Neurological soft signs in first-episode schizophrenia: State and trait related
relationships to psychopathology, cognition and antipsychotic medication effects
Running title: Neurological soft signs in schizophrenia
Robin Emsley*,a, Bonginkosi Chilizaa, Laila Asmala, Sanja Kiliana, M. Riaan Oliviera,
Lebogang Phahladiraa, Akinsola Ojagbemib, Freda Schefflera, Jonathan Carrc, Martin Kiddd,
Paola Dazzane.
a Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch
University, Tygerberg Campus, Cape Town, South Africa
b Department of Psychiatry, University of Ibadan, Nigeria
c Division of Neurology, Faculty of Medicine and Health Sciences, Stellenbosch University,
Tygerberg Campus, Cape Town, South Africa
d Centre for Statistical Consultation, Stellenbosch University, South Africa
e Psychosis Studies Department, Institute of Psychiatry, Psychology and Neuroscience,
King’s College London, London, UK.
*To whom correspondence should be addressed: Department of Psychiatry, Faculty of
Medicine and Health Sciences, Stellenbosch University, PO Box 19063, Tygerberg Campus,
Cape Town 7505, South Africa; tel: +27 21 9389227; fax:+27 21 9389738; e-mail:
Word count:
Abstract: 245
Text body: 3146
1
Abstract
Background: Neurological soft signs (NSS) are proposed to represent both state- and trait-
related features of schizophrenia.
Method: We assessed the course of NSS with the Neurological Evaluation Scale (NES) over
12 months of standardised treatment in 126 patients with first-episode schizophrenia,
schizophreniform or schizoaffective disorder, and evaluated their state- and trait-related
associations with psychopathology, functionality, cognition and antipsychotic treatment. We
considered change scores from baseline to be state-related and endpoint scores to be trait-
related. Results: Significant effects for time were recorded for all NSS domains. For state-
related change-scores greater improvements in sensory integration were predicted by more
improvement in working memory (p=0.01); greater improvements in motor sequencing
scores were predicted by more improvement in working memory (p=0.005) and functionality
(p=0.005); and greater improvements in NES Total score were predicted by more
improvement in disorganised symptoms (p=0.02). There were more substantial associations
between trait-related endpoint scores than for state-related change scores. For endpoint
scores lower composite cognitive score predicted poorer sensory integration (p=0.001);
higher Parkinsonism score predicted poorer motor co-ordination (p=0.0001); lower
composite cognitive score (p=0.001) and higher Parkinsonism score (p=0.005) predicted
poorer motor sequencing; higher Parkinsonism score (p=0.0001) and disorganised
symptoms (p=0.04), and lower composite cognitive score (p=0.0007) predicted higher NES
total score.
Conclusions: NSS improved with treatment, but were weakly associated with improvements
in psychopathology. Studies investigating NSS as trait-markers should ensure that patients
have been optimally treated at the time of testing, and should take possible effects of
extrapyramidal symptoms into account.
Keywords: neurological; schizophrenia; psychosis; outcome; depot; flupenthixol
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1. Introduction
Neurological soft signs (NSS) are a well-established component of the symptom
expression of schizophrenia spectrum disorders (Chan et al., 2010). As such, they have
been proposed as an endophenotype for these conditions (Chan and Gottesman, 2008).
NSS are present at the time of the first psychotic episode (Dazzan and Murray, 2002), and
prior to first initiation of antipsychotic treatment (Gupta et al., 1995;Peralta et al., 2011). NSS
are not static over time, although findings are inconsistent. While several studies reported
that NSS remain stable, or worsen over the course of the illness (Madsen et al., 1999;Smith
et al., 1999;Chen et al., 2000;Chen et al., 2005) a recent meta-analysis reported that 14 of
17 longitudinal studies found reductions in NSS in parallel with symptom improvement
(Bachmann et al., 2014). NSS improvements were greater in patients achieving remission
(Bachmann et al., 2014), and worsened in patients not attaining remission (Prikryl et al.,
2012). However, even in patients achieving remission, some NSS persisted. This has led to
the proposal that NSS represent both state- and trait- related features of the illness
(Bachmann et al., 2014). Which NSS are state or trait markers is not clear (Cuesta et al.,
2012). Many previous studies are limited by methodological shortcomings including small
samples, chronic samples, varying degrees of antipsychotic exposure, different follow-up
durations and non-standardisation of treatments (Chan et al., 2015). Another critical
consideration is timing of baseline assessments (Bachmann et al., 2014). For assessing
state-related NSS, baseline assessments should be conducted during the acute psychosis,
before treatment. Similarly, trait-related NSS should be investigated after optimal treatment-
response.
We conducted a study addressing several of the methodological inconsistencies.
Firstly, we selected first-episode patients to avoid the effects of disease chronicity. Secondly,
by selecting treatment-naïve or minimally treated patients we minimised contaminating
effects of prior medication. This also allowed us to accurately document treatment-emergent
extrapyramidal symptoms (EPS) and their relationship to NSS. Thirdly, by treating patients
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with a single antipsychotic and according to a fixed protocol, we avoided differential effects
of various antipsychotics. Fourth, we used a low-dosing strategy to minimise medication
effects on NSS. Finally, using a depot antipsychotic formulation eliminated the confounding
effect of non-adherence which may be substantial, given the very high rates of non-
adherence reported in the early stages of illness (Coldham et al., 2002). Our aim was to
investigate the course of NSS over the first 12 months of standardised treatment and to
assess how both state- and trait-related NSS are related to other symptoms, functionality,
cognition, antipsychotic dose and emergent EPS.
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2. Methods
This longitudinal study assessed the outcome of patients with a first-episode of
schizophrenia or related disorder treated with the lowest effective dose of flupenthixol
decanoate according to a standard protocol over 12 months. Ethics approval was obtained
from the Human Research Ethics Committee of Stellenbosch University Faculty of Medicine
and Health Sciences.
2.1 Participants
Participants were recruited from hospitals and community clinics in Cape Town and
vicinity. Written, informed consent was obtained from participants. Inclusion criteria were:
men and women; aged 16-45 years; experiencing a first psychotic episode meeting
Diagnostic and Statistical Manual of Mental Diseases, Fourth Edition, Text Revisions (DSM-
IV TR) (American Psychiatric Association, 1994) criteria for schizophrenia, schizophreniform
or schizo-affective disorder. Exclusion criteria were: lifetime exposure >4 weeks
antipsychotic medication; previous treatment with a depot antipsychotic; mental retardation;
overt current substance abuse; unstable general medical condition; history of head injury or
epilepsy.
2.2 Treatment
Patients received oral flupenthixol 1-3mg/day for 7 days, followed by flupenthixol
decanoate injections 2-weekly for the study duration. Initiation dose was 10mg 2-weekly,
with 6-weekly increments of 10mg 2-weekly IMI permitted, to a maximum of 30mg 2-weekly
IMI. Additional oral flupenthixol was permitted at the discretion of the investigator, as was
lorazepam, anticholinergics, propranolol, antidepressants and medication for general
medical conditions. No benzodiazepines, propranolol or anticholinergics were permitted in
the 12 hours prior to assessments.
2.3 Assessments
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Assessments were conducted at baseline (prior to treatment), 6 and 12 months.
2.3.1 Neurological soft signs
NSS were assessed with the Neurological Evaluation Scale (NES) (Buchanan and
Heinrichs, 1989). Thirteen of 26 items are assigned to three ‘functionally meaningful’ sub-
scales reflecting dysfunction in sensory integration, motor coordination and motor
sequencing, and NES total score (Buchanan and Heinrichs, 1989;Sanders et al., 2000). NES
assessments were performed by three psychiatrists (BC, LA, LP) who underwent initial
training (Inter-rater reliability >.9) and participated in ongoing reliability assessments to
ensure stability of rating over time.
2.3.2 Clinical evaluations
Patients were assessed with the Structured Clinical Interview for DSM-IV (SCID)
(First et al., 1994). Psychopathology was assessed with the Positive and Negative
Syndrome Scale (PANSS) (Kay et al., 1987). We used factor-analysis derived symptom
domains for positive, negative and disorganised symptoms (Emsley et al., 2003).
Functionality was assessed with the Social and Occupational Functioning Assessment Scale
(SOFAS) (American Psychiatric Association, 1994), depressive symptoms with the Calgary
Depression Rating Scale for Schizophrenia (CDSS) (Addington and Addington J., 1993) and
EPS with the Extrapyramidal Symptom Rating Scale (ESRS) (Chouinard and Margolese,
2005).
2.3.3 Cognitive evaluations
Cognitive performance was assessed by the MATRICS (Measurement and
Treatment Research to Improve Cognition in Schizophrenia) Cognitive Consensus Battery
(MCCB), developed to measure cognitive functioning in schizophrenia. The MCCB
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measures seven cognitive domains (speed of processing; attention/vigilance; working
memory; verbal learning; visual learning; reasoning and problem solving; and social
cognition) and a composite score. (Nuechterlein and Green, 2006). The MCCB was
administered by trained psychologists.
2.4 State vs. trait assessments
NSS display both state and trait characteristics (Bachmann et al., 2014). We
assumed that NES scores in the acute state represent both state and trait components,
while those in clinically stable patients represent trait components, and the degree of change
from the acute state to stable state would represent state components. Therefore, for state-
related NSS we used change scores (endpoint - baseline score). (For ESRS change scores
we subtracted the baseline score from the highest score at any time point.) For trait-related
NSS we used endpoint scores, calculated by last observation carried forward.
2.5 Statistical analyses
All participants with completed baseline NES assessments were included in the
analyses. We assessed the distribution of the data by inspection of histograms and normal
probability plots. We employed linear mixed-effect models for continuous repeated measures
(MMRM) to assess the changes in NSS subscale and total scores over time, with age,
gender and previous antipsychotic exposure (yes/no) as covariates. Within analyses Fisher’s
Least Significant Difference (LSD) tests were used for post hoc multiple comparisons. We
conducted Pearson correlational coefficient analyses to investigate both state (change
scores) and trait-related (endpoint scores) associations between NSS and psychopathology,
cognition and EPS. We used general regression models to further explore these
correlations. NSS subscales and total score were dependent variables, covariates were age,
gender and level of education and for the predictor variables we were guided by effect sizes
>0.3 (moderate) in the correlational analyses. All tests were 2-tailed.
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3. Results
Details of the 126 participants are provided in Table 1, and baseline and endpoint NSS,
clinical and cognitive scores are provided in Table 2. There were significant improvements in
NSS scores, as well as in psychopathology, functionality and cognitive performance. There
were significant increases in ESRS scores for Parkinsonism and dyskinesia subscales.
3.1 Longitudinal course of NSS
For the linear mixed effects models there was a significant effect for time for NES
total and all subscale scores (Figure 1). Post-hoc LSD test results indicated similar patterns
for the NES total and subscale scores – i.e. significant reductions from baseline to month 6
but no further reductions thereafter. Mean reductions (and confidence intervals) for baseline
to month 6 and from month 6 to month 12 were, respectively, NES total score=4.8(3.4-6.1),
p<0.0001 for 0-6 months and 0.8(-0.7-2.3), p=0.2 for 6-12 months; sensory
integration=1.3(0.8-1.8), p<0.0001 for 0-6 months and 0.1(-0.4-0.6), p=0.7 for 6-12 months;
motor coordination=0.5(0.1-0.8), p=0.007 for 0-6 months and 0.1(-0.2-0.4), p=0.5 for 6-12
months; motor sequencing=1.2(0.7-1.7), p<0.0001 for 0-6 months and 0.2(-0.4-0.7), p=0.5
for 6-12 months.
3.2 State-related change-scores
The change score correlations are provided in Supplementary Table 1. Mostly, effect
sizes for NSS correlations with psychopathology, functionality and cognition were small (0.1-
0.3) to moderate (0.3 – 0.5). For the general regression models, we entered gender as a
categorical factor and age, highest level of education, and change scores for PANSS
disorganised factor, SOFAS and MCCB working memory as continuous predictors. For the
sensory integration subscale model (R2=0.1, p=0.1) improved working memory (t=-2.6,
p=0.01) was the only significant predictor; for the motor coordination model (R2 0.07, p=0.2)
there were no significant predictors; for the motor sequencing model (R2=24, p=0.0001)
working memory (t=-2.9, p=0.005) and SOFAS score (t=-2.8, p=0.005) were significant
8
predictors; and for the NES Total score model (R2 22, p=0.0001) PANSS disorganised factor
(t=2.3, p=0.02) was a significant predictor.
3.3 Trait-related endpoint analyses
The endpoint score correlations are provided in Supplementary Table 2. There were
considerably more correlations with a moderate (0.3-0.5) and even large (>.5) effect size
between the endpoint scores than was the case for the change scores. For the general
regression models, we entered gender as a categorical factor and age, highest level of
education, PANSS positive, negative and disorganised factors, SOFAS, MCCB composite
score and ESRS Parkinsonism score as continuous predictors. (We elected to enter the
MCCB composite score only, as most of cognitive domains showed moderate to strong
correlations with NSS.) For the sensory integration subscale model (R2 0.3, p=0.0001),
MCCB composite score was the only significant predictor (t=-3.4, p=0.001); for the motor co-
ordination subscale model (R2 0.35, p=0.001) ESRS Parkinsonism score was the only
significant predictor (t=4.9, p= 0.0001); for the motor sequencing subscale model (R2 0.47,
p=0.0001) MCCB composite score (t=-3.4, p=0.001) and ESRS Parkinsonism score (t=2.8,
p=0.005) were significant predictors. For the NES total score model (R2 0.53, p=0.0001)
ESRS Parkinsonism score (t=3.7, p=0.0001), PANSS disorganised factor (t=2.0, p=0.04)
and MCCB composite score (t=-3.5, p=0.0007) were significant predictors.
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4. Discussion:
While there have been a number of studies of NSS in first-episode psychosis (Schroder
et al., 1998;Whitty et al., 2003;Chen et al., 2005;Bachmann et al., 2005;Emsley et al.,
2005;Boks et al., 2006;Prikryl et al., 2007;Mayoral et al., 2008;Prikryl et al., 2012;Mayoral et
al., 2012), this is the first to prospectively assess changes in NSS in first episode
schizophrenia in which patients were treated according to a standard protocol with assured
medication adherence. Our main finding was that significant reductions occurred in all NSS
domains. While some state-related NSS reductions were related to improvements in
components of cognition, psychopathology and functionality, there were stronger
associations between the trait-related endpoint NSS scores and these domains. While
antipsychotic treatment was associated with an overall beneficial effect on NSS, the
presence of Parkinsonian side-effects predicted higher trait-related NSS scores.
4.1 Course of NSS:
The improvements in NSS that we observed are consistent with most longitudinal
studies (Bachmann et al., 2014). Our results further indicate that the greatest reductions
occurred between baseline and month 6, with no additional improvements thereafter. The
timing of the initial assessments may be critically important when assessing longitudinal NSS
changes. Our baseline assessments were conducted in the acute psychotic state, before
treatment was initiated. Of the four studies reporting no longitudinal improvement, one
conducted baseline assessments in chronically hospitalised patients (Smith et al., 1999) and
one in stable, chronic patients (Chen et al., 2000). The two other studies did not specify
whether patients were initially assessed prior to initiation of treatment – one stated that they
were assessed “at the time of their first admission” (Madsen et al., 1999), and the other “at
initial assessment” in first-episode patients (Chen et al., 2005). We observed improvements
in all of the NES subscales, suggesting that the state-related component of NSS is
10
generalised. This differs slightly from a study reporting improvements in motor coordination
and motor sequencing but not in sensory integration (Whitty et al., 2003), but is similar
another in which improvements in all subscales were reported (Cuesta et al., 2012).
4.2 State-related associations between NSS, psychopathology and functionality:
Several previous studies have reported a relationship between changes in NSS and
changes in psychopathology. Chan et al.(Chan et al., 2015) examined the course of NSS in
145 patients with first-episode schizophrenia, and compared patients with prominent
negative symptoms with those without prominent negative symptoms, for up to a year. They
found that, despite general improvement in NSS, the patients with prominent negative
symptoms exhibited poorer motor coordination and higher overall levels of NSS. Whitty et
al., (Whitty et al., 2003) reported that reductions in NES total scores and motor coordination
subscales were associated with improvements in PANSS total and positive and negative
subscale scores; reductions in motor sequencing scores were associated with improvements
in PANSS positive and negative subscale scores; and reductions in sensory integration
scores were associated with improvements in PANSS positive subscale score. Our findings
in terms of change correlations differ from the above studies insofar as only the PANSS
disorganised factor independently predicted NSS changes, and only with NES total score. A
possible explanation for this is that most previous studies applied the originally described
subscales of the PANSS, i.e. positive, negative and general psychopathology. Later PANSS
factor-analyses reported a best-fit five factor model comprising positive, negative and
disorganised domains (as well as anxiety/depression and excitement/hostility domains)
(Emsley et al., 2003). The disorganised domain that we used includes two items from the
original PANSS negative subscale, i.e. conceptual disorganisation and difficulty in abstract
thinking, plus the items stereotyped thinking, disorientation, poor attention and
preoccupation (Emsley et al., 2003). Indeed, another study using factor-analysis derived
PANSS domains also found that NSS change scores were positively correlated with the
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disorganised (and positive) domains (Cuesta et al., 2012). Our findings are therefore only
partly consistent with the proposal that NSS changes are linked to changes in
psychopathology, and can be attributed to treatment response (Bombin et al., 2005).
4.3 State-related associations between NSS and cognitive performance:
Associations between NSS and cognitive performance are well recognised in
schizophrenia (Mohr et al., 2003;Mellacqua et al., 2012), and have led to the proposal that
they are manifestations of the same underlying pathophysiological process (Mellacqua et al.,
2012). In chronic patients, deficits in sensory integration had the strongest association with
cognitive impairments (Arango et al., 1999), while motor sequencing deficits were associated
with poor planning and inhibition, spatial span and spatial memory (Arabzadeh et al., 2014).
Furthermore, associations were reported between NSS and cognitive function in healthy
volunteers, although there are several associations that appear to be specific to psychotic
illness (Mellacqua et al., 2012). Higher scores in all NES subscales have been associated
with poorer general cognitive function, while poorer performances on the sensory integration
and motor sequencing tests are associated with deficits in specific cognitive domains
(Mellacqua et al., 2012). However, these associations were reported in cross-sectional
studies. The association between state-related NSS and cognition is less clear. We found
only one cognitive domain to be a significant predictor of NES scores - impaired working
memory predicted poorer sensory integration, motor sequencing and NES total scores -
suggesting that the state related component of NSS is related specifically to this cognitive
domain.
4.4 Trait-related associations between NSS, psychopathology and functionality:
Associations between NSS and psychopathology and functionality were stronger for
endpoint scores than for change scores, and the endpoint prediction models explained more
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of the variation than was the case with the change scores. Nevertheless, the only
independent predictor of endpoint NSS that retained significance in the regression models
was the PANSS disorganised factor, and only for NES total score. The strong association at
endpoint between motor sequencing difficulties and persistent psychopathology and poorer
functional outcome is consistent with a report that motor-sequencing difficulties remained
relatively unchanged across the course of illness, suggesting that they are the trait-marking
NSS of schizophrenia (Ojagbemi et al., 2015).
4.5 Trait-related associations between NSS and cognitive performance:
As was the case for psychopathology and functionality, there were more substantial
associations between NSS and cognitive function in terms of the endpoint scores than for
change scores. This suggests a closer association between the trait-related components of
NSS and cognitive function than those related to the acute psychotic state. Also, the fact that
cognitive impairment significantly predicted poorer performance on NES sensory
integration, motor sequencing and NES total scores suggests that associations between
trait-related NSS and cognitive function are global rather than specific. That social cognition
was the only cognitive domain not to be significantly correlated with NSS may be due to this
cognitive domain being less suitable for non-Western cultural settings (Karim and Weisz,
2010).
The importance of these trait-related NSS and their clinical and cognitive
concomitants is that they likely reflect the persistent underlying neurodevelopmental
impairments associated with schizophrenia. Given the reported specificity and sensitivity of
NSS in schizophrenia spectrum disorders (Chan et al., 2016) and evidence linking them to
specific brain regions Mittal (Mittal, 2016), future studies investigating the
neurodevelopmental impairments in schizophrenia would do well to focus on endpoint NSS
specifically.
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4.6 Effects of antipsychotic treatment on NSS:
Most evidence to date indicates that NSS improve with antipsychotic treatment, and
that this coincides with improvements in accompanying symptoms (Bachmann et al., 2014).
Our findings partly confirm this, although the effect sizes for change correlations between
NSS and psychopathology were only small to moderate. This suggests that NSS
improvements are not a direct consequence of improvements in psychopathology. Also, the
limited variation explained by the change score predictor models suggests that other factors
are involved. Whether the treatment effect on NSS is non-specific and secondary to
improvements in e.g. attention, concentration and cooperativeness remains to be
determined.
NSS have been reported to not be exacerbated by antipsychotic medication (Browne
et al., 2000). However, our finding that higher endpoint ESRS Parkinsonism and total scores
independently predicted greater motor coordination and motor sequencing difficulties is
consistent with a previous report of an association between NSS and EPS (Jahn et al.,
2006) and suggests that emergent EPS may negatively affect performance on the NES
scale – i.e. that some NSS may be iatrogenic. Even subtle EPS may have an effect, as we
prescribed the lowest effective antipsychotic dose and EPS were generally very mild (Chiliza
et al., 2016). Antipsychotic-induced EPS cannot, however, entirely account for these NSS,
as abnormalities in motor coordination and motor sequencing have also been reported in
antipsychotic-naïve individuals (Dazzan et al., 2008).
Strengths of this study include the selection of first episode patients who were
treatment naïve or only minimally medicated, standardised treatment regime with assured
adherence, and repeated, comprehensive assessments of psychopathology, functionality,
cognition and EPS. There are also limitations to our study. First, the absence of a healthy
14
control group prevented us from assessing practice effects, and from inferring that our
findings are specific to schizophrenia. Second, study investigators were not blinded as to
visit status, and as far as possible patients were assessed at follow-up visits by the same
investigator to minimise inter-rater variations. This introduced the possibility of observer bias.
Third, IQ was not measured and therefore could not be controlled for. This may be
important, as both premorbid and current IQ may influence NES performance (Dazzan et al.,
2008). We used highest education attained as a proxy for IQ which is not ideal, as other
factors such as socioeconomic circumstances and age of illness onset could have influenced
educational status. Finally, our findings cannot necessarily be generalised to patients treated
with other antipsychotics. However, we consider it unlikely that our findings are restricted to
treatment with flupenthixol, or to the conventional antipsychotics, for the following reasons:
Conventional and atypical antipsychotics are not distinct classes and it has been
recommended that this categorisation be abandoned (Leucht et al., 2009); flupenthixol has
receptor binding profile that is similar to some atypical antipsychotics and has been referred
to as a “partially atypical” antipsychotic (Gatazz et al., 2004); and because we used the
lowest effective dose we were able to minimise the occurrence of EPS. Indeed, the levels of
EPS reported in our study are similar to those reported with atypical antipsychotics in a
similar patient sample (Kahn et al., 2008).
In conclusion, our study provides further evidence that NSS improve with treatment
and that improvements are only partly associated with improvements in psychopathology,
functionality and cognition. The stronger endpoint associations between NSS and those of
psychopathology, functionality and cognition suggest that trait-related components of these
phenomena are more closely related to one another than state-related components. Future
studies should take care to distinguish between NSS present in acute psychotic states and
those present in optimally treated, stable patients. The latter have a different set of clinical
and cognitive correlates, and are better suited as trait endophenotypes.
15
References
Addington,D. and Addington J. Assessing depression in schizophrenia: the Calgary
Depression Scale. Br J Psychiatry. 163, S39-S44. 1993.
American Psychiatric Association, 1994. Diagnostic and Statistical Manual of Mental
Disorders., 4th edn. Washington, D.C..
Arabzadeh,S., Amini,H., Tehrani-Doost,M., Sharifi,V., Noroozian,M. and Rahiminejad,F.,
2014. Correlation of neurological soft signs and neurocognitive performance in first
episode psychosis. Psychiatry Res. 220, 81-88.
Arango,C., Bartko,J.J., Gold,J.M. and Buchanan,R.W., 1999. Prediction of
neuropsychological performance by neurological signs in schizophrenia. Am J
Psychiatry. 156, 1349-1357.
Bachmann,S., Bottmer,C. and Schroder,J., 2005. Neurological soft signs in first-episode
schizophrenia: a follow-up study. Am J Psychiatry. 162, 2337-2343.
Bachmann,S., Degen,C., Geider,F.J. and Schroder,J., 2014. Neurological soft signs in the
clinical course of schizophrenia: results of a meta-analysis. Front Psychiatry. 5, 185.
Boks,M.P., Selten,J.P., Leask,S. and van den Bosch,R.J., 2006. The 2-year stability of
neurological soft signs after a first episode of non-affective psychosis. Eur Psychiatry.
21, 288-290.
Bombin,I., Arango,C. and Buchanan,R.W., 2005. Significance and meaning of neurological
signs in schizophrenia: two decades later. Schizophr Bull. 31, 962-977.
Browne,S., Clarke,M., Gervin,M., Lane,A., Waddington,J.L., Larkin,C. and O'Callaghan,E.,
2000. Determinants of neurological dysfunction in first episode schizophrenia.
Psychol Med. 30, 1433-1441.
16
Buchanan,R.W. and Heinrichs,D.W., 1989. The Neurological Evaluation Scale (NES): a
structured instrument for the assessment of neurological signs in schizophrenia.
Psychiatry Res. 27, 335-350.
Chan,R.C., Geng,F.L., Lui,S.S., Wang,Y., Ho,K.K., Hung,K.S., Gur,R.E., Gur,R.C. and
Cheung,E.F., 2015. Course of neurological soft signs in first-episode schizophrenia:
Relationship with negative symptoms and cognitive performances. Sci Rep. 5,
11053.
Chan,R.C. and Gottesman,I.I., 2008. Neurological soft signs as candidate endophenotypes
for schizophrenia: a shooting star or a Northern star? Neurosci Biobehav Rev. 32,
957-971.
Chan,R.C., Xu,T., Heinrichs,R.W., Yu,Y. and Wang,Y., 2010. Neurological soft signs in
schizophrenia: a meta-analysis. Schizophr Bull. 36, 1089-1104.
Chan,R.C., Xie,W., Geng,F.L., Wang,Y., Lui,S.S., Wang,C.Y., Yu,X., Cheung,E.F. and
Rosenthal,R., 2016. Clinical Utility and Lifespan Profiling of Neurological Soft Signs
in Schizophrenia Spectrum Disorders. Schizophr Bull. 42, 560-570.
Chen,E.Y., Kwok,C.L., Au,J.W., Chen,R.Y. and Lau,B.S., 2000. Progressive deterioration of
soft neurological signs in chronic schizophrenic patients. Acta Psychiatr Scand. 102,
342-349.
Chen,E.Y., Hui,C.L., Chan,R.C., Dunn,E.L., Miao,M.Y., Yeung,W.S., Wong,C.K., Chan,W.F.
and Tang,W.N., 2005. A 3-year prospective study of neurological soft signs in first-
episode schizophrenia., 2005. Schizophr Res. 75, 45-54.
Chiliza,B., Ojagbemi,A., Esan,O., Asmal,L., Oosthuizen,P., Kidd,M., Gureje,O. and
Emsley,R., 2016. Combining depot antipsychotic with an assertive monitoring
programme for treating first-episode schizophrenia in a resource-constrained setting.
Early Interv Psychiatry. 10, 54-62.
17
Chouinard,G. and Margolese,H.C. Manual for the extrapyramidal symptom rating scale
(ESRS). Schizophr Res 76, 247-265. 2005.
Coldham,E.L., Addington,J. and Addington,D., 2002. Medication adherence of individuals
with a first episode of psychosis. Acta Psychiatr Scand. 106, 286-290.
Cuesta,M.J., Campos,M.S., Garcia-Jalon,E., Sanchez-Torres,A.M. and Peralta,V., 2012.
Treatment response of neurological soft signs in drug-naive patients with a first
psychotic episode. Schizophr Res. 139, 144-150.
Dazzan,P., Lloyd,T., Morgan,K.D., Zanelli,J., Morgan,C., Orr,K., Hutchinson,G., Fearon,P.,
Allin,M., Rifkin,L., McGuire,P.K., Doody,G.A., Holloway,J., Leff,J., Harrison,G.,
Jones,P.B. and Murray,R.M., 2008. Neurological abnormalities and cognitive ability in
first-episode psychosis. Br J Psychiatry. 193, 197-202.
Dazzan,P. and Murray,R.M., 2002. Neurological soft signs in first-episode psychosis: a
systematic review. Br J Psychiatry Suppl. 43, s50-s57.
Emsley,R., Rabinowitz,J. and Torreman,M., 2003. The factor structure for the Positive and
Negative Syndrome Scale (PANSS) in recent-onset psychosis. Schizophr Res. 61,
47-57.
Emsley,R., Turner,H.J., Oosthuizen,P.P. and Carr,J., 2005. Neurological abnormalities in
first-episode schizophrenia: temporal stability and clinical and outcome correlates.
Schizophr Res. 75, 35-44.
First,M.B., Spitzer,R.L.G.M. and Williams,L.B.W. Structured Clinical Interview for DSM-IV
Axis I Disorders, Patient Edition (SCID-P). 2nd. 1994. New York, New York State
Psychiatric Institute, Biometrics Research.
Gattaz WF, Diehl A, Geuppert MS, Hubrich P, Schmitt A, Linde I, et al (2004): Olanzapine
versus flupenthixol in the treatment of inpatients with schizophrenia: a randomized
double-blind trial. Pharmacopsychiatry 37:279-285.
18
Gupta,S., Andreasen,N.C., Arndt,S., Flaum,M., Schultz,S.K., Hubbard,W.C. and Smith,M.,
1995. Neurological soft signs in neuroleptic-naive and neuroleptic-treated
schizophrenic patients and in normal comparison subjects. Am J Psychiatry. 152,
191-196.
Jahn,T., Hubmann,W., Karr,M., Mohr,F., Schlenker,R., Heidenreich,T., Cohen,R. and
Schroder,J., 2006. Motoric neurological soft signs and psychopathological symptoms
in schizophrenic psychoses. Psychiatry Res. 142, 191-199.
Kahn RS, Fleischhacker WW, Boter H, et al. Effectiveness of antipsychotic drugs in first-
episode schizophrenia and schizophreniform disorder: an open randomised clinical
trial. Lancet 2008;371: 1085-1097
Karim,J. and Weisz,R. Cross-Cultural Research on the Reliability and Validity of the Mayer-
Salovey-Caruso Emotional Intelligence Test (MSCEIT). Cross-Cultural Research
44[4], 374-404. 2010.
Kay,S.R., Fizbein,A. and Opler,L.A. The Positive and Negative Syndrome Scale (PANSS) for
Schizophrenia. Schizophr Bull 13, 261-267. 1987.
Leucht S, Corves C, Arbter D, Engel RR, Li C, Davis JM (2009): Second-generation versus
first-generation antipsychotic drugs for schizophrenia: a meta-analysis. Lancet
373:31-41.
Madsen,A.L., Vorstrup,S., Rubin,P., Larsen,J.K. and Hemmingsen,R., 1999. Neurological
abnormalities in schizophrenic patients: a prospective follow-up study 5 years after
first admission. Acta Psychiatr Scand. 100, 119-125.
Mayoral,M., Bombin,I., Zabala,A., Robles,O., Moreno,D., Parellada,M., Ruiz-Sancho,A. and
Arango,C., 2008. Neurological soft signs in adolescents with first episode psychosis:
two-year followup. Psychiatry Res. 161, 344-348.
Mayoral,M., Bombin,I., Castro-Fornieles,J., Gonzalez-Pinto,A., Otero,S., Parellada,M.,
Moreno,D., Baeza,I., Graell,M., Rapado,M. and Arango,C., 2012. Longitudinal study
19
of neurological soft signs in first-episode early-onset psychosis. J Child Psychol
Psychiatry. 53, 323-331.
Mellacqua,Z., Eyeson,J., Orr,K.D., Morgan,K.D., Zanelli,J., Lloyd,T., Morgan,C., Fearon,P.,
Hutchinson,G., Doody,G.A., Chan,R.C., Harrison,G., Jones,P.B., Murray,R.M.,
Reichenberg,A. and Dazzan,P., 2012. Differential relationship between neurological
and cognitive dysfunction in first episode psychosis patients and in healthy
individuals. Schizophr Res. 142, 159-164.
Mittal,V.A., 2016. Cross-Cutting Advancements Usher in a New Era for Motor Research in
Psychosis. Schizophr Bull. 42, 1322-1325.
Mohr,F., Hubmann,W., Albus,M., Franz,U., Hecht,S., Scherer,J., Binder,J. and Sobizack,N.,
2003. Neurological soft signs and neuropsychological performance in patients with
first episode schizophrenia. Psychiatry Res. 121, 21-30.
Nuechterlein,K.H. and Green,M.F. MATRICS Consensus Battery Manual. 2006. Los
Angeles, MATRICS Assessment Inc.
Ojagbemi,A., Esan,O., Emsley,R. and Gureje,O., 2015. Motor sequencing abnormalities are
the trait marking neurological soft signs of schizophrenia. Neurosci Lett. 600, 226-
231.
Peralta,V., de Jalon,E.G., Campos,M.S., Basterra,V., Sanchez-Torres,A. and Cuesta,M.J.,
2011. Risk factors, pre-morbid functioning and episode correlates of neurological soft
signs in drug-naive patients with schizophrenia-spectrum disorders. Psychol Med. 41,
1279-1289.
Prikryl,R., Ceskova,E., Kasparek,T. and Kucerova,H., 2007. Neurological soft signs and their
relationship to 1-year outcome in first-episode schizophrenia. Eur Psychiatry. 22,
499-504.
Prikryl,R., Ceskova,E., Tronerova,S., Kasparek,T., Kucerova,H.P., Ustohal,L., Venclikova,S.
and Vrzalova,M., 2012. Dynamics of neurological soft signs and its relationship to
20
clinical course in patients with first-episode schizophrenia. Psychiatry Res. 200, 67-
72.
Sanders,R.D., Keshavan,M.S., Forman,S.D., Pieri,J.N., McLaughlin,N., Allen,D.N., van
Kammen,D.P. and Goldstein,G., 2000. Factor structure of neurologic examination
abnormalities in unmedicated schizophrenia. Psychiatry Res. 95, 237-243.
Schroder,J., Silvestri,S., Bubeck,B., Karr,M., Demisch,S., Scherrer,S., Geider,F.J. and
Sauer,H., 1998. D2 dopamine receptor up-regulation, treatment response,
neurological soft signs, and extrapyramidal side effects in schizophrenia: a follow-up
study with 123I-iodobenzamide single photon emission computed tomography in the
drug-naive state and after neuroleptic treatment. Biol Psychiatry. 43, 660-665.
Smith,R.C., Hussain,M.I., Chowdhury,S.A. and Stearns,A., 1999. Stability of neurological
soft signs in chronically hospitalized schizophrenic patients. J Neuropsychiatry Clin
Neurosci. 11, 91-96.
Whitty,P., Clarke,M., Browne,S., McTigue,O., Kamali,M., Feeney,L., Lane,A., Kinsella,A.,
Waddington,J.L., Larkin,C. and O'Callaghan,E., 2003. Prospective evaluation of
neurological soft signs in first-episode schizophrenia in relation to psychopathology:
state versus trait phenomena. Psychol Med. 33, 1479-1484.
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Figure legend:
Figure 1. Mixed model repeated measures for the NES total and subscale scores over 12 months.
22
Table 1. Characteristics of the 126 participants with first-episode schizophrenia
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Gender, N (%)
Male 93 (74%)
Female 33 (26%)
Age, Years, Mean (SD) 24.1 (6.6)
Highest level of education, N (%)
Elementary school 9 (7%)
Secondary school 76 (60%)
Completed secondary school 25 (20%)
Tertiary education 14 (11%)
Technical 2 (2%)
DSM Diagnosis, N (%)
Schizophrenia 84 (66%)
Schizophreniform 40 (32%)
Schizoaffective 2 (2%)
Race, N (%)
Mixed ancestry 98 (78%)
Black 18 (14%)
White 10 (8%)
Substance abuse, N (%) 59 (47%)
Previous antipsychotic exposure, N (%) 56 (45%)
Duration of exposure, Days, Mean (SD) 11 (6.8)
Completed the study, N (%) 84 (67%)
Achieved remission N (%) 61 (48%)
Table 2. Baseline and endpoint clinical and cognitive scores for the 126 patients
Baseline score Endpoint score
Mean SD Mean SD t P
NES:
Total 15.02 7.99 10.72 6.71 4.6 <0.0001
Sensory Integration 2.79 2.52 1.62 2.13 4.0 <0.0001
Motor Coordination 1.41 1.60 0.93 1.36 2.6 <0.01
Motor sequencing 2.94 2.47 1.90 2.18 3.5 <0.001
PANSS:
Total 94.78 16.48 52.85 17.92
19.3 <0.0001
Negative 17.57 4.80 10.68 4.56 11.7 <0.0001
Positive 13.59 2.76 5.47 3.36 21.0 <0.0001
Excitement hostility 8.57 3.83 5.24 2.33 8.3 <0.0001
Disorganised 18.26 4.46 10.69 4.40 13.6 <0.0001
CDSS Total 3.37 4.07 1.26 2.74 4.8 <0.0001
CGI SOFAS 44.04 11.55 60.32 13.27
-10.4 <0.0001
MCCB:*
Speed of processing 17.25 16.12 25.28 15.88
-3.6 <0.001
Attention and vigilance 25.61 11.72 33.62 11.27
-4.9 <0.0001
Working memory 23.29 15.47 30.95 13.85
-3.7 <0.001
Verbal learning 34.36 8.41 36.93 7.69 -2.3 0.02
Visual learning 29.07 15.40 35.92 13.65
-3.4 <0.001
Reasoning and problem solving 31.87 8.83 36.90 10.25
-3.8 <0.001
Social cognition 28.92 11.41 32.17 12.48
-1.9 0.06
Composite score 12.89 15.38 21.61 15.19
-3.9 <0.0001
ESRS:**
Parkinsonism 1.76 3.74 4.51 6.67 -6.34 <0.0001
Dystonia 0 0 0.11 0.88 -1.4 0.16
Dyskinesia 0.04 0.27 0.22 0.72 -2.99 0.003
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Total 2.69 5.52 7.34 9.30 -8.11 <0.0001
NES, Neurological Evaluation Scale; PANSS, Positive and Negative Syndrome Scale;
CDSS, Calgary Depression Scale for Schizophrenia; SOFAS, Social and Occupational
Functioning Assessment Scale; MCCB, MATRICS Consensus Cognitive Battery
* For the cognitive assessments there were 100 participants with complete baseline data
** For ESRS the change scores are from baseline to the highest score ever achieved
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Figure 1. Mixed model repeated measures for the NES total and subscale scores over 12 months.
Vertical bars denote 95% confidence intervals
26
Supplementary Table 1. Pearson correlation coefficients for the change scores† between
NES total and subscales and clinical and cognitive measures.
Sensory
integration
Motor co-
ordination
Motor
sequencing
NES Total
PANSS:
Positive factor 0.15 0.12 0.22* 0.24*
Negative factor 0.09 0.11 0.24* 0.23*
Disorganised factor 0.18* 0.22* 0.32*** 0.40*** Total 0.12 0.15 0.20* 0.26*
CDSS Total -0.02 0.04 -0.01 -0.00
SOFAS -0.18* -0.17 -0.39*** -0.35***
MCCB:
Speed of processing -0.23* -0.16 -0.22* -0.24*
Attention and vigilance -0.14 -0.18* -0.28* -0.23*
Working memory -0.35*** -0.22* -0.41*** -0.41*** Verbal learning -0.18* -0.25* -0.18* -0.18*
Visual learning -0.18* -0.20* -0.12 -0.24*
Reasoning and problem
solving-0.11 0.05 -0.22* -0.20*
Social cognition 0.03 -0.11 0.03 0.08
Composite score -0.32*** -0.27* -0.36*** -0.39***
ESRS:
Parkinsonism -0.03 -0.03 -0.05 -0.01
Dystonia -0.07 -0.05 -0.14 -0.09
Dyskinesia -0.18 -0.07 0.08 -0.05
Total score -0.06 -0.07 -0.06 -0.05
NES, Neurological Evaluation Scale; PANSS, Positive and Negative Syndrome Scale;
CDSS, Calgary Depression Scale for Schizophrenia; SOFAS, Social and Occupational
Functioning Assessment Scale; MCCB, MATRICS Consensus Cognitive Battery
27
† For NES, PANSS, CDSS, SOFAS and MCCB change scores are from baseline to endpoint;
for ESRS change scores are from baseline to the highest score ever achieved
*p<0.05; **p<0.001; ***p<0.0001
Supplementary Table 2. Pearson correlation coefficients for the endpoint scores between NES total and subscales and clinical and cognitive measures, extrapyramidal symptom scores and antipsychotic dose.
Sensory integration
Motor co-ordination
Motor sequencing NES Total
PANSS:
Positive factor 0,26* 0,11 0,31** 0,30**
Negative factor 0,22* 0,27* 0,37*** 0,40***
Disorganised factor 0,42*** 0,32*** 0,53*** 0,58***
Total 0,34*** 0,27* 0,45*** 0,49***
CDSS TOTAL 0,05 0,08 0,01 0,04
SOFAS -0,37*** -0,20* -0,45*** -0,45***
MCCB:
Speed of processing -0,48*** -0,35*** -0,55*** -0,55***
Attention and vigilance -0,39*** -0,23* -0,45*** -0,45***
Working memory -0,46*** -0,29* -0,51*** -0,48***
Verbal learning -0,40*** -0,31* -0,43*** -0,46***
Visual learning -0,42*** -0,36*** -0,43*** -0,50***
Reasoning and problem solving -0,38*** -0,08 -0,36*** -0,31*
Social cognition -0,07 -0,19 -0,19 -0,15
Composite score -0,49*** -0,34** -0,55*** -0,55***
ESRS:
Parkinsonism 0,25* 0,48*** 0,45*** 0,49***
Dystonia -0,08 -0,07 -0,09 -0,12
Dyskinesia -0,05 0,01 -0,01 -0,04
28
Total score 0,23* 0,45*** 0,39*** 0,44***
Antipsychotic dose -0,13 -0,02 -0,16 -0,13
NES, Neurological Evaluation Scale; PANSS, Positive and Negative Syndrome Scale;
CDSS, Calgary Depression Scale for Schizophrenia; SOFAS, Social and Occupational
Functioning Assessment Scale; MCCB, MATRICS Consensus Cognitive Battery; ESRS,
Extrapyramidal Symptom Rating Scale
*p<0.05; **p<0.001; ***p<0.0001
29
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