Review

ee relatives

patients. Earlier age of onset was associated with verbal memory impairment and psychomotor slowing.

Journal of Affective Disorders 113 (2009) 120www.elsevier.com/locate/jadLimitation: Data related to some confounding variables was not reported in a substantial number of extracted studies.Conclusions: Response inhibition deficit, a potential marker of ventral prefrontal dysfunction, seems to be the most prominentendophenotype of BD. The cognitive endophenotype of BD also appears to involve fronto-temporal and fronto-limbic relatedcognitive impairments. Processing speed impairment is related, at least partly, to medication effects indicating the influence ofconfounding factors rather than genetic susceptibility. Patterns of sustained attention and processing speed impairments differ fromschizophrenia. Future work in this area should differentiate cognitive deficits associated with disease genotype from impairmentsrelated to other confounding factors. 2008 Elsevier B.V. All rights reserved.

Keywords: Bipolar disorder; Cognitive; Endophenotype; Memory; Executive functionEmre Bora a,, Murat Yucel a,b, Christos Pantelis a

a Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, VIC. Australiab ORYGEN Research Centre, Melbourne, VIC. Australia

Received 24 April 2008; received in revised form 10 June 2008; accepted 10 June 2008Available online 5 August 2008

Abstract

Background: Our aim was to delineate neuropsychological deficits related to genetic susceptibility, illness process and iatrogenicfactors in bipolar disorder (BD).Methods: Following an extensive publication search on several databases, meta-analyses were conducted for 18 cognitive variablesin studies that compared performances of euthymic BD patients (45 studies; 1423 subjects) or first-degree relatives of BD patients(17 studies; 443 subjects) with healthy controls. The effect of demographic variables and confounding factors like age of onset,duration of illness and medication status were analysed using the method of meta-regression.Results: While response inhibition, set shifting, executive function, verbal memory and sustained attention deficits were commonfeatures for both patient (medium to large effect sizes) and relative groups (small to medium effect sizes), processing speed, visualmemory and verbal fluency deficits were only observed in patients. Medication effects contributed to psychomotor slowing in BDfirst-degrCognitive endophenotypes of bipolar disorder: A meta-analysis ofneuropsychological deficits in euthymic patients and their Corresponding author. Melbourne Neuropsychiatry Centre, University of Melbourne, Alan Gilbert Building, NNF level 3, Carlton, VIC, 3053,Australia.

E-mail address: emrebora@hotmail.com (E. Bora).

0165-0327/$ - see front matter 2008 Elsevier B.V. All rights reserved.doi:10.1016/j.jad.2008.06.009

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fectiv1. Introduction

Endophenotypes are intermediate phenotypes thatare considered a more promising index of underlyinggenetic liability than the illness itself. To be acceptedas an endophenotype, intermediate phenotypes mustmeet several criteria proposed by Gottesman andGould (2003). Endophenotypes should be associatedwith illness, they should be heritable and they shouldco-segregate within families with illness. There aretwo additional conditions needed to meet criteria foran endophenotype: (a) the endophenotype must bestate independent, it must be demonstrable in remittedpatients. (b) The endophenotypes should be morefrequent in unaffected relatives of patients comparedto the general population. In this context, while thereis convincing evidence regarding the value ofcognitive deficits as putative endophenotypes ofschizophrenia (Gur et al., 2007; Pantelis et al., inpress; Snitz et al., 2006), the value of such markers asendophenotypes of bipolar disorder (BD) is a largelyunderstudied subject.

With respect to the first criterion (that markers arestate independent and observable in remitted patients),the most consistent cognitive findings that may

patients with BD are verbal memory, executive functionand sustained attention deficits. Recently, three meta-analytic reports (Arts et al., 2008; Robinson et al., 2006;Torres et al., 2007) provided further evidence forcognitive impairment in BD. However, these findingsshould be interpreted cautiously, as it is quite likely thatconfounding factors such as medication, chronicity andsubthreshold affective symptoms are also contributingto the observed findings. Furthermore, it is still notknown whether these findings are signs of multipleindependent cognitive impairments or whether they arereflections of an underlying a single more basiccognitive abnormality (for example, psychomotorspeed or working memory).

Regarding the second criterion (that markers are morefrequently observed in unaffected relatives of patients incomparison to the general population), only a handful ofstudies have investigated cognitive deficits of unaffectedrelatives of affected patients. The findings of these studieshave been less consistent than those conducted in affectedpatients themselves. For example, while several studiessuggest that verbal memory deficits are themost prominentfindings in relatives ofBDpatients (Gourovitch et al., 1999;Keri et al., 2001), other studies do not support this notion(Ferrier et al., 2004; Clark et al., 2005a,b). The evidenceContents

1. Introduction . . . . . . . . . . . . . . . . . . . . . . .2. Method . . . . . . . . . . . . . . . . . . . . . . . . .

2.1. Neuropsychological variables . . . . . . . . . .2.1.1. Verbal learning and memory . . . . . .2.1.2. Visual memory . . . . . . . . . . . . .2.1.3. Sustained attention . . . . . . . . . . .2.1.4. Processing speed . . . . . . . . . . . .2.1.5. Verbal fluency . . . . . . . . . . . . .2.1.6. Set shifting . . . . . . . . . . . . . . .2.1.7. Working memory . . . . . . . . . . . .2.1.8. Response inhibition . . . . . . . . . . .2.1.9. Visuospatial abilities . . . . . . . . . .2.1.10. General intelligence . . . . . . . . . .

2.2. Statistical analyses . . . . . . . . . . . . . . . .3. Results . . . . . . . . . . . . . . . . . . . . . . . . .

3.1. Remission . . . . . . . . . . . . . . . . . . . .3.2. Relatives . . . . . . . . . . . . . . . . . . . . .

4. Discussion . . . . . . . . . . . . . . . . . . . . . . .Role of funding source . . . . . . . . . . . . . . . . . . . .Conflict of interest . . . . . . . . . . . . . . . . . . . . . .Acknowledgements. . . . . . . . . . . . . . . . . . . . . .References . . . . . . . . . . . . . . . . . . . . . . . . . .

2 E. Bora et al. / Journal of Afrepresent potential endophenotypes within euthymic. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

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e Disorders 113 (2009) 120regarding executive dysfunction appears to be similarly

fectiveinconsistent. For example, Frangou et al. (2005a,b)suggested that executive functions attributable to theventral prefrontal cortex (VPFC) but not dorsal prefrontalcortex (DPFC) are associated with genetic risk for BD,however some other studies (Clark et al., 2005a,b) do notsupport this proposal. One important limitation of relativestudies is sample size wherein studies are typicallycharacterised by small numbers.

Overall, while verbal memory, executive functionand sustained attention deficits are frequently reported,the nature and magnitude of such impairments, as wellas their consistency can vary markedly across studiesdue to differences in sample characteristics andresearch methodologies. In this context, meta-analysisis a useful tool for systematically combining allresearch in this area to identify cognitive deficitsshowing the most robust changes in BD. It is also auseful methodology to workout the effect of confound-ing factors. In this way, we may be able to betterunderstand the pervasive cognitive disturbances thatcan't be explained by the effects of iatrogenic factors orby the neurotoxic effects of recurrent episodes, as wellas their neural underpinnings in bipolar disorder. Todate, only one meta-analytic study has analysed thestudies in first-degree relatives of BD. To our knowl-edge, the effects of clinical and iatrogenic confoundershave not been studied by meta-analytic methodspreviously. Our aim was to investigate the possibilitythat there exist cognitive endophenotypes of BD. To dothis we used published data in euthymic patients andfirst-degree relatives.

2. Method

The relevant articles were searched using Pubmed,Medline Web of Science and Psychinfo with thefollowing search terms: bipolar disorder (or manicdepress) and cognit, neuropsych, attention, mem-ory, learning, executive. The search was limited tostudies published in peer-reviewed journals in Englishavailable between 1995 and October 2007. Inclusioncriteria for studies were that they: (1) includedneuropsychological data pertaining to a remitted adultBD patient group or first-degree relatives of patientswith BD; (2) included a healthy control group (3)reported mean test scores and standard deviations (orstandard errors) of neuropsychological measures forhealthy controls and BD patients or their unaffectedrelatives: (4) included at least one cognitive measurethat was studied in at least three studies in both BDpatients and unaffected relatives of BD patients.

E. Bora et al. / Journal of AfFollowing initial publication search, the titles andabstracts of articles were assessed for potentialsuitability and references of these articles were alsocrosschecked for further relevant articles. This stepidentified 185 studies. When these articles wereexamined further, only 68 of themmet all four inclusioncriteria. Another 12 studies were excluded since theywere based on the same sample with other includedstudies. Finally 56 studies that compared cognitiveperformances of patients with BD (45 studies) orrelatives of BD patients (17 studies) with healthycontrols were included in the current meta-analysis(Tables 1 and 2) (Altshuler et al., 2004; Antila et al.,2007; Balanza-Martinez et al., 2005; Bora et al., 2007;Bora et al., 2008; Brambilla et al., 2007; Cavanaghet al., 2002; Christensen et al., 2006; Clark et al., 2002;Clark et al., 2005a,b; Clark et al., 2005b; Deckersbachet al., 2004a; Deckersbach et al., 2004b; Dittmann et al.,2007; Dixon et al., 2004; El-Badri et al., 2001; Ferrieret al., 1999; Ferrier et al., 2004; Fleck et al., 2003;Frangou et al., 2005a; Frangou et al., 2005b; Goswamiet al., 2006; Gourovitch et al., 1999; Harmer et al.,2002; Hawkins et al., 1997; Jones et al., 1994; Kayaet al., 2007; Keri et al., 2001; Kerr et al., 2005;Kieseppa et al., 2005; Klimes-Dougan et al., 2006;Kolur et al., 2006; Krabbendam et al., 2000; Kremenet al., 1998; Martinez-Aran et al., 2007; McIntosh et al.,2005; Mur et al., 2007; Nehra et al., 2006; Paradisoet al., 1997; Pirkola et al., 2005; Rocca et al., 2008;Rossi et al., 2000; Schouws et al., 2007; Senturk et al.,2007; Smith et al., 2006; Sobczak et al., 2003; Stoddartet al., 2007; Swann et al., 2003; Szoke et al., 2006;Thompson et al., 2005; Thompson et al., 2007; VanGorp et al., 1998; Van Gorp et al., 1999; Varga et al.,2006; Zalla et al., 2004; Zubieta et al., 2001).

2.1. Neuropsychological variables

2.1.1. Verbal learning and memoryEffect sizes of 4 different measures of verbal memory

were included in the meta-analysis (Learning, immedi-ate recall, delayed recall and recognition). These scoreswere derived from the following tests: Rey AuditoryVerbal Learning Test (RAVLT) (Rey, 1964), CaliforniaVerbal Learning Test (CVLT) (Delis et al., 1987), VisualVerbal Learning Test (VVT) (Lezak, 2005).

2.1.2. Visual memoryRey Osterreich Complex Figure (ROCF) (Rey, 1941)

and WMS-R (Wechsler Memory Scale-Revised) Visualmemory (Wechsler, 1987) were used to assess visualmemory skills. For both tests, only delayed recall scores

3Disorders 113 (2009) 120were extracted.

Table 1Studies with bipolar patients included in the meta-analysis

Study Groups Matched Cognitive tests d a

Jones et al. (1994) (13) 26 BD Gender DSST 0.4716 HC Stroop 0.46

CPT commission 0.50CPT commission 0.55Visual memory recall 0.47

Paradiso et al. (1997) (14) 11 BD Gender DSST 0.6519 HC Stroop 0.55

TMT-A 0.69TMT-B 0.19

Hawkins et al. (1997) (15) 22 BD Age, edu, gender DSST 0.8222 HC TMT-A 0.54

TMT-B 0.78Van Gorp et al. (1998) (16) 13 BD Age, edu, IQ Fluency 0.11

22 HC WCST cat 1.01WCST per 0.95Stroop 0.08TMT-A 0.32TMT-B 0.24Verbal learning 0.96Immediate recall 0.70Delayed recall 0.52Visual copy 0.09Visual memory recall 0.25

Ferrier et al., (1999) (17) 41 BD Premorbid IQ Fluency 0.6720 HC Age DSST 0.59

TMT-A 0.55TMT-B 0.86CPT commission 0.21Rey Learning 0.68Digit span forwards 0.21Digit Span backwards 0.70Visual copy 0.53Visual memory recall 0.77

Van Gorp et al. (1999) (18) 18 BD Age, edu, IQ CVLT recognition 0.1720 HC

Krabbendam et al. (2000) (19) 22 BD Education, age Fluency 0.5422 HC Verbal learning 0.94

Delayed recall 0.94Verbal recognition 0.50Stroop 0.67DSST 1.12

Rossi et al., 2000 (20) 66 HC - WCST cat 0.8240 BD WCST per 0.69

El-Badri et al. (2001) (21) 29 BD Age, IQ Fluency 0.4226 HC TMT-B 0.80

DSST 0.73Zubieta et al. (2001) (22) 15 BD Age, education Fluency 0.77

Ethnicity, IQ Stroop 1.12All patients has a history of psychotic episodes CPT commission 0.97

CPT commission 1.41WCST cat 0.84WCST per 1.52Visual memory recall 0.42

Cavanagh et al. (2002) (23) 20 BD Age, gender, premorbid IQ Fluency 0.3120 HC Stroop 0.61

Verbal learning 1.06Delayed recall 0.96Verbal recognition 0.62

4 E. Bora et al. / Journal of Affective Disorders 113 (2009) 120

Table 1 (continued)

Study Groups Matched Cognitive tests d a

Clark et al. (2002) (24) 30 BD Gender, edu, IQ, age Verbal learning 0.7430 HC Immediate recall 0.44

Delayed recall 0.16Verbal recognition 0.29CPT commission 0.96CPT commission 0.18CANTAB ED errors 0.71

Harmer et al. (2002) (25) 19 BD Age, edu, premorbid IQ CPT commission 1.0119 HC CPT commission 0.04

Fleck et al., (2003) (26) 14 BD Gender, age, edu Verbal learning 1.2540 HC Immediate recall 1.01

Delayed recall 0.77Verbal recognition 0.00

Swann et al. (2003) (27) 22 BD ? CPT commission 0.7135 HC CPT commission 0.22

Altshuler et al. (2004) (28) 40 BD Education, age Fluency 0.1622 HC Gender WCST cat 0.89

WCST per 0.77TMT-A 0.39TMT-B 0.40Stroop, 0.41Verbal learning 0.91Immediate recall 0.75Delayed recall 0.78Verbal recognition 0.22Visual copy 0.30Visual memory recall 0.57

Deckersbach et al. (2004a,b) (29) 30 BD Education, age Verbal learning 2.0330 HC Gender Immediate recall 1.40

Delayed recall 1.67Verbal recognition 0.64

Deckersbach et al. (2004a,b) (30) 25 BD Education, age Visual copy 0.0625 HC Gender Visual memory recall 0.70

Dixon et al. (2004) (31) 15 BD Gender, age Fluency 0.1730 HC Stroop 0.72

Zalla et al. (2004) (32) 37 BD Gender, age Stroop 1.1720 HC TMT-A 0.61

TMT-B 0.83WCST cat 0.44WCST per 0.72

Balanza-Martinez et al. (2005) (33) 15 BD Gender, age Fluency 1.2826 HC DSST 1.05

Stroop 1.62TMT-A 0.68TMT-B 0.89WCST cat 1.48WCST per 1.67

Clark et al. (2005a,b) (34) 15 BD IQ, age, gender CPT commission 1.0015 HC

Frangou et al. (2005a,b) (35) 44 BD Gender, age premorbid IQ Fluency 0.8844 HC WCST cat 0.25

WCST per 0.38Stroop 0.57Visual memory recall 0.60

Kerr et al. (2005) (36) 15 BD Gender, premorbid IQ Stroop 1.7818 HC

Kieseppa et al. (2005) (37) 26 BD Estimated IQ, age Verbal learning 0.43114 HC Delayed recall 0.60

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5E. Bora et al. / Journal of Affective Disorders 113 (2009) 120

Table 1 (continued)

Study Groups Matched Cognitive tests d a

Kieseppa et al. (2005) (37) Digit span Backwards 0.37DSST 0.64Visual memory recall 1.08

McIntosh et al. (2005) (38) 47 BD Premorbid IQ Fluency 0.7850 HC DSST 1.39

Pirkola et al. (2005) (39) 22 BD Gender, edu, premorb IQ Digit span forwards 0.36100 HC Digit span backwards 0.41

Thompson et al. (2005) (40) 63 BD Age, gender, IQ, edu Fluency 0.3663 HC TMT-A 0.47

TMT-B 0.23DSST 0.91Stroop 0.58Digit span backwards 0.37Digit span forwards 0.05Verbal learning 0.59Immediate recall 0.53Delayed recall 0.53Verbal recognition 0.56CPT commission 0.63CPT commission 0.33

Goswami et al. (2006) (41) 37 BD Age, gender, education TMT-A 0.5437 HC TMT-B 1.99

Digit span backwards 2.28Digit span forwards 0.50Verbal learning 0.69Immediate recall 0.30Delayed recall 0.41DSST 0.19

Kolur et al. (2006) (42) 30 BD Education, age WCST cat 2.5930 HC Gender WCST per 1.96

Stroop 1.86TMT-A 1.31TMT-B 1.93CPT commission 1.35CPT commission 0.40

Nehra et al. (2006) (43) 46 BD Gender, Fluency 0.8520 HC TMT-A 0.76

TMT-B 0.81WCST cat 0.09WCST per 0.08

Smith et al. (2006) (44) 21 BD Age, gender, epre IQ Verbal learning 1.0933 HC Immediate recall 0.95

Delayed recall 0.84Recog 0.90Stroop 0.81TMT-A 1.56TMT-B 1.52

Szoke et al. (2006) (45) 95 BD Age TMT-A 0.6048 HC TMT-B 0.61

WCST per 0.34Varga et al. (2006) (46) 19 BD Edu, gender TMT-A 0.53

31 HC TMT-B 1.18Verbal learning 1.02Immediate recall 1.53Delayed recall 1.04Stroop 0.71WCST cat 0.15WCST per 0.55DSST 0.54

6 E. Bora et al. / Journal of Affective Disorders 113 (2009) 120

Table 1 (continued)

Study Groups Matched Cognitive tests d a

Bora et al. (2007) (47) 65 BD Gender, age, edu Fluency 0.7830 HC Stroop 0.73

TMT-A 0.68TMT-B 0.84CPT commission 0.67CPT commission 0.58WCST cat 0.62WCST per 0.57Verbal learning 0.57Immediate recall 0.73Delayed recall 0.63Verbal recognition 0.54

Brambilla et al. (2007) (48) 15 BD Gender, age CPT commission 1.1426 HC CPT commission 0.33

Dittmann et al. (2007) (49) 55 BD Age, edu, gender TMT-A 0.4517 HC TMT-B 0.50

Kaya et al. (2007) (50) 43 BD Gender, age, edu AVLT learning 1.0122 HC AVLT delayed 1.30

AVLT recog 0.19Stroop 0.27

Martinez-Aran et al. (2007) (51) 77 BD Age, education, gender Fluency 0.3935 HC WCST cat 0.28

WCST per 0.56Verbal learning 0.67Immediate recall 0.55Delayed recall 0.88Verbal recognition 0.56Stroop 0.57TMT-A 0.90TMT-B 0.60Digit Span forwards 0.77Digit span backwards 0.94

Mur et al. (2007) (52) 44 BD Age, gender Fluency 0.9146 HC WCST cat 0.95

WCST per 0.73Digit span forward 0.78Digit span backwards 0.97Stroop 0.90Verbal learning 0.49Immediate recall 0.43Delayed recall 0.65Verbal recognition 0.48Visual memory recall 0.23TMT-A 0.97TMT-B 1.05

Rocca et al. (2008) (53) 25 BD Age Fluency 0.8731 BD WCST cat 0.08

WCST per 0.04Stroop 0.01

Schouws et al. (2007) (54) 15 BD Edu, gender, age Fluency 1.2815 HC TMT-A 0.64

TMT-B 0.65Stroop 1.08Digit span forwards 0.31Digit span backwards 0.52Verbal learning 1.30

Senturk et al. (2007) (55) 28 BD Edu, gender WCST cat 0.5829 HC WCST per 0.67

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7E. Bora et al. / Journal of Affective Disorders 113 (2009) 120

er, ag

fectiv2.1.3. Sustained attentionTo assess sustained attention continuous performance

tests (CPT) (Clark and Goodwin, 2004) were used.Omission error and commission error scores of CPTtasks were included in this study. Target sensitivityindexes that are dependent on both omission andcommission errors were not included. Reaction timemeasures were also not included since there was notenough data for the relatives of BD patients.

2.1.4. Processing speedTwo different effect sizes were calculated to analyse

processing speed abilities.Time to complete the part A of the Trail Making Test

(TMT-A) (Reitan, 1958) and the Digit Symbol Sub-stitution test and symbol digit modalities test (DSST).

2.1.5. Verbal fluencyAmeasure of phonetic fluency (FAS) was included in

the current meta-analysis (Lezak, 1995). Categoryfluency tasks were not included since there was nosufficient study for the relatives of the patients with BD.

Table 1 (continued)

Study Groups Matched

Senturk et al. (2007) (55)Stoddart et al. (2007) (56) 22 BD Gender

40 HC

Thompson et al. (2007) (57) 50 BD IQ, edu, gend57 HC

a =Cohen d.

8 E. Bora et al. / Journal of Af2.1.6. Set shiftingSet shifting is the ability to change the cognitive

strategies in response to change in the environment. Toassess the impairment in the set shifting abilities twodifferent tests was included into the current meta-analysis:

Trail Making TestPart B (TMT-B) (Reitan, 1958):This test is a measure of set shifting and processingspeed.

Wisconsin Cart Sorting Test (WCST) (Heaton,1981): Perseverative errors scores of this test wereused as a measure of set shifting. A measure ofCambridge Neuropsychological Test Automated Battery(CANTAB) (Downes et al., 1989) extradimensional/intradimensional task (extradimensional shifting errors)was also involved with this task. Number of categoriesachieved scores of WCSTwas involved as a measure ofrule discovery.

2.1.7. Working memoryAs a measure of working memory Backwards digit

span of the WAIS-R Digit Span (Wechsler, 1987) wasused.

2.1.8. Response inhibitionResponse inhibition refers to the suppression of

actions that are inappropriate in a given context. In thismeta-analysis, interference score (time to completion) ofthe Stroop Colour-Word test (Lezak, 1995) was used toassess response inhibition deficits.

2.1.9. Visuospatial abilitiesROCF copy score (Rey, 1941) was included for

analysing visuospatial abilities.

2.1.10. General intelligenceWAIS-R (Wechsler Adult Intelligence Scale-

Revised) (Wechsler, 1981) full Scale IQ and its shorter

Cognitive tests d a

DSST 0.65Stroop 1.29TMT-A 0.90TMT-B 1.23

e Fluency 0.35Stroop 0.58Digit span backwards 0.40Digit span forwards 0.05

e Disorders 113 (2009) 120versions were used to assess current IQ abilities. Foranalysing premorbid IQ, effect sizes of the NART(National Adult Reading Test) (Nelson, 1982) and theWAIS Vocabulary subtask (premorbid IQ) wereincluded.

For the purpose of the study, tasks measuring similarconstructs were assessed together. For example, wecombined the following: (a) RAVLT, CVLT and VVT,(b) WCST perseverative errors and CANTAB extra-dimensional error scores, (c) Digit Symbol Substitutiontest and symbol digit modalities test, (d) ROCF andWMS visual memory. Identical scores (omission andcommission error scores) from various different ver-sions of sustained attention tasks were also includedtogether. Since different studies reported different

Table 2Studies with relatives of bipolar patients included in the meta-analysis

Study Groups Matched Cognitive tests d a

Kremen et al. (1998) 15 BD Gender, age DSST 0.0544 HC edu Stroop 0.42

TMT-A 0.28TMT-B 0.11WCST cat 0.45WCST per 0.09Visual copy 0.24Visual memory recall 0.34

Gourovitch et al. (1999) 7 BD Fluency 0.2815 HC TMT-A 0.10

TMT-B 0.01Verbal learning 0.73Immediate recall 0.32Delayed recall 1.15Verbal recognition 0.92WCST cat 0.00WCST per 0.52Dig span forwards 1.16Digit Span backwards 0.97CPT commission 0.32Visual copy 0.04Visual memory recall 0.68

Keri et al. (2001) 20 BD Gender, age, edu Fluency 0.1220 HC WCST cat 0.11

WCST per 0.10Digit span forwards 0.33Digit span backwards 0.18

Sobczak et al. (2003) 22 BD Fluency 0.2515 HC Stroop 0.46

Verbal learning 0.25Delayed recall 0.34Verbal recognition 0.09

Ferrier et al. (2004) 17 BD Gender, age, edu Fluency 0.1217 HC Premorbid IQ DSST 0.24

Stroop 0.00TMT-A 0.07TMT-B 0.32Verbal learning 0.18Digit span forwards 0.40Digit span backwards 0.99Verbal recognition 0.29CPT commission 0.44CPT commission 0.06

Zalla et al. (2004) 33 BD Gender, age Stroop 0.9620 HC TMT-A 0.31

TMT-B 0.60WCST cat 0.12WCST per 0.57

Clark et al. (2005a) 27 BD Gender, age, edu Verbal learning 0.4346 HC Immediate recall 0.20

Delayed recall 0.12CANTAB IDED 0.77

Clark et al. (2005b) 27 BD Gender, age, edu CPT commission 0.3847 HC

Frangou et al. (2005a) 15 BD IQ WCST cat 0.5343 HC WCST per 0.40

Kieseppa et al. (2005) 19 BD DSST 0.12

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atche

fectivTable 2 (continued)

Study Groups M

Kieseppa et al. (2005) 114 HC

10 E. Bora et al. / Journal of Afscoring systems for the Stroop task, identical scores thatare sensitive to response inhibition were includedtogether.

In some studies, means and standard deviations(SDs) of more than one group with euthymic BD(Ferrier et al., 1999; Nehra et al., 2006; Senturk et al.,2007) or unaffected BD relatives (Christensen et al.,2006) were reported. In these studies, the mean values

McIntosh et al. (2005) 24 BD Gender50 HC

Pirkola et al. (2005) 16 BD Age ??100 HC

Antila et al. (2007) 40 BD Gender55 HC Premor

Christensen et al. (2006) 21 BD Age88 HC

Klimes-Dougan et al. (2006) 43 BD Age50 HC

Szoke et al. (2006) 63 BD Age48 HC

Bora et al. (2008) 34 BD Gender25 HC Premor

a =Cohen d.d Cognitive tests d a

Verbal learning 0.13Delayed recall 0.08Visual memory recall 0.24Visual copy 0.04Digit span backwards 0.18

e Disorders 113 (2009) 120and SDs are combined. However, in another study thatreported scores from two different groups (Van Gorpet al., 1998), only patients without comorbid alcoholdependency were included in the current meta-analysis.If there were more than one publication from thecommon samples, only the data from the study with thelarger sample was included, unless results were reportedfor different cognitive tasks.

, age Fluency 0.58DSST 0.50Digit span forwards 0.80Digit span backwards 0.31

, age DSST 0.44bid IQ TMT-A 0.27

TMT-B 0.26Verbal learning 0.13Immediate recall 0.19Delayed recall 0.09Verbal recognition 0.29Digit span forwards 0.05Digit span backwards 0.17Stroop 0.40TMT-A 0.00TMT-A 0.24TMT-B 0.35Verbal learning 0.39Immediate recall 0.62Delayed recall 0.62WCST cat 0.60WCST per 0.56CPT commission 0.24CPT commission 0.14TMT-A 0.32TMT-B 0.50WCST per 0.22

, age, edu Stroop 0.72bid IQ TMT-A 0.15

TMT-B 0.72Verbal learning 0.26Immediate recall 0.27Delayed recall 0.04Verbal recognition 0.33WCST cat 0.68WCST per 0.69Digit span forwards 0.37Digit span backwards 0.56CPT commission 0.50CPT commission 0.39

The current study reports the results of meta-analysesfor seventeen neurocognitive variables in 45 euthymicBD (1423 BD patients1524 healthy controls) and 17BD relative studies (443 relatives, 797 healthy controls)Mean effect sizes for current IQ, premorbid IQ andeducation were also calculated since these variables cansignificantly influence the magnitude of groupdifferences.

2.2. Statistical analyses

Meta-analyses were conducted with MIX software(Bax et al., 2006). We used the standardised meandifference method with Hedge's correction for bias insmall samples. Whenever BD patients and their relativesperformed poorer than controls, we reported between-group differences by positive effect sizes. Therefore, theeffect sizes for the relevant variables were multiplied byminus one. Homogeneity of the resulting meanweighted effect sizes was tested with Q test. Since

likely to be published. In the current meta-analysis,publication bias was tested with funnel plot and Egger'stest. However, Egger test may give false positive results,especially when effect sizes distributed heterogeneously.To reduce the risk of false positive results and to furtherinvestigate the source of funnel plot asymmetry, taskswith a significant asymmetry (Egger's test, pb0.05)were further analysed. The individual characteristics ofthe studies were further investigated, a Fail Safe number(number of negative studies necessary to make thegroup difference insignificant) was calculated and trimand fill method was used to estimate the actual effectsize. A significance level of pb0.05 was used for therandom effects model, homogeneity and publicationbias analyses.

The effects of demographic variables, medication(percentage of patients using antipsychotics, antidepres-sants, and lithium), clinical variables (age of onset andduration of illness, number of manic and depressiveepisodes, Hamilton depression score), between-group

nt-co

6537655309609407637

11E. Bora et al. / Journal of Affective Disorders 113 (2009) 120there was heterogeneity for many of the analyses, weused a random effects model rather than a fixed effectsmodel for the meta-analyses.

Meta-analytic methods accept published studies as arepresentative of all valid studies undertaken. However,direction of results may influence the chance ofsubmission and publication of the studies and this factcan be a source of bias in results of meta-analyses(publication bias). Studies with negative outcomes(especially when the sample size is small) are less

Table 3Mean weighted effect sizes for individual tasks and education for patie

Test Study Bipolar Control D

TMT-B 21 793 626 0.8Verbal learning 18 619 632 0.8CPT ommission 10 303 279 0.8Delayed recall 17 578 612 0.7Stroop 24 746 707 0.7DSST 13 381 479 0.7Digit span backwards 9 375 487 0.7Immediate recall 12 453 419 0.7WCST per 17 663 543 0.7TMT-A 20 768 600 0.6WCST Cat 15 538 465 0.6FAS 19 681 594 0.6Visual memory recall 9 274 424 0.5Verbal recognition 13 488 411 0.4Current IQ 7 239 218 0.4Digit span forwards 8 349 373 0.3CPT commission 9 288 264 0.3Visual copy 4 119 89 0.2IQ premorbid 23 714 792 0.1

Education 32 1017 1046 0.01differences of IQ and other cognitive skills wereanalysed with meta-regression. One difficulty in per-forming meta-regression analyses was the limited datafor clinical and treatment variables. Therefore, toincrease the number of studies three combined scoresfor psychomotor speed (TMT-A, DSST), executivefunction (WCST perseverations, Stroop Interferencescore, TMT-B) and memory recall (delayed verbalmemory, ROCF delayed) were also calculated and usedfor meta-regression analyses. Meta-regression analyses

ntrol differences

95% CI z P Q-test p Bias

0.651.06 8.20 b0.0001 b0.001 0.130.681.01 10.1 b0.0001 0.03 0.00040.661.00 9.42 b0.0001 0.55 0.100.610.93 9.34 b0.0001 0.06 0.070.590.93 8.68 b0.0001 0.0004 0.070.570.94 7.98 b0.0001 0.1 0.750.411.01 4.29 b0.0001 b0.001 0.210.530.93 7.15 b0.0001 0.04 0.020.490.91 6.54 b0.0001 0.0001 0.020.570.82 11.09 b0.0001 0.31 0.590.360.96 4.33 b0.0001 b0.0001 0.150.450.74 7.95 b0.0001 0.07 0.500.400.78 6.02 b0.0001 0.31 0.660.310.58 6.33 b0.0001 0.46 0.130.010.80 1.95 0.05 0.0003 0.790.150.60 3.21 0.001 0.06 0.620.130.59 3.09 0.002 0.1 0.430.050.51 1.61 0.11 0.49 0.32

0.020.36 1.73 0.08 b0.0001 0.20

0.130.16 0.14 0.89 b0.0001 0.04

fectiv12 E. Bora et al. / Journal of Afwere conducted in SPSS 11.0 by using the macroswritten by David B. Wilson. This procedure allows theperformance of weighted generalized least squaresregression. Meta-regression analyses were performedwith the random effects model using restricted-informa-tion maximum likelihood method with a significancelevel of pb0.05.

3. Results

3.1. Remission

The meta-analysis for euthymic BD patients included45 studies. These studies compared cognitive perfor-mance of a total of 1446 patients and 1524 healthycontrols. There were no significant differences for age(reported in 44 studies) and gender composition(reported in 43 studies) between patients (meanage=38.8, percentage of males=48.8%) and controls(mean age=38.3, percentage of males=49.9%). There

Fig. 1.e Disorders 113 (2009) 120were no significant between-group differences foreducation and premorbid IQ (Table 3). Current IQ hada tendency to be lower in patients. There was asignificant level of heterogeneity for current andpremorbid IQ analyses.

In 17 of 18 meta-analyses conducted for eachcognitive test, BD patients performed significantlyworse than control subjects (Table 3). Medium orlarge effect sizes were noted in most measures ofexecutive functions, verbal memory, sustained attentionand psychomotor speed. However, effect sizes for visualmemory, verbal recognition memory, CPT commissionerrors and digits forward were small. There was nobetween-group difference on the visual copying task.

Five of the 18 analyses reported a significant degreeof heterogeneity (Trails B, Digit Span-backwards,Stroop, WCST category, WCST perseveration). Mostof the heterogeneity in these studies was explained byseveral studies. The studies of Goswami et al. (2006),Kolur et al. (2006), Smith et al. (2006) were responsible

ig. 2.

13E. Bora et al. / Journal of Affective Disorders 113 (2009) 120for heterogeneity in the meta-analysis of TMT-B. Thestudy of Goswami et al. (2006) was also the cause of theheterogeneity of Digit Span-backwards. In the case of

Fthe Stroop test, (Fig. 1) extreme positive effect sizes ofKerr et al. (2005), Balanza-Martinez et al. (2005), Koluret al. (2006) and negative effect sizes of Rocca et al.

Table 4Mean weighted effect sizes for individual tasks and education for relative-co

Test Study Bipolar relatives Control relatives

Stroop 6 142 209TMT-B 8 252 274WCST per 9 257 312CPT ommission 5 128 153Immediate recall 5 151 192Learning 8 209 338FAS 5 90 117Delayed recall 7 192 321WCST cat 7 167 217DSST 5 115 280Digit Span Backwards 7 153 346Memory recognition 5 120 127Current IQ 7 157 242CPT commission 3 94 92Edu 11 269 576TMT-A 9 277 358Visual memory recall 3 41 173Digit span forwards 6 134 232Premorbid IQ 8 165 441Visual copy 3 41 173(2008) were responsible for the heterogeneity. Finally,the heterogeneity in the analysis of WCST category andperseveration scores (Fig. 2) was mostly due to the

studies of Balanza-Martinez et al. (2005) and Koluret al. (2006). After excluding all of these studies thatcaused the heterogeneity the findings, Q-tests for all of

ntrol differences

D 95% CI z p Q-test p Bias

0.51 0.270.76 4.1 b0.0001 0.37 0.600.38 0.200.55 4.15 b0.0001 0.52 0.520.36 0.200.54 4.18 b0.0001 0.08 0.710.36 0.12060 2.93 0.003 0.95 0.530.33 0.110.55 2.94 0.003 0.62 0.860.28 0.090.46 2.97 0.003 0.92 0.380.27 0.010.55 1.85 0.06 0.56 0.340.27 0.040.50 2.27 0.02 0.21 0.320.24 0.080.56 1.48 0.14 0.05 0.220.22 0.040.49 1.69 0.09 0.28 0.520.22 0.140.57 1.21 0.23 0.02 0.240.20 0.110.51 1.27 0.20 0.25 0.960.20 0.240.63 0.89 0.37 0.0006 0.360.18 0.110.47 1.21 0.23 0.55 0.830.18 0.050.42 1.52 0.13 0.02 0.110.17 00.33 1.97 0.05 0.82 0.070.13 0.390.65 0.48 0.63 0.14 0.740.08 0.380.54 0.32 0.75 0.003 0.44

0.03 0.290.23 0.23 0.83 0.07 0.450.1 0.440.25 0.56 0.58 0.84 0.84

these five tasks were non-significant (pN0.15). Somedifferences in the characteristics of these studies may

number of omission errors (B=0.029, SE=0.01,p=0.02). IQ difference between-groups was only

Fig. 3.

14 E. Bora et al. / Journal of Affective Disorders 113 (2009) 120explain these results. In the study of Balanza-Martinezet al. (2005), the patients had lower education andpremorbid IQ, while in the study of Rocca et al. (2008),the patients had a significantly higher IQ. Further, thestudy of Smith et al. (2006) was characterized by earlyonset (b15 years of age).

Egger's test for the meta-analyses for three tasksshowed a significant publication bias (Verbal learningand verbal memory early recall and WCST persevera-tion). The publication bias was especially significant forverbal learning score. Fail Safe number for the verballearning was 836 studies and trim and fill methodpredicted a medium effect size of D=0.66 (CI=0.48-0.85) instead of a large effect size suggested by the prioranalysis. Fail-safe numbers for verbal memory earlyrecall and WCST perseveration score were 297 and 513,respectively. Trim and fill method did not predict adifferent effect size for these tasks.

Meta-regression analyses revealed that mean age ofBD patients was negatively associated with the increasedFig. 4.associated with the effect size of the Stroop (B=0.45,SE=0.16, p=0.007, 10 studies). Younger age of illnessonset was associated with larger effect sizes for verballearning (B=0.05, SE=0.02, p=0.027, 15 studies) andTMT-A (B=0.07, SE=0.02, p=0.0014, 14 studies).Medication was associated with the magnitude ofimpairment for psychomotor speed and sustainedattention. Studies that had reported a higher percentageof antipsychotic usage found larger effect size impair-ments for psychomotor speed (B=0.05, SE=0.02,p=0.04, 24 studies) and omission errors (B=0.011,SE=0.005, p=0.037, 9 studies). Antidepressant use wasalso associated with psychomotor speed (B=0.0107,SE=0.004, p=0.0039, 17 studies) and TMT-A perfor-mance (B=0.01, SE=0.004, p=0.01, 12 studies).

Psychomotor slowness also increased the effect sizeof the impairment for WCST (B=1.1, SE=0.43,p=0.009, 13 studies) and Stroop (B=0.66, SE=0.27,p=0.015, 17 studies). Low performance on TMT-Awas also associated with larger effect sizes for the

fectiveStroop (B=0.66, SE=0.30, p=0.025, 14 studies),omission errors (B=0.88, SE=0.4, p=0.03) and FAS(B=0.98, SE=0.45, p=0.03, 10 studies).

There was no association between verbal memoryand executive function impairments. Patients who mademore omission errors performed more poorly on theStroop task (B=1.69, SE=0.41, pb0.001). Workingmemory impairment (reverse digit span) was alsoassociated with the magnitude of executive dysfunction(B=0.76, SE=0.15, pb0.001, 7 studies).

3.2. Relatives

Meta-analyses of relatives' studies included 17studies (443 relatives of BD patients and 797 healthycontrols). The mean age (15 studies) and gendercompositions (16 studies) of relatives (38.5 years,37.7% male) and healthy controls (41.4 years, 43.6%male) were comparable. There were no significant groupdifferences for education, current and premorbid IQbetween groups (Table 4).

Q-test revealed a significant heterogeneity for currentIQ. In 6 of 18 cognitive measures, relatives of BDpatients performed significantly poorer than controls(see Table 4). The greatest impairment was found on theStroop task (medium effect size) (Fig. 3). The effectsizes for the impairments in TMT-B, WCST persevera-tion (Fig. 4), CPT omission, verbal learning andimmediate recall were small.

There was a significant heterogeneity for only onetask (Digit Span-forwards). Positive effect size in thestudy of Gourovitch et al. (1999) and good performanceof the relatives in the study of Pirkola et al. (2005) wereresponsible for this heterogeneity. The study ofGourovitch had an extremely small sample size andincluded only monozygotic twins. None of the analysesin relatives showed a significant publication bias.

Meta-regression analyses revealed effects ofbetween-group IQ differences and the mean age offirst-degree relatives on some cognitive tasks. Age had asignificant effect on relative-control differences ofpsychomotor speed (B=0.022, SE=0.007, p=0.003,10 studies) and verbal memory delayed recall (B=0.016, SE=0.008, p=0.03, 5 studies). Thus, thestudies with older samples reported smaller effectsizes. Studies that reported lower IQ scores in relatives(compared to controls) also found larger effect sizes forexecutive function (B=0.57, SE=0.24, p=0.022, 8studies), psychomotor speed (B=0.559, SE=0.218,p=0.01, 8 studies), verbal delayed recall (B=0.68,SE=0.30, p=0.02, 5 studies), Digit Span-backwards

E. Bora et al. / Journal of Af(B=1.41, SE=0.47, p=0.003, 6 studies) and DigitSpan-forwards (B=1.71, SE=0.56, p=0.0025, 5studies).

4. Discussion

This meta-analytic study demonstrated that impairedresponse inhibition might be the most prominentcognitive endophenotype of BD. Another executivemeasure, set shifting and two other cognitive domains,verbal memory and sustained attention also met thecriteria as potential endophenotypes of BD. Whileimpairments in processing speed, verbal workingmemory and visual memory are related to the clinicalexpression of BD, they were not observed in relativesand therefore do not seem to be associated with geneticsusceptibility to BD. Processing speed impairments maybe partly secondary to medication and can alsocontribute to other cognitive impairments found ineuthymic patients with BD. Early onset of illness maybe associated with more severe verbal memory impair-ment and psychomotor slowing in BD. The observedpattern of sustained attention impairment and promi-nence of response inhibition deficit and lack ofimpairment in processing speed in relatives of patientswith BD partly contrast with reported findings of studiesin first-degree relatives of schizophrenia.

Response inhibition seems to be the most significantendophenotype of BD. In previous studies in BD, inaddition to the Stroop test, impaired response inhibitionwas also reported with the Hayling Sentence CompletionTask both in euthymic patients and relatives (Frangouet al., 2005a). However, we did not include this task in ouranalyses, since fewer than three published studies havereported thismeasure in relatives of patients with BD. Ourresults are partly consistent with Frangou et al. (2005a,b)who suggested that only VPFC related functions areendophenotypes of BD.While it may be oversimplistic toequate response inhibition with VPFC and Cingulatefunction, brain imaging studies provided evidenceregarding differential role of VPFC and dorsal prefrontalcortex for response inhibition (Blumberg et al., 2003) andset shifting (Monchi et al., 2001) respectively. AnteriorCingulate gyrus and VPFC abnormalities may have a rolein the aetiology of BD. However, unlike Frangou et al.(2005a,b), current results also suggest a role for dorsalprefrontal cortex related set shifting abilities as cognitiveendophenotypes of BD. We found a small but significantimpairment for TMT-B andWCST perseverative errors inrelatives of patients with BD. In a recent meta-analysis,Arts et al. (2008) found impairments in TMT-B but not inWCST perseverative errors in relatives of BD patients.

15Disorders 113 (2009) 120This difference may be related to their lower sample size

fectivfor this aspect of their meta-analysis. The current studyprovides evidence for a selective role for executivefunctions as endophenotypes of BD. Thus, while abilityon tasks of set shifting and response inhibition seemed tobe more related to genetic risk for BD, other EF functionslike working memory and verbal fluency were not.

In our study, verbal memory was also impaired bothin euthymic patients and their relatives. While arelatively large effect size for verbal memory wasfound in euthymic patients, the effect sizes for verbalmemory in relatives were modest. This result partlycontradicts the findings of Arts et al. (2008) whoreported that relatives had the largest impairment inverbal memory. Publication bias seems to exaggerate theactual impairment for verbal memory, especially verballearning, in euthymic patients with BD. Originally, wealso included visual memory skills in our analyses. Theresults of the study do not suggest a role for nonverballearning abilities as endophenotypes of BD.

Originally, the current meta-analysis also providedsupport for the potential role of sustained attention as anendophenotype of BD. As far as we know, this is the firstmeta-analysis that has examined sustained attention inrelatives of BD patients. Both the euthymic BD patientsand relatives made more omission errors on CPT tasks.Failure to detect targets seems to be a possible traitmarker for BD. We found larger effect size impairmentfor CPT in euthymic patients compared to meta-analysesof Robinson et al. (2006) and Arts et al. (2008). Thedifferent outcome seems to be related to the measures ofsustained attention examined by these other authors.These studies analysed the measures of sensitivity indexof sustained attention and latency. Sensitivity is a derivedscore from correct target detection percentage and falsealarm rates. This measure depends on not only omissionerrors but also commission errors that do not seem to beincreased in euthymia (Bora et al., 2006). The selectiveimpairment of target detection in BD differs from thepattern observed in schizophrenia (see below).

While the effect sizes for impairment on psychomotortasks were relatively large in patients with BD, psycho-motor processing seems to be intact in first-degreerelatives of BD. These results suggest that otherconfounding factors rather than genetic susceptibilitymay be the source of psychomotor slowness of BDpatients. According to our results, treatment effects maybe partly responsible for this finding in euthymic patients.Antipsychotic use was associated with psychomotorslowness. There is some previous evidence regardingnegative impact of typical and atypical antipsychotics onpsychomotor abilities (Hughes et al., 1999;Morrens et al.,

16 E. Bora et al. / Journal of Af2007).Antipsychoticswere also associatedwith increasedmagnitude of impairment for sustained attention. Sincepsychomotor slowness was related to larger effect sizesfor verbal fluency, sustained attention and WCSTperseverative errors, antipsychotics may also have anindirect impact on other cognitive functions.

The proposed cognitive endophenotypes of bipolardisorder partly differ from schizophrenia. While meta-analytic studies in relatives of schizophrenia patientsrevealed psychomotor slowing and verbal fluency as animportant endophenotype of schizophrenia (Sitskoornet al., 2004; Snitz et al., 2006; Szke et al., 2005), thiswas not the case for BD in the current study. Meta-analyses of the Stroop test in relatives of schizophreniapatients (Sitskoorn et al., 2004; Snitz et al., 2006)reported a milder deficit than in BD patients in thecurrent study, despite the fact that they reported morepronounced general intellectual deficits compared to BDrelative studies. Unlike in BD, response inhibitiondeficit is not the most pronounced impairment inrelatives of patients with schizophrenia. The observedpattern of sustained attention is also different inschizophrenia and BD. Meta-analyses in relatives ofschizophrenia patients provided evidence for all aspectsof sustained attention but especially for false alarmingand target sensitivity (Sitskoorn et al., 2004). In contrast,target detection impairment rather than false alarminghas a role as an endophenotype of BD. While responseinhibition and a selective type of sustained attentiondeficit are more specific endophenotypes of BD,processing speed and general intelligence impairmentsmay be endophenotypes of schizophrenia. However,there is also evidence for shared endophenotypes in BDand schizophrenia. Verbal memory and set shiftingimpairments are observed in relatives of both patientgroups. This finding may be compatible with brainimaging findings, which suggest there are shared fronto-limbic and fronto-subcortical deficits in schizophreniaas well as BD (McIntosh et al., 2006). Heterogeneity ofschizophrenia and BD may also contribute to shared anddifferent endophenotypes of BD. While verbal memoryand set-shifting abnormalities may be trait markers ofonly BD patients with a history of psychosis, responseinhibition deficits may be an endophenotype for allpatients with BD (Bora et al., 2005; Bora et al., 2007;Martinez-Aran et al., 2008). This may also explain thelarger effect sizes for response inhibition in relatives ofpatients with BD. Verbal memory and set shiftingimpairments may be endophenotypes of psychosisindependent of diagnosis.

Not all of the cognitive impairments in euthymicpatients with BD are true endophenotypes, even though

e Disorders 113 (2009) 120they are not secondary to iatrogenic effects or

fectivesubsyndromal symptoms. Since endophenotypes must bestable over time, progressive impairments related todisease progression may contribute to the cognitiveprofile of established BD patients. While longitudinalstudies are very rare in BD, there is some evidence ofprogression of cognitive impairments in schizophreniastudies. Late maturational changes that may start beforethe onset of illness and continue after the first episodemaycontribute to observed neurocognitive pattern in majorpsychoses (Pantelis et al., 2005). Wood and colleaguesrecently examined progressive changes in cognitivefunction over the transition to psychosis as part of theMelbourne UHR studies (Wood et al., 2007). Whileperformance on most tests was stable or improved,visuospatial memory, verbal fluency and attention switch-ing showed significant decline over the transition topsychosis. These progressive impairments were not seenin the non-psychotic UHR group. These data would seemconsistent with progressive brain structural changes overtransition to psychosis (Pantelis et al., 2005; Pantelis et al.,2007). Unfortunately, there is very scarce data regardinglongitudinal studies in BD. However, it is interesting thatworking memory and verbal fluency are among theimpairments which are only observed in patientswith BD.Considering the overlaps between schizophrenia and BD,it is likely that late-maturational changes can contribute tothe cognitive profile of BD.Another proposedmechanismfor illness related impairments in BD is the potentialneurotoxic effects of repeated illness episodes on limbicstructures. Thus, there is some evidence for the associa-tion between the number of manic episodes, duration ofillness and cognitive impairment in BD (Robinson andFerrier, 2006). While our meta-regression analyses failedto support evidence for this association, some methodo-logical factors including the limitations of the meta-regression approach, and factors related to sampleselection in published studies may explain this outcome.Analysis of direct correlations from the individual studieswould be a better option, however insufficiencies ofpublished data prevent us from performing a correlationalmeta-analysis. Long term follow-up studies that investi-gate cognitive functions in high-risk groups and patientswith established diagnosis are necessary to tackle the pre-onset and post-onset cognitive changes in BD.

Differences between underlying disease-severities ofpatients included in different studies may be anotherconfounding factor. Consistent with this idea, meta-regression analysis demonstrated an association betweenyoung onset, verbal memory and psychomotor slowness.A subgroup of BD patients may present with earlier onsetand more pronounced impairments in verbal memory

E. Bora et al. / Journal of Afand processing speed. A similar pattern was previouslyobserved in schizophrenia studies, with more severeimpairment for verbal memory reported for early-onsetschizophrenia (Tuulio-Henriksson et al., 2004). Residualmood symptoms also can have an impact on hetero-geneity of analyses and can increase the magnitude ofeffect sizes in euthymic patients. This issue was simplynot investigated in many studies and in others verydifferent measures were used to assess residual symp-toms. We were only able to undertake an analysis on asample of studies with regard to the effect of Ham-Dscores on cognition and failed to show any impact on anycognitive measures. However, the relationship betweenantidepressant use and lower processing speed may be asign of an impact of residual symptoms on cognition.This issue deserves further investigation. One otherpotential confounding factor that can have an impact onthe magnitude of impairment in first-degree relatives ofBD could be the type of family members included(siblings, offspring, twins). Since the number ofpublished relative studies was restricted, it was notpossible to investigate this issue further.

This meta-analytic study has several strengths andoriginal points. It investigates the cognitive deficits bothin euthymic patients and relatives of patients with BD.Regarding sample size and cognitive domains involved,it the most comprehensive meta-analytic study to date.To our knowledge, it is the first meta-analytical studythat attempts to address the impact of clinical andtreatment confounders on cognitive phenotypes of BD.

In conclusion, response inhibition, set shifting, verbalmemory and target detection impairments are potentialcandidate endophenotypes for BD. Some of the cognitiveimpairments (including psychomotor slowness) observedin euthymic patients could be related to the effects ofmedication and illness-related factors. Futurework shouldcarefully try to differentiate cognitive deficits associatedwith disease genotype from impairments related to otherconfounding factors. Longitudinal studies, studies inves-tigating heritability of cognitive impairment in BD and itsrelation with brain connectivity and genetics would beespecially useful.

Role of funding sourceNo funding source contributed to this paper.

Conflict of interestAuthors report no conflict of interest.

Acknowledgements

Murat Ycel was supported by a National Health &Medical Research Council (NH&MRC) Clinical Career

17Disorders 113 (2009) 120Development Award (I.D. 509345).

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Cognitive endophenotypes of bipolar disorder: A meta-analysis of neuropsychological deficits in.....IntroductionMethodNeuropsychological variablesVerbal learning and memoryVisual memorySustained attentionProcessing speedVerbal fluencySet shiftingWorking memoryResponse inhibitionVisuospatial abilitiesGeneral intelligence

Statistical analyses

ResultsRemissionRelatives

DiscussionRole of funding sourceConflict of interestAcknowledgementsReferences