Clinical and brain morphological characteristics of LRRK2-associated Parkinson disease
Poster No:
133
Submission Type:
Abstract Submission
Authors:
Qin Tao1, Shady Rahayel2,3, Christina Tremblay1, Andrew Vo1, Alain Dagher1
Institutions:
1Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, 2Department of Medicine and Medical Specialities, University de Montreal, Montreal, QC, 3Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, Montreal, QC
First Author:
Co-Author(s):
Shady Rahayel
Department of Medicine and Medical Specialities, University de Montreal|Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal
Montreal, QC|Montreal, QC
Department of Medicine and Medical Specialities, University de Montreal|Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal
Montreal, QC|Montreal, QC
Introduction:
LRRK2 mutation is the most significant genetic risk factor for developing late-onset Parkinson disease (PD), accounting for around 1% of sporadic PD (sPD) and 4-36% of familial PD [1-3]. However, the impact of LRRK2 mutation in PD remains unclear. The preclinical markers of LRRK2 mutation carriers who will develop PD still need to be explored [4, 5]. Here we examined the clinical and brain morphological characteristics of non-manifest LRRK2 mutation carriers (LRRK2-NMC) and LRRK2-associated PD (LRRK2-PD).
Methods:
We collected samples from the Parkinson's Progression Marker Initiative (PPMI, www.ppmi-info.org/) and analyzed the baseline clinical and T1 MRI data from 331 sPD, 77 LRRK2-PD, 78 LRRK2-NMC, and 162 healthy controls (HC) [6]. The LRRK2 patients do not have known GBA variants associated with PD. The analyzed clinical characteristics include 1) demographic, cognitive, motor, and nonmotor features; 2) dopamine transporter binding ratio of bilateral caudate and putamen (DAT SBR); and 3) four PD-related CSF biomarkers. Brain morphological features include cortical thickness, surface area, and cortical and subcortical volume (using FreeSurfer 7.2).
Afterwards, the clinical and brain morphological features were analyzed statistically between the four groups. For clinical data, differences between groups were analyzed using chi-square and t-tests with Bonferroni correction. For brain morphological features, general linear models were used for whole cortical surface vertex-wise statistics, controlling for age, sex, education, and disease duration. In the model, age and sex were included as covariates for cortical thickness and the estimated total intracranial volume was added as an additional covariate for surface area and volume. Differences between groups were corrected for multiple comparisons using the random field theory [7].
Afterwards, the clinical and brain morphological features were analyzed statistically between the four groups. For clinical data, differences between groups were analyzed using chi-square and t-tests with Bonferroni correction. For brain morphological features, general linear models were used for whole cortical surface vertex-wise statistics, controlling for age, sex, education, and disease duration. In the model, age and sex were included as covariates for cortical thickness and the estimated total intracranial volume was added as an additional covariate for surface area and volume. Differences between groups were corrected for multiple comparisons using the random field theory [7].
Results:
HC vs LRRK2-NMC. The LRRK2-NMC group showed a significantly higher MDS-UPDRS score and SCOPA-AUT total score than HC, suggesting that LRRK2-NMC may already present slight motor and autonomic deficits. Specifically, the tremor score was higher in LRRK2-NMC than in HC, while their postural instability and gait disorder scores were similar. No sleep or smell differences were found between the two groups. For brain morphometry, LRRK2-NMC had decreased surface area but thicker cortical thickness in parts of bilateral temporal lobes compared to HC. In addition, regions in the left paracentral lobe showed lower cortical thickness, surface area, and cortical volume in LRRK2-NMC than in HC. Moreover, LRRK2-NMC had a smaller surface area and cortical volume in parts of bilateral medial orbitofrontal lobes. There was no subcortical volume difference between the two groups.
LRRK2-PD vs sPD. There were no age, sex, or education differences between LRRK2-PD and sPD and the disease duration was longer in LRRK2-PD than in sPD. Thus, the lower DAT SBR and higher MDS-UPDRS scores in LRRK2-PD may be influenced by disease progression. However, the cognitive scores were almost similar between LRRK2-PD and sPD, suggesting slower cognitive decline in LRRK2-PD. In terms of brain morphometry, after matching for disease duration, LRRK2-PD patients showed thinner cortical thickness in a part of the left lingual gyrus and smaller surface area in parts of the right paracentral and middle temporal lobes compared to sPD. No subcortical volume difference was found between the two groups.
LRRK2-PD vs sPD. There were no age, sex, or education differences between LRRK2-PD and sPD and the disease duration was longer in LRRK2-PD than in sPD. Thus, the lower DAT SBR and higher MDS-UPDRS scores in LRRK2-PD may be influenced by disease progression. However, the cognitive scores were almost similar between LRRK2-PD and sPD, suggesting slower cognitive decline in LRRK2-PD. In terms of brain morphometry, after matching for disease duration, LRRK2-PD patients showed thinner cortical thickness in a part of the left lingual gyrus and smaller surface area in parts of the right paracentral and middle temporal lobes compared to sPD. No subcortical volume difference was found between the two groups.
Conclusions:
This study investigated the clinical and brain morphological characteristics of LRRK2 mutation carriers with and without PD. Our findings show that early LRRK2-NMC presents different clinical and brain structural patterns compared to HC. This research may deepen our understanding of LRRK2-related PD mechanisms and contribute to disease prediction and diagnosis.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 1
Genetics:
Genetic Association Studies 2
Keywords:
Other - LRRK2 mutation carriers; Parkinson disease; LRRK2-associated Parkinson disease
1|2Indicates the priority used for review
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2. Marek, K. (2011). "The Parkinson progression marker initiative (PPMI)." Progress in neurobiology 95(4): 629-635.
3. Menozzi, E. (2023). "Who is at Risk of Parkinson Disease? Refining the Preclinical Phase of GBA1 and LRRK2 Variant Carriers: a Clinical, Biochemical, and Imaging Approach." Current Neurology and Neuroscience Reports.
4. Sosero, Y. L. (2023). "LRRK2 and Parkinson's disease: from genetics to targeted therapy." Annals of Clinical and Translational Neurology.
5. Taymans, J.-M. (2023). "Perspective on the current state of the LRRK2 field." npj Parkinson's Disease 9(1).
6. Tolosa, E. (2020). "LRRK2 in Parkinson disease: challenges of clinical trials." Nature Reviews Neurology 16(2): 97-107.
7. Worsley, K. J. (1996). "A unified statistical approach for determining significant signals in images of cerebral activation." Human Brain Mapping 4(1): 58-73.