Can Metabolomic Profiling Predict Parkinson’s Disease Progression?

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Fifteen baseline plasma elements correlated with change in UPDRS scores.

Metabolomic profiling of plasma strongly predicts Parkinson’s disease progression, according to a study published February 28 in Neurology. Metabolomic biomarkers may help researchers better understand Parkinson’s disease pathogenesis.

“Our findings offer novel biomarkers for studying Parkinson’s disease progression and, with them, several new directions for investigation of its pathogenesis,” said Peter A. LeWitt, MD, Professor of Neurology at Henry Ford Hospital and Wayne State University School of Medicine in Detroit. Diagnosing and measuring progression of Parkinson’s disease continues to present many challenges. How to identify biomarkers with high specificity and sensitivity also remains unclear. The latest methodologies of metabolomic analysis can measure a large fraction of low-molecular-weight compounds in biospecimens for characterizing the biochemical environment of the body.

Dr. LeWitt and colleagues sought to determine whether a Parkinson’s disease–specific biochemical signature might be found in plasma and CSF. They used ultra-high performance liquid chromatography linked to gas chromatography and tandem mass spectrometry to measure concentrations of small-molecule constituents of plasma and CSF of 49 unmedicated patients with mild parkinsonism. Participants were between ages 38 and 78, and the mean age was 62.9. Investigators collected specimens twice: at baseline and up to 24 months later. During the study, patients’ mean Unified Parkinson’s Disease Rating Scale (UPDRS) parts II and III scores increased by 47%.

The investigators performed unbiased univariate and multivariate analyses of the measured compounds to determine associations with Parkinson’s disease progression. The analyses included fitting data in multiple linear regressions with variable selection using the Least Absolute Shrinkage and Selection Operator. The researchers detected 575 plasma biochemicals and 283 CSF biochemicals. Of those biochemicals, 15 baseline plasma elements had high positive correlation with baseline-to-final change in UPDRS Part II and Part III scores. Three of the compounds had xanthine structures, and four of the compounds were medium- or long-chain fatty acids. CSF concentrations of homovanillate, the major metabolite of dopamine, varied little between baseline and final collections and showed minimal correlation with worsening UPDRS scores.

—Erica Tricarico

Suggested Reading

LeWitt PA, Li J, Lu M, et al. Metabolomic biomarkers as strong correlates of Parkinson disease progression. Neurology. 2017;88(9):862-869.

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Neurology Reviews - 25(5)

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Parkinson's Disease

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Fifteen baseline plasma elements correlated with change in UPDRS scores.

Metabolomic profiling of plasma strongly predicts Parkinson’s disease progression, according to a study published February 28 in Neurology. Metabolomic biomarkers may help researchers better understand Parkinson’s disease pathogenesis.

“Our findings offer novel biomarkers for studying Parkinson’s disease progression and, with them, several new directions for investigation of its pathogenesis,” said Peter A. LeWitt, MD, Professor of Neurology at Henry Ford Hospital and Wayne State University School of Medicine in Detroit. Diagnosing and measuring progression of Parkinson’s disease continues to present many challenges. How to identify biomarkers with high specificity and sensitivity also remains unclear. The latest methodologies of metabolomic analysis can measure a large fraction of low-molecular-weight compounds in biospecimens for characterizing the biochemical environment of the body.

Dr. LeWitt and colleagues sought to determine whether a Parkinson’s disease–specific biochemical signature might be found in plasma and CSF. They used ultra-high performance liquid chromatography linked to gas chromatography and tandem mass spectrometry to measure concentrations of small-molecule constituents of plasma and CSF of 49 unmedicated patients with mild parkinsonism. Participants were between ages 38 and 78, and the mean age was 62.9. Investigators collected specimens twice: at baseline and up to 24 months later. During the study, patients’ mean Unified Parkinson’s Disease Rating Scale (UPDRS) parts II and III scores increased by 47%.

The investigators performed unbiased univariate and multivariate analyses of the measured compounds to determine associations with Parkinson’s disease progression. The analyses included fitting data in multiple linear regressions with variable selection using the Least Absolute Shrinkage and Selection Operator. The researchers detected 575 plasma biochemicals and 283 CSF biochemicals. Of those biochemicals, 15 baseline plasma elements had high positive correlation with baseline-to-final change in UPDRS Part II and Part III scores. Three of the compounds had xanthine structures, and four of the compounds were medium- or long-chain fatty acids. CSF concentrations of homovanillate, the major metabolite of dopamine, varied little between baseline and final collections and showed minimal correlation with worsening UPDRS scores.

—Erica Tricarico

Suggested Reading

LeWitt PA, Li J, Lu M, et al. Metabolomic biomarkers as strong correlates of Parkinson disease progression. Neurology. 2017;88(9):862-869.

Metabolomic profiling of plasma strongly predicts Parkinson’s disease progression, according to a study published February 28 in Neurology. Metabolomic biomarkers may help researchers better understand Parkinson’s disease pathogenesis.

“Our findings offer novel biomarkers for studying Parkinson’s disease progression and, with them, several new directions for investigation of its pathogenesis,” said Peter A. LeWitt, MD, Professor of Neurology at Henry Ford Hospital and Wayne State University School of Medicine in Detroit. Diagnosing and measuring progression of Parkinson’s disease continues to present many challenges. How to identify biomarkers with high specificity and sensitivity also remains unclear. The latest methodologies of metabolomic analysis can measure a large fraction of low-molecular-weight compounds in biospecimens for characterizing the biochemical environment of the body.

Dr. LeWitt and colleagues sought to determine whether a Parkinson’s disease–specific biochemical signature might be found in plasma and CSF. They used ultra-high performance liquid chromatography linked to gas chromatography and tandem mass spectrometry to measure concentrations of small-molecule constituents of plasma and CSF of 49 unmedicated patients with mild parkinsonism. Participants were between ages 38 and 78, and the mean age was 62.9. Investigators collected specimens twice: at baseline and up to 24 months later. During the study, patients’ mean Unified Parkinson’s Disease Rating Scale (UPDRS) parts II and III scores increased by 47%.

The investigators performed unbiased univariate and multivariate analyses of the measured compounds to determine associations with Parkinson’s disease progression. The analyses included fitting data in multiple linear regressions with variable selection using the Least Absolute Shrinkage and Selection Operator. The researchers detected 575 plasma biochemicals and 283 CSF biochemicals. Of those biochemicals, 15 baseline plasma elements had high positive correlation with baseline-to-final change in UPDRS Part II and Part III scores. Three of the compounds had xanthine structures, and four of the compounds were medium- or long-chain fatty acids. CSF concentrations of homovanillate, the major metabolite of dopamine, varied little between baseline and final collections and showed minimal correlation with worsening UPDRS scores.

—Erica Tricarico

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