Int J Pharm Pharm Sci, Vol 8, Issue 7, 73-80Original Article


118A>G AND IVS2+691G>C POLYMORPHISMS OF OPRM1 GENE HAVE NO INFLUENCE ON COLD-PAIN SENSITIVITY AMONG HEALTHY OPIOID-NAIVE MALAY MALES

ZALINA ZAHARI1,2*, LEE CHEE SIONG3, LEE YEONG YEH4, MUSLIH ABDULKARIM IBRAHIM2,5, NURFADHLINA MUSA2, MD AZHAR MOHD YASIN2,6, TAN SOO CHOON2, NASIR MOHAMAD2,7, RUSLI ISMAIL2,8

1Department of Pharmacy, Hospital Universiti Sains Malaysia, Kubang Kerian, Kelantan, Malaysia, 2Pharmacogenetics and Novel Therapeutics Cluster, Institute for Research in Molecular Medicine (INFORMM), Universiti Sains Malaysia (USM), Kubang Kerian, Kelantan, Malaysia, 3Department of Emergency Medicine, School of Medical Sciences, Universiti Sains Malaysia (USM), Kubang Kerian, Kelantan, Malaysia, 4School of Medical Sciences, Universiti Sains Malaysia (USM), Kubang Kerian, Kelantan, Malaysia, 5Department of Pharmacology and Toxicology, College of Pharmacy, Hawler Medical University, Hawler, Iraq, 6Department of Psychiatry, School of Medical Sciences, Universiti Sains Malaysia (USM), Kubang Kerian, Kelantan, Malaysia, 7Faculty of Medicine & Health Sciences, Universiti Sultan Zainal Abidin, Kuala Terengganu, Terengganu, Malaysia, 8Centre of Excellence for Research in AIDS (CERiA), University of Malaya, Kuala Lumpur, Malaysia.
Email: zzalina@usm.my   
 

 Received: 23 Dec 2015 Revised and Accepted: 17 May 2016


ABSTRACT

Objective: Common polymorphisms of the mu-type opioid receptor (OPRM1) including 118A>G and IVS2+691G>C may affect experimental pain responses in healthy subjects, and the effect could be ethnic-dependent. The aim of this study was to investigate the influence of these OPRM1 polymorphisms on cold-pressor pain responses among healthy opioid-naive Malay males.

Methods: Pain-threshold, pain-tolerance, and pain-intensity in response to the cold pressor test (CPT) were measured in healthy opioid-naive Malay males. DNA was extracted from the collected venous blood before PCR-genotyping. Repeated measure analysis of variance (RM-ANOVA) was used to compare CPT responses and OPRM1 polymorphisms (118A>G and IVS2+691G>C) according to their genotypes and allelic additive models, genotype dominant and recessive models, haplotypes, and diplotypes.

Results: A total of 152 participants were recruited. Both 118A>G and IVS2+691G>C polymorphisms were not associated with cold-pressor pain-threshold, pain-tolerance and pain-intensity despite using genotypes and allelic additive models and genotype dominant and recessive models (all p>0.05). Likewise, there were no significant associations between haplotypes and diplotypes for the 118A>G and IVS2+691G>C polymorphisms and the three cold-pain responses (all p>0.05).

Conclusion: The common OPRM1 polymorphisms (i.e., 118A>G and IVS2+691G>C), are not associated with cold-pressor pain responses in healthy opioid-naive Malay males. However, this may be unique for this particular ethnicity. Other polymorphisms may be more relevant for this population, and this should be further investigated.

Keywords: Cold pressor test (CPT), Mu-type opioid receptor (OPRM1), Opioid receptor, mu 1 gene (OPRM1), Pain-threshold, Pain-tolerance, Pain-intensity, Opioid-naive, Male, Malays


INTRODUCTION

The mu-type opioid receptor (OPRM1) is a major opioid receptor in human. Together with the δ-opioid receptor (DOR) and κ-opioid receptor (KOR), they are the binding sites for endogenous opioid peptides [1, 2] and exogenous opioids, including methadone [3]. Studies have shown that activation of the OPRM1 system was associated with reductions in the sensory and affective ratings of pain experience [4]. Variability in pain modulation and inter-individual differences in treatment outcomes with opioid-based analgesic therapy may be a result of variations in the OPRM1 gene [5-12]. A previous study in healthy males found that a low OPRM1 binding potential in the striatum was associated with a low cold pain-threshold [13]. Thus, it is hypothesized that individuals with low OPRM1 binding potential have low receptor density, and consequently, low level of OPRM1-mediated suppression of pain pathways, leading to increased experimental pain sensitivity [13].

The 118A>G polymorphism being the most common variation of the OPRM1 gene is found to exert influences on experimental pain responses in healthy subjects [14, 15] but the effect may be ethnic-dependent [16]. Individuals with 118G allele but not the wild-type allele exhibited lower sensitivity to pressure pain (or higher pressure pain-threshold) [14]. Other less common but important polymorphisms of the OPRM1 gene have included IVS2+31G>A (dbSNP rs9479757) and IVS2+691G>C (dbSNP rs2075572). While IVS2+31G>A polymorphism was associated with a higher pressure pain-threshold in healthy adult females [17] but IVS2+691G>C polymorphism has not been previously studied.

Southeast Asia is a highly populated and culturally diverse region with ethnic Malays consisted the largest population group, mainly populating countries including Malaysia, Indonesia and southern part of the Philippines. Males of ethnic Malays consisted the majority of opioid-dependent patients on methadone treatment in Malaysia, but it is not known whether OPRM1 polymorphisms influence the inter-individual variations in pain responses. The current study aimed to investigate the influence of common OPRM1 polymorphisms (i.e., 118A>G and IVS2+691G>C) on cold-pressor pain responses among healthy opioid-naive Malay males. Results of this study would be helpful to determine whether these polymorphisms are suitable for further studies in opioid-dependent patients.

MATERIALS AND METHODS

Study participants

Participants comprised 152 opioid-naive Malay males between 18 and 63 y of age (mean = 27.46 y). They were randomly sampled from within the hospital compound. The participants consisted of staffs and students. Written informed consents were obtained from each participant prior to enrolment. This study was part of a larger study to investigate the genetic factors that may influence cold-pressor pain responses in opioid-dependent patients on methadone treatment (National Medical Research Register (NMRR) number: NMRR-13-524-16614). It was approved by the Human Research Ethics Committee (HREC), Universiti Sains Malaysia (USM) in Kelantan, Malaysia (Reference number: USMKK/PPP/JEPeM (253.3) [14].

Assessment of study participants

Urine drug screens for morphine, tetra-hydrocannabinol, amphetamines and benzodiazepines using drugs of abuse rapid test, F. A. C. T. S TM 4 in 1 Combo Dipcard Rapid Test (MOR/ THC/ AMP/BZO) (Scientifacts Sdn. Bhd., Malaysia) were performed for each participant twice in one week prior to CPT. Only subjects with two consecutive negative urine tests were allowed to continue with the study. A history of analgesics consumption within 72 h prior to study entry and a positive history of any painful conditions were exclusion criteria. Subjects with any known acute or chronic medical, surgical and psychiatric illnesses that required concurrent medical, surgical or psychiatric therapy and severe cognitive impairment which might interfere with pain assessments and/or communication were also excluded from the study.

Cold pressor test (CPT)

The CPT method utilized in the current study was adapted from Chen et al. (1989) and Compton et al. (2001) and had been described else where [20]. Briefly, the CPT apparatus consisted of a 48-quart cool box filled with a mixture of two-thirds crushed ice and one-third tap water. A constant temperature of 0–2 °C was maintained by adding ice intermittently. The non-dominant hand and forearm of the participant would be placed in the ice bath with their palm flat at the bottom of the box, with ice water covered the hand and approximately 10 cm of the forearm. The test was truncated at 300 s, since after this time, the numbness would set in and the pain diminished [19, 21, 22]. Pain-threshold was defined as the first experience of pain that can be identified, pain-tolerance as the time elapsed when the participant had to withdrew his hand (i.e., the most severe pain that a subject was willing to tolerate) and pain-intensity as the maximal pain experienced during test on a visual analogue scale (VAS; 0–100). We examined the cold-pressor responses six times over a 24 h period [i.e., at 0 h (at about 8.00 am), and at 2, 4, 8, 12, and 24 h after the first CPT], in order to minimise the possible diurnal variations in cold-pressor pain response [23].

PCR genotyping for 118A>G, IVS2+31G>A and IVS2+691G>C polymorphisms of OPRM1

Venous blood (2.5 ml) samples for genotyping were collected in tubes containing sodium citrate and the blood samples were stored at–20 °C until further processing. Genomic DNA was extracted from the unclotted venous blood using QIAampâ DNA Blood Mini Kit (Qiagen Gmbh, Hilden, Germany) according to the manufacturer’s instructions. The quantity and quality of the extracted genomic DNA were determined on the NanoDropâND-1000 Spectrophotometer (NanoDropTechnologies, Inc. Wilmington, USA) with measurements performed at 260 and 280 nm.

A two-step PCR method for simultaneous OPRM1 and CYP2B6 genotyping were developed by the Institute for Research in Molecular Medicine (INFORMM) and this had been validated for reproducibility and specificity through direct sequencing [24]. All PCR reactions were performed in standard 0.2 ml Eppendorf PCR tubes and carried out in a volume of 25 ml comprising buffer [10 mM Tris-HCl (pH 8.0), 50 mM KCl, 1 mM EDTA, 0.1% Triton X-100, 50.0% glycerol (v/v)]. The reactions were performed on the Applied Biosystemsâ Veritiâ 96-Well Thermal Cycler (Applied Biosystems, Carlsbad, CA, USA).

Briefly, the first step PCR (‘Set A’) was performed using specifically designed primers (table 1) to isolate out regions of interest that contain the relevant OPRM1 polymorphisms (118A>G, IVS2+31G>A and IVS2+691G>C) that were later used for the second allele-specific PCR to avoid amplifications of similar sequences in the human genome that may be located outside the gene. PCR reaction mixture for Set A contained 1.0 U of Biotoolâ DNA Taq Polymerase (Biotools, Biotechnological & Medical Laboratories, SA, Madrid, Spain), 2.0 mM MgCl2, 0.2 mM dNTPs (Biotools, Biotechnological & Medical Laboratories, SA, Madrid, Spain) and 0.10–0.25 µM of the primers (Invitrogen, Waltham, MA, USA). The cycling conditions were optimized for Set A. Ten microliters of the first PCR products of Set A were analyzed using 2.0% agarose gel (Promega Corporation, Madison, WI, USA) and 1 x TBE (Tris, Borate, EDTA) at 100 V for 60 min. Two microliters of the diluted first step PCR products of Set A were used as a template for detection of wild-type or mutant-type alleles in second step PCR.  The second step PCR reaction was carried out using identical reaction mixture described for the first step PCR, with the exceptions of primer concentrations shown in table 1. The cycling conditions were again optimized and ten microliters of the second PCR products were again analyzed using 2.0% agarose gel (Promega Corporation, Madison, WI, USA) and 1 x TBE at 100 V for 60 min.

Data and statistical analysis

The sample size was calculated prior to recruitment based on the Cohen sample size table [25], using medium population effect size (ES) at the power of 0.80 for an α value of 0.05. Samples of 64 alleles or subjects per group were required for comparisons of means of two groups (under the allelic additive model, genotype dominant and recessive model).

Genotyping data were analyzed using the population genetic data analytical program, Golden Helix SNP and Variation Suite 7 (SVS 7, version 7.3.1; Golden Helix Inc., Bozeman, MT, USA) based on an expectation-maximization (EM) algorithm for the following procedures: (a) the calculation of OPRM1 alleles and genotypes frequencies; (b) the estimation of heterozygosity in each polymorphism in Hardy-Weinberg proportion; (c) the estimation of maximum-likelihood haplotype frequency.

Table 1: OPRM1 primers used for allele-specific multiplex PCR of OPRM1 118A>G (dbSNP rs1799971), IVS2+31G>A (dbSNP rs9479757) and IVS2+691G>C (dbSNP rs2075572)

PCR

Primer

Sequence (5’–3’)

Fragment size (bp)

[Primer] (mM)

First PCR Set A

m EX1 FW

aaa gtc tcg gtg ctc ctg gct

420

0.10

m EX1 RV

tgg gag tta ggt gtc tct ttg ta

0.10

m INT2 FW

tag att tcc gta ctc ccc gaa

1020

0.20

m INT2 RV

cgc aag atc atc agt cca tag

0.20

Second PCR Set 1

Common primer

m EX1 RV

tgg gag tta ggt gtc tct ttg ta

0.25

Wild-type primers

m 118 A FW

caa ctt gtc cca ctt aga tgg ca

267

0.25

Mutant-type primers

m 118 G FW

caa ctt gtc cca ctt aga tgg cg

0.25

Second PCR Set 2

Common primer

m INT2 RV

cgc aag atc atc agt cca tag

0.15

Wild-type primers

m 691G FW

gct ctg gtc aag gct aaa aat g

240

0.15

Mutant-type primers

m 691C FW

gct ctg gtc aag gct aaa aat c

0.15

Second PCR Set 3

Common primer

m INT2 FW

tag att tcc gta ctc ccc gaa

0.25

Wild-type primers

m 31G RV

aac ata tca ggc tgt gaa ccc

162

0.25

Mutant-type primers

m 31A RV

aac ata tca ggc tgt gaa cct

0.25


RESULTS

Distributions of OPRM1 polymorphisms

The 118A/G, IVS2+31G>A and IVS2+691G>C allele of OPRM1 gene were successfully amplified from all 152 subjects. Genotyping analysis revealed that one subject possessed polymorphism in the IVS2+31 locus of the OPRM1 gene (table 2). The genotype at the locus was heterozygous for IVS2+31A allele (IVS2+31G>A). The distribution of OPRM1 118A>G, IVS2+31G>A and IVS2+691G>C genotypes were in Hardy-Weinberg equilibrium (HWE) (p>0.129). Assuming a mutant-type allele was a high-risk allele, genotype frequencies under the dominant and recessive models were determined. The most likely haplotype pair or diplotype in each individual was estimated and the haplotype frequency distributions were obtained with an expectation-maximum (EM) algorithm (table 2).

The lack of associations of 118A>G and IVS2+691G>C polymorphisms with pain sensitivity

Due to low frequency of IVS2+31G>A polymorphism in the current study samples, further, analyses were not performed for this polymorphism, and thus, haplotype patterns were constructed from the two polymorphisms of OPRM1 (118A>G and IVS2+ 691G>C).

The 118A>G and IVS2+691G>C polymorphisms were not associated with pain-threshold, pain-tolerance and pain-intensity despite using genotypes and allelic additive models and genotype dominant and recessive models (all p>0.05) (table 3, 4 and 5). Likewise, there were no significant associations between haplotypes and diplotypes for the 118A>G and IVS2+691G>C polymorphisms and the three cold-pain responses (all p>0.05) (table 3, 4 and 5

Table 2: Allele, genotype, haplotype and diplotype distributions for the three screened polymorphisms of OPRM1 in opioid-naive Malay males

Polymorphism

 

N

Frequency (%)

95% CI of frequency

HWE p value

 

 

 

 

Lower limit

Upper limit

 

118A>G

Genotype (N = 152)

AA

35

23.0

16.3

29.7

0.748

AG

74

48.7

40.8

56.6

GG

43

28.3

21.1

35.5

Allele (N = 304)

A

144

47.4

41.8

53.0

G

160

52.6

47.0

58.2

Dominant model

AA

35

23.0

16.3

29.7

AG+GG

117

77.0

70.3

83.7

Recessive model

AA+AG

109

71.7

64.5

78.9

GG

43

28.3

21.1

35.5

IVS2+691G>C

Genotype (N = 152)

GG

1

0.7

0.0

2.0

0.129

GC

45

29.6

22.3

36.9

CC

106

69.7

62.4

77.0

Allele (N = 304)

G

47

15.5

11.4

19.6

C

257

84.5

80.4

88.6

Dominant model

GG

1

0.7

0.0

2.0

GC+CC

151

99.3

98.0

100.0

Recessive model

GG+GC

46

30.3

23.0

37.6

CC

106

69.7

62.4

77.0

IVS2+31G>A

Genotype (N = 152)

GG

151

99.3

98.0

100.0

1.000

GA

1

0.7

0.0

2.0

AA

0

0.0

0.0

0.0

Allele (N = 304)

G

303

99.7

99.1

100.0

A

1

0.3

0.0

0.9

Dominant model

GG

151

99.3

98.0

100.0

GA+AA

1

0.7

0.0

2.0

Recessive model

GG+GA

152

100.0

100.0

100.0

AA

0

0.0

0.0

0.0

Haplotype (N = 304)a

  1.  

GCG

158

52.0

46.4

57.6

  1.  

ACG

99

32.6

27.3

37.9

  1.  

AGG

44

14.5

10.5

18.5

  1.  

GGG

2

0.7

0.0

1.6

  1.  

AGA

1

0.3

0.0

0.9

Diplotype (N = 152)

  1.  

ACG/GCG

51

33.6

26.1

41.1

  1.  

GCG/GCG

41

27.0

19.9

34.1

  1.  

GCG/AGG

23

15.1

9.4

20.8

  1.  

ACG/AGG

19

12.5

7.2

17.8

  1.  

ACG/ACG

14

9.2

4.6

13.8

  1.  

GCG/GGG

2

1.3

0.0

3.1

  1.  

AGA/ACG

1

0.7

0.0

2.0

  1.  

AGG/AGG

1

0.7

0.0

2.0

N, number of subject/allele/haplotype/diplotype; CI, confidence interval; HWE, Hardy-Weinberg equilibrium, aHaplotype patterns were constructed from the three screened polymorphisms of OPRM1 (118A>G, IVS2+691G>C and IVS2+31G>A)


Table 3: Influences of 118A>G and IVS2+691G>C polymorphisms on pain-threshold in opioid-naive Malay males

Polymorphism

N

Mean#

95% CI

F-stat. (df)a

p value*

 

 

 

Lower limit

Upper limit

 

 

118A>G

Genotype (N = 152)

AA

35

62.40

40.83

83.98

0.73 (2)

0.483

AG

74

48.88

34.05

63.72

GG

43

45.69

26.22

65.15

Allele (N = 304)

A

144

55.46

44.91

66.01

1.26 (1)

0.263

G

160

47.16

37.15

57.17

Dominant model

AA

35

62.40

40.90

83.91

1.40 (1)

0.238

AG+GG

117

47.71

35.95

59.47

Recessive model

AA+AG

109

53.22

41.00

65.45

0.42 (1)

0.518

GG

43

45.69

26.22

65.15

IVS2+691G>C

Genotype (N = 152)

GG

1

20.90

-107.10

148.89

0.29 (2)

0.747

GC

45

46.40

27.32

65.48

CC

106

53.37

40.93

65.80

Allele (N = 304)

G

47

45.32

26.83

63.81

0.45 (1)

0.504

C

257

52.15

44.24

60.06

Dominant model

GG

1

20.90

-106.82

148.61

0.22 (1)

0.640

GC+CC

151

51.29

40.90

61.68

Recessive model

GG+GC

46

45.85

27.03

64.67

0.43 (1)

0.511

CC

106

53.37

40.97

65.76

Haplotype (N = 304)b

GC

158

47.40

37.32

57.48

0.94 (3)

0.422

AC

99

59.73

46.99

72.46

AG

45

46.06

27.18

64.95

GG

2

28.55

-61.04

118.14

GC

158

47.40

37.33

57.46

1.34 (2)

0.263

AC

99

59.73

47.01

72.44

Combined AG and GG

47

45.32

26.86

63.77

GC

158

47.40

37.32

57.47

1.08 (1)

0.299

Not GC

146

55.09

44.61

65.57

AC

99

59.73

47.03

72.42

2.66 (1)

0.104

Not AC

205

46.92

38.10

55.74

AG

45

46.06

27.16

64.96

0.32 (1)

0.571

Not AG

259

51.97

44.09

59.84

Diplotype (N = 152)

AC/GC

51

55.81

37.92

73.71

0.76 (4)

0.554

GC/GC

41

46.52

26.56

66.48

GC/AG

23

33.51

6.86

60.16

AC/AG

20

63.01

34.43

91.59

Othersc

17

57.71

26.71

88.71

AC/GC

51

55.81

37.94

73.69

0.41 (1)

0.523

Not AC/GC

101

48.71

36.01

61.41

GC/GC

41

46.52

26.58

66.46

0.28 (1)

0.597

Not GC/GC

111

52.78

40.66

64.90

GC/AG

23

33.51

7.04

59.98

2.03 (1)

0.156

Not GC/AG

129

54.23

43.05

65.40

AC/AG

20

63.01

34.51

91.52

0.79 (1)

0.377

Not AC/AG

132

49.29

38.19

60.38

N, number of subject/allele/haplotype/diplotype; CI, confidence interval, # Means for cold pain-threshold (seconds); * p-value is significant at<0.05, aRepeated measured ANOVA between-group analysis was applied, bHaplotype patterns were constructed from the two polymorphisms of OPRM1 (118A>G and IVS2+691G>C), cDiplotype with frequency less than 10.0% were pooled under ‘Others’ (included AC/AC, GC/GG, AG/AG)


Table 4: Influences of 118A>G and IVS2+691G>C polymorphisms on pain-tolerance in opioid-naive Malay males

Polymorphism

N

Mean#

95% CI

F-stat. (df)a

p value*

 

 

 

Lower limit

Upper limit

 

 

118A>G

Genotype (N = 152)

AA

35

73.92

50.24

97.60

0.72 (2)

0.491

AG

74

57.35

41.06

73.63

GG

43

58.02

36.66

79.39

Allele (N = 304)

A

144

65.40

53.82

76.99

0.90 (1)

0.344

G

160

57.71

46.72

68.70

Dominant model

AA

35

73.92

50.32

97.52

1.44 (1)

0.232

AG+GG

117

57.60

44.69

70.51

Recessive model

AA+AG

109

62.67

49.24

76.10

0.13 (1)

0.717

GG

43

58.02

36.64

79.41

IVS2+691G>C

Genotype (N = 152)

GG

1

29.11

-111.47

169.68

0.20 (2)

0.817

GC

45

57.62

36.66

78.57

CC

106

63.25

49.59

76.90

Allele (N = 304)

G

47

56.41

36.10

76.71

0.27 (1)

0.602

C

257

62.26

53.58

70.94

Dominant model

GG

1

29.11

-111.09

169.30

0.21 (1)

0.649

GC+CC

151

61.57

50.16

72.98

Recessive model

GG+GC

46

57.00

36.33

77.67

0.25 (1)

0.619

CC

106

63.25

49.63

76.86

Haplotype (N = 304)b

GC

158

57.98

46.90

69.06

0.65 (3)

0.586

AC

99

69.09

55.10

83.09

AG

45

57.28

36.52

78.05

GG

2

36.63

-61.85

135.11

GC

158

57.98

46.91

69.04

0.89 (2)

0.412

AC

99

69.09

55.12

83.07

Combined AG and GG

47

56.40

36.12

76.69

GC

158

57.98

46.91

69.04

0.75 (1)

0.387

Not GC

146

65.01

53.50

76.52

AC

99

69.09

55.14

83.05

1.77 (1)

0.185

Not AC

205

57.62

47.92

67.32

AG

45

57.28

36.53

78.04

0.17 (1)

0.676

Not AG

259

62.06

53.41

70.71

Diplotype (N = 152)

AC/GC

51

63.93

44.27

83.60

0.68 (4)

0.609

GC/GC

41

59.07

37.13

81.00

GC/AG

23

42.75

13.46

72.03

AC/AG

20

76.82

45.42

108.23

Othersc

17

66.12

32.05

100.18

AC/GC

51

63.93

44.30

83.57

0.10 (1)

0.751

Not AC/GC

101

60.05

46.10

74.01

GC/GC

41

59.07

37.16

80.97

0.06 (1)

0.810

Not GC/GC

111

62.20

48.89

75.51

GC/AG

23

42.75

13.67

71.82

1.89 (1)

0.172

Not GC/AG

129

64.67

52.40

76.95

AC/AG

20

76.82

45.57

108.08

1.10 (1)

0.296

Not AC/AG

132

59.01

46.85

71.18

N, number of subject/allele/haplotype/diplotype; CI, confidence interval, # Means for cold pain-tolerance (seconds); * p-value is significant at<0.05, aRepeated measured ANOVA between-group analysis was applied, bHaplotype patterns were constructed from the two polymorphisms of OPRM1 (118A>G and IVS2+691G>C), cDiplotype with frequency less than 10.0% were pooled under ‘Others’ (included AC/AC, GC/GG, AG/AG)


Table 5: Influences of 118A>G and IVS2+691G>C polymorphisms on pain-intensity scores in opioid-naive Malay males

Polymorphism

N

Mean#

95% CI

F-stat. (df)a

p value*

 

 

 

Lower limit

Upper limit

 

 

118A>G

Genotype (N = 152)

AA

35

65.24

60.55

69.93

0.79 (2)

0.457

AG

74

65.05

61.82

68.27

GG

43

61.94

57.71

66.17

Allele (N = 304)

A

144

65.14

62.84

67.43

1.20 (1)

0.274

G

160

63.38

61.20

65.55

Dominant model

AA

35

65.24

60.54

69.93

0.24 (1)

0.623

AG+GG

117

63.90

61.33

66.47

Recessive model

AA+AG

109

65.11

62.46

67.76

1.58 (1)

0.211

GG

43

61.94

57.72

66.16

IVS2+691G>C

Genotype (N = 152)

GG

1

66.67

38.77

94.56

0.02 (2)

0.984

GC

45

64.11

59.95

68.27

CC

106

64.23

61.52

66.94

Allele (N = 304)

G

47

64.22

60.19

68.25

0.00 (1)

0.996

C

257

64.21

62.49

65.93

Dominant model

GG

1

66.67

38.86

94.47

0.03 (1)

0.861

GC+CC

151

64.19

61.93

66.46

Recessive model

GG+GC

46

64.17

60.07

68.27

0.00 (1)

0.980

CC

106

64.23

61.53

66.93

Haplotypeb (N = 304)

GC

158

63.52

61.33

65.72

0.89 (3)

0.448

AC

99

65.30

62.53

68.07

AG

45

64.78

60.67

68.89

GG

2

51.67

32.17

71.16

GC

158

63.52

61.33

65.72

0.49 (1)

0.613

AC

99

65.30

62.53

68.08

Combined AG and GG

47

64.22

60.19

68.25

GC

158

63.52

61.33

65.72

0.79 (1)

0.374

Not GC

146

64.95

62.67

67.24

AC

99

65.30

62.53

68.07

0.89 (1)

0.345

Not AC

205

63.68

61.76

65.61

AG

45

64.78

60.66

68.89

0.09 (1)

0.769

Not AG

259

64.11

62.40

65.83

Diplotype (N = 152)

AC/GC

51

65.10

61.18

69.02

0.23 (4)

0.922

GC/GC

41

62.44

58.07

66.81

GC/AG

23

64.93

59.09

70.77

AC/AG

20

64.42

58.15

70.68

Othersc

17

64.61

57.82

71.40

AC/GC

51

65.10

61.21

68.99

0.31 (1)

0.581

Not AC/GC

101

63.76

61.00

66.53

GC/GC

41

62.44

58.11

66.77

0.90 (1)

0.346

Not GC/GC

111

64.86

62.23

67.50

GC/AG

23

64.93

59.13

70.72

0.07 (1)

0.791

Not GC/AG

129

64.08

61.64

66.53

AC/AG

20

64.42

58.20

70.63

0.00 (1)

0.944

Not AC/AG

132

64.18

61.76

66.60

N, number of subject/allele/haplotype/diplotype; CI, confidence interval, # Means for cold pain-intensity scores; * p value is significant at<0.05, aRepeated measured ANOVA between-group analysis was applied, bHaplotype patterns were constructed from the two polymorphisms of OPRM1 (118A>G and IVS2+691G>C), cDiplotype with frequency less than 10.0% were pooled under ‘Others’ (included AC/AC, GC/GG, AG/AG)

DISCUSSION

The allelic frequencies of OPRM1 polymorphisms in the present study were similar to previous reports from Singapore [118G = 45 (95% CI 39.0, 51.1) and IVS2+691C = 79.5 (95% CI 74.7, 84.4)] [27] with the exception of IVS2+31G allele. The frequency of IVS2+31G allele in our study was similar to other Asian populations for example, in the Taiwan population, the reported frequency was 2.8% (95% CI 0.1, 5.5)][17].

Among the identified polymorphisms within the OPRM1gene, 118A>G polymorphism is the most frequently studied in the literature but the evidence is, unfortunately, inconsistent with regards to its association with pain sensitivity to various experimental stimuli [14, 15, 17, 28, 29]. In the present study, 118A>G and IVS2+691G>C polymorphisms were not associated with cold-pain responses among the Malay males. Only one published study which was similar to ours where the same cold-pain technique was used but in the Japanese subjects [29]. Although the association of cold pain sensitivity with vs. without 118G allele was significant in this Japanese population but the response difference was only one second (7%) [29]. Tan, et al. (2009) found an association between 118A>G genotypes and pain-intensity among the non-laboring Chinese women undergoing caesarean section but again no such association was found among the Malays. This suggests that ethnicity may be a major determinant for the role of 118A>G polymorphism in pain sensitivity [17].

There are other explanations to our negative results. There may be differences in experimental pain models (for example electrical or heat pain rather than cold), gender, study sample size, frequency of mutant-type 118G allele and whether study participants had been pre-medicated with centrally acting agents. Furthermore, the clinical impact of 118A>G polymorphism in pain sensitivity remains controversial. An earlier in vitro functional study has demonstrated that 118G allele altered the β-endorphin binding affinity [31]. Moreover, a recent study did not find any marked functional differences between variant and wild-type receptors in terms of morphine, morphine-6-glucuronide and β-endorphin binding affinities and potencies [32]. They also found both the variant receptor and wild-type receptors exhibited robust receptor internalization and they showed similar desensitization time courses [32]. But in vitro studies showed that there was a lower expression of the receptor protein corresponding to the 118G allele [32, 33]. In addition, it is likely that variations of other candidate genes may be more relevant in our population including CYP2D6, ABCB1, COMT, and other opioid receptor genes including OPRD1 and OPRK1 genes [34].

Some study limitations need to be highlighted. Firstly, we only studied Malay males, but this was to control for gender effect on pain sensitivity [35-41] besides the fact that Malay males were the majority of opioid-dependent patients on methadone treatment in Malaysia. Secondly, our study did not evaluate for psychological distress including anxiety or stress which might influence pain perception [42]. Lastly, the sample size was inadequate for post-hoc studies and it was underpowered because the observed numbers of subjects with AA and GG genotypes were small. Thirdly, only one pain modality (i.e., cold-pain) was studied.

CONCLUSION

The current study indicates that the common OPRM1 polymorphisms (i.e., 118A>G and IVS2+691G>C) are not associated with cold-pressor pain-threshold, tolerance and intensity in healthy opioid-naive Malay males. However, this may be unique for this particular ethnicity. Other polymorphisms may be more relevant for this population and this should be further investigated.

ACKNOWLEDGEMENT

We wish to thank Prof. Howard McNulty of the Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, UK for English language editing and proofreading of this article. We are grateful to Nur Amalina Che Rahim and Wan Izzati Mariah Binti Wan Hassan from Department of Pharmacy, Hospital Universiti Sains Malaysia, Kubang Kerian, Kelantan, Malaysia; Hazwan Mat Din and Wan Nor Arifin Wan Harun, Biostatistics & Research Methodology Unit, School of Medical Sciences, Universiti Sains Malaysia (USM); and all the members of Pharmacogenetics and Novel Therapeutics Cluster, Institute for Research in Molecular Medicine (INFORMM), Universiti Sains Malaysia (USM) for their support and valuable suggestions during the study. The study was supported by the Universiti Sains Malaysia (USM) grant under the ‘Research University Cluster (RUC)’ Grant No.1001. PSK.8620014, under the project; Application of Personalized Methadone Therapy Methadone Maintenance Therapy (PMT for MMT).

CONFLICT OF INTERESTS

The authors declare that there are no conflicts of interest

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About this article

Title

118A>G AND IVS2+691G>C POLYMORPHISMS OF OPRM1 GENE HAVE NO INFLUENCE ON COLD-PAIN SENSITIVITY AMONG HEALTHY OPIOID-NAIVE MALAY MALES

Date

01-07-2016

Additional Links

Manuscript Submission

Journal

International Journal of Pharmacy and Pharmaceutical Sciences
Vol 8, Issue 7, 2016 Page: 73-80

Online ISSN

0975-1491

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Authors & Affiliations

Zalina Zahari
Department of Pharmacy, Hospital Universiti Sains Malaysia, Kubang Kerian, Kelantan, Malaysia, Pharmacogenetics and Novel Therapeutics Cluster, Institute for Research in Molecular Medicine (INFORMM), Universiti Sains Malaysia (USM), Kubang Kerian, Kelantan, Malaysia,
Malaysia

Lee Chee Siong
Department of Emergency Medicine, School of Medical Sciences, Universiti Sains Malaysia (USM), Kubang Kerian, Kelantan, Malaysia

Lee Yeong Yeh
School of Medical Sciences, Universiti Sains Malaysia (USM), Kubang Kerian, Kelantan, Malaysia

Muslih Abdulkarim Ibrahim
Pharmacogenetics and Novel Therapeutics Cluster, Institute for Research in Molecular Medicine (INFORMM), Universiti Sains Malaysia (USM), Kubang Kerian, Kelantan, Malaysia5Department of Pharmacology and Toxicology, College of Pharmacy, Hawler Medical University, Hawler, Iraq

Nurfadhlina Musa
Pharmacogenetics and Novel Therapeutics Cluster, Institute for Research in Molecular Medicine (INFORMM), Universiti Sains Malaysia (USM), Kubang Kerian, Kelantan, Malaysia,

Md Azhar Mohd Yasin
Pharmacogenetics and Novel Therapeutics Cluster, Institute for Research in Molecular Medicine (INFORMM), Universiti Sains Malaysia (USM), Kubang Kerian, Kelantan, Malaysia Department of Psychiatry, School of Medical Sciences, Universiti Sains Malaysia (USM), Kubang Kerian, Kelantan, Malaysia

Tan Soo Choon

Nasir Mohamad
Pharmacogenetics and Novel Therapeutics Cluster, Institute for Research in Molecular Medicine (INFORMM), Universiti Sains Malaysia (USM), Kubang Kerian, Kelantan, Malaysia, 7Faculty of Medicine & Health Sciences, Universiti Sultan Zainal Abidin, Kuala Terengganu, Terengganu, Malaysia.

Rusli Ismail
2Pharmacogenetics and Novel Therapeutics Cluster, Institute for Research in Molecular Medicine (INFORMM), Universiti Sains Malaysia (USM), Kubang Kerian, Kelantan, Malaysia, Centre of Excellence for Research in AIDS (CERiA), University of Malaya, Kuala Lumpur, Malaysia.


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