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PubMed2004

Beta2 adrenergic receptor gene Arg16Gly polymorphism is associated with therapeutic efficacy of benazepril on essential hypertension in Chinese.

BACKGROUND: There is considerable variability in individual response to antihypertensive agents. The reason for this is not known, but may be related to individual genetic variability. This study examined whether the therapeutic efficacy of benazepril on essential hypertension is modified by beta2 adrenergic receptor gene (ADRB2) Arg16Gly (R16G) polymorphism. METHODS AND RESULTS: We conducted a family-based study of 321 and 610 hypertensive subjects from Yuexi and Huoqiu Counties of Anhui, China, respectively. Both systolic and diastolic blood pressures (SBP and DBP) before and after a 15-day benazepril treatment were measured. ADRB2 R16G genotypes were determined for all subjects. ADRB2 G16 allele frequency was found to be 41.0% and. 47.4% in Huoqiu and Yuexi, respectively. In Yuexi family-based association test (FBAT) revealed that the G16 allele was associated with a greater DBP decrease in response to a 15-day benazepril treatment (Z = 2.12, P = 0.03), and the data were consistent with a dominant inheritance model. A similar trend was observed in Huoqiu Chinese, but the magnitudes of effects were smaller and did not reach statistical significance. The FBAT results were further confirmed by using a generalized estimating equation model. CONCLUSION: Our family-based study provided the first evidence that ADRB2 R16G polymorphism may play an important role in DBP response to benazepril treatment, although the magnitude of the effect appears to be modified by other risk factors such as plasma lipid and glucose profiles.

Adult↗

PubMed2004

Incorporating individual error rate into association test of unmatched case-control design.

OBJECTIVES: Genotyping error commonly occurs and could reduce the power and bias statistical inference in genetics studies. In addition to genotypes, some automated biotechnologies also provide quality measurement of each individual genotype. We studied the relationship between the quality measurement and genotyping error rate. Furthermore, we propose two association tests incorporating the genotyping quality information with the goal to improve statistical power and inference. METHODS: 50 pairs of DNA sample duplicates were typed for 232 SNPs by BeadArray technology. We used scatter plot, smoothing function and generalized additive models to investigate the relationship between genotype quality score (q) and inconsistency rate (ĩ) among duplicates. We constructed two association tests: (1) weighted contingency table test (WCT) and (2) likelihood ratio test (LRT) to incorporate individual genotype error rate (epsilon(i)), in unmatched case-control setting. RESULTS: In the 50 duplicates, we found q and ĩ were in strong negative association, suggesting the genotypes with low quality score were more likely to be mistyped. The WCT improved the statistical power and partially corrects the bias in point estimation. The LRT offered moderate power gain, but was able to correct the bias in odds ratio estimation. The two new methods also performed favorably in some scenarios when epsilon(i) was mis-specified. CONCLUSIONS: With increasing number of genetic studies and application of automated genotyping technology, there is a growing need to adequately account for individual genotype error rate in statistical analysis. Our study represents an initial step to address this need and points out a promising direction for further research.

Case-Control Studies↗