Plasma Levels of Food-Derived Metabolites as Biomarkers of Parkinson’s Disease

Parkinson's disease (PD) is a progressive neurodegenerative disorder shaped by genetic factors such as <i>LRRK2</i> and <i>GBA1</i> mutations, as well as dietary and metabolic influences. Food-derived plasma metabolites-including caffeine, paraxanthine, trigonelline, piperine, and sitosteryl hexoside-have emerged as promising, accessible biomarkers for early detection, progression monitoring, and therapeutic targeting, yet their longitudinal behavior and genetic interactions remain insufficiently characterized. Using the Parkinson's Progression Markers Initiative (PPMI) cohort (<i>n</i> = 455; 303 PD patients, 152 controls), we quantified plasma levels of these metabolites by quantitative LC-MS/MS with batch correction, examining sporadic PD and genetically defined subgroups (<i>LRRK2</i>-PD [PDL], <i>GBA1</i>-PD [PDG], dual-mutation PD [PDGL], and prodromal equivalents). Baseline one-way ANOVA showed significantly lower caffeine and paraxanthine in PDL (<i>p</i> = 0.0467, <i>p</i> = 0.0178) and PDG (<i>p</i> = 0.0408), reduced piperine in PDL (<i>p</i> = 0.0009), PDG (<i>p</i> = 0.0257), and prodromal <i>LRRK2</i> (<i>p</i> = 0.0168), and elevated sitosteryl hexoside in PDG (<i>p</i> = 0.0184). Longitudinal regression analyses revealed that in sporadic PD, caffeine negatively correlated with MDS-UPDRS parts I (β = -2, <i>p</i> = 0.0475) and III (β = -7.2, <i>p</i> = 0.007), trigonelline declined over time and was inversely associated with part III (β = -1.7, <i>p</i> = 0.0069), and sitosteryl hexoside negatively correlated with parts II (β = -68.3, <i>p</i> = 0.042) and III (β = -74.1, <i>p</i> = 0.0425). In PDL, sitosteryl hexoside inversely correlated with part I (β = -54.2, <i>p</i> = 0.0049), while in PDGL, paraxanthine showed negative associations with part II (β = -18.5, <i>p</i> = 0.00327). These findings demonstrate subgroup-specific alterations in food-derived metabolites and consistent inverse associations with PD severity, supporting their potential as non-invasive biomarkers, particularly in <i>LRRK2/GBA1</i> mutation carriers, and highlighting the need for longitudinal validation and dietary intervention trials to advance personalized PD management.

Authors

Institutions

Publication Details

Journal
International Journal of Molecular Sciences
Published
2025-12-19
DOI
https://doi.org/10.3390/ijms27010016
Primary Topic
Parkinson's Disease Mechanisms and Treatments
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Plasma Levels of Food-Derived Metabolites as Biomarkers of Parkinson’s Disease

Bin Xiao, Yun‐Cheng Wu, Yilong Zheng, Qiao Yang Sun et al.
International Journal of Molecular Sciences
Parkinson's Disease Mechanisms and Treatments
article

Plasma Levels of Food-Derived Metabolites as Biomarkers of Parkinson’s Disease

Bin Xiao, Yun‐Cheng Wu, Yilong Zheng, Qiao Yang Sun, Zhidong Zhou, Xiaoxue Dong, Edgar Yong Sheng Tan, Eng-King Tan
article en

Abstract

Parkinson's disease (PD) is a progressive neurodegenerative disorder shaped by genetic factors such as <i>LRRK2</i> and <i>GBA1</i> mutations, as well as dietary and metabolic influences. Food-derived plasma metabolites-including caffeine, paraxanthine, trigonelline, piperine, and sitosteryl hexoside-have emerged as promising, accessible biomarkers for early detection, progression monitoring, and therapeutic targeting, yet their longitudinal behavior and genetic interactions remain insufficiently characterized. Using the Parkinson's Progression Markers Initiative (PPMI) cohort (<i>n</i> = 455; 303 PD patients, 152 controls), we quantified plasma levels of these metabolites by quantitative LC-MS/MS with batch correction, examining sporadic PD and genetically defined subgroups (<i>LRRK2</i>-PD [PDL], <i>GBA1</i>-PD [PDG], dual-mutation PD [PDGL], and prodromal equivalents). Baseline one-way ANOVA showed significantly lower caffeine and paraxanthine in PDL (<i>p</i> = 0.0467, <i>p</i> = 0.0178) and PDG (<i>p</i> = 0.0408), reduced piperine in PDL (<i>p</i> = 0.0009), PDG (<i>p</i> = 0.0257), and prodromal <i>LRRK2</i> (<i>p</i> = 0.0168), and elevated sitosteryl hexoside in PDG (<i>p</i> = 0.0184). Longitudinal regression analyses revealed that in sporadic PD, caffeine negatively correlated with MDS-UPDRS parts I (β = -2, <i>p</i> = 0.0475) and III (β = -7.2, <i>p</i> = 0.007), trigonelline declined over time and was inversely associated with part III (β = -1.7, <i>p</i> = 0.0069), and sitosteryl hexoside negatively correlated with parts II (β = -68.3, <i>p</i> = 0.042) and III (β = -74.1, <i>p</i> = 0.0425). In PDL, sitosteryl hexoside inversely correlated with part I (β = -54.2, <i>p</i> = 0.0049), while in PDGL, paraxanthine showed negative associations with part II (β = -18.5, <i>p</i> = 0.00327). These findings demonstrate subgroup-specific alterations in food-derived metabolites and consistent inverse associations with PD severity, supporting their potential as non-invasive biomarkers, particularly in <i>LRRK2/GBA1</i> mutation carriers, and highlighting the need for longitudinal validation and dietary intervention trials to advance personalized PD management.

International Journal of Molecular SciencesVol. 27(1)
SingHealth (SG), Nanyang Technological University (SG), Singapore General Hospital (SG), Ruijin Hospital (CN), Duke-NUS Medical School (SG), National Neuroscience Institute (SG)
Duke-NUS Medical School, National Natural Science Foundation of China, Medical Research Council, National Medical Research Council
Openalex Percentile: Top 44%
Parkinson's Disease Mechanisms and Treatments
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.