The association of A1513C (rs3751143) polymorphism of P2X7 gene with the risk of extrapulmonary tuberculosis (EPTB) has been extensively analyzed, but no consensus has been achieved. In this study, a meta-analysis was done to assess this precise association. Online web databases, like PubMed (MEDLINE) and EMBASE were searched for pertinent reports showing association of P2X7 A1513C polymorphism with EPTB risk. To assess the strength of this association, we calculated pooled odds ratios (ORs) and 95% confidence intervals (95% CIs). A total of eight reports involving 2237controls and 594 EPTB cases were included in this study. Four genetic models, viz. allele (C vs. A: p=0.011; OR= 1.677, 95% CI = 1.125-2.501), homozygous (CC vs. AA: p = 0.053; OR= 2.362, 95% CI = 0.991-5.632), heterozygous (AC vs. AA: p = 0.003; OR= 1.775, 95% CI = 1.209-2.607) and dominant (CC + AC vs. AA: p = 0.005; OR= 1.890, 95% CI = 1.207-2.962) showed significant associations compared with wild type genotypes. Subgroup analysis stratified by ethnicity was also performed and the results suggested that homozygous and heterozygous genotypes were associated significantly with increased susceptibility of EPTB in Asian population. Similarly, heterozygous and dominant models showed increased EPTB risk in Caucasian population. The present meta-analysis suggests that P2X7 A1513C polymorphism may be an important risk factor for EPTB. Also, our sub-group analysis indicates that P2X7 A1513C polymorphism confers increased EPTB risk among Asians and Caucasians. However, future larger studies are needed to provide more precise conclusion and endorse the present results.

This review aimed to arrange the process of a systematic review of genome-wide association studies in order to practice and apply a genome-wide meta-analysis (GWMA). The process has a series of five steps: searching and selection, extraction of related information, evaluation of validity, meta-analysis by type of genetic model, and evaluation of heterogeneity. In contrast to intervention meta-analyses, GWMA has to evaluate the Hardy-Weinberg equilibrium (HWE) in the third step and conduct meta-analyses by five potential genetic models, including dominant, recessive, homozygote contrast, heterozygote contrast, and allelic contrast in the fourth step. The \'genhwcci\' and \'metan\' commands of STATA software evaluate the HWE and calculate a summary effect size, respectively. A meta-regression using the \'metareg\' command of STATA should be conducted to evaluate related factors of heterogeneities.

Using the conditional likelihood, a model-specific score test can be derived under a given genetic model to test genetic association for case-parents triad family data. When the underlying genetic model is correctly specified, the score test is most powerful. However, it can lose substantial power when the model is misspecified. Several robust tests have been proposed to deal with the problem, such as the maximum test statistic, the maximin efficiency robust test, and the constrained likelihood ratio test. These tests have been shown to be robust against model misspecification compared with those model-specific score tests, but they are either time-consuming in computation or not sufficiently high in power robustness under some situations. In this study, a data-driven procedure is proposed to construct two adaptive robust genetic association tests WMERT and WMAX . The WMERT is simple in calculation and has fairly high power robustness. The empirical power of WMAX is quite stable and close to those of the model-specific score tests. The two proposed tests should be beneficial to practical genetic association studies. A real dataset consisting of neural tube defect triad families is used for illustration of the methods. R-scripts are also provided for numerical calculation of the proposed methods in practical studies.