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. 2018 Aug 29;8:13000. doi: 10.1038/s41598-018-31240-9

A common polymorphism of COMT was associated with symptomatic lumbar disc herniation based on a large sample with Chinese Han ancestry

Hongliang Liu 1,2, Hongmou Zhao 3, Zhong Li 4, Hanzhong Xue 4, Jun Lu 5,, Wei Ma 1,
PMCID: PMC6115408  PMID: 30158547

Abstract

Lumbar disc herniation (LDH) is a common spine disease characterized by a tear in the disc ring and bulges out at the soft portion. COMT is a protein coding gene located at 22q11.21, and its gene product is a major mammalian enzyme involved in the degradation of catecholamines. A total of 2,678 study subjects with Chinese Han ancestry were recruited and 15 SNPs were selected for genotyping in our study subjects. A synonymous coding SNP, rs4633, was identified to be significantly associated with the disease status of LDH after adjusting for BMI (OR = 0.76, P = 4.83 × 10−5). This SNP was also identified to be significantly associated with COMT gene expression in three types of human tissues. Minor alleles of rs4633 (T) increased the expression of COMT in these 3 tissues. We have identified a significant SNP of COMT, rs4633, which is associated with symptomatic LDH in a large Chinese Han-based sample of the study subjects. This significant finding is further replicated by haplotypic analysis. Evidence from bioinformatics analyses have shown that rs4633 is also significantly associated with the gene expression of COMT. Our findings provide additional supportive evidence for an important role of COMT gene in the symptomatic LDH susceptibility.

Introduction

Lumbar disc herniation (LDH) is a common spine disease characterized by a tear in the disc ring and bulging out of its soft portion1. The most common symptom of symptomatic LDH is sciatica, and approximately 90% of the time, sciatica is caused by symptomatic LDH1. Symptomatic LDH patients might also experience a numb feeling throughout one or both of their legs due to the compression of the femoral nerve root by the hernia. Symptomatic LDH and its related low back pain can be devastating for the quality of life for LDH patients. Compared to those without symptomatic LDH, patients with symptomatic LDH have heavy health care loads and incur great work loss. As a complex disease with multiple contributing factors, previous studies have identified various factors, such as age, smoking, and obesity, to be significantly associated with LDH. In addition to these environmental factors, genetics have also been proven to play an important role in the pathology of LDH. A study conducted by Sambrook et al. showed that genetic variations could explain approximately 50–70% of the phenotypic variations of LDH2. Genes including COL11A13, THBS24, ASPN5, CILP6,7, COL9A38 and MMP94 have been confirmed to be loci of susceptibility to LDH or disc degeneration. The effect size of the significant polymorphisms identified from these loci were tiny compared to the heritability of LDH, and this indicated that more genes that contributed to the risk of LDH were still not discovered and more studies are still needed in the future to unravel the genetic etiology of LDH. COMT is a protein coding gene comprised of 10 exons located at 22q11.21. This gene was well known for its connections with psychiatric disorders (especially schizophrenia)911. Some recent studies have shown that this gene also contributed to bone related disorders. A 2014 study conducted by Gruber et al. has shown that SNP rs4633 of COMT was significantly associated with disc degeneration in a study sample of Europeans12. However, to the best of our knowledge, this finding has not been replicated in any other population and therefore studies based on populations other than Europeans are necessary to validate the significant hits identified by Gruber et al. In this study, we aimed to investigate the genetic association between the polymorphisms of COMT and the symptomatic LDH in a study sample comprised of 2,678 subjects with Chinese Han ancestry. The biological functions of significant SNPs were also examined by relevant bioinformatics tools. Our findings will validate the results of previous studies based on European populations and offer insights for unraveling the underlying mechanisms of COMT and its association with LDH.

Methods

Study Subjects

In our study, 875 patients with symptomatic LDH and 1,803 normal controls were recruited from Honghui Hospital of Xi’an Jiaotong University. The patients were diagnosed by positive magnetic resonance imaging (MRI) findings for symptomatic LDH with a history of unilateral pain radiating from the back along the femoral or sciatic nerve to the corresponding dermatome of the nerve root for more than 4 weeks at least. The exclusion criteria for the patients were as follows: (1) patients with mental illness or severe dysfunction of important organs (such as heart, lung, liver, or kidney); (2) patients with blood diseases, diabetes, autoimmune diseases, or tumors; and (3) patients with a body mass index (BMI) ≤ 18.5 kg/m2 or with a BMI ≥ 28 kg/m2. The controls with good health as confirmed by physical examination were enrolled, and they had a lifetime lack of symptoms indicating symptomatic LDH, such as lumbocrural pain. Subjects with osteoarthritis, rheumatism, connective tissue diseases, previous fractures of the spine, lumbar spinal stenosis, malignancies involving the spine and poliomyelitis were excluded from the study. Lumbar sagittal MRI was conducted by using a 1.5 Tesla Magnetom unit (Siemmens AG, Germany). A sagittal T2-weighted image with a slice thickness of 5 mm, a repetition of 2500 ms, and an echo time of 90 ms was applied for all subjects. The MRI diagnosis of LDH was based on the disk extended beyond the margins of adjacent vertebral bodies, which was confirmed by two observers at least. The disc degeneration was graded by using the Schneiderman classification (based on the signal intensity): grade 1, normal signal intensity; grade 2, slightly decreased signal intensity; grade 3, diffuse signal loss; grade 4, lack of signal. The clinical data and characteristics of all the subjects were measured or recorded (Table 1). We have collected informed consent with signature for all of our study subjects. All procedures were conducted in accordance with the ethical standards of the Helsinki Declaration of 1975, revised in 2008, and the study was reviewed and approved by the Medical Ethics Committee of Honghui Hospital of Xi’an Jiaotong University.

Table 1.

The clinical characteristics of the subjects.

Characteristics Subjects (N = 2,678) P-value
Cases (N = 875) Controls (N = 1,803)
Age (years), mean ± SD 44.7 ± 10.2 44.8 ± 9.9 0.84
Gender (male/female) 604/271 1248/555 0.96
BMI (kg/m2), mean ± SD 24.1 ± 0.83 24.0 ± 0.84 2.9 × 10−6
Family history (yes/no) 99/776 144/1659 0.006
Smoking history (yes/no) 201/674 409/1394 0.91
History of alcohol intake (yes/no) 125/750 255/1548 0.97
Grade of disc degeneration
2 248 NA NA
3 463 NA NA
4 164 NA NA

SD: standard deviation; BMI, body mass index; NA, not available. χ2 tests were performed for gender, family history, smoking history and history of alcohol intake, while t tests were conducted for age and BMI.

SNP Selection and Genotyping

We searched for all the SNPs with minor allele frequencies (MAF) ≥ 0.05 within the region of the COMT gene in the 1000 Genomes Project Chinese Han Beijing population database. Then, MAF ≥ 0.05 with pair-wise tagging and r2 ≥ 0.6 were used as the cut-off criteria during tag SNP selection, which generated 14 tag SNPs for our study. In addition, we also included SNP rs4680 as our candidate SNPs based on previous publications. Basic information on the 15 selected SNPs is summarized in Table 2. We have extracted the genomic DNA using the peripheral blood of our study subjects. The DNA extractions were conducted using Tiangen DNA extraction kit based on the protocol recommended by the manufacturer. Sequenom MassARRAY platform was utilized for SNP genotyping. The detected signals from MassARRAY platform were analyzed by software Typer 4.0 which was recommended by Sequenom13. About 5% of the sample was repeated for genotyping to estimate the quality of genotyping experiments. With a concordance rate of 100%, the quality of our genotyping data were guaranteed. Case control status of our study sample were blinded to the technicians during genotyping process.

Table 2.

Results of single marker based association analyses.

CHR SNP BP FUNC MAF HWE A1 OR T P
22 rs3788319 19942028 intron 0.41 0.62 G 1.01 0.13 0.90
22 rs8185002 19945525 intron 0.28 0.77 G 1.01 0.21 0.84
22 rs174673 19946255 intron 0.32 0.79 C 0.96 −0.58 0.56
22 rs9332331 19947460 intron 0.08 0.28 A 0.89 −1.05 0.29
22 rs9332334 19947625 intron 0.31 0.78 C 0.99 −0.15 0.88
22 rs76157168 19951186 intron 0.19 0.94 T 1.02 0.21 0.83
22 rs112080665 19951236 intron 0.11 0.64 G 1.05 0.51 0.61
22 rs5993887 19953138 intron 0.42 0.92 T 0.97 −0.53 0.60
22 rs165767 19957037 intron 0.34 0.83 A 1.02 0.25 0.80
22 rs11912354 19959824 intron 0.47 0.85 C 1.01 0.21 0.84
22 rs4633 19962712 coding-synon 0.27 0.86 T 0.76 −4.06 4.83 × 10 −5
22 rs4680 19963748 coding-nonsy 0.36 0.50 A 1.19 2.90 0.0037
22 rs4646315 19964374 intron 0.12 1.00 C 1.04 0.41 0.68
22 rs165737 19964978 intron 0.20 0.88 T 0.99 −0.19 0.85
22 rs165728 19969500 intron 0.35 0.76 C 0.99 −0.24 0.81

HWE: P values of Hardy-Weinberg Equilibrium tests.; A1: Tested allele. Significant SNP was shown in bold.

Statistical Analysis

Single marker based genetic association analyses were performed for each SNP using logistic models. According to the results from Table 1, we have included BMI as covariates in the logistic models. Bonferroni corrections were applied to address multiple comparison (Pthreshold = 0.05/15 ≈ 0.0033). Plink was utilized for single marker based analysis. Q-Q plot was made to examine the potential inflation for the significance of the P values caused by population stratifications. In addition to single marker based analyses, we also constructed LD blocks using our data and performed haplotypic analyses. Haploview was utilized for these analyses. In addition to the genetic association analyses, we have also conducted an association analysis for symptomatic LDH cases only to investigate the potential link between targeted SNPs and the disc degeneration.

Bioinformatics Analysis

To further examine the potential functional significance of those significant hits in genetic association analysis, we performed bioinformatics analyses through online databases. Significant SNPs identified in genetic association analyses were checked in RegulomeDB (http://regulomedb.org/). RegulomeDB is an online tool to predict the potential functional significance of SNPs by integrating Encode data. It returns a score, which ranges from 1 to 6, to label the regulatory function of the SNPs regarding the gene expression and translation. In addition, we have also investigated the potential effects of targeted SNPs on COMT gene expression in multiple human tissues using the GTEx database (https://www.gtexportal.org/home/).

Results

Significant hits in genetic association analyses

The clinical characteristics of the study subjects are summarized in Table 1. Significant differences in body mass index (BMI) can be identified for symptomatic LDH patients and controls. All the selected 15 SNPs were in Hardy-Weinberg equilibrium in our control sample. A synonymous coding SNP, rs4633, was identified to be significantly associated with the disease status of symptomatic LDH after adjusting for BMI (OR = 0.76, P = 4.83 × 10−5, Table 2). No signs of inflation caused by population stratification can be identified from the Q-Q plot for the results of the single marker-based association analyses (Supplemental Fig. S1).

A total of 4 linkage disequilibrium (LD) blocks were constructed based on our data (Supplemental Fig. S2). Haplotypic association analyses were performed for these LD blocks and have validated the results of the single marker based analyses. A 3-SNP haplotype, which included the SNP rs4633, was identified to be significantly associated with symptomatic LDH (rs4633|rs4680|rs4646315, P = 2.23 × 10−28, Table 3). No significant association can be identified between rs4633 and the disc degeneration using the data of symptomatic LDH patients only (χ2 = 5.99, P = 0.1999, Supplemental Table S1).

Table 3.

Results of haplotype based analysis.

LOCUS HAPLOTYPE F_A F_U CHISQ DF P SNPs
H1 OMNIBUS 0.19 2 0.91 rs3788319|rs8185002
H1 GG 0.28 0.27 0.06 1 0.81 rs3788319|rs8185002
H1 GT 0.14 0.13 0.09 1 0.76 rs3788319|rs8185002
H1 AT 0.59 0.59 0.18 1 0.67 rs3788319|rs8185002
H2 OMNIBUS 1.03 2 0.60 rs5993887|rs165767
H2 TA 0.34 0.33 0.03 1 0.86 rs5993887|rs165767
H2 TG 0.08 0.08 1.03 1 0.31 rs5993887|rs165767
H2 CG 0.59 0.58 0.16 1 0.69 rs5993887|rs165767
H3 OMNIBUS 131.8 3 2.23 × 10 −28 rs4633|rs4680|rs4646315
H3 TAC 0.12 0.12 0.00 1 0.96 rs4633|rs4680|rs4646315
H3 TAG 0.11 0.16 28.45 1 9.62 × 10 −8 rs4633|rs4680|rs4646315
H3 CAG 0.16 0.07 116.21 1 4.36 × 10 −27 rs4633|rs4680|rs4646315
H3 CGG 0.61 0.65 7.86 1 0.005 rs4633|rs4680|rs4646315
H4 OMNIBUS 0.20 2 0.91 rs165737|rs165728
H4 TC 0.19 0.20 0.20 1 0.66 rs165737|rs165728
H4 CC 0.16 0.16 0.02 1 0.89 rs165737|rs165728
H4 CT 0.65 0.64 0.07 1 0.79 rs165737|rs165728

Significant results were highlighted in bold. F_A: frequency in cases; F_U: frequency in controls; DF: degree of freedom.

RegulomeDB score and eQTL results from GTEx

The regulomeDB score for rs4633 is 2b, which indicates that this SNP has a relatively significant regulatory function on gene expression and translation of COMT. According to the records of regulomeDB, this SNP located at a DNase I hypersensitivity region based on the data of 125 cell types from ENCODE. In addition, the location of this SNP belongs to a transcription factor binding motif and is an important protein binding site for multiple human proteins.

The eQTL data of rs4633 in 47 human tissues were extracted from the GTEx database. The SNP rs4633 was identified to be significant (Pthreshold = 0.05/47 ≈ 0.001) in three types of human tissues (Fig. 1): the mucosa of the esophagus, the skin of lower leg (sun exposed) and the skin of suprapubic (non-exposed for sun). Minor alleles of rs4633 (T) increased the expression of COMT in all 3 tissues (Supplemental Fig. S3).

Figure 1.

Figure 1

eQTL data of COMT for rs4633 in multiple human tissues. Data were extracted from GTEx database. P value threshold obtained through bonferroni correction was indicated by red dotted line.

Discussion

Catechol-O-methyltransferase, which is encoded by COMT, is a major mammalian enzyme involved in the degradation of catecholamines. It assists the process of transferring a methyl group from S-adenosyl-methionine to a hydroxyl group on a catechol nucleus14. In recent years, candidate gene studies have successfully identified many susceptible loci for complex diseases1521. Because of its molecular biological function, which is related to multiple neurotransmitters, a significant number of previous studies have tried to identify its susceptibility to brain related disorders, such as schizophrenia911, anorexia nervosa22 and mental retardation23. Unlike these brain-related disorders, very limited studies have tried to establish the link between COMT and human bone-related disorders. In a 2007 study conducted by Stolk et al., SNP rs4680 of COMT was identified to be significantly associated with osteoporotic and fragility fracture risk in European men after adjusting for age, height, weight, and bone mineral density (BMD)24. Two other studies have reported significant associations between polymorphisms of COMT and the treatment outcome of lumbar degenerative disc disease and low back pain2527. SNP rs4633, the same SNP identified to be significant in our study, has been reported to be related to disc degeneration in a 2014 study conducted by Gruber et al.12. Considering that only SNPs analyses are not sufficient to reach a reliable conclusion2832, we have further analyzed the haplotype, of which the results are similar with that of SNPs analyses. To the best of our knowledge, this study is the first one to establish the link between symptomatic LDH and polymorphisms of COMT in the Chinese population. We have successfully replicated the results reported by Gruber et al. using sample from different populations. Unlike the brain related disorders, which have a clear connection with the biological function of Catechol-O-methyltransferase, its connection with bone related disorders has not been clearly established. More studies focusing on pathological mechanisms of LDH and disc degeneration are needed in the future.

The significant SNP identified in our study, rs4633, is a synonymous coding variant. Our bioinformatics analysis using regulomeDB has shown that it might have significant regulatory function on the gene expression of COMT. Further eQTL data from GTEx also provides some evidence on its role in the expression of COMT. Nevertheless, it is still too early to conclude that rs4633 is a genetic polymorphism that contributes directly to the risk of LDH (but not a surrogate of some underlying variant(s)). An interesting observation is that most of the previous association studies targeting COMT (including both brain-related disorders and bone-related disorders) have reported rs4680 (also referred as Val-158-Met), but not rs4633, to be a significant hit. Unlike rs4633, rs4680 is a non-synonymous coding variant, which will cause a change in the amino acid gene product of COMT. However, in the study conducted by Gruber et al., although both rs4680 and rs4633 were genotyped, only rs4633 was found to be significantly associated with disc degeneration. The explanation for this discordance is unknown. In our study, only rs4633 was identified to be significantly associated with LDH, which supported findings from the study of Gruber et al.

One important thing to note is that the P values of single SNP associations in Table 2 were much weaker than the P values of haplotype analysis in Table 3. The results suggested that the association signal may be contributed by haplotypes rather than single SNP. If we only considered the two functional SNPs, rs4633 and rs4680, in this haplotype, we could find that the global association was driven by haplotype CA. There is a possible explanation for that in potential molecular effects of these SNPs. Furthermore, we could hypothesize that both A allele of rs4680 and C allele of rs4633 are related to the low protein abundance of COMT and in turn will affect the activity of COMT, which have been reported in a previous study33. Give of the lack of direct supportive biological evidence in our study, the hypothesis would be desired to verify in the future study.

A potential limitation for our study is that the SNPs selected for genotyping might not provide enough information on the coverage of COMT. There are approximately 2,000 variants located within the COMT gene regions, and even if we considered the LD pattern of the SNPs, 15 SNPs are not enough to represent a very limited number of SNPs. In addition, all our selected SNPs were located within the gene region of COMT. However, the evidence has shown that the genomic regions located several kbs up/down-stream of the targeted gene might have important regulatory effects. Failing to consider variants of these regions might miss important genetic signals for LDH susceptibility. Therefore, additional studies with more SNPs and rare/low frequency variants based on targeted sequencing are needed to conclude that COMT is involved in pathological process of LDH. Another potential limitation is that our selection strategy for study subjects might introduce bias for this study. The prevalence of LDH in the asymptomatic population is high, but asymptomatic LDH patients hardly go to the hospital for diagnosis and treatment, which also makes it more difficult for us to recruit the asymptomatic LDH patients. Therefore, in this study, we only focus on symptomatic LDH patients. It is also partly uncertain whether our results are applicable to the general population. Our data are of the interest harboring further etiological and genetic study of LDH. However, given that the development of LDH is an extremely complex pathophysiology process involving many genes and factors, further studies are necessary to confirm our results.

In summary, in this study, we have identified a significant SNP of COMT, rs4633, that is associated with the disease status of symptomatic LDH in a large Han Chinese-based sample of study subjects. This significant finding is further replicated by haplotypic analysis. Evidence from the bioinformatic analyses have shown that rs4633 is also significantly associated with the gene expression of COMT. More studies focusing on the pathological mechanisms of LDH and COMT are still needed in the future to unravel the role that COMT and its gene products played in the onset and development of LDH.

Electronic supplementary material

Supplementary materials (191.9KB, docx)

Author Contributions

Authors Liu H.L. and Ma W. conceived and designed the study. Liu H.L. and Zhao H.M. carried out candidate SNPs selection and statistical analyses. Zhao H.M., Li Z. and Xue H.Z. conducted subject screening and contributed to the collection and preparation of control DNA samples. Liu H.L. and Lu J. wrote the paper.

Competing Interests

The authors declare no competing interests.

Footnotes

Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Jun Lu, Email: junluhh@163.com.

Wei Ma, Email: mawwei60@163.com.

Electronic supplementary material

Supplementary information accompanies this paper at 10.1038/s41598-018-31240-9.

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