Multi-tracer PET correlation analysis reveals disease-specific patterns in Parkinson's disease and asymptomatic LRRK2 pathogenic variant carriers compared to healthy controls

Julia G Mannheim ¹, Jessie Fanglu Fu ², Tilman Wegener ³

¹Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada; Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, Eberhard-Karls University Tuebingen, Tuebingen, Germany; Cluster of Excellence iFIT (EXC 2180) "Image Guided and Functionally Instructed Tumor Therapies", University of Tuebingen, Tuebingen, Germany.
²Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States.
³Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada; Department of Medical Engineering, University of Luebeck, Luebeck, Germany.
⁴Division of Neurology, Department of Medicine, University of British Columbia, Vancouver, BC, Canada.
⁵Pacific Parkinson's Research Centre, The University of British Columbia, Vancouver, British Columbia, Canada.
⁶Division of Neurology, Department of Medicine, University of British Columbia, Vancouver, BC, Canada; Pacific Parkinson's Research Centre, The University of British Columbia, Vancouver, British Columbia, Canada.
⁷Mayo Clinic Florida, Department of Neurology, Jacksonville, FL, USA.
⁸Division of Neurology, Department of Medicine, University of British Columbia, Vancouver, BC, Canada; Djavad Mowafaghian Centre for Brain Health, Pacific Parkinson's Research Centre, University of British Columbia & Vancouver Coastal Health, Vancouver, BC, Canada.
⁹Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada; Djavad Mowafaghian Centre for Brain Health, Pacific Parkinson's Research Centre, University of British Columbia & Vancouver Coastal Health, Vancouver, BC, Canada.

⁰Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada; Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, Eberhard-Karls University Tuebingen, Tuebingen, Germany; Cluster of Excellence iFIT (EXC 2180) "Image Guided and Functionally Instructed Tumor Therapies", University of Tuebingen, Tuebingen, Germany.

Neuroimage. Clinical +

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April 10, 2024

View abstract on PubMed

Summary

Multi-set canonical correlation analysis identified common spatial patterns of dopaminergic denervation in Parkinson's disease (PD) and LRRK2 variant carriers. This method reveals early disease alterations, even in asymptomatic individuals, aiding in understanding PD progression.

Area Of Science

Neuroscience
Genetics
Medical Imaging

Background

Genetic factors, particularly leucine-rich repeat kinase 2 (LRRK2) gene variants, are significant risk factors for Parkinson's disease (PD).
Understanding the spatial patterns of dopaminergic system changes is crucial for diagnosing and tracking PD progression.

Purpose Of The Study

To apply multi-set canonical correlation analysis (MCCA) to multi-tracer Positron Emission Tomography (PET) data for extracting PD and LRRK2 variant-specific spatial patterns.
To investigate dopaminergic denervation patterns in asymptomatic and symptomatic PD stages and compare MCCA with traditional univariate analysis.

Main Methods

Utilized multi-set canonical correlation analysis (MCCA) on multi-tracer PET data from Parkinson's disease (PD) patients, LRRK2 variant carriers, and healthy controls (HCs).
Extracted spatial patterns of dopaminergic terminal density alterations (DAT and VMAT2) across different subject cohorts and stages of the disease.

Main Results

Identified common PD-induced spatial distribution alterations in both asymptomatic LRRK2 variant carriers and PD subjects.
The dominant pattern indicated overall dopaminergic terminal density denervation, followed by asymmetry and rostro-caudal gradients, with deficits in the less affected side being a key progression marker.
Observed a trend towards PD-related patterns in LRRK2 variant carriers correlating with age, reflecting their increased PD risk.

Conclusions

MCCA effectively identifies common spatial alterations in tracer binding patterns, offering a more comprehensive view of disease-induced changes than traditional methods.
The study highlights the potential of MCCA in detecting early, subtle dopaminergic changes associated with PD and LRRK2 variants.

Keywords:

HCs Joint pattern analysis LRRK2 PD PET

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