Related Experiment Video
Updated: Aug 6, 2026

High-throughput Functional Screening using a Homemade Dual-glow Luciferase Assay
Published on: June 1, 2014
Genome-wide association studies identify genetic determinants of synucleinopathy biomarkers
Emma N Somerville1, Lang Liu1, Michael Ta2
1The Neuro (Montréal Neurological Institute-Hospital), McGill University.
Background:
α-Synucleinopathies are clinically and biologically heterogeneous disorders lacking reliable biomarkers to assist with early diagnosis, disease progression, patient stratification, and therapeutic targeting. Genetic variation is known to impact biomarker levels, influencing their utility and interpretation in research and clinical settings. We aimed to identify common genetic modulators of biomarker levels implicated in α-synucleinopathy pathogenesis.
Methods:
63 CSF, plasma, and urine biomarkers were analyzed in 581 individuals from the Parkinson's Progression Markers Initiative (PPMI). GWAS was performed to test for associations with common variants, while regressions and area under the curve (AUC) analysis was used to assess predictive power. Analyses were adjusted for age, sex, disease status, and principal components. PD- and DLB-risk loci associations were separately assessed for each GWAS.
Results:
We confirm strong associations between urine bis(monoacylglycerol)phosphate (BMP) isoforms and the variants LRRK2 p.G2019S and GBA1 p.N370S, while providing support for BMPs use as a LRRK2-PD biomarker. CSF Aβ was significantly associated with an APOE ε4 allele, reinforcing its central role in amyloid regulation. Novel associations were detected between CSF ceramide isoforms the MCF2L2 and GMNN loci, and between CSF tau and the TP63 locus. Multiple PD risk loci, including MAPT, SIPA1L2, MCCC1, and RAB29, were associated with lysosomal lipid biomarkers, highlighting pathway-level convergence.
Conclusions:
The present study reveals established and novel genetic modulators of potential α-synucleinopathy biomarkers, demonstrating that genetic background significantly shapes biomarker levels. These genetic influences should be accounted for when conducting biomarker-based research, clinical trials, or therapeutic development to ensure accurate interpretation and improve their translational relevance.
More Related Videos
Related Concept Videos
Genome-wide Association Studies-GWAS
GWAS does not require the identification of the target gene involved in...
Single Nucleotide Polymorphisms-SNPs
Parkinson Disease ll: Pathophysiology
Pharmacogenomics: Identification of New Drug Targets
Neural Regulation

