Genes, Brain and Behavior (2014) 13: 653–662 doi: 10.1111/gbb.12154

SIRPB1 copy-number polymorphism as candidatequantitative trait locus for impulsive-disinhibitedpersonality

M. Laplana†,‡,1, J. L. Royo†,‡,1, L. F. García§,A. Aluja∗,‡,¶, J. L. Gomez-Skarmeta∗∗ andJ. Fibla∗,†,‡

†Department of Basic Medical Sciences, University of Lleida,‡Institute of Biomedical Research of Lleida (IRBLleida), Lleida,Catalonia, §Department of Biological and Health Psychology,Autonomous University of Madrid, Madrid, ¶Department ofPedagogy and Psychology, University of Lleida, Lleida, Catalonia,and ∗∗Developmental Biology Center of Andalucia, Pablo deOlavide University-Junta de Andalucia-CSIC, Seville, Spain1These authors contributed equally to this work.

*Corresponding authors: J. Fibla, Genetics of Complex Dis-eases Research Group, Departament de Ciències MèdiquesBàsiques, Universitat de Lleida-IRBLLEIDA Campus de Cièn-cies de la Salut, Edifici Biomedicina I. Av. Rovira Roure, 80,25198 Lleida, Catalonia. Spain. E-mail: joan.fibla@cmb.udl.cat andA. Aluja, Psychobiological Models of Personality: Neurotrans-mission and Behavior Genetics Research Group, Universitat deLleida, Avda, Estudi General 4, 25100 Lleida, Catalonia. Spain.E-mail: aluja@pip.udl.cat

Impulsive-disinhibited personality (IDP) is a behavioral

trait mainly characterized by seeking immediate grati-

fication at the expense of more enduring or long-term

gains. This trait has a major role in the development of

several disinhibitory behaviors and syndromes, including

psychopathy, attention-deficit and hyperactivity disor-

der, cluster-B personality disorders, criminality and alco-

holism. Available data consistently support a strong heri-

table component, accounting for 30–60% of the observed

variance in personality traits. A genome-wide analysis

of copy-number variants was designed to identify novel

genetic pathways associated with the IDP trait, using a

series of 261 male participants with maximized oppo-

site IDP scores. Quantitative trait locus analysis of candi-

date copy-number variants (CNVs) was conducted across

the entire IDP continuum. Functional effects of asso-

ciated variants were evaluated in zebrafish embryos.

A common CNV mapping to the immune-related gene

SIRPB1 was significantly associated with IDP scores in a

dose-dependent manner (𝜷 =−0.172, P <0.017). Expres-

sion quantitative trait locus analysis of the critical region

revealed higher SIRPB1 mRNA levels associated with the

haplotype containing the deleted allele (P < 0.0007). Epi-

genetic marks highlighted the presence of two potential

insulators within the deleted region, confirmed by func-

tional assays in zebrafish embryos, which suggests that

SIRPB1 expression rates are affected by the presence/

absence of the insulator regions. Upregulation of SIRPB1

has been described in prefrontal cortex of patients with

schizophrenia, providing a link between SIRPB1 and dis-

eases involving disinhibition and failure to control impul-

sivity. We propose SIRPB1 as a novel candidate gene to

account for phenotypic differences observed in the IDP

trait.

Keywords: Association study, behavior, CGH, copy-numbervariant, disinhibition, eQTL, impulsivity, insulator, personality,SIRPB1

Received 24 April 2014, revised 12 June 2014, accepted forpublication 3 July 2014

Impulsive-disinhibition behavior has been defined as the lackof active inhibitory processes that regulate the tendencyto respond. Accordingly, the psychopathology of disinhibi-tion refers to a disposition focused more on immediategratification than on obtaining long-term rewards or con-sidering negative future consequences (Gorenstein & New-man 1980). This construct underlies several psychopatho-logical syndromes defined by a failure to inhibit or controlimpulses, including psychopathic personality, antisocial andhistrionic personality disorders, attention deficit and hyper-activity disorder, and primary alcoholism (Zuckerman 1999).The impulsive-disinhibited personality (IDP) trait describesa continuum from strong inhibition to an extreme pole ofimpulsive-disinhibition behavior characterized by a tendencyto commit social transgressions (García et al. 2010).

Research consistently supports the hypothesis of a strongheritable component in personality traits, typically accountingfor 30–60% of the observed variance (Loehlin 1992; Plomin1990). A large meta-analysis of twin and adoption studiesestimated the magnitude of genetic and environmental influ-ences on antisocial behavior. According to this meta-analysis,the best-fitted model included moderate proportions of vari-ance due to additive (32%) and non-additive (9%) geneticinfluences, as well as shared (16%) and non-shared (43%)environmental influences (Rhee & Waldman 2002). Thus,about 40% of the differences in a behavioral pattern closelyassociated with IDP were explained by genetic sources(Eaves et al. 1989).

Genome-wide association studies have been performedto explore the impact of individual genetic differences onpersonality traits, focusing on psychiatric disorders suchas schizophrenia, manic-depressive illness, bipolar disor-der and autism (Alliey-Rodriguez et al. 2011; Munafò et al.2003; Schinka et al. 2004; Tucker et al. 2011; Zuckermanet al. 1993). However, the genetic evidence associated with

© 2014 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society 653

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non-pathogenic personality traits such as novelty-seekingand impulsive-disinhibited behaviors is far from being con-clusive (Munafò & Gage 2013; Munafò et al. 2003). No singlemodel of inheritance can be easily applied to behavior andpersonality. As for other complex traits, to date only a smallpercentage of the estimated heritability of personality traitscan be explained by an association with single nucleotidepolymorphisms (Munafò et al. 2003). Novel approaches areneeded, including the evaluation of alternative genomicsources of variability, to capture this missing heritability.

Copy-number variants (CNVs) are structural polymorphicregions involving several kilobases and are spread through-out the human genome. Some authors suggest that theireffect on transcriptional regulation may be greater than thatattributed to single nucleotide polymorphisms (Henrichsenet al. 2009; Schlattl et al. 2011). Associations between CNVand behavioral traits have been explored, with encouragingresults (Cook & Scherer 2008; Luciano et al. 2012; Need et al.2009; Vu et al. 2011). Thus, the aim of this study was toexplore the role of CNVs throughout the IDP continuum.

Methods

ParticipantsThe study recruited 261 male participants, including 153 prisoninmates (mean age: 33.7; SD: 8.7) and 108 university student vol-unteers (general population donors) (mean age: 26.7; SD: 9.7). Allparticipants completed personality questionnaires and gave a salivasample for DNA extraction. Criteria for exclusion were non-Caucasianethnicity, previous diagnosis of psychotic or affective disorder, andbeing a relative of any other participant in the study.

Each participant received a document explaining the purpose ofthe study, written at an appropriate reading level, and providedsigned consent to participate. All participants were informed that theirparticipation was voluntary and they could remove themselves fromthe study at any time. No incentives were provided in any case. Thestudy protocol conforms to the ethical guidelines of the Declarationof Helsinki and was approved by the Ethics Committee for ClinicalResearch of the University of Lleida and University Hospital Arnau deVilanova.

Personality variables and psychometric scales

Aggression-hostility scaleA validated short-form scale with 13 items was used (Aluja et al.2003). About half of the items are related to readiness to expressverbal aggression and the remainder to rudeness, thoughtless orantisocial behavior, revengefulness and spitefulness. On this scale,high scores indicate a quick temper and impatience with others.

Barratt impulsivity scaleThese 34 items measure motor, cognitive and unplanned impulsive-ness (Barratt 1985). These correspond to acting without thinking,making quick cognitive decisions on the spur of the moment, and‘present orientation’ or lack of ‘futuring’, respectively.

Impulsive sensation-seeking scaleTaken from the Zuckerman-Kuhlman Personality Questionnaire (Zuck-erman et al. 1993), this scale measures lack of planning and the ten-dency to act impulsively without thinking. The questions are generaland do not ask about specific activities such as drinking or sex. Mostitems describe the tendency to seek experiences or the willingnessto take risks for the sake of excitement or novelty.

Novelty-seeking scaleThis 40-item scale from the Temperament and Character Inventory(Cloninger et al. 1993; Eysenck & Eysenck 1997) reflects a tendencytoward impulsive decision-making, exploratory activity in response tonovelty and active avoidance of monotony.

Psychoticism scaleThis 12-item ‘P scale’ was derived from the revised Eysenck Person-ality Questionnaire (Aluja et al. 2003; Eysenck & Eysenck 1997). Itmeasures egocentrism, lack of empathy and proneness to antisocialbehavior.

Sensitivity-to-reward questionnaireThis 24-item scale was taken from the Sensitivity to Punishment andSensitivity to Reward Questionnaire (Torrubia et al. 2001).

Impulsiveness-disinhibition indexAfter computing the personality variables and psychometric scales,the impulsiveness-disinhibition index (z-index) was formed by addingthe z value of the six personality scales to obtain a standardized,continuous measure (Aluja et al. 2011).

Genome-wide analysisComparative genomic hybridization (CGH) analysis was performedusing the Agilent 2X400K CGH array in a discovery group of 20 par-ticipants whose scores on the impulsive-disinhibition questionnairesfitted>Q75. A whole-genome amplification kit (WGA2, Sigma-Aldrich,St. Louis, MO, USA) was used to amplify DNA whenever needed.DNA from each high-scoring participant was compared with a poolof DNA obtained from 21 low-scoring participants (<Q25). Arrayswere processed by Oxford Gene Technology facilities (Oxford, UK).Agilent CytoGenomics 2.5.8.11 software was used to identify CNVregions (CNVRs). Log2 ratios were corrected for GC content witha window of 10 Kb. Two arrays of self-to-self hybridization sampleswere used to set the aberration detection algorithm (ADM2) at athreshold of 9.5. All genomic coordinates refer to UCSC version hg19(http://genome.ucsc.edu).

Multiplex ligation-dependent probe amplification

analysesGene-dosage variations at NEGR1, LCE3C, UGT2B17, SIRPB1and GSTTP1/2 loci in CNVRs were analyzed by multiplexligation-dependent probe amplification (MLPA) technology. FollowingMRC-Holland (Amsterdam, Netherlands) recommendations, wedesigned five sets of probes using MAPD: MLPA probe design soft-ware (http://genomics01.arcan.stonybrook.edu/mlpa2/cgi-bin/mlpa.cgi) to detect CNVs affecting these genes (Table S1, SupportingInformation). The MLPA EK-1FAM P300A2 kit was supplied byMRC-Holland. Capillary electrophoresis analysis was performed withan ABI PRISM Genetic Analyzer 3130 (Applied Biosystems, FosterCity, CA, USA) and data were analyzed using GeneMarker v1.75(Softgenetics L.L.C., State College, PA, USA).

Taqman genotyping assaysSIRPB1 CNV status was determined according to a previouslyreported assay (Jin et al. 2011) using a commercially available Taq-man probe (Hs04057639). According to manufacturer instructions,RNaseP locus was used as internal control for gDNA copy-numberstandardization (reference PN4316831). Genotyping of SIRPB1rs2209313 marker was performed by Taqman assay (referenceC1911298).

Online resources and statistical analysisGene ontology analysis was performed using Genotype-PhenotypeIntegrator (http://ncbi.nlm.nih.gov) and GeneDecks v3 online resource

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Figure 1: Distribution of z-index values. Histogram representation of z-index values from population donors (white boxes) andinmates (gray boxes). Lines correspond to fitted normal distribution for population donors (dotted gray line; M=0.213; SD=0.991;Kolmogorov-Smirnov test for normal distribution P < 0.468), inmates (continuous gray line, M=−0.302; SD= 0.967; P <0.673) andboth subsets joined (continuous black line, M=0; SD=1; P <0.563).

(http://www.genecards.org). Expression quantitative trait locus(eQTL) analysis for the markers at the SIRPB1 genomic regionchr20:1528038-1621686 was performed by correlating genotypedata obtained from unrelated CEPH individuals (Hapmap release2) with SIRPB1 mRNA expression levels of their respective lym-phoblastoid cell lines, obtained from the GO profiles available fromthe NCBI web (DO ID: 25703673). The presence of cis-regulatoryelements near SIRPB1 promoter was evaluated, taking into accountthe chromatin immunoprecipitation tracks from the ENCODE project(http://genome.ucsc.edu/). Statistical analyses were performedusing PLINK v1.07 (Purcell et al. 2007) and IBM SPSS software v20.Graphical representation of data was performed with the aid of Locus-Zoom web tool (http://csg.sph.umich.edu/locuszoom/) (Pruim et al.2010).

In vivo enhancer-blocking assaysTo evaluate the potential insulator activity of the CTCF-associatedregions, we used a Tol2 transposase-derived vector assay, as pre-viously described (Bessa et al. 2009; Royo et al. 2010). This con-struct contains a strong midbrain enhancer, a Gateway™ (Invitro-gen, Carlsbad, CA, USA) entry site, and the cardiac actin promotercontrolling GFP expression. Each candidate region was recombinedbetween the midbrain enhancer and the cardiac actin promoter; theoriginal non-recombined backbone was used as a negative control.Wild-type zebrafish embryos at the one-cell stage were injected with3–5 nl of a solution containing 25 nM of each construct plus 25 nM

of Tol2 mRNA. Embryos were then incubated at 28∘C and GFPexpression was evaluated 24 hours post-fertilization (hpf). The mid-brain/somite GFP intensity ratio was quantified using ImageJ free-ware. The human regions tested (INS1 and INS2) were delimitedby the following primers: Ins1F: (5′-CTCCACCTTGACTCCCAGTAA-3′)and Ins1R (5′-ATATGTTGCCACAGGCATCC-3′) on one side, and Ins2F(5′-CACAGCAGGCAGCTACAAAG-3′) and Ins2R (5′-TACTGGGTTTCAGGCATGGT-3′) on the other side.

RESULTS

Comparative genomic hybridization identified

NEGR1, LCE3C, UGT2B17, SIRPB1 and GSTTP1/2

as candidate genes

The series (n= 261) presented a normal IDP z-index distri-bution (P < 0.563, Kolmogorov-Smirnov test). The inclusionof both inmates and controls allowed us to create a singlestudy population with a wider amplitude in the spectrum ofIDP scores (Fig. 1).

As a discovery strategy we first selected participants witha higher IDP z-index (>Q75, n= 20) to perform high-resolutionCGH, using as reference a genomic DNA pool obtained fromparticipants with a lower IDP z-index (<Q25, n= 21). The ratio-nale for this opposite-phenotype comparison was to maxi-mize the potential genomic differences associated with theIDP trait. Results from the CGH arrays are summarized inFig. 2. A total of 54 CNV regions (CNVRs) were detected,25 (46%) containing gains, 27 (50%) containing losses and2 (4%) containing both gains and losses (Table S2). Com-parative genomic hybridization analysis revealed that oneindividual carried an extra X chromosome; the diagnosis ofKlinefelter Syndrome excluded this participant from furtheranalysis. On average, we observed 6.6 CNVRs per individual,with a range from 2 to 14.

Most CNVRs were present on a single individual(33.66%). The two most frequent CNVs were presentin 11 and 15 individuals (chr2:179385858-179528531 and

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Figure 2: Comparative genomic analysis results. Overall view of the CNV regions identified by comparative genome hybridization(a). Representative plots of the five CNV regions selected for subsequent studies (b).

chr20:560379-1590485, respectively). On average, CNVRsexpanded to 109 Kb, ranging from 9 to 800 Kb; all but sevenwere already described. From the total of 76 genes locatedon the 54 CNVR genomic intervals, we selected NEGR1,LCE3C, UGT2B17 , SIRPB1 and GSTTP1/2 as candidategenes, based on their prevalence or potential phenotypicinvolvement in behavior disturbances according to geneontology analysis.

Copy-number variation analysis of selected

candidates revealed SIRPB1 CNVR as a quantitative

trait locus for IPD

We designed MLPA probes for each of the five selectedCNV regions, taking interindividual variation into account.Thus, only the common gained/lost regions of each CNVR

were analyzed. A subset of 57 participants representingthe total ID>Q75 sample were subjected to MLPA analysisfor these five CNVRs. For quality control, 10% duplicateswere included in the experiment, with 100% concordance.MLPA results fitted the data obtained from the CGH anal-ysis. Copy-number distribution of the different CNVRs issummarized in Table S3. SIRPB1 copy-number status wassignificantly correlated with several impulsive-disinhibitedparameters, including Barratt impulsivity scale (Tau=−302;P <0.022), impulsive sensation-seeking (Kendall-Taunon-parametric correlation tests=−0.349; P <0.008),novelty-seeking (Tau=−0.262; P <0.049) and psychoticism(Tau=−0.278; P <0.036) (Table 1). Moreover, increasedSIRPB1 CNV was associated with lower scores on thez-index (Tau=−0.324; P <0.014), which integrates all thepersonality variables considered.

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Table 1: Kendall-Tau non-parametric correlations between personality variables and candidate CNVRs

NEGR1 LCE3C UGT2B17 SIRPB1 GSTTP1/2

Personality variables Tau P< Tau P< Tau P< Tau P< Tau P<

Aggression-hostility −0.058 0.671 −0.046 0.731 −0.137 0.310 −0.231 0.084 −0.012 0.930Barratt impulsivity 0.032 0.811 0.052 0.702 0.114 0.400 −0.302 0.022 0.028 0.837Impulsive sensation-seeking 0.175 0.193 −0.093 0.491 −0.054 0.690 −0.349 0.008 −0.166 0.218Novelty-seeking 0.050 0.714 0.047 0.731 −0.025 0.855 −0.262 0.049 0.101 0.455Psychoticism 0.094 0.486 −0.154 0.254 −0.090 0.505 −0.278 0.036 −0.106 0.432Sensitivity to reward 0.191 0.154 −0.102 0.450 −0.158 0.240 −0.078 0.563 −0.045 0.737Impulsive-disinhibition z-index 0.113 0.402 −0.072 0.593 −0.071 0.597 −0.324 0.014 −0.060 0.658

Table 2: Regression analysis of selected personality variablesand SIRPB1 CNV copies

Personality variables 𝛽

95%CI(lower:upper) P-value

Aggression-hostility −0.184 −0.616:0.248 0.402Barratt impulsivity −3.212 −5.796:−0.628 0.015Impulsive

sensation-seeking−0.863 −1.342:−0.385 <0.001

Novelty-seeking −0.653 −1.428:0.122 0.098Psychoticism −0.237 −0.592:0.118 0.190Sensitivity to reward −0.105 −0.788:0.578 0.763Impulsive-disinhibited

z-index−0.172 −0.312:−0.031 0.017

Regression analysis included age in the equation.

Given these results, we extended the analysis of theSIRPB1 CNV to all study participants finding a total of 167(70.5%) subjects with 0 copies, 29 (12.2%) subjects with1 copy, 31 (13.1%) subjects with 2 copies and 10 (4.2%)subjects with 3 copies. No differences were observed oncopy-number distribution between inmates and controlsubsets (Contingency Table Analysis, P <0.172). Table 2

shows the results of linear regression analysis of SIRPB1CNV-genotypes according to the different personality vari-ables for the all study participants. When age was included,regression analysis showed statistical significance forBarratt impulsivity scale-10 (𝛽 =−3.212, P <0.015), impul-sive sensation-seeking (𝛽 =−0.863, P <0.001) and z-index(𝛽 =−0.172, P <0.017). Figure 3 illustrates the significantreduction in the z-index associated with SIRPB1 CNVstatus. Thus, we could conclude that the presence ofadditional copies of the SIRPB1 CNV was correlated withreduced scores for different personality traits, especiallythose measured by the Barratt impulsivity and impulsivesensation-seeking scales. The nature of this association wasconsistent for both the inmate and control subsets, but wassignificant only in controls (data not shown).

The haplotype bearing the SIRPB1 CNV-deleted

allele was correlated with increasing levels of SIRPB1

expression

SIRPB1 CNV expands along chr20: 1560379-1590485 coor-dinates that include the SIRBP1 intron 1. We integrated thegenotypes of unrelated individuals from CEU series withthe mRNA expression levels from their corresponding lym-phoblastic cell lines (n=56).

(a) (b)

Figure 3: Distribution of z-index values according to the SIRPB1 CNV genotype. Box plot of the impulsivity-disinhibition z-indexvalues according to the SIRPB1 CNV genotype (a). Lines represent the range, gray boxes both Q25 and Q75. Dashes representtheir respective mean. Relative distribution of individuals carrying 0–3 SIRPB1 CNV copies in impulsivity-disinhibition percentilesubgroups (b).

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(a)

(b)

(c)

(d)

Figure 4: eQTL analysis of

SIRPB1. (a) Results from regres-sion analysis of markers in theSIRPB1 vicinity using data fromHapMap CEU linfoblastoid celllines. Colors represent link-age disequilibrium (LD) values(r2) between each marker andSIRPB1 CNV tagSNP rs2209313.Blue line represents regionalrecombination rates. Aster-isk indicates departure fromHardy-Weinberg equilibrium.(b) Results from regressionanalysis of haplotypes definedby rs6034036, rs2263664 andrs2209313 markers. Green-Redgradient indicates correlationcoefficient sign. Sizes of col-ored circles are proportional tothe haplotype frequencies. (c)Genomic coordinates of theSIRPB1 genomic region accord-ing to hg19 that apply to panels(a) and (b). (d) Results fromregression analysis of GG(D)Cimputed diplotypes.

eQTL analysis revealed two markers associated withSIRPB1 mRNA expression (rs6034036; 𝛽 =−17.32, P <0.005and rs2263664; 𝛽 =−11.8, P <0.002) (Fig. 4a and Table S4).

Previous studies reported that the SIRPB1 CNV-deletedallele was in strong linkage disequilibrium (LD) (r2 =0.93,D′ = 1) with rs2209313 allele-C (Jin et al. 2011). We geno-typed rs2209313 in our sample showing that SIRPB1CNV-deleted allele was mainly captured by rs2209313-Callele (94% of homozygous subjects for SIRPB1 CNV-deletedallele were also rs2209313-CC homozygotes). Using

rs2209313 as tagSNP for SIRPB1 CNV we inferredhaplotypes including markers rs6034036, rs2263664 andrs2209313 in the HapMap sample. We found four haplo-types representing 61% (GGC), 22.2% (GTT), 10.2% (ATC)and 6.6% (GGT) of the total HapMap sample. Taking intoaccount the observed linkage between SIRPB1 CNV-deletedallele and rs2209313-C allele we can infer that the commonhaplotype GGC harbors the deletion (D), hereafter haplotypeGG(D)C. Regression analysis showed that the haplotypeGG(D)C was significantly associated to higher levels of

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Figure 5: Epigenetic marks of the SIRPB1 proximal regulatory landscape. Data according to the ENCODE project and the BROADinstitute public chromatin immunoprecipitation results. Boxed region corresponds to the CNV region found within SIRPB1 intron 1.H3K4me1 stands for monomethylation of histone-3 lysine 4. H3K27ac stands for acetylation of histone-3 lysine 27. CTCF ChIP from bothH1-hESC and GM12878 cell lines are also plotted. INS1 and INS2 indicate the two regions that were selected for the enhancer-blockingassays. Yellow shadowed region corresponds to deleted region.

SIRPB1 expression (𝛽 =12.4, P <0.0006) (Fig. 4b). Weimputed GG(D)C diplotype status of subjects and performedregression analysis that showed high expression levels ofSIRPB1 in GG(D)C homozygotes, intermediate in GG(D)Cheterozygotes and low in non carriers of GG(D)C haplo-type (𝛽 =0.421; P <0.001)(Fig. 4d). These data allow us topropose that the eQTL results obtained for the markers atthe SIRPB1 genomic landscape may be attributable to theSIRPB1 CNV-deleted allele.

SIRPB1 CNV observed to contain CTCF-associated

insulator regions

To explore the potential link between an intronic deletionand the variations in mRNA levels of SIRPB1, we examinedthe genomic environment to determine the presence ofpotential cis regulatory elements. Interestingly, two potentialbinding sites for the transcriptional repressor CTCF werepresent in the deleted region, acting as insulators. We pos-tulated that the absence of these insulators might alter theregulatory landscape of SIRPB1 and allow the interaction ofadditional enhancers. To test this hypothesis, we isolated theregions designated as INS1 and INS2 (Fig. 5) and evaluatedtheir insulator activity using Tol2-mediated transgenesis inzebrafish embryos.

As shown in Fig. 6a, whenever an insulator is placedbetween the midbrain enhancer and the actin promoter,the resulting embryos exhibit a significant decrease in GFPexpression levels in the brain. Some illustrative examplesare shown in Fig. 6c–e. Upon quantification, we determinedthat both INS1 and INS2 exhibited a statistically significantreduction of the midbrain/muscle GFP expression ratio whencompared to the control transposon using the Kruskal-Wallistest (P <0.007 and P <0.001, respectively). These resultssuggest that in their natural genomic context these regionswould contribute to preventing the cis-regulatory action of

downstream enhancers, which may compromise regulationof the SIRPB1 promoter.

DISCUSSION

Differences in personality traits, including impulsive-disinhibited dimensions, are associated with geneticbackground. However, identification of specific variants asso-ciated with concrete behavioral traits has eluded researchers.Considering the state-of-the-art in the genetic approach toquantitative traits, some authors have recommended exten-sive psychological evaluation based on several phenotypicmeasures, use of an extreme groups design, and thedevelopment of new genetic approaches (Munafò et al.2003). Our study design followed these recommendations.

Extreme phenotype groups (top scores vs. low scoreson IDP z-index) were subjected to CNV discovery analysis.Correlation tests were performed, taking into account boththe personality scores and the copy-number status of thecandidate CNV regions identified. We found a CNV affectingSIRPB1 intron 1 that was statistically correlated with vari-ous impulsivity measurements. The analysis was extendedto the full series, showing that the presence/absence ofthe 30.1 Kb region within SIRPB1 intron 1 was correlatedwith the levels of impulsivity and sensation-seeking in acopy-number dependent manner. This association allowedus to propose SIRPB1 as a novel candidate gene associatedwith the IDP trait in men.

Signal regulatory proteins (SIRP) constitute a family oftransmembrane glycoproteins with extracellular Ig-likedomains. Several SIRP family members have thus far beenidentified on myeloid cells, and some reports have addressedtheir immunological properties. Specifically, SIRPB1 hasbeen associated with the innate immune system (van Beek

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Figure 6: Enhancer-blocking assay. Representative diagram of the basis of the enhancer-blocking assay (a). In the absence of aninsulator, the enhancer –E– contacts the promoter –P– and activates transcription both in the muscles and the midbrain. Wheneveran insulator –I– is located between the enhancer and the promoter, midbrain expression is compromised (a’). Box plot of themidbrain/somite GFP expression ratio obtained 24 hpf from individual zebrafish injected with each construct (Backbone n=72, INS1n=55, and INS2 n=53) (b). Lines represent the range, gray boxes both Q25 and Q75. Dashes represent means. (**) P-value<0.01and (*) P-value<0.007 by Kruskal-Wallis tests. Somite expression did not show differences between constructs (P < 0.1, Kruskal-Wallistest). Panels (c) to (e) show a representative animal in each series (Control, INS1 and INS2, respectively) under visible light (c to e) andfluorescence (c’ to e’).

et al. 2005). There is evidence that ionic interaction betweenSIRPB1 and adapter protein DAP12 leads to phosphorylationof spleen tyrosine kinase and mitogen-activated proteinkinase, and promotes phagocytosis by macrophages andthe migration of neutrophils as part of the regulation ofinflammatory response (Barclay & Brown 2006).

The relationship between the immune system statusand behavior is not new and constitutes one of the bestevolutionary-conserved circuits in vertebrates. Differentbehavioral traits have been associated with pro-inflammatorycytokines. Upon infection, the body naturally undergoes aseries of behavior alterations, including disinterest in socialinteractions or engagement with the environment, lethargy,reduction in motor activity, somnolence and failure to concen-trate. This is an adaptive response that enhances recoveryby conserving energy to combat acute inflammation.

There is evidence that this behavior is mediated bypro-inflammatory cytokines such as IL-1, TNFa or IL6 (Maeset al. 2012). Therefore, we cannot rule out the possibilitythat common variants affecting immune-related genes suchas SIRPB1 are associated with behavior traits. A recentgenome-wide screen performed at a 10-cM resolution indepressive patients of Turkish origin reveals a region within20p13 as a locus for depression (LOD= 1.95). The critical

region contains the SIRPB1 gene and was mapped betweenD20S103 and D20S484 (Bulayeva et al. 2012). This line ofresearch is supported by our finding that links SIRPB1 withpersonality, as depression is correlated with some person-ality variables, including sensation-seeking (Duggan et al.2002; Farmer et al. 2001).

Expression quantitative trait locus (eQTL) analysis sug-gested that the haplotype containing the CNV-deleted alleleexhibit higher rates of SIRPB1 transcription than those bear-ing at least one insertion of the CNV. We have identified twoCTCF-enriched regions within the SIRPB1 intron 1 that wereaffected by the CNV. These two sequences (here named INS1and INS2) clearly displayed in vivo enhancer-blocking capac-ity when assayed in zebrafish embryos. This allowed us topostulate that the lack of these insulators in the 3′ region ofthe SIRPB1 promoter as it appears on the CNV-deleted allelewould facilitate the interaction of downstream enhancers,leading to an increase in SIRPB1 transcription rates.

Other authors have reported overexpression of SIRPB1 insuperior temporal neocortex from Alzheimer disease patientsand in prefrontal cortex samples from schizophrenia patients(Gaikwad et al. 2009; Martins-de-Souza et al. 2009). Impor-tantly, the prefrontal cortex plays a major role in gating impul-sive actions in several behavioral tasks (Kim & Lee 2011).

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SIRPB1 and personality

It remains to be determined whether the reported SIRPB1overexpression in a disease involving disinhibition and failureto control impulsivity – such as schizophrenia – is related tothe CNV described here.

It should be outlined that SIRPB1 region shows a complexgenomic structure with a total of 14 isoforms described fromwhich only four (isoforms 1, 2, 3 and 5) have a consensus CDSprotein. The CNV deleted allele leaves isoforms 1 and 2 intactwhile affecting isoforms 3 and 5. The eQTL association isbased on the analysis of Affymetrix probes series 206934_at,that labels 3′UTR region of isoforms 1 and 2. No single workhas been addressed to date characterizing the differentialfunctionality of SIRPB1 splice variants. Thus, we cannotrule-out additional effects of the CNV as a consequence ofthe nonsense-mediated decay of isoforms 3 and 5.

Our study opens a new avenue for future research, pro-viding the first evidence for the association of SIRPB1 CNVwith a complex personality trait; replication in other cohortswill be needed to validate the association with IDP that weobserved. In addition, in-depth molecular characterization isneeded to better understand the contribution of the CNV toSIRPB1 regulation.

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Acknowledgments

We wish to express our sincere thanks to the study participantsfor their invaluable contribution, as well as to the staff mem-bers who assisted us. We thank Ana Fernandez Miñan and Car-men Hidalgo for their technical help. We also thank Elaine Lilly,Ph.D. (Writer’s First Aid), for English language revision of themanuscript. This study was founded by Fundació Marató TV3 (ref200925-10). All authors declare no conflict of interest.

Supporting Information

Additional supporting information may be found in the onlineversion of this article at the publisher’s web-site:

Table S1: Probe sequences for multiplexligation-dependent probe amplification.

Table S2: CNV summaryTable S3: Copy number distribution analyzed by MLPA.Table S4: Selected SNP from HapMap covering SIRPB1

genomic region (chr20: 1528038-1621686).

662 Genes, Brain and Behavior (2014) 13: 653–662