An empirical comparison of meta-analyses of published gene-disease associations versus consortium analyses

A systematic analysis of the association studies between CASP8 D302H polymorphisms and breast cancer risk

Caspase 8 (CASP8) is a regulator of apoptosis, whose genetic variation has been reported to be associated with the risk of various cancers. Especially, the single-nucleotide polymorphism (SNP) rs1045485, which generates the substitution D302H in CASP8, is likely to be associated with breast cancer. Several previous studies have reported the association of CASP8 D302H polymorphism with breast cancer; however, the results are inconsistent. To validate the association between CASP8 D302H polymorphism and breast cancer risk, we performed an updated meta-analysis of 18 studies including 27,807 cases and 32,332 controls. We tested the overall association between this SNP and breast cancer susceptibility and stratified subgroups based on countries where cases are from. We confirmed a significant correlation between CASP8 D302H polymorphism and the reduced breast cancer susceptibility in population from UK, Germany and Poland, but no significant association was observed in other countries, such as Finland or USA. Our findings indicate the relationship of SNP CASP8 D302H and breast cancer would not be universal but only be sensitive in some particular European countries. The genetic difference for diverse countries may be useful in individual and precision medicine or health.

A systematic review of cancer GWAS and candidate gene meta-analyses reveals limited overlap but similar effect sizes

Candidate gene and genome-wide association studies (GWAS) represent two complementary approaches to uncovering genetic contributions to common diseases. We systematically reviewed the contributions of these approaches to our knowledge of genetic associations with cancer risk by analyzing the data in the Cancer Genome-wide Association and Meta Analyses database (Cancer GAMAdb). The database catalogs studies published since January 1, 2000, by study and cancer type. In all, we found that meta-analyses and pooled analyses of candidate genes reported 349 statistically significant associations and GWAS reported 269, for a total of 577 unique associations. Only 41 (7.1%) associations were reported in both candidate gene meta-analyses and GWAS, usually with similar effect sizes. When considering only noteworthy associations (defined as those with false-positive report probabilities≤0.2) and accounting for indirect overlap, we found 202 associations, with 27 of those appearing in both meta-analyses and GWAS. Our findings suggest that meta-analyses of well-conducted candidate gene studies may continue to add to our understanding of the genetic associations in the post-GWAS era.

Genome-based prediction of breast cancer risk in the general population: a modeling study based on meta-analyses of genetic associations

BACKGROUND

Genome-wide association studies identified novel breast cancer susceptibility variants that could be used to predict breast cancer in asymptomatic women. This review and modeling study aimed to investigate the current and potential predictive performance of genetic risk models.

METHODS

Genotypes and disease status were simulated for a population of 10,000 women. Genetic risk models were constructed from polymorphisms from meta-analysis including, in separate scenarios, all polymorphisms or statistically significant polymorphisms only. We additionally investigated the magnitude of the odds ratios (OR) for 1 to 100 hypothetical polymorphisms that would be needed to achieve similar discriminative accuracy as available prediction models [modeled range of area under the receiver operating characteristic curve (AUC) 0.70-0.80].

RESULTS

Of the 96 polymorphisms that had been investigated in meta-analyses, 41 showed significant associations. AUC was 0.68 for the genetic risk model based on all 96 polymorphisms and 0.67 for the 41 significant polymorphisms. Addition of 50 additional variants, each with risk allele frequencies of 0.30, requires per-allele ORs of 1.2 to increase this AUC to 0.70, 1.3 to increase AUC to 0.75, and 1.5 to increase AUC to 0.80. To achieve AUC of 0.80, even 100 additional variants would need per-allele ORs of 1.3 to 1.7, depending on risk allele frequencies.

CONCLUSION

The predictive ability of genetic risk models in breast cancer has the potential to become comparable to that of current breast cancer risk models.

IMPACT

Risk prediction based on low susceptibility variants becomes a realistic tool in prevention of nonfamilial breast cancer.

Assessment of cumulative evidence for the association between glutathione S-transferase polymorphisms and lung cancer: application of the Venice interim guidelines

OBJECTIVE

There is an overwhelming abundance of genetic association studies available in the literature, which can often be collectively difficult to interpret. To address this issue, the Venice interim guidelines were established for determining the credibility of the cumulative evidence. The objective of this report is to evaluate the literature on the association of common glutathione S-transferase (GST) variants (GSTM1 null, GSTT1 null and GSTP1 Ile105Val polymorphism) and lung cancer, and to assess the credibility of the associations using the newly proposed cumulative evidence guidelines.

METHODS

Information from the literature was enriched with an updated meta-analysis and a pooled analysis using data from the Genetic Susceptibility to Environmental Carcinogens database.

RESULTS

There was a significant association between GSTM1 null and lung cancer for the meta-analysis (meta odds ratio=1.17, 95% confidence interval: 1.10-1.25) and pooled analysis (adjusted odds ratio=1.10, 95% confidence interval: 1.04-1.16), although substantial heterogeneity was present. No overall association between lung cancer and GSTT1 null or GSTP1 Ile105Val was found. When the Venice criteria was applied, cumulative evidence for all associations were considered 'weak', with the exception of East Asian carriers of the G allele of GSTP1 Ile105Val, which was graded as 'moderate' evidence.

CONCLUSION

Despite the large amounts of studies, and several statistically significant summary estimates produced by meta-analyses, the application of the Venice criteria suggests extensive heterogeneity and susceptibility to bias for the studies on association of common genetic polymorphisms, such as with GST variants and lung cancer.

Transforming growth factor-beta1 polymorphisms and breast cancer risk: a meta-analysis based on 27 case-control studies

The association between transforming growth factor-beta1 (TGF-beta1) gene polymorphisms and breast cancer risk has been widely reported, but results were somewhat controversial and underpowered. To derive a more precise estimation of the relationship between TGF-beta1 polymorphisms and breast cancer risk, we conducted a meta-analysis of all available case-control studies relating the T869C and/or C-509T polymorphisms of the TGF-beta1 gene to the risk of developing breast cancer. Eligible articles were identified by search of databases including MEDLINE, PubMed, Web of Science, EMBASE, and Chinese Biomedical Literature database (CBM) for the period up to March 2010. Finally, a total of 17 articles involving 27 case-control studies were identified, 25 with 20,022 cases and 24,423 controls for T869C polymorphism and eight with 10,633 cases and 13,648 controls for C-509T polymorphism. The pooled ORs were performed for the allele contrasts, additive genetic model, dominant genetic model and recessive genetic model, respectively. Subgroup analysis was also performed by ethnicity for T869C polymorphism. With respect to T869C polymorphism, no association was found in overall analysis (C vs. T: OR = 1.033, 95% CI = 0.996-1.072). In the subgroup analysis by ethnicity, significantly increased risk was found in Caucasian population (C vs. T: OR = 1.051, 95% CI = 1.018-1.085; CC vs. TT + TC: OR = 1.083, 95% CI = 1.019-1.151), but not in Asian population (C vs. T: OR = 1.054, 95% CI = 0.983-1.130). With respect to C-509T polymorphism, no significant association with breast cancer risk was demonstrated in overall analysis (T vs. C: OR = 0.986, 95% CI = 0.936-1.039). It can be concluded that potentially functional TGF-Beta1 T869C polymorphism may play a low penetrance role in breast cancer susceptibility in an ethnicity-specific manner.