Literature DB >> 25658328

Polymorphism in the serotonin receptor 2a (HTR2A) gene as possible predisposal factor for aggressive traits.

Zsofia Banlaki1, Zsuzsanna Elek1, Tibor Nanasi1, Anna Szekely2, Zsofia Nemoda1, Maria Sasvari-Szekely1, Zsolt Ronai1.   

Abstract

Aggressive manifestations and their consequences are a major issue of mankind, highlighting the need for understanding the contributory factors. Still, aggression-related genetic analyses have so far mainly been conducted on small population subsets such as individuals suffering from a certain psychiatric disorder or a narrow-range age cohort, but no data on the general population is yet available. In the present study, our aim was to identify polymorphisms in genes affecting neurobiological processes that might explain some of the inter-individual variation between aggression levels in the non-clinical Caucasian adult population. 55 single nucleotide polymorphisms (SNP) were simultaneously determined in 887 subjects who also filled out the self-report Buss-Perry Aggression Questionnaire (BPAQ). Single marker association analyses between genotypes and aggression scores indicated a significant role of rs7322347 located in the HTR2A gene encoding serotonin receptor 2a following Bonferroni correction for multiple testing (p = 0.0007) both for males and females. Taking the four BPAQ subscales individually, scores for Hostility, Anger and Physical Aggression showed significant association with rs7322347 T allele in themselves, while no association was found with Verbal Aggression. Of the subscales, relationship with rs7322347 was strongest in the case of Hostility, where statistical significance virtually equaled that observed with the whole BPAQ. In conclusion, this is the first study to our knowledge analyzing SNPs in a wide variety of genes in terms of aggression in a large sample-size non-clinical adult population, also describing a novel candidate polymorphism as predisposal to aggressive traits.

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Year:  2015        PMID: 25658328      PMCID: PMC4319849          DOI: 10.1371/journal.pone.0117792

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Introduction

Aggression, defined as any behavior intended to be destructive, lies at the root of numerous major ills of humanity ranging from verbal abuse through both interpersonal and self-directed violence to mass criminal acts. Consequences of aggression-driven acts pose an enormous burden on society and economics, rendering it important to understand the biological basis behind [1,2]. Increased levels of aggression are characteristic to patients with a variety of neurodegenerative and psychiatric disorders as well as to alcoholics and drug addicts [3-7], but can also often be observed among the normal human population, even conferring certain privileges to the aggressor under certain circumstances e.g. by means of social dominance [8,9]. From the evolutionary point of view, some degree of aggression is indeed necessary for gaining adequate fitness (through an improved access of food supplies and other resources) and reproductive success; however, these benefits are compensated for by an increased risk of injury and social isolation. Hence, optimal levels of aggression are presumably shaped by a fine balance between effects of positive and negative selection pressure, implying a strong genetic background next to the role of environment [10,11]. This assumption is further underpinned by the fact that aggression proved to be heritable in several twin studies, with an estimated genetic contribution to the risk of aggressiveness of above 40% [12-17]. Experimental evidence suggest that aggressive manifestations and the accompanying emotions (anger, anxiety, fear) can be strongly related to highly conserved brain regions, chiefly to the amygdala and its linked neural circuits, but also to the anterior cingulated cortex and the prefrontal cortex [18,19]. In terms of biochemistry, it is principally the monoaminergic neurotransmitter systems (e.g. dopamine, noradrenaline and serotonin pathways) that are believed to play a major role in aggressive behavior, though possible effects of sexual hormones, the hypothalamic-pituitary-adrenal (HPA) axis and blood sugar levels have also been implicated [20,21]. Great efforts have been made to decipher the possible genetic background behind predisposition to aggression, describing novel polymorphisms in a variety of genes with a role in neuropsychiatry, and also identifying promising candidates for aggressive behavior and the related mental states (impulsivity, hostility). However, most of these association studies were carried out in small samples, raising the possibility of committing statistical errors (Pavlov 2012). Besides, the vast majority of aggression-related genetic investigations either were based on comparisons between healthy individuals and patients suffering from personality disorders etc., or concentrated on restricted samples not representative of the general population (e.g. [22-28]). These factors render data evaluation challenging, and often lead to controversial results. Our aim was to simultaneously examine the effect of a set of putatively functional single nucleotide polymorphisms (SNP) on aggressive tendencies of the general Hungarian adult population using a microarray system, with a principal focus on monoaminergic pathways and its close interactors. Selected SNPs are located in genes encoding monoaminergic neurotransmitter transporters and receptors, their associated proteins and other signal transduction molecules, enzymes involved in the biosynthesis or degradation of neurotransmitters, neurotrophic factors and regulators of circadian rhythm as well as of neuronal death, all with an implicated role in emotional responses and behavioral traits [20,29-32].

Materials and Methods

Individuals involved

Non-related individuals of Caucasian Hungarian origin without any known psychiatric disorder were recruited for this study on a voluntary basis at the Institute of Psychology, Eotvos Lorand University (Budapest). Buccal samples and self-filled out aggression questionnaires were obtained from 887 subjects (45.8% males and 54.2% females). The sample comprised of 495 psychology and law enforcement students studying in the Budapest area and 392 random volunteers recruited at academic institutions and events popularizing this survey. All participants belonged to the middle socioeconomic status. Mean age was 23.2 (±7.55) years within the range from 18 to 75 years. All participants gave written informed consent and the study was approved by the Scientific and Research Ethics Committee of the Medical Research Council (“ETT TUKEB”—Ministry of Health, Medical Research Council, Budapest, H-1051 Hungary).

Phenotypic measure

The original 29-item version of the self-report Buss-Perry Aggression Questionnaire (BPAQ) [33] was used to assess aggressive tendencies. This instrument comprises four subscales: Verbal Aggression (5 items), Physical Aggression (9 items), Anger (7 items) and Hostility (8 items). Individual items are rated from one (‘extremely uncharacteristic of me’) to five (‘extremely characteristic of me’). Total score for aggression was calculated as the sum of ratings for all the items, with a possible range between 29 and 145. Hungarian version of the original English language questionnaire was obtained by the “forward-backward” translation method and was pilot tested prior to the present study [34].

Sample collection

Buccal cells were collected by gently scraping the inner cheek with cotton-tipped collection swabs. Genomic DNA preparation was performed by a traditional, salting-out procedure [35]. Briefly, collection swabs were incubated overnight in 450 μl cell lysis buffer (0.2 g/l Proteinase K, 0.1 M NaCl, 0.5% SDS, 0.01 M Tris buffer pH = 8.0) at 56°C, followed by RNase treatment at room temperature. Proteins were precipitated with saturated NaCl (6 M) and removed by centrifugation. DNA was precipitated with isopropanol, purified with 70% ethanol and resuspended in 100 μl of Tris-EDTA pH = 8.0 (containing 0.5 M EDTA). DNA concentrations were measured by a fluorometry based intercalation assay (AccuBlue Broad Range dsDNA Quantification Kit, Biotium). Concentration of samples analyzed in this study ranged between 15 and 200 ng/μl. Isolated DNA samples were kept at −20°C until used.

Marker selection

Common SNPs with a higher than 5% minor allele frequency (MAF) were selected from the dbSNP database of NCBI [36]. Priority was given to polymorphisms referred to in various association studies in connection with personality or mood disorders as well as aggression or impulsivity in psychiatric disorders, and to putative functional variants, either causing an amino acid change or with an implicated gene regulatory role.

Genotyping

Genotyping was performed in 384-well plates on an Open Array real-time PCR platform (Applied Biosystems) based on allele-specific, fluorescent (TaqMan) probes and pre-designed, validated primers immobilized to a solid surface obtained from the manufacturer. Approximately 100 ng DNA per sample was used in each measurement. DNA amplification was carried out in the GeneAmp PCR System 9700 (Applied Biosystems) according to the manufacturer’s instructions, using the master mix, containing each dNTP and AmpliTaq Gold DNA-polymerase, provided by the manufacturer. Endpoint detection of signal intensities of allele specific fluorescent dyes was conducted by the OpenArray NT Imager, and genotypes were called by the TaqMan Genotyper v1.2 software. Call rate for individual SNPs is shown in Table 1 (mean: 77.9%).
Table 1

Genotype distribution of the studied SNPs.

SNPGeneNGenotypeHWE* Call rate
MMMmmm
1.rs1048101 ADRA1A 76321828,6%38450,3%16121,1%0.94586%
2.rs3808585 ADRA1A 72239654,8%27738,4%496,8%0.99881%
3.rs2236554 ADRA1D 75729338,7%34645,7%11815,6%0.64185%
4.rs553668 ADRA2A 69251975,0%15822,8%152,2%0.77078%
5.rs11030104 BDNF 70239356,0%26437,6%456,4%0.99779%
6.rs2049045 BDNF 69041960,7%24134,9%304,3%0.82078%
7.rs6265 BDNF 60136260,2%21235,3%274,5%0.84768%
8.rs7103411 BDNF 71539355,0%27638,6%466,4%0.96681%
9.rs7094179 CDNF 68730544,4%30244,0%8011,6%0.92477%
10.rs7900873 CDNF 69638455,2%27339,2%395,6%0.57378%
11.rs1051730 CHRNA3 75332042,5%34545,8%8811,7%0.94385%
12.rs16969968 CHRNA5 66327942,1%30746,3%7711,6%0.86675%
13.rs4680 COMT 60317729,4%29548,9%13121,7%0.92768%
14.rs135745 CSNK1E 71818726,0%37552,2%15621,7%0.46081%
15.rs1997644 CSNK1E 68817625,6%36452,9%14821,5%0.29178%
16.rs1611115 DBH 76144358,2%28337,2%354,6%0.48286%
17.rs6271 DBH 78065784,2%11614,9%70,9%0.75988%
18.rs4532 DRD1 76128637,6%35746,9%11815,5%0.93186%
19.rs6277 DRD2 57916929,2%28449,1%12621,8%0.94865%
20.rs1800497 DRD2 60539966,0%19231,7%142,3%0.26168%
21.rs1079597 DRD2 60844372,9%15826,0%71,2%0.22669%
22.rs1800498 DRD2 59521536,1%28047,1%10016,8%0.86267%
23.rs2134655 DRD3 76041053,9%29538,8%557,2%0.98186%
24.rs3732790 DRD3 73424333,1%36549,7%12617,2%0.85783%
25.rs6280 DRD3 74935447,3%32643,5%699,2%0.88784%
26.rs963468 DRD3 73624633,4%36449,5%12617,1%0.90983%
27.rs11246226 DRD4 68517325,3%34750,7%16524,1%0.94177%
28.rs3758653 DRD4 71448668,1%20829,1%202,8%0.92380%
29.rs916455 DRD4 70264491,7%568,0%20,3%0.80379%
30.rs936460 DRD4 69734449,4%28440,7%699,9%0.65579%
31.rs3733829 EGLN2 68326338,5%32147,0%9914,5%0.99877%
32.rs222843 GABARAP 68330744,9%29342,9%8312,2%0.60177%
33.rs11111 GDNF 71954075,1%16022,3%192,6%0.24181%
34.rs1549250 GDNF 71023132,5%35349,7%12617,7%0.90780%
35.rs1981844 GDNF 57632055,6%22338,7%335,7%0.77165%
36.rs2910702 GDNF 70538754,9%26938,2%497,0%0.97179%
37.rs2973041 GDNF 69549270,8%18226,2%213,0%0.71078%
38.rs2973050 GDNF 58224241,6%27547,3%6511,2%0.60866%
39.rs3096140 GDNF 67132047,7%28742,8%649,5%1.00076%
40.rs3812047 GDNF 67952176,7%14421,2%142,1%0.55977%
41.rs6925 HTR1A 60716727,5%28947,6%15124,9%0.51068%
42.rs1228814 HTR1B 59943272,1%15325,5%142,3%0.99568%
43.rs130058 HTR1B 59533055,5%23239,0%335,5%0.64267%
44.rs13212041 HTR1B 60637662,0%20934,5%213,5%0.46768%
45.rs11568817 HTR1B 60018731,2%29248,7%12120,2%0.93768%
46.rs6296 HTR1B 60732553,5%23338,4%498,1%0.73068%
47.rs6311 HTR2A 77724331,3%39150,3%14318,4%0.80988%
48.rs6313 HTR2A 76924031,2%38550,1%14418,7%0.89387%
49.rs6314 HTR2A 77364082,8%13016,8%30,4%0.40987%
50.rs7322347 HTR2A 76524231,6%37048,4%15320,0%0.86686%
51.rs7984966 HTR2A 75841154,2%29338,7%547,1%0.98485%
52.rs3813929 HTR2C 74455574,6%11715,7%729,7%0.97584%
53.rs518147 HTR2C 71737952,9%16623,2%17224,0%0.23781%
54.rs6318 HTR2C 76957074,1%12716,5%729,4%0.73787%
55.rs907094 PPP1R1B 70540958,0%24634,9%507,1%0.30879%

M: major allele, m: minor allele

*Hardy Weinberg Equilibrium.

M: major allele, m: minor allele *Hardy Weinberg Equilibrium.

Statistical analysis

Statistical analyses were performed by the SPSS 22.0 (SPSS Inc.) software. Allele and genotype frequency distributions were determined by the χ 2 test. Independent samples t-test was used to assess gender differences, and relationship with age was tested by Pearson correlation. Genetic associations were tested by one way analysis of covariance (ANCOVA) assuming a dominant model of inheritance with sex and age as covariates. Bonferroni correction for multiple testing was applied for the total number of SNPs in this study when assessing relationship between BPAQ scores and individual SNPs (the corrected level of significance was p = 0.05 / 55 = 0.0009). In all other cases, p ˂ 0.05 values were regarded as significant. Effect of prior associations in males and females was analyzed by two-way ANCOVA with age as covariate. All tests were two-tailed. Lewontin’s D’ and r 2 values of linkage disequilibrium were calculated using HaploView 4.2. [37]. Haplotypes were determined by the PHASE software [38,39].

Results

Reliability of the markers analyzed

Internal consistency of the self-report BPAQ was assessed by Chronbach’s alpha, which had a value of 0.895 for total scores ensuring reliability of the study. Coefficients for Verbal Aggression, Physical Aggression, Anger and Hostility were 0.640, 0.842, 0.831 and 0.792, respectively. Alleles of all the SNPs studied were in Hardy-Weinberg equilibrium (Table 1).

Potential confounders

Gender differences on the BPAQ scale were evaluated by Independent samples t-test. Males presented significantly higher scores than females (68.52±17.14 compared to 64.49±15.09; p<0.001). Relationship between BPAQ scores and age was tested by Pearson correlation coefficient and was found to be significant (p = 0.008). Thus, both gender and age were used as covariates in all association analyses.

Significant association of the HTR2A rs7322347 T/A intronic SNP with aggression

Table 2 summarizes results of phenotypic data as a function of each SNP analyzed. Association with aggression reached nominal level of significance p<0.05 in the case of two SNPs, rs916455 located in the promoter region of the DRD4 gene and rs7322347 in intron 2 of HTR2A. Corresponding statistical values for these were [F = 4.878, p = 0.0275, η2 = 0.007, power = 0.597] and [F = 11.617, p = 0.0007 η2 = 0.015, power = 0.926], respectively. In order to reduce the likelihood of a type I error, Bonferroni adjustment on the target alpha level was performed to correct for multiple testing. Effect of the rs7322347 polymorphism remained significant after Bonferroni-correction, labeled by an asterisk in Table 2. Individuals homozygous for the wild type allele (T) of rs7322347 had significantly higher aggression scores (69.21±17.00) compared to those carrying at least one minor allele (A) of this polymorphism (65.34±15.69). The corresponding Cohen’s d effect size for rs7322347 was d = 0.24.
Table 2

Association of the 55 polymorphisms studied with aggression levels.

SNPGeneAggression (total score)p #
MMMmmm
1.rs1048101 ADRA1A 66.6666.5066.460.9684
2.rs3808585 ADRA1A 66.1568.1965.930.2294
3.rs2236554 ADRA1D 65.3167.1868.290.0840
4.rs553668 ADRA2A 66.5266.6170.470.8682
5.rs11030104 BDNF 66.5666.6067.730.8735
6.rs2049045 BDNF 66.3467.1566.730.5703
7.rs6265 BDNF 66.9466.8065.980.9220
8.rs7103411 BDNF 66.5566.5367.340.9163
9.rs7094179 CDNF 65.8166.4668.320.6485
10.rs7900873 CDNF 67.0366.4964.680.3912
11.rs1051730 CHRNA3 67.5365.5166.580.1190
12.rs16969968 CHRNA5 67.4565.7766.610.2138
13.rs4680 COMT 67.0766.5867.620.8569
14.rs135745 CSNK1E 65.9966.6366.240.7121
15.rs1997644 CSNK1E 66.8366.3165.680.7781
16.rs1611115 DBH 65.7467.3670.890.0941
17.rs6271 DBH 66.5966.6861.000.8731
18.rs4532 DRD1 66.5565.9467.910.9000
19.rs6277 DRD2 66.8167.0666.390.9148
20.rs1800497 DRD2 66.7267.7061.290.7106
21.rs1079597 DRD2 67.2066.3857.950.4397
22.rs1800498 DRD2 67.0766.4667.340.7979
23.rs2134655 DRD3 65.7167.8166.120.1250
24.rs3732790 DRD3 67.0366.4265.900.5267
25.rs6280 DRD3 66.9866.6064.460.4667
26.rs963468 DRD3 67.2567.0165.060.5779
27.rs11246226 DRD4 67.3166.3366.410.4831
28.rs3758653 DRD4 66.5166.4869.930.9091
29. rs916455 DRD4 66.93 62.82 46.67 0.0275
30.rs936460 DRD4 66.6066.3967.700.9890
31.rs3733829 EGLN2 66.9666.7665.380.6238
32.rs222843 GABARAP 66.5066.0968.770.9562
33.rs11111 GDNF 66.5665.9073.850.9972
34.rs1549250 GDNF 66.7565.3870.340.8604
35.rs1981844 GDNF 66.4866.8572.220.4727
36.rs2910702 GDNF 66.2766.4068.790.5293
37.rs2973041 GDNF 66.6866.2471.950.9268
38.rs2973050 GDNF 66.3066.4968.890.5259
39.rs3096140 GDNF 65.7966.9768.520.1457
40.rs3812047 GDNF 66.4567.4670.870.3422
41.rs6925 HTR1A 66.5567.6365.630.9441
42.rs1228814 HTR1B 67.2066.4763.950.5336
43.rs130058 HTR1B 67.2265.5570.740.3419
44.rs13212041 HTR1B 67.0966.2166.870.5259
45.rs11568817 HTR1B 68.7065.7667.120.0605
46.rs6296 HTR1B 66.2167.3368.600.2601
47.rs6311 HTR2A 66.7866.3267.410.9130
48.rs6313 HTR2A 66.4466.0967.440.9969
49.rs6314 HTR2A 67.0263.9873.670.0765
50. rs7322347 HTR2A 69.21 64.92 66.35 0.0007*
51.rs7984966 HTR2A 67.4565.6565.580.1356
52.rs3813929 HTR2C 67.0163.6766.430.2163
53.rs518147 HTR2C 66.7366.4467.180.3203
54.rs6318 HTR2C 66.4366.4667.630.2277
55.rs907094 PPP1R1B 67.0465.1868.840.2994

Nominally significant associations are indicated by bold, italics.

* Significant after Bonferroni correction

# Dominant model (MM vs. Mm and mm).

Nominally significant associations are indicated by bold, italics. * Significant after Bonferroni correction # Dominant model (MM vs. Mm and mm). In order to gain a more detailed insight into the nature of the observed association, post hoc analyses were performed testing for possible relationship between rs7322347 and each of the four individual BPAQ subscales (Fig. 1). With the exception of Verbal Aggression, where mean scores did not differ in non-carriers compared to carriers of allele A (15.09±3.47 vs. 14.65±3.24; p = 0.1076), scores of all subscales showed significant association with rs7322347. Differences in mean scores between those homozygous for rs7322347 T and those with at least one copy of rs7322347 A was most remarkable in the case of Hostility (18.41±5.55 vs. 17.05±5.48), with statistical difference between groups virtually equaling that observed with the overall BPAQ scale [F = 11.535, p = 0.0007, η2 = 0.015, power = 0.924]. Mean scores for both Physical Aggression and Anger were also higher in the absence of rs7322347 A than in its presence (18.86±7.08 vs. 17.80±6.63) [F = 7.419, p = 0.0066, η2 = 0.010, power = 0.776] and (16.91±5.67 vs. 15.89±5.46) [F = 5.858, p = 0.0157, η2 = 0.008, power = 0.676], respectively.
Fig 1

Relationship of each of the Buss-Perry Aggression Questionnaire subscales with rs7322347 A allele carrier status.

Mean scores of each the Buss-Perry Aggression Questionnaire subscales according to rs7322347 genotypes. Error bars represent standard errors of the mean.

Relationship of each of the Buss-Perry Aggression Questionnaire subscales with rs7322347 A allele carrier status.

Mean scores of each the Buss-Perry Aggression Questionnaire subscales according to rs7322347 genotypes. Error bars represent standard errors of the mean.

Effect of the HTR2A rs7322347 polymorphism on male and female aggression

As significant gender effect was observed in the BPAQ scores, male vs. female differences were also tested in terms of rs7322347 genotype and aggression using two-way ANCOVA with age as covariate. Although interaction between gender and aggression scores was highly significant [F = 10.991, p = 0.0010, η2 = 0.014, power = 0.912], no gene-sex interaction was found (p = 0.8834). Both males and females carrying the minor (A) allele of rs7322347 showed lower levels of aggression (Fig. 2).
Fig 2

Effect of the HTR2A rs7322347 polymorphism on male and female aggression.

Mean scores of the Buss-Perry Aggression Questionnaire in males and females according to rs7322347 genotypes. Error bars represent standard errors of the mean.

Effect of the HTR2A rs7322347 polymorphism on male and female aggression.

Mean scores of the Buss-Perry Aggression Questionnaire in males and females according to rs7322347 genotypes. Error bars represent standard errors of the mean.

Linkage disequilibrium (LD) and haplotype analyses within the HTR2A gene

Taken that four other SNPs than rs7322347 (rs6311 C/T, rs6313 G/A, rs6314 G/A and rs7984966 T/C) within the HTR2A gene were also genotyped in this study, LD and haplotype analyses were performed as well to explore possible further contribution of loci in nearby regions to higher aggression levels. The associating polymorphism rs7322347 was found to be in complete linkage disequilibrium (D’ = 1) with rs6314 located 1069 bp upstream from rs7322347 (Fig. 3), due to the fact that allele A of rs6314 could only be observed in subjects also carrying rs7322347 A and that all individuals homozygous for rs6314 A were homozygous for rs7322347 A as well. However, this was accompanied by a relatively low r2 value as there was a marked difference in MAFs for these two SNPs (8.8% for rs6314 vs. 44.2% for rs7322347). The polymorphism rs7322347 was in strong LD with rs7984966 as well (chromosomal distance: 19343 bp), although to a lesser extent than with rs6314. In addition, prominently high LD was also observed between rs6313 and rs6311 spaced 1538 bp apart, where in the majority of cases allele A of rs6313 was linked to rs6311 T (662/665 chromosomes; 99.6%) and allele G of rs6313 to rs6311 C (850/853 chromosomes; 99.7%) (Fig. 3).
Fig 3

Linkage disequilibrium patterns between SNPs studies within the HTR2A gene.

A: Lewontin’s D’ (%) and B: r2 (%) values of linkage disequilibrium between each SNP pairs, as determined by HaploView (version 4.2.). Higher values and darker colors indicate stronger LD between loci pairs. Red square indicates 100% LD.

Linkage disequilibrium patterns between SNPs studies within the HTR2A gene.

A: Lewontin’s D’ (%) and B: r2 (%) values of linkage disequilibrium between each SNP pairs, as determined by HaploView (version 4.2.). Higher values and darker colors indicate stronger LD between loci pairs. Red square indicates 100% LD. One-way ANCOVAs were applied on the overall BPAQ scale scores with 2-SNP haplotypes (comprising rs7322347 and each of the other four HTR2A variants genotyped) as the grouping variable and gender and age as covariates (Table 3). In a dominant model (haplotypes containing only major alleles of the constituting SNPs), haplotypes rs6314/ rs7322347 and rs7322347/ rs7984966 showed a significant effect [F = 11.128, p = 0.0009, η2 = 0.014, power = 0.915 and F = 7.352, p = 0.0068, η2 = 0.009, power = 0.773, respectively], while no significant differences in the mean scores of aggression were observed with regard to the other two haplotypes analyzed (p = 0.1875 and p = 0.1232, respectively). Subjects homozygous for haplotype rs6314 G/ rs7322347 T had higher aggression scores as compared to the rest of the population (69.05±17.07 vs. 65.33±15.77). Similarly, individuals carrying haplotype rs7322347 T/ rs7984966 T on both chromosomes presented with higher mean BPAQ scores than those with other haplotype combinations (68.83±17.19 vs. 65.64±15.85). Haplotype-wise analyses also indicated significant association of haplotype rs6314/ rs7322347, but to a lesser extent than in the dominant model [F = 3.205, p = 0.0408, η2 = 0.004, power = 0.614] (Table 4).
Table 3

Association of rs7322347 comprising 2-SNP within-HTR2A haplotypes with aggression scores.

Aggression scorep
HHHh & hh
rs6314/ rs7322347 69.05±17.0765.33±15.77 0.0009
rs7322347/ rs7984966 68.83±17.1965.64±15.85 0.0068
rs7322347/ rs6313 68.58±18.9266.23±15.890.1875
rs7322347/ rs6311 68.95±18.6966.19±15.920.1232

H: Haplotype containing major alleles of the constituting SNPs;

h: haplotype containing minor allele of at least of the two constituting SNPs

Significant associations are indicated by bold, italics.

Table 4

Haplotype-wise analysis of rs7322347 and each of the other HTR2A SNPs studied.

NHaplotype frequencyAggression scorep
rs6314G-rs7322347T8620,5667.28±16.53 0.041
rs6314G-rs7322347A5470,3565.78±16.04
rs6314A-rs7322347A1350,0964.46±15.28
rs6314A-rs7322347T00-
rs7322347T-rs7984966T8090,5267.34±16.540.115
rs7322347A-rs7984966C3470,2265.45±15.63
rs7322347A-rs7984966T3350,2265.59±16.18
rs7322347T-rs7984966C530,0366.37±16.38
rs7322347T-rs6313G5920,3867.03±16.500.072
rs7322347A-rs6313A4050,2665.88±16.40
rs7322347A-rs6313G2770,1864.99±15.14
rs7322347T-rs6313A2700,1767.83±16.60
rs7322347T-rs6311C5900,3867.07±16.480.074
rs7322347A-rs6311T4030,2665.92±16.42
rs7322347A-rs6311C2790,1864.94±15.10
rs7322347T-rs6311T2720,1867.74±16.66

Significant p value is indicated by bold, italics.

H: Haplotype containing major alleles of the constituting SNPs; h: haplotype containing minor allele of at least of the two constituting SNPs Significant associations are indicated by bold, italics. Significant p value is indicated by bold, italics.

Discussion

In this study, we examined possible contribution of 55 SNPs to aggressive tendencies measured by the BPAQ in the general adult Hungarian population [33,34]. Only two of these SNPs showed association reaching nominal significance, and merely rs7322347 of the HTR2A gene retained significant effect after Bonferroni adjustment. These findings underpin the long-suspected key role of the serotonin neurotransmitter system in aggression and the related disorders [40,41]. There is convergent evidence that low or impaired serotonergic function underlies aggression and impulsivity [42-44]. As within the central nervous system (CNS) serotonin is synthesized solely in neurons of the raphe nuclei innervating virtually the entire neuraxis, this neurotransmitter is believed to exert a global effect on the brain with a holistically general role, even though local specialized functions are achieved by a variety of receptors [45,46]. It has been proposed that the principal role of serotonin might be the withdrawal from dangerous and aversive situations; consequently, serotonergic hypofunction could lead to impaired avoidance of undesirable stimuli, which in turn could provoke aggressive responses [47]. Strong experimental evidence supports this concept. The inverse correlation of aggression, impulsivity and antisocial behavior with serotonin metabolite 5-hydroxyindoleacetic acid levels in the cerebrospinal fluid was already known decades ago [40,48-50]. Later on, numerous studies confirmed these early observations regarding the relationship between dysregulation of the serotonergic system and aggressive-impulsive traits both in human and animals [51-54]. Behavioral functions of serotonin and also the effect of drugs influencing serotonergic mechanisms shows a marked conservation even between evolutionarily remote species [55]. This enables utilization of animal models for different types of aggression, e.g. affective (or defensive) and predatory (referred to as impulsive and premediated in humans, respectively) [56]. Data especially on rodents and felines provide valuable insight into underlying molecular mechanisms, shedding light for example on the interplay of proinflammatory cytokines and serotonin receptors in defensive rage and also on differential modulation of aggression by distinct types of serotonin receptors [57-59]. Administration of selective serotonin reuptake inhibitors (SSRIs), such as fluoxetine, citalopram or paroxetine usually reduces aggression [60-69], though contradictory results have also been reported, especially in juvenile humans and animals [70-72]. Reduced levels of serotonin caused by depletion of its precursor tryptophan have been linked to aggressive behavior [73-76], and disrupted function of enzymes involved in serotonin metabolism, such as tryptophan hydroxylase or monoamine oxidase, are also related to aggressive traits [77-79]. Observations on the link between life history of aggression and platelet serotonin content as well as platelet serotonin receptor and transporter binding further underpin the constantly growing body of evidence referring to a close relationship between the serotonergic system and aggression [80-82]. Serotonin (5-hydroxytryptamine) receptor 2a, encoded by the gene HTR2A, is a G-protein coupled excitatory receptor exerting its influence through the activation of secondary messengers phospholipase C and D [83]. Among others it is expressed in high levels on pyramidal cells of the prefrontal cortex, where it is ideally positioned to modulate both cognitive functions such as working memory or executive control and also emotions through dynamic interactions with the amygdala [84,85]. Serotonin receptors are also distributed along the midbrain periaqueductal grey (PAG) and the hypothalamus [56], brain areas that both have a direct connection with the prefrontal cortex and amygdala and long have been proved to control components of aggression including vocalization [86,87]. In accordance, mice with inherited aberrations in development and function of serotonergic neurons in the CNS exhibit increased levels of aggression which can be ameliorated by SSRIs [88]. Functional polymorphisms of the HTR2A gene are thus expected to influence neuronal networks regulating all the above mentioned features, providing a physiological basis for associations between HTR2A genetic variations and different mental states. During the last decade, several groups investigated SNPs of the HTR2A gene in connection with psychiatric and personality disorders [89-95]. Noteworthy observations have been made with regard to a number of variations located mainly in the promoter or the coding region; however, though scarce, literature data also indicate that intronic variant rs7322347 might as well be of interest from behavioral aspects, as it showed marked association with the combined subtype of childhood attention-deficit hyperactivity disorder (ADHD) and with suicide attempt in females subjected to physical assault in younger age [96,97]. Interestingly, according to our findings the missense polymorphism rs6314 is in complete LD with rs7322347, and the haplotype defined by these two SNPs has a similarly high impact on aggression levels as rs7322347 alone, despite the great difference observed between their MAFs. This might reflect that a complex background lies behind the robust association observed in the case of rs7322347, possibly consisting of several minor factors. Intrinsically, marked physiological effect of a single genetic variation with a MAF nearing 50% is generally improbable, simply based on the consideration that the spread of newly arisen alleles with functional relevance is most probably controlled by either positive or negative selection, hardly allowing quasi equal allele frequencies to evolve. Although in the present case it is plausible that a fine evolutionary balance has been struck between avoiding fights thus injury and gaining access to better resources, it cannot be excluded that other, linked polymorphic loci also contribute to the overall observed effect, even though similarly high D’ values as seen for rs6314 are unlikely for any such sites. Indeed, full linkage disequilibrium can only be expected when no crossing over event between the linked loci has yet occurred, which is mainly characteristic to the situation when at least one of the polymorphic sites is evolutionarily young. It is, though, noteworthy that immensely strong LD has been identified elsewhere within the HTR2A gene as well (between rs6311 and rs6313), both in this study and before [98-100]. As the linked polymorphism rs6314 causes a histidine to tyrosine change, thus the substitution of a basic amino acid residue to an uncharged one, this SNP could potentially affect both protein structure and function [101]. In vitro studies implicate that its rare allele causes slower receptor response, decreased activation levels of phospholipases C and D, reduced calcium ion mobilization and thus a general hypofunctioning of the whole signaling cascade [102,103]. Recent findings imply that rs6314 also interferes with adequate splicing of pre-mRNA, with defective transcript forms triggering the RNA surveillance machinery, leading to a lower expression of the variant allele both on RNA and protein level [104]. Another possible explanation for the observed relationship between rs7322347 and aggression lies in gene regulation. Over the last few years, growing number of disease-associating polymorphisms in intergenic and intronic regions identified especially in GWA studies, combined with the fact that the more complex an organism is, the larger proportion of its genome will consist of non-coding sequences, has drawn attention of the scientific community towards the significance of expression regulation. By now, light has been thrown on several molecular mechanisms modifying gene expression, mostly with the involvement of non-coding sequences. Polymorphic intronic sites can lead to splicing efficiency bias or modified pre-mRNA stability, or they might affect long-distance gene regulation, for instance as part of an enhancer or an insulator, or through the RNAi pathway. In fact, according to the miRBase registry, T allele of rs7322347 disrupts a potential miRNA binding site [105,106]. It has recently been demonstrated by our group that differences in transcriptional regulation caused by a miRNA binding site disrupting SNP can indeed contribute to elevated aggression levels [107]. Though functional relevance of intronic miRNA target sites is obscure, recent evidence suggests that at least in plants miRNA interaction with intronic sequences is indeed involved in gene regulation processes [108]. In addition, expression quantitative trait loci (eQTL) data (http://genenetwork.nl/bloodeqtlbrowser) indicate that minor allele (A) of rs7322347 negatively affects (Z-score: -8.06) transcription of the ESD gene located 34 kb downstream of HTR2A [109]. ESD encodes esterase D, a poorly characterized protein with a suggested role in the recycling of sialic acids and also in detoxification [110,111]. Thus, it would be intriguing to explore possible interaction of ESD with neurobiological aspects and behavioral traits, especially as it is expressed all across the brain in considerable amounts according to AceView and TiGER databases [112,113]. In the present report, we demonstrate a robust contribution of the rs7322347 variation within the gene encoding serotonin receptor 2a to aggressive traits. As the study was conducted on a large sample of 887 normal individuals and the effect of this polymorphism was strong enough to endure Bonferroni correction for multiple tests, it can be assumed that the observed association has a substantive biological basis. This might provide us with a better insight into the driving forces underlying aggression, hopefully facilitating early identification of individuals at risk, hereby also improving prevention of negative consequences derived from aggressive manifestations. Nevertheless, care must be taken not to overestimate the impact of these findings. Psychological and behavioral processes are complex traits comprising a not at all negligible environmental component, and deciphering all gene-environment (G×E) as well as epistatic interactions is more than challenging. There is far more to mental states than simply biochemical processes; thus, even though anatomical structure of the brain, neurophysiological functioning and gene expression regulation mechanisms are essentially identical in all human beings, socialization and culture also largely influences our acts and behavior [114,115]. Presumably, the role of genes in terms of human behavior is neither less nor more than establishing a reaction spectrum; within the available range, however, former experiences, belief-systems and social atmosphere are supposed to serve as key determinants of the actual behavior [46]. In conclusion, this study adds on the growing evidence that the serotoninergic system greatly influences aggressive tendencies. To our best knowledge, this is the first report demonstrating a direct relationship between the HTR2A gene and aggression. However, confirmation of the present findings by independent replication would inevitably be necessary before drawing any further conclusions from these results. Functional studies should also be performed in order to explore the exact biochemical background of the association described, and to elicit possible contribution of rs7322347 to psychiatric and personality disorders. By no means forgetting about the significance of environmental exposure, our findings will hopefully provide help to elucidate the genetic basis behind increased predisposition to aggression.
  115 in total

1.  dbSNP: the NCBI database of genetic variation.

Authors:  S T Sherry; M H Ward; M Kholodov; J Baker; L Phan; E M Smigielski; K Sirotkin
Journal:  Nucleic Acids Res       Date:  2001-01-01       Impact factor: 16.971

2.  A new statistical method for haplotype reconstruction from population data.

Authors:  M Stephens; N J Smith; P Donnelly
Journal:  Am J Hum Genet       Date:  2001-03-09       Impact factor: 11.025

3.  Genetic and environmental influences on antisocial behavior: a meta-analysis of twin and adoption studies.

Authors:  Soo Hyun Rhee; Irwin D Waldman
Journal:  Psychol Bull       Date:  2002-05       Impact factor: 17.737

4.  Brain-derived neurotrophic factor-deficient mice develop aggressiveness and hyperphagia in conjunction with brain serotonergic abnormalities.

Authors:  W E Lyons; L A Mamounas; G A Ricaurte; V Coppola; S W Reid; S H Bora; C Wihler; V E Koliatsos; L Tessarollo
Journal:  Proc Natl Acad Sci U S A       Date:  1999-12-21       Impact factor: 11.205

5.  Association of aggressive behavior with altered serotonergic function in patients who are not suicidal.

Authors:  B Stanley; A Molcho; M Stanley; R Winchel; M J Gameroff; B Parsons; J J Mann
Journal:  Am J Psychiatry       Date:  2000-04       Impact factor: 18.112

6.  Social impulsivity inversely associated with CSF 5-HIAA and fluoxetine exposure in vervet monkeys.

Authors:  L A Fairbanks; W P Melega; M J Jorgensen; J R Kaplan; M T McGuire
Journal:  Neuropsychopharmacology       Date:  2001-04       Impact factor: 7.853

Review 7.  Dysfunction in the neural circuitry of emotion regulation--a possible prelude to violence.

Authors:  R J Davidson; K M Putnam; C L Larson
Journal:  Science       Date:  2000-07-28       Impact factor: 47.728

8.  Prediction of level of serotonin 2A receptor binding by serotonin receptor 2A genetic variation in postmortem brain samples from subjects who did or did not commit suicide.

Authors:  G Turecki; R Brière; K Dewar; T Antonetti; A D Lesage; M Séguin; N Chawky; C Vanier; M Alda; R Joober; C Benkelfat; G A Rouleau
Journal:  Am J Psychiatry       Date:  1999-09       Impact factor: 18.112

9.  Noninvasive genotyping of dopamine receptor D4 (DRD4) using nanograms of DNA from substance-dependent patients.

Authors:  K Boór; Z Rónai; Z Nemoda; P Gaszner; M Sasvári-Székely; A Guttman; H Kalász
Journal:  Curr Med Chem       Date:  2002-04       Impact factor: 4.530

10.  The serotonin reuptake inhibitor fluoxetine reduces sex steroid-related aggression in female rats: an animal model of premenstrual irritability?

Authors:  H P Ho; M Olsson; L Westberg; J Melke; E Eriksson
Journal:  Neuropsychopharmacology       Date:  2001-05       Impact factor: 7.853

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1.  Coevolution of Residues Provides Evidence of a Functional Heterodimer of 5-HT2AR and 5-HT2CR Involving Both Intracellular and Extracellular Domains.

Authors:  Bernard Fongang; Kathryn A Cunningham; Maga Rowicka; Andrzej Kudlicki
Journal:  Neuroscience       Date:  2019-06-01       Impact factor: 3.590

2.  Association of SNPs in dopamine and serotonin pathway genes and their interacting genes with temperament traits in Charolais cows.

Authors:  E Garza-Brenner; A M Sifuentes-Rincón; R D Randel; F A Paredes-Sánchez; G M Parra-Bracamonte; W Arellano Vera; F A Rodríguez Almeida; A Segura Cabrera
Journal:  J Appl Genet       Date:  2016-12-16       Impact factor: 3.240

3.  Association of Polymorphisms of Serotonin Transporter (5HTTLPR) and 5-HT2C Receptor Genes with Criminal Behavior in Russian Criminal Offenders.

Authors:  Valentina A Toshchakova; Yalda Bakhtiari; Alexander V Kulikov; Sergey I Gusev; Marina V Trofimova; Olga Yu Fedorenko; Ekaterina V Mikhalitskaya; Nina K Popova; Nikolay A Bokhan; Johannes E Hovens; Anton J M Loonen; Bob Wilffert; Svetlana A Ivanova
Journal:  Neuropsychobiology       Date:  2018-04-05       Impact factor: 2.328

4.  Elevated levels of serotonin 5-HT2A receptors in the orbitofrontal cortex of antisocial individuals.

Authors:  Giulia Braccagni; Simona Scheggi; Marco Bortolato
Journal:  Eur Arch Psychiatry Clin Neurosci       Date:  2022-09-12       Impact factor: 5.760

Review 5.  Good daily habits during the early stages of life determine success throughout life.

Authors:  Jun Kohyama
Journal:  Sleep Sci       Date:  2016-10-05

6.  Serotonergic gene polymorphisms (5-HTTLPR, 5HTR1A, 5HTR2A), and population differences in aggression: traditional (Hadza and Datoga) and industrial (Russians) populations compared.

Authors:  Marina L Butovskaya; Polina R Butovskaya; Vasiliy A Vasilyev; Jane M Sukhodolskaya; Dania I Fekhredtinova; Dmitri V Karelin; Julia N Fedenok; Audax Z P Mabulla; Alexey P Ryskov; Oleg E Lazebny
Journal:  J Physiol Anthropol       Date:  2018-04-16       Impact factor: 2.867

7.  Possible roles of genetic variations in chemotherapy related cardiotoxicity in pediatric acute lymphoblastic leukemia and osteosarcoma.

Authors:  Judit C Sági; Bálint Egyed; Andrea Kelemen; Nóra Kutszegi; Márta Hegyi; András Gézsi; Martina Ayaka Herlitschke; Andrea Rzepiel; Lili E Fodor; Gábor Ottóffy; Gábor T Kovács; Dániel J Erdélyi; Csaba Szalai; Ágnes F Semsei
Journal:  BMC Cancer       Date:  2018-07-03       Impact factor: 4.430

8.  5-HT2A Gene Variants Moderate the Association between PTSD and Reduced Default Mode Network Connectivity.

Authors:  Mark W Miller; Emily Sperbeck; Meghan E Robinson; Naomi Sadeh; Erika J Wolf; Jasmeet P Hayes; Mark Logue; Steven A Schichman; Angie Stone; William Milberg; Regina McGlinchey
Journal:  Front Neurosci       Date:  2016-06-28       Impact factor: 4.677

9.  Polymorphism of serotonin transporter gene in male subjects with antisocial behavior and MMA fighters.

Authors:  Elena V Cherepkova; Vladimir V Maksimov; Lyubomir I Aftanas
Journal:  Transl Psychiatry       Date:  2018-11-15       Impact factor: 6.222

10.  Association of rs4680 COMT, rs6280 DRD3, and rs7322347 5HT2A With Clinical Features of Youth-Onset Schizophrenia.

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Journal:  Front Psychiatry       Date:  2019-11-12       Impact factor: 4.157

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