enetic Variation in the DAOA (G72) Gene Modulatesippocampal Function in Subjects at High Risk ofchizophrenia
eremy Hall, Heather C. Whalley, T. William J. Moorhead, Ben J. Baig, Andrew M. McIntosh,ominic E. Job, David G.C. Owens, Stephen M. Lawrie, and Eve C. Johnstone
ackground: Strong evidence exists for an association between genetic variation in the gene DAOA (D-amino acid oxidase activator, alsonown as G72) and risk for schizophrenia. Preliminary evidence in healthy control subjects has implicated genetic variation in the DAOAene in the modulation of hippocampal complex and prefrontal cortex activation.
ethods: Assessment was performed on 61 subjects at high genetic risk of schizophrenia for familial reasons. All subjects were genotypedor two closely linked single nucleotide polymorphisms in the DAOA gene complex, M23 (rs3918342) and M24 (rs1421292), that havereviously shown association with schizophrenia. The effect of genotype on brain activation was assessed with functional magnetic
esonance imaging data gathered during performance of the verbal initiation section of the Hayling Sentence Completion Task.
esults: Differences between DAOA genotype groups were seen in the activation of the left hippocampus and parahippocampus in theontrast of sentence completion versus rest. In addition the DAOA genotype groups differed in their recruitment of right inferior prefrontalortex in relation to increasing task difficulty. The effects of genotype on brain activation could not be explained in terms of differences inrey matter density.
onclusions: These results support the view that genetic variation in the DAOA gene influences hippocampal complex and prefrontal
ortex function, an effect that might be particularly prominent in the context of enhanced genetic risk for schizophrenia.
ey Words: DAOA, fMRI, G72, hippocampus, prefrontal cortex,chizophrenia
chizophrenia is a highly heritable severe psychiatric condi-tion with a lifetime risk of approximately 1%. The disorderis characterized by psychotic symptoms including delu-
ions and hallucinations as well as social withdrawal and affec-ive blunting. Cognitive deficits have also been demonstrated,nd these are generally present across the course of the illness.bnormalities in cerebral structure and function have beenemonstrated in patients with schizophrenia, and these arearticularly prominent in the frontal and temporal lobes, includ-
ng the hippocampus (1). Less-severe deficits in cognition andrain structure and function have been identified in the relativesf individuals with schizophrenia, suggesting that these might benherited as part of a state of vulnerability (2).
The primate-specific gene D-amino acid oxidase activatorDAOA, also termed G72) is a leading candidate as a schizophre-ia susceptibility gene (3). Chumakov et al. (4) first demonstratedssociation of DAOA with schizophrenia after high-density map-ing of single nucleotide polymorphisms (SNPs) in a region ofhromosome 13q that has shown linkage to schizophrenia.articularly strong association with schizophrenia was foundith markers in the 3’ region of DAOA, including the closely
inked markers M23 (rs3918342) and M24 (rs1421292) (4). Asso-iation of DAOA with schizophrenia has subsequently beenonfirmed in the majority, but not all, association studies con-ucted in a wide range of populations (5–11). Notably, two
rom the Division of Psychiatry, University of Edinburgh, United Kingdom.ddress reprint requests to Jeremy Hall, Ph.D., Division of Psychiatry, Uni-
versity of Edinburgh, Kennedy Tower, Royal Edinburgh Hospital, Edin-burgh, United Kingdom EH10 5HF; E-mail: [email protected].
eceived September 17, 2007; revised February 6, 2008; accepted March 10,
recent meta-analyses of association studies have supported anoverall association between schizophrenia and genetic variationin DAOA, in particular in the M23/M24 region (12,13).
Evidence regarding the function of DAOA also supports itsinvolvement in the pathogenesis of schizophrenia. An interactionbetween DAOA and the enzyme D-amino acid oxidase (DAAO)has been shown in vitro that results in increased activation of theDAAO enzyme (4). D-amino acid oxidase is expressed in thebrain where it oxidizes D-serine to hydroxy-pyruvate (14).Because D-serine is a potent activator of the N-methyl-D-asparticacid (NMDA) receptor via the glycine modulatory site, the overalleffect of activation of DAAO is to decrease glutamatergic neuro-transmission at NMDA receptors. This provides an importantpotential pathogenic link between DAOA and the glutamatehypofunction hypothesis of schizophrenia (15). More recentlyDAOA has also been implicated in the regulation of mitochon-drial function and dendritic branching, suggesting that DAOAmight impact on multiple processes of potential pathogenicrelevance to schizophrenia (16).
There has only been one previous study that has investigatedthe effect of genetic variation in DAOA on cerebral function (17).In that study Goldberg et al. demonstrated that genetic variationat SNPs M23 and M24 is associated with impairments in cognitivefunction in tests of attention and memory. Of note, there wasevidence of an interaction between genetic variation in DAOAand background vulnerability for the disorder, because cognitivedeficits associated with DAOA genotype were more pronouncedin patients than in control subjects. Goldberg et al. also providedpreliminary evidence that, in healthy control subjects, geneticvariation in the same region of the DAOA gene was associatedwith decreased hippocampal/parahippocampal activation andincreased right frontal lobe activation in functional magneticresonance imaging (fMRI) (17).
In the present study we have investigated the effects of
genetic variation in the M23/M24 region of the DAOA gene on
J. Hall et al. BIOL PSYCHIATRY 2008;64:428–433 429
erebral function in subjects at familial high risk of schizophre-ia, using data from the Edinburgh High Risk Study (EHRS) (18).e hypothesized that within this cohort genetic variation inAOA would be associated with abnormalities of medial tempo-
al lobe and frontal lobe function in fMRI.
aterials and Methods
ubjectsDetails of the recruitment process have been described in full
reviously (18). Briefly, individuals with schizophrenia, with aamily history of schizophrenia and with adolescent relatives,ere identified from psychiatric hospital case records in several
egions of Scotland. Case-note diagnoses of schizophrenia wereerified with the Operational Criteria Checklist (19). We thenpproached their unaffected relatives and from them recruitedigh-risk subjects ages 16–25, all of whom had one first- orecond-degree relative with schizophrenia and a minimum ofne further genetic relative with the illness. All subjects were wellt the time of recruitment into the study, and subjects wereithdrawn from the study if they developed syndromal schizo-hrenia.
Participants were given detailed clinical, neuropsychological,nd brain imaging assessment at baseline. The clinical assess-ent included the Present State Examination (PSE, 9th edition),structured psychiatric interview schedule that has been widelysed in studies of schizophrenia. Psychotic symptoms noted atSE were scored as described previously (18). Educationalchievement was rated categorically (high school without takingxams; high school with exams; higher education). Furtherimilar assessments were conducted at biennial intervals up until004, including fMRI scan of the brain during which subjectsompleted the Hayling Sentence Completion Test (HSCT) (20).one of the subjects were receiving psychotropic medication at
he time of fMRI scanning. Subjects were given the opportunity torovide a blood sample for genetic analysis at the end of thetudy. A total of 61 high-risk subjects for whom both genetic andMRI data were available were included in the current study.
enotype AnalysisGenomic DNA was extracted from venous blood samples
ith standard protocols. Single nucleotide polymorphisms wereenotyped by the Wellcome Trust Clinical Research Facility,dinburgh, with TaqMan assay-by-design assays. The comple-ion rate for genotyping was � 95%. Reproducibility of Taqmanenotypes is typically � 99.5%. Genotyping was performed forwo SNPs from the DAOA gene complex, M23 (rs3918342) and24 (rs1421292), both of which were originally reported as
howing association with schizophrenia (4).
MRIFunctional imaging was carried out on a GE 1.5-T Signa
canner (GE Medical, Milwaukee, Wisconsin) equipped with3mT/m Echospeed gradients having a rise time of 200 �sec.ubjects were imaged with axial gradient-echo planar imagesrepetition time/echo time � 4000/40 msec; matrix 64 � 128;ield of view 220 � 440 mm) acquired continually during thexperimental paradigm. Thirty-eight contiguous 5-mm slicesere acquired within each repetition time period. Each echolanar image acquisition was run for 204 volumes, of which theirst four volumes were discarded. Visual stimuli were presentedith a screen (IFIS; MRI Devices, Waukesha, Wisconsin) placed
n the bore of the magnet; corrective lenses were used where
ecessary.
The participants in the study performed the verbal initiationsection of the Hayling Sentence Completion Test (HSCT) in thescanner (21). Subjects were shown sentences with the last wordmissing and were asked to silently think of an appropriate wordto complete the sentence (i.e., without speaking the word) andpress a button when they had done so, giving a reaction timemeasure. The task was adapted for fMRI to have four levels ofconstraint, according to the range of suitable completion wordssuggested by the sentence context. Sentences were presented inblocks of fixed constraint; each block lasted 40 sec and includedeight sentences. Sentences were presented for a period of 3 secfollowed by a fixation cross for 2 sec. Subjects were asked torespond at any time by button press before the next sentenceappeared. The rest condition consisted of viewing a screen ofwhite circles on a black background for 40 sec. The order of theblocks was pseudo-random, and each block was repeated fourtimes (different sentences were used for each sentence block).This design allowed both a standard subtraction (sentencecompletion vs. rest) and parametric analysis (examining areas ofincreasing activation with reducing constraint/increasing taskdifficulty). Immediately after scanning, subjects were given thesame sequence of sentences on paper and requested to completeeach sentence with the word they first thought of in the scanner.Scores for word appropriateness and reaction time were deter-mined for each constraint level.
The fMRI scan analysis was performed with SPM2 (WellcomeDepartment of Cognitive Neurology and collaborators, Instituteof Neurology, London, United Kingdom), blind to the genotypeof the individual. For each subject, echo planar image volumeswere realigned to the mean volume. The images were thennormalized to a study-specific template with a linear affinetransformation, followed by non-linear deformations and resa-mpled with sinc interpolation to cubic voxels of size 8 mm3.Normalized images were spatially smoothed with a 6-mm full-width at half maximum (FWHM) kernel to minimize residualinter-subject differences and meet assumptions for statisticalanalysis.
At the individual subject level the data were modelled withfive conditions (the four difficulty levels and the rest condition),each modelled by a boxcar convolved with a synthetic hemody-namic response function. The estimates of the subject’s move-ment during the scan were also entered as “covariates of nointerest.” Before fitting the model the AR-1 technique was used toaddress issues of temporal autocorrelations in the data, and thedata were filtered in the time domain with a high-pass filter(200-sec cut-off). Contrasts were constructed to examine all foursentence completion conditions versus rest and areas of increas-ing activation with increasing task difficulty (the parametriccontrast).
Separate analyses were conducted for SNPs M23 and M24. Foreach of these analyses subjects were divided into three groupsaccording to their genotype at that SNP. For each contrast ofinterest (sentence completion vs. rest, and parametric effects)one contrast image/subject was entered into a second levelrandom effects analysis to examine areas of activation withineach of the genotype groups and differences in activationbetween the genotype groups. Because the genotype groupswere matched on demographic variables, and there were nosignificant differences in movement parameters, we did notinclude these factors as potential confounds in the model.
Statistical maps were thresholded at a level of p � .005uncorrected to look for genotype � task interactions, and
regions were considered significant at p � .05 cluster level
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orrected for multiple comparisons across the whole brainolume. All p values quoted in the text are at the corrected clusterevel. Coordinates are given with the Montreal Neurologicalnstitute (MNI) convention. Where a positive effect was foundarameter estimates were inspected graphically.
tructural MRIAll participants were scanned on a 1.5-T GE MRI scanner (GE
edical Systems). We employed a coronal gradient echo se-uence with magnetization preparation and produced 128 coro-al high-resolution T1-weighted images, which were used fortructural image analysis (time of inversion [TI] � 600 msec, echoime � 3.4 msec, flip angle � 15°, field of view � 22, slicehickness �1.7 mm, matrix � 256 � 192).
In an adaptation of the SPM optimized methodology pro-osed by Good et al. (22), we used nonlinear warping ofxtracted (skull stripped) brains to a study-specific template (23).ll scans were segmented in normalized space with study-pecific a priori tissue maps (23,24). The grey tissue segmenta-ions were smoothed with a 12-mm FWHM Gaussian kernel (25).
Separate statistical parametric maps were created to examinehe effects of genotype group on grey matter density for bothNP M23 and SNP M24. T-contrast maps were generated with thencorrected threshold set to T � 3.00. Results were corrected forultiple comparisons and reported for corrected p values � .05.
mall volume corrections (SVC) were applied through the use ofilateral temporal lobe and bilateral amygdalo-hippocampalomplex masks.
esults
enotyping and Demographic DataGenetic and MRI data were available for 61 high-risk subjects.
enotyping of SNPs M23 and M24 confirmed that both SNPsere in Hardy-Weinberg Equilibrium (p � .8 in both cases). Inddition, consistent with previous studies, there was very stronginkage disequilibrium (LD) between M23 and M24 in our studyroup (D’ � .93), with the T allele at SNP M23 showing closeinkage with the T allele at SNP M24. We therefore focussed ourmaging analysis on SNP M23, although subsequent analysisonfirmed that qualitatively and quantitatively similar resultsere present for SNP M24 (Supplement 1). The three genotyperoups at SNP M23 did not differ in age [F (2,60) � .4, p � .7],ational Adult Reading Test (NART) IQ [F (2,60) � .7, p � .5],
evel of education achievement [�2 � 2.6, p � .5], gender [�2 �7, p � .7], or in behavioral performance during the HSCT inerms of either reaction time in the scanner or word appropri-teness scores at any level of constraint (p � .05 in all cases)Table 1).
We did not find any association between genetic variation inNP M23 and the development of psychotic symptoms [�2 � .7,� .7] or syndromal schizophrenia [�2 � .1, p � .9] within our
tudy sample. Similarly, no significant association was seen forNP M24 with either psychotic symptoms [�2 � .8, p � .6] oryndromal illness [�2 � .2, p � .9]. We recognize, however, thathe current study was underpowered for the detection of geneticffects on these measures on the basis of the effect sizes reportedn previous studies of DAOA (12).
egional Brain Activation During the HSCTPrevious studies, including our own, have confirmed that the
SCT produces broad activation of frontal and temporal lobeegions (20,26,27). In the current study we were particularly
nterested in determining whether genetic variation in DAOA
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modified hippocampal function as previously reported (17). Wetherefore examined data from all 61 high-risk subjects includedin the present study to identify whether there was task-depen-dent hippocampal activation. Inspection of the data confirmed asignificant cluster of activation in the left hippocampus in thecontrast of sentence completion versus rest (Supplement 2).
Effect of DAOA Genotype on Regional Brain ActivationWe next investigated the effect of genetic variation in DAOA
at SNP M23 on regional brain activation in subjects at highgenetic risk of schizophrenia, with fMRI data from the HSCT.
We first examined the contrast of sentence completion versusrest. A linear test for trend (CC � TT) confirmed an effect of M23genotype on hippocampal and parahippocampal activation, withsubjects bearing the TT genotype showing decreased activationof a single large cluster centered on the left hippocampus (peakMNI coordinates �28, �12, �10; extent 386 voxels; Z � 4.01;p � .05 corrected for multiple comparisons across whole brainvolume; Figure 1A). This cluster included left hippocampus andparahippocampus and extended to a small part of the lateralborder of the left midbrain. Inspection of parameter estimatesconfirmed that this effect derived from decreased activation ofthe left hippocampus and parahippocampus in subjects with theTT genotype relative to the CC genotype, with CT genotypesubjects having an intermediate level of activation (Figure 1B).There were no other clusters showing significantly greater acti-vation in the CC relative to the TT group and no significantclusters of difference between genotype groups in the reversecontrast. We confirmed that a similar effect of genotype onhippocampal and parahippocampal activation was seen whensubjects were divided on the basis of genotype at the closelylinked SNP M24 (Supplement 1).
We next determined the effects of DAOA genotype on brainactivation in the parametric contrast of increasing task difficulty.Here we again found a significant effect of genotype at SNP M23on the blood oxygen level dependent (BOLD) signal withsubjects with the TT genotype showing a cluster of increasedactivation in the right inferior frontal gyrus/sub-gyral region(Brodmann area [BA] 47) with increasing difficulty of sentencecompletion (peak MNI coordinates 22, 20, �16; extent 333voxels; Z � 3.86; p � .05 corrected for multiple comparisonsacross whole brain volume; Figure 2A). No other areas showed asignificant difference between genotype groups in this contrast.Examination of parameter estimates confirmed that this effect
Table 1. Behavioural and Demographic Characteristics of the High-RiskParticipants by Genotype Group
The RTs (reaction times for Hayling Sentence Completion Test [HSCT] inthe scanner) and WA (word appropriateness scores) for the HSCT— on thebasis of standardized norms (21)—are shown as means across all levels ofconstraint. Age is given at time of functional magnetic resonance imaging.
SNP, single nucleotide polymorphism; NART, National Adult ReadingTest.
derived from increased activation in the TT subjects relative to
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J. Hall et al. BIOL PSYCHIATRY 2008;64:428–433 431
he CC subjects, with heterozygotes showing an intermediateevel of activation (Figure 2B). There were no significant clustersn the reverse contrast. We confirmed that a similar pattern ofctivation differences is seen between genotype groups at thelosely linked SNP M24 (Supplement 1).
ffects of DAOA Genotype on Grey Matter DensityWe assessed the effect of DAOA SNP M23 genotype on grey
atter density with voxel-based morphometry. In whole-brainnalysis we found no significant differences in grey matterensity between M23 genotype groups. We then looked morepecifically at whether there were any differences in grey mattern the temporal lobes that could account for the observedifferences in BOLD signal by applying small volume correctionsor the temporal lobe as a whole and for the amygdalo-hip-ocampal complex. No significant differences in grey matterensity between groups were detected even with these moreestricted search volumes. We repeated these analyses for SNP24 and again found no differences between groups in greyatter density.
igure 1. Effect of D-amino acid oxidase activator (DAOA) single nucleotictivation in the Hayling task. (A) Statistical parametric map showing a cluste
n the TT genotype compared with the CC genotype (p � .05 corrected). Cnstitute [MNI] coordinates �28, �12, �10). Extent threshold 300 voxels.ifference in the hippocampus/parahippocampus. Error bars show SEM.
igure 2. Effect of DAOA SNP M23 genotype on right inferior frontal gyrus he right inferior frontal gyrus with significantly increased activity in the TThe voxel of maximum difference (peak MNI coordinates 22, 20, �16). Extent
or the cluster of difference in the right inferior frontal gyrus. Error bars show SEM
Discussion
In the present study we have shown that genetic variation inthe DAOA gene modulates both hippocampal and frontal lobefunctions in a large group of subjects at high genetic risk ofschizophrenia. These results were obtained in a group of youngadults at risk for schizophrenia and were unconfounded by theeffects of established illness or psychotropic medication. Further-more, the differences in brain activation could not be explainedin terms of differences in grey matter density or behavioralperformance between genotype groups.
The current results show a striking convergence with the onlyprevious study of the effect of genetic variation in DAOA onbrain activation (17). In that study Goldberg et al. demonstratedthat healthy control subjects homozygous for the T allele at SNPM24 had decreased activation of the hippocampus and parahip-pocampus during an episodic memory task and increased acti-vation of regions of the prefrontal cortex, including the subgyralarea during performance of the N-back task. In the present studywe examined the effect of genetic variation at SNP M23 on
lymorphism (SNP) M23 genotype on hippocampal and parahippocampale hippocampus and parahippocampus with significantly decreased activity
hairs show the voxel of maximum difference (peak Montreal Neurologicalarameter estimates for the three M23 genotype groups for the cluster of
tion in the Hayling task. (A) Statistical parametric map showing a cluster intype compared with the CC genotype (p � .05 corrected). Cross hairs showhold 300 voxels. (B) Parameter estimates for the three M23 genotype groups
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erebral activation. The SNP M23 is in very close LD with SNP24 in both our sample and in other studies, including that ofoldberg et al. (17), with the T allele at both SNP M23 and M24eing the risk-associated alleles in the original report of Chuma-ov et al. (4). We found that genetic variation in the M23 wasssociated with both decreased hippocampal/parahippocampalctivation and increased prefrontal activation in fMRI and con-irmed that a similar pattern of activation differences was alsoeen for SNP M24 in our sample. These results strongly supporthe view that genetic variation in the M23/M24 region of theAOA gene has effects on cerebral function.Both SNP M23 and M24 lie 3’ to the coding region of the gene,
nd currently there is no evidence that either variant has a directffect on gene function, although it is possible that geneticariation in this region influences gene function by an effect onene expression. The current study focussed primarily on SNP23; however, it is possible that the effects seen were mediatedia the closely linked SNP M24 or through another unspecifiedariant in LD with these markers.
Our results extend the findings of Goldberg et al. (17) in aumber of ways. Firstly we were able to study the effects ofenetic variation in DAOA on brain function in a relatively largeroup of subjects. The replication of effects of genetic variationn the M23/M24 region on both hippocampal and frontal lobeunction in this larger cohort lends considerable support to themportance of this region in modulating cerebral activation.econdly, we have been able to investigate the effects of geneticariation in DAOA in the context of a background of increasedenetic risk for schizophrenia. The use of high-risk subjectsnables the effect of genetic variation to be examined in theontext of increased genetic risk, without the potential confoundf syndromal illness. Thirdly, we have shown that variation inAOA is associated with opposite effects on hippocampal
unction and prefrontal function within a single behavioralaradigm. This result parallels that reported by Goldberg et al.cross different behavioral tasks and suggests that these oppositeffects cannot simply be explained by differences in the taskemands.
Substantial evidence supports the involvement of medialemporal lobe structures, in particular the hippocampus andarahippocampus, in the pathogenesis of schizophrenia (28,29).tructural studies have consistently reported decreases in hip-ocampal and parahippocampal volume in subjects with schizo-hrenia (30,31). These volume deficits are also reflected, to a
esser degree, in the genetic relatives of individuals with schizo-hrenia (2,32). Decreased hippocampal activation in patientsith schizophrenia has been demonstrated in a number of
unctional neuroimaging studies, particularly those testing epi-odic or relational memory (33,34). Fewer studies have demon-trated differences in parahippocampal activation between pa-ients with schizophrenia and control subjects, althoughysregulation of parahippocampal activation has been reported35). Notably decreased parahippocampal activation has beenemonstrated in the at-risk genetic relatives of patients withchizophrenia performing a verbal memory task (36). Theresent finding of a modulatory influence of DAOA genotype onippocampal and parahippocampal function suggests that ge-etic variation at this locus might contribute to the abnormalitiesf medial temporal lobe function seen in patients with schizo-hrenia, an effect that might be mediated by influences on theMDA receptor (4).Previous functional neuroimaging studies of both patients
ith schizophrenia and their unaffected relatives have reported
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both hypoactivation and hyperactivation of frontal cortex regions(1,2). These apparently discrepant findings can be understood asreflecting the complex interplay between task demand, perfor-mance, and prefrontal recruitment in which patient groups reachperformance capacity at a lower level than control subjects(37,38). Under such a model inefficient prefrontal cortex functioncan result in both hyperactivation and hypoactivation, depend-ing on the task demands. Amongst studies of at-risk relatives withbalanced task performance, right-sided prefrontal hyperactiva-tion has been one of the most consistently reported findings(2,38–44). Notably, two recent studies of unaffected relativeshave both reported hyperactivation of right inferior frontal gyrus(BA 47) in the same region that showed increased activation inTT subjects in the current study (43,44). This right-sided hyper-activation might represent a compensatory mechanism for im-paired prefrontal function as a whole. A compensatory role of theright inferior prefrontal cortex in the current study is suggestedby the fact that recruitment of this region was seen specifically inthe context of increasing task difficulty. The present findingstherefore support the view that genetic variation in DAOA mightcontribute to the hyperactivation of right prefrontal cortex in thegenetic relatives of patients with schizophrenia.
We did not find an association between DAOA genotype atSNP M23 or M24 and development of psychosis in the presentstudy. Given that genetic variation in DAOA has only been foundto confer modest increase in overall risk for schizophrenia, thecurrent sample is likely not to have sufficient power to demon-strate an association effect (12). However two meta-analyseshave recently confirmed that genetic variation in the M23/M24region of DAOA is associated in large samples with increased riskfor schizophrenia (12,13). In addition genetic variation in DAOAhas also been shown to be associated with specific phenotypicfeatures within groups of subjects with schizophrenia, includingcognitive dysfunction and mood disorder (17,45). These inter-mediate phenotypes might be present in both at-risk relativeswho do not manifest the full schizophrenia syndrome as well asthose with established illness, decreasing the power of family-based studies to demonstrate an association with the disorder asa whole.
The present work supports the DAOA gene product as apotential target for the modulation of hippocampal and frontallobe function in schizophrenia. These brain regions are well-known to be involved in mnemonic and executive function thatare impaired in the disorder. The current study confirms thatgenetic variation in the DAOA gene is associated with alteredactivation of the hippocampus and frontal lobe as assessed byfMRI.
The work was funded by the Medical Research Council andthe Dr Mortimer and Theresa Sackler Foundation. The author JHis supported by an MRC Clinical Research Training Fellowship,and AMcI is supported by The Health Foundation. The authorsHCW and SML are supported by the Dr Mortimer and TheresaSackler Foundation. Genotyping was performed at the WellcomeTrust Clinical Research Facility, Edinburgh. Brain Imaging wasperformed at the SFC Brain Imaging Research Centre in Edin-burgh. We would also like to thank all the participants.
The authors JH, HCW, AMcI, and SML have received fundingfrom the Translational Medical Research Collaboration, which isin part funded by Wyeth, for work unrelated to the currentreport. The other authors reported no biomedical financial
interests or potential conflicts of interest.
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