Jean-Paul Wiegand's Abstracts

Jean-Paul Wiegand's Abstracts

Jean-Paul Wiegand

     Jean-Paul Wiegand
     Neuroscience
     Ph.D. Candidate

     Conference Summary
     Society for Neuroscience
     San Diego, CA

 

Lay Abstract

Despite the LRRK2 mutation being the most common genetic cause of Parkinson’s
disease (PD), no study to date has investigated its impact on network-level neural
activity. This project is currently looking at circuit level sleep patterns in this very
prevalent genetic Parkinson's model. In both Parkinson's and Alzheimer's disease, sleep
disorders precede classic symptomatic onset and our hypothesis is that it may actually be
a contributing factor (rather than a symptom). As sleep oscillations are comparable in
rodents and primates, signatures of altered network communication during sleep could
serve as a diagnostic biomarker for the progression of LRRK2 PD and contribute to the
understanding of systems-level mechanisms underlying the disease. Our preliminary
evidence suggests that sleep oscillations are stronger in this model, and potentially more
stressful for sensitive striatal neurons that die off in PD.

Abstract

Stronger cortical spindles and less power variability in hippocampal ripples in a LRRK2
mouse model of Parkinson’s disease

Jean-Paul Wiegand (1,2), Kathleen Gies(3), Mitchell J. Bartlett(4,5), Torsten Falk(4,5), and
Stephen L. Cowen(1,3)

1Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ; 2Department of
Neuroscience. 3Department of Psychology, University of Arizona, Tucson, AZ; 4Department of
Neurology, University of Arizona, Tucson, AZ; 5Department of Pharmacology, University of
Arizona, Tucson, AZ

The LRRK2 mutation is the most common genetic cause of Parkinson’s disease (PD). Despite
this, no study to date has investigated its impact on network-level neural activity. Recent data
from Beccano-Kelly et al. (2014) suggest that LRRK2 knock-in mice exhibit an increase in
glutamatergic release in cortical neurons. Such changes could significantly alter cortico-thalamic
networks and enhance oscillatory activity produced by cortico-thalamic interactions.

Objective: We hypothesized that sleep-spindle oscillations are enhanced in LRRK2 knock-in
mice. To investigate this question, we compared ripple and spindle activity recorded from
LRRK2 knock-in and wild-type mice.

Methods: 5 LRRK2 G2019S and 9 WT C57bl/6 male mice (The Jackson Laboratory) were
implanted with depth electrodes and surface EEG electrodes. Depth electrodes were implanted
into the motor cortex (M1), anterior cingulate cortex (ACC), hippocampus and striatum. Surface
electrodes were implanted above somatosensory (S1) and visual cortex (V1). We recorded neural
activity during sleep periods preceding and following an open-field foraging task and novel
object exposure. Activity was recorded at 20kHz and down-sampled to 2kHz. We filtered for
spindle activity (9-16Hz) that exceeded 2.5 std above the mean power and ripple activity (80-
180Hz) that exceeded 5.5 std above the mean power.

Results: LRRK2 mice expressed a significant increase in the power of both early and late peak
spindle frequency (dB/Hz) relative to controls (p < 0.05, Student’s t-test) in all cortical regions
(M1, ACC, S1, and V1). In contrast, no difference in the distributions of peak spindle
frequencies and durations was observed between LRRK2 and wild-type mice. Moreover,
preliminary results from our analysis indicate that ripple-to-ripple variance in the power of each
ripple event is reduced in LRRK2 relative to WT mice (p < 0.05, Student’s t-test).

Conclusions: Our results support the conclusion that the LRRK2 G2019S mutation results in
lasting alterations in two sleep-associated patterns of neural activity that are linked to memory
consolidation. Because cortical sleep spindles and ripple oscillations are highly preserved across
species, these alterations could serve as a diagnostic biomarker for LRRK2 PD.