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AS654 - Blood Metabolomic Profile of Glioma Risk: A Collaborative Multi-Cohort Project

Investigator Names and Contact Information

Demetrius Albanes (daa@nih.gov)

Introduction/Intent

 Although glioma is a relatively rare malignancy (20,000 cases in the U.S. in 2018), it is among the most lethal. With the exception of radiation exposure, family history, tallness and possibly allergies, its etiology remains unknown. Recent advances in metabolomics technologies enable identification of a broad array of low molecular weight compounds (i.e., the metabolome) in blood and other tissues potentially associated with cancer. Given the current paucity of etiologic leads for glioma, broad, untargeted biochemical approaches for examining this lethal malignancy are warranted. Prior clinical studies demonstrated unique patient tumor metabolomic signatures (e.g., cellular energetics and phospholipid metabolism). Transitioning from these clinical profiles, we conducted the first prospective nested case-control analysis of serum metabolites and glioma risk in the ATBC Study cohort with 22 years of follow-up, identifying 43 metabolites associated with risk, including 2-oxoarginine, argininate, cysteine, alpha-ketoglutarate, chenodeoxycholate and xanthine caffeine metabolites related to coffee consumption. These promising leads based on 64 cases require re-examination in a larger, definitive study. The proposed multi-cohort project within the NCI Consortium of Metabolomics Studies (COMETS) will provide such a rigorous investigation with the primary aim of identifying blood metabolites and pre-defined metabolite chemical classes/subclasses prospectively associated with glioma risk. The analysis will include 1,085 nested case-control sets from 10 cohorts, including 250 sets from the Women's Health Initiative (WHI). Controls will be incidence-density sampled and matched to cases 1:1 based on age, sex, race, and blood collection date. Conditional logistic regression-based meta-analysis of aggregate main effects will be used to examine the association between ~1100 metabolites identified by the Metabolon ultra-high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS) HD4 global platform and glioma risk.  Aliquoted study samples (150 ul baseline serum) will be shipped to NCI for batching and inclusion of blinded QC samples.  Secondary analyses will examine differences related to latent period, age, sex, race/ethnicity, stage/grade, and other clinical factors.

Materials/Methods

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Results/Findings

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References

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