An Evaluation of Gene-Diet Interaction Statistical Methods and Discovery of rs7175421-Whole Grain Interaction in Lung Cancer.
Dietary factors show different effects on genetically diverse populations. Scientific research uses gene-environment interaction models to study the effects of dietary factors on genetically diverse populations for lung cancer risk. However, previous study designs have not investigated the degree of...
| Publicado en: | Nutrition & Cancer Vol. 75; no. 1; pp. 219 - 228 |
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| Autores principales: | , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Taylor & Francis Ltd
2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=160755249&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 160755249 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01635581 7MS jtl: Nutrition & Cancer issn: 01635581 maglogo: N pubinfo: dt: 2023 vid: 75 iid: 1 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 160755249 158360512 160755249 160755249 10.1080/01635581.2022.2104878 160755249 ppf: 219 ppct: 9 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: An Evaluation of Gene-Diet Interaction Statistical Methods and Discovery of rs7175421-Whole Grain Interaction in Lung Cancer. aug: au: Tao, Jun Helali, Aya El Ho, James C. Lam, Wendy W.T. Pang, Herbert affil: School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong, China sug: subj: Lung Neoplasms Risk Factors Genes Diet Grain Proteins Human Dietary Proteins ab: Dietary factors show different effects on genetically diverse populations. Scientific research uses gene-environment interaction models to study the effects of dietary factors on genetically diverse populations for lung cancer risk. However, previous study designs have not investigated the degree of type I error inflation and, in some instances, have not corrected for multiple testing. Using a motivating investigation of diet-gene interaction and lung cancer risk, we propose a training and testing strategy and perform real-world simulations to select the appropriate statistical methods to reduce false-positive discoveries. The simulation results show that the unconstrained maximum likelihood (UML) method controls the type I error better than the constrained maximum likelihood (CML). The empirical Bayesian (EB) method can compete with the UML method in achieving statistical power and controlling type I error. We observed a significant interaction between SNP rs7175421 with dietary whole grain in lung cancer prevention, with an effect size (standard error) of −0.312 (0.112) for EB estimate. SNP rs7175421 may interact with dietary whole grains in modulating lung cancer risk. Evaluating statistical methods for gene-diet interaction analysis can help balance the statistical power and type I error. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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