Multivariate genomic and transcriptomic determinants of imaging-derived personalized therapeutic needs in Parkinson's disease

Sci Rep. 2022 Mar 31;12(1):5483. doi: 10.1038/s41598-022-09506-0.

Abstract

Due to the marked interpersonal neuropathologic and clinical heterogeneity of Parkinson's disease (PD), current interventions are not personalized and fail to benefit all patients. Furthermore, we continue to lack well-established methods and clinical tests to tailor interventions at the individual level in PD. Here, we identify the genetic determinants of individual-tailored treatment needs derived from longitudinal multimodal neuroimaging data in 294 PD patients (PPMI data). Advanced multivariate statistical analysis revealed that both genomic and blood transcriptomic data significantly explain (P < 0.01, FWE-corrected) the interindividual variability in therapeutic needs associated with dopaminergic, functional, and structural brain reorganization. We confirmed a high overlap between the identified highly predictive molecular pathways and determinants of levodopa clinical responsiveness, including well-known (Wnt signaling, angiogenesis, dopaminergic activity) and recently discovered (immune markers, gonadotropin-releasing hormone receptor) pathways/components. In addition, the observed strong correspondence between the identified genomic and baseline-transcriptomic determinants of treatment needs/response supports the genome's active role at the time of patient evaluation (i.e., beyond individual genetic predispositions at birth). This study paves the way for effectively combining genomic, transcriptomic and neuroimaging data for implementing successful individually tailored interventions in PD and extending our pathogenetic understanding of this multifactorial and heterogeneous disorder.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Brain / metabolism
  • Genomics
  • Humans
  • Infant, Newborn
  • Neuroimaging
  • Parkinson Disease* / diagnostic imaging
  • Parkinson Disease* / genetics
  • Parkinson Disease* / metabolism
  • Transcriptome