Potential Impact of COMT-rs4680 G > A Gene Polymorphism in Coronary Artery Disease
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Population
2.2. Patient Selection Criteria
2.2.1. Inclusion Criteria
2.2.2. Selection Criteria of Healthy Controls
2.3. Sample Collection
2.4. Measurement of Serum Lipids and Apolipoproteins
2.5. Data Collection
2.6. Genotyping Analysis
2.6.1. DNA Extraction
2.6.2. AS-PCR for COMT (Val158Met) gene Polymorphism
2.7. Stastical Analysis
3. Results
3.1. Baseline Characteristics of the Study Subjects
3.1.1. Case Control Genotype Distribution
3.1.2. Case Control Genotype Distribution
3.2. Association of COMT rs4680 G > A Gene Variation with Coronary Artery Disease
4. Discussion
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Homozygous COMT G/G | Homozygous Val158val | Enzyme with high activity | Low level of dopamine |
Heterozygous COMT A/G | Heterozygous Val158Met | Enzyme with medium activity | Medium level of dopamine |
Homozygous COMT A/A | Homozygous Met158met | Enzyme with low activity | High level of dopamine |
Primer Direction | Nucleotide Change | Amino Acid Change | Primer Sequence | Annealing Tempt | Product Size |
---|---|---|---|---|---|
Forward F | 5′-ACTGTGGCTACTCAGCTGTG-3′ | 56 °C | 169 bp | ||
Reverse R1 | G allele | (Val158) | 5′-GCATGCACACCTTGTCCTT-3′ | ||
Reverse R2 | A allele | (Met158) | 5′-GCATGCACCACCTTGTCCTTCAT-3′ |
Variable | No. of CAD Cases | Healthy Controls |
---|---|---|
Subjects | 100 100% | 100 100% |
Men | 96 96% | 90 90% |
Women | 4 4% | 10 10% |
Age difference | ||
Age ≤ 50 | 47 47% | 60 60% |
Age > 50 | 53 53% | 40 40% |
Variable for CAD cases | Number | (%) |
Random Blood Sugar | ||
≤140 mg | 55 | 57% |
>140 mg | 45 | 43% |
Cholesterol | ||
≤200 mg | 93 | 93% |
>200 mg | 7 | 7% |
HDL | ||
≤40 mg | 91 | 91% |
>40 mg | 9 | 9% |
LDL | ||
≤100 mg | 79 | 79% |
>100 mg | 21 | 21% |
TGL | ||
≤150 mg | 51 | 51% |
>150 mg | 49 | 49% |
Hypertension | ||
Yes | 14 | 14% |
No | 86 | 86% |
Type 2 Diabetes | ||
Yes | 23 | 23% |
No | 77 | 77% |
Smoking | ||
Yes | 63 | 63% |
No | 37 | 37% |
Alcohol | ||
Yes | 40 | 40% |
No | 60 | 60% |
Pan Masala | ||
Yes | 2 | 2% |
No | 98 | 98% |
Subjects | Number | G/G (Val/Val) | A/G (Val/Met) | A/A (Met/Met) | X2 | df | G | A | p Value |
---|---|---|---|---|---|---|---|---|---|
Patients | 100 | 10 (10%) | 70 (70%) | 20 (20%) | 14.1 | 2 | 0.45 | 0.55 | <0.008 |
Controls | 100 | 30 (30%) | 60 (60%) | 10 (10%) | 0.60 | 0.40 |
Allele/Genotype | Number | G/G (Val/Val) | A/G (Val/Met) | A/A (Met/Met) | p Value |
---|---|---|---|---|---|
COMT G > A correlation with sex | |||||
Men | 96 | 09 | 68 | 19 | 0.53 |
Women | 4 | 01 | 02 | 01 | |
COMT G > A correlation with age | |||||
≤50 years | 47 | 03 | 27 | 17 | 0.0480 |
>50 years | 53 | 07 | 43 | 03 | |
COMT G > A correlation with RBS | |||||
≤140 mg | 55 | 03 | 45 | 7 | 0.016 |
>140 mg | 45 | 07 | 25 | 13 | |
COMT G > A correlation with cholesterol | |||||
≤200 mg | 93 | 09 | 69 | 15 | NS |
>200 mg | 07 | 01 | 01 | 05 | |
COMT G > A correlation with HDL | |||||
≤40 mg | 91 | 08 | 65 | 18 | NS |
>40 mg | 9 | 02 | 05 | 02 | |
COMT G > A correlation with LDL | |||||
≤100 mg | 79 | 07 | 58 | 14 | NS |
>100 mg | 21 | 03 | 12 | 06 | |
COMT G > A correlation with TGL | |||||
≤150 mg | 51 | 08 | 40 | 03 | <0.006 |
>150 mg | 49 | 02 | 30 | 17 | |
Correlation with hypertension | |||||
Hypertension | 14 | 02 | 08 | 04 | NS |
No hypertension | 86 | 08 | 62 | 16 | |
Correlation with diabetes | |||||
Diabetes | 23 | 04 | 13 | 06 | 0.023 |
No Diabetes | 77 | 06 | 57 | 14 | |
Correlation with smoking | |||||
Smoking | 63 | 05 | 45 | 13 | <0.667 |
No Smoking | 37 | 05 | 25 | 07 | |
Correlation with alcohol consumption | |||||
Alcohol | 40 | 04 | 24 | 16 | <0.001 |
No Alcohol | 60 | 06 | 46 | 04 | |
Correlation with Pan Masala consumption | |||||
Pan Masala | 02 | 1 | 1 | 0 | <0.206 |
No Pan Masala | 98 | 09 | 69 | 20 |
Genotype | Healthy Controls | CAD Patients | OR (95% CI) | Risk Ratio (RR) | p-Value | ||
---|---|---|---|---|---|---|---|
(N = 100) | % | (N = 100) | % | ||||
Codominant inheritance model | |||||||
COMT-GG | 30 | 30% | 10 | 10% | 1 (ref.) | 1 (ref.) | |
COMT-GA | 60 | 60% | 70 | 70% | 3.5 (1.58–7.74) | 1.62 (1.25–2.10) | 0.002 |
COMT-AA | 10 | 10% | 20 | 20% | 6.0 (2.11–17.03) | 2.25 (1.31–3.8) | <0.003 |
Dominant inheritance model | |||||||
COMT-GG | 30 | 30% | 10 | 10% | 1 (ref.) | 1 (ref.) | |
COMT-(GA + AA) | 70 | 70% | 90 | 90% | 3.85 (1.76–8.4) | 1.71 (1.33–2.20) | <0.0007 |
Recessive inheritance model | |||||||
COMT-(GG + GA) | 90 | 90% | 80 | 81.63% | 1 (ref.) | 1 (ref.) | |
COMT-AA | 10 | 10% | 18 | 18.36% | 2.02 (0.86–4.7) | 1.05 (0.74–1.51) | 0.72 |
Allele | |||||||
COMT-G | 120 | 60% | 90 | 45.45% | 1 (ref.) | 1 (ref.) | |
COMT-A | 80 | 40% | 108 | 54.55% | 1.8 (1.20–2.67) | 1.34 (1.09–1.64) | <0.004 |
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Mir, R.; Bhat, M.; Javid, J.; Jha, C.; Saxena, A.; Banu, S. Potential Impact of COMT-rs4680 G > A Gene Polymorphism in Coronary Artery Disease. J. Cardiovasc. Dev. Dis. 2018, 5, 38. https://doi.org/10.3390/jcdd5030038
Mir R, Bhat M, Javid J, Jha C, Saxena A, Banu S. Potential Impact of COMT-rs4680 G > A Gene Polymorphism in Coronary Artery Disease. Journal of Cardiovascular Development and Disease. 2018; 5(3):38. https://doi.org/10.3390/jcdd5030038
Chicago/Turabian StyleMir, Rashid, Musadiq Bhat, Jamsheed Javid, Chandan Jha, Alpana Saxena, and Shaheen Banu. 2018. "Potential Impact of COMT-rs4680 G > A Gene Polymorphism in Coronary Artery Disease" Journal of Cardiovascular Development and Disease 5, no. 3: 38. https://doi.org/10.3390/jcdd5030038
APA StyleMir, R., Bhat, M., Javid, J., Jha, C., Saxena, A., & Banu, S. (2018). Potential Impact of COMT-rs4680 G > A Gene Polymorphism in Coronary Artery Disease. Journal of Cardiovascular Development and Disease, 5(3), 38. https://doi.org/10.3390/jcdd5030038