Biomedical Engineering Reference
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11.3.2 Toward Physiological Endophenotypes
As illustrated by the clinical presentations listed earlier in Table 11.1, there can be
considerable heterogeneity in individuals all carrying the same clinical diagnosis.
Given the limited historical success in relating symptom-based subtypes to individ-
ual response to treatment, it has been suggested that expanding our ability to relate
neurobiological discoveries to clinical realities will require a shift in perspective,
away from symptom-focused nosologies and toward that of endophenotypes [153],
namely, the “measurable components unseen by the unaided eye along the pathway
between disease and distal genotype.” In the present context, the endophenotype
concept can be stated as follows: Within a set of individuals who all meet the diag-
nostic criteria for unipolar major depressive disorder, there are distinct, discrete
subpopulations each of which shares a common set of meaningful physiological
characteristics.
The identification of these groups might allow better understanding of many
important issues: how genes and the environment may contribute vulnerability to
developing depression; why some individuals respond preferentially to one treat-
ment over another; why some patients will have a single, brief bout of depression in
their lifetime and others will spend large fractions of the lives disabled by recurrent,
chronic depression; why some patients have cognitive disabilities that impair work
and social function, while others do not; why some women with past experiences
with depression develop significant episodes during pregnancy and in the
postpartum period, while others do not; why some patients with depression go on to
develop dementia in a few years and others do not, to name a few. Measurements
with qEEG techniques may be able to aid in endophenotypic characterization.
Additional research along this thematic line will be needed to determine the useful-
ness of this approach.
11.4
Conclusions
Quantitative EEG methods have much to contribute to psychiatry, not only in
expanding our understanding of the physiological underpinnings of disorders such
as depression, but critically in improving the ability of clinicians to treat patients
struggling with psychiatric brain disorders. The use of qEEG-based biomarkers
could greatly impact the field, but there are considerable risks to premature adop-
tion of methods and measures that have not met the usual peer-reviewed independ-
ent replication standards.
We proposed some useful guidelines in assessing the readiness of any qEEG
biomarker for clinical use, particularly in the sphere of major depression. Finally,
many new methods are being developed by groups around the world, some of which
will come to find clinical application. We described some of the promising
approaches being examined in our own laboratory and elsewhere, but note that this
rapidly evolving field is best monitored via online databases of peer-reviewed jour-
nal publications.
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