Reference
Complete the bibliographic reference for the article according to AJE format.

Sayed-Tabatabaei FA et al.  Angiotensin converting enzyme gene polymorphism and cardiovascular morbidity and mortality: the Rotterdam Study. J Med Genet. 2005;42:26-30

Category of HuGE information
Specify the types of information (from the list below) available in the article:

1. Prevalence of gene variant
2. Gene-disease association
3. Gene-environment interaction
4. Gene-gene interaction
5. Genetic test evaluation/monitoring

1. Prevalence of gene variant
2. Gene-disease association
3. Gene-environment interaction

Study hypotheses or purpose
The authors study hypotheses or main purpose for conducting the study

Null form:
Cardiovascular mortality and morbidity are the same for those who have the ACE ID or DD genotype when compared to those who have the II genotype, regardless of their smoking status.

Gene(s)
Identification of the following:

1. Gene name
2. Chromosome location
3. Gene product/function
4. Alleles
5. OMIM #
6. GDPInfo link

1. Gene name: Angiotensin I converting enzyme, ACE
2. Gene location: 17q23
3. Gene product/function: Converts angiotensin I to angiotensin II by release of the terminal His-Leu, resulting in increased vasoconstrictor activity and inactivation of bradykinin, a potent vasodilator.
4. Alleles: An insertion (I)/deletion (D) polymorphism situated in intron 16 of the ACE gene--known as the ACE I/D polymorphism—has been implicated in coronary artery disease (Cambien et al. (1992).
5. OMIM#: +106180
6. Go to GDPInfo Genes A-Z result

Environmental factor(s)
Identification of the major environmental factors studied (infectious, chemical, physical, nutritional, and behavioral)

1. Smoking

Health outcome(s)
Identification of the major health outcome(s) studied

1. Mortality due to coronary heart disease or cardiovascular disease
2. Myocardial infarction

1. Case-control
2. Cohort 
3. Cross-sectional
4. Descriptive or case series
5. Clinical trial
6. Population screening

1. Cohort

Case definition
For study designs 2, 3, and 6, the following are defined, where available:

1. Case selection criteria
2. Exclusion criteria
3. Gender
4. Race/ethnicity
5. Age
6. Time period
7. Geographic location
8. Number of participants

1. Disease case definition:
2. Exclusion criteria:
3. Gender:
4. Race/ethnicity: [if not specified, state ‘not specified']
5. Age:
6. Time period:
7. Geographic location: [if not specified, state ‘not specified']
8. Number of participants: N (% of total eligible)

Control definition  
For study design 1, the following are defined, if available. 

1. Control selection criteria
2. Matching variables
3. Exclusion criteria 
4. Gender
5. Race/ethnicity
6. Age
7. Time period
8. Geographic location
9. Number of participants

1. Control selection criteria:
2. Matching variables:
3. Exclusion criteria:
4. Gender:
5. Race/ethnicity: [if not specified, state ‘not specified']
6. Age:
7. Time period:
8. Geographic location: [if not specified, state ‘not specified']
9. Number of participants: N (% of total eligible)

Cohort definition
For study designs 2, 3, and 6, define the following if available:

1. Cohort selection criteria
2. Exclusion criteria
3. Gender
4. Race/ethnicity
5. Age
6. Time period
7. Geographic location
8. Number of participants (% of total eligible)

1. Cohort selection criteria: “This study is embedded in the Rotterdam Study, a prospective population based cohort study of 7983 men and women aged 55 years or older, living in
   Rotterdam, the Netherlands .”
2. Exclusion criteria: missing genotype or smoking status, prevalent MI
3. Gender: mixed
4. Race/ethnicity: Caucasian
5. Age: >=55
6. Time period: recruitment 1990-93, end of follow up is 2002
7. Geographic location: Rotterdam
8. Number of participants: 6714 (84% of total eligible)

1. Environmental factor
2. Exposure assessment
3. Exposure definition
4. Number of participants with exposure data (%
   of total eligible)

1. Environmental factor: smoking
2. Exposure assessment: current smoker?Yes or No
3. Exposure definition: current smoker
4. Number of participants: 6714 (84% of total eligible)

1. Gene
2. DNA source
3. Methodology
4. Number of participants genotyped (% of total eligible) 

1. Gene: ACE
2. DNA source: stored plasma, extracted through standard procedures
3. Genotyping method: PCR
4. Number of participants genotyped: 6714 (84% of total eligible)

Survival analysis, Cox proportional hazards models, stratified on sex, age, and smoking status to examine effect modification. Multiplicative models with interaction terms were also used. The analysis was appropriate.

1. Prevalence of gene variant
2. Gene-disease association
3. Gene-environment interaction
4. Gene-gene interaction
5. Genetic test evaluation/monitoring

1. DD 28%, ID 50% II, 22%; allele distribution follows H-W equilibrium.
2. (a) No statistically significant effect on CHD mortality was reported.
   (b) For the effect on CVD mortality, hazard ratios (HRs) were obtained (see table 4) and the DD genotype was significantly positively associated with CVD mortality (HR DD/II was 5.19; p=0.03); the weaker, yet insignificant, positive association of the ID genotype suggested a trend (HR ID/II was 1.91; p>0.05). However, the observed association and trend depended on age and smoking status (see category 3 below); thus, there is no evidence of an independent association between the ACE gene and CVD mortality.
   (c) ACE genotype was not associated with incident MI (see table 2).
3. When considering age specific mortality (Figures 1 and 2), an increased risk of CHD and CVD mortality in the DD genotype group was observed only among younger smokers (<68.2 years old). In the logistic regression model, gene-environment interaction was assessed on a multiplicative scale:
   • Among younger subjects, DD genotype-smoking interaction terms were nearly significant and borderline significant for CHD and CVD mortality, respectively (see table 3).
   • Among smokers, all ACE I/D-age interaction terms were significant (see table 3).
   • Among young non-smokers, the hazard ratio (HR) for the DD/II genotype was 0.89 (95% CI 0.33--2.36); and HR (ID/II) was 0.63 (95% CI 0.25—1.60). Among young smokers, HR (DD/II) was 5.19 (95% CI 1.15--23.42) and HR (ID/II) was 1.91 (95% CI 0.41—9.02) (see table 4).
4. No gene-gene interaction was assessed
5. N/A

This study showed that the ACE I/D polymorphism is not a strong risk factor for MI but its interaction with smoking might play a role in cardiovascular mortality especially at younger ages.

Comments
Provide additional insight, including methodologic issues and/or concerns about the study

The authors also conclude that their data do not support an association between ACE I/D and MI, which is consistent with the meta-analysis they cited. The study was conducted among older people living in Rotterdam , so it is very likely that they are mostly of northern European descent. Still, the authors should have included a statement about the racial composition of the study sample. Current smoking status was included in this investigation as a potential effect modifier but it is not clear whether the researchers examined effect modification due to ex-smoking status; it is also not clear why ex-smokers were grouped with current non-smokers. Did the authors determine that the effect of being an ex-smoker is comparable to that of being a current non-smoker?

In Table 1, there were trends in the mean systolic blood pressure and the mean of common carotid artery IMT with respect to genotype. The p-values for the heterogeneity in the distribution of these variables were less than 0.05. These variables were not included in the analyses as confounders because they could be considered as intermediary factors in the causal pathway between ACE I/D and CVD.

Like many epidemiologic studies that attempt to reveal associations between certain genes and health outcomes, this study did not employ haplotypes and did not examine gene-gene interactions.

The study design was appropriate and economical; genotyping was done on a pre-existing cohort. The retrospective design saved the time and cost that is usually associated with prolonged follow-up periods, especially for such a large sample size. The data analysis was comprehensive, and the authors did investigate a gap in the li tera ture by including smoking as an effect modifier.

With considerable caution, we can infer that if the ACE deletion polymorphism does have an effect on CVD mortality, it would be when the subject is a middle-aged, light smoker whose genotype is DD. Additional studies are needed to confirm the significant association between ACE gene polymorphisms and CVD mortality among young smokers.

Census 2000 data show that the approximate percentage of Americans who are 68 years old and below is 87.5% 13; the estimated 28% who have the DD genotype might be at an increased risk of CVD if they smoke. However, smoking is a major risk factor for CVD regardless of genotype, the results of this study do not have immediate public health implications.