more extensive application. Conclusion: This study predicted several disturbed pathways via detecting pathway aberrance on a personalized basis. The results might provide new sights into the pathogenesis of SCD and facilitate the application of custom treatment for SCD.

Location
Deutsche Nationalbibliothek Frankfurt am Main
Extent
Online-Ressource
Language
Englisch

Bibliographic citation
Individualized identification of disturbed pathways in sickle cell disease ; volume:12 ; number:1 ; year:2017 ; pages:418-424 ; extent:7
Open life sciences ; 12, Heft 1 (2017), 418-424 (gesamt 7)

Creator
Lu, Chun-Juan
Wang, Yan
Huang, Ya-Li
Li, Xin-Hua

DOI
10.1515/biol-2017-0049
URN
urn:nbn:de:101:1-2409201653017.339827745154
Rights
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Last update
15.08.2025, 7:29 AM CEST

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Associated

  • Lu, Chun-Juan
  • Wang, Yan
  • Huang, Ya-Li
  • Li, Xin-Hua

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