Conceived and designed the experiments: MZ MB Yv DG. Performed the experiments: Pd Yv. Analyzed the data: MZ MB. Contributed reagents/materials/analysis tools: MZ MB. Wrote the paper: MZ MB Pd Yv DG.
The authors have declared that no competing interests exist.
The M235T polymorphism in the
A case-cohort study was conducted in 1,732 unrelated middle-age women (210 CHD cases and 1,522 controls) from a prospective cohort of 15,236 initially healthy Dutch women. We applied a Cox proportional hazards model to study the association of the polymorphism with acute myocardial infarction (AMI) (n = 71) and CHD. In the case-cohort study, no increased risk for CHD was found under the additive genetic model (hazard ratio [HR] = 1.20; 95% confidence interval [CI], 0.86 to 1.68;
The pooled OR of the present meta-analysis, including our own data, presented evidence that there is an increase in the risk of CHD conferred by the M235T variant of the
Angiotensinogen (AGT) is a liver protein that interacts with renin to produce angiotensin I, the pro-hormone of angiotensin II. Angiotensin II is the major effector molecule of the renin-angiotensin-aldosterone system (RAAS) and plays a key role in the regulation of blood pressure (BP) by increasing vascular tone and promoting sodium retention. Genetic variants in the angiotensinogen gene modify the plasma concentration of angiotensinogen, which has been directly related to arterial blood pressure
Given the importance of hypertension in the occurrence of coronary heart disease
Study design, general questionnaire, anthropometric and laboratory measurements have been described in detail elsewhere
We applied the case-cohort design introduced by Prentice
Genetic analysis was performed at the Cardiovascular Genotyping (CAGT) laboratory of the Department of Internal Medicine of the University Hospital Maastricht. Genomic DNA was extracted from buffy coats using the QIAamp® Blood Kit (Qiagen Inc., Valencia, California, USA). Genotyping of the polymorphisms was performed using a multilocus genotyping assay for candidate markers of cardiovascular disease risk (Roche Molecular Systems Inc., Pleasanton, CA, USA)
Hardy-Weinberg equilibrium (HWE) was tested with the χ2 test among the controls. Allele frequencies were estimated by gene counting. We used the ANOVA
To assess the relationship of the M235T polymorphism in the
We searched PubMed/MEDLINE, Web of Science, and EMBASE up to February 2007 for observational studies evaluating an association between the M235T polymorphism in the
All studies were considered potentially eligible if they aimed to investigate the relationship between the M235T genotypes and risk of CHD or MI. Any observational study, regardless of sample size, which fulfilled the following criteria, was included: (i)
The following information was extracted from each study that we included: the first author's name; country; year of publication; the population evaluated; study design; mean age or age range for case-patients and controls; definition and number of cases and controls; allele frequencies and genotype distribution in case-patients and controls (where data were not given, they were calculated from the corresponding genotyping frequencies of the case and control groups); consistency of genotype frequencies with HWE (calculated); gender in the evaluated population and male percentage, matching variables, use of blinding of genotyping staff, performing regenotyping of a random sample, and crude ORs and 95% CIs for development of CHD or MI related to the
The method of Mantel-Haenszel was used to calculate the odds ratio for the pooled data in a fixed-effects model, and, if there was evidence for heterogeneity, the DerSimonian-Laird method was used for the pooled odds ratio in a random-effects model, under pairwise comparisons of the different genotypes and dominant, recessive, and additive inheritance models. For all the models used, the T allele was considered the risk allele. The genetic model to be considered as the
In addition, we used Cochran's χ2 – based
We used funnel plots to examine the publication bias of reported associations. We also used Egger's test and the Begg-Mazumdar test with 95% CI for evaluation of publication bias, which are considered to be significant for
For evaluating the impact of HWE-violated studies on effect estimates (at the 0.05 significance level) under different genetic models, odds ratios, and variances were corrected by using the HWE-predicted genotype counts in the control instead of the observed counts as previously suggested
The general characteristics of the randomly sampled participants of the cohort (N = 1522) are given in
Characteristics | sub-cohort (N = 1522) | CHD cases | Sub-cohort | |||||
M235M | M235T | T235T | ||||||
N total (%) | 535 (35.2) | 737 (48.4) | 250 (16.4) | - | 210 | 1522 | - | |
Age at intake (yr) | 57.1±5.8 | 57.1±6.2 | 57.4±6.3 | 0.83 | 60.5±5.9 | 57.1±6.1 | <0.01 | |
Body mass index (kg/m2) | 26.0±4.1 | 25.6±3.8 | 25.8±4.1 | 0.19 | 26.8±3.9 | 25.8±4.0 | <0.01 | |
Weight (kg) | 70±11 | 69±11 | 69±11 | 0.17 | 71±11 | 69±11 | 0.07 | |
Height (cm) | 164.4±5.9 | 164.2±6.0 | 164.0±6.1 | 0.66 | 162.8±6.0 | 164.3±6.0 | <0.01 | |
Waist to hip ratio | 0.794±0.057 | 0.786±0.058 | 0.786±0.055 | 0.03 | 0.813±0.060 | 0.789±0.057 | <0.01 | |
Hypertension (%) | 39.4 | 41.2 | 48.4 | 0.06 | 60.5 | 41.8 | <0.01 | |
Systolic blood pressure (mm Hg) | 131±19 | 133±21 | 135±20 | 0.07 | 143±22 | 133±20 | <0.01 | |
Diastolic blood pressure (mm Hg) | 79±10 | 79±11 | 80±11 | 0.14 | 82±11 | 79±11 | <0.01 | |
Presence of diabetes (%) | 2.2 | 2.0 | 2.8 | 0.78 | 5.7 | 2.2 | <0.01 | |
Presence of hypercholesterolemia (%) | 3.6 | 4.6 | 2.8 | 0.38 | 11.4 | 3.9 | <0.01 | |
Current alcohol consumption (%) | 88.7 | 87.1 | 89.2 | 0.60 | 80.7 | 88.0 | <0.01 | |
Smoking status (%) | Past | 35.1 | 33.8 | 36.4 | 0.73 | 26.2 | 34.7 | 0.02 |
Current | 23.2 | 22.4 | 23.6 | 0.90 | 33.8 | 22.9 | <0.01 | |
Pack- years | 6.8±9.5 | 6.5±9.5 | 6.7±9.3 | 0.87 | 9.7±11.4 | 6.7±9.5 | <0.01 | |
Total cholesterol (mmol/L) | 5.9±1.0 | 5.8±0.9 | 5.9±1.1 | 0.05 | 6.4±1.0 | 5.9±1.0 | <0.01 | |
HDL cholesterol (mmol/L) | 1.6±0.4 | 1.6±0.4 | 1.6±0.4 | 0.33 | 1.4±0.3 | 1.6±0.4 | <0.01 | |
LDL cholesterol (mmol/L) | 4.0±1.0 | 3.9±0.9 | 3.9±0.9 | 0.25 | 4.4±1.0 | 3.9±0.9 | <0.01 | |
Serum glucose (mmol/L) | 4.6±1.5 | 4.5±1.3 | 4.5±1.2 | 0.52 | 5.1±2.5 | 4.5±1.4 | <0.01 |
HDL, high-density lipoprotein; LDL, low-density lipoprotein; CHD, coronary heart disease (ICD 410–414).
Mean±standard deviation.
Comparison of risk factors across genotypes, using the ANOVA
Comparison of risk factors across disease status, using the
Defined as a systolic blood pressure ≥140 mm Hg and/or diastolic blood pressure ≥90 mm Hg and/or questionnaire positive.
The number of packs of cigarettes smoked per day by the number of years the person has smoked.
Due to the association of the M235T genotypes with some risk factors of CHD, we presented crude models and models adjusted for hypertension, total cholesterol and waist to hip ratio as potential confounding factors.
Mode of Inheritance | Crude: model 1 | Adjusted: model 2 | ||||
Hazard ratio | 95% CI | P-value | Hazard ratio | 95% CI | P-value | |
Additive | 1.20 | 0.86–1.68 | 0.28 | 1.17 | 0.83–1.64 | 0.38 |
Recessive (TT vs. M-carriers) | 0.77 | 0.43–1.41 | 0.40 | 0.87 | 0.46–1.58 | 0.62 |
Dominant (T-carriers vs. MM) | 0.79 | 0.47–1.32 | 0.36 | 0.79 | 0.46–1.33 | 0.37 |
MT vs. MM | 1.09 | 0.84–1.41 | 0.53 | 1.11 | 0. 85–1.45 | 0.45 |
TT vs. MM | 1.21 | 0.86–1.70 | 0.28 | 1.17 | 0.83–1.63 | 0.38 |
Additive | 1.14 | 0.93–1.39 | 0.20 | 1.11 | 0.90–1.38 | 0.33 |
Recessive (TT vs. M-carriers) | 0.87 | 0.60–1.26 | 0.45 | 0.98 | 0.66–1.47 | 0.93 |
Dominant (T-carriers vs. MM) | 0.82 | 0.60–1.12 | 0.21 | 0.80 | 0.58–1.10 | 0.18 |
MT vs. MM | 1.09 | 0.93–1.27 | 0.31 | 1.13 | 0.95–1.34 | 0.16 |
TT vs. MM | 1.14 | 0.93–1.40 | 0.20 | 1.11 | 0.90–1.37 | 0.33 |
AMI = acute myocardial infarction (ICD 410); CHD = coronary heart disease (ICD 410–414).
The additive genetic model assumes that there is a linear gradient in risk between the MM, MT and TT genotypes (MM genotype baseline). This is equivalent to a comparison of the T allele versus the M allele (baseline).
We used a cox proportional hazards model with an estimation procedure adapted for case-cohort designs; adjusted for waist to hip ratio, hypertension, total cholesterol.
Characteristics of the studies are shown in
Author | Year | Country | Ethnicity | Total cases | Total controls | Study size based on average weight | Cases MM | Cases MT | Cases TT | Controls MM | Controls MT | Controls TT | |
1 | Katsuya et al. | 1995 | New Zealand | Caucasian | 422 | 406 | Large | 144 | 186 | 92 | 156 | 191 | 59 |
2 | Tiret et al. | 1995 | France and UK | Caucasian | 630 | 741 | Large | 229 | 301 | 100 | 258 | 372 | 111 |
3 | Ludwig et al.a | 1997 | USA | Caucasian | 58 | 55 | Small | 17 | 30 | 11 | 20 | 23 | 12 |
4 | Ludwig et al.b | 1997 | USA | Caucasian | 255 | 245 | Large | 79 | 117 | 59 | 85 | 118 | 42 |
5 | Wenzel et al. | 1997 | Germany | Caucasian | 111 | 102 | Small | 25 | 59 | 27 | 39 | 46 | 17 |
6 | Winkelmann et al. | 1999 | Germany | Caucasian | 329 | 92 | Small | 103 | 148 | 78 | 28 | 53 | 11 |
7 | Fernandez-Arcas et al. | 1999 | Spain | Caucasian | 272 | 182 | Small | 84 | 132 | 56 | 36 | 96 | 50 |
8 | Gardemann et al. | 1999 | Germany | Caucasian | 1739 | 511 | Large | 536 | 920 | 283 | 168 | 247 | 96 |
9 | Fatini et al. | 2000 | Italy | Caucasian | 205 | 209 | Small | 61 | 91 | 53 | 84 | 86 | 39 |
10 | Fomicheva et al. | 2000 | Russia | Caucasian | 198 | 152 | Small | 63 | 85 | 50 | 43 | 75 | 34 |
11 | Reinhardt et al. | 2000 | Germany | Caucasian | 184 | 155 | Small | 56 | 101 | 27 | 38 | 91 | 26 |
12 | Batalla et al. | 2000 | Spain | Caucasian | 220 | 200 | Small | 69 | 99 | 52 | 64 | 96 | 40 |
13 | Wierzbicki et al. | 2000 | UK | Caucasian | 48 | 108 | Small | 23 | 21 | 4 | 58 | 44 | 6 |
14 | Rodriguez-Perez et al. | 2001 | Spain | Caucasian | 299 | 315 | Large | 67 | 145 | 87 | 97 | 158 | 60 |
15 | Olivieri et al. | 2001 | Italy | Caucasian | 454 | 245 | Large | 148 | 205 | 101 | 74 | 114 | 57 |
16 | Sethi et al. | 2001 | Denmark | Caucasian | 943 | 7975 | Large | 335 | 460 | 148 | 2779 | 3886 | 1310 |
17 | Ortlepp et al. | 2002 | Germany | Caucasian | 100 | 100 | Small | 25 | 58 | 17 | 29 | 55 | 16 |
18 | Ermis et al. | 2002 | Turkey | Caucasian | 102 | 114 | Small | 32 | 48 | 22 | 39 | 59 | 16 |
19 | Bis et al. | 2003 | USA | Caucasian | 208 | 717 | Large | 71 | 98 | 39 | 215 | 349 | 153 |
20 | Buraczynska et al. | 2003 | Poland | Caucasian | 200 | 200 | Small | 28 | 122 | 50 | 72 | 80 | 48 |
21 | Tobin et al. | 2004 | UK | Caucasian | 547 | 505 | Large | 212 | 252 | 83 | 197 | 226 | 82 |
22 | Sekuri et al. | 2005 | Turkey | Caucasian | 115 | 128 | Small | 46 | 42 | 27 | 33 | 71 | 24 |
23 | Methot et al. | 2005 | Canada | Caucasian | 198 | 149 | Small | 65 | 93 | 40 | 60 | 70 | 19 |
24 | Renner et al. | 2005 | Austria | Caucasian | 2582 | 732 | Large | 841 | 1205 | 536 | 237 | 357 | 138 |
25 | Zafarmand et al. (present study) | 2008 | Netherlands | Caucasian | 210 | 1522 | Large | 64 | 108 | 38 | 535 | 737 | 250 |
26 | Kamitani et al. | 1995 | Japan | East Asian | 103 | 103 | Small | 6 | 31 | 66 | 10 | 41 | 52 |
27 | Ishigami et al. | 1995 | Japan | East Asian | 82 | 160 | Small | 6 | 22 | 54 | 30 | 51 | 79 |
28 | Yamakawa-Kobayashi et al. | 1995 | Japan | East Asian | 315 | 380 | Small | 15 | 91 | 209 | 9 | 131 | 240 |
29 | Ko et al. | 1997 | China | East Asian | 267 | 337 | Small | 6 | 36 | 225 | 4 | 54 | 279 |
30 | Ichihara et al. | 1997 | Japan | East Asian | 327 | 352 | Small | 15 | 103 | 209 | 13 | 112 | 227 |
31 | Cong et al. | 1998 | Japan | East Asian | 104 | 170 | Small | 2 | 31 | 71 | 16 | 43 | 111 |
32 | Sheu et al. | 1998 | China | East Asian | 102 | 145 | Small | 1 | 26 | 75 | 1 | 37 | 107 |
33 | Tsai et al. | 2006 | Taiwan | East Asian | 735 | 519 | Large | 15 | 195 | 525 | 5 | 111 | 403 |
34 | Frossard et al. | 1998 | UAE | Arab | 74 | 61 | Small | 21 | 32 | 21 | 16 | 26 | 19 |
35 | Hooper et al. | 2002 | USA | African- American | 100 | 100 | Small | 4 | 29 | 67 | 2 | 31 | 67 |
36 | Nair et al. | 2003 | India | South Asian | 141 | 131 | Small | 9 | 36 | 96 | 11 | 40 | 80 |
37 | Araujo et al. | 2004 | Brazil | South American | 110 | 104 | Small | 46 | 52 | 12 | 43 | 51 | 10 |
38 | Ranjith et al. | 2004 | South Africa | African | 195 | 300 | Small | 24 | 80 | 91 | 29 | 127 | 144 |
Author | Study design | Mean age±SD (years) in Cases | Mean age±SD (years) in Controls | Sex | Male percent | Matching variable (s) | Allele frequency 235T (%) | Blinding of genotyping staff | Regenotyping of random subsample | |
Katsuya et al. | Case-control | 62±7 | 62±7 | M/F | NR | None | 38 | 0.97 | NR | NR |
Tiret et al. | Case-control | 54±0.3 | 53±0.3 | M | 100 | Age | 40 | 0.22 | NR | NR |
Ludwig et al.a | Case-control | NR | NR | M/F | 86 | Age and sex | 43 | 0.28 | NR | NR |
Ludwig et al.b | Case-control | NR | NR | M/F | 80.5 | Age and sex | 41 | 0.92 | NR | NR |
Wenzel et al. | Case-control | 42 | 38 | M/F | 88 | None | 39 | 0.59 | NR | NR |
Winkelmann et al. | Case-control | 56±10 | 56±10 | M | 100 | None | 41 | 0.06 | NR | NR |
Fernandez-Arcas et al. | Case-control | 67±7 | 60±10 | M/F | 42 | None | 54 | 0.41 | NR | Yes |
Gardemann et al. | Cross-sectional | 63±9 | 59±11 | M | 100 | None | 43 | 0.76 | NR | NR |
Fatini et al. | Case-control | 59±5 | 51±6 | M/F | 76 | None | 39 | 0.0476 | NR | NR |
Fomicheva et al. | Case-control | 67 | 11 | M | 100 | None | 47 | 0.90 | NR | NR |
Reinhardt et al. | Case-control | 57±11 | 56±14 | M/F | 62 | None | 46 | 0.0240 | Yes | Yes |
Batalla et al. | Case-control | 43±5 | 42±6 | M | 100 | Age and ethnicity | 44 | 0.71 | NR | NR |
Wierzbicki et al. | Cohort | 57±13 | 53±12 | M/F | 68 | None | 26 | 0.53 | Yes | Yes |
Rodriguez-Perez et al. | Case-control | 56±10 | 54±10 | M/F | 76 | None | 44 | 0.76 | Yes | NR |
Olivieri et al. | Case-control | 60±9 | 58±13 | M/F | 83.5 | None | 47 | 0.31 | NR | NR |
Sethi et al. | Case-control | 59±9 | 56±15 | M/F | 74 | None | 41 | 0.43 | NR | NR |
Ortlepp et al. | Case-control | 58±13 | 59±11 | M/F | 68 | Age, sex, and prevalence of standard cardiac risk factors | 43 | 0.23 | NR | NR |
Ermis et al. | Case-control | 42±12 | 40±13 | NR | NR | None | 40 | 0.40 | NR | NR |
Bis et al. | Case-control | 70 | 64 | M/F | 61.5 | Age, sex and calendar year of identification | 46 | 0.61 | Yes | NR |
Buraczynska et al. | Case-control | 53±7 | 47±11 | M | 100 | None | 44 | 0.0077 | NR | NR |
Tobin et al. | Case-control | 62±9 | 57±11 | M/F | 68 | None | 39 | 0.21 | NR | Yes |
Sekuri et al. | Case-control | 48±8 | 44±7 | M/F | 77.4 | None | 47 | 0.19 | NR | NR |
Methot et al. | Case-control | 63±10 | 62±7 | F | 0 | Age | 37 | 0.84 | NR | NR |
Renner et al. | Case-control | 64±10 | 58±12 | M/F | 74.8 | None | 43 | 0.86 | Yes | NR |
Zafarmand et al. (present study) | Case-cohort | 61±6 | 57±6 | F | 0 | None | 41 | 0.89 | Yes | Yes |
Kamitani et al. | Case-control | 52±1 | 54±1 | M | 100 | Age, sex, BMI, blood pressure, total cholesterol, smoking and history of diabetes | 70 | 0.65 | NR | NR |
Ishigami et al. | Case-control | 62±1 | 60±1 | M/F | 68.3 | None | 65 | 0.0002 | NR | NR |
Yamakawa-Kobayashi et al. | Case-control | 57±8 | 51±8 | M/F | 80 | None | 80 | 0.07 | NR | NR |
Ko et al. | Case-control | 62±1 | 56±1 | M/F | 77 | None | 91 | 0.51 | NR | NR |
Ichihara et al. | Case-control | 53±6 | 53±5 | M | 100 | Age, sex, BMI and some CHD risk factors (history of smoking, hypertension, diabetes, hypercholesterolemia) | 80 | 0.86 | NR | NR |
Cong et al. | Case-control | 65±1 | NR | M/F | 76 | None | 78 | 0.0006 | NR | NR |
Sheu et al. | Case-control | 63±1 | 58±1 | M | 100 | None | 87 | 0.47 | NR | NR |
Tsai et al. | Case-control | 64±11 | 59±13 | M/F | 72.2 | None | 88 | 0.38 | NR | NR |
Frossard et al. | Case-control | 57±12 | 54±14 | M/F | 48.2 | None | 52 | 0.26 | NR | NR |
Hooper et al. | Case-control | NR | NR | M/F | NR | None | 83 | 0.73 | NR | NR |
Nair et al. | Case-control | 56±5 | 48±6 | M/F | 82.3 | Age and sex | 76 | 0.08 | NR | NR |
Araujo et al. | Case-control | NR | NR | M/F | 66.6 | None | 34 | 0.36 | NR | NR |
Ranjith et al. | Case-control | NR | NR | M/F | NR | Age | 69 | 0.90 | NR | NR |
Author | End point | Case definition | Source of controls |
Katsuya et al. | CHD | Admission for treatment of myocardial infarction or unstable angina, PTCA, or CABG, or stable angina with angiographic evidence of CHD or a positive exercise test result | Controls without a history of CHD and symptoms suggesting angina from two previous studies |
Tiret et al. | MI | WHO MONICA category I | Electoral rolls in France and the list of general practitioners in N. Ireland |
Ludwig et al.a | CHD | Diagnosed MI by a physician, a PTCA, a CABG, prior MI in ECG, fatal CHD | Healthy controls without the conditions, no lipid-lowering medications and no family history |
Ludwig et al.b | CHD | Diagnosed MI by a physician, a percutaneous coronary angioplasty, a coronary artery bypass, prior MI, fatal CHD | Healthy controls without the conditions, no lipid-lowering medications and no family history |
Wenzel et al. | CHD | >50% stenosis of at least one major coronary vessel, defined as MI, PTCA, CABG | Healthy young persons without any symptoms for CVD |
Winkelmann et al. | CHD, MI | At least one coronary stenosis ≥ 50% | controls without coronary artery disease in coronary angiography |
Fernandez-Arcas et al. | MI | Typical prolonged chest pain or atypical symptoms, acute congestive heart failure, syncope, and serial cardiac enzymes elevation exceeding twice the upper limit of reference range and dynamic ECG changes typical of MI | Healthy controls with no CVD using health service identity card |
Gardemann et al. | CHD, MI | CHD: coronary stenosis ≥ 50% MI: Using the WHO criteria | No vessel disease in the coronary angiography |
Fatini et al. | CHD | History of CHD (previous MI or angina pectoris) with coronary stenosis >75% by angiography | Random healthy controls from the staff of the University |
Fomicheva et al. | MI | Using the WHO criteria | From secondary schools |
Reinhardt et al. | CHD | At least one coronary stenosis ≥ 50% of a major coronary artery with or without prior MI | Random healthy controls from the local registry office |
Batalla et al. | MI | WHO MONICA protocol | Healthy controls from residents of the region |
Wierzbicki et al. | CHD | Confirmed cardiac event, angioplasty, coronary bypass surgery, or significant lesions on angiography | No CHD |
Rodriguez-Perez et al. | CHD | Hospital-admitted with a diagnosis of MI or unstable angina and documented evidence of coronary artery disease by angiography | Random controls without CVD |
Olivieri et al. | CHD, MI | CHD: Candidate patients for CABG, having >50% stenosis of at least one major coronary vessel MI: By medical records showing diagnostic electrocardiogram and enzyme changes, and/or the typical sequelae of myocardial infarction on ventricular angiography | CHD-free group documented by angiography who were examined for other reasons in the institute |
Sethi et al. | CHD, MI | CHD: ICD, 8th edition, codes 410-414 MI: ICD, 8th edition, code 410 | Random healthy controls without CHD, MI or CVA from the city of Copenhagen |
Ortlepp et al. | CHD | >50% stenosis of at least one coronary vessel | Patients without any signs of atherosclerosis in angiography |
Ermis et al. | Early MI | WHO criteria | Healthy subjects without a history of CHD, hypertension or diabetes |
Bis et al. | MI | Criteria were adapted from the Cardiovascular Health Study | Randomly selected subjects from the members of a health maintenance organization |
Buraczynska et al. | CHD | Hospitalized patients with unstable angina, stable angina or acute MI | Healthy subjects without family history of CHD |
Tobin et al. | MI | Using the WHO criteria | Healthy visitors to patients |
Sekuri et al. | CHD | At least one stenosis ≥ 50% in a major coronary artery or one of their branches | Healthy subjects without history of CVD |
Methot et al. | CHD | Acute coronary syndrome: AMI or unstable angina defined according to standard criteria | Postmenopausal women without signs or symptoms of acute or previous acute coronary syndrome |
Renner et al. | CHD, MI | CHD: At least one stenosis ≥ 50% in one of 15 coronary segments MI: positive history of MI or patients presented with ST elevation or non-ST elevation | Subjects without CHD (with stenoses <20%) from a cohort study |
Zafarmand et al. (present study) | CHD, MI | CHD: ICD, 9th edition, codes 410-414 MI: ICD, 9th edition, code 410 | Members of a 10% random sample from the whole cohort at the baseline without CVD |
Kamitani et al. | MI | Having MI by coronary angiography, ECG criteria, and measurements of heart-specific serum enzymes | Randomly selected subjects attending the same hospital with no CVD |
Ishigami et al. | CHD | At least one coronary artery with >25% luminal obstruction on average according to multiple coronary angiographic views | Hospital-admitted patients for other diseases with no CHD |
Yamakawa-Kobayashi et al. | CHD | At least one 75% stenosis in coronary arteries | Healthy controls |
Ko et al. | CHD | >50% stenosis of at least one major coronary vessel | Healthy subjects and patients without angiographic evidence of CHD |
Ichihara et al. | CHD | MI was based on typical ECG changes and increased serum enzymes and by the presence of wall motion abnormality on left ventriculography, Angina pectoris by typical ECG changes and stenosis of >70% in any major coronary artery or of >50% in the left main trunk, without wall motion abnormality on left ventriculography | Random healthy controls with no history or sign of CHD from attendants of the hospitals |
Cong et al. | CHD | ≥ 50% stenosis in at least one major coronary artery | Subjects with no history of CHD or abnormal resting electrocardiogram |
Sheu et al. | CHD | A postnitroglycerin stenosis of major vessels ≥ 50% or a >70% reduction of luminal diameter of a first-order branche | Healthy subjects in their annual physical checkups |
Tsai et al. | CHD | >50% stenosis of at least one coronary vessel | CHD-free group documented by angiography |
Frossard et al. | CHD, MI | CHD: Exertional angina, unstable angina or MI MI: ECG changes; presence of regional wall motion abnormalities on trans-thoracic echocardiography; and serial enzyme elevations | Healthy controls |
Hooper et al. | MI | Prior MI confirmed by ECG and/or cardiac enzymes or cardiac thallium scanning or catheterization | Outpatients with no history of heart attack, stroke, or thrombosis |
Nair et al. | CHD | At least one coronary artery with 50% stenosis | Healthy controls with BP<140/90 mm Hg and no history of CVD |
Araujo et al. | MI | Using the WHO criteria confirmed by stenosis >50% in an angiography and ventricular damage in a ventriculography | Hospital-admitted patients for other diseases with a normal coronary angiography |
Ranjith et al. | MI | Using the WHO criteria | Healthy normotensive subjects with no CVD or other associated risk factors |
PTCA, percutaneous coronary angioplasty; CABG, coronary artery bypass graft; ICD, international classification of diseases; ECG, electrocardiography; AMI, acute myocardial infarction; CHD, coronary heart disease; CVD, cardiovascular diseases; CVA, cerebrovascular accident; BMI, body mass index; WHO, world health organization; NR, not reported.
Exact significance probability.
All studies used polymerase chain reaction methods for genotyping, and most used a restriction fragment length method for polymorphism analysis. Blinding of investigators involved in genotyping with respect to the case/control status of the participants was reported in six studies
The overall OR under a random-effects model using an additive model for CHD risk was 1.08 (95% CI, 1.01 to 1.15;
ORs for the outcome compared the T235 allele vs. the M235 allele (Additive model). The size of the box is proportional to the weight of the study. Given
Genetic model | Random effects OR (95% CI) | Egger's test | Begg's test | ||||
Additive | 1.08 (1.01–1.15) | 0.025 | 55.5 (36–69) | 83.21 | <0.001 | 0.066 | 0.074 |
Recessive (TT vs. M-carriers) | 1.11 (1.02–1.22) | 0.016 | 37.5 (7–58) | 59.23 | 0.012 | 0.011 | 0.070 |
Dominant (T-carriers vs. MM) | 1.07 (0.96–1.19) | 0.253 | 56.0 (37–69) | 84.02 | <0.001 | 0.549 | 0.706 |
MT vs. MM | 1.02 (0.91–1.14) | 0.724 | 51.3 (29–66) | 75.99 | <0.001 | 0.895 | 0.960 |
TT vs. MM | 1.15 (1.00–1.32) | 0.045 | 53.3(33–68) | 79.30 | <0.001 | 0.286 | 0.615 |
The additive genetic model assumes that there is a linear gradient in risk between the MM, MT and TT genotypes (MM genotype baseline). This is equivalent to a comparison of the T allele versus the M allele (baseline).
Study characteristics | Number of studies | Per-allele OR (95%CI) | ||||
Overall | 38 | 1.08 (1.01–1.15) | 0.025 | 55.5 (36–69) | 83.21 | <0.001 |
Study size | ||||||
Small | 26 | 1.12 (1.02–1.24) | 0.021 | 50.2 (35–73) | 50.24 | 0.002 |
Large | 12 | 1.03 (0.95–1.12) | 0.502 | 62.0 (29–80) | 28.92 | 0.002 |
Ethnicity | ||||||
Caucasians | 25 | 1.08 (1.01–1.17) | 0.028 | 58.2 (35–73) | 57.43 | <0.001 |
Eastern Asians | 8 | 1.12 (0.89–1.40) | 0.325 | 69.5 (36–85) | 22.96 | 0.002 |
Others | 5 | 0.99 (0.84–1.18) | 0.944 | 0.00 (0–79) | 2.31 | 0.679 |
Matching | ||||||
Matched | 11 | 1.07 (0.96–1.18) | 0.211 | 26.2 (0–63) | 13.56 | 0.194 |
Unmatched | 27 | 1.08 (0.99–1.17) | 0.072 | 62.7 (44–75) | 69.65 | <0.001 |
Violating HWE | ||||||
Violated | 5 | 1.38 (1.05,–1.83) | 0.022 | 70.7 (26–88) | 13.65 | 0.009 |
Confirmed | 33 | 1.04 (0.98–1.11) | 0.188 | 43.5 (5–63) | 56.66 | 0.005 |
Blinding of genotyping staff | ||||||
Blinded | 6 | 1.07 (0.92–1.24) | 0.391 | 62.6 (9–85) | 13.36 | 0.020 |
Not reported | 32 | 1.08 (1.00–1.16) | 0.040 | 55.5 (34–70) | 69.88 | <0.001 |
Regenotyping of a random subsample | ||||||
Performed | 5 | 0.94 (0.79–1.14) | 0.544 | 58.9 (0–85) | 9.74 | 0.045 |
Not reported | 33 | 1.10 (1.03–1.18) | 0.007 | 54.7 (33–69) | 70.64 | <0.001 |
Case definition | ||||||
>50%stenosis of ≥1 major vessels | 16 | 1.09 (0.97–1.23) | 0.135 | 62.4 (35–78) | 39.9 | <0.001 |
>70%stenosis of ≥1 major vessels | 4 | 1.10 (0.90–1.34) | 0.358 | 40.7 (0–80) | 5.1 | 0.167 |
WHO criteria | 14 | 1.00 (0.93–1.09) | 0.942 | 36.9 (0–67) | 20.6 | 0.081 |
Clinical diagnosis | 4 | 1.31 (1.15–1.49) | <0.001 | 0.00 (0–85) | 2.7 | 0.439 |
Source of controls | ||||||
Population-based | 21 | 1.09 (1.01–1.19) | 0.036 | 62.6 (40–77) | 53.5 | <0.001 |
Hospital-based | 17 | 1.05 (0.95–1.17) | 0.354 | 44.6 (2–69) | 28.9 | 0.025 |
First, an empty regression was run with only the log of the effect estimate of pooled studies under the additive model to determine the baseline value for τ2, an estimate of between-study variation (baseline τ2 = 0.025). Next, single covariates were added in a series of univariate models. We performed the regression analysis for ten pre-defined potential sources of heterogeneity, including ethnicity, sex, mean age of cases, study size, case definition, source of controls, HWE-violation, blinding in genotyping, performing a sub-sample regenotyping, and matching (we hypothesized that studies that used matching might produce more conservative estimates of association). Univariate regression analyses showed that violation of HWE (β coefficient = 0.27 (0.06 to 0.48);
First, the influence of deviation from the HWE on effect estimates was examined by using HWE-deviated adjusted ORs.
Genotype contrasts | Population | Number of studies | Random effects model | |||||
Odds ratio | 95%CI | P-value | ||||||
Additive | All | 38 | 1.11 | 0.81–1.53 | 0.522 | 0 (0–37) | 2.04 | 1.000 |
Caucasians | 25 | 1.11 | 0.75–1.64 | 0.616 | 0 (0–44) | 1.04 | 1.000 | |
East Asians | 8 | 1.19 | 0.60–2.36 | 0.626 | 0 (0–68) | 0.82 | 0.997 | |
Recessive | All | 38 | 1.14 | 1.04–1.26 | 0.007 | 56 (37–70) | 84.66 | <0.001 |
Caucasians | 25 | 1.15 | 1.03–1.29 | 0.014 | 56 (32–72) | 55.02 | <0.001 | |
East Asians | 8 | 1.18 | 0.90–1.55 | 0.242 | 73 (45–87) | 26.15 | <0.001 | |
Dominant | All | 38 | 1.05 | 0.96–1.15 | 0.330 | 49 (26–65) | 72.52 | <0.001 |
Caucasians | 25 | 1.08 | 0.98–1.20 | 0.121 | 58 (35–73) | 57.82 | <0.001 | |
East Asians | 8 | 0.92 | 0.64–1.33 | 0.656 | 33 (0–70) | 10.41 | 0.166 | |
MT vs MM | All | 38 | 1.00 | 0.92–1.09 | 0.996 | 15 (0–43) | 43.41 | 0.217 |
Caucasians | 25 | 1.03 | 0.94–1.14 | 0.497 | 25 (0–54) | 31.99 | 0.127 | |
East Asians | 8 | 0.82 | 0.60–1.11 | 0.204 | 0 (0–68) | 6.53 | 0.480 | |
TT vs MM | All | 38 | 1.13 | 0.99–1.28 | 0.080 | 52 (31–67) | 77.88 | <0.001 |
Caucasians | 25 | 1.19 | 1.02–1.38 | 0.023 | 60 (38–74) | 60.11 | <0.001 | |
East Asians | 8 | 1.01 | 0.65–1.59 | 0.952 | 50 (0–77) | 13.87 | 0.054 |
The size of the circle is proportional to the weight of the study.
Red squares are missed studies due to publication bias.
In this prospective study of healthy women aged 49 to 70 years, we investigated the relationship between the M235T polymorphism in the
In our study, the data collection was prospective, before the diagnosis of AMI or CHD and equal for all participants. This ensures that the cases and the randomly selected controls are comparable
The current meta-analysis, which includes new data from a prospective study in a large population-based cohort of Dutch women, represents a comprehensive evaluation of the M235T variant of the
Some aspects of the current meta-analysis need to be considered to appreciate the findings. First, it might not be very practical to adjust for violation of HWE in the studies that mentioned that the violation is not due to genotyping errors. However, in the current meta-analysis, the HWE-violated studies that were included in the pooled estimate did not provide any reason for the violation. Therefore, we performed sensitivity analyses by using HWE-adjusted ORs and corresponding variances. Thereafter, a smaller overall effect was seen under most of the genetic models. Second, the power of tests for HWE and the power to detect genotyping errors are low. Therefore, the inability to detect a deviation from the HWE does not mean that there is no deviation, nor does it rule out the presence of genotyping errors, especially for small sample sizes. Third, our meta-analysis was based on published studies and we did not have access to the original data. However, it could be possible that an association between the genotype and disease exists in certain contexts rather than in all people studied. For example, a case-control study showed that the TT genotype was associated with an increased risk of CHD and MI only in smokers
Approximately 10% of gene-disease association studies are affected by statistically significant deviation from HWE, which could result from genotyping error, chance, inbreeding, non-random mating, differential survival of marker carriers, genetic drift, population stratification, or a combination of these reasons
Violation of HWE cannot solely explain the observed between-study variation in gene-disease association studies. The large between-study heterogeneity presented in most meta-analyses could be due to true heterogeneity (i.e., racial differences or differences in gene-environment interactions among various populations) or bias
In conclusion, the present meta-analysis, including our own data, indicated that, although a weak association between the M235T variant in the
We are grateful to the participants of the Prospect-EPIC study. We would like to thank all field workers and laboratory technicians for their skillful contributions to the data collection.