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GAD1 but not GAD2 polymorphisms are associated with heroin addiction phenotypes
Neuroscience Letters 717 (2020) 134704
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Research article
GAD1 but not GAD2 polymorphisms are associated with heroin addiction phenotypes
T
Shi Yuhuia,1, Li Yunxiaob,1, Zhang Jinyua, Xiao Yifana, Yan Penga, Zhu Yongshenga,c,* a
College of Forensic Science, Xi’an Jiaotong University, Xi’an, Shaanxi, China Department of Human Anatomy, Shaanxi University of Chinese Medicine, Xianyan, Shaanxi, China c Key Laboratory of Environment and Genes Related to Diseases, Ministry of Education, Xi’an, Shaanxi, China b
A R T I C LE I N FO
A B S T R A C T
Keywords: Heroin Addiction phenotypes Glutamate dehydrogenase Single nucleotide polymorphisms
Introduction: Heroin addiction is a chronic complex brain disease that contains multiple phenotypes, which vary widely among addicts and may be affected by genetic factors. A total of 801 unrelated heroin addicts were recruited and divided into different subgroups according to eight phenotypes of heroin addiction. Polymorphisms in GAD1 (rs3762555, rs3762556, rs3791878, rs3749034, rs11532313 and rs769395) and GAD2 (rs2839669, rs2839670 and rs2236418) were genotyped using the SNaPshot assay. Associations between genetic variants and the eight phenotypes were mainly assessed by binary logistic regression. Results: We found that the frequencies of G allele of GAD1 rs3749034 and rs3762555 were associated with daily dose of methadone use and memory change after heroin addiction. The C allele frequency of GAD1 rs3762556 was associated with lower daily dose of methadone use. In GAD1, SNPs rs3762556, rs3762555, rs3791878 and rs3749034 had strong linkage, and the frequency of the C-G-C-A haplotype was higher in the lower dose of methadone group. Patients with the TT genotype of rs11542313 were maintained on lower dose of methadone than patients with the CC genotype. The G alleles of rs3762555 and rs3749034 were lower, while the T allele of rs11542313 was higher, in the memory decreased group. The results of association analyses of GAD2 with phenotypes of heroin addiction showed no significant differences. Conclusion: GAD1 polymorphisms were associated with phenotypes of heroin addiction, especially the daily dose of methadone use and memory change in the Han Chinese population. These results may provide individualized guidance for the treatment of heroin addiction.
1. Introduction Heroin addiction is a chronic complex brain disease that contains multiple phenotypes [1]. Heroin dose is one major determinant of opiate withdrawal severity [2]. The duration of transition from first use to addiction (DTFUA) varies dramatically among heroin addicts [3], and may reflect addictive liability in particular subjects [4]. Animal experiments have revealed varying levels of vulnerability in the transition to addiction [5] and an association of this transition to persistent impairments in synaptic plasticity [6]. Drug-induced persistent neuroadaptation in reward-related learning and memory processes, which leads to hypersensitivity to drug-associated cues, impulsive decisionmaking and abnormal learned behaviors, is the neurobiological basis for the transition to addiction [3,7]. Decreased sexual function with loss
of libido and impotence in males and menstrual disturbances in females as well as low levels of gonadotropins and/or sex hormones are common findings in heroin addicts [8,9]. Endogenous opioid peptides play an important role in sleep. Due to the feedback inhibition of the endogenous opioid system caused by the long-term use of heroin, the patients with heroin addiction may exhibit difficulties in sleep initiation and maintenance. Sleep disorders are significantly associated with addiction relapse, greater likelihood of the use of multiple drugs and poorer quality of life [10]. The majority of heroin addicts did not have apparent pleasant feelings upon first opioid use. In contrast, most heroin addicts felt euphoria upon exposure after the development of addiction, suggesting an enhanced sensitivity to opioid rewarding effects [11]. Therefore, dividing the heroin addicts into different subgroups according to these phenotypes could contribute to the precise
Abbreviations: GAD, Glutamate dehydrogenase; SNP, Single nucleotide polymorphisms; DTFUA, The duration of transition from first use to addiction; MMT, Methadone Maintenance Treatment; HD, high methadone dose group; LD, low methadone dose group ⁎ Corresponding author at: No. 76, Yanta West Road, Xi’an, Shaanxi, 710061, China. E-mail address: [email protected] (Y. Zhu). 1 These authors contributed equally to the article. https://doi.org/10.1016/j.neulet.2019.134704 Received 8 July 2019; Received in revised form 12 December 2019; Accepted 17 December 2019 Available online 19 December 2019 0304-3940/ © 2019 Elsevier B.V. All rights reserved.
Neuroscience Letters 717 (2020) 134704
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Written informed consent was obtained from all participants. The study protocol was approved by the Ethical Committee of the Medical College, Xi’an Jiaotong University. In this study, we turned the variables with continuous data such as daily dose of methadone use, onset age, DTFUA and daily dose of heroin use into binary variables and divided the addicts into two groups based on the median. The mean and median of the 4 continuous variables related to heroin addiction phenotypes are shown in Table S3. The phenotypes related to the categorical data (memory, libido, euphoria and sleep quality) were classified into two categories according to the patient's self-report. The number of people in each category is shown in Table S4.
and personalized treatment of heroin addiction. Glutamate dehydrogenase (GAD) is the rate-limiting enzyme involved in synthesizing GABA, and consists of two isoforms of 67 kDa and 65 kDa that are encoded by GAD1 and GAD2, respectively, and coexpressed in most brain regions [12]. GAD1 is widely distributed in cells and is responsible for the synthesis of cytoplasmic GABA, while GAD2 is mainly located in the membrane and nerve endings, where the synthesized of GABA is used in vesicular release [13]. The lack of GAD1 in mice was lethal, while deletion of GAD2 increased ethanol palatability and intake and slightly reduced the severity of ethanol-induced withdrawal [14]. Based on predictions from bioinformatics (https://snpinfo.niehs. nih.gov/cgi-bin/snpinfo/Snpfunc.cgi), GAD1 rs3762555, rs3762556, rs3791878 and rs3749034 may be transcription factor binding sites of GAD1, while rs769395 may be microRNA-binding sites (Table S1). The G allele of rs3749034 has been associated with a decreased level of transcription enzyme, a genetic risk for childhood onset of schizophrenia and decreased cortical thickness [15]. The haplotype frequencies of T-A-C and C-C-T of rs1978340-rs3791878-rs11542313 of GAD1 were significantly higher in the heroin addiction group than in a control group [16]. The GAD1 polymorphism rs769404 (formerly known as rs11542313) has been reported to be associated with alcohol and heroin addiction [17,18]. GAD1 SNP rs769395 was further reported to be associated with phobias [19]. Patients with panic disorder exhibited significantly lower average GAD1 methylation than healthy controls at CpG sites in the promoter (rs3762556, rs3791878 and rs3762555) [20]. The G allele of rs2236418 (GAD2) was related to an increased risk of methamphetamine addiction [21]. A case-control association analysis was performed by screening 1350 variants of 130 genes and found a statistically significant association between rs8190646 of GAD2 and heroin addiction [22]. Therefore, both GAD1 and GAD2 are important candidate genes for the risk of heroin addiction; however, studies about GAD1 and GAD2 with various phenotypes of heroin addiction have been less frequent and worth further study [22]. To further clarify the role of the GAD1 and GAD2 in heroin addiction phenotypes, we first divided the heroin addicts into different subgroups according to eight phenotypes of heroin addiction. We then selected six SNPs (rs3762555, rs3762556, rs3791878, rs3749034, rs11532313 and rs769395) of the GAD1 and three SNPs (rs2839669, rs2839670 and rs2236418) of the GAD2. Finally, we analyzed the associations between GAD1 and GAD2 polymorphisms and these eight phenotypes of heroin addiction.
2.2. SNPs selection We performed a systematic screen of the promoter regions, untranslated regions (5′ and 3′UTRs), exons, and intron-exon boundaries of the GAD1 and GAD2. Nine SNPs with minor allele frequencies (MAF) greater than 0.05 and minor genotype frequencies more than 0.01 were selected from the two genes and nearby regions based on a search of HapMap and dbSNP (public databases that contain information about the Han Chinese population). These SNPs were further analyzed in an association study. 2.3. Genotyping Peripheral blood (2−5 ml) was collected from the enrolled subjects in tubes containers with EDTA anticoagulant. Genomic DNA was extracted from blood leukocytes using the EZNATM Blood DNA Midi Kit (Omega Bio-Tek, Norcross, GA, USA) according to the manufacturer’s protocol. SNP genotyping was performed using the SNaPshot assay (Genesky, Shanghai, China) with the standard protocol [24]. 2.4. Statistics Associations between genetic variants and the eight statistical indicators were assessed using binary logistic regression analysis adjusted for age, sex, income, occupation, marriage status, education and family relationship. Linkage disequilibrium was analyzed by Haploview 4.2 [25]. The haplotype block was determined and the D’ values for each pair of markers were calculated. The differences in alleles and haplotype frequencies between groups were conducted by Pearson’s χ2 tests. Bonferroni’s correction was performed to compensate for multiple comparison testing. For the measurement data, one-way analysis of variance (ANOVA) was used to analyze the differences in phenotypes by genotype. Statistical significance was defined as p < 0.05. All statistical analyses were performed with SPSS 20.0 software (SPSS Inc., Chicago, IL, USA).
2. Methods 2.1. Sample and phenotypes A total of 801 unrelated heroin addicts (mean age = 39.30 ± 8.29 years) were recruited from the Lantian Detoxification Center, Methadone Maintenance Treatment (MMT) Program at the Xi’an Mental Health Center and Xin’an Hospital (Table S2). Among them, there were 637 valid questionnaires of daily methadone use. Since DTFUA in most addicts (more than 95 %) was less than one year [23] and the error of recall increases with the self-reported DTFUA, the participants who reported using heroin for more than one year without addiction (n = 35) were excluded. The diagnosis of heroin addiction was conducted by at least two senior psychiatrists according to the Diagnostic and Statistical Manual of Mental Disorders (DSM)-5 criteria, medical history and urine test results. A self-designed questionnaire was made to assist with diagnosis, using a structured interview with questions. Participants were excluded if they were age < 18 years old; met DSM-5 criteria for an additional Axis I disorder; suffered from other mental disorders; had severe liver or kidney impairment; were pregnant; participated in other clinical drug trials. All participants were self-identified as northern Han Chinese.
3. Results 3.1. Associations between GAD1 and daily dose of methadone use In GAD1, binary logistic regression analysis demonstrated that the genotype distribution in the SNPs rs3762555, rs3762556 and rs3749034 had significant differences between the LD and HD groups (p < 0.05). For the SNP rs3762556, the GG genotype frequency was higher (p = 0.002), while the CC genotype was lower (p = 0.005) in the HD group compared to the LD group. The GG genotype frequency of rs3762555 was higher (p < 0.001) in the HD group than the LD group. The G allele frequencies of rs3762555 and rs3762556 were higher in the HD group than the LD group (p < 0.001 and p = 0.001, respectively). In the HD group, the GG genotype frequency of rs3749034 was higher (p < 0.001), but the GA and AA genotype frequencies were lower than the LD group (p = 0.002 and p = 0.005, respectively). The chi-square test indicated that the G allele of rs3749034 was associated 2
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Table 1 The logistic regression analysis (genotype) and Chi-square (allele) results between GAD1 SNPs and daily dose of methadone use. SNP
Location
Position
rs3762555 GG GC CC Alt G Ref C rs3762556 GG GC CC Alt G Ref C rs3791878 TT TG GG Ref G Alt T rs3749034 GG GA AA Ref G Alt A rs11542313 TT TC CC Ref T Alt C rs769395 GG GA AA Ref G Alt A
5' near
2:170815885
5' near
5' near
5' UTR
Exon 3
3' UTR
LD(n,%)
HD(n,%)
170(48.57) 148(42.29) 32(9.14) 488(69.71) 212(30.29)
188(65.51) 88(30.66) 11(3.83) 464(80.84) 110(19.16)
93(26.57) 160(45.71) 97(27.71) 346(49.43) 354(50.57)
105(36.59) 129(44.95) 53(18.47) 339(59.06) 235(40.94)
23(6.57) 120(34.29) 207(59.14) 166(23.71) 534(76.29)
20(6.97) 119(41.46) 148(51.57) 159(27.7) 415(72.3)
169(48.29) 151(43.14) 30(8.57) 489(69.86) 211(30.14)
188(65.51) 90(31.36) 9(3.14) 466(81.18) 108(18.82)
97(27.71) 176(50.29) 77(22) 370(52.86) 330(47.14)
58(20.21) 146(50.87) 83(28.92) 262(45.64) 312(54.36)
44(12.57) 155(44.29) 151(43.14) 243(34.71) 457(65.29)
42(14.63) 132(45.99) 113(39.37) 216(37.63) 358(62.37)
2:170815568
2:170815681
2:170816965
2:171504132
2:170860293
P Value
OR(CI 95%)
< 0.001 < 0.001 0.002 0.008 < 0.001
0.482(0.348-0.669) 1.696(1.215–2.369) 2.631(1.286–5.380) 0.546(0.419-0.710)
0.002 0.002 0.587 0.005 0.001
0.574(0.406-0.811) 1.093(0.793–1.506) 1.728(1.175–2.540) 0.678(0.542-0.847)
0.114 0.739 0.052 0.039 0.104
0.898(0.478–1.689) 0.722(0.519–1.002) 1.401(1.016–1.927) 1.233(0.958–1.587)
< 0.001 < 0.001 0.002 0.005 < 0.001
0.48(0.346-0.665) 1.689(1.212–2.354) 3.009(1.389–6.515) 0.537(0.412-0.700)
0.036 0.022 0.729 0.061 0.010
1.553(1.066–2.268) 0.945(0.688–1.299) 0.705(0.489–1.016) 0.749(0.600-0.935)
0.474 0.315 0.773 0.323 0.291
0.789(0.496–1.253) 0.954(0.693–1.313) 1.177(0.852–1.626) 0.881(0.700–1.109)
LD, low methadone dose group; HD, high methadone dose group. LD, n = 350; HD, n = 287. Ref: Reference, Alt: Alternative. The P value remains significant after the Bonferroni’s correction was marked in bold (P < 0.0056).
distribution of SNPs rs3762555, rs3749034 and rs11542313 had significant differences between the memory decreased and unchanged groups. For SNP rs3762555, the frequency of GG genotype was lower (p = 0.003) in the memory decreased group compared to the unchanged group. The GG genotype frequency of rs3749034 was lower (p = 0.001) in the memory decreased group than the unchanged group. The G allele frequencies of rs3749034 was lower in the memory decreased group than the memory unchanged group (p = 0.004). The T allele frequency of rs11542313 was higher in memory decreased group (p = 0.005), but the difference of TT did not survive the Bonferroni’s correction. The genotype distributions and frequencies of the two groups are shown in Table 4 (GAD1) and Table S7 (GAD2). Other results without significant differences are shown in supplemental materials (Table S8-S15).
with a higher daily dose of methadone use (p < 0.001). The genotype distributions and frequencies of SNPs in LD and HD groups are shown in Table 1 (GAD1) and Table S5 (GAD2). In GAD1, One-way ANOVA followed by the LSD-t test revealed that there were significant differences in the methadone dose of different genotypes of SNPs rs3762555, rs3749034 and rs11542313. The patients with the GG genotype of rs3762555 had a higher daily dose of methadone use than that of the GC patients (p < 0.001). The patients with the GG genotype of rs3749034 had a higher daily dose of methadone use than the GA and AA patients (p < 0.001 and p = 0.005, respectively). Patients with TT genotype of rs11542313 had lower daily dose of methadone use than patients with CC (p = 0.001). Daily methadone dose between TC and CC carriers had nominal difference (p = 0.011), and the results did not survive the Bonferroni’s correction. Data is listed in Table 2 (GAD1) and Table S6 (GAD2). Linkage disequilibrium analysis found that one block was formed in the GAD1 and GAD2, respectively. For the GAD1, SNPs rs3762555, rs3762556, rs3791878 and rs3749034 were located in block 1. Compared with the LD group, the frequency of the C-G-C-A haplotype (p = 0.001) was lower in the HD group. The haplotype structures and pairwise calculations of D’ values between SNPs are shown in Fig. 1. The frequencies and statistical analyses of the haplotypes are presented in Table 3.
4. Discussion MMT is a well-established and cost-effective treatment for heroin addiction [26]. However, disadvantages have also been associated with this treatment; for instance, the daily dose of methadone use has been associated with cognitive functioning impairment [27]. To keep impairments to a minimum, the daily methadone dose is customized. Furthermore, the pharmacokinetics of methadone vary greatly among individuals, so when the same dose of methadone is administered, considerably different concentrations and pharmacological effects are obtained across subjects [28]. Our results found that the G alleles of rs3762555, rs3762556 and rs3749034 in the GAD1 were strongly
3.2. Associations between GAD1 and memory change after addiction Binary logistic regression analysis demonstrated that the genotype 3
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genetic background should be taken into account during methadone maintenance treatment for heroin addiction. In the clinical, methadone dosage usually is related to the amount of heroin. We found the different results between the dose of methadone and heroin. Community Methadone Maintenance Treatment Management Measures in China prescribes that when daily abuse of heroin over 1 g, the maximum methadone dose the patients take shall be 60 ml/day; and when heroin is less than 1 g, methadone shall be precisely calculated. Therefore, daily methadone dose can’t reflect the amount of heroin taken by the patients. Furthermore, a 5′-promoter SNP in linkage disequilibrium with rs3749034 has been associated with variations in working memory performance [30]. Our results showed that the G allele of GAD1 rs3749034 and rs3762555 reduced the risk of memory loss in heroin addicts. Wu et al. did not find an association between rs3749034 and heroin addiction in a case-control study [18]. These findings suggest rs3749034 may have an important role in the memory phenotype. The allelic and genotypic frequency of the rs11542313 polymorphism in heroin addicts were significantly different from those in healthy controls [18]. SNP rs11542313 has been reported has interaction with mental disorders, such as antidepressant response [31], and attentiondeficit/hyperactivity disorder [32]. We are the first to show a significant association of GAD1 rs11542313 with memory changes after heroin addiction, which indicated that people with the A allele of GAD1 are more prone to memory loss. We evaluated the GAD2 for genetic variants. There were no significant differences in the genotype distribution and haplotype of SNPs among the different phenotypes, suggesting that the majority of genetically influenced variation in the function of this enzyme does not result in phenotypes of heroin addicts. Therefore, GAD2 polymorphisms were not a major risk factors for heroin addiction in the Chinese population.
Table 2 The daily dose of methadone use in different genotypes of GAD1 SNPs. Variants rs3762555 GG GC CC GG vs GC GG vs CC GC vs CC rs3762556 GG GC CC rs3791878 TT TG GG rs3749034 GG GA AA GG vs GA GG vs AA GA vs AA rs11542313 TT TC CC TT vs TC TT vs CC TC vs CC rs769395 GG GA AA
N
Mean
SD.
358 236 43
47.92 41.8 39.53
22.2 15.44 19.39
198 289 150
47.35 44.78 42.7
20.14 19.19 21.13
43 239 355
45 45.36 44.92
20.82 18.54 20.88
357 241 39
47.97 41.87 38.59
22.16 15.46 20
155 322 160
86 287 264
42 44.46 49.34
45.58 44.23 45.85
F
P Value
8.633
< 0.001
2.379
< 0.001 0.009 0.49 0.093
0.04
0.966
9.114
< 0.001
5.71
< 0.001 0.005 0.337 0.003
0.48
0.206 0.001 0.011 0.619
18.83 17.17 25.15
18.92 18.22 22.12
SD, standard deviation. The values of the variable with significant p-value after Bonferroni’s correction are marked in bold.
5. Conclusion
associated with higher daily dose of methadone use. Furthermore, the haplotype analysis revealed significantly more C-G-C-A haplotypes (rs3762556-rs3791878-rs3762555-rs3749034) in the LD group, which indicated that the mechanisms of rs3762555 and rs3762556 may be similar to that of rs3749034 in the methadone treatment. Previous study has demonstrated an association between heroin self-administration and decreased GABA efflux [29], which supports our experimental results. The T allele of GAD1 rs11542313 was strongly associated with a decreased risk of heroin addiction [18]. In our study, the patients with the TT genotype of rs11542313 were maintained on a lower dose of methadone than the patients with the CC genotype. Our conjecture was that the T allele increased the body's sensitivity to methadone and reduced the risk of addiction. Therefore, patients’
In conclusion, GAD1 polymorphisms were associated with multiple phenotypes of heroin addiction in the Han Chinese population. These results may provide guidance for the precise treatment for heroin addicts. Future studies are required to corroborate the results and elucidate the mechanism of the GAD1 in heroin addicts.
Author’s contributions SYH carried out data analysis. SYH and LYX drafted the manuscript. ZJY and XYF conducted samples collection and DNA extraction. YP provided suggestions for the manuscript. ZYS designed the study and revised the manuscript. All the authors have read and approved the final manuscript.
Fig. 1. GAD1 and GAD2 SNPs linkage disequilibrium plot in daily methadone dose analysis. Empty squares indicate D’ = 1 (i.e. complete linkage disequilibrium between a pair of SNPs). 4
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Table 3 The association results of haplotype frequencies of GAD1 and GAD2 between LD and HD group. Gene
ID
Haplotype
LD(n,%)
HD(n,%)
P Value
OR(CI 95 %)
GAD1
Hap1 Hap2 Hap3 Hap4 Hap1 Hap2
G-G-G-G G-T-G-G C-G-G-G C-G-C-A C-C-A T-A-G
90(25.7) 82(23.3) 72(20.5) 104(29.7) 233(66.7) 117(33.3)
90(31.4) 78(27.3) 63(22.0) 53(18.4) 201(70.0) 86(30.0)
0.115 0.278 0.672 0.001 0.351 0.351
0.758(0.536–1.071) 0.82(0.573–1.174) 0.921(0.629–1.348) 1.876(1.281–2.719) 0.852(0.609–1.193) 1.174(0.838–1.642)
GAD2
LD, low methadone dose group; HD, high methadone dose group. LD, n = 350; HD, n = 287. P-value with statistically significant differences after Bonferroni’s correction was marked in bold.
Funding
participants were asked to provide written informed consent. The study protocol was approved by the Ethical Committee of the Medical College, Xi’an Jiaotong University.
This study was totally supported by National Natural Science Foundation of China (81571858) and Shaanxi Province Foundation for Returness (2018020).
Consent for publication Not applicable.
Availability of data and materials The datasets in this study are available from the corresponding author on request.
Declaration of Competing Interest The authors declare that they have no competing interests.
Ethics approval and consent to participant Acknowledgments Samples were collected from the Lantian Compulsory Isolated Detoxification Center, Methadone Maintenance Treatment (MMT) Program at the Xi’an Mental Health Center and Xin’an Hospital. All
We would like to thank the two senior psychiatrists, who conducted diagnosis of the 801 heroin addicts, from the Lantian Compulsory
Table 4 Associations between genotypic and allelic frequencies of GAD1 gene polymorphisms and memory change in heroin addicts. SNP
Location
rs3762555 GG GC CC Alt G Ref C rs3762556 GG GC CC Alt G Ref C rs3791878 TT TG GG Ref G Alt T rs3749034 GG GA AA Ref G Alt A rs11542313 TT TC CC Ref T Alt C rs769395 GG GA AA Ref G Alt A
5' near
Memory unchanged (n,%)
Memory decreased (n,%)
140(65.12) 63(29.3) 12(5.58) 343(79.77) 87(20.23)
315(53.75) 231(39.42) 40(6.83) 861(73.46) 311(26.54)
73(33.95) 89(41.4) 53(24.65) 235(54.65) 195(45.35)
181(30.89) 279(47.61) 126(21.5) 641(54.69) 531(45.31)
11(5.12) 89(41.4) 115(53.49) 319(74.19) 111(25.81)
42(7.17) 228(38.91) 316(53.92) 860(73.38) 312(26.62)
141(65.58) 64(29.77) 10(4.65) 346(80.47) 84(19.53)
313(53.41) 235(40.1) 38(6.48) 861(73.46) 311(26.54)
38(17.67) 116(53.95) 61(28.37) 192(44.65) 238(55.35)
158(26.96) 300(51.19) 128(21.84) 616(52.56) 556(47.44)
29(13.49) 102(47.44) 84(39.07) 160(37.21) 270(62.79)
82(13.99) 270(46.08) 234(39.93) 434(37.03) 738(62.97)
5' near
5' near
5' UTR
Exon 3
3' UTR
Memory unchanged group, n = 215; Memory decreased group, n = 586. P-values with statistically significant differences after Bonferroni’s correction are marked in bold. 5
P Value
OR(CI 95 %)
0.010 0.003 0.006 0.476 0.010
0.601(0.432-0.837) 1.615(1.145–2.277) 1.28(0.649–2.524) 1.424(1.089–1.863)
0.283 0.354 0.113 0.390 0.988
0.852(0.606–1.196) 1.3(0.940–1.799) 0.847(0.581–1.236) 0.998(0.800–1.246)
0.439 0.275 0.374 0.751 0.745
1.473(0.735–2.950) 0.862(0.621–1.196) 1.053(0.761–1.452) 1.043(0.810–1.341)
0.006 0.001 0.006 0.269 0.004
0.582(0.418-0.811) 1.61(1.144–2.267) 1.507(0.728–3.121) 1.488(1.134–1.952)
0.015 0.007 0.480 0.058 0.005
1.731(1.158–2.587) 0.891(0.647–1.228) 0.703(0.489–1.012) 0.728(0.583-0.909)
0.961 0.970 0.785 0.802 0.948
1.009(0.632–1.610) 0.956(0.694–1.318) 1.043(0.752–1.447) 1.008(0.802–1.267)
Neuroscience Letters 717 (2020) 134704
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Isolated Detoxification Center, Methadone Maintenance Treatment (MMT) Program of the Xi’an Mental Health Center and Xin’an Hospital.
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Research article
GAD1 but not GAD2 polymorphisms are associated with heroin addiction phenotypes
T
Shi Yuhuia,1, Li Yunxiaob,1, Zhang Jinyua, Xiao Yifana, Yan Penga, Zhu Yongshenga,c,* a
College of Forensic Science, Xi’an Jiaotong University, Xi’an, Shaanxi, China Department of Human Anatomy, Shaanxi University of Chinese Medicine, Xianyan, Shaanxi, China c Key Laboratory of Environment and Genes Related to Diseases, Ministry of Education, Xi’an, Shaanxi, China b
A R T I C LE I N FO
A B S T R A C T
Keywords: Heroin Addiction phenotypes Glutamate dehydrogenase Single nucleotide polymorphisms
Introduction: Heroin addiction is a chronic complex brain disease that contains multiple phenotypes, which vary widely among addicts and may be affected by genetic factors. A total of 801 unrelated heroin addicts were recruited and divided into different subgroups according to eight phenotypes of heroin addiction. Polymorphisms in GAD1 (rs3762555, rs3762556, rs3791878, rs3749034, rs11532313 and rs769395) and GAD2 (rs2839669, rs2839670 and rs2236418) were genotyped using the SNaPshot assay. Associations between genetic variants and the eight phenotypes were mainly assessed by binary logistic regression. Results: We found that the frequencies of G allele of GAD1 rs3749034 and rs3762555 were associated with daily dose of methadone use and memory change after heroin addiction. The C allele frequency of GAD1 rs3762556 was associated with lower daily dose of methadone use. In GAD1, SNPs rs3762556, rs3762555, rs3791878 and rs3749034 had strong linkage, and the frequency of the C-G-C-A haplotype was higher in the lower dose of methadone group. Patients with the TT genotype of rs11542313 were maintained on lower dose of methadone than patients with the CC genotype. The G alleles of rs3762555 and rs3749034 were lower, while the T allele of rs11542313 was higher, in the memory decreased group. The results of association analyses of GAD2 with phenotypes of heroin addiction showed no significant differences. Conclusion: GAD1 polymorphisms were associated with phenotypes of heroin addiction, especially the daily dose of methadone use and memory change in the Han Chinese population. These results may provide individualized guidance for the treatment of heroin addiction.
1. Introduction Heroin addiction is a chronic complex brain disease that contains multiple phenotypes [1]. Heroin dose is one major determinant of opiate withdrawal severity [2]. The duration of transition from first use to addiction (DTFUA) varies dramatically among heroin addicts [3], and may reflect addictive liability in particular subjects [4]. Animal experiments have revealed varying levels of vulnerability in the transition to addiction [5] and an association of this transition to persistent impairments in synaptic plasticity [6]. Drug-induced persistent neuroadaptation in reward-related learning and memory processes, which leads to hypersensitivity to drug-associated cues, impulsive decisionmaking and abnormal learned behaviors, is the neurobiological basis for the transition to addiction [3,7]. Decreased sexual function with loss
of libido and impotence in males and menstrual disturbances in females as well as low levels of gonadotropins and/or sex hormones are common findings in heroin addicts [8,9]. Endogenous opioid peptides play an important role in sleep. Due to the feedback inhibition of the endogenous opioid system caused by the long-term use of heroin, the patients with heroin addiction may exhibit difficulties in sleep initiation and maintenance. Sleep disorders are significantly associated with addiction relapse, greater likelihood of the use of multiple drugs and poorer quality of life [10]. The majority of heroin addicts did not have apparent pleasant feelings upon first opioid use. In contrast, most heroin addicts felt euphoria upon exposure after the development of addiction, suggesting an enhanced sensitivity to opioid rewarding effects [11]. Therefore, dividing the heroin addicts into different subgroups according to these phenotypes could contribute to the precise
Abbreviations: GAD, Glutamate dehydrogenase; SNP, Single nucleotide polymorphisms; DTFUA, The duration of transition from first use to addiction; MMT, Methadone Maintenance Treatment; HD, high methadone dose group; LD, low methadone dose group ⁎ Corresponding author at: No. 76, Yanta West Road, Xi’an, Shaanxi, 710061, China. E-mail address: [email protected] (Y. Zhu). 1 These authors contributed equally to the article. https://doi.org/10.1016/j.neulet.2019.134704 Received 8 July 2019; Received in revised form 12 December 2019; Accepted 17 December 2019 Available online 19 December 2019 0304-3940/ © 2019 Elsevier B.V. All rights reserved.
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Written informed consent was obtained from all participants. The study protocol was approved by the Ethical Committee of the Medical College, Xi’an Jiaotong University. In this study, we turned the variables with continuous data such as daily dose of methadone use, onset age, DTFUA and daily dose of heroin use into binary variables and divided the addicts into two groups based on the median. The mean and median of the 4 continuous variables related to heroin addiction phenotypes are shown in Table S3. The phenotypes related to the categorical data (memory, libido, euphoria and sleep quality) were classified into two categories according to the patient's self-report. The number of people in each category is shown in Table S4.
and personalized treatment of heroin addiction. Glutamate dehydrogenase (GAD) is the rate-limiting enzyme involved in synthesizing GABA, and consists of two isoforms of 67 kDa and 65 kDa that are encoded by GAD1 and GAD2, respectively, and coexpressed in most brain regions [12]. GAD1 is widely distributed in cells and is responsible for the synthesis of cytoplasmic GABA, while GAD2 is mainly located in the membrane and nerve endings, where the synthesized of GABA is used in vesicular release [13]. The lack of GAD1 in mice was lethal, while deletion of GAD2 increased ethanol palatability and intake and slightly reduced the severity of ethanol-induced withdrawal [14]. Based on predictions from bioinformatics (https://snpinfo.niehs. nih.gov/cgi-bin/snpinfo/Snpfunc.cgi), GAD1 rs3762555, rs3762556, rs3791878 and rs3749034 may be transcription factor binding sites of GAD1, while rs769395 may be microRNA-binding sites (Table S1). The G allele of rs3749034 has been associated with a decreased level of transcription enzyme, a genetic risk for childhood onset of schizophrenia and decreased cortical thickness [15]. The haplotype frequencies of T-A-C and C-C-T of rs1978340-rs3791878-rs11542313 of GAD1 were significantly higher in the heroin addiction group than in a control group [16]. The GAD1 polymorphism rs769404 (formerly known as rs11542313) has been reported to be associated with alcohol and heroin addiction [17,18]. GAD1 SNP rs769395 was further reported to be associated with phobias [19]. Patients with panic disorder exhibited significantly lower average GAD1 methylation than healthy controls at CpG sites in the promoter (rs3762556, rs3791878 and rs3762555) [20]. The G allele of rs2236418 (GAD2) was related to an increased risk of methamphetamine addiction [21]. A case-control association analysis was performed by screening 1350 variants of 130 genes and found a statistically significant association between rs8190646 of GAD2 and heroin addiction [22]. Therefore, both GAD1 and GAD2 are important candidate genes for the risk of heroin addiction; however, studies about GAD1 and GAD2 with various phenotypes of heroin addiction have been less frequent and worth further study [22]. To further clarify the role of the GAD1 and GAD2 in heroin addiction phenotypes, we first divided the heroin addicts into different subgroups according to eight phenotypes of heroin addiction. We then selected six SNPs (rs3762555, rs3762556, rs3791878, rs3749034, rs11532313 and rs769395) of the GAD1 and three SNPs (rs2839669, rs2839670 and rs2236418) of the GAD2. Finally, we analyzed the associations between GAD1 and GAD2 polymorphisms and these eight phenotypes of heroin addiction.
2.2. SNPs selection We performed a systematic screen of the promoter regions, untranslated regions (5′ and 3′UTRs), exons, and intron-exon boundaries of the GAD1 and GAD2. Nine SNPs with minor allele frequencies (MAF) greater than 0.05 and minor genotype frequencies more than 0.01 were selected from the two genes and nearby regions based on a search of HapMap and dbSNP (public databases that contain information about the Han Chinese population). These SNPs were further analyzed in an association study. 2.3. Genotyping Peripheral blood (2−5 ml) was collected from the enrolled subjects in tubes containers with EDTA anticoagulant. Genomic DNA was extracted from blood leukocytes using the EZNATM Blood DNA Midi Kit (Omega Bio-Tek, Norcross, GA, USA) according to the manufacturer’s protocol. SNP genotyping was performed using the SNaPshot assay (Genesky, Shanghai, China) with the standard protocol [24]. 2.4. Statistics Associations between genetic variants and the eight statistical indicators were assessed using binary logistic regression analysis adjusted for age, sex, income, occupation, marriage status, education and family relationship. Linkage disequilibrium was analyzed by Haploview 4.2 [25]. The haplotype block was determined and the D’ values for each pair of markers were calculated. The differences in alleles and haplotype frequencies between groups were conducted by Pearson’s χ2 tests. Bonferroni’s correction was performed to compensate for multiple comparison testing. For the measurement data, one-way analysis of variance (ANOVA) was used to analyze the differences in phenotypes by genotype. Statistical significance was defined as p < 0.05. All statistical analyses were performed with SPSS 20.0 software (SPSS Inc., Chicago, IL, USA).
2. Methods 2.1. Sample and phenotypes A total of 801 unrelated heroin addicts (mean age = 39.30 ± 8.29 years) were recruited from the Lantian Detoxification Center, Methadone Maintenance Treatment (MMT) Program at the Xi’an Mental Health Center and Xin’an Hospital (Table S2). Among them, there were 637 valid questionnaires of daily methadone use. Since DTFUA in most addicts (more than 95 %) was less than one year [23] and the error of recall increases with the self-reported DTFUA, the participants who reported using heroin for more than one year without addiction (n = 35) were excluded. The diagnosis of heroin addiction was conducted by at least two senior psychiatrists according to the Diagnostic and Statistical Manual of Mental Disorders (DSM)-5 criteria, medical history and urine test results. A self-designed questionnaire was made to assist with diagnosis, using a structured interview with questions. Participants were excluded if they were age < 18 years old; met DSM-5 criteria for an additional Axis I disorder; suffered from other mental disorders; had severe liver or kidney impairment; were pregnant; participated in other clinical drug trials. All participants were self-identified as northern Han Chinese.
3. Results 3.1. Associations between GAD1 and daily dose of methadone use In GAD1, binary logistic regression analysis demonstrated that the genotype distribution in the SNPs rs3762555, rs3762556 and rs3749034 had significant differences between the LD and HD groups (p < 0.05). For the SNP rs3762556, the GG genotype frequency was higher (p = 0.002), while the CC genotype was lower (p = 0.005) in the HD group compared to the LD group. The GG genotype frequency of rs3762555 was higher (p < 0.001) in the HD group than the LD group. The G allele frequencies of rs3762555 and rs3762556 were higher in the HD group than the LD group (p < 0.001 and p = 0.001, respectively). In the HD group, the GG genotype frequency of rs3749034 was higher (p < 0.001), but the GA and AA genotype frequencies were lower than the LD group (p = 0.002 and p = 0.005, respectively). The chi-square test indicated that the G allele of rs3749034 was associated 2
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Table 1 The logistic regression analysis (genotype) and Chi-square (allele) results between GAD1 SNPs and daily dose of methadone use. SNP
Location
Position
rs3762555 GG GC CC Alt G Ref C rs3762556 GG GC CC Alt G Ref C rs3791878 TT TG GG Ref G Alt T rs3749034 GG GA AA Ref G Alt A rs11542313 TT TC CC Ref T Alt C rs769395 GG GA AA Ref G Alt A
5' near
2:170815885
5' near
5' near
5' UTR
Exon 3
3' UTR
LD(n,%)
HD(n,%)
170(48.57) 148(42.29) 32(9.14) 488(69.71) 212(30.29)
188(65.51) 88(30.66) 11(3.83) 464(80.84) 110(19.16)
93(26.57) 160(45.71) 97(27.71) 346(49.43) 354(50.57)
105(36.59) 129(44.95) 53(18.47) 339(59.06) 235(40.94)
23(6.57) 120(34.29) 207(59.14) 166(23.71) 534(76.29)
20(6.97) 119(41.46) 148(51.57) 159(27.7) 415(72.3)
169(48.29) 151(43.14) 30(8.57) 489(69.86) 211(30.14)
188(65.51) 90(31.36) 9(3.14) 466(81.18) 108(18.82)
97(27.71) 176(50.29) 77(22) 370(52.86) 330(47.14)
58(20.21) 146(50.87) 83(28.92) 262(45.64) 312(54.36)
44(12.57) 155(44.29) 151(43.14) 243(34.71) 457(65.29)
42(14.63) 132(45.99) 113(39.37) 216(37.63) 358(62.37)
2:170815568
2:170815681
2:170816965
2:171504132
2:170860293
P Value
OR(CI 95%)
< 0.001 < 0.001 0.002 0.008 < 0.001
0.482(0.348-0.669) 1.696(1.215–2.369) 2.631(1.286–5.380) 0.546(0.419-0.710)
0.002 0.002 0.587 0.005 0.001
0.574(0.406-0.811) 1.093(0.793–1.506) 1.728(1.175–2.540) 0.678(0.542-0.847)
0.114 0.739 0.052 0.039 0.104
0.898(0.478–1.689) 0.722(0.519–1.002) 1.401(1.016–1.927) 1.233(0.958–1.587)
< 0.001 < 0.001 0.002 0.005 < 0.001
0.48(0.346-0.665) 1.689(1.212–2.354) 3.009(1.389–6.515) 0.537(0.412-0.700)
0.036 0.022 0.729 0.061 0.010
1.553(1.066–2.268) 0.945(0.688–1.299) 0.705(0.489–1.016) 0.749(0.600-0.935)
0.474 0.315 0.773 0.323 0.291
0.789(0.496–1.253) 0.954(0.693–1.313) 1.177(0.852–1.626) 0.881(0.700–1.109)
LD, low methadone dose group; HD, high methadone dose group. LD, n = 350; HD, n = 287. Ref: Reference, Alt: Alternative. The P value remains significant after the Bonferroni’s correction was marked in bold (P < 0.0056).
distribution of SNPs rs3762555, rs3749034 and rs11542313 had significant differences between the memory decreased and unchanged groups. For SNP rs3762555, the frequency of GG genotype was lower (p = 0.003) in the memory decreased group compared to the unchanged group. The GG genotype frequency of rs3749034 was lower (p = 0.001) in the memory decreased group than the unchanged group. The G allele frequencies of rs3749034 was lower in the memory decreased group than the memory unchanged group (p = 0.004). The T allele frequency of rs11542313 was higher in memory decreased group (p = 0.005), but the difference of TT did not survive the Bonferroni’s correction. The genotype distributions and frequencies of the two groups are shown in Table 4 (GAD1) and Table S7 (GAD2). Other results without significant differences are shown in supplemental materials (Table S8-S15).
with a higher daily dose of methadone use (p < 0.001). The genotype distributions and frequencies of SNPs in LD and HD groups are shown in Table 1 (GAD1) and Table S5 (GAD2). In GAD1, One-way ANOVA followed by the LSD-t test revealed that there were significant differences in the methadone dose of different genotypes of SNPs rs3762555, rs3749034 and rs11542313. The patients with the GG genotype of rs3762555 had a higher daily dose of methadone use than that of the GC patients (p < 0.001). The patients with the GG genotype of rs3749034 had a higher daily dose of methadone use than the GA and AA patients (p < 0.001 and p = 0.005, respectively). Patients with TT genotype of rs11542313 had lower daily dose of methadone use than patients with CC (p = 0.001). Daily methadone dose between TC and CC carriers had nominal difference (p = 0.011), and the results did not survive the Bonferroni’s correction. Data is listed in Table 2 (GAD1) and Table S6 (GAD2). Linkage disequilibrium analysis found that one block was formed in the GAD1 and GAD2, respectively. For the GAD1, SNPs rs3762555, rs3762556, rs3791878 and rs3749034 were located in block 1. Compared with the LD group, the frequency of the C-G-C-A haplotype (p = 0.001) was lower in the HD group. The haplotype structures and pairwise calculations of D’ values between SNPs are shown in Fig. 1. The frequencies and statistical analyses of the haplotypes are presented in Table 3.
4. Discussion MMT is a well-established and cost-effective treatment for heroin addiction [26]. However, disadvantages have also been associated with this treatment; for instance, the daily dose of methadone use has been associated with cognitive functioning impairment [27]. To keep impairments to a minimum, the daily methadone dose is customized. Furthermore, the pharmacokinetics of methadone vary greatly among individuals, so when the same dose of methadone is administered, considerably different concentrations and pharmacological effects are obtained across subjects [28]. Our results found that the G alleles of rs3762555, rs3762556 and rs3749034 in the GAD1 were strongly
3.2. Associations between GAD1 and memory change after addiction Binary logistic regression analysis demonstrated that the genotype 3
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genetic background should be taken into account during methadone maintenance treatment for heroin addiction. In the clinical, methadone dosage usually is related to the amount of heroin. We found the different results between the dose of methadone and heroin. Community Methadone Maintenance Treatment Management Measures in China prescribes that when daily abuse of heroin over 1 g, the maximum methadone dose the patients take shall be 60 ml/day; and when heroin is less than 1 g, methadone shall be precisely calculated. Therefore, daily methadone dose can’t reflect the amount of heroin taken by the patients. Furthermore, a 5′-promoter SNP in linkage disequilibrium with rs3749034 has been associated with variations in working memory performance [30]. Our results showed that the G allele of GAD1 rs3749034 and rs3762555 reduced the risk of memory loss in heroin addicts. Wu et al. did not find an association between rs3749034 and heroin addiction in a case-control study [18]. These findings suggest rs3749034 may have an important role in the memory phenotype. The allelic and genotypic frequency of the rs11542313 polymorphism in heroin addicts were significantly different from those in healthy controls [18]. SNP rs11542313 has been reported has interaction with mental disorders, such as antidepressant response [31], and attentiondeficit/hyperactivity disorder [32]. We are the first to show a significant association of GAD1 rs11542313 with memory changes after heroin addiction, which indicated that people with the A allele of GAD1 are more prone to memory loss. We evaluated the GAD2 for genetic variants. There were no significant differences in the genotype distribution and haplotype of SNPs among the different phenotypes, suggesting that the majority of genetically influenced variation in the function of this enzyme does not result in phenotypes of heroin addicts. Therefore, GAD2 polymorphisms were not a major risk factors for heroin addiction in the Chinese population.
Table 2 The daily dose of methadone use in different genotypes of GAD1 SNPs. Variants rs3762555 GG GC CC GG vs GC GG vs CC GC vs CC rs3762556 GG GC CC rs3791878 TT TG GG rs3749034 GG GA AA GG vs GA GG vs AA GA vs AA rs11542313 TT TC CC TT vs TC TT vs CC TC vs CC rs769395 GG GA AA
N
Mean
SD.
358 236 43
47.92 41.8 39.53
22.2 15.44 19.39
198 289 150
47.35 44.78 42.7
20.14 19.19 21.13
43 239 355
45 45.36 44.92
20.82 18.54 20.88
357 241 39
47.97 41.87 38.59
22.16 15.46 20
155 322 160
86 287 264
42 44.46 49.34
45.58 44.23 45.85
F
P Value
8.633
< 0.001
2.379
< 0.001 0.009 0.49 0.093
0.04
0.966
9.114
< 0.001
5.71
< 0.001 0.005 0.337 0.003
0.48
0.206 0.001 0.011 0.619
18.83 17.17 25.15
18.92 18.22 22.12
SD, standard deviation. The values of the variable with significant p-value after Bonferroni’s correction are marked in bold.
5. Conclusion
associated with higher daily dose of methadone use. Furthermore, the haplotype analysis revealed significantly more C-G-C-A haplotypes (rs3762556-rs3791878-rs3762555-rs3749034) in the LD group, which indicated that the mechanisms of rs3762555 and rs3762556 may be similar to that of rs3749034 in the methadone treatment. Previous study has demonstrated an association between heroin self-administration and decreased GABA efflux [29], which supports our experimental results. The T allele of GAD1 rs11542313 was strongly associated with a decreased risk of heroin addiction [18]. In our study, the patients with the TT genotype of rs11542313 were maintained on a lower dose of methadone than the patients with the CC genotype. Our conjecture was that the T allele increased the body's sensitivity to methadone and reduced the risk of addiction. Therefore, patients’
In conclusion, GAD1 polymorphisms were associated with multiple phenotypes of heroin addiction in the Han Chinese population. These results may provide guidance for the precise treatment for heroin addicts. Future studies are required to corroborate the results and elucidate the mechanism of the GAD1 in heroin addicts.
Author’s contributions SYH carried out data analysis. SYH and LYX drafted the manuscript. ZJY and XYF conducted samples collection and DNA extraction. YP provided suggestions for the manuscript. ZYS designed the study and revised the manuscript. All the authors have read and approved the final manuscript.
Fig. 1. GAD1 and GAD2 SNPs linkage disequilibrium plot in daily methadone dose analysis. Empty squares indicate D’ = 1 (i.e. complete linkage disequilibrium between a pair of SNPs). 4
Neuroscience Letters 717 (2020) 134704
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Table 3 The association results of haplotype frequencies of GAD1 and GAD2 between LD and HD group. Gene
ID
Haplotype
LD(n,%)
HD(n,%)
P Value
OR(CI 95 %)
GAD1
Hap1 Hap2 Hap3 Hap4 Hap1 Hap2
G-G-G-G G-T-G-G C-G-G-G C-G-C-A C-C-A T-A-G
90(25.7) 82(23.3) 72(20.5) 104(29.7) 233(66.7) 117(33.3)
90(31.4) 78(27.3) 63(22.0) 53(18.4) 201(70.0) 86(30.0)
0.115 0.278 0.672 0.001 0.351 0.351
0.758(0.536–1.071) 0.82(0.573–1.174) 0.921(0.629–1.348) 1.876(1.281–2.719) 0.852(0.609–1.193) 1.174(0.838–1.642)
GAD2
LD, low methadone dose group; HD, high methadone dose group. LD, n = 350; HD, n = 287. P-value with statistically significant differences after Bonferroni’s correction was marked in bold.
Funding
participants were asked to provide written informed consent. The study protocol was approved by the Ethical Committee of the Medical College, Xi’an Jiaotong University.
This study was totally supported by National Natural Science Foundation of China (81571858) and Shaanxi Province Foundation for Returness (2018020).
Consent for publication Not applicable.
Availability of data and materials The datasets in this study are available from the corresponding author on request.
Declaration of Competing Interest The authors declare that they have no competing interests.
Ethics approval and consent to participant Acknowledgments Samples were collected from the Lantian Compulsory Isolated Detoxification Center, Methadone Maintenance Treatment (MMT) Program at the Xi’an Mental Health Center and Xin’an Hospital. All
We would like to thank the two senior psychiatrists, who conducted diagnosis of the 801 heroin addicts, from the Lantian Compulsory
Table 4 Associations between genotypic and allelic frequencies of GAD1 gene polymorphisms and memory change in heroin addicts. SNP
Location
rs3762555 GG GC CC Alt G Ref C rs3762556 GG GC CC Alt G Ref C rs3791878 TT TG GG Ref G Alt T rs3749034 GG GA AA Ref G Alt A rs11542313 TT TC CC Ref T Alt C rs769395 GG GA AA Ref G Alt A
5' near
Memory unchanged (n,%)
Memory decreased (n,%)
140(65.12) 63(29.3) 12(5.58) 343(79.77) 87(20.23)
315(53.75) 231(39.42) 40(6.83) 861(73.46) 311(26.54)
73(33.95) 89(41.4) 53(24.65) 235(54.65) 195(45.35)
181(30.89) 279(47.61) 126(21.5) 641(54.69) 531(45.31)
11(5.12) 89(41.4) 115(53.49) 319(74.19) 111(25.81)
42(7.17) 228(38.91) 316(53.92) 860(73.38) 312(26.62)
141(65.58) 64(29.77) 10(4.65) 346(80.47) 84(19.53)
313(53.41) 235(40.1) 38(6.48) 861(73.46) 311(26.54)
38(17.67) 116(53.95) 61(28.37) 192(44.65) 238(55.35)
158(26.96) 300(51.19) 128(21.84) 616(52.56) 556(47.44)
29(13.49) 102(47.44) 84(39.07) 160(37.21) 270(62.79)
82(13.99) 270(46.08) 234(39.93) 434(37.03) 738(62.97)
5' near
5' near
5' UTR
Exon 3
3' UTR
Memory unchanged group, n = 215; Memory decreased group, n = 586. P-values with statistically significant differences after Bonferroni’s correction are marked in bold. 5
P Value
OR(CI 95 %)
0.010 0.003 0.006 0.476 0.010
0.601(0.432-0.837) 1.615(1.145–2.277) 1.28(0.649–2.524) 1.424(1.089–1.863)
0.283 0.354 0.113 0.390 0.988
0.852(0.606–1.196) 1.3(0.940–1.799) 0.847(0.581–1.236) 0.998(0.800–1.246)
0.439 0.275 0.374 0.751 0.745
1.473(0.735–2.950) 0.862(0.621–1.196) 1.053(0.761–1.452) 1.043(0.810–1.341)
0.006 0.001 0.006 0.269 0.004
0.582(0.418-0.811) 1.61(1.144–2.267) 1.507(0.728–3.121) 1.488(1.134–1.952)
0.015 0.007 0.480 0.058 0.005
1.731(1.158–2.587) 0.891(0.647–1.228) 0.703(0.489–1.012) 0.728(0.583-0.909)
0.961 0.970 0.785 0.802 0.948
1.009(0.632–1.610) 0.956(0.694–1.318) 1.043(0.752–1.447) 1.008(0.802–1.267)
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Isolated Detoxification Center, Methadone Maintenance Treatment (MMT) Program of the Xi’an Mental Health Center and Xin’an Hospital.
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