Symptom Overlap
Between
Schizophrenia and Bipolar Disorder
(Neurobiological and Genetic insights)
Abstract
The debate of symptom overlap in bipolar disorder and schizophrenia is
not a new one. However the irony is that despite advancements in biological sciences of
mental illness, diagnosis and classification systems and treatments, the question remains
alive as ever. This limitation opens up possibilities of some overlap of symptoms between
several psychiatric disorders, more specifically between schizophrenia and mood
disorders. The overlap of symptoms has given rise to a thought in retrospect whether
some of syndromes or domains or the illnesses itself arise from a common origin. The
present paper examines the categorical diagnostic position of schizophrenia and bipolar
disorder based upon current evidence. We argue that both schizophrenia and bipolar
disorder lie of same spectrum of psychopathology and therefore have significant overlap
of symptoms at least in few of the domains of the illnesses. We then discuss the common
territories of over lap in symptomatology and psychopathology. Further we propose that
the two illnesses or at least a subgroup of each, are not distinctly different but share a
common origin and manifestation. We conclude that both schizophrenia and bipolar
disorder share significant feature which are indistinguishable from each other suggesting
possibility of both these illnesses as continuous and not dichotomous.
Key words : bipolar disorder, symptoms, schizophrenia, psychopathology
Introduction
The debate of symptom overlap in bipolar disorder and schizophrenia is
not a new one. However the irony is that despite advancements in biological sciences of
mental illness, diagnosis and classification systems and treatments, the question remains
alive as ever. Further increasing evidence, showing biological overlap between
schizophrenia and bipolar disorder challenges the concept of two distinct clinical
identities. Symptoms and symptom clusters are the main criteria for diagnosis in
nosological as well as in systems of classifications. Though there have been revolutionary
advancements in the field of biological basis of mental disorders, no definite markers
have emerged for any particular disorder.
In the psychosocial field, no definite factor or group of factors, have
been helpful in defining any ‘pathognomonic’ symptom for making a definitive diagnosis.
In fact so far neither biological nor psychosocial etiopathological factors form basis or
criteria for diagnosis of mental disorder. Consequently we are still relying of
characteristic symptomatology for diagnosis. This limitation opens up possibilities of
some overlap of symptoms between several psychiatric disorders, more specifically
between schizophrenia and mood disorders. The overlap of symptoms has given rise to a
thought in retrospect whether some of syndromes or domains or the illnesses itself arise
from a common origin. More precisely questioning that schizophrenia and bipolar
disorder are two different disorders.
The present paper examines the categorical diagnostic position of
schizophrenia and bipolar disorder based upon current evidence. We argue that both
schizophrenia and bipolar disorder lie of same spectrum of psychopathology and
therefore have significant overlap of symptoms at least in few of the domains of the
illnesses. It is likely that overlapping symptoms form manifestation of ‘common
endophenotype’, which may need to be assessed and treated differently. In this paper we
first examine the current state of diagnostic criteria, diagnostic stability,
psychopathological and biological evidence in support of schizophrenia and bipolar
disorder. We then discuss the common territories of over lap in symptomatology and
psychopathology. Further we propose that the two illnesses or at least a subgroup of each,
are not distinctly different but share a common origin and manifestation. We conclude
that both schizophrenia and bipolar disorder share significant feature which are
indistinguishable from each other suggesting possibility of both these illnesses as
continuous and not dichotomous.
Historical evolution of a psychopathologic terminology
The Kraepelinian dichotomy between schizophrenia and bipolar
disorder, otherwise classically referred to dementia praecox and manic-depressive
insanity respectively, has sustained a recent and vigorous onslaught.1 This debate echoes
Kraepelin’s own prescient observation that no one will deny that there is n overlap in
large number of cases in which it seems impossible, in spite of the most careful
observation, to make a firm diagnosis.2 Historical aspects of the dichotomy between
manic-depressive disorders and schizophrenia raise the question of a continuum between
the two entities. Although Kraepelin’s traditional dichotomy is still a common base for
clinicians every day: diagnosis, prognosis and treatment of psychotic disorders, recent
epidemiological and neurobiological data are congruent with a dimensional aspect of
psychosis. Epidemiological data are consistent with the existence of an individual and a
familial overlap between bipolar disorder and schizophrenia.2
Attempts to define patient-experienced symptoms, was not made until the
19 century and psychiatrists at that time were embedded in an intellectual system that
described the functions of the mind on the basis of the “pure reasoning” of philosophers
such as Kant4 and Locke5. The descriptions of the mind focused on the senses, and mental
representations. This emphasis led to a fairly straightforward development of clinical
terms for dysfunctions of the ‘thought’ process. A more difficult challenge for
psychiatrists in the 1800s was the creation of concepts such as ‘mood’ and ‘affect’ and
the conceptualization of affect as a discrete faculty of the mind.6 Further, nineteenthcentury psychiatrists soon found that there were many possible combinations of psychotic
disorders i.e. disorders marked by symptoms such as delusions, hallucinations, and
disintegration of linear thought, and affective disorder. These were defined by the
evolving concept of affective syndromes such as depression and mania. Discussions soon
developed on the means of determining when mania or depression might be secondary or
primary to psychotic disorders7-8 and whether mood disorders with comorbid psychosis
should be considered as separate from mood disorders without psychosis.9
th
3
In 1863 Kahlbaum10 described volition as a third mental faculty and
defined a category of psychiatric disturbances that could be described as dysfunctional
conditions of volition, a separate from disturbances of the intellect and the emotions. This
division gained predominance. In 20th-century it took a unique proposition which
described Kraepelin’s ‘dementia praecox’ and ‘manic-depressive illness’ as two separate
disease processes. Bleuler7 and Schneider11 took Kraepelin’s basic notion of a chronic
psychotic disease, which was renamed as schizophrenia. They developed descriptions of
particular symptoms or primary traits, i.e. symptoms that were always present and were
believed to be pathognomonic of the disease. Bleuler recognized disorders of affect as
one of the primary or fundamental symptoms of schizophrenia and described that other
types of mood disorder, such as depression and mania, are often present among persons
who have schizophrenia. It is important to note that he considered depression and mania
as two of many possible secondary or ‘accessory’ syndromes of schizophrenia.
Concurrently with Bleuler’s and Schneider’s attempts to define the
schizophrenias, English clinicians defined particular symptom clusters and syndromal
variants that could be used to define the manic-depressive illnesses, including
nonpsychotic versions of these illnesses.12 In 1933 a third diagnostic entity called
‘schizoaffective psychosis’ was introduced by Kasanin13 to describe psychiatric illness
marked by prominent affective and psychotic features that appear in a cyclical course.
The 1970s saw the development of tentative, or experimental, specific diagnostic
categories by Feighner and associates14 and Spitzer and associates.15 These categories
were intended to provide criteria to be used by clinicians who wanted to define major
depressive, manic, and schizoaffective syndromes as well as the diseases. These authors
derived their criteria by asking a number of colleagues what they considered to be the
essential symptoms or signs of these syndromes or illnesses. The concepts for making
differential diagnoses were derived principally from the work of Feighner and
associates14, who emphasized course of illness in contrast with the cross-sectional
diagnoses.
The American Psychiatric Association16, in successive versions of the
Diagnostic and Statistical Manual of Mental Disorders, adopted the research criteria
developed by Feighner and Spitzer and further clarified the notions of syndromes,
episodes, and disorders. The nomenclature that has developed allows identical clusters of
symptoms to be considered as an episode, for example, major depressive episode and
manic episode or a syndrome for example, major depressive syndrome and manic
syndrome on the basis of whether the cluster of symptoms occurs in the context of bipolar
disorder or major depressive disorder or in the context of schizophrenia or schizoaffective
disorder, respectively. Kendler and colleagues17 applied a latent class analysis to 343
patients who had been treated for psychotic and affective disorders and, using a 21-item
rating scale, determined six underlying disease syndromes. These syndromes were
validated on the basis of distinct demographic, familial, clinical, and course data that were
not used in the latent class analysis. Their study used modern computer and statistical
methods to define a nosology in much the same way that Kraepelin had once used
empirical observation and grouping of patients to derive his binary psychosis model. The
six types of illness proposed by Kendler and colleagues suggest that the spectrum of
psychotic and affective disorders is more complex than Kraepelin suggested. The types of
illness proposed by Kendler and colleagues are classic schizophrenia, bipolar schizomania, major depression, schizo-depression, schizophreniform disorder, and hebephrenia.
At last, the question of schizophrenia and mania as a distinct disorder
remains, suggesting what is more clearer today than ever is the significance and evidence
of overlap of symptoms in both the disorders.
Overlapping symptoms (what do we mean by overlapping )
While categories at the extreme end of the psychotic spectrum
meaningfully differed across a number of the illness-related variables, no substantial
discontinuity was apparent between adjacent categories of psychotic disorders. Risk
factors, premorbid adjustment, clinical features and impairment appeared to be present in
a mostly monotonic continuous fashion from non affective psychoses to mood disorders
with psychotic features. The overall association pattern of illness-related variables with
mood and psychotic syndromes was largely independent of specific diagnostic categories,
and the dimensional approach was neatly superior to the traditional diagnostic approach
in explaining the characteristics of the illness.18
However the extent to which bipolar disorder is considered separately
from schizophrenia and other psychoses varies. For example, schizophrenia usually
includes psychotic symptoms such as hallucinations, delusions, and thought disorder, as
well as “negative” symptoms such as flatness of affect, poverty of speech, or loss of
motivation. The diagnosis of schizophrenia excludes significant mood disorder. In
contrast bipolar disorder is characterized by prominent mood symptoms and may or may
not involve psychosis.19
Diagnostic dilemma
Cross-sectional diagnoses, while improved with the advent of welldefined diagnostic criteria, still remain a blunt instrument. Kraepelin emphasized the
importance of the course of illness in arriving at a diagnosis. Subsequent work has shown
that initial diagnoses do not always remain stable over time, though the great majority of
those with an initial SCZ or mood disorder diagnosis do receive the same diagnosis on
reassessment.20-23 For example, one study showed that between six months from initial
contact, and 24 months, 5% of those initially diagnosed with SCZ switched to mood
disorder or schizoaffective disorder, while 9% of those initially diagnosed with mood
disorder switched to SCZ or schizoaffective disorder.23 In another study, 15 of the 16
patients whose diagnosis changed at later follow-up from affective to non-affective
psychosis had mood-incongruent features initially.24 Diagnostic stability has been
particularly poor for schizoaffective disorder. One study showed that only 36% of those
initially diagnosed with the disorder received the same diagnosis at a later time point.25 In
addition to the problems with diagnostic stability over time in schizoaffective disorder,
investigators have also found a lack of cross-sectional diagnostic reliability for this
disorder.26-27
The evidence for the overlap
Biological parameters (neurochemistry, neurophysiology and neuroimaging)
Finally, as neuroscience has developed, more detailed hypotheses have
emerged to describe the neural substrate from which all psychiatric disorders ultimately
derive. Anatomical studies, functional imaging studies, and more detailed cognitive
studies have begun to piece together the neural mechanisms of emotion.28 As described
by Derryberry and Tucker28, psychiatry’s historical tendencies to search for biological
systems that underlie a given syndrome, such as depression or mania, ultimately fail to
appreciate the interdependence of the multiple layers of the neural hierarchy. The
hippocampal system, for example, connects putative behavioral inhibitory and excitatory
systems with other neural mechanisms in the paralimbic cortex and neocortex, which
process complex mental representations of the self and the social environment.
Medications provide yet another useful tool for separating distinct pathologic processes
that, from an observational standpoint, might appear identical.
Pharmaceutical treatments may reflect the pathological mechanism
of a disease. A few same classes of pharmaceutical treatments are arguably considered to
treat these two disorders. The mechanisms of actions of these treatments may shed some
insights into the molecular basis for these two disorders. Atypical antipsychotics that
target both the dopamine 2 (D2) and serotonin 5-HT2A receptors can be used to treat
schizophrenia (SCZ). Recently, anti-psychotic agents have been increasingly prescribed
to bipolar mood disorder (BMD) patients. The effects of these pharmaceutical
compounds on SCZ and BMD suggest that dopaminergic and serotonergic pathways are
both involved in the pathogenesis of SCZ and BMD.29 It is of note that these antipsychotics may have varying affinities for these receptors. The efficacy of these different
anti-psychotics may also vary by diagnosis. Possibly, the pathogenesis of these two
disorders may be influenced by heterogeneous mechanisms underlying dopaminergic and
serotonergic pathways.
Genetic pathways
The most compelling line of support for a common biological
pathogenesis shared by SCZ and BMD is provided by genetic studies suggesting that
some of the same genes influence risk for both disorders. For example, one study has
recently reported altered expressions of oligodendroglia-related genes in multiple brain
regions to be associated with both SCZ and BMD.30 Linkage studies have provided
another line of support. In genome-wide linkage analyses of these disorders, at least 5
distinct genomic regions have been implicated as being linked to susceptibility for both
SCZ and BMD.31 Among the chromosomal regions identified as possibly harboring
putative risk genes for both SCZ and BMD are 4p32, 6q, 18p, 13q, and 22q.33-34 Candidate
gene-based association studies have also implicated several risk genes that may
contribute to susceptibility to both SCZ and BMD. Among these implicated genes that
may influence susceptibility to both disorders are dysbindin (DTNBP1), G72 (DAOA),
disrupted in schizophrenia (DISC1), catechol-O-methyl transferase (COMT), and brainderived neurotrophic factor (BDNF), and others, as reviewed elsewhere.35 These findings
have provided potentially useful leads for efforts to disentangle the shared liability for
SCZ and BMD. In the next section, we describe some of the epidemiological and
statistical approaches for such efforts.
Craddock and colleagues35 postulated a formulation to conceptualize a
spectrum of clinical phenotypes associated with SCZ, schizoaffective disorder, and mood
disorders. In this putative spectrum of symptoms, psychotic symptoms, mixed psychoticaffective features, and mood symptoms (particularly mania) are modulated by 3 clusters
of susceptibility genes; these 3 clusters of genes are partially overlapped with each other.
Owen and others36 pointed out that these 3 subsets of genes are represented by the
DTNBP1, DISC1, and DAOA genes, respectively. Based on this model, one may infer
that different genes may influence the risk of SCZ or BMD to the different extents.
Familial Co-Aggregation of SCZ and BMD and genetics
Schizophrenia and bipolar disorder are 2 of the most severe mental disorders
that still are associated with insufficient clinical response, a chronic relapsing course, and
functional disability in a substantial number of patients. Although treatments during the
first episode of psychosis and mania have yielded encouraging results, follow-up
studies37 have been somewhat disappointing, reconfirming that despite high initial
response rates, illness relapse38 and lack of functional recovery39-40 are relatively frequent.
Over the past decade, the schizophrenia field has responded to this situation with a push
toward early recognition and intervention during the pre-psychotic (i.e., prodromal) phase
of the illness.40-41 However, there is a lack of studies that have focused on the
identification of patients who are identified based on emerging clinical symptoms that
would be indicative of future bipolar I disorder, rather than on the presence of genetic
risk or a preceding diagnosis, such as unipolar depression, attention deficit hyperactivity
disorder, or a bipolar spectrum disorder. This dearth of clinical high-risk studies in
bipolar disorder can be explained by the fact that the presence and nature of a clinical
prodrome is not well established in this condition.42
determinants
43
However, both conditions are intimately related, with shared genetic
and common polygenic variants, as confirmed by the International
Schizophrenia Consortium (ISC) in a genome-wide association study of 3,322
Europeans.44 Thus, epidemiological characteristics, family studies, and overlapping
genetic linkages together support shared genetic risk factors in bipolar and
schizophrenia33 and there is additional new evidence showing similar changes in gene
expression in both conditions.45
Bipolar disorder shares many of the same brain regions as
schizophrenia. However, relative to neurotypical controls, lower gray matter volume in
schizophrenia is more extensive and includes the amygdala. Common biological
mechanisms may explain the neuroanatomical overlap between these major disorders, but
explaining why brain differences are more extensive in schizophrenia remains
challenging. There is a substantial overlap in clinical and neuropathological findings
between these disorders. Moreover, recent studies have demonstrated that the genetic
vulnerability for schizophrenia, bipolar disorder and depression is shared.46-49
Consequently there is also an increasing debate about the current classification of
psychotic disorders. Indeed, the identification of groups of patients with a particular
vulnerability to underlying neuropathological processes could provide an alternative
classification of psychotic disorders of greater utility to psychiatric genetic research as
compared to current classifications.
A common pathological mechanism for two diseases may be reflected by
comorbidity in the same individual. However, the current hierarchical diagnostic systems
for psychiatric diseases do not allow dual diagnoses for SCZ and BMD in the same
individual (with BMD-Not Otherwise Specified as an exception) and thus pose a
challenge for assessing shared etiology for SCZ and BMD at the individual level. As an
alternative, familial co-aggregation, which reflects excessive occurrence of two disorders
within the same family, can provide evidence for common genetic pathways for SCZ and
BMD. Familial co-aggregation50 and co-segregation51 differ in that the former indicates
that the clustering of two diseases within families, which does not necessarily result in the
occurrence of two diseases in the same individual; the latter can lead to the occurrence of
two diseases in the same individual. One common approach for testing for the presence of
familial co-aggregation is to determine if the risk for one disease (e.g., SCZ) is elevated
in relatives of an individual affected with a second disease (e.g., BMD). Excess familial
risk can be assessed either by contrasting disease prevalence (e.g., of SCZ) in relatives of
case (e.g., BMD) probands with disease prevalence in either the relatives of control
probands or with overall population prevalence rates.
In fact, evidence for familial co-segregation of SCZ and BMD has
been provided by Valles52 who reported that first-degree relatives of BMD patients had a
4-fold higher risk of SCZ compared with relatives of healthy individuals. In familial cosegregation studies, various statistical approaches can be used for the comparisons to take
into account such issues as the ages of the family members, other disease risk factors, and
the correlations in measurements due to the family members being related to each other.53
One caveat of co-aggregation studies is that they may provide spurious evidence for
familial co-aggregation if the 2 diseases being studied are easily misdiagnosed or can be
confused with each other due to resemblances of clinical features of these two disorders.
Gene versus environment factors
The clustering of a disease within families alone does not permit one to
distinguish between the effects of genetic factors and environmental factors in the
etiological pathway of disease because relatives who share genes in common are also
more likely to share similar lifestyles and/or environmental risk factors. In the same way,
the presence of familial co-aggregation of two diseases within the same family alone
cannot distinguish between the role of shared genetic factors and environmental factors in
a shared etiological pathway.54 One conventional approach used to clarify the relative
impact of genetic variants versus environmental factors on a single disorder is to parse
out the variance in trait susceptibility to that attributable to genes and that attributable to
non-genetic (or environmental) risk factors using statistical approaches akin to analysis of
variance. In such approaches, the variation in the trait due to genetic factors is modeled as
a function of trait similarity among related individuals, and the heritability of the trait is
defined as the proportion of the total trait variance due to genetic effects.55
The standard variance decomposition procedures can be extended for
the joint study of two diseases to tease apart genetic and environmental influences of two
disorders using a bivariate extension of the variance component approach. This method
partitions the joint variation in the two traits into their trait-specific genetic components,
trait-specific environmental components, shared genetic effects, and shared
environmental effects. The shared genetic effects represent effectively the “coheritability” of the two traits. One can use bivariate variance component method to study
the genetic relationship between 2 continuous traits.56 One application of this approach is
described by researchers57 who reported strong genetic correlations between serum
concentrations of insulin and body mass index and between insulin and plasma levels of
high-density lipoprotein-cholesterol, suggesting that one or more genes influences joint
variation in these sets of traits. This bivariate analysis method has been extended for
analysis of binary phenotypes using variance component models or generalized linear
mixed models.58-60
Twin studies
The analysis of twin studies represents a subtype of family analysis that
can be used to differentiate between genetic and environmental contributions to familial
aggregation. In principle, one can evaluate whether genes play an important role in
susceptibility to disease by comparing disease prevalence in the monozygotic (MZ) twin
siblings of affected probands to disease prevalence in the dizygotic (DZ) twin siblings of
affected probands. Higher disease prevalence in the MZ twin pairs is generally
interpreted to indicate a genetic basis for disease if one assumes that environmental risk
factors are shared equally among DZ twin pairs as among MZ twin pairs (an assumption
that can be challenged in some situations).61 By extending the framework of twin studies
from one disorder to two disorders, one can further test whether the MZ twin siblings of
SZ probands have higher risk of BP compared with DZ twin siblings of SZ probands (or
vice versa) to provide insights into the relative impact of genes on familial co-aggregation
of these two disorders.62 Cardno and colleagues examined genetic correlations between
SCZ, schizoaffective disorder, and BMD in 77 monozygotic and 89 same-sex dizygotic
twin pairs using relaxed diagnostic criteria. They found evidence for both common and
syndrome-specific genetic contributions to the variance in liability to SCZ and manic
syndromes, but the genetic liability to the schizoaffective syndrome was entirely shared
in common with the other two syndromes. In contrast, environmental liability to the
schizoaffective syndrome was not shared with the other syndromes.63
Identifying the Shared Risk Genes
Conventional approaches used to identify risk alleles for single
disorders include linkage and association studies. Linkage analysis is based on using
recombination frequencies to infer physical distance between a genetic marker and target
risk locus64, while association studies directly measure the correlation between the
genetic polymorphism at a locus and the disease endpoint.65 Association analyses are
more powerful to detect causal variants, provided there is linkage disequilibrium (i.e.,
correlation between a paired of genetic loci) between the genetic marker and disease loci;
however, linkage analyses are more powerful in the absence of such disequilibrium. 66
Excellent reviews of both approaches have been published elsewhere.67
The introduction of high-output, low-cost genotyping technologies has
recently generated great enthusiasm in the field of complex disease genetics by making
possible the conduct of large-scale genetic association studies that use 500,000 or more
single nucleotide polymorphisms (SNPs) scattered throughout the genome.68 Such studies
have rapidly gained popularity and complement traditional candidate gene studies that are
based on measurement and analysis of only a single SNP or set of SNPs within a single
gene. Identification of disease susceptibility genes using the genome-wide association
approach has proven remarkably successful, with novel genes already reported for
complex traits such as cardiovascular diseases70-71 and diabetes.72-73 These studies have
employed either single- or multistage designs to generate evidence for association in an
initial original sample and have then replicated these associations in other populations.
An important lesson learned from the GWAS scans of diabetes and cardiovascular
disease is that the associations detected have tended to be in novel genes rather than in
previously studied candidate genes.
It is possible that approaches such as genome-wide association
analysis may identify single SNPs that will turn out to be associated with both SCZ and
BMD or may even reveal different SNPs in the same gene to be associated with each
disorder. Other studies have explored the genetic underpinnings for disorders
characterized by a mix of mood and psychotic features, such as schizoaffective
disorder.73 The pathological processes in schizoaffective disorder are thought to be
correlated with those in SCZ and BMD, although some investigators have questioned the
validity of the independent diagnostic entity of schizoaffective disorder.74 It thus remains
to be seen whether susceptibility genes for schizoaffective disorder will turn out to be, at
least in part, involved in the shared genetic liability of SCZ and BMD.
Common Endophenotypes for SCZ and BMD
According to Gottesman and Gould75, endophenotypes are
neurophysiological, biochemical, endocrinological, neuroanatomical, cognitive, or
neuropsychological components associated with the target disorder. From a genetic
perspective, endophenotype can be very attractive targets for study if they are easily and
reliably measured, co-aggregate with the target disorder within families, and are also
present in unaffected relatives. A desirable endophenotype is also one that is more
proximal to a causative gene than the end-stage disease state and thus may be more
amenable to genetic study than the downstream disease.
Many candidate endophenotypes in SCZ and BMD are neurophysiological
markers. Other endophenotype that should be explored extensively include drug response
and metabolism, RNA expression, and protein levels.76 Studies of other neurocognitive
functions related to information processing also reveal the biological resemblances of
SCZ and BMD. For instance, impaired performance in span of apprehension has been
shown in both SCZ and BMD.77 Other abnormalities in information processing associated
with these 2 disorders include P300-evoked response latency78 and amplitude79, P50
auditory-evoked response suppression80-81, prepulse inhibition82, facial scan path
patterns83 and a mismatch negativity paradigm.84 Additionally, other cognitive function
impairments, such as executive deficits, can be demonstrated in psychotic and bipolar
disorder.85 These biomarkers related to neurocognitive functions may hence serve as
common endophenotype upstream to pathological pathways to SCZ and BMD.
If an endophenotype is influenced more directly by genetic factors, one
may expect to observe a higher heritability of an endophenotype compared with its endpoint disease (although a high heritability may not necessarily result from a smaller
number of genes involved in the pathological mechanism). Take smooth pursuit eye
movement (SPEM) as an example. SPEM refers to the movement of the eyes as they
track a slowly moving target, a process that is initiated by visual processing of motion
signals (i.e., extra-retinal motion). One of the major SPEM sub measurements, predictive
pursuit gain, is highly heritable (heritability estimate = 0.90)86, indicating that this trait is
under substantial genetic control. Additionally, both schizophrenic patients and their
unaffected relatives are more likely than healthy individuals to have deficits in SPEM,
suggesting that this trait co-segregates with SCZ and that deficits in SPEM are not
secondary sequelae occurring as a result of SCZ. Moreover, individuals affected with
BMD and their relatives are also more likely to have deficits in SPEM compared with
healthy individuals.87 Genetic analysis of SPEM-related phenotypes has provided further
insights into shared genetic influences that might cut across different psychiatric
diagnoses, including SCZ and BMD. For example, 2 studies have reported evidence for
linkage of SPEM phenotype to 6p23-21, suggesting that this chromosomal region may
harbor one or more genes influencing variation in SPEM.88-89 Interestingly, the same
region also harbors 2 genes previous associated with risk of schizophrenia, ATXN1
(SCA1) and NOTCH4.90 Other candidate genes associated with SPEM include dopamine
D3 receptor gene (DRD3)91, DISC192 and COMT.92 All these genes have also been
hypothesized to play a role in the pathogenesis of SCZ and BMD. Taken together, these
findings suggest that the study of common endophenotypes for SCZ and BMD, such as
SPEM, may reveal insights into alleged etiologic factors linking these two disorders.
Studying common endophenotypes may circumvent the limitation of
hierarchical diagnostic system posed on SCZ and BMD. Meanwhile, the
conceptualization of endophynotypes does not contradict the putative hierarchical
pathological relationship between SCZ and BMD. Furthermore, endophenotypes can
allow the investigator to examine the genotype-phenotype relationship in the same
population. Conventional studies focusing on SCZ and BMD in different populations
separately may produce findings that cannot be transferred to each other. Therefore,
deciphering the genetics of common endophenotypes may serve as an alternative and
effective approach to untangling the mechanism of shared genetic liability for these 2
disorders.
The success of endophenotype-based approaches hinges on the assumption
that endophynotypes are modulated by less complex genetic factors than the disease
syndrome itself. Hence, the identification of genetic variants that yield a larger effect on
endophynotypes than the end-point disease will benefit from such an approach. Goldman
et al.94 discovered a number of loci with a greater impact on endophynotypes compared
with related psychiatric disorders, such as BMD and alcoholism. However, one recent
study compared the effects of genetic variants on several endophenotypes and end-point
diseases using the meta-analysis technique and did not produce supportive evidence for
this assumption. The investigators examined 7 different endophenotypes, such as
“circadian rhythm” and prefrontal cognitive function, etc., as the endophynotypes for BP,
and “spatial and verbal working memory” and “ventricular enlargement,” etc., as
endophynotypes for SCZ. Their findings suggest that genetic contributions of the COMT
gene Val/Met polymorphism to endophenotypes were not significantly different from
those effects on SCZ or BMD.95 Therefore, one needs to carefully evaluate the locusspecific genetic effect size of the endophenotype in order to unravel the joint genetic
determinants for SCZ and BMD. Alternatively, investigators can use an endophenotype
to select a more clinically homogeneous subgroup of subjects for genetic studies. SCZ
and BMD characterized by a shared endophenotypic feature may be regarded as subtypes
of SCZ and BMD, respectively. Such an endophenotype-based approach may not only
overcome the problem of genetic heterogeneity in each individual disorder but also
enhance clinical resemblances for these 2 disorders and hence help identify the shared
genetic variant of a possibly larger effect. This approach may allow investigators to avoid
the concern that an endophenotype is not modulated by less complex genetic factors than
those associated with the risk of SCZ or BMD.
Conclusion
To summarize, the conventional nosological distinction between SCZ
and BMD has been challenged by research showing a phenomenological and biological
overlap of these two disorders. Genetic research suggesting that common genes may be
involved in both SCZ and BMD has lent additional support for the presence of shared
etiological pathways between these two disorders, although specific genes associated
with SCZ and BMD jointly have yet to be identified. Just as the long-standing “Kraepelin
dichotomy” has become subject to re-evaluation, the diagnostic systems for other
disorders cantered on psychotic symptoms, such as schizoaffective disorder, may also
need to be re-examined.
The hierarchical diagnostic system for SCZ and BMD precludes the usual
approaches for assessing their being associated with each other because the two
diagnoses usually cannot be assigned to the same individual. However, assessment of
familial co-aggregation may provide very useful insights into whether these two disorders
share common etiologies. Although previous evidence has suggested a number of
susceptibility genes shared by SCZ and BMD, most of these studies have focused on one
disorder at a time in independent populations. Alternatively, mapping genes for
schizoaffective disorder, which shares symptoms related to both SCZ and BMD, may
help unravel shared genetic mechanisms for these two disorders. Finally, identifying the
genes modulating common endophenotypes, such as SPEM, provided that they are
influenced more directly by genetic factors, may unveil the shared genetic pathways for
SCZ and BMD.
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