The GCAG Haplotype of the CRHBP Gene May Decrease the Risk for Robbery Behavior Among the Han Chinese

Abstract

Aims:

Hypothalamic-pituitary-adrenocortical axis gene polymorphisms have been reported to affect aggressive behavior. Corticotropin releasing hormone binding protein (CRHBP) polymorphisms have been shown to contribute to the susceptibility to stress-related disorders, including aggressive behavior. However, no study has been conducted on the relationship between CRHBP polymorphisms and aggressive behavior risk in the Han Chinese population.

Methods:

A case-control study that comprised 194 male criminals and 303 healthy controls was carried out to investigate the genetic association between several CRHBP gene polymorphisms and aggressive behavior risk in the Hunan Han population. Genotyping was conducted by using the improved multiplex ligase detection reaction method for four CRHBP loci: rs10062367, rs32897, rs7718461, and rs7721799.

Results:

The incidence of the rs32897C allele was significantly lower in the robbery group compared with the control subjects after a Bonferroni correction (p = 0.016), indicating a protective role for the C allele of rs32897. Interestingly, a haplotypic analysis that was stratified by robbery and intentional injury showed that the haplotype consisting of rs10062367G, rs32897C, rs7718461A, and rs7721799G (which includes the protective rs32897 C allele) was significantly associated with decreased robbery risk (odds ratio [OR] = 0.31, p = 0.0005), but not for intentional injury (OR = 0.82, p = 0.44). The haplotype consisting of rs10062367G, rs32897T, rs7718461A, and rs7721799G carrying the rs32897 T allele significantly increased the risk for robbery (OR = 1.47, p = 0.0213), but not for intentional injury (OR = 0.92, p = 0.64).

Conclusions:

The rs32897 alleles and the haplotypes containing the rs32897 alleles, including GCAG and GTAG, may be factors associated with committing robbery in the Hunan Han population, and could be used to provide clinical counseling with regard to aggressive behavior. However, further studies including multiple ethnicities are needed.

Introduction

Aggressive behavior is a social problem that includes intentionally destroying objects or harming others with intent (Valois et al., 2002). Both the genetic and environmental factors were shown to play a role in the development of aggression behavior (Eley et al., 1999). Genetic factors are mainly involved in the polymorphisms of genes in 5-hydroxytryptamine (5-HT) and dopaminergic (DA) systems and the neuroendocrine system (Labella and Masten, 2018). Currently, a number of candidate genes such as monoamine oxidase A (MAOA), 5-serotonin transporter (5-HTT), dopamine receptor 4 (DRD4), catechol-o-methyltransferase (COMT), and hypothalamic-pituitary-adrenocortical (HPA) axis genes, including glucocorticoid receptor (GR) and mineralocorticoid receptor (MR), have been proposed to put persons at an increased risk for aggressive behavior (Newman et al., 2005; Brennan et al., 2011; Tang et al., 2015). Environmental factors include early life abuse, stress, socioeconomic status, and parenting styles (Nkomo et al., 2018). Moreover, environmental factors (especially adverse ones) may induce changes in epigenetics levels (such as DNA methylation levels) to regulate the expression of these factors (Keil and Lein, 2016), which in turn affect the development of aggressive behavior. However, none of this identification explains the pathogenesis of aggressive behavior.

The HPA axis is the main biological basis of the human stress system (Keck et al., 2008). Multiple individual behavioral features have also been suggested to be linked to the HPA axis function (Swaab et al., 2005; Lupien et al., 2009). The activities of the HPA have been shown to influence aggressive behavior in rhesus monkeys (Newman et al., 2005). When exposed to stress, the HPA system is activated by binding to components, including corticotropin-releasing hormone (CRH) receptors (CRHR1 and CRHR2) and corticotropin-releasing hormone binding protein (CRHBP) (Keck et al., 2008). CRH is responsible for the HPA axis activation. In addition, hyperactivation of the HPA axis primarily occurs in persons who exhibit increased anxiety, and in those with some form of aggressive behavior (Hawes et al., 2009; Bohnke et al., 2010a, 2010b). The CRHBP is essential for CRH binding, which plays a critical role in the moderation of CRH (Westphal and Seasholtz, 2006a). CRH is mostly combined with CRHBP in the human body and plays a pivotal role in the HPA axis (Holsboer and Ising, 2008). The level of CRHBP can affect the binding level of CRH and the level of active CRH in vivo, as well as affecting the function of the HPA axis. Therefore, it is of vital importance to understand the underlying molecular mechanism with regard to how CRHBP is involved in the development of aggressive behavior.

One of the possible mechanisms driving HPA axis dysfunction in psychotic disorders are genetic variants in genes encoding these receptors. The CRHBP gene is located on chromosome 5q13.3, with a length of ∼28.45 Kb. A total of 340 single nucleotide polymorphisms (SNPs) have been identified in this gene. Multiple potential functional SNPs, including rs10473984 (Binder et al., 2010) and rs1715747 (Kertes et al., 2011) have been identified. Recently, an increasing number of studies have been conducted on the correlation of these CRHBP variants with stress-related disorders. (Enoch et al., 2008; Binder et al., 2010; De Luca et al., 2010; Kertes et al., 2011; Ray, 2011; Roy et al., 2012). Owing to the fact that aggressive behaviors have multiple subtypes (robbery, blackmail, and intentional injury), it is worth conducting comprehensive studies to assess any possible role that variations of the CRHBP gene plays with regard to aggressive behaviors of multiple subtypes.

However, evaluations of the associations between the CRHBP gene polymorphisms and aggressive behavior susceptibility in the Han Chinese population has been very limited.

Experimental Procedures

Subjects

This study protocol was approved by the Ethical Committee of Changsha Medical University (CMUEC-150913). Written informed consent was obtained from all participants or their guardians. The violent criminals were recruited as volunteers from a prison in Changsha, Hunan. We enrolled 194 violent criminals (33.3 ± 1.5 years), who were divided into two subgroups: robbery group (n = 100, age: 29.6 ± 5.1 years) and intentional injury group (n = 94, age: 37.4 ± 7.2 years). In addition, we also enrolled 303 healthy controls matched by ethnicity, gender, and age (29.1 ± 3.2 years). All of the controls were individuals without a criminal record who were undergoing clinical examination at the first affiliated hospital of Changsha Medical University. All subjects were of Han Chinese origin.

SNPs selection and genotyping

The SNP selection was performed using the Haploview Software with minor allele frequency >0.05 and r² ≥ 0.8 based on the HapMap database (Chinese Han population [CHB]). Four SNPs (rs10062367, rs32897, rs7718461, and rs7721799) of the CRHBP gene were selected. Peripheral blood samples were obtained from all subjects. Genomic DNA was extracted from peripheral leukocytes according to a method established by Kochl et al. (Kochl et al., 2005). Multiplex polymerase chain reactions (PCRs) were performed on a GeneAmp 9700 PCR thermocycler (Applied Biosystems). Genotyping of the CRHBP polymorphisms was determined by an improved multiplex ligase detection reaction method (iMLDR; Genesky Bio-Tech Cod., Ltd., China). The PCR products were purified by adding 1U Shrimp Alkaline Enzyme (Sap) and 1U nucleic acid Exo I (Exo I) into the PCR products, then incubated at 37°C for 1 h and inactivated at 75°C for 15 min. The reaction system was as follows: 1 uL 10 × buffer, 0.25 uL high temperature linker, 0.4 uL 5′ linker mixture, 0.4 uL 3′ linker mixture, 2 uL purified multiplex PCR product and double-distilled H₂O 6 uL mixed well. The connecting procedure was as follows: 94°C 1 min, 56°C 4 min, 38 cycles. The product of 0.5 uL connection was mixed with 0.5 uL Liz 500, 9 uL Hi-Di and denatured at 95°C for 5 min. The products were detected with the ABI 3730XL DNA Sequencer (Applied Biosystems). Data were analyzed using GeneMapper software (version 4.1, Applied Biosystems). For genotyping quality control, 10% of the samples were selected at random to perform repeat assays. Specific multiplex PCR-LDR primers and probes for each SNP locus used in this assay are listed in Supplementary Table S1.

Statistical analysis

The Hardy-Weinberg equilibrium (HWE) of polymorphisms were tested by a χ² test. The distributions of the alleles and genotypes between the control group and aggressive behavior group were evaluated with the t-test. Genetic association was assessed by corresponding odds ratios (ORs) and 95% confidence intervals (CIs) through a standard logistic regression analysis. The p-value was corrected by a stringent Bonferroni's correction in multiple comparisons in cases where a significant relationship was found. The haplotype estimation for the CRHBP SNPs was performed using the full-precise-iteration (FPI) algorithm (Shi and He, 2006). A p < 0.05 indicated a statistical significance. All of the calculations were performed through SHEsis. The calculation power was analyzed by using the G*Power software.

Results

All of the four SNPs were in the HWE (p > 0.05). Table 1 shows that the selected four SNPs were in low linkage disequilibrium with each other.

Table 1.

The Patterns of Linkage Disequilibrium in the CRHBP Gene

Total subjects (n = 497)				Healthy controls (n = 303)				Aggressive behavior cases (n = 194)
r ²	rs32897	rs7718461	rs7721799	r ²	rs32897	rs7718461	rs7721799	r ²	rs32897	rs7718461	rs7721799
rs10062367	0.074	0.162	0.004	rs10062367	0.104	0.158	0.016	rs10062367	0.063	0.172	0.001
rs32897	—	0.003	0.061	rs32897	—	0.001	0.083	rs32897	—	0.004	0.031
rs7718461	—	—	0.113	rs7718461	—	—	0.144	rs7718461	—	—	0.077

CRHBP, corticotropin releasing hormone binding protein.

Results of single-locus analysis

No association was detected between the four SNPs (rs10062367, rs32897, rs7718461, and rs7721799) of CRHBP and aggressive behavior risk when the two behavioral subgroups (robbery and injury) were assayed together (p > 0.05) (Table 2). Moreover, our study obtained >73.5% power at the 5% significant level (two-tailed), which indicate the sample size is large enough to detect an association at an OR of 1.5.

Table 2.

Genotype and Allele Distributions in Aggressive Behavior Cases and Healthy Controls

Polymorphisms	Groups	N	Allele (frequency)		p^a	p^b	OR (95% CI)^c	Genotype (frequency)			p^a	p^b
rs10062367			A	G				AA	AG	GG
	Cases	194	71 (0.183)	317 (0.817)	0.150	—	1.28 (0.91-1.81)	8 (0.041)	55 (0.284)	131 (0.675)	0.368	—
	Controls	303	90 (0.149)	516 (0.851)	0.150	—	1.28 (0.91-1.81)	8 (0.026)	74 (0.244)	221 (0.729)	0.368	—
	R group^d	100	35 (0.175)	165 (0.825)	0.370	—	1.22 (0.79-1.87)	4 (0.040)	27 (0.270)	69 (0.690)	0.661	—
	Controls	303	90 (0.149)	516 (0.851)	0.370	—	1.22 (0.79-1.87)	8 (0.026)	74 (0.244)	221 (0.729)	0.661	—
	II group^d	94	36 (0.191)	152 (0.809)	0.159	—	1.35 (0.89-2.08)	4 (0.043)	28 (0.298)	62 (0.660)	0.384	—
	Controls	303	90 (0.149)	516 (0.851)	0.159	—	1.35 (0.89-2.08)	8 (0.026)	74 (0.244)	221 (0.729)	0.384	—
rs32897			C	T				CC	CT	TT
	Cases	194	80 (0.206)	308 (0.794)	0.117	—	0.78 (0.56-1.06)	11 (0.057)	58 (0.299)	125 (0.644)	0.165	—
	Controls	303	151 (0.249)	455 (0.751)	0.117	—	0.78 (0.56-1.06)	18 (0.059)	115 (0.380)	170 (0.561)	0.165	—
	R group^d	100	30 (0.150)	170 (0.850)	0.004	0.016	0.53 (0.35-0.82)	1 (0.010)	28 (0.280)	71 (0.710)	0.012	0.048
	Controls	303	151 (0.249)	455 (0.751)	0.004	0.016	0.53 (0.35-0.82)	18 (0.059)	115 (0.380)	170 (0.561)	0.012	0.048
	II group^d	94	50 (0.266)	138 (0.734)	0.644	—	1.09 (0.75-1.58)	10 (0.106)	30 (0.319)	54 (0.574)	0.226	—
	Controls	303	151 (0.249)	455 (0.751)	0.644	—	1.09 (0.75-1.58)	18 (0.059)	115 (0.380)	170 (0.561)	0.226	—
rs7718461			A	G				AA	AG	GG
	Cases	194	185 (0.477)	203 (0.523)	0.877	—	0.98 (0.76-1.26)	46 (0.237)	93 (0.479)	55 (0.284)	0.882	—
	Controls	303	292 (0.482)	314 (0.518)	0.877	—	0.98 (0.76-1.26)	70 (0.231)	152 (0.502)	81 (0.267)	0.882	—
	R group^d	100	100 (0.500)	100 (0.500)	0.656	—	1.08 (0.78-1.48)	23 (0.230)	54 (0.540)	23 (0.230)	0.733	—
	Controls	303	292 (0.482)	314 (0.518)	0.656	—	1.08 (0.78-1.48)	70 (0.231)	152 (0.502)	81 (0.267)	0.733	—
	II group^d	94	85 (0.452)	103 (0.548)	0.476	—	0.89 (0.64-1.23)	23 (0.245)	39 (0.415)	32 (0.340)	0.283	—
	Controls	303	292 (0.482)	314 (0.518)	0.476	—	0.89 (0.64-1.23)	70 (0.231)	152 (0.502)	81 (0.267)	0.283	—
rs7721799			A	G				AA	AG	GG
	Cases	194	77 (0.198)	311 (0.802)	0.813	—	0.96 (0.70-1.32)	9 (0.046)	59 (0.304)	126 (0.649)	0.801	—
	Controls	303	124 (0.205)	482 (0.795)	0.813	—	0.96 (0.70-1.32)	12 (0.040)	100 (0.330)	191 (0.630)	0.801	—
	R group^d	100	43 (0.215)	157 (0.785)	0.753	—	1.06 (0.72-1.57)	6 (0.060)	31 (0.310)	63 (0.630)	0.673	—
	Controls	303	124 (0.205)	482 (0.795)	0.753	—	1.06 (0.72-1.57)	12 (0.040)	100 (0.330)	191 (0.630)	0.673	—
	II group^d	94	34 (0.181)	154 (0.819)	0.476	—	0.86 (0.56-1.31)	3 (0.032)	28 (0.298)	63 (0.670)	0.771	—
	Controls	303	124 (0.205)	482 (0.795)	0.476	—	0.86 (0.56-1.31)	12 (0.040)	100 (0.330)	191 (0.630)	0.771	—

p-Values were calculated using Fisher's exact test.

Corrected p-value by a stringent Bonferroni's correction, “—” not significant.

OR (95% CI) were estimated by logistic regression analysis.

R group—robbery group; II group—intentional injury group.

CI, confidence interval; OR, odds ratio.

In addition, we also stratified the aggressive behavior group into two subgroups (robbery and intentional injury) and compared the two subgroups with the healthy controls. The distributions of the rs32897C allele in the robbery subgroup significantly differed from the control group (p = 0.004), even after a stringent Bonferroni correction (p = 0.016). Logistic regression analysis showed that rs32897C was significantly less prevalent in the robbery group than in the control group [OR (95% CI): 0.53 (0.35-0.82)]. The distributions of genotypes of rs32897 were also significantly different between the robbery group and the control group after a stringent Bonferroni correction (p = 0.012, p_adj = 0.048). We also assessed the association of the rs32897 genotypes with robbery behavior in the dominant model (TT vs. CT + CC), and found that subjects carrying the TT genotype were more likely to commit robbery behavior as compared with those carrying the CT or CC genotype [p = 0.009, OR (95% CI): 1.92 (1.18-3.12)].

Furthermore, subjects in intentional injury group and control group were divided into four subgroups according to the mean age: <25 years, 25 years ≤age <35 years, 35 years ≤age <45 years, and >45 years. The allele distributions of CRHBP polymorphisms in different ages were analyzed. As shown in Supplementary Table S2, evaluation of the risk of age related to intentional injury showed no significant association between CRHBP SNPs and intentional injury (p > 0.05), which indicated that increased age has no influence on the susceptible for intentional injury.

Result of haplotype-based analysis

A total of eight haplotypes (frequency >1%) consisting of the four SNPs of the CRHBP gene (rs10062367(A/G), rs32897(C/T), rs7718461(A/G), and rs7721799(A/G)) were obtained. None of the haplotypes were found to be related with aggressive behavior risk overall, or with intentional injury behavior. However, the distribution of the haplotype GCAG (p = 0.0005) was significantly lower in the robbery subgroup (4.7%) than that in the control group (13.4%), even after a Bonferroni correction (p_adj = 0.004). Logistic regression analysis indicated that the haplotype GCAG might be a protective factor for robbery [OR (95% CI): 0.31 (0.16-0.62)] (Table 3).

Table 3.

Haplotype Analysis of the Aggressive Behavior Subjects and the Healthy Controls in the CRHBP Gene

Haplotype^a	Cases	Controls	p^b	p^c	OR (95% CI)^d	R group^e	Controls	p^b	p^c	OR (95% CI)^d	II group^e	Controls	p^b	p^c	OR (95% CI)^d
ACGG	0.08	0.086	0.8026	—	0.94 (0.59-1.50)	0.068	0.086	0.2945	—	0.71 (0.38-1.35)	0.101	0.086	0.4986	—	1.21 (0.70-2.10)
ATGG	0.07	0.055	0.3224	—	1.30 (0.77-2.20)	0.067	0.055	0.7211	—	1.13 (0.58-2.21)	0.076	0.055	0.2923	—	1.41 (0.74-2.68)
GCAG	0.088	0.137	0.0227	0.16	0.62 (0.40-0.94)	0.047	0.137	0.0005	0.004	0.31 (0.16-0.62)	0.115	0.137	0.4427	—	0.82 (0.50-1.36)
GCGG	0.036	0.026	0.7098	—	1.16 (0.54-2.50)	0.043	0.026	0.3040	—	1.57 (0.66-3.72)	0.031	0.026	0.6861	—	1.22 (0.47-3.18)
GTAA	0.037	0.024	0.7248	—	1.16 (0.51-2.60)	0.035	0.024	0.5937	—	1.30 (0.50-3.40)	0.025	0.024	0.9160	—	1.06 (0.37-3.05)
GTAG	0.35	0.321	0.2615	—	1.17 (0.89-1.53)	0.41	0.321	0.0213	0.16	1.47 (1.06-2.05)	0.301	0.321	0.6385	—	0.92 (0.64-1.31)
GTGA	0.146	0.174	0.1394	—	0.76 (0.53-1.09)	0.157	0.174	0.3718	—	0.82 (0.52-1.27)	0.127	0.174	0.1076	—	0.67 (0.42-1.09)
GTGG	0.178	0.17	0.6583	—	1.08 (0.77-1.51)	0.16	0.17	0.5198	—	0.87 (0.56-1.35)	0.205	0.17	0.4049	—	1.20 (0.79-1.82)
Global test	0.985	0.993	0.0663			0.987	0.993	0.0001			0.981	0.993	0.1582

Haplotype structure was rs10062367 (A/G), rs32897(C/T), rs7718461(A/G), rs7721799(A/G). Haplotypes with frequency <0.01 were ignored in analysis.

p-Values were calculated using Fisher's exact test.

Corrected p-value by a stringent Bonferroni's correction, “—” not significant.

OR (95% CI) were estimated by logistic regression analysis.

R group—robbery group; II group—intentional injury group.

Discussion

The HPA axis is known to be a critical pressure feedback pathway. Under acute stress, CRH stimulates the release of adrenocortical hormone in the anterior pituitary, and then adrenocorticotropic hormone (ACTH) further stimulates the release of adrenal cortex to complete the body's stress response. CRHBP is a high affinity binding protein that is widely distributed in the whole body. CRHBP can bind a large amount of CRH and cannot activate CRHR1 and CRHR2 receptors. CRHBP has the function of regulating CRH activity and is an important link of negative feedback regulation(Westphal and Seasholtz, 2006a). Previous studies involving CRHBP focused on stress-related disorders such as antidepressant treatment response (Binder et al., 2010), suicidal behavior (De Luca et al., 2010; Roy et al., 2012), alcoholism and anxiety (Enoch et al., 2008), depressive symptoms with alcohol dependence (Kertes et al., 2011), schizophrenia (Tang et al., 2015), as well as induced alcohol dependence (Ray, 2011). Binder et al. (Binder et al., 2010) found that the CRHBP rs10473984 SNP was significantly associated with antidepressant treatment response, and that the rs10473984T SNP was associated with poor treatment outcomes. In addition, De Luca et al. revealed that CRHBP polymorphisms were related to suicide attempt susceptibility (De Luca et al., 2010); and that the interaction between CRHR1 and CRHBP might be associated with suicide attempts and the severity of suicidal behavior. Furthermore, Kertes et al. suggested that the rs1715747 SNP of the CRHBP gene contributes to depressive symptoms in alcohol-dependent individuals (Kertes et al., 2011). Roy et al. showed that the interaction between childhood trauma and CRHBP variants appears to increase the risk of suicidal behavior (Roy et al., 2012). Thus, the previous results support the notion that CRHBP is involved in the regulation of the stress response pathway, and affects human behavior.

To our knowledge, this is the first time that all of the four SNPs tested in this study were evaluated for their contribution to aggressive behavior in the Hunan Han Chinese population. Surprisingly, all of the four SNPs are located in the intron regions of CRHBP (rs32897 and rs7721799 in intron 3, rs7718461 in intron 5, and rs10062367 in intron 6). Among the four intron SNPs, rs32897 showed a significant association with robbery, whereas the others individually did not. When the robbery group was compared with the control group, the distribution of rs32897C was significantly lower in the robbery subgroup indicating a protective role for the C allele of rs32897. Further genotypic analyses showed that individuals with the CT/CC genotypes have a reduced robbery behavior, which is consistent with the allelic analysis results. According to the traditional view, the intron tag SNP rs32897 might not have any putative function. However, with the emergence of SNP Splicer (ElSharawy et al., 2006), there is increasing evidence to suggest that intron SNPs might affect alternative splicing of human coding genes (Cooper, 2010; Moyer et al., 2011; Jacobsson et al., 2012), The prediction of gene functions revealed that rs32897 SNP may be one of the expression quantitative trait loci (eQTLs) of the CRHBP gene, which may regulate protein levels (Wang et al., 2003). Further functional studies are clearly warranted.

Our haplotype analysis indicated that there are a total of eight haplotypes with frequencies >1%. The distribution of the haplotype GCAG was not significantly different between the combined criminal groups control group. However, this haplotype appears to significantly decrease the risk of robbery behavior, which might indicate that aggressive behavior is not influenced by a single site but multiple polymorphic sites. These results need to be confirmed in larger case-control studies.

Several limitations of this research must be considered. First, the positive results of this study may be a result of a type I error; however, we did address this limitation by using a Bonferroni's correction. Second, the sample size of this study was relatively small.

In conclusion, our results suggest that the rs32897C allele and the haplotype GCAG of the CRHBP gene might be potential protective factors for robbery behavior in the Hunan Han population.

Footnotes

Acknowledgments

We are grateful to all of the individuals who participated in this study.

Author Disclosure Statement

No competing financial interests exist.

Funding Information

This study was funded by the National Natural Science Foundation of China (Grant Nos. 81873780 and 61702054); Hunan Natural Science Foundation Youth Program (2019JJ50697); The Changsha Outstanding Innovative Young People Training Scheme (kq1905047, kq1905045); The Foundation of the Education Department of Hunan Province (16A027, 19A058); The Foundation of Health and Family Planning Commission of Hunan Province (20201918); The Application Characteristic Discipline of Hunan Province; The Hunan Key Laboratory Cultivation Base of the Research and Development of Novel Pharmaceutical Preparations (No. 2016TP1029); The Clinical Research Center of Neurodegenerative Diseases in Hunan province (2018SK4002); The Hunan Provincial Innovation Platform and Talents Program (No. 2018RS3105); The Hunan Provincial Science and Technology Department and Hunan Provincial Health and Family Planning Commission (Grant No. [2018]85); The Natural Science Foundation of Hunan Province (Grant No. [2017]1); The Key Project of Hunan Provincial Commission of Health and Family Planning (Grant No. [2017]144); The Hunan Province Science and Technology Major Project (Grant No. [2016]158); Hunan Provincial Science and Technology Department Clinical Medical Technology Innovation Guide Project (2018SK51711).

Supplementary Material

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