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      Gene-Gene and Gene-Environment Interactions in Meta-Analysis of Genetic Association Studies

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          Abstract

          Extensive genetic studies have identified a large number of causal genetic variations in many human phenotypes; however, these could not completely explain heritability in complex diseases. Some researchers have proposed that the “missing heritability” may be attributable to gene–gene and gene–environment interactions. Because there are billions of potential interaction combinations, the statistical power of a single study is often ineffective in detecting these interactions. Meta-analysis is a common method of increasing detection power; however, accessing individual data could be difficult. This study presents a simple method that employs aggregated summary values from a “case” group to detect these specific interactions that based on rare disease and independence assumptions. However, these assumptions, particularly the rare disease assumption, may be violated in real situations; therefore, this study further investigated the robustness of our proposed method when it violates the assumptions. In conclusion, we observed that the rare disease assumption is relatively nonessential, whereas the independence assumption is an essential component. Because single nucleotide polymorphisms (SNPs) are often unrelated to environmental factors and SNPs on other chromosomes, researchers should use this method to investigate gene–gene and gene–environment interactions when they are unable to obtain detailed individual patient data.

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          Most cited references 13

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          A method for quantifying differentiation between populations at multi-allelic loci and its implications for investigating identity and paternity.

          A method is proposed for allowing for the effects of population differentiation, and other factors, in forensic inference based on DNA profiles. Much current forensic practice ignores, for example, the effects of coancestry and inappropriate databases and is consequently systematically biased against defendants. Problems with the 'product rule' for forensic identification have been highlighted by several authors, but important aspects of the problems are not widely appreciated. This arises in part because the match probability has often been confused with the relative frequency of the profile. Further, the analogous problems in paternity cases have received little attention. The proposed method is derived under general assumptions about the underlying population genetic processes. Probabilities relevant to forensic inference are expressed in terms of a single parameter whose values can be chosen to reflect the specific circumstances. The method is currently used in some UK courts and has important advantages over the 'Ceiling Principle' method, which has been criticized on a number of grounds.
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            A comparison of summary patient-level covariates in meta-regression with individual patient data meta-analysis.

            To compare meta-analysis of summary study level data with the equivalent individual patient data (IPD) analysis when interest lies in identification of binary patient characteristics related to treatment efficacy. A simulation study comparing meta-regression with IPD analyses of randomized controlled trials. Twenty-seven different meta-analysis situations were simulated with 1000 repetitions in each case. The following parameters were varied: (1) the treatment effect magnitude for different patient risk groups; (2) sample sizes of individual studies; and (3) number of studies. The meta-regression and IPD results were then compared for each situation. The statistical power of meta-regression was dramatically and consistently lower than that of IPD analysis, with little agreement between the parameter estimates obtained from the two methods. Only in meta-analyses of large numbers of large trials, did meta-regression detect differential treatment effects between risk groups with any consistency. Meta-analysis of summary data may be adequate when estimating a single pooled treatment effect or investigating study level characteristics. However, when interest lies in investigating whether patient characteristics are related to treatment, IPD analysis will generally be necessary to discover any such relationships. In these situations practitioners should try to obtain individual-level data.
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              The strengths and limitations of meta-analyses based on aggregate data

              Background Properly performed systematic reviews and meta-analyses are thought by many to represent among the highest level of evidence addressing important clinical issues. Few would disagree that meta-analyses based on individual patient data (IPD) offer several advantages and represent the standard to which all other systematic reviews should be compared. Methods All cancer-related meta-analyses cited in Medline were classified as based on aggregate or individual patient data. A review was then undertaken of all reports comparing the comparative strengths and limitations of meta-analyses using either aggregate or individual patient data. Results The majority of published meta-analyses are based on summary or aggregate patient data (APD). Reasons suggested for this include the considerable resources, years of study and often, broad international cooperation required for IPD meta-analyses. Many of the most important features of systematic reviews including formal meta-analyses are addressed by both IPD and APD meta-analyses. The need for defining an explicit and relevant clinical question, exhaustively searching for the totality of evidence, meticulous and unbiased data transfer or extraction, assessment of between study heterogeneity and the use of appropriate statistical methods for estimating summary effect measures are essentially the same for the two approaches. Conclusion IPD offers advantages and, when feasible, should be considered the best opportunity to summarize the results of multiple studies. However, the resources, time and cooperation required for such studies will continue to limit their use in many important areas of clinical medicine which can be meaningfully and cost-effectively approached by properly performed APD meta-analyses. APD meta-analyses continue to be the mainstay of systematic reviews utilized by the US Preventive Services Task Force, the Cochrane Collaboration and many professional societies to support clinical practice guidelines.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                29 April 2015
                2015
                : 10
                : 4
                Affiliations
                [1 ]Graduate Institute of Life Sciences, National Defense Medical Center, Taipei, Taiwan, ROC
                [2 ]School of Public Health, National Defense Medical Center, Taipei, Taiwan, ROC
                [3 ]Math Teachers’ Office, Kaohsiung Municipal Girls' Senior High School, Kaohsiung, Taiwan, ROC
                Memorial Sloan Kettering Cancer Center, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: CL HYY SLS. Performed the experiments: CL. Analyzed the data: CL. Contributed reagents/materials/analysis tools: CL HYY SLS. Wrote the paper: CL HYY SLS. Critical review and comments: CMC JL. Modified manuscript: CL CMC JL SLS.

                Article
                PONE-D-14-37207
                10.1371/journal.pone.0124967
                4414456
                25923960

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

                Page count
                Figures: 2, Tables: 3, Pages: 13
                Product
                Funding
                The authors received no specific funding for this work.
                Categories
                Research Article
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

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