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An empirical comparison of meta-analyses of published gene-disease associations versus consortium analyses
Abstract
Consortia of investigators currently compile sufficiently large sample sizes to investigate the effects of low-risk susceptibility genetic variants. It is not clear how the results obtained by consortia compare with those derived from meta-analyses of published studies.
We performed meta-analyses of published data for 16 genetic polymorphisms investigated by the Breast Cancer Association Consortium, and compared sample sizes, heterogeneity, and effect sizes. PubMed, Web of Science, and Human Genome Epidemiology Network databases were searched for breast cancer case-control association studies.
We found that meta-analyses of published data and consortium analyses were based on substantially different data. Published data by non-consortium teams amounted on average to 26.9% of all available data (range 3.0 -50.0%). Both approaches showed statistically significant decreased breast cancer risks for CASP8 D302H. The meta-analyses of published data demonstrated statistically significant results for five other genes and the consortium analyses for two other genes, but the strength of this evidence, evaluated on the basis of the Venice criteria, was not strong.
Because both approaches identified the same gene out of 16 candidates, the methods can be complimentary. The expense and complexity of consortium-based studies should be considered vis-à-vis the potential methodological limitations of synthesis of published studies.
... On the other hand, there is relative unanimity regarding CASP8 D302H polymorphism. Two studies have reported a protective effect of the polymorphism [3, 5], which has been confirmed by a recent critical meta-analysis [13] ; nevertheless , the majority of data come from the Breast Cancer Association Consortium [5] , which seems to have established the protective action. Since then two studies have appeared [6, 14]; Palanca Suela et al. were in accordance with the protective effect, whereas Sigurdson et al. limited the effect of CASP8 D302H on homozygous carriers. ...
... Analyses were conducted using STATA 10.0 (STATA Corp. College Station, TX, USA) and metaanalysis was performed using the ''metan'' command.Figure 1 graphically illustrates the trial flow chart. Out of the 30 abstracts retrieved through the search criteria, 17 studies were irrelevant, two studies were excluded due to the fact that they did not report the allele frequencies [14, 18], and two articles were meta-analyses [4, 13]. As a result, nine case–control studies were included in this metaanalysis ; five of them pertained to the -652 6N del polymorphism (12,439 breast cancer cases, 13,253 controls), and four of them concerned D302H polymorphism (18,791 breast cancer cases, 20,318 controls). ...
... Indeed, the underpowered character of individual studies may have accounted for the fact that none of them was able per se to reach statistical significance, although all of them pointed to the same, protective direction; the protective effect became thus evident solely at the meta-analytical level. Concerning CASP8 D302H, this meta-analysis is in accordance with previous ones [4, 13], which had been performed on a smaller number of studies. It is worth mentioning, however, that the lack of studies on Chinese women does not permit the safe extrapolation of findings onto the former race. ...
Caspase-8 (CASP8) is an initiator caspase implicated in the process of apoptosis in breast cancer cells. Attention has been drawn upon two polymorphisms: CASP8 D302H (rs1045485) and, more recently, CASP8 -652 6N del (rs3834129). The CASP8 -652 6N del polymorphism remains an open field, as studies are controversial. This meta-analysis aims to examine: (i) the association between CASP8 -652 6N del and breast cancer risk, separately in Chinese and Caucasian populations, and (ii) the association between CASP8 D302H and breast cancer risk. Eligible articles were identified by a search of MEDLINE, Cochrane, and EMBASE bibliographical databases for the period from June 1996 to July 2009. Regarding -652 6N del, five case-control studies were eligible (12,439 breast cancer cases, 13,253 controls) and four case-control studies were eligible for D302H (18,791 breast cancer cases, 20,318 controls). In case significant heterogeneity was detected, the random effects model was chosen; nevertheless, the fixed effects estimates are also secondarily reported as an alternative approach. Where appropriate, power calculations were performed. CASP8 -652 6N del was associated with reduced breast cancer risk at a borderline level (for del carriers: pooled OR = 0.884, 95% CI: 0.761-1.028); the power calculation pointed to lack of power in the individual studies. In the Caucasian populations, the same results seem valid (for del carriers: pooled OR = 0.944, 95% CI: 0.884-1.008). The random effects model in Chinese subjects has not reached statistical significance (for del carriers: pooled OR = 0.811, 95% CI: 0.492-1.338). CASP8 D302H was associated with reduced breast cancer risk (for H carriers: pooled OR = 0.874, 95% CI: 0.834-0.917). In conclusion, both CASP8 -652 6N del and D302H polymorphisms are associated with reduced cancer risk. Further studies are needed to gain the optimal power on -652 6N del, especially in Chinese subjects, as well as to gain insight into D302H in Chinese populations.
... Meta-analysis of GWAS using summary statistics, in contrast to direct analysis of pooled individual-level data, diminishes the limitations that are imposed by restrictions on sharing individual-level data. Empirical findings (Janssens et al., 2009) suggest that using time-consuming individual data methods for meta-analysis of GWAS does not necessarily lead to increase efficiency (Lin and Zeng, 2010a,b) and thus, summary methods are routinely used for meta-analyses of GWAS (de Bakker et al., 2008;Magi and Morris, 2010;Willer et al., 2010). ...
Motivation:
In the context of genome-wide association studies (GWAS), there is a variety of statistical techniques in order to conduct the analysis, but, in most cases, the underlying genetic model is usually unknown. Under these circumstances, the classical Cochran-Armitage trend test is suboptimal. Robust procedures that maximize the power and preserve the nominal type I error rate are preferable. Moreover, performing a meta-analysis using robust procedures is of great interest and has never been addressed in the past. The primary goal of this work is to implement several robust methods for analysis and meta-analysis in the statistical package Stata and subsequently to make the software available to the scientific community.
Results:
The Cochran-Armitage trend test under a recessive, additive and dominant model of inheritance as well as robust methods based on the MERT statistic, the MAX statistic and the MIN2 were implemented in Stata. Concerning MAX and MIN2, we calculated their asymptotic null distributions relying on numerical integration resulting in a great gain in computational time without losing accuracy. All the aforementioned approaches were employed in a fixed or a random effects meta-analysis setting using summary data with weights equal to the reciprocal of the combined cases and controls. Overall, this is the first complete effort to implement procedures for analysis and meta-analysis in GWAS using Stata.
Availability:
A Stata program and a web-server are freely available for academic users at http://www.compgen.org/tools/GWAR CONTACT: pbagos@compgen.org.
... More specifically, a six nucleotide deletion polymorphism (-652 6N del) has been identified in the promoter region of the CASP8 gene and is associated with decreased RNA expression in lymphocytes due to the altering of an Sp1 binding site. 20 This variant has been found to decrease CASP8 activity and apoptotic reactivity of T lymphocytes through the cancer cell ex vivo model. Recently, due to the functional significance of the CASP8 -652 6N del variant, genetic variants of the CASP8 gene in the aetiology of several cancers have drawn increasing attention. ...
Purpose:
Many studies have investigated the association between CASP8-652 6N del polymorphism and the risk of breast cancer, but the result is still unclear owing to the obvious inconsistence among those studies. This study aims to quantify the strength of association between CASP8-652 6N del polymorphism and risk of breast cancer.
Methods:
We searched the electronic MEDLINE database for studies relating to the association between CASP8-652 6N del polymorphism and risk of breast cancer. We estimated summary odds ratios (ORs) with their 95% confidence intervals (95% CIs) to assess the association. Ten case-control studies with 13,220 cases and 13,750 controls were included into this meta-analysis.
Results:
Meta-analysis of a total of ten studies showed that reduced breast cancer risk was associated with CASP8 -652 6N del polymorphism (homozygous: OR=0.85, 95% CI 0.93-0.98). After adjustment for heterogeneity, meta-analysis showed that reduced breast cancer risk was also associated with CASP8-652 6N del polymorphism (homozygous: OR=0.78, 95% CI 0.63-0.95, dominant: OR=0.93, 95% CI 0.88-0.99). For Caucasians, CASP8-652 6N del was associated with reduced breast cancer risk at a borderline level (homozygous: OR=0.94, 95% CI 0.86-1.02, heterozygous: OR=0.96, 95% CI 0.90-1.03, recessive: OR=0.96, 95% CI 0.90-1.03, dominant: OR=0.94, 95% CI 0.88-1.01). No evidence of publication bias was observed.
Conclusion:
Meta-analyses of the available data suggest that CASP8 -652 6N del polymorphism is associated with reduced breast cancer risk.
... One aspect emerging from our exercise is the good correspondence of the results obtained with the meta-and respective pooled (individual-level) analyses. These two approaches have different principles, strengths, and limitations and may not always agree in their results [134]. For some analyses, such as those restricted to populations of African descent, the pooled analysis offered the appropriate data that were missing in the meta-analysis, thus allowing the drawing of a more complete picture. ...
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.
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.
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.
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.
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.
There are several user-written programs for performing meta-analysis in Stata (Stata Statistical Software: College Station, TX: Stata Corp LP). These include metan, metareg, mvmeta, and glst. However, there are several cases for which these programs do not suffice. For instance, there is no software for performing univariate meta-analysis with correlated estimates, for multilevel or hierarchical meta-analysis, or for meta-analysis of longitudinal data. In this work, we show with practical applications that many disparate models, including but not limited to the ones mentioned earlier, can be fitted using gllamm. The software is very versatile and can handle a wide variety of models with applications in a wide range of disciplines. The method presented here takes advantage of these modeling capabilities and makes use of appropriate transformations, based on the Cholesky decomposition of the inverse of the covariance matrix, known as generalized least squares, in order to handle correlated data. The models described earlier can be thought of as special instances of a general linear mixed-model formulation, but to the author's knowledge, a general exposition in order to incorporate all the available models for meta-analysis as special cases and the instructions to fit them in Stata has not been presented so far. Source code is available at http:www.compgen.org/tools/gllamm. Copyright © 2015 John Wiley & Sons, Ltd.
The brain is by far the most complicated structure of the human being, and its malfunction is
characterized by various degrees and types of morbidity. Several brain functions deteriorate with
increasing age during life. Cognitive decline and age-related brain pathology are common in the
elderly, but these changes may also become manifest early in life and preceding the onset of clinical
symptoms of disease. The detection of early changes may be relevant for therapeutic interventions to
prevent disease, and are therefore also increasingly targeted in genetic research as endophenotypes.
Endophenotypes are defined as heritable phenotypes that are related to the disease of interest, and
are typically approached as quantitative outcomes, i.e., instead of hypertension, the endophenotype
of interest is systolic or diastolic blood pressure. In contrast to classical risk factors in epidemiology,
an endophenotype is by definition not uniquely associated to a single disease. Blood pressure for
example, is consistently associated to various clinically relevant outcomes such as stroke, myocardial
infarction and heart failure. There is an increasing interest in the genetic research of endophenotypes,
and genome-wide association studies of endophenotypes have been very successful. In this
thesis I focus on cognitive function and age-related brain changes early in life as endophenotypes for
late-life brain disease and as targets for early prevention.
Cognitive deterioration can be seen in pre-clinical stages of neurodegenerative and
neuropsychiatric disorders like dementia, schizophrenia, bipolar disorder and attention deficit
hyperactivity disorder (ADHD). Cognitive function is a broad concept referring to multiple
cognitive domains, among which memory, language, executive function and visuospatial ability.
Although the domains are highly correlated, it is known that specific domains are related to
specific diseases. Cognitive function is in part determined by our genetic make-up. The
heritability is estimated to around 40% and there have been various studies that have tried to
identify genes explaining the heritability of cognitive functions. These included candidate gene
studies, linkage studies and genome-wide association studies. The genes
and chromosomal regions that have been found so far are partly explained by genes related
to neuropsychiatric disease, and partly by genes related to dementia and Alzheimer’s disease
(AD) with the Apolipoprotein E gene as genetic factor with one of the strongest effects. In the
studies presented here, we will focus on a cognitive test battery targeting AD. Dementia is
one of the most common causes of morbidity and mortality in the Western society (prevalence
of 25 million cases worldwide), in which Alzheimer disease accounts for over 70% of cases. Regarding the high prevalence and major impact of these diseases, early diagnosis and
treatment strategies have a high priority in neuroscience. Identifying risk factors for cognitive
decline would benefit our increasingly elderly population.
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.European Journal of Human Genetics advance online publication, 24 July 2013; doi:10.1038/ejhg.2013.161.
The association between transforming growth factor-β1 (TGF-β1) 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-β1 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-β1 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-Β1 T869C polymorphism may play a low penetrance
role in breast cancer susceptibility in an ethnicity-specific manner.
Abstract In genetic association studies (GAS) as well as in genome-wide association studies (GWAS), the mode of inheritance (dominant, additive and recessive) is usually not known a priori. Assuming an incorrect mode of inheritance may lead to substantial loss of power, whereas on the other hand, testing all possible models may result in an increased type I error rate. The situation is even more complicated in the meta-analysis of GAS or GWAS, in which individual studies are synthesized to derive an overall estimate. Meta-analysis increases the power to detect weak genotype effects, but heterogeneity and incompatibility between the included studies complicate things further. In this review, we present a comprehensive summary of the statistical methods used for robust analysis and genetic model selection in GAS and GWAS. We then discuss the application of such methods in the context of meta-analysis. We describe the theoretical properties of the various methods and the foundations on which they are based. We also present the available software implementations of the described methods. Finally, since only few of the available robust methods have been applied in the meta-analysis setting, we present some simple extensions that allow robust meta-analysis of GAS and GWAS. Possible extensions and proposals for future work are also discussed.
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.
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].
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.
The predictive ability of genetic risk models in breast cancer has the potential to become comparable to that of current breast cancer risk models.
Risk prediction based on low susceptibility variants becomes a realistic tool in prevention of nonfamilial breast cancer.
Meta-analyses and Individual Patient Data (IPD) meta-analyses of genetic association studies are a powerful tool to summarize the scientific evidences, however their application present considerable potential and several pitfalls. We reviewed systematically all published meta-analyses and IPD meta-analyses of genetic association studies in the field of cancer research, searching for relevant studies on the Medline, Embase, and HuGE Reviews Archive databases until January 2009. The association between selected predictors of methodological quality and the year of publication was also evaluated. 144 meta-analyses involving 299 gene-disease associations, and 25 IPD meta-analyses on 83 gene-disease were included. Overall quality of the reports showed a substantial improvement over time, as authors have become more inclusive of primary papers published in all languages since 2005 (P-value = 0.087), as well as statistical heterogeneity and publication bias were evaluated more systematically. Only 35.4% of the meta-analyses, however, adopted a comprehensive bibliographic search strategy to identify the primary reports, 63.9% did not specify the language of the included studies, 39.8% did not test for Hardy-Weinberg Equilibrium (HWE), while 62.2 and 75.9% of the meta-analyses and IPD meta-analyses, respectively, did not declare the scientific rationale for the genetic model chosen. Additionally, the HWE assessment showed a substantial decreasing trend over time (P-value = 0.031) while publication bias was more often evaluated when statistical heterogeneity was actually present (P-value = 0.007). Although we showed a general methodological improvement over time, guidelines on conducting and reporting meta-analyses of genetic association studies are needed to enhance their methodological quality.
Binding of IGF-1 to the type I IGF receptor starts a signalling cascade that plays an important role in regulating cell proliferation, differentiation and apoptosis. The interaction between the IGF-1 and its receptor is mainly regulated by a binding protein, IGFBP 3. We studied a CA repeat polymorphism 969 bp upstream of the transcription start site in the IGF-1 gene and an A-202 C polymorphism in the IGFBP 3 gene and tested their association with breast cancer risk using four case-control series with a total of 787 cases and 900 controls. We did not find any association between the breast cancer risk and the IGF-1 repeat length (19 versus non-19) or the IGFBP 3 A-202 C polymorphism in the postmenopausal breast cancer series or in women diagnosed for breast cancer under the age of 50. In the familial breast cancer series we observed a non-significantly increased odds-ratio (OR) in homozygotes for the non-19 alleles of the IGF-1 gene (OR 1.51, 95% CI 0.96-2.39, p=0.07). Similarly, in the familial breast cancer series we detected an increased frequency of the IGFBP 3 -202 C allele carriers (OR 1.50, 95% CI 1.05--2.14, p=0.03). The association was stronger in individuals homozygous for these alleles (OR 3.76, 95% CI 1.44-v-9.81, p=0.006). Thus, the polymorphisms in the IGF-1 and IGFBP 3 genes associated with an increased risk of breast cancer in familial cases carrying the variant alleles.
There is increasing evidence that genome-wide association (GWA) studies represent a powerful approach to the identification of genes involved in common human diseases. We describe a joint GWA study (using the Affymetrix GeneChip 500K Mapping Array Set) undertaken in the British population, which has examined 2,000 individuals for each of 7 major diseases and a shared set of 3,000 controls. Case-control comparisons identified 24 independent association signals at P < 5 10-7: 1 in bipolar disorder, 1 in coronary artery disease, 9 in Crohn's disease, 3 in rheumatoid arthritis, 7 in type 1 diabetes and 3 in type 2 diabetes. On the basis of prior findings and replication studies thus-far completed, almost all of these signals reflect genuine susceptibility effects. We observed association at many previously identified loci, and found compelling evidence that some loci confer risk for more than one of the diseases studied. Across all diseases, we identified a large number of further signals (including 58 loci with single-point P values between 10-5 and 5 10-7) likely to yield additional susceptibility loci. The importance of appropriately large samples was confirmed by the modest effect sizes observed at most loci identified. This study thus represents a thorough validation of the GWA approach. It has also demonstrated that careful use of a shared control group represents a safe and effective approach to GWA analyses of multiple disease phenotypes; has generated a genome-wide genotype database for future studies of common diseases in the British population; and shown that, provided individuals with non-European ancestry are excluded, the extent of population stratification in the British population is generally modest. Our findings offer new avenues for exploring the pathophysiology of these important disorders. We anticipate that our data, results and software, which will be widely available to other investigators, will provide a powerful resource for human genetics research.
Certain rare, familial mutations in the ATM, BRCA1, BRCA2, CHEK2 or TP53 genes increase susceptibility to breast cancer but it has not, until now, been clear whether common polymorphic variants in the same genes also increase risk.
We have attempted a comprehensive, single nucleotide polymorphism (SNP)- and haplotype-tagging association study on each of these five genes in up to 4,474 breast cancer cases from the British, East Anglian SEARCH study and 4,560 controls from the EPIC-Norfolk study, using a two-stage study design. Nine tag SNPs were genotyped in ATM, together with five in BRCA1, sixteen in BRCA2, ten in CHEK2 and five in TP53, with the aim of tagging all other known, common variants. SNPs generating the common amino acid substitutions were specifically forced into the tagging set for each gene.
No significant breast cancer associations were detected with any individual or combination of tag SNPs.
It is unlikely that there are any other common variants in these genes conferring measurably increased risks of breast cancer in our study population.
It has been suggested that oxidative stress and mitochondrial DNA damage play important roles in breast cancer carcinogenesis. Manganese superoxide dismutase (MnSOD) is a major enzyme that is responsible for the detoxification of reactive oxygen species in the mitochondria. A T --> C substitution in the MnSOD gene results in a Val --> Ala change at the -9 position of the mitochondrial targeting sequence (Val-9Ala), which alters the protein secondary structure and thus affects transport of MnSOD into the mitochondria.
We evaluated this genetic polymorphism in association with breast cancer risk using data from the Shanghai Breast Cancer Study, a population-based case-control study conducted in urban Shanghai from 1996 to 1998. The MnSOD Val-9Ala polymorphism was examined in 1125 breast cancer cases and 1197 age-frequency-matched control individual.
Breast cancer risk was slightly elevated in women with Ala/Ala genotype (odds ratio [OR] 1.3, 95% confidence interval [CI] 0.7-2.3), particularly among premenopausal women (OR 1.8, 95% CI 0.9-3.7), as compared with those with Val/Val genotype. The increased risk with the Ala/Ala genotype was stronger among premenopausal women with a higher body mass index (OR 2.5, 95% CI 0.9-7.0) and more years of menstruation (OR 2.6, 95% CI 0.8-8.0). The risk among premenopausal women was further increased twofold to threefold among those with a low intake of fruits, vegetables, vitamin supplements, selenium, or antioxidant vitamins, including carotenes and vitamins A, C, and E. However, the frequency of the Ala allele was low (14%) in the study population, and most of the ORs provided above were not statistically significant.
The present study provides some evidence that genetic polymorphism in the MnSOD gene may be associated with increased risk of breast cancer among Chinese women with high levels of oxidative stress or low intake of antioxidants. Studies with a larger sample size are needed to confirm the findings.
Recent evidence suggests a role for progesterone in breast cancer development and tumorigenesis. Progesterone exerts its effect on target cells by interacting with its receptor; thus, genetic variations, which might cause alterations in the biological function in the progesterone receptor (PGR), can potentially contribute to an individual's susceptibility to breast cancer. It has been reported that the PROGINS allele, which is in complete linkage disequilibrium with a missense substitution in exon 4 (G/T, valine-->leucine, at codon 660), is associated with a decreased risk for breast cancer.
Using a nested case-control study design within the Nurses' Health Study cohort, we genotyped 1252 cases and 1660 matched controls with the use of the Taqman assay.
We did not observe any association of breast cancer risk with carrying the G/T (Val660-->Leu) polymorphism (odds ratio 1.10, 95% confidence interval 0.93-1.30). In addition, we did not observe an interaction between this allele and menopausal status and family history of breast cancer as reported previously.
Overall, our study does not support an association between the Val660-->Leu PROGINS polymorphism and breast cancer risk.
The extent of concordance between meta-analyses and large trials on the same topic has been investigated with different protocols. Inconsistent conclusions created confusion regarding the validity of these major tools of clinical evidence.
To evaluate protocols comparing meta-analyses and large trials in order to understand if and why they disagree on the concordance of these 2 clinical research methods.
Systematic comparison of protocol designs, study selection, definitions of agreement, analysis methods, and reported discrepancies between large trials and meta-analyses.
More discrepancies were claimed when large trials were selected from influential journals (which may prefer trials disagreeing with prior evidence) than from already performed meta-analyses (which may target homogeneous trials) and when both primary and secondary (rather than only primary) end points were considered. Depending on how agreement was defined, kappa coefficients varied from 0.22 (low agreement) to 0.72 (excellent agreement). The correlation of treatment effects between large trials and meta-analyses varied from -0.12 to 0.76, but was more similar (0.50-0.76) when only primary end points were considered. When both the magnitude and uncertainty of treatment effects were considered, large trials disagreed with meta-analyses 10% to 23% of the time. Discrepancies were attributed to different disease risks, variable protocols, quality, and publication bias.
Comparisons of large trials with meta-analyses may reach different conclusions depending on how trials and meta-analyses are selected and how end points and agreement are defined. Scrutiny of these 2 major research methods can enhance our appreciation of both for guiding medical practice.
Insulin-like growth factor I (IGF-I) stimulates cell proliferation and can enhance the development of tumours in different organs. Epidemiological studies have shown that an elevated level of circulating IGF-I is associated with increased risk of breast cancer, as well as of other cancers. Most of circulating IGF-I is bound to an acid-labile subunit and to one of six insulin-like growth factor binding proteins (IGFBPs), among which the most important are IGFBP-3 and IGFBP-1. Polymorphisms of the IGF1 gene and of genes encoding for the major IGF-I carriers may predict circulating levels of IGF-I and have an impact on cancer risk. We tested this hypothesis with a case-control study of 807 breast cancer patients and 1588 matched control subjects, nested within the European Prospective Investigation into Cancer and Nutrition. We genotyped 23 common single nucleotide polymorphisms in IGF1, IGFBP1, IGFBP3 and IGFALS, and measured serum levels of IGF-I and IGFBP-3 in samples of cases and controls. We found a weak but significant association of polymorphisms at the 5' end of the IGF1 gene with breast cancer risk, particularly among women younger than 55 years, and a strong association of polymorphisms located in the 5' end of IGFBP3 with circulating levels of IGFBP-3, which confirms previous findings. Common genetic variation in these candidate genes does not play a major role in altering breast cancer risk in Caucasians.
Three polymorphisms in the human tumor suppressor gene p53 (BstUI and MspI RFLPs in exon 4 and intron 6 respectively and a 16 bp duplication in intron 3) and their haplotype combinations were studied
in patients with breast cancer and controls. A significant increase in the codon 72 BstUI A1 (pro) allele frequency (p= 0.016) and of individuals carrying the pro allele (pro/pro and pro/arg) (OR,1.47; p = 0.014; 95% CI, 1.08–2.00) was observed in breast cancer. This increase wasmost pronounced in highly differentiated breast
cancer. Significant associations were found only in BstUIand haplotypes containing this polymorphism, which indicates that the codon 72 pro allele may be functionally involved in
low malignancy breast cancer. The distributions of genotypic combinations in breast cancer patients and controls were significantly
different (p = 0.005). Two BstUI–16 bp-MspI combinations were significantly overrepresented; 2–1, 1–1, 2–2 (OR, 1.61; 95% CI, 1.13–2.30) and 1–1, 2–1, 2–1 (OR, 2.94;
95% CI, 1.37–6.27).
To determine the relative merits of two quantitative methods used to estimate the summary effects of observational studies, the authors compared two methods of meta-analysis. Each quantified the relation between oral contraceptive use and the risk for ovarian cancer. One analysis consisted of a meta-analysis using summary data from 11 published studies from the literature (MAL) in which the study was the unit of analysis, and the second consisted of a meta-analysis using individual patient data (MAP) in which the patient was the unit of analysis. The authors found excellent quantitative agreement between the summary effect estimates from the MAL and the MAP. The MAP permits analysis 1) among outcomes, exposures, and confounders not investigated in the original studies, 2) when the original effect measures differ among studies and cannot be converted to a common measure (e.g., slopes vs. correlation coefficients), and 3) when there is a paucity of studies. The MAL permits analysis 1) when resources are limited, 2) when time is limited, and 3) when original study data are not available or are available only from a biased sample of studies. In public health epidemiology, data from original studies are often accessible only to limited numbers of research groups and for only a few types of studies that have high public health priority. Consequently, few opportunities for pooled analysis exist. However, from a policy view, MAL will provide answers to many questions and will help in identifying questions for future investigation.
Superoxide dismutases play a key role in the detoxification of superoxide radicals and thus protect cells from damage induced by free radicals. Within mitochondria manganese superoxide dismutase (MnSOD) provides a major defence against oxidative damage by reactive oxygen species. Polymorphism in the mitochondrial targeting sequence of MnSOD has recently been associated with risk of breast cancer. We examined this in a study population consisting of 483 breast cancer cases and 482 controls, all of Finnish Caucasian origin. Odds ratios (OR) and 95% confidence intervals (95% CIs) were estimated by unconditional logistic regression. MnSOD genotypes containing the variant A allele were found to be associated with a 1.5-fold (95% CI 1.1-2.0) increased risk of breast cancer compared with those with the homozygous wild-type genotype (MnSOD VV). This finding supports the proposal that MnSOD genotypes may modify individual breast cancer risk.
Transgenic animal experiments suggest that increased expression of transforming growth factor beta1 (TGF-beta1) is protective against early tumor development, particularly in breast cancer. A T-->C (thymine to cytosine) transition in the 29th nucleotide in the coding sequence results in a leucine to proline substitution at the 10th amino acid and is associated with increased serum levels of TGF-beta1.
To determine whether an association exists between this TGF-beta1 polymorphism and breast cancer risk.
The Study of Osteoporotic Fractures, a prospective cohort study of white, community-dwelling women aged 65 years or older who were recruited at 4 US centers between 1986 and 1988. Three thousand seventy-five women who provided sufficient clinical information, buffy coat samples, and adequate consent for genotyping are included in this analysis.
Breast cancer cases during a mean (SD) follow-up of 9.3 (1.9) years, verified by medical chart review and compared by genotype.
Risk of breast cancer was similar in the 1124 women with the T/T genotype (56 cases; 5.4 per 1000 person-years) and the 1493 women with the T/C genotype (80 cases; 5.8 per 1000 person-years) but was significantly lower (P =.01) in the 458 women with the C/C genotype (10 cases; 2.3 per 1000 person-years). In analyses that adjusted for age, age at menarche, age at menopause, estrogen use, parity, body mass index, and bone mineral density, women with the C/C genotype had a significantly lower risk of developing breast cancer compared with women with the T/T or T/C genotype (hazard ratio [HR], 0.36; 95% confidence interval [CI], 0.17-0.75). There was no significant difference between the risk for women with the T/C genotype compared with women with the T/T genotype (adjusted HR, 1.04; 95% CI, 0.73-1.48).
Our findings suggest that TGF-beta1 genotype is associated with risk of breast cancer in white women aged 65 years or older. Because the T allele is the common variant and confers an increased risk, it may be associated with a large proportion of breast cancer cases.
The rapid growth of human genetics creates countless opportunities for studies of disease association. Given the number of potentially identifiable genetic markers and the multitude of clinical outcomes to which these may be linked, the testing and validation of statistical hypotheses in genetic epidemiology is a task of unprecedented scale. Meta-analysis provides a quantitative approach for combining the results of various studies on the same topic, and for estimating and explaining their diversity. Here, we have evaluated by meta-analysis 370 studies addressing 36 genetic associations for various outcomes of disease. We show that significant between-study heterogeneity (diversity) is frequent, and that the results of the first study correlate only modestly with subsequent research on the same association. The first study often suggests a stronger genetic effect than is found by subsequent studies. Both bias and genuine population diversity might explain why early association studies tend to overestimate the disease protection or predisposition conferred by a genetic polymorphism. We conclude that a systematic meta-analytic approach may assist in estimating population-wide effects of genetic risk factors in human disease.
An acquired genetic instability, resulting from the loss of some types of DNA repair, is an early event in the development of a subset of human cancers. The involvement of BRCA1 and BRCA2 in the homologous recombination repair (HRR) of double-strand breaks in DNA implicates this pathway in the suppression of breast cancer. A family of proteins related to human RAD51, including XRCC2, are essential components of this repair pathway. Using site-directed mutagenesis of XRCC2, we show that non-conservative substitution or deletion of amino acid 188 of XRCC2 can significantly affect cellular sensitivity to DNA damage, and that a polymorphic variant at this site (R188H ), present on 6% of chromosomes in the population, has a weak effect on damage sensitivity. We tested the hypothesis that the R188H polymorphism could be a low-penetrance susceptibility factor for breast cancer, by genotyping 521 women with breast cancer and a total of 895 control women. Carriage of the rare allele of XRCC2 R188H was associated with breast cancer overall [odds ratio 1.3; 95% confidence interval (CI)=(1.0, 1.8)] and when younger-onset cases with a positive family history were compared with older controls with no family history [odds ratio 1.9; 95% CI=(1.0, 3.8)]. These results support the hypothesis that subtle variation in DNA repair capacity may influence cancer susceptibility in the population.
The authors summarize their experience in the conduct of meta-analysis of individual participants' data (MIPD) with time-to-event analyses in the field of genetic epidemiology. The MIPD offers many advantages compared with a meta-analysis of the published literature. These include standardization of case definitions, outcomes, and covariates; inclusion of updated information; the ability to fully test the assumptions of time-to-event models; better control of confounding; standardization of analyses of genetic loci that are in linkage disequilibrium; evaluation of alternative genetic models and multiple genes; consistent treatment of subpopulations; assessment of sampling bias; and the establishment of an international collaboration with the capability to prospectively update the meta-analyses and synthesize new information on multiple genetic loci and outcomes. The disadvantages of a MIPD compared with a meta-analysis of the published literature are that a much greater commitment of time and resources is required to collect primary data and to coordinate a large collaborative project. An MIPD may collect additional, unpublished data, but it is possible that not all published data may be contributed at the individual level. For questions that justify the required intensive effort, the MIPD method is a useful tool to help clarify the role of candidate genes in complex human diseases.
Laboratory studies suggest a dual role for the transforming growth factor-beta (TGF-beta) signaling pathway in breast cancer. The normal antiproliferative activity of TGF-beta in early breast tumor development is replaced by a promoting effect in later stages. A T29C transition polymorphism in the TGFB1 gene has been associated with higher circulating TGF-beta1 levels, and inconsistently with breast cancer risk in three recent studies. We tested the association of this variant with invasive breast cancer in a case-control study of 1123 cases and 2314 controls nested in the Multiethnic Cohort (MEC) Study. This study is a large prospective study being conducted in Hawaii and Los Angeles that includes Japanese, white, African American, Latino, and Native Hawaiian women who were predominantly postmenopausal at baseline. After adjustment for breast cancer risk factors, the odds ratio (OR) and 95% confidence interval (95% CI) for the TGFB1 29 CC genotype was 0.95 (95% confidence interval: 0.76-1.18), compared to the TT genotype. Analyses stratified by race/ethnicity, stage, or age category did not reveal any association of this variant with breast cancer. Given the strong biological rationale and the scarce and divergent epiderniologic data to date, additional investigations of the relationship between breast cancer and genetic variants in the TGF-beta signaling pathway appear warranted.
The Breast Cancer Association Consortium (BCAC) is an international collaboration that was established to provide large sample sizes for examining genetic associations. We conducted combined analyses on all single-nucleotide polymorphisms (SNPs) whose associations with breast cancer have been investigated by at least three participating groups. METHODS: Data from up to 12 studies were pooled for each SNP (ADH1C I350V, AURKA F31I, BRCA2 N372H, CASP8 D302H, ERCC2 D312N, IGFBP3 -202 c>a, LIG4 D501D, PGR V660L, SOD2 V16A, TGFB1 L10P, TP53 R72P, XRCC1 R399Q, XRCC2 R188H, XRCC3 T241M, XRCC3 5' UTR, and XRCC3 IVS7-14). Genotype frequencies in case and control subjects were compared, and genotype-specific odds ratios for the risk of breast cancer in heterozygotes and homozygotes for the rare allele compared with homozygotes for the common allele were estimated with logistic regression. Statistical tests were two-sided. RESULTS: The total number of subjects for analysis of each SNP ranged from 12,013 to 31,595. For five SNPs--CASP8 D302H, IGFBP3 -202 c>a, PGR V660L, SOD2 V16A, and TGFB1 L10P--the associations with breast cancer were of borderline statistical significance (P = .016, .060, .047, .056, and .0088 respectively). The remaining 11 SNPs were not associated with breast cancer risk; genotype-specific odds ratios were close to unity. There was some evidence for between-study heterogeneity (P<.05) for four of the 11 SNPs (ADH1C I350V, ERCC2 D312N, XRCC1 R399Q, and XRCC3 IVS5-14). CONCLUSION: Pooling data within a large consortium has helped to clarify associations of SNPs with breast cancer. In the future, consortia such as the BCAC will be important in the analysis of rare polymorphisms and gene x gene or gene x environment interactions, for which individual studies have low power to identify associations, and in the validation of associations identified from genome-wide association studies.
The Breast Cancer Association Consortium (BCAC) has been established to conduct combined case-control analyses with augmented statistical power to try to confirm putative genetic associations with breast cancer. We genotyped nine SNPs for which there was some prior evidence of an association with breast cancer: CASP8 D302H (rs1045485), IGFBP3 -202 C --> A (rs2854744), SOD2 V16A (rs1799725), TGFB1 L10P (rs1982073), ATM S49C (rs1800054), ADH1B 3' UTR A --> G (rs1042026), CDKN1A S31R (rs1801270), ICAM5 V301I (rs1056538) and NUMA1 A794G (rs3750913). We included data from 9-15 studies, comprising 11,391-18,290 cases and 14,753-22,670 controls. We found evidence of an association with breast cancer for CASP8 D302H (with odds ratios (OR) of 0.89 (95% confidence interval (c.i.): 0.85-0.94) and 0.74 (95% c.i.: 0.62-0.87) for heterozygotes and rare homozygotes, respectively, compared with common homozygotes; P(trend) = 1.1 x 10(-7)) and weaker evidence for TGFB1 L10P (OR = 1.07 (95% c.i.: 1.02-1.13) and 1.16 (95% c.i.: 1.08-1.25), respectively; P(trend) = 2.8 x 10(-5)). These results demonstrate that common breast cancer susceptibility alleles with small effects on risk can be identified, given sufficiently powerful studies.
Superoxide dismutases play a key role in the detoxification of superoxide radicals and thus protect cells from damage induced by free radicals. Within mitochondria manganese superoxide dismutase (MnSOD) provides a major defence against oxidative damage by reactive oxygen species. Polymorphism in the mitochondrial targeting sequence of MnSOD has recently been associated with risk of breast cancer. We examined this in a study population consisting of 483 breast cancer cases and 482 controls, all of Finnish Caucasian origin. Odds ratios (OR) and 95% confidence intervals (95% CIs) were estimated by unconditional logistic regression. MnSOD genotypes containing the variant A allele were found to be associated with a 1.5-fold (95% CI 1.1-2.0) increased risk of breast cancer compared with those with the homozygous wild-type genotype (MnSOD W). This finding supports the proposal that MnSOD genotypes may modify individual breast cancer risk.
Objective.
—To compare the meta-analytic results from published literature vs those obtained from pooling original patient data.Data Sources.
—Individual patient data from 15 completed or ongoing trials on paternal white blood cell immunization as treatment for recurrent miscarriage were obtained through the American Society for Reproductive Immunology.Study Selection.
—Only randomized controlled trials were selected. Within these eight selected trials, 202 patients were from four published studies, 43 were added by the same investigators after publication, and 140 were from four unpublished trials.Data Extraction.
—Individual patient data were collected using a standardized form and double data entry.Data Synthesis.
—Using the fixed treatment effect model, we found that the effect of immunization, denoted as the relative live-birth ratio (RR), was greater by pooling summary data from published articles (RR, 1.29; 95% confidence interval [CI], 1.03 to 1.60) than by pooling all individual patient data from the same investigators (RR, 1.17; 95% CI, 0.97 to 1.37) or when individual patient data were pooled from four unpublished trials (RR, 1.01; 95% CI, 0.74 to 1.28). A similar diminishing treatment effect for the same comparisons was observed using the random treatment effect model (RR, 1.38; 95% CI, 0.89 to 1.87 using published summary data; RR, 1.18; 95% CI, 0.98 to 1.42 using individual patient data; RR, 1.01; 95% CI, 0.74 to 1.28 using unpublished trials).Conclusions.
—Meta-analytic results may differ depending on the use of various data sources: whether the source was from summary statistics in the literature, from individual patient data provided by trialists, or from unpublished trials.(JAMA. 1995;274:830-836)
The polygenic concept of breast cancer susceptibility calls for the identification of genetic variants that contribute to breast cancer risk. Reduced DNA repair proficiencies in women with breast cancer pointed to a possible role of DNA repair enzymes in the risk to develop the disease. The nucleotide excision repair enzyme encoded by the excision repair cross-complementing group 2 gene ERCC2 (formerly XPD) known to cause skin cancer by germ line mutations has multiple regulatory cellular functions, including nucleotide excision repair, basal transcription, cell cycle control, and apoptosis. ERCC2 polymorphisms ERCC2_6540_G>A (Asp(312)Asn) and ERCC2_18880_A>C (Lys(751)Gln) within the coding region of this evolutionarily highly conserved gene have been of functional relevance and therefore are potential candidates to confer breast cancer susceptibility. Using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry, we analyzed genotype frequencies in constitutional DNA of study participants of a German case-control study that included 688 cases of incident breast cancer and 724 population-based, age-matched controls. We identified ERCC2_6540_GG (Asp(312)Asp) as an at-risk genotype [odds ratio (OR), 2.06; 95% confidence interval (95% CI), 1.39-3.07]. The ERCC2_6540_GG-associated breast cancer risk was even higher in women who were also carriers of the ERCC2_18880_CC (Gln(751)Gln) genotype (OR, 3.69; 95% CI, 1.76-7.74). We identified ERCC2_6540_G/ERCC2_18880_C (Asp(312)/Gln(751)) as the most potent risk-conferring haplotype (OR, 3.49; 95% CI, 2.30-5.28). To our knowledge, this is the first study assigning breast cancer risk to both the ERCC2 genotype encoding Asp(312)Asp and the haplotype encoding Asp(312)/Gln(751).
To evaluate the relationship of genetic polymorphism in XRCC3 Thr241Met and the risk of breast cancer, a hospital-based case-control study was conducted in Korea. Histologically confirmed breast
cancer cases (n = 574) and controls (n = 502) with no present or previous history of cancer were recruited from several teaching hospitals in Seoul during 1995–2001.
Information on demographic characteristics and other information were collected by interviewed questionnaire. Genetic polymorphisms
of XRCC3 Thr241Met (C > T) was determined by single base extention assay. The frequency of Thr/Thr, Thr/Met, and Met/Met genotype were 89.4,
10.4, 0.2% in cases and 92.3, 7.7, 0.0% in controls, respectively. Genotype distribution in controls fit well to the Hardy–Weinberg
equilibrium (P = 0.74). XRCC3 codon 241 Thr/Met or Met/Met genotype moderately increased the risk of breast cancer (OR = 1.4, 95% CI: 0.87–2.33), but not
significant in this study. In the results of meta-analysis using twelve reports, however, Thr/Met or Met/Met genotype increased
the risk of breast cancer (OR = 1.08, 95%CI: 1.00–1.17). In conclusion, although the genetic polymorphism of XRCC3 Thr241Met was unlikely to have a substantial overall association in Korean women, the meta-analysis of studies, including ours,
provided that Thr/Met and Met/Met was weakly increased the risk of breast cancer compare to Thr/Thr genotype.
Genetic polymorphisms in double-strand break repair genes may influence DNA repair capacity and, in turn, confer predisposition to breast cancer. We prospectively assessed the associations of candidate polymorphisms G31479A (R188H) in XRCC2, A4541G (5'-UTR), A17893G (IVS5-14) and C18067T (T241 M) in XRCC3, and C299T (5'-UTR) and T1977C (D501D) in Ligase IV with breast cancer risk in a nested case-control study within the Nurses' Health Study (incident cases, n=1004; controls, n=1385). We observed no overall associations of these six genotypes with breast cancer risk. Four common haplotypes in XRCC3 accounted for 99% of the chromosomes of the present study population. We observed that Ligase IV 1977C carriers were at increased breast cancer risk if they had a first degree family history of breast cancer (test for interaction, P=0.01). We observed that the XRCC2 R188H polymorphism modified the association of plasma alpha-carotene level and breast cancer risk (test for ordinal interaction, P=0.03); the significantly decreased risk seen overall for women in the highest quartile of plasma alpha-carotene was only present among 188H non-carriers (the top quartile versus the bottom quartile; multivariate odds ratio, 0.55; 95% confidence interval, 0.40-0.75). No significant interactions were seen between any of these polymorphisms and duration or dose of cigarette smoking. The gene-environment interaction data suggest that the subtle effects of some of these variants on breast cancer risk may be magnified in the presence of certain exposures.
Objectives: Because alcohol dehydrogenase 3 (ADH3) is rate-limiting in alcohol oxidation and is polymorphic, we examined ADH3 genotype in relation to alcohol intake and breast cancer risk.Methods: We conducted a case–control study among Caucasian women aged 40–85 with incident, pathologically confirmed breast cancer and controls, frequency-matched on age and county. Queries included alcohol intake in the past 20 years. Genomic DNA was genotyped for the exon VIII ADH polymorphism by PCR followed by restriction enzyme digestion. Computation of odds ratios (OR) and 95% confidence intervals (CI) was by unconditional logistic regression.Results: We found increased risk among pre- (OR 2.3, 95%, CI 1.2–4.3) but not postmenopausal women (OR 1.1, 95% CI 0.7–1.7) associated with ADH3
1-1 compared to ADH3
1-2 and ADH3
2-2 genotypes. Risk was increased for premenopausal women with the ADH3
1-1 genotype and alcohol intake above the median (OR 3.6, 95% CI 1.5–8.8) compared to lighter drinkers with the ADH3
2-2 or ADH3
1-2 genotypes. ORs were close to null for premenopausal women in other drinking and genotype groups and for postmenopausal women categorized by genotype and alcohol consumption.Conclusion: Among premenopausal women there may be a group more genetically susceptible to an alcohol consumption effect on breast cancer risk.
Association studies aimed at identifying breast cancer susceptibility variants in the progesterone receptor (PGR) gene have been previously reported in the literature with conflicting results, ranging from a protective effect conferred
by the PROGINS allele in German Caucasian women, to an increased risk for the leucine variant of the Val660Leu (rs1042838)
polymorphism in East Anglian cases. We report the results of genotype and haplotype analyses of five PGR polymorphisms, +44C/T
(rs518162), +331G/A (rs10895068), V660L (rs1042838), H770H (rs1042839) and Q886Q (rs500760), conducted on 1,847 Australian
breast cancer cases (including 276 cases from a cohort of multiple-case breast cancer families) and 833 controls. Genotype
and haplotype analyses of the five polymorphisms showed no evidence of an association with breast cancer (p>0.3). We also conducted a meta-analysis of the V660L (rs1042838) polymorphism on our and six other published studies including
10,205 cases and 11,320 controls. Compared to the VV homozygotes, VL heterozygotes and LL homozygotes were associated with
a non-significant increased risk for breast cancer [Odds ratio (OR)VL, 1.06; 95% confidence intervals (95% CI), 0.97–1.15, ORLL, 1.05; 95% CI, 0.75–1.49]. Analysis of a per-leucine allele risk under a codominant model, however, suggested a significant
leucine-allele dose effect, ORper-L, 1.07; 95% CI, 1.02–1.13, p=0.01. We conclude that the leucine allele of the V660L SNP may be associated with a small increase in breast cancer risk,
while the other four PGR SNPs, +44C/T (rs518162), +331G/A (rs10895068), H770H (rs1042839) and Q886Q (rs500760), do not substantially
increase breast cancer risk.
This paper was published as Nature, 2007, 447 (7145), pp. 661-678. It is available from http://www.nature.com/nature/journal/v447/n7145/abs/nature05911.html. Doi: 10.1038/nature05911 Metadata only entry There is increasing evidence that genome-wide association (GWA) studies represent a powerful approach to the identification of genes involved in common human diseases. We describe a joint GWA study (using the Affymetrix GeneChip 500K Mapping Array Set) undertaken in the British population, which has examined 2,000 individuals for each of 7 major diseases and a shared set of 3,000 controls. Case-control comparisons identified 24 independent association signals at P < 5 10-7: 1 in bipolar disorder, 1 in coronary artery disease, 9 in Crohn's disease, 3 in rheumatoid arthritis, 7 in type 1 diabetes and 3 in type 2 diabetes. On the basis of prior findings and replication studies thus-far completed, almost all of these signals reflect genuine susceptibility effects. We observed association at many previously identified loci, and found compelling evidence that some loci confer risk for more than one of the diseases studied. Across all diseases, we identified a large number of further signals (including 58 loci with single-point P values between 10-5 and 5 10-7) likely to yield additional susceptibility loci. The importance of appropriately large samples was confirmed by the modest effect sizes observed at most loci identified. This study thus represents a thorough validation of the GWA approach. It has also demonstrated that careful use of a shared control group represents a safe and effective approach to GWA analyses of multiple disease phenotypes; has generated a genome-wide genotype database for future studies of common diseases in the British population; and shown that, provided individuals with non-European ancestry are excluded, the extent of population stratification in the British population is generally modest. Our findings offer new avenues for exploring the pathophysiology of these important disorders. We anticipate that our data, results and software, which will be widely available to other investigators, will provide a powerful resource for human genetics research.
Background: The Breast Cancer Association Consortium (BCAC) is an international collaboration that was established to provide large sample
sizes for examining genetic associations. We conducted combined analyses on all single-nucleotide polymorphisms (SNPs) whose
associations with breast cancer have been investigated by at least three participating groups. Methods: Data from up to 12 studies were pooled for each SNP (ADH1C I350V, AURKA F31I, BRCA2 N372H, CASP8 D302H, ERCC2 D312N, IGFBP3 −202 c>a, LIG4 D501D, PGR V660L, SOD2 V16A, TGFB1 L10P, TP53 R72P, XRCC1 R399Q, XRCC2 R188H, XRCC3 T241M, XRCC3 5′ UTR, and XRCC3 IVS7-14). Genotype frequencies in case and control subjects were compared, and genotype-specific odds ratios for the risk
of breast cancer in heterozygotes and homozygotes for the rare allele compared with homozygotes for the common allele were
estimated with logistic regression. Statistical tests were two-sided. Results: The total number of subjects for analysis of each SNP ranged from 12 013 to 31 595. For five SNPs—CASP8 D302H, IGFBP3 −202 c>a, PGR V660L, SOD2 V16A, and TGFB1 L10P—the associations with breast cancer were of borderline statistical significance (P = .016, .060, .047, .056, and .0088 respectively). The remaining 11 SNPs were not associated with breast cancer risk; genotype-specific
odds ratios were close to unity. There was some evidence for between-study heterogeneity (P<.05) for four of the 11 SNPs (ADH1C I350V, ERCC2 D312N, XRCC1 R399Q, and XRCC3 IVS5-14). Conclusion: Pooling data within a large consortium has helped to clarify associations of SNPs with breast cancer. In the future, consortia
such as the BCAC will be important in the analysis of rare polymorphisms and gene × gene or gene × environment interactions,
for which individual studies have low power to identify associations, and in the validation of associations identified from
genome-wide association studies.
This paper examines eight published reviews each reporting results from several related trials. Each review pools the results from the relevant trials in order to evaluate the efficacy of a certain treatment for a specified medical condition. These reviews lack consistent assessment of homogeneity of treatment effect before pooling. We discuss a random effects approach to combining evidence from a series of experiments comparing two treatments. This approach incorporates the heterogeneity of effects in the analysis of the overall treatment efficacy. The model can be extended to include relevant covariates which would reduce the heterogeneity and allow for more specific therapeutic recommendations. We suggest a simple noniterative procedure for characterizing the distribution of treatment effects in a series of studies.
The BJC is owned by Cancer Research UK, a charity dedicated to understanding the causes, prevention and treatment of cancer and to making sure that the best new treatments reach patients in the clinic as quickly as possible. The journal reflects these aims. It was founded more than fifty years ago and, from the start, its far-sighted mission was to encourage communication of the very best cancer research from laboratories and clinics in all countries. The breadth of its coverage, its editorial independence and it consistent high standards, have made BJC one of the world's premier general cancer journals. Its increasing popularity is reflected by a steadily rising impact factor.
To compare the meta-analytic results from published literature vs those obtained from pooling original patient data.
Individual patient data from 15 completed or ongoing trials on paternal white blood cell immunization as treatment for recurrent miscarriage were obtained through the American Society for Reproductive Immunology.
Only randomized controlled trials were selected. Within these eight selected trials, 202 patients were from four published studies, 43 were added by the same investigators after publication, and 140 were from four unpublished trials.
Individual patient data were collected using a standardized form and double data entry.
Using the fixed treatment effect model, we found that the effect of immunization, denoted as the relative live-birth ratio (RR), was greater by pooling summary data from published articles (RR, 1.29; 95% confidence interval [CI], 1.03 to 1.60) than by pooling all individual patient data from the same investigators (RR, 1.17; 95% CI, 0.97 to 1.37) or when individual patient data were pooled from four unpublished trials (RR, 1.01; 95% CI, 0.74 to 1.28). A similar diminishing treatment effect for the same comparisons was observed using the random treatment effect model (RR, 1.38; 95% CI, 0.89 to 1.87 using published summary data; RR, 1.18; 95% CI, 0.98 to 1.42 using individual patient data; RR, 1.01; 95% CI, 0.74 to 1.28 using unpublished trials).
Meta-analytic results may differ depending on the use of various data sources: whether the source was from summary statistics in the literature, from individual patient data provided by trialists, or from unpublished trials.
The use of meta-analyses or overviews to combine formally the results of related randomised clinical trials is becoming increasingly common. However the distinction between analyses based on information extracted from the published literature and those based on collecting and reanalysing updated individual patient data is not clear. We have investigated the difference between meta-analysis of the literature (MAL) and meta-analysis of individual patient data (MAP) by comparing the two approaches using randomised trials of cisplatin-based therapy in ovarian cancer. The MAL was based on 788 patients and the MAP on 1329 and estimated median follow-ups were 3.5 and 6.5 years, respectively. The MAL gave a result of greater statistical significance (p = 0.027 vs p = 0.30) and an estimate of absolute treatment effect three times as large as the MAP (7.5% vs 2.5%). Publication bias, patient exclusion, length of follow-up, and method of analysis all contributed to this observed difference. The results of a meta-analysis of the literature alone may be misleading. Whenever possible, a meta-analysis of updated individual patient data should be done because this provides the least biased and most reliable means of addressing questions that have not been satisfactorily resolved by individual clinical trials.
The BJC is owned by Cancer Research UK, a charity dedicated to understanding the causes, prevention and treatment of cancer and to making sure that the best new treatments reach patients in the clinic as quickly as possible. The journal reflects these aims. It was founded more than fifty years ago and, from the start, its far-sighted mission was to encourage communication of the very best cancer research from laboratories and clinics in all countries. The breadth of its coverage, its editorial independence and it consistent high standards, have made BJC one of the world's premier general cancer journals. Its increasing popularity is reflected by a steadily rising impact factor.
Certain polymorphic variants of H-ras-1 and p53 have been investigated for an association between inheritance and cancer risk. The results of a metaanalysis, which reviews studies of H-ras-1 rare alleles and p53 codon 72 allelic variants in breast and lung cancer, are presented. The data constituted evidence for elevated risk of both breast and lung cancer with inheritance of rare H-ras-1 alleles. Calculated population attributable risks are 0.092 and 0.037 for breast and lung cancer, respectively. The frequency of the rare H-ras-1 alleles was observed to be greater in African Americans than in Caucasians, and a specific allele (A3.5) that is common in African Americans was found only at low frequency in Caucasians. For p53 a consensus has yet to be reached. Lung cancer studies conducted in Caucasian and African-American populations have found no evidence of risk associated with the proline variant of codon 72. Two similar studies conducted in Japanese populations suggested an association between p53 genotype distribution and lung cancer risk. However, one implicates the proline allele but the other implicates the arginine allele. The frequency of the proline variant is significantly dependent on race. Frequencies have been reported for control populations of Japanese (0.347 and 0.401), Caucasian (0.295, 0.284, and 0.214), African American (0.628 and 0.527), and Mexican American (0.263).
Oxidative stress, resulting from the imbalance between prooxidant and antioxidant states, damages DNA, proteins, cell membranes, and mitochondria and seems to play a role in human breast carcinogenesis. Dietary sources of antioxidants (chemical) and endogenous antioxidants (enzymatic), including the polymorphic manganese superoxide dismutase (MnSOD), can act to reduce the load of oxidative stress. We hypothesized that the valine-to-alanine substitution that seems to alter transport of the enzyme into the mitochondrion, changing its efficacy in fighting oxidative stress, was associated with breast cancer risk and that a diet rich in sources of antioxidants could ameliorate the effects on risk. Data were collected in a case-control study of diet and breast cancer in western New York from 1986 to 1991. Caucasian women with incident, primary, histologically confirmed breast cancer were frequency-matched on age and county of residence to community controls. Blood specimens were collected and processed from a subset of participants in the study (266 cases and 295 controls). Using a RFLP that distinguishes a valine (V) to alanine (A) change in the -9 position in the signal sequence of the protein for MnSOD, we characterized MnSOD genotypes in relation to breast cancer risk. We also evaluated the effect of the polymorphism on risk among low and high consumers of fruits and vegetables. Premenopausal women who were homozygous for the A allele had a 4-fold increase in breast cancer risk in comparison to those with 1 or 2 V alleles (odds ratio, 4.3; 95% confidence interval, 1.7-10.8). Risk was most pronounced among women below the median consumption of fruits and vegetables and of dietary ascorbic acid and alpha-tocopherol, with little increased risk for those with diets rich in these foods. Relationships were weaker among postmenopausal women, although the MnSOD AA genotype was associated with an almost 2-fold increase in risk (odds ratio, 1.8; confidence interval, 0.9-3.6). No appreciable modification of risk by diet was detected for these older women. These data support the hypothesis that MnSOD and oxidative stress play a significant role in breast cancer risk, particularly in premenopausal women. The finding that risk was greatest among women who consumed lower amounts of dietary antioxidants and was minimal among high consumers indicates that a diet rich in sources of antioxidants may minimize the deleterious effects of the MnSOD polymorphism, thereby supporting public health recommendations for the consumption of diets rich in fruits and vegetables as a preventive measure against cancer.
In a population-based case-control study for breast cancer before the age of 51 years, 554 cases and 559 age-matched controls were genotyped for the polymorphic progesterone receptor allele PROGINS. Breast cancer risk was decreased in women carrying the PROGINS allele. The odds ratio adjusted for age and study region was 0.76 [95% confidence interval (CI), 0.58-1.00]. Compared with wild-type A1/A1 homozygotes, the odds ratio for A1/A2 heterozygotes and A2/A2 homozygotes was 0.82 (95% CI, 0.62-1.08) and 0.27 (95% CI, 0.10-0.74), respectively, suggesting a gene dosage effect of the A2 allele. There was suggestive evidence for a differential effect by menopausal status (P = 0.07) and by family history of breast cancer (P = 0.15).
One suggested mechanism underlying the positive association between alcohol consumption and breast cancer risk is an influence of alcohol on steroid hormone levels. A polymorphism in alcohol dehydrogenase type 3 (ADH3) affects the kinetics of alcohol oxidation and thereby could influence the effect of alcohol consumption on hormone levels. We investigated the ADH3 polymorphism, alcohol intake, and risk of breast cancer in a nested case-control study. Among women in the Nurses' Health Study who gave a blood sample in 1989-1990, 465 incident breast cancer cases were diagnosed before June 1994 and were matched to 621 controls. Using conditional logistic regression, we calculated relative risks and confidence intervals to assess breast cancer risk for ADH3 genotype. Among postmenopausal controls not using hormones at time of blood collection, partial Pearson correlation coefficients were calculated to assess the association between alcohol intake and plasma hormone levels according to ADH3 genotype. No association was observed between ADH3 genotype and overall breast cancer risk (relative risk = 0.9 for slow oxidizers compared with fast; 95% confidence interval = 0.6-1.3). Among postmenopausal women, ADH3 genotype did not modify the weak association observed between alcohol intake and breast cancer risk (P for interaction = 0.45). Statistically significant trends in the relationship between alcohol consumption and hormone level dependent on oxidative capacity (ADH3 genotype) were observed for dehydroepiandrosterone sulfate and sex hormone-binding globulin (P < 0.05). These data suggest that the ADH3 polymorphism modestly influences the response of some plasma hormones to alcohol consumption but is not independently associated with breast cancer risk and does not modify the association between alcohol and breast cancer risk.
When performing a meta-analysis, interest often centres on finding explanations for heterogeneity in the data, rather than on producing a single summary estimate. Such exploratory analyses are frequently undertaken with published, study-level data, using techniques of meta-analytic regression. Our goal was to explore a real-world example for which both published, group-level and individual patient-level data were available, and to compare the substantive conclusions reached by both methods. We studied the benefits of anti-lymphocyte antibody induction therapy among renal transplant patients in five randomized trials, focusing on whether there are subgroups of patients in whom therapy might prove particularly beneficial. Allograft failure within 5 years was the endpoint studied. We used a variety of analytic approaches to the group-level data, including weighted least-squares regression (N=5 studies), logistic regression (N=628, the total number of subjects), and a hierarchical Bayesian approach. We fit logistic regression models to the patient-level data. In the patient-level analysis, we found that treatment was significantly more effective among patients with elevated (20 per cent or more) panel reactive antibodies (PRA) than among patients without elevated PRA. These patients comprise a small (about 15 per cent of patients) subgroup of patients that benefited from therapy. The group-level analyses failed to detect this interaction. We recommend using individual patient data, when feasible, to study patient characteristics, in order to avoid the potential for ecological bias introduced by group-level analyses.
Systematic reviews of published time-to-event outcomes commonly rely on calculating odds ratios (OR) at fixed points in time and where actual numbers at risk are not presented. These estimates are usually based on the total numbers included in the published analysis and take no account of censoring. We have assessed the impact of adjusting for censoring on weighting, estimates and statistical heterogeneity of meta-analyses in cancer.
Meta-analyses of survival data for five meta-analyses of published trials in cancer were conducted. The OR and associated statistics were calculated based on unadjusted total numbers of participants and events. These were compared with calculations that first adjusted the numbers at risk for censoring using a simple model.
Pooled OR were changed in 17/24 cases. On average, there was a 2.6% difference between the adjusted and unadjusted OR. Confidence intervals were frequently wider for the adjusted OR. Adjusting also reduced weighting of individual trials with immature follow-up. In 18/24 cases, adjusting reduced statistical heterogeneity and affected the associated P-values.
Reviewers conducting meta-analyses of published time-to-event data where actual numbers at risk are not available should adjust the numbers at risk, estimated from total numbers analysed, to account for immature data and censoring.
We used a large population-based case-control study to determine whether three known p53 polymorphisms, intron 3 16 bp duplication, codon 72(Arg/Pro) and intron 6 MspI restriction fragment length polymorphism, alter the risk for breast cancer in German women. For all three polymorphisms, the odds ratios (ORs) for breast cancer were increased in women carrying the rare allele; however, this was statistically significant only for the 16 bp duplication polymorphism. Compared with the 16 bp duplication wild-type A1/A1 genotype, ORs for A1/A2 genotype and A2/A2 genotype were 1.3 [95% confidence interval (CI) 1.0-1.7] and 1.7 (95% CI 0.8-3.4), suggesting an allele dosage effect (trend test, P = 0.03). Significant evidence was found for a differential effect by family history of breast cancer (P = 0.03 for interaction), with the OR being 5.3 among women with a first degree family history. Our data suggest that inheritance of an intronic polymorphism in the p53 gene increases breast cancer risk appreciably in women by the age of 50 years with a family history of breast cancer in the German population.
The BRCA2 N372H nonconservative amino acid substitution polymorphism appears to affect fetal survival in a sex-dependent manner, and the HH genotype was found to be associated with a 1.3-fold risk of breast cancer from pooling five case-control studies of Northern European women. We investigated whether the BRCA2 N372H polymorphism was associated with breast cancer in Australian women using a population-based case-control design. The BRCA2 372 genotype was determined in 1397 cases under the age of 60 years at diagnosis of a first primary breast cancer and in 775 population-sampled controls frequency matched for age. Case-control analyses and comparisons of genotype distributions were conducted using logistic regression. All of the statistical tests were two-tailed. The HH genotype was independent of age and family history of breast cancer within cases and controls, and was more common in cases (9.2% versus 6.5%). It was associated with an increased risk of breast cancer, 1.47-fold unadjusted (95% confidence interval, 1.05-2.07; P = 0.02), and 1.42-fold (95% confidence interval, 1.00-2.02; P = 0.05) after adjusting for measured risk factors. This effect was still evident after excluding women with any non-Caucasian ancestry or the 33 cases known to have inherited a mutation in BRCA1 or BRCA2, and would explain approximately 3% of breast cancer. The BRCA2 N372H polymorphism appears to be associated with a modest recessively inherited risk of breast cancer in Australian women. This result is consistent with the findings for Northern European women.
We performed genetic association studies in a population-based breast cancer case-control study analysing polymorphisms in genes involved in homologous recombination (NBS1, RAD52, RAD51, XRCC2 and XRCC3) and non-homologous end-joining (KU70/80 and LIG4). These DNA double-strand break repair genes are candidates for breast cancer susceptibility. Genotype results were available for up to 2205 cases and 1826 controls. In the homologous recombination (HR) pathway, genotype frequencies differed between cases and controls for two polymorphisms in XRCC3; T241M (P=0.015) and IVS5 A>G at nt 17893 (P=0.008). Homozygous carriers of M241 were associated with an increased risk [odds ratio (OR) MM versus TT=1.3 (95% confidence interval (CI) 1.1-1.6)], while the rare allele of IVS5A>G was associated with a dominant protective effect [OR AG versus AA=0.8 (0.7-0.9)]. The association of a rare variant in XRCC2 (R188H) was marginally significant [P=0.07; OR HH versus RR=2.6 (1.0-6.7)]. In the non-homologous end-joining (NHEJ) pathway, a polymorphism in LIG4 (T>C at nt 1977) was associated with a decrease in breast cancer risk [P=0.09; OR CC versus TT=0.7 (0.4-1.0)]. No significant association was found for 12 other polymorphisms in the other genes studied. For XRCC3, we found evidence for four common haplotypes and four rarer ones that appear to have arisen by recombination. Two haplotypes, AGC and GGC, were associated with non-significant reductions in breast cancer risk, and the rare GAT haplotype was associated with a significantly increased risk. These data provide some evidence that variants in XRCC2 and LIG4 alter breast cancer risk, together with stronger evidence that variants of XRCC3 are associated with risk. If these results can be confirmed, understanding the functional basis should improve our understanding of the role of DNA repair in breast carcinogenesis.
A germline TaqI restriction fragment length polymorphism in the intron G of the progesterone receptor (PR) gene designated PROGINS was described to be associated with an increased risk for ovarian carcinoma. It was supposed that the PR isoform A protein associated with PROGINS has an increased stability and therefore, a higher transcriptional activity. This may cause an inadequate control of estrogen receptor (ER) and PR B isoform and lead to the increased risk of tumor development. On the other hand, loss of heterozygosity (LOH) of the chromosomal region 11q22-23, where the PR gene is located, was frequently observed in breast cancer, suggesting the presence of a tumor suppressor gene in this region. Recently, it was reported that PROGINS is associated with a decreased risk for breast cancer. In order to examine if PROGINS is associated with an alteration of the risk for breast cancer, we examined PROGINS in 155 sporadic breast cancer patients in Austrian women and in a control group of 106 healthy volunteers. LOH affecting the PR gene was also analyzed in the tumor patients. No statistically significant difference was found for the frequencies of the PROGINS carriers (23.2%) in the Austrian breast cancer patients and in the healthy control group (26.4%), indicating that PROGINS is not associated with either an increased or a decreased risk for breast cancer. Furthermore, no associations between the PROGINS status and the protein levels of ER and PR, clinical data like tumor type, differentiation grade, tumor size, and the nodal status as well as the age of the patients were found. There was also no significant difference in the frequency of LOH affecting the PR gene in the PROGINS carriers and non carriers, demonstrating that LOH at PR gene is not associated with the PROGINS status.
Biases in systematic reviews and meta-analyses may be examined in 'meta-epidemiological' studies, in which the influence of trial characteristics such as measures of study quality on treatment effect estimates is explored. Published studies to date have analysed data from collections of meta-analyses with binary outcomes, using logistic regression models that assume that there is no between- or within-meta-analysis heterogeneity. Using data from a study of publication bias (39 meta-analyses, 394 published and 88 unpublished trials) and language bias (29 meta-analyses, 297 English language trials and 52 non-English language trials), we compare results from logistic regression models, with and without robust standard errors to allow for clustering on meta-analysis, with results using a 'meta-meta-analytic' approach that can allow for between- and within-meta-analysis heterogeneity. We also consider how to allow for the confounding effects of different trial characteristics. We show that both within- and between meta-analysis heterogeneity may be of importance in the analysis of meta-epidemiological studies, and that confounding exists between the effects of publication status and trial quality.