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On Demand: Comprehensive Blood Metabolomics Profiling of Parkinson’s Disease

Parkinson’s disease is characterized by a multitude of complexities, ranging from its heterogeneous clinical presentation to the intricate interplay of genetic, environmental, and neurobiological factors underlying its pathogenesis. While there are various therapies available to manage symptoms and improve the quality of life in Parkinson’s disease, the development of treatments capable of halting or reversing the underlying neurodegeneration remains an ongoing challenge.

Metabolomics research has emerged as a pivotal tool in unraveling the complexities of Parkinson’s disease (PD). By scrutinizing the intricate metabolic pathways within biological systems, metabolomics offers valuable insights into the biochemical alterations associated with PD onset and progression. This comprehensive approach enables researchers to identify potential biomarkers for early diagnosis, track disease progression, and evaluate treatment efficacy. Moreover, metabolomics facilitates a deeper understanding of the underlying mechanisms implicated in PD pathology, paving the way for the development of targeted therapeutic interventions. Through the integration of metabolomics data with other omics technologies and clinical findings, researchers can elucidate the intricate interplay between genetic predisposition, environmental factors, and metabolic dysregulation in PD pathogenesis. Ultimately, metabolomics research holds immense promise in revolutionizing our understanding of PD and advancing the development of personalized therapeutic strategies tailored to the unique metabolic profiles of individual patients.

You will learn:

  • How comprehensive blood metabolomics profiling was used in the study of Parkinson’s disease (PD) by comparing treated and untreated patients with healthy controls.
  • How bioinformatic analyses were used to uncover molecular mechanisms and significant metabolic alterations in PD.
  • Benefits of targeted and untargeted metabolomics approaches
  • The potential role of the enzyme hypoxanthine phosphoribosyltransferase 1 (HPRT1) as a key regulator of coordinated changes in xanthine metabolism.


Dr. Enrico Glaab, Ph.D.
We present the results of a comprehensive, cohort-wide blood metabolomics profiling of Parkinson's disease (PD) patients, identifying significant alterations in dopaminergic-treated and untreated de novo patients compared to healthy controls. The research combines statistical, bioinformatic pathway, and network analyses to elucidate mechanistic underpinnings of PD at the molecular level. Key findings include pronounced changes in individual metabolite levels and global pathway activities, with the enzyme hypoxanthine phosphoribosyltransferase 1 (HPRT1) identified as a potential key regulator of coordinated changes in xanthine metabolism. These changes are congruent with independent transcriptomic data, suggesting HPRT1 as a potential target for disease modification. Novel aspects of the approach are the network-based integration of metabolomics with transcriptomics data to detect coordinated changes and the specific consideration of de novo patients, in addition to patients receiving dopaminergic medications. The results may open new avenues for the discovery of diagnostic biomarker signatures and pharmaceutical targets in PD.
Dr. Patrick Arnott, Ph.D.
Routine Solutions for Untargeted and Targeted Metabolomics - Analyses, Bioinformatics, Interpretive Insights
Achieving fast, accurate, and reproducible metabolomic data can be a challenging task that requires investing in people, technology, and novel methods to derive functional insights. In this short session, we demonstrate how Metabolon’s metabolomics-as-a-service solution can be leveraged to improve metabolite-level insights today.
Dr. Enrico Glaab, Ph.D.
This section of the webinar includes: 
  • Examination of pronounced changes in xanthine metabolism in PD and their potential implications in the disease.
  • Integrated analysis of metabolomics and transcriptomics data to identify potential key enzyme regulators of the metabolite changes observed in PD.
Dr. Patrick Arnott, Ph.D.
Questions & Answers



Enrico Glaab, Ph.D.

Assistant Professor in Bioinformatics and Deputy Course Director at the University of Luxembourg,

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Enrico Glaab is Assistant Professor in Bioinformatics and Deputy Course Director at the University of Luxembourg, where he leads the Biomedical Data Science group at the Luxembourg Centre for Systems Biomedicine. His research focuses on the development and application of mechanistic network analyses and statistical learning approaches guided by prior knowledge to interpret changes in complex human disorders. Using structured data integration and interpretable machine learning approaches that use biological domain knowledge, he studies complementary biomedical data types, including omics, clinical, imaging, and digital biomarker data. The research applications mainly focus on the development of diagnostic and prognostic biomarker signatures, and the discovery and functional characterization of candidate molecular drug targets, primarily for the neurodegenerative disorders Parkinson’s disease (PD) and Alzheimer’s disease (AD). By combining statistical modeling, causal graph analysis and computational drug discovery methods, he aims to contribute to both basic biomedical research and translational applications for PD and AD.


Patrick Arnott, Ph.D.

Business Development Director at Metabolon

With a robust background in academia, Patrick brings a wealth of experience to his role at Metabolon. His tenure in academia was marked by numerous publications and successful grant acquisitions, attesting to his expertise and dedication. Patrick's forte lies in optimizing project costs without compromising quality, making him an invaluable asset in translating research endeavors into pioneering discoveries. His commitment to driving innovation makes him the ideal partner to elevate your projects to new heights with Metabolon.


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