Clinical Trial Details
— Status: Completed
Administrative data
NCT number |
NCT00670709 |
Other study ID # |
QEEG and HD |
Secondary ID |
|
Status |
Completed |
Phase |
|
First received |
|
Last updated |
|
Start date |
September 2006 |
Est. completion date |
February 2008 |
Study information
Verified date |
November 2023 |
Source |
University of California, Los Angeles |
Contact |
n/a |
Is FDA regulated |
No |
Health authority |
|
Study type |
Observational
|
Clinical Trial Summary
The pace of basic science research defining the mechanisms of selective neuronal degeneration
in Huntington disease (HD) has far exceeded the pace of translation of this information into
clinically effective treatments for the disease. One reason for this bottleneck between bench
and bedside is the paucity of available surrogate markers for HD. Identification of surrogate
markers is critical for the design of future clinical trials. Such markers could provide a
reliable signal of early brain dysfunction in HD and could be used as a biomarker in trials
of agents that could prevent onset or delay progression of disease.
Frontal-subcortical networks are known to be affected in HD and contribute to the cognitive
dysfunction characteristic of the disease. Quantitative EEG (QEEG) can be used to assess the
integrity of this circuitry; characteristic QEEG abnormalities long have been known to be
present in the early stages of the illness (Bylsma et al., 1994). More recent research has
suggested that a comprehensive topographic approach to QEEG analysis may reveal additional
changes in brain activity (Bellotti et al., 2004) that may be indicative of subclinical
disease (de Tommaso et al., 2003). This proposal aims to determine whether quantitative EEG
techniques can be used to identify HD-specific abnormalities and thus serve as surrogate
markers of disease.
The goals of this pilot project are three-fold. First, we will determine if there are QEEG
differences between normal control subjects and those with mild or moderate HD. Second, we
will examine associations between severity of HD and the QEEG differences detected and
determine if these QEEG differences are present when comparing the least affected HD subjects
and normal controls. Third, we will examine associations between QEEG variables of interest
and other clinical variables, including age of onset of symptoms, number of CAG repeats,
severity of motor and behavioral symptoms as measured by the Unified Huntington Disease
Rating Scale (UHDRS) subscores, and severity of cognitive impairment as measured by the
cognitive subscore of the UHDRS and Mini-Mental State Examination (MMSE).
Description:
We will examine three subject groups in this study: those with mild HD, those with moderate
HD, and normal controls. Fifteen subjects will be examined in each group, for an overall
total of forty-five subjects. HD subjects will be recruited from the UCLA Huntington Disease
Center of Excellence where they have been followed with serial neurologic examinations and
completion of all portions of the UHDRS every 6-12 months. Subjects that have been given a
diagnosis of HD based on appropriate motor signs and a confirmatory genetic test or a known
family history of HD will be invited to participate. Healthy control subjects will be
recruited from the clinic as well through spouses or other unaffected relatives of patients.
In addition, control subject data acquired from previous studies will be used after matching
for age. All subjects will be over the age of 21 and free of other medical illnesses that
could also affect brain function and will be able to give informed consent. Mild HD is
defined as having Total Functional Capacity [TFC] scores on the UHDRS of 11-13, moderate is
defined as TFC of 7-10, and normal control subjects will be free of any neurologic or
psychiatric illness. Subjects will be free of antipsychotic or antidepressant medications,
benzodiazepines, or other medications known to affect central nervous system function for at
least 10 days prior to QEEG examination.
All subjects will undergo QEEG recording in a manner similar to that employed clinically,
using procedures that have been approved in other protocols by the UCLA Medical IRB and that
are consistent with standard clinical EEG procedures promulgated by ABRET (American Board of
Registered Electroencephalographic Technologists). Recording electrodes are applied to the
scalp using an electrode cap (ElectroCap, Inc., Eaton OH); electrodes are arrayed to record
electrical activity from all major brain regions using a standard extension of the
International 10-20 system (figure 1). Recording electrodes are connected to an isolation
amplifier that is part of the digital EEG system (NuAmp System, NeuroScan, Inc., El Paso,
TX). Data are recorded in real-time on computer disk. During recording, subjects will be
resting in a quiet room with subdued lighting, in the eyes-closed, maximally alert state; the
EEG technologists will alert the subjects whenever drowsiness is evident on the computer
monitor. Data will be displayed in real-time on a computer monitor during recording, with
adjustable filtering and amplification to facilitate identification of EEG patterns as well
as artifact. Data will be collected using a bandpass filter of 0.3 to 70 Hz, and will be
digitized at a rate of 250 samples/channel/second. Data will be recorded with a Pz
referential montage, and the NeuroScan software then will reformat the data into bipolar
montages as needed for the cordance calculations. Three EOG leads will be used (RIO-A2,
ROC-A2, and LOC-A1) so that lateral, horizontal, or oblique eye movement artifact may be
detected easily. Data for quantitative analysis will be selected from the data recorded
according to standard procedures: each EEG will be reviewed by a technician and the first
20-32 seconds of artifact-free data will be selected to be processed to obtain absolute and
relative power in four frequency bands (0.5-4 Hz, 4-8 Hz, 8-12 Hz, and 12-20 Hz) after the
selections are confirmed by a second technician; both technicians will be blinded to clinical
status while making or reviewing the selections.
Two QEEG measures will be calculated for each subject. The first of these is cordance, which
will be calculated using an algorithm that has been detailed elsewhere (Leuchter et al.,
1999). Cordance is based upon a normalization of absolute and relative power values across
all electrode sites and all frequency bands for a given recording. Cordance values have a
stronger association with cerebral perfusion in brain tissue underlying each electrode site
than do standard QEEG power measures. The second QEEG measure to be examined is QEEG
coherence (Leuchter et al., 1992; 1994b), a measure of the shared functional activity between
brain regions. Coherence values range between 0 - 1 and are analogous to a correlation
coefficient, with values near 1 signifying highly coordinated cerebral activity. Coherence
reflects not only cortical activity, but also the function of deep gray matter structures
that coordinate cortical activity as well as white-matter tracts connecting brain regions.