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

Ge, D, J Huang, J He, B Li, X Duan, R Chen, and D Gu. B₂-Adrenergic receptor gene variations associated with stage-2 hypertension in Northern Han Chinese. Annals of Human Genetics 2005;69:36-44.

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 ADRB2 variants
2. Association of ADRB2 polymorphisms with stage-2 hypertension
3. Linkage disequilibrium among variants

Study Hypothesis:
Sequence at -47C/T, Arg16/Gly, Gln27/Glu polymorphi c loci of ADRB2 gene affects risk of stage-2 hypertension among Han Chinese population residing in Northern China .

Null Hypotheses for Statistical Testing:
Proportions of -47C/T genotypes are same among cases and controls
Proportions of Arg16/Gly genotypes are same among cases and controls
Proportions of Gln27/Glu genotypes are same among cases and controls

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:  Beta-2-adrenergic receptor (ADRB2)
2. Chromosome location: 5q32-34
3. Gene product: Beta-2 adrenergic receptors are important in a number of physiologic processes including: (1) vasodilation in cardiovascular system; (2) bronchodilation in bronchial smooth muscles; (3) energy metabolism such as diet-induced thermogenesis (to prevent diet-induced obesity).
4. Alleles studied and Rationale: The subjects of this study are three polymorphisms in the intronless human ADRB2 gene: C and T alleles at -47C/T polymorphism; Arg16 and Gly16 alleles at Arg16/Gly polymorphism; and Gln27 and Glu27 alleles at Gln27/Glu polymorphism. The transition from T to C at -47 may alter the expression level of the beta-2 adrenergic receptor because the nucleotide substitution at -47 results in a Cys-to-Arg exchange at the C terminal of the leader peptide. Decreased expression may impair responsiveness to beta agonist and impair vasodilation. Obesity is a known risk factor for hypertension, and it has been reported that the C variant allele frequency is significantly higher in obese subjects than in nonobese subjects (0.18 vs 0.11; p = 0.0026).

   The Gly16 allele has been associated in some studies with susceptibility to nocturnal asthma, possibly due to excessive agonist-induced downregulation. Excessive downregulation may impair vasodilation and contribute to the association of Gly16 with hypertension in some populations; however, there is conflicting findings regarding this association.

   Glu27 allele variant has been implicated in impaired exercise-induced

   sympathetic system activity (possibly limiting the utility of exercise in such individuals) and associated with increased Body Mass Index (BMI).
5. OMIM# : +109690
6. Go to GDPInfo Genes A-Z result

The following environmental factors are not the focus of the study but are characterized for each of the participants:

• BMI
• Total cholesterol
• HDL-cholesterol
• LDL-cholesterol
• Triglyceride
• Glucose
• Creatinine
• History of smoking

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

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

1. Case-control Study

The cases and controls are unrelated individuals identified through three field centers of InterASIA (International Collaborative Study of Cardiovascular Disease in Asia ). This population has a high prevalence of hypertension.

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

1. Disease case definition: The definition of Stage-2 hypertension conforms to the latest definitions by the seventh report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure (JNC 7) as follows: Normal(previously considered optimal) when systolic <120 mmHg and diastolic <80; Prehypertension (new category, previously considered normal/high normal) when systolic 120-139 or diastolic 80-89; Stage 1 Hypertension when systolic 140-159 or diastolic 90-99; and Stage 2 Hypertension when systolic >160 or diastolic >100 (encompasses former stages 2 and 3).

   Disease case definition is predicated on accurate blood pressure measurements, which were performed three times by trained and certified observers. Authors calculated adjusted blood pressures which take into account the intake of medications.

2. Exclusion criteria: Secondary hypertension, CHD, diabetes
3. Gender: 262 male; 241 female
4. Race/ethnicity: Han Chinese
5. Age: mean 53.5 +/- 9.3(35-74 eligible)
6. Time period: Not clearly stated; circa 2001-2002
7. Geographic location: Jilin, Beijing and Shandong regions in Northern China
8. Number of participants: 503 cases from a pool of 15,838 persons who completed a survey and an examination. Stated that "all hypertensive subjects" meeting the blood pressure criteria were recruited, but the actual percentage of eligible individuals enrolled is not clear.

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: Unrelated individuals with systolic BP<140 and diatolic blood pressure <90 selected from three northern field centers of interASIA from the same initial pool of 15,838 persons who completed a survey and an examination.

   With recent addition of the "Prehypertension" category, the threshold used in the study is too high by today's standards. Because the mean systolic and diastolic blood pressures of the controls are reported to be 117.58 +/- 11.65, and 75.08 +/- 7.96, respectively, it appears that some control subjects indeed fall into the category of "Prehypertension".

2. Matching variables: Age, gender and area of residence
3. Exclusion criteria: Presence of hypertension of any degree, in addition to exclusion criteria listed for cases.
4. Gender: 263 male; 241 females
5. Race/ethnicity: same as for cases
6. Age: 53.67 +/- 9.18
7. Time period: concurrent with study of cases
8. Geographic location: same as for cases
9. Number of participants: 504 controls.

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: Not applicable
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)

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

1. Environmental factor: Not the focus of the study, but there are baseline differences in exposures to various environmental risk factors for the outcome variable among the cases and controls.
2. Exposure assessment: blood tests and history
3. Exposure definition: Smoking defined as having smoked more than 100 cigarettes; alcohol consumption defined as having drunk alcohol more than 12 times during the preceding year.

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

1. Gene: B 2-Adrenergic Receptor (ADRB2)
2. DNA source: Not stated
3. Genotyping method: PCR-RFLP, along with two references, is stated as the method used for genotyping; otherwise, the paper does not include any information about the method. Hardy Weinberg equilibrium checked.
4. Number of participants genotyped: 1007 (100% of studied)

Analysis
Comment on the analysis carried out by the author(s), e.g. matching, modeling or statistical tests used. Were the analyses appropriate?

Data Presentation and Analyses:

(1) Table 1 compares demographic characteristics, clinical features, and habits of cases and controls. The mean systolic blood pressure among cases and control subjects are 177.07 +28.05 mmHg and 117.58 +11.65 mmHg, respectively. There is no significant difference regarding age, gender, LDL-C level, history of cigarette or alcohol consumption. However, BMI, total cholesterol, triglyceride, glucose, and creatinine are significantly higher among cases. Furthermore, HDL-C is lower among cases.

(2) Polymorphisms at -47C/T, Arg16/Gly, and Gln27/Glu in the ADRB2 gene are genotyped by PCR-RFLP and tabulated in Table 2. The paper names but does not describe the genotyping method. There is no information about the primer sequences, thermocycling program, any use of internal controls or repeated assays, whether the test result is judged visually (if so, whether the observer is blinded to the blood pressure of the individual to which the sample belongs), or any quality control measures.

(3) Univariate analyses are performed on genotype data, and chi-square statistics measure association of each of the three polymorphisms with the outcome variable (presence or absence of stage-2 hypertension).

(4) Backward stepwise regression is used to explore contributions of a host of predictor variables (genotype data, clinical and demographic information) to the outcome variable (presence or absence of hypertension). The full model in this case assumes that the presence of hypertension is predicted by all the characteristics listed in Table 1 as well as genotype at the three polymorphic loci. The reduced model typically omits various predictors or covariates.

(5) Authors measure association of genotype with actual blood pressure (using blood pressure as a continuous dependent variable instead of hypertension status as a dichotomous dependent variable) in multivariate analysis (containing other covariates). ANCOVA is used to compare mean blood pressures of each ADRB2 genotype (Table 3).

(6) The study does not have genotypes of the parents, and therefore the phase of the genotype data is unknown. EH/EH+ softwareis used togenerate estimates of haplotype frequencies based on observed allele frequencies and genotype data. Table 4 compares estimated haplotype frequencies between cases and controls. Likelihood ratio and chi-square statistics were calculated for various comparisons of estimated haplotype frequency among cases and controls.

(7) Pairwise linkage disequilibrium, the extent of disequilibrium, and haplotype frequencies for different polymorphism combinations were determined by 2LD and EH/EH+ softwares. Lastly, omnibus likelihood ratio test was used to examine the differences in haplotype frequency profiles between the cases and the controls.

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

Tabulation of Genotype Frequencies of 3 ADRB2 Polymorphisms in Cases and Controls and calculated Chi Square statistics:

(1) no difference in frequency of C allele among groups, suggesting no association of -47C/T polymorphism with hypertension;
(2) among cases, there are more individuals homozygous or heterozygous for Gly16 alleles, suggesting an association of Arg16/Gly with hypertension (p <.05);
(3) among cases, there are more individuals with Gln27 allele mainly due to higher percentage of cases homozygous for Gln27 (p<.001).

Note amino acid abbreviations:
G=gly, R=arg, E=glu, Q=gln

Determine if Genotype is a Predictor of Hypertension Status (dichotomous variable) by Stepwise Logistic Regression Analysis:

(1) significant positive contribution from Gly16 allele (OR=1.46, 95% C.I. of 1.11-1.93);

(2) significant negative contribution from Gln27 allele (OR=.42, 95% C.I. of .28-.62).

(3) however, genotypes at Arg16/Gly and Gln27/Glu do not predict hypertension completely as BMI, glucose, triglyceride, creatinine, and drinking status were found to contribute to prediction using models already incorporating Arg16/Gly and Gln27/Glu genotypes.

There is no data on allele or genotype frequencies at the population level.

Population allele frequencies as estimated by allele frequencies (%) among controls:

• C allele: 11.3; T allele: 88.7
• Gly allele: 38.6; Arg allele: 61.4
• Glu allele: 9.9; Gln allele: 90.1

--Therefore, the most highly associated alleles in this study, Gly16 and Gln27, are highly prevalent in the population. Thus, disease penetrance of these alleles appears to be low, as expected in multigenic disorders.

Determine if Genotype is a Predictor of Blood Pressure (continous variable)

The mean systolic blood pressures (SBP) of genotypes associated with the Arg16/Gly polymorphic locus as follows:

(1) Gly/Gly 150.25 +/- 36.3 mmHg
(2) Gly/Arg 149.49 +/- 36.6 mmHg
(3) Arg/Arg 142.98 +/- 36.7 mmHg

--Multivariate analysis of above shows significant difference (p=.025).

--The mean blood pressure for Gly16 homozygote (Gly/Gly) is not statistically different from Gly16 heterozygote (Gly/Arg). Hence, there does not appear to be a dose effect.

The mean SBP of genotypes associated with the Gln27/Glu polymorphic locus are as follows:

(1) Glu/Glu and Glu/Gln combined 136.25 +/- 30.5 mmHg
(2) Gln/Gln 149.1 +/- 37.3 mmHg

--The above difference is significant (p < .001)

--The mean blood pressure of the Glu/Glu and Glu/Gln were combined when compared to Gln/Gln. However, Table 2 shows that the odds ratios of Glu homo- and heterozygotes are 1.20 and .40, respectively (relative to the Gln/Gln referent group), which is not consistent with a gene dose effect.

Implications of Findings for Underlying Population

Genotypes with significantly elevated blood pressures are Gly/Gly, Gly/Arg, and Gln/Gln. The prevalence of these genotypes is not known but may be estimated by prevalence in the control group (%) as follows:

• Gly/Gly (G/G): 17.06
• Gly/Arg (G/R): 43.06
• Gln/Gln (Q/Q): 81.34
• Gln/Glu (Q/E): 8.9
• Glu/Glu (E/E): .98

However, the estimates above may not be valid because genotypes at the Arg16/Gly site may not be in Hardy Weinberg equilibrium (see below).

Estimation of Attributable Risk Fraction for hypertension due to Gly16 -containing genotypes or Gln27 homozygosity.

Ordinarily, Attributable Risk Fraction (ARF) can be calculated based on odds ratio of a particular genotype and the estimated prevalence of the genotype in the population. However, such calculations are probably not valid in this case because the association of these polymorphisms with hypertension remains questionable despite the present study, "penetrance" of the culpable genotypes seems far from complete, the definition of control group is problematic, and Hardy Weinberg equilibrium (HWE) may not be present (see below).

Determine if genotype distribution follow Hardy Weinberg Equilibrium

Determine if Haplotype Data Improve Prediction of Hypertension

The haplotype frequencies shown in Table 4 are calculated based on allele frequencies reported in Table 2. The authors noted that:

(1) The -47C/T and Arg16/Gly polymorphisms has the largest LD coefficient (D`=.66, p<.0001).
(2) T-Gly is preferrentially linked to Gln in cases and to Glu in controls.
(3) C/C and Glu/Glu are preferentially linked to Gly/Gly.
(4) There is linkage disequilibrium between any of the two polymorphism combinations.

Given the uncertainty of HWE equilibrium in both cases and controls, it may not be legitimate to estimate haplotype frequencies based on allele frequencies.

Cautionary Note Regarding Inference:

The genotyping method is not well documented and the definition of hypertension has shifted, introducing potential error in inferences drawn from the results of this study.

Authors concluded that the frequencies of Gly16 and Gln27 alleles of ADRB2 are significantly higher in hypertension cases than in controls, and that these variants confer an increased risk for stage-2 hypertension in northern Han Chinese population.

Limitations:

• Some subjects belonging to the 'control' group in the study almost certainly fall into the 'prehypertension' category by the current standard.
• There are significant differences in baseline characteristics in cases vs. controls regarding total cholesterol, HDL cholesterol, BMI, triglycerides, glucose, and creatinine. The last four factors listed are associated with significant p values in regression models. Potential gene-environment interactions were not examined.
• Documentation of genotyping methodology and quality control are lacking.
• There is a concern for accuracy of genotyping for the following reasons: The Arg16/Gly and Gln27/Glu polymorphisms were not in Hardy Weinberg equilibrium (HWE) among controls and cases, respectively; however, the -47C/T polymorphism, which is in linkage disequilibrium with the other two, was in HWE.
• The authors' conclusion that the estimated haplotype frequencies in Table 4 substantiate the findings based on genotypes (Table 2) is problematic because the former does not represent independent data. Furthermore, such calculations may not be valid in the absence of HWE.
• Haplotypes could have been established independently by sequencing PCR products.
• The paper does not address gene-environment interactions and only speculated as to whether Gly16 variation impacts salt sensitivity.
• There is no supporting biochemical or other data to indicate that polymorphisms observed are associated with dysregulation of BAR levels or functions. The association with Gly16 or Gln27 does not necessarily implicate these variations as causative because they may merely be in linkage disequilibrium with the real disease gene.

Future studies suggested:

It may be beneficial for future studies to define cases based on age-adjusted distribution of blood pressure rather than an overall threshold. The use of DNA microarrays, instead of examing polymorphisms in single genes, is likely to add power to detective works regarding gene-disease associations.