Electrophysiological Biomarkers in Dup15q Syndrome: Evaluation of Clinical Predictors and Longitudinal Stability

Poster Presentation
Saturday, May 12, 2018: 11:30 AM-1:30 PM
Hall Grote Zaal (de Doelen ICC Rotterdam)
V. Saravanapandian1, J. Frohlich1, C. DiStefano1, S. Huberty2 and S. Jeste3, (1)University of California Los Angeles, Los Angeles, CA, (2)Mcgill University, Montreal, QC, Canada, (3)University of California, Los Angeles, Los Angeles, CA

Dup15q syndrome is a neurodevelopmental disorder characterized by global developmental delay, hypotonia, intellectual disability (Battaglia et al, 2010), and an increased risk for both autism spectrum disorder (ASD) and epilepsy (Conan et al, 2014). Our previous study identified a unique electrophysiological signature in the form of increased beta oscillations (12-30 Hz) that distinguish Dup15q children from typically developing and non-syndromic ASD children (Frohlich et al, 2016). This EEG signature strongly resembles the pattern induced by gamma-aminobutyric acid alpha subunit (GABAA) receptor modulation and likely reflects overexpression of the GABAA receptor genes in the syndrome. With rigorous data collection in a much larger cohort, we have now quantified beta oscillations longitudinally and examined its relationship to clinical variables, which will help evaluate its properties as a potential biomarker to be used in longitudinal and intervention studies.


To determine: 1) whether beta power relates to clinical and demographic features including age, duplication type, epilepsy, IQ, social, communication, adaptive and motor skills in individuals with Dup15q syndrome and 2) whether beta power is stable over time.


Spontaneous resting state EEG was recorded from n=56 Dup15q syndrome patients (age range: 5 months - 41 years) seen both at UCLA and at the National Dup15q family conferences (IDDRC-NIH Grant#U54HD087101). Participants under medications that pharmacologically elicit beta oscillations were excluded. Relative beta power was computed, averaged across the whole scalp and simple linear regression models were implemented to model effects of clinical features. In participants who had follow-up EEG recordings (n=13, age range: 15-162 months), a generalized linear mixed model was used to model longitudinal beta power. Clinical measures tested included verbal and nonverbal cognition based on the Mullen Scales of Early Learning, adaptive function based on the Vineland Adaptive Behavior Scales (VABS), and autism severity based on the Autism Diagnostic Observation Schedule (ADOS).


Epilepsy diagnosis predicted beta power (R2=0.1839 P=0.0011) in Dup15q syndrome, consistent with our previous findings. A trend towards younger participants having higher beta oscillations was seen but not statistically significant (R2= 0.0658, P=0.0612). Verbal, nonverbal cognition and adaptive skills did not predict beta power. Autism severity was associated with increase in beta power but not statistically significant (R2= 0.1703, P = 0.0632). Beta power was significantly stable over time (P = .003), except in three participants who developed epilepsy between visits and beta power reduced after seizure onset.


Elevated beta oscillations in Dup15q syndrome appear to be stable over time in the absence of epilepsy. Further investigation is needed to evaluate EEG power changes after epilepsy onset, and to identify whether beta oscillations represent a protective biomarker for the development of seizures. The lack of a relationship with behavior reinforces the hypothesis that the unique brain activity pattern seen in Dup15q syndrome reflects the overexpression of the GABAA receptor genes and proves to be a robust biomarker of disease. Identification of brain-based biomarkers in rare disorders like Dup15q is instrumental in understanding the underlying biology of atypical brain development and can be used in targeted therapeutic trials.