gender differences in prepulse inhibition (ppi) in bipolar disorder: men have reduced ppi, women...

Gender differences in prepulse inhibition (PPI)in bipolar disorder: men have reduced PPI,women have increased PPI

Andrea Gogos1,2,3, Maarten van den Buuse1,2 and Susan Rossell3,4

1 Behavioural Neuroscience Laboratory, Mental Health Research Institute of Victoria, Parkville, VIC, Australia2 Centre for Neuroscience, University of Melbourne, Parkville, VIC, Australia3 Department of Cognitive Neuropsychiatry, Mental Health Research Institute of Victoria, Parkville, VIC, Australia4 Cognitive Neuropsychiatry Laboratory, Monash-Alfred Psychiatry Research Centre, School of Psychology, Psychiatry and

Psychological Medicine, Monash University, The Alfred, Prahran, VIC, Australia

Abstract

Prepulse inhibition (PPI) is a measure of sensorimotor gating or information processing. Few studies have

examined PPI in bipolar disorder (BD) ; two studies reported a PPI disruption and two reported no

change. There are gender differences in PPI and within the clinical profile of BD, which may explain some

of these discrepancies. Thus, the effect of gender on PPI in BDwas the focus of the current study. Euthymic

BD patients (14 male/15 female) were compared to age- and IQ-matched healthy control participants

(16 male/16 female). Assessment of PPI included 21 pulse-alone trials (115 dB) and a total of 42 prepulse-

pulse trials (seven of each prepulse : 74, 78, 86 dB) at two stimulus onset asynchrony levels (SOA: 60,

120 ms). There was a grouprSOA and a grouprgender interaction, reflecting that men with BD showed

reduced PPI compared to control males at the 60-ms SOA (3% in BD vs. 26% in controls), but not the

120-ms SOA. In contrast, women with BD had significantly increased PPI compared to female controls at

the 120-ms SOA (49% in BD vs. 29% in controls), but not the 60-ms SOA. Compared to control participants

BD patients showed changes in PPI, which are gender-dependent ; male BD participants had reduced PPI,

whereas female BD participants had increased PPI. This gender difference highlights the need to consider

men and women with BD as two distinct groups, at least in PPI studies.

Received 9 November 2008 ; Reviewed 12 February 2009 ; Revised 19 March 2009 ; Accepted 24 April 2009 ;

First published online 3 June 2009

Key words : Bipolar disorder (BD), gender differences, PPI, schizophrenia, startle.

Introduction

Bipolar disorder (BD) is a serious mental illness where

patients may experience both manic episodes and

syndromal major depression. BD can be characterized

by an abrupt onset and a fluctuating course in which

the patient returns to a relatively normal state between

episodes (Berns &Nemeroff, 2003). Gender differences

are present in the clinical profile of BD, e.g. men have

an earlier onset of BD, as determined by the first manic

episode (Kennedy et al. 2005). Compared to men,

women have higher incidence rates throughout adult-

hood rather than early life and are at a greater risk

for depressive episodes, episodes of mixed mania

and rapid-cycling (Curtis, 2005; Kennedy et al. 2005 ;

Leibenluft, 1996). These gender differences may be

attributed to the effect of the female sex hormone,

oestrogen, in the brain. Oestrogen has been implicated

in mood, higher cognitive function and sensorimotor

gating (Bethea et al. 1998 ; Gogos et al. 2006 ; McEwen,

2001 ; Rubinow et al. 1998).

Prepulse inhibition (PPI) is a measure of sensori-

motor gating or in other words, information pro-

cessing. Sensorimotor gating is a normal protective

mechanism in the brain that filters irrelevant sensory,

motor or cognitive information, allowing for coherent

thought (Braff et al. 2001). Deficits in gating sensori-

motor information may result in an information over-

load or a misinterpretation of stimuli and may also

cause certain symptoms of schizophrenia, such as

thought disorder (Braff et al. 2001 ; Perry & Braff, 1994).

Address for correspondence : A. Gogos, Ph.D., Mental Health

Research Institute of Victoria, National Neuroscience Facility,

161 Barry St, Carlton South, VIC 3053, Australia.

Tel. : +613 8344 1851 Fax : +613 9387 5061

Email : [email protected]

International Journal of Neuropsychopharmacology (2009), 12, 1249–1259. Copyright f CINP 2009doi:10.1017/S1461145709000480

ARTICLE

CINP

https://www.researchgate.net/publication/8053704_Gender_Differences_in_Incidence_and_Age_at_Onset_of_Mania_and_Bipolar_Disorder_Over_a_35-Year_Period_in_Camberwell_England?el=1_x_8&enrichId=rgreq-46b42379-428e-4ba6-9035-03641a3cb46b&enrichSource=Y292ZXJQYWdlOzI2MjYxMzI4O0FTOjk4NTkzNjMzNDcyNTIxQDE0MDA1MTc5NjI1NTc=

https://www.researchgate.net/publication/15088896_Perry_W_Braff_DL_Information-processing_deficits_and_thought_disorder_in_schizophrenia_Am_J_Psychiatry_151_363-367?el=1_x_8&enrichId=rgreq-46b42379-428e-4ba6-9035-03641a3cb46b&enrichSource=Y292ZXJQYWdlOzI2MjYxMzI4O0FTOjk4NTkzNjMzNDcyNTIxQDE0MDA1MTc5NjI1NTc=

In humans, PPI of the acoustic startle is measured via

the eye-blink startle response (Braff et al. 2001). There

is an extensive literature on how PPI is affected in

schizophrenia patients (for review see Braff et al. 2001).

PPI is also deficient in other disorders including

obsessive–compulsive disorder (Hoenig et al. 2005)

and Huntington’s disease (Swerdlow et al. 1995).

These disorders have a common underlying deficit, i.e.

PPI deficits are the result of abnormalities within a

specific brain circuit rather than a specific psycho-

pathology (Swerdlow et al. 2001).

A limited number of studies have recently ex-

amined PPI in BD and found that remitted or acutely

manic BD patients, as well as their unaffected siblings,

show disruptions of PPI compared to healthy control

subjects (Giakoumaki et al. 2007 ; Perry et al. 2001).

However, other studies have shown no disruption

of PPI in BD adults (Barrett et al. 2005; Carroll et al.

2007) and children (Rich et al. 2005). These inconsistent

findings do not appear to be due to current symptom

severity, as two studies tested euthymic participants

(Barrett et al. 2005 ; Giakoumaki et al. 2007) and two

studies tested symptomatic participants [acute mania

and psychosis (Perry et al. 2001), manic or mixed epi-

sode (Carroll et al. 2007)]. It is possible that a history

of psychotic episodes may explain PPI deficits in BD,

as psychosis can occur in BD and schizophrenia.

Alternatively, gender may play a role in mediating PPI

deficits.

Gender differences in PPI have been described

in healthy participants, where men show greater PPI

than women (Swerdlow et al. 1993). Further, women

have greater PPI during the early follicular (low oes-

trogen) phase of the menstrual cycle, compared to

the luteal phase (Jovanovic et al. 2004 ; Swerdlow et al.

1997). The previous PPI literature for BD does not state

which stage of the menstrual cycle the women were in

when tested for PPI. In the schizophrenia literature

some studies have reported PPI gender differences,

with disruptions in male, but not female, clinical par-

ticipants (Kumari et al. 2004), alternatively disruptions

in female schizophrenia patients (Braff et al. 2005) and

lastly female patients have a greater PPI disruption

compared to male patients (Swerdlow et al. 2006a),

overall suggesting variable findings.

The present study aimed to examine gender differ-

ences in PPI in BD. We tested PPI in men and women

with BD compared to gender-, age- and IQ-matched

healthy controls. We recruited euthymic BD patients

to reduce the potential confounds present when test-

ing acutely unwell patients. Additionally, this recruit-

ment strategy enabled us to obtain patient groups that

were matched for symptom severity, a potential cause

of a gender difference. We hypothesized that there

would be a gender difference in PPI when comparing

BD patients and controls.

Methods

Participants

The present study tested 66 participants : 31 BD

patients and 35 healthy controls. All participants were

aged between 21 and 61 yr, were fluent in English,

and were recruited from the local community via

advertisements, outpatient facilities (Northern Hospital

and St Vincent’s Health) and word-of-mouth. The

procedures described in this study were approved

by the Mental Health Research and Ethics Committee

(Melbourne Health, Victoria, Australia) and partici-

pants gave their written, informed consent prior to

testing.

Participants from either group were excluded if

they reported a history of brain trauma, neurological

illness (n=1), concurrent substance abuse (n=1), co-

morbidity with Axis I disorders, had undergone elec-

troconvulsive therapy in the previous year, or had an

estimated full-scale verbal IQ<80 (n=1) as indicated

by the National Adult Reading Test (NART; Nelson,

1982). Handedness was assessed with the Edinburgh

Handedness Inventory (Oldfield, 1971). Control par-

ticipants were free from psychiatric illness [self-

reported and screened for current symptoms using

the Brief Psychiatric Rating Scale (BPRS; Ventura et al.

1993)] and were excluded if they had a first-degree

relative with schizophrenia or BD (n=1). Finally, one

male control showed inadequate startle responses

(defined in the PPI section below) and was excluded

from the final analysis. Therefore, the final analysis

included 61 participants (14 male/15 female BD par-

ticipants, 16 male/16 female controls) (Table 1).

BD patients were remitted outpatients, self-

reported euthymic and most were on medication. BD

diagnosis was confirmed according to DSM-IV criteria

during a clinical interview with a trained researcher

(independent and naive to the study hypothesis)

using the combined Structured Clinical Interview for

DSM-IV and Positive and Negative Syndrome Scale

(PANSS; Table 1) (First et al. 1997). As assessed using

the Bech–Rafaelsen Mania Rating Scale (MRS; Bech

et al. 1979), 27 patients were currently euthymic (score

0–10) and two patients had mild mania (score 11–15).

As assessed using the Hamilton Depression Rating

Scale (HAMD; Hamilton, 1960), 18 patients were cur-

rently euthymic (score 0–7), eight patients had mild

depression (score 8–13), two patients had moderate

1250 A. Gogos et al.

depression (score 14–18) and one female patient had

very severe depression (o23, scored 25). Of the 29 BD

patients included in the study, three were unmedi-

cated and 26 were prescribed psychotropic medication

[median number of medications 2 (S.D.=0.9) ; Table 2].

Study design

All participants were tested once, with females tested

during low levels of circulating oestrogen and pro-

gesterone in order to eliminate the confounding

variable of cycling hormone levels. Therefore, women

with a natural menstrual cycle were tested during the

early follicular phase (days 1–8 of cycle ; n=9 BD,

n=10 control), women prescribed the oral contra-

ceptive pill were tested during administration of

the inactive pills (n=2 BD, n=2 control), and post-

menopausal women (lack of period for>2 years) were

tested at any time (n=4 BD, n=4 control). Although

all women were tested during low levels of circulating

hormones, it is unclear whether the varying hormonal

conditions (natural cycle vs. contraceptive pill vs. post-

menopause) may be associated with endocrine effects

on PPI. However, there was a similar distribution of

control and BD women in each of the three hormonal

conditions.

Measures

PPI involved measuring the eye-blink component of

the acoustic startle response using the EMG Startle

System (San Diego Instruments, USA), which was

regularly calibrated (Quest SoundPro dB Meter, Quest

Technologies, USA). Electromyogram (EMG) activity

of the orbicularis oculi was recorded using two small

Ag/AgCl electrodes (electrolyte gel-filled) placed

under the right eye ; the reference electrode was at-

tached to the right mastoid (average impedance

<16 kV). The EMG system delivered acoustic stimuli

binaurally to the participant via headphones (Maico,

San Diego Instruments). Before being tested for PPI, all

participants refrained from smoking for >20 min and

Table 1. Demographic information

Bipolar disorder Control

Male (n=14) Female (n=15) Male (n=16) Female (n=16)

Age (yr) 45 (10.9) 41 (10.9) 40 (11.7) 41 (12.0)

Predicted IQ 105 (12.2) 108 (11.1) 111 (7.0) 112 (4.9)

Smoking status (Y/N) 6/7* 3/11 0/16 1/15

Handedness (R/L) 13/1 15/0 11/5 15/1

BPRS – – 26 (2.1) 27 (2.8)

Age at onset (yr) 28 (11.1) 20 (8.0)# – –

Illness duration (yr) 17 (8.8) 21 (12.1) – –

MRS 2 (3.6) 3 (3.8) – –

HAMD 6 (5.6) 8 (6.9) – –

PANSS

Total 44 (9.3) 44 (10.0) – –

Positive 11 (3.7) 11 (3.9) – –

Negative 10 (2.8) 9 (1.9) – –

General 23 (5.3) 24 (5.2) – –

Sodium valproate (Y/N) 8/6 (57%) 6/9 (40%) – –

Antipsychotics (Y/N) 10/4 (71%) 5/10 (33%)# – –

Lithium (Y/N) 3/11 (21%) 4/11 (27%) – –

Antidepressants (Y/N) 3/11 (21%) 8/7 (53%) – –

BPRS, Brief Psychiatric Rating Scale ; HAMD,Hamilton Depression Rating Scale ; MRS, Mania Rating Scale ; PANSS, Positive and

Negative Syndrome Scale.

Data represent mean (S.D.) except for smoking status and medication frequencies.

Age at onset was defined as the first appearance of symptoms. Predicted IQ was determined using the National Adult Reading

Test (NART). Smoking status (Yes/No) represents the number of participants that smoke regularly (i.e. every day), status was

not recorded for one male and one female participant with bipolar disorder. The medication frequencies (Yes/No) indicate the

number and percentage of participants within that group that were prescribed that medication.

* p<0.05, compared to controls ; # p<0.05, compared to males in the same group.

Gender differences in PPI in bipolar disorder 1251

underwent a hearing test indicating that they could

hear o40 dB. EMG activity was amplified (full scale

0.25), band-pass filtered (10–1000 Hz) and recorded

for 250 ms following stimulus onset (sample interval

1 ms). The startle amplitude output was in mV, where

1 mV=0.1 mV at the electrode.

The PPI task took 20 min to complete, during which

time participants were seated comfortably, instructed

to minimize movement, relax, ignore the sounds and

keep their eyes open during the task. The task began

with 3 min of 70-dB white noise (acclimation period),

which continued throughout the session. The partici-

pant was then presented with 67 acoustic stimuli in a

pseudo-random order at variable intervals (12–24 s,

average 16.5 s). There were 21 pulse-alone trials, i.e.

a startling pulse of 115 dB, presented for 40 ms.

The pulse-alone trials were grouped in three blocks :

(1) the first seven trials of the session, (2) seven trials

Table 2. Medications

Sodium

valproate

Antipsychotics

(CPZeq) Lithium Antidepressants Anticonvulsants Anxiolytics

Male

1 – – – – – –

2 – 150 Zu – – – –

3 1700 – – – – –

4 2000 285 Ri – – – –

5 – 670 Qu – – – Diazepam 10

6 – – 1250 – – –

7 1000 402 Qu – – – Oxazepam 30

8 1500 536 Qu – Citalopram 20 – –

9 1500 – – Citalopram 10 – –

10 1500 385 Ri & CPZ 1350 – – –

11 – 202.5 Ol 1250 – – –

12 500 67.5 Ol – – – –

13 1500 100 Ar – – Lamotrigine 200 –

14 – 405 Ol – Moclobemide 600 – –

Mean 1400 320 1283 – – –

(S.D.) (457) (195) (58)

Female

1 – – – – – –

2 – – – – – –

3 – 200 Am – Venlafaxine 450 Lamotrigine 400 –

4 – – 1500 – – –

5 1500 270 Ol – – – –

6 – 400 Ar 900 – – –

7 – – 500 – Carbamazepine 200 –

8 – – – Escitalopram 80 Lamotrigine 250 –

9 1500 402 Qu – Citalopram 20 – –

10 1400 – – – – –

11 1000 – – Venlafaxine 450 – –

12 – 16.75 Qu 900 Fluoxetine 40 – –

13 – – – Fluvoxamine 100 Carbamazepine 800 –

14 1000 – – – – –

15 1000 – – Escitalopram 10,

Mirtazapine 20

– –

Mean 1233 258 950 – – –

(S.D.) (258) (160) (412)

Am, Amisulpride ; Ar, aripiprazole ; CPZ, chlorpromazine ; Ol, olanzapine ; Qu, quetiapine ; Ri, risperidone ; Zu, zuclopenthixol.

Data represent dose (mg/day) of the different medications prescribed to the participants with bipolar disorder, except for the

antipsychotics which are expressed in chlorpromazine equivalents (CPZeq).


interspersed with the prepulse-pulse trials, (3) the last

seven trials. There were 42 prepulse-pulse trials con-

sisting of a 20-ms prepulse of 74, 78 and 86 dB (4, 8 and

16 dB above background) followed 60 or 120 ms later

by the startling pulse of 115 dB. The startling pulse

and the prepulse-pulse trials involved bursts of white

noise with near instantaneous rise-fall times. The

mean of the seven trials per stimulus type was used in

data analysis. There were also four trials where no

sound was presented (control trials).

All EMG recordings were screened for spontaneous

eye-blink activity and trials were excluded if excessive

EMG activity occurred during 20-ms post-stimulus

(baseline shifted >90 mV). Nine percent of trials were

excluded for control participants and 10% of trials for

BD patients. Raw EMG data were smoothed: rolling

average 3, filter order 4, pass frequency 350, response

criterion 2. The magnitude of the startle response was

defined as the peak EMG response within 20–100 ms

post-stimulus. One participant was classified as a

‘non-responder’ and excluded from any further data

analysis as the average startle amplitude (of the three

blocks) was <50 mV when accounting for the control

trials. The following measurements of the startle re-

sponse were conducted: PPI (where %PPI is) :

amplitude of block 2

pulse-alone trials

� �x

amplitude of

prepulse-pulse trials

� �

amplitude of block 2 pulse-alone trialsr100,

startle reactivity (amplitude of block 1 pulse-alone

trials), startle amplitude (amplitude of blocks 1–3),

habituation (decrease in the pulse-alone amplitudes

across blocks 1–3).

Data analysis

Group and gender differences in terms of demo-

graphic and clinical factors were examined using

Pearson’s x2, one-way ANOVA, independent-sample

t test or Mann–Whitney U test, as required using

SPSS software (SPSS Inc., USA). A p value of <0.05

was considered significant, where applicable the

Greenhouse–Geisser corrected p value was instead

reported.

According to the Kolmogorov–Smirnov statistic,

PPI data were normally distributed and therefore

analysed with a repeated-measures ANOVA. For PPI

data, the main effects and interactions were analysed

for group (control, BD), gender (male, female), stimu-

lus onset asynchrony (SOA; 60 or 120 ms) and pre-

pulse intensity (PP4, PP8, PP16). Startle data (i.e. blocks

1–3) were highly positively skewed (Kolmogorov–

Smirnov test, p<0.01 for each block) and had a

significant heterogeneity of variance (Levene’s test,

p<0.05). After log-transformation (Csomor et al. 2008),

startle amplitudes were normally distributed and

there was homogeneity of variance. For graphical

purposes the non-transformed startle data was pre-

sented. The %PPI was based on non-transformed

startle data. For startle amplitude and habituation,

the main effects and interactions were analysed for

group, gender and block (1–3). The between-subjects

variables were gender and group, while the within-

subjects, repeated–measures variables refer to the PPI

protocol (i.e. SOA, prepulse intensity, block). When

the three participants with moderate to severe de-

pression were removed, the PPI findings did not

change direction, therefore they were retained in the

analysis. Further, when the analysis was repeated with

handedness as an additional between-subjects vari-

able, handedness did not interact with PPI, nor did the

PPI findings change when the seven left-handed par-

ticipants were removed.

Using Pearson’s r correlation, the relationship be-

tween average PPI scores (60 and 120 ms; i.e. the

average of the three prepulse intensities for 60 and

120 ms) and/or startle amplitude, and each demo-

graphic and clinical variable, was examined across the

four groups individually. These variables included

BPRS, age, predicted IQ, age of onset, illness duration,

PANSS (total and subscales), MRS and HAMD. Due

to the large number of comparisons, the Bonferroni

correction was applied, therefore p<0.002 was con-

sidered significant. Correlations with medication

and PPI were only completed with the BD partici-

pants that were actively taking the medication of

interest (Table 2). Pearson’s r correlations were per-

formed on the mean dosage of chlorpromazine equi-

valents (CPZeq), sodium valproate and lithium, and

Spearman’s rho correlations were performed on the

medication frequencies for antipsychotics, antide-

pressants, sodium valproate and lithium. Similarly to

Barrett et al. (2005), we performed exploratory com-

parisons between patients being prescribed a certain

medication or not, and whether this changed PPI

levels. Based on previous literature suggesting that

smoking can influence PPI (Della Casa et al. 1998 ;

Postma et al. 2006), the effect of smoking status on PPI

was examined using Spearman’s rho correlation and

also by using smoking status as a covariate.

Results

Demographic variables (Tables 1 and 2)

Using one-way ANOVA, the four groups were not

significantly different in terms of age and predicted


full-scale IQ. There was a difference in the number

of smokers between the four groups [x2(3)=12.6,

p<0.01], which was significant when comparing male

BD and control participants [x2(1)=9.3, p<0.01], but

not female participants. Forty-six percent of male and

21% of female BD participants and 6% of female and

0% of male control participants were smokers. The

BPRS scores of the male and female control partici-

pants were not significantly different.

There were no significant gender differences in BD

patients in terms of illness duration, positive, negative,

general or total PANSS, MRS, HAMD, or mean dose of

medication (antipsychotic, sodium valproate, lithium).

There was a difference in medication frequency with

more male patients prescribed antipsychotics [x2(1)=4.2, p=0.04], but not for lithium, sodium valproate or

antidepressants. There was a significant difference in

terms of age of illness onset (U14,14=x2.1, p=0.04),

reflecting an earlier onset in women with BD (Table 1).

PPI

The 2 groupr2 genderr2 SOAr3 prepulse intensity

ANOVA revealed no main effect of group or gender.

There was a significant main effect of SOA (F1,57=71.4,

p<0.001) and prepulse intensity (F2,114=88.0, p<0.001), reflecting the expected increase in PPI (i.e.

greater reduction in startle) with increasing prepulse

intensity and increasing SOA (Fig. 1). There was an

SOArprepulse intensity interaction (F2,114=7.6, p<0.01), reflecting the increase in PPI, particularly at the

lower prepulse intensities, with increasing SOA. There

was an SOArprepulse intensityrgender interaction

(F2,114=5.3, p<0.01). Importantly, there was a signifi-

cant grouprSOA interaction (F1,57=8.8, p<0.01) and a

grouprgender interaction (F1,57=7.5, p<0.01), sug-

gesting that the groups exhibit different PPI depend-

ing on the SOA or gender, respectively.

In exploring the grouprgender interaction, a 2

groupr2 SOAr3 prepulse intensity ANOVA for

male participants demonstrated a trend for a group

effect (F1,28=3.7, p=0.06) and grouprSOA interaction

(F1,28=3.4, p=0.08), reflecting the tendency for BD

participants to have reduced PPI at the 60-ms SOA.

The ANOVA for female participants revealed a sig-

nificant grouprSOA interaction (F1,29=5.8, p=0.02)

and a trend for a group effect (F1,29=3.9, p=0.06),

reflecting the increased PPI in BD participants at the

120-ms SOA. Further, when comparing gender within

a group, there was a trend for a gender effect for con-

trols (F1,30=3.8, p=0.06) and BD (F1,27=3.6, p=0.07),

reflecting that female controls tended to have reduced

PPI compared to male controls, but male BD partici-

pants tended to have reduced PPI compared to female

BD participants, respectively (Fig. 2).

In exploring the grouprSOA interaction, a 2

groupr2 genderr3 prepulse intensity ANOVA at the

60-ms SOA demonstrated significant interactions of

grouprgender (F1,57=4.7, p=0.03) and prepulse in-

tensityrgender (F2,114=4.1, p=0.03). Examination of

the data (Fig. 2) suggests that male BD participants

had reduced PPI compared to male controls, while fe-

male control and BD participants showed similar PPI.

This observation was confirmed using post-hoc one-

way ANOVAs (male BD vs. male controls : F1,28=6.4,

80

40

0

–40

%P

PI

60 ms 120 ms

80

40

0

–40

60 ms 120 ms

Control: Males BD: Males

80

40

0

%P

PI

60 ms 120 ms

80

40

0

60 ms 120 ms

Control: Females BD: Females

SOA SOA

Fig. 1. Mean¡S.E.M. % prepulse inhibition (PPI) of healthy

control males (n=16) and females (n=16), and bipolar

disorder (BD) males (n=14) and females (n=15). %PPI is

shown with three levels of prepulse (PP) intensity [PP4 (%),

PP8 ( ) and PP16 (&) dB above 70 dB background] with

two levels of stimulus onset asynchrony (SOA) (60 and

120 ms).

60

40

20

0

Ave

rag

e %

PP

I

60 ms 120 ms

Males

*

60

40

20

060 ms 120 ms

Females

SOA SOA

*

Fig. 2. Mean¡S.E.M. average % prepulse inhibition (PPI) of

male and female participants that are healthy controls (%) or

participants with bipolar disorder (BD, &). Average %PPI is

the average of the three levels of prepulse intensity, and is

shown at two stimulus onset asynchrony (SOA) levels (60 and

120 ms) (* p<0.05 compared to controls).


p=0.02 ; female BD vs. female controls : p=0.7).

ANOVA for the 120-ms SOA also demonstrated a

significant grouprgender interaction (F1,57=6.7, p=0.01). One-way ANOVA comparing male control and

BD participants revealed no significant main effect of

group (p=0.4). In contrast, when comparing female

participants, BD participants showed significantly

greater PPI than controls (F1,29=11.4, p<0.01).

Startle amplitude

Startle reactivity (Fig. 3), as measured by the magni-

tude of block 1 pulse-alone trials, was different across

the groups depending on gender (grouprgender

interaction : F1,57=4.3, p=0.04). When comparing male

participants, there was a significant group effect

(F1,28=8.0, p<0.01), reflecting the reduced startle re-

activity in men with BD compared to controls ; there

was no significant difference when comparing female

participants.

When analysing all three blocks of startle amplitude

data, there was a significant main effect of block

(F2,114=109.2, p<0.001), reflecting the reduction in

startle amplitude after repeated administration of the

startling pulse (i.e. habituation; Fig. 3). There was no

blockrgroup interaction, reflecting the similar habi-

tuation across groups. There was a grouprgender

interaction (F1,57=4.5, p=0.04) and a trend for a group

effect (F1,57=3.1, p=0.08). Of interest, when examining

block 2 (i.e. the startle pulses used to calculate PPI)

there was a grouprgender interaction (F1,57=5.6,

p=0.02), reflecting the reduced startle amplitude in

men with BD compared to male controls (F1,28=9.8,

p<0.01).

Given that the significant difference in startle

amplitude between male BD patients and controls

may have influenced PPI, we repeated the analysis on

a sample of participants with matched startle ampli-

tude: male BD patients (n=9, mean=781, S.E.M.=121)

and male controls (n=9, mean=778, S.E.M.=99). PPI

analysis revealed a significant main effect of group

(F1,16=5.4, p=0.03), which remained significant at the

60-ms SOA (F1,16=5.9, p=0.03), but not at 120 ms.

Clinical and demographic correlates

There was a trend for a positive correlation between

average PPI at the 60-ms and the 120-ms SOA in male

(r=0.69, p=0.003) and female controls (r=0.62, p=0.01), but not in BD. There was no correlation between

average PPI and startle data (either average startle,

block 2 original or log-transformed) in any of the four

groups, or between average startle and any demo-

graphic or clinical variable. In all participants there

were no significant correlations between PPI (at either

SOA) and demographic variables. In male BD partici-

pants there was a trend for a correlation between

60-ms average PPI and age of onset (r=0.67, p=0.009).

Importantly, there were no significant correlations

between PPI and symptoms (PANSS, HAMD, MRS) or

any medication (dosages : CPZeq, sodium valproate,

lithium; frequencies : antipsychotics, sodium valpro-

ate, lithium, antidepressants). When all BD patients

were combined, there was no difference in the effect of

each medication on PPI, for either medication type.

To examine the effects of smoking on PPI, smoking

status was added as a covariate to the PPI analyses.

There was no significant effect of smoking, nor did

it change the direction of our findings. The analyses

were repeated comparing men and women in both

groups for non-smokers only and the findings were

similar to the whole-group results. Using Spearman’s

rho correlation, we found that in female BD partici-

pants there was a negative correlation between 60-ms

average PPI and cigarette smoking (r=x0.58, p=0.03) ; however, this does not explain the PPI effect that

was observed in these participants at the 120-ms SOA.

3000

2000

1000

0

Am

plit

ud

e

3000

2000

1000

01 2 3

Am

plit

ud

e

ConM ConFBDM BDF

Startle reactivity

Startle habituation

Group

*

Block

Con MBD MCon FBD F

Fig. 3.Mean¡S.E.M. startle responses (mV) in the four groups :

healthy control males (Con M, n=16) and females (Con F,

n=16), and bipolar disorder (BD) males (BD M, n=14) and

females (BD F, n=15). Startle reactivity refers to the startle

response to the first block of seven 115 dB pulse-alone trials

(top panel). Startle habituation refers to the decrease in the

startle response to the pulse-alone trials across blocks 1, 2

and 3.


Discussion

The present study examined gender differences in

PPI in BD. The main finding was that men and women

with BD both show changes in PPI compared to

healthy controls ; however, in the opposite direction.

Specifically, compared to controls, men with BD

showed reduced PPI, while women with BD had in-

creased PPI.

Our finding of disrupted PPI in men with BD was

consistent with previous literature showing a PPI dis-

ruption in BD (Giakoumaki et al. 2007 ; Perry et al.

2001). In both of these previous studies, the PPI dis-

ruption was greater at the 60-ms than the 120-ms SOA,

similar to the present results. The present finding also

parallels that of patients with schizophrenia, where

men with schizophrenia have reduced PPI compared

to male controls (Braff et al. 2001; Kumari et al. 2004).

A PPI disruption has been suggested to be related to

some symptoms of mental illness, such as psychosis,

mania or thought disturbance (Perry & Braff, 1994;

Perry et al. 2001). However, in the present study and

the Giakoumaki et al. (2007) study, PPI was not cor-

related with psychopathology, although this was not

surprising as we recruited patients with low levels

of psychopathology. Not all the previous literature

supports the present findings ; Carroll et al. (2007) and

Barrett et al. (2005) found that there was no change in

PPI in BD compared to controls. This may be ex-

plained by a number of methodological and sample

differences. For example, the Carroll et al. (2007) study

used a low-intensity startling pulse (95 dB) and a long

duration prepulse (50 ms) which may have caused a

floor effect in their study; they also tested sympto-

matic patients. The Barrett et al. (2005) study measured

PPI using the left eye, while the majority of PPI re-

search tests the right eye. Recently, it has been re-

ported that PPI can be affected by startle magnitude,

with a reduction in startle amplitude resulting in

an increase in PPI (Csomor et al. 2008). However, this

does not appear to be a confounding factor in the

present study as male BD patients showed reduced

startle amplitude and reduced PPI. Further, when

male participants were matched for startle, there was

still a significant disruption of PPI in male BD patients

compared to male controls.

Strikingly, the opposite effect was observed for fe-

male participants, where women with BD showed in-

creased PPI compared to female controls. This finding

was not supported by the previous PPI literature in

BD, where the majority of participants have been men

(Perry et al. 2001) or there was an equal mix of men

and women (Barrett et al. 2005 ; Carroll et al. 2007;

Giakoumaki et al. 2007). It is possible that in some

studies the decrease in PPI in men with BD may have

predominated, while in the other studies an increase

in PPI in women was counterbalanced by a decrease in

PPI in men with the net effect being no change in PPI.

However, the Giakoumaki et al. (2007) study used

gender as a factor in their statistical analyses, but

found no significant effects of gender. The previous

studies of PPI in BD did not report the stage of the

menstrual cycle the women were in when tested for

PPI. Given that PPI can vary in women across the

menstrual cycle (Jovanovic et al. 2004 ; Swerdlow et al.

1997), testing women at various stages may also

lead to a net effect of no change in PPI. In the present

study, both women with BD and control women were

tested at a stage with low circulating oestrogen and

progesterone. Kumari et al. (2004) speculated that

the gender difference observed in their PPI study of

schizophrenia patients may have been because the

women were less symptomatic than the men. In the

present study, there was no difference between

the men and women on any of the symptom ratings.

However, it is possible, that a difference in the fre-

quency or history of psychotic episodes may influence

PPI. The two studies showing a disruption of PPI in

BD tested 100% acutely psychotic patients (Perry et al.

2001) or 50% of patients with a history of psychotic

symptoms (Giakoumaki et al. 2007). In contrast, the

two studies showing no change in PPI in BD were

Carroll et al. (2007), who found no relationship be-

tween psychosis and PPI, and Barrett et al. (2005),

who did not report on psychotic features. The present

study found no correlation between the Positive

PANSS subscale and PPI in BD patients. Future stu-

dies should, however, specifically examine the pres-

ence of psychotic features (past and present) and their

influence on PPI.

As was also speculated by Kumari et al. (2004),

a simple explanation for the increased PPI in female

BD patients was that the control women showed rela-

tively low levels of PPI compared to other studies.

However, within the present study the four groups

had similar PPI levels, i.e. within a close range.

Further, the increase observed in female BD patients

was even greater than the male participants (average

PPI at 120-ms SOA: female BD 49%, male control 42%,

male BD 35%), where males generally have greater

PPI than females (Swerdlow et al. 1993). Alternatively,

medication may have had a greater effect in women

with BD. Medication can influence PPI ; some studies,

but not all, have found that antipsychotics can nor-

malize PPI in schizophrenia patients (Braff et al. 2001).

In the present study, it is unlikely that antipsychotic


medication is responsible for the PPI increase in fe-

male BD patients, as only a small number of women

were prescribed an antipsychotic (5/15 patients).

Further, the majority of our male BD patients were

prescribed antipsychotics (10/14 patients) and they

still showed a disruption of PPI. Barrett et al. (2005)

suggested that BD patients prescribed sodium val-

proate (n=6) had reduced PPI compared to those who

were not taking sodium valproate (n=17). Our results

did not confirm this finding, where we had a fairly

equal distribution of patients prescribed vs. not pre-

scribed sodium valproate (Table 1). In our sample,

most patients were on multiple and various medica-

tions (Table 2), thus making it very difficult to extract

the effect of medication on PPI. Overall, the present

study found no correlation between medication and

PPI. Future research in drug-naive BD patients should

investigate the role of medication on PPI. Another

possible limitation of the present results is that we

did not match participants for smoking status, which

may influence PPI (Della Casa et al. 1998 ; Postma et al.

2006). Although there were more male smokers, fur-

ther analysis revealed no significant effect of smoking

status on PPI.

An increase in PPI in humans has been seen in a

number of studies, e.g. after treatment with nicotine

(Kumari et al. 1997), the indirect dopamine receptor

agonist, amantadine (Swerdlow et al. 2002), the

NMDA receptor antagonist, ketamine (Abel et al.

2003 ; Duncan et al. 2001 ; Heekeren et al. 2007), the

serotonin (5-HT) releaser, MDMA (Liechti et al.

2001 ; Vollenweider et al. 1999), the 5-HT2A receptor

agonist, psilocybin (Gouzoulis-Mayfrank et al. 1998 ;

Vollenweider et al. 2007) and by atypical antipsy-

chotics including quetiapine (Swerdlow et al. 2006b)

and clozapine (Vollenweider et al. 2006). Of these

studies, few included female participants and only one

was gender-balanced (Vollenweider et al. 2007). In the

latter study, psilocybin treatment increased PPI at a

long SOA (120 ms), but a PPI reduction occurred at a

short SOA (30 ms). Thus, it is possible that the 5-HT2A

receptor may be mediating the PPI increase in BD

women observed in the present study. There is some

evidence for a role of 5-HT2A receptors in BD (Lopez-

Figueroa et al. 2004 ; Pandey et al. 2003; Ranade et al.

2003). Other 5-HT receptor subtypes or other neuro-

transmitters may also be involved and therefore the

mechanism by which a PPI increase occurred remains

unknown and warrants further investigation.

In the present study, the PPI disruption in men with

BD occurred only at the 60-ms SOA, while the PPI in-

crease in women with BD occurred at the 120-ms SOA.

Using different SOAs can result in different effects on

PPI, with the optimal SOA (maximum inhibition) typ-

ically used in human PPI experiments being 120 ms

(Braff et al. 2001). While PPI is generally thought of as

an automatic process, at an SOA greater than 120 ms

attentional influences may play a role (Braff et al. 2001 ;

Filion et al. 1993). Future studies examining gender

differences in BD are needed whereby attention to

prepulses is controlled. Further investigation is also

required in order to clarify the different roles of vary-

ing SOAs on PPI.

In conclusion, the present results showed reduced

PPI in men and increased PPI in women with BD,

compared to controls. Although we have proposed a

number of mechanisms underlying these opposite

effects on PPI, further studies are required to clarify

which of these, if any, is responsible. The fact that men

and women with BD showed opposite effects in PPI

has implications for the interpretation of past and

future BD studies. In particular, combining men and

women in one group might be masking two opposite

effects and this highlights the importance of acknowl-

edging gender differences in PPI studies.

Acknowledgements

The authors gratefully acknowledge the financial

support of the J. & P. Clemenger Trust and the

National Health and Medical Research Council of

Australia (A. Gogos, Peter Doherty Fellowship, ID

435690). This research was also supported by Oper-

ational Infrastructure Support (OIS) from the Victorian

State Government. We acknowledge the assistance of

Alison O’Regan in administering the SCID-PANSS

and Nicole Joshua for assistance with recruitment.

Statement of Interest

None.

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