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Review
Neuroimaging Intermediate Phenotypes of
Executive Control Dysfunction in Schizophrenia
Grant Sutcliffe, Anais Harneit, Heike Tost, and Andreas Meyer-Lindenberg
ABSTRACT
Genetic risk for schizophrenia is associated with impairments in the initiation and performance of executive control of
cognition and action. The nature of these impairments and of the neural dysfunction that underlies them has been
extensively investigated using experimental psychology and neuroimaging methods. In this article, we review
schizophrenia-associated functional connectivity and activation abnormalities found in subjects performing
experimental tasks that engage different aspects of executive function, such as working memory, cognitive control,
and response inhibition. We focus on heritable traits associated with schizophrenia risk (intermediate phenotypes or
endophenotypes) that have been revealed using imaging genetics approaches. These data suggest that genetic risk
for schizophrenia is associated with dysfunction in systems supporting the initiation and application of executive
control in neural circuits involving the anterior cingulate and dorsolateral prefrontal cortex. This article discusses
current findings and limitations and their potential relevance to symptoms and disease pathogenesis.
Keywords: Cognitive control, Endophenotypes, Executive function, fMRI, n-back, Review
http://dx.doi.org/10.1016/j.bpsc.2016.03.002
Schizophrenia is a severe mental illness whose pathophysi-
ology involves systems-level dysfunction, likely as a conse-
quence of brain maturational abnormalities. Schizophrenia is
associated with reduced cognitive ability in a wide range of
domains, and marked impairment is found in a cluster of
abilities that can be grouped together under the umbrella
term executive function, such as working memory (WM),
response inhibition, and the organized production of
extended sequences of behavior. Below-normal performance
in tasks that involve these abilities has been repeatedly found
in schizophrenia patients, an effect that is detectable from
thetimeofthefirst psychotic episode but is usually more
pronounced in chronic patients (1). Milder impairments also
exist before the onset of psychotic symptoms and are also
found in close relatives and subjects carrying risk alleles,
indicating a genetic basis (1–3). As executive function
involves the ability to appropriately engage and manage
multiple cognitive abilities, executive control dysfunction
has been proposed as a parsimonious and plausible impair-
ment contributing to the wide range of cognitive dysfunction
found in schizophrenia (4–6). The hypothesis of a central role
for executive dysfunction is further supported by findings that
schizophrenia patients display gray matter reductions (7)and
metabolic abnormalities (8) in prefrontal cortical areas that
support executive control, in addition to a clustering of
abnormalities in temporal brain regions. Clinically, executive
functions are of central interest since they are important for
independent living and social function (9) and are correlated
with patient functional outcomes (1,10).
The application of modern imaging and genetics techniques
has begun to uncover a range of functional abnormalities that
accompany genetic risk for schizophrenia (11). A brief sum-
mary of findings will be presented here, with a focus on
disease-related heritable traits (intermediate phenotypes)
based on neuroimaging tests of executive function.
NEURAL ANATOMY OF EXECUTIVE FUNCTION
The term executive function can have different meanings
depending on author and research context, so it is helpful to
provide a working definition for the purposes of this review.
Executive function is related to similar terms such as executive
control or cognitive control, and while the terms are some-
times considered to be synonymous (9), in practice cognitive
control most often refers specifically to the context-dependent
shifting of attention or behavioral set and the inhibition of
prepotent responses, while executive function refers to a
broader set of abilities including forms of creativity and
problem solving (9). We use executive function and executive
control interchangeably to mean the ability to engage top-
down control of perception and action to optimize behavior in
the service of achieving goals, using a process analogous to
multidomain attention to send bias signals to perceptual and
motor systems to maintain task representations, enhance or
maintain perceptions of relevant stimuli, activate context-
appropriate stimulus-response correspondences, and inhibit
inappropriate prepotent responses (12,13). This includes those
functions commonly engaged by tests of cognitive control and
218 &2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.
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also WM and attention control functions. These abilities
activate and require a highly overlapping group of cortical
regions, centered around the anterior cingulate cortex (ACC),
dorsolateral prefrontal cortex (DLPFC), and posterior parietal
cortex (14,15), and engage a set of overlapping and interde-
pendent cognitive functions (9).
Executive function is heavily dependent on the PFC and,
broadly stated, involves a division of labor between the ACC
and lateral PFC, which, respectively, serve implementation and
initiation functions. During cognitive control tasks, the ACC
selectively activates in response to the appearance of con-
flicting behavioral cues and is believed to be integral to the
function of detecting sources of potential conflict and error
(16) and engaging additional control to avoid error.
During the application of control, the ACC selectively
couples with the anatomically adjacent DLPFC (17). The
DLPFC appears to be particularly important for the direction
of modulation to sensory and motor circuits, due to its
structural connectivity with sensory and motor regions and
consistent activation in tasks involving the internal and
external direction of attention (12). In the context of cognitive
control, the right ventrolateral PFC has a particular importance
in response inhibition, the withholding of a frequently per-
formed prepotent response due to additional contextual
information (18).
Functional connectivity analyses indicate that both ACC
and DLPFC are parts of larger functional networks with related
functions. The ACC appears to be part of a network including
the ventrolateral PFC, which is involved in the selection and
maintenance of behavioral sets, while the DLPFC-associated
frontoparietal network supports the direction of top-down
modulation (19). Cortical executive control networks are also
connected with and dependent on subcortical structures,
particularly the dorsomedial striatum and the mediodorsal
nucleus of the thalamus (20,21).
Abnormalities in these neural systems will be the focus of
the following discussion of the neurogenetic imaging pheno-
types related to schizophrenia.
GENETIC PREDISPOSITION AND INTERMEDIATE
PHENOTYPES
Schizophrenia is highly heritable, with genetic factors being
estimated to account for up to 80% of the disease risk (22). In
most cases, genetic risk is believed to result from alterations in
an extended developmental cascade due to interacting down-
stream molecular, cellular, and system level consequences of
multiple common risk variants, each of which confers only
small increments in risk.
As a method of discovering the proximal biological effects
of genetic risk factors, the identification of intermediate
phenotypes is a popular strategy for investigating the patho-
physiology of psychiatric conditions. Intermediate phenotypes
are heritable biological traits that confer risk for a disease and
are believed to be causally closer to risk gene effects than the
disease itself (23,24). These have been well established for
common nonpsychiatric illnesses and have in several cases
been demonstrated to have relatively strong associations with
specific genes (24). One example is the use of high plasma
lipid levels as an intermediate phenotype of coronary heart
disease, which has led to the identification of the protease
PCSK9 as a novel therapeutic target in the treatment for
hypercholesterolemia (25,26).
Although the terms are essentially interchangeable in
practice, many neuroimaging genetics researchers prefer the
term intermediate phenotype over endophenotype, as endo-
phenotype was originally meant to imply an unobservable
internal feature, which may not necessarily be the case, for
example, in the case of a neuropsychological trait. The use of
intermediate also emphasizes the concept of biological inter-
mediacy in pathogenesis (23).
Previous analysis has concluded that a neuroimaging
intermediate phenotype should fulfill several requirements to
be useful for the dissection of the genetic risk architecture of
mental illness (23,27,28). Accordingly, an intermediate pheno-
type should be 1) quantitative in nature; 2) heritable; 3) reliably
measurable; 4) associated with the illness in the general
population; 5) linked to genetic risk for the illness; and 6) state
independent (i.e., traceable in carriers of genetic risk variants
whether or not the illness is manifest). However, finding an
intermediate phenotype that satisfies all of the criteria is very
demanding in practice and rarely accomplished for measures
derived from functional neuroimaging (29).
Imaging genetics is the application of the intermediate
phenotype approach with structural or functional outcome
measures derived from in vivo neuroimaging techniques. In
addition to earlier measures of functional activation magni-
tude, the comparatively recent popularization of functional
connectivity analysis techniques has further enhanced the
usefulness of the neuroimaging approach (11,28). Functional
connectivity analysis is in theory particularly advantageous in
the investigation of multimodal higher association areas, such
as those involved in executive control, which are involved in
multiple cognitive processes and may plausibly change their
connectivity profile depending on the specifics of the task at
hand (13), which functional connectivity analysis can help
uncover (19).
The neuroimaging investigation of unaffected first-degree
relatives of patients, ideally twins or siblings, has been a
particularly important search strategy for intermediate pheno-
types. Unaffected relatives share an enriched set of genetic
risk variants but do not manifest clinical symptoms, which
attenuates the effects of confounding factors, such as med-
ication, that interfere with functional neuroimaging readouts
and complicate the interpretation of patient data. Imaging
genetics has been used to explore functional effects of risk
genes, such as ZNF804A (30) and CACNA1C (31), which have
been discovered with genome-wide association analysis (32),
as well as to test biologically driven hypotheses regarding
genes that have a known function, such as COMT, which is
involved in dopamine metabolism and therefore influences
cortical dopamine levels (33).
NEURAL DYSFUNCTION OF EXECUTIVE CONTROL
SYSTEMS
Review Method
Candidate studies were identified using PubMed and the
bibliographies of relevant reviews and meta-analyses. Studies
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were selected for further analysis if they reported imaging
analysis of subjects performing experimental tests of execu-
tive function and if the subjects included either close relatives
of schizophrenia patients or populations who were tested for
genetic variants that the authors identified as potentially
conferring risk for schizophrenia.
One hundred thirty-one articles that fulfilled these criteria
were identified. Full search details and summaries of identified
studies are available in Supplement 1. Replicated candidate
intermediate phenotypes, which have been reported in
patients and at least two heritable risk populations, including
one or more populations of first-degree relatives, are displayed
in Table 1 and also described in the following text.
Cognitive Control/Response Inhibition
Experimental tasks of cognitive control emphasize the
dynamic detection of conflicting behavioral cues that neces-
sitate additional focus of attention and the inhibition of
incorrect responses (16). Response inhibition tasks test
related abilities but with a greater emphasis on withholding
prepotent (i.e., habitual or innate) responses (18). An example
paradigm that requires all of these abilities, the go/no-go
flanker task, is illustrated in Figure 1A.
The literature search returned 19 studies of context proc-
essing and/or response inhibition, of which 9 compared
differences between relatives and control subjects and 10
were studies of specific genetic variants (Supplement 1).
Activation and connectivity abnormalities were reported in
and between diverse components of the cognitive control
network.
In a series of studies using the same variable attentional
control paradigm, associations were found between specific
risk alleles and altered activation in the cingulate (34,35) and
anterior, superior, and dorsolateral PFC (36–39). In studies
comparing relatives with control subjects, PFC and parietal
activation differences have been found during performance of
the Stroop task (40) and diffuse increases of activation have
been found during performance of a variant of the Continuous
Performance Task (41).
Of replicated results, during performance of the go/no-go
flanker task, Sambataro et al. (17) found that patients and
siblings display lower performance, decreased ACC activation,
and increased connectivity of the ACC with the left DLPFC
during no-go response inhibition trials. The increased ACC–
DLPFC connectivity finding was subsequently also found in
ZNF804A risk allele carriers in the general population (30). The
increased ACC–DLPFC connectivity in this case does not have
an unambiguous functional interpretation but has been
hypothesized to reflect a compensatory response to regional
processing inefficiency (17). The increased connectivity result
was found in an analysis that corrected for performance
differences by comparing correct responses only, suggesting
that greater functional coupling may be necessary to achieve
successful inhibition.
In two similar response inhibition paradigms employed by a
group based at the University Medical Center Utrecht, reduced
activity in the striatum has been reported in patients, siblings
(42,43), and sibling carriers of risk alleles of DRD2 (44). The
test-retest reliability of this paradigm has also been measured
(45). The reduced activation and accompanying performance
impairment here was a function of anticipation, in that striatal
activation increased with likelihood of presentation of the
withhold signal in control subjects but not in patients or
siblings, which was interpreted as indicating an impairment
in proactive cognitive control, supporting the hypothesis that
schizophrenia involves a specific impairment in this function
(5). The same group has also found similar striatal hypoacti-
vation in siblings performing an antisaccade task (46), another
test of response inhibition.
Working Memory
Working memory is a core executive function, involving the
temporary conscious storage and manipulation of information.
This requires top-down attention to the neural representations
of the information to be stored and manipulated and engages
the frontoparietal network in a load-dependent manner (14). A
popular experimental paradigm that engages WM, the n-back
task, is illustrated in Figure 2A.
Eighty-eight WM papers were found in the literature search,
of which 70 tested the effect of genetic risk variants. Sixty-six
studies used some variant of the n-back task, including 43 that
used the diamond numerical-spatial variant depicted in
Figure 2A. Studies reported abnormalities in and between
various components of the executive control network. The
2016 meta-analysis of WM studies of relatives by Zhang et al.
(47), which integrated much of this literature, reported both
increases and decreases mostly in right lateral PFC, in
addition to the thalamus and left inferior parietal lobule.
Many WM imaging studies increase statistical power by
preselecting lateral PFC as a region of interest, as this area has
repeatedly been demonstrated to be sensitive to genetic and
illness-state factors. Schizophrenia patients show a complex
pattern of abnormal frontal activation during the n-back task,
which appears to reflect inefficient function. The DLPFC of
patients is more highly activated than that of control subjects
at equivalent performance levels (48–53), and this may be
accompanied by a compensatory additional activation of
neighboring regions such as the ventrolateral PFC (54). The
WM capacity of patients tends to be exceeded at lower levels
of load than that that of control subjects, and this failure of WM
at high loads is accompanied by reduced DLPFC activation in
comparison with control subjects when performance is not
matched between groups (49). A similar inefficiency pattern
has also been found in healthy relatives of patients (50–52,55–
58). Associations between this phenotype and specific genes
and measures of risk are extensive (38,53,59–83)(Table 1).
Both heritability (84) and reliability (85) estimates have been
made for this phenotype. Similar findings of prefrontal ineffi-
ciency have been found in subjects performing the Sternberg
working memory task, including patients (86,87), relatives
(88,89), and subjects with specific genetic variants (86,90–92).
Another WM intermediate connectivity phenotype is
reduced PFC–parietal coupling, which appears to reflect
impaired function. This has been found in patients using
functional (54,93,94) and effective connectivity (95,96) meth-
ods. Recently, decreased connectivity of this circuit has also
been identified in unaffected relatives (50), providing evidence
for an association between this coupling phenotype and
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Table 1. Summary of Current Major Findings of Potential Neuroimaging Intermediate Phenotypes in Terms of the Criteria Listed in This Article
Task Phenotype Heritability Reliability Patients
a
Relatives
Genes
Positive Association
With Risk Variant
Negative Finding or Opposite
Correlation With Phenotype
b
Partial Support
c
Go/No-Go Flanker ↑ACC-DLPFC (17)
V
(17)
V
ZNF804A (30)
IV
Response Inhibition ↓Dorsal striatum (45) (42)
II
(43)
II
(42)
II
(43)
II
DRD2 (44)
I
N-back (All Variants) DLPFC inefficiency (84) (85) (48)
I
(49)
I
(50)
VI
(51)
II
(52)
I
(53)
I
(50)
VI
(51)
II
(55)
I1I
(52)
I
(56)
I
(57)
I
(58)
II
5-HT2AR (38)
III
CACNA1C (31)
II
COMT (153)
III
(154)
IV
AKT1 (59)
III1II
CHRNA5 (73)
V
GPR85 (155)
II
BclI (60)
II
COMT (67)
III
(111)
II, HF
GRIN2B (156)
III
CACNA1C (61)
V
CYP2D6 (146)
III, HF
NRG3 (120)
VII
CIT (62)
III
DAOA (64)
II
(147)
II, HF
SCN2A (125)
VI
CIT3DISC1 (62)
III
DRD2 (74)
V
(73)
V
(148)
II
(149)
I
CIT3NDEL1 (62)
III
DTNBP1 (67)
III
COMT (63)
I
(53)
I
(64)
II
(65)
II
(66)
I
GSK-3β(39)
III
COMT3BclI (60)
II
HTR2A (74)
V
(60)
II
(150)
I
COMT3DAOA (64)
II
PRODH (151)
III
COMT3DTNBP1 (67)
III
RELN (119)
V
COMT3GRM3 (66)
I
RGS4 (98)
II
COMT3RGS4 (68)
II
ZNF804A (101)
II
(50)
VI
(100)
III
COMT methylation (69)
II
Polygenic risk (152)
III
DAOA (70)
I
DAT (65)
II
DISC1 (71)
III
DRD2 (72)
II
DRD23CHRNA5 (73)
V
DRD23HTR2A (74)
V
DTNBP1 (75)
II
GAD1 (76)
III
GRM3 (77)
II
IL1B (78)
II
KCNH2 (79)
III
NKCC1 (80)
V
NRG1 (81)
II
(82)
III
NRG13ERBB4 (82)
III
NRG13ERBB4 3AKT1 (82)
III
RASD2 (83)
III
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Table 1. Continued
Task Phenotype Heritability Reliability Patients
a
Relatives
Genes
Positive Association
With Risk Variant
Negative Finding or Opposite
Correlation With Phenotype
b
Partial Support
c
Sternberg WM Task DLPFC
inefficiency
(86)
III
(87)
II
(88)
I
(89)
I
COMT (157)
I
COMT (158)
III
COMT3MTHFR (158)
III
COMT methylation (92)
III
CPLX2 (159)
IV
DISC1 (91)
V
miR-137 (86)
III
Polygenic risk (126)
IV
(90)
III
N-back (All Variants) ↑DLPFC-HC (160) (50)
VI
(99)
I
(50)
VI
CACNA1C (31)
II
COMT (66)
I
ZNF804A (100)
III
(101)
II
(102)
III
(103)
II
(50)
VI
COMT3GRM3 (66)
I
RGS4 (98)
II
Working Memory ↓PFC-PC (93)
I
(54)
I
(94)
I
(95)
II
(96)
II
(50)
VI
COMT (97)
I
ZNF804A (50)
VI
COMT3GRM3 (66)
I
RGS4 (98)
II
N-back (All Variants) ↑MPFC (52)
I
(105)
I
(106)
II
(107)
II
(108)
I
(109)
III
(110)
III
(111)
II
(52)
I
(110)
III
(112)
I
COMT (111)
II
(60)
II
(All HF)
BclI (60)
II
COMT (154)
IV
COMT3RGS4 (68)
II
COMT methylation (69)
II
CYP2D6 (146)
III
DAOA (147)
II
DRD2 (148)
II
GRM3 (77)
II
IL1B (78)
II
(149)
I
PRODH (151)
III
RGS4 (98)
II
ZNF804A (101)
II
(50)
VI
Sample sizes for each study: I 5below 50; II 5between 50 and 100; III 5between 100 and 200; IV 5between 200 and 300; V 5between 300 and 400; VI 5between 400 and 500; VII 5
above 500.
Hypothesis-free negative finding indicates that the phenotype was not detected after correcting for multiple comparisons across the whole brain, which may have limited statistical
sensitivity.
ACC, anterior cingulate cortex; DLPFC, dorsolateral prefrontal cortex; HC, hippocampus; HF, hypothesis-free negative finding; MPFC, medial prefrontal cortex; PC, parietal cortex; WM,
working memory.
a
Lists of patient studies are provided as examples and are not an exhaustive list.
b
Negative findings should be interpreted with caution, as the study may have been underpowered to detect the phenotype, and the negative finding may be in respect to a genetic variant
different from a variant of the same gene that was positively associated with the phenotype elsewhere. This column includes studies in which no significant main effect of a single gene was
found, even if significant interaction effects were found in the same study.
c
For example, nonlinear or genotype 3diagnosis effects only.
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genetic risk for the disorder. Reported specific genetic asso-
ciations with this phenotype are candidate risk variants of
COMT (97), RGS4 (98), and COMT 3GRM3 epistasis (66).
An intriguing WM functional abnormality is the failure to
decrease connectivity between the right DLPFC and left
hippocampus during n-back performance. This has been
found in patients (50,99), relatives (50), and carriers of risk
alleles of CACNA1C (31) and has been linked to ZNF804A in
five separate studies (50,100–103)(Figure 2C). As genome-
wide association studies have established genetic variants in
ZNF804A as schizophrenia risk alleles (32), this is a strong link
between genetic risk and neural function.
The increased DLPFC–hippocampus connectivity finding is
conceptually similar to the emerging hypothesis that the
functional abnormalities of schizophrenia involve context-
inappropriate hyperfunction as much as hypofunction. A key
Figure 1. (A) Schematic illustration
of the go/no-go flanker cognitive con-
trol task for functional magnetic reso-
nance imaging with four task
conditions. In each trial, a central arrow
with four flanking stimuli is presented
and participants are instructed to press
the button corresponding to the direc-
tion of the central arrow. In the con-
gruent condition, the flankers point in
the direction of the target arrow. In the
incongruent condition, the flankers
point in the direction opposite to that
of the target arrow. In the go condition,
flanking stimuli consist of squares and
signal the demand for a response, while
in the no-go condition, flanking Xs
indicate that the response should be
inhibited. (B) Whole-brain significant
activations increase in the anterior cingulate cortex, inferior frontal gyrus, dorsolateral prefrontal cortex, and posterior parietal cortex in the incongruent 1
no-go relative to the congruent 1go conditions in a sample of 100 healthy control subjects (p
family-wise error
,.05). Activation maps are displayed on two
sagittal sections of a structural magnetic resonance imaging template. Color bar represents tvalues.
Congruent
Nogo
Incongruent
Go
AB
x=0 x=39
Figure 2. (A) Schematic illustration
of a numerical-spatial variant of the n-
back working memory task for func-
tional magnetic resonance imaging. A
series of numbers are displayed in a
random order at set locations with
alternating 0-back and 2-back epo-
chs. In the working memory condition
(2-back), participants encode a cur-
rently seen number, simultaneously
recall the number seen two presenta-
tions earlier, and press the button
corresponding to the position of the
number two presentations before. In
the control condition (0-back), sub-
jects press the button corresponding
to the position of the currently seen
number. (B) Whole-brain significant
increase of frontoparietal activation
in the 2-back condition relative to
the 0-back condition (p
family-wise error
,.05) in a sample of 100 healthy
control subjects. Activation maps are
displayed on a sagittal, coronal, and
transverse section of a structural
magnetic resonance imaging tem-
plate. Color bar represents tvalues.
(C) A genome-wide supported schizo-
phrenia risk variant in ZNF804A
impacts prefrontal–hippocampal func-
tional coupling during n-back working
memory performance. Left figure:
illustration of the hippocampal voxels
in which ZNF804A genotype predicts increased functional connectivity with the right dorsolateral prefrontal cortex. Right figure: bar plot illustrating the
dorsolateral prefrontal cortex–hippocampus connectivity estimates for the three genotype groups. [Reprinted with permission from Meyer-Lindenberg (29)
and Esslinger et al. (100)].
A1
23
4
1
23
4
1
23
4
1
23
4
0back
2back
Time
B
x=42 y=38 z=27
C
ZNF804A genotype
x=-38 y=-20
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concept here is the failure to deactivate or decouple non-task-
related areas of the brain during task performance, particularly
areas of the default mode network, a group of mainly midline
and temporal cortical areas that are suppressed during the
performance of tasks that require external attention and
activated during self-referential mental activities (104).
Reduced WM-induced deactivation of the medial prefrontal
cortex, a key default mode network area, has been found in
patients (52,105–111), first-degree relatives (52,110,112), and
carriers of the valine/valine COMT genotype (111).
Verbal Fluency
Verbal fluency tasks test cognitive flexibility by challenging
subjects to generate words in response to a cue, such as a
letter, semantic category, or incomplete sentence (9). These
paradigms require selective attention and inhibition to the
areas of memory concerned and engage prefrontal areas,
particularly the left inferior frontal gyrus (9,113,114). The
literature search found 27 articles in this category, of which
12 used phonetic verbal fluency tasks, 6 used semantic verbal
fluency tasks, and 9 used the Hayling sentence completion
task. A majority of articles within each category reported
different analyses of a common or overlapping subject group
(Supplement 1). The results of these studies are heteroge-
neous and largely unreplicated, with a couple of exceptions.
During tests of semantic verbal fluency, increased activation in
the right middle temporal cortex has been found in patients
(113) and associated with risk alleles of DAOA (114) and
DTNBP1 (115). Increased activation in the left inferior frontal
gyrus has been associated with COMT (116) and CACNA1C
(117) during semantic verbal fluency performance and asso-
ciated with polygenic risk (118) during the Hayling task.
DISCUSSION
The imaging genetics approach is a promising method for
investigating a disorder that is particularly difficult to research,
and current results are encouraging. However, certain caveats
should be made. Ideal criteria for intermediate phenotypes
have generally not been fulfilled for the candidates described,
and heritability and reliability estimates, in particular, are often
lacking (Table 1)(28). A great number of exploratory studies
have been made that use inconsistent task variants, subject
selection criteria, and analysis methods, and often report
different and sometimes contradictory findings (Supplement 2),
which are difficult to integrate. The reported effects of risk
gene variants are particularly varied, although between-variant
differences in effect are not necessarily a sign of unreliability,
as well-powered studies of specific risk variants have failed to
find the expected typical schizophrenia intermediate pheno-
type, indicating that effects are likely to be heterogeneous
(50,119,120). The inconsistent directionality of differences
found within the same region or circuit is potentially partly
due to methodological issues, particularly in regard to the
performance matching of groups or the methods used for
neuroimaging data preprocessing, especially in the case of
connectivity studies. Sample sizes have often been compara-
tively low, which constrains power and the reliability of
findings, although commonly used state of the art statistical
methods are effective at avoiding false-positives (121). Future
research could be made more powerful, reproducible, and
resource-efficient by the use of larger datasets and stand-
ardized paradigms and methods across centers. Recommen-
dations of research practices and clinically relevant paradigms
have been made by expert groups (122–124), and the last few
years have seen a number of high-powered imaging genetics
studies with hundreds or even thousands of subjects
(30,38,62,73,80,119,120,125,126). Much of the problem of
small sample sizes can be attributed to the expense of
acquiring imaging data, which limits the number of subjects
that individual groups can afford to use. In recent years,
multisite consortia, such as the ENIGMA and IMAGEMEND
networks (127,128), have been formed to tackle this problem,
and although accumulating large sample sizes is still problem-
atic due to inconsistencies in study designs between sites,
large initiatives with harmonized task protocols are underway.
Table 1 summarizes the evidence for the intermediate
connectivity phenotypes described here. Overall, evidence
indicates that genetic risk for schizophrenia is associated with
dysfunction of neural mechanisms of executive control of
behavior and cognition, with functional imaging of patients,
relatives, and carriers of risk alleles showing comparable
abnormalities of activation and functional connectivity during
experimental tests of executive function. The association of
genetic risk with dysfunction in different components of
control suggests that dysfunction of executive control sys-
tems may be a convergence point for the pathogenic effect
trajectories of multiple genetic risk factors.
A few tentative observations can be made about the
patterns of dysfunction reported in Table 1. Phenotypes
involve more often increased rather than decreased activity
and connectivity, suggesting inefficiency of task-related sys-
tems, compensation by or interference from secondary or non-
task-related systems, and a possible causal link between the
two. Meta-analyses of imaging studies of relatives also show a
mix of increases and decreases of activity during executive
function tasks (47,129,130).
Ideally, intermediate phenotypes should have explanatory
value in regard to disease etiology. In this respect, heritable
executive control dysfunction has a clear relevance to the
cognitive impairments associated with schizophrenia. How-
ever, as putative intermediate states in disease pathogenesis,
intermediate phenotypes should ideally also have explanatory
value in regard to disease symptoms in general and not just a
limited set of test measures. Here, the following observations
are potentially relevant.
First, one of the negative symptoms of schizophrenia is
avolition, which can be framed as the reduced initiation of
goal-directed behavior (131). Executive control is a form of
goal-directed behavior, and the neural control systems sup-
porting it potentially play a role in the initiation of action plans
as well as supporting their execution (132), with lesion damage
of the ACC and DLPFC being associated with avolition and
apathy (133). Dysfunction of executive control systems is
therefore plausibly related to avolition-associated negative
symptoms. Supporting this, negative symptoms are correlated
with cognitive symptoms to a greater extent than with positive
symptoms (134,135). A caveat here is that it is uncertain
to what extent the negative symptom correlation is with
executive function rather than general cognitive ability (135).
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This, in turn, relates back to the hypothesis that generalized
cognitive impairment may result from a specific impairment in
executive control (4–6).
Second, as Cole et al.(136) argue, the extensive brain-wide
connectivity of executive control systems suggests that they
have the potentially clinically relevant function of regulating
multiple hierarchically lower brain systems. Studies indicate
that control systems connect to and regulate the activity of
limbic and task-irrelevant structures, such as the default mode
network (137) and the amygdala (138), when excessive activity
of these is detrimental to goal attainment. Control dysfunction
could contribute to the pathology of mental health disorders
by disinhibiting or failing to regulate excessive activity of other
neural systems, such as the amygdala in the case of anxiety
disorders (136).
In the case of schizophrenia, this has potential relevance to
hypotheses regarding psychotic symptoms that propose that
psychosis develops as a result of dysfunction of striatal
dopaminergic systems that mediate responses to salient
environmental events. According to these, psychosis develops
as a consequence of the incorrect attribution of salience to
environmental events or internal perceptions due to dysfunc-
tion of subcortical dopaminergic systems that signal the
occurrence of salient events. These spurious event-salience
associations are hypothesized to trigger erroneous cognitive
reasoning processes, which result in delusional beliefs and
perceptions (139,140). With respect to executive control, there
is a potential link between PFC dysfunction and dysregulation
of striatal dopamine (141), and it is also potentially relevant
that executive control selectively filters and suppresses
bottom-up attention responses to salient events and stimuli
during task performance (142–144). Impairment of this sup-
pression could plausibly result in a greater tendency to direct
attention to aberrantly salient phenomena, with a correspond-
ing facilitating effect on the resulting pathological cognitive
processes. In this regard, the failure to deactivate the default
mode network and decouple non-task-related DLPFC con-
nectivity during the n-back task suggests that heritable risk for
schizophrenia is associated with dysfunctional executive
regulation of neural activity and cognitive focus and a greater
tendency for action to be controlled by hierarchically lower or
bottom-up systems. Genetic risk for schizophrenia is associ-
ated with impaired ability to inhibit prepotent responses to
stimuli in antisaccade, prepulse inhibition, and response
inhibition tasks (2,145), and meta-analyses indicate that
cortical activation dysfunction in relatives displays a notable
right lateralization to areas overlapping with or closely con-
nected to the right-lateralized frontoparietal network, which
supports bottom-up reorienting of cognitive focus to unpre-
dicted behaviorally relevant events (47,123,129,130,142).
CONCLUSIONS
Overall, task-based imaging genetics is a useful strategy for
providing insight into the genetic risk architecture of what is
likely to be a core dysfunction in schizophrenia. The combi-
nation of molecular genetics and network-based analysis
methods is a relatively novel methodological extension of
established imaging genetics approaches that has the
potential to help delineate the neurogenetic architecture of
more complex network dynamics in the future.
ACKNOWLEDGMENTS AND DISCLOSURES
AM-L acknowledges grant support by the German Federal Ministry of
Education and Research (IntegraMent: Grant No. 01ZX1314G; NGFNplus
MooDS: Grant No. 01GS08147) and the European Community’s Seventh
Framework Programme under the Grant Agreement Nos. 115300 (Project
EU-AIMS), 115008 (Project EU-NEWMEDS), 602805 (Project EU-AGGRES-
SOTYPE), and 602450 (Project EU-IMAGEMEND). HT acknowledges grant
support by the German Federal Ministry of Education and Research (Grant
No. 01GQ1102).
We thank Carolin Mößnang for assistance with the figures.
AM-L has received consultant fees from AstraZeneca, Elsevier, F.
Hoffmann-La Roche, Gerson Lehrman Group, Lundbeck, Outcome Europe
Sárl, Outcome Sciences, Roche Pharma, Servier International, and Thieme
Verlag and has received lecture fees including travel expenses from Abbott,
AstraZeneca, Aula Médica Congresos, BASF, Boehringer Ingelheim,
Groupo Ferrer International, Janssen-Cilag, Lilly Deutschland, LVR Klinikum
Düsseldorf, Otsuka Pharmaceuticals, and Servier Deutschland. The other
authors report no biomedical financial interests or potential conflicts of
interest.
ARTICLE INFORMATION
From the Department of Psychiatry and Psychotherapy, Central Institute of
Mental Health, Medical Faculty Mannheim, University of Heidelberg,
Mannheim, Germany.
Address correspondence to Grant Sutcliffe, M.Sc., University of
Heidelberg, Department of Psychiatry and Psychotherapy, Central Institute
of Mental Health, Medical Faculty Mannheim, J5, Mannheim 68159,
Germany; E-mail: grant.sutcliffe@zi-mannheim.de.
Received Oct 29, 2015; revised Mar 11, 2016; accepted Mar 14, 2016.
Supplementary material cited in this article is available online at http://
dx.doi.org/10.1016/j.bpsc.2016.03.002.
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