Retrospective analysis of case-control studies when the population is in Hardy–Weinberg equilibrium

2005 ◽  
Vol 24 (21) ◽  
pp. 3289-3310 ◽  
Author(s):  
K. F. Cheng ◽  
W. J. Lin
Keyword(s):  
Retrospective Analysis ◽  
Case Control ◽  
Case Control Studies ◽  
Weinberg Equilibrium ◽  
Hardy Weinberg Equilibrium

A Simple Loglinear Model for Haplotype Effects in a Case-Control Study Involving Two Unphased Genotypes

2005 ◽  
Vol 4 (1) ◽  
Author(s):  
Stuart G. Baker
Keyword(s):  
Interactive Effect ◽  
Case Control ◽  
Nuisance Parameters ◽  
Design Matrix ◽  
Case Control Studies ◽  
Weinberg Equilibrium ◽  
Hardy Weinberg Equilibrium ◽  
Unphased Genotype ◽  
Unphased Genotype Data ◽  
Control Study

Because haplotypes may parsimoniously summarize the effect of genes on disease, there is great interest in using haplotypes in case-control studies of unphased genotype data. Previous methods for investigating haplotypes effects in case-control studies have not allowed for both of the following two scenarios that could have a large impact on results (i) departures from Hardy-Weinberg equilibrium in controls as well as cases, and (ii) an interactive effect of haplotypes and environmental covariates on the probability of disease. A new method is proposed that generalizes the model of Epstein and Satten to incorporate both (i) and (ii). Computations are relatively simple involving a single loglinear design matrix for parameters modeling the distribution of haplotype frequencies in controls, parameters modeling the effect of haplotypes and covariate-haplotype interactions on disease, and nuisance parameters required for correct inference. Based on simulations with realistic sample sizes, the method is recommended with data from two genotypes, a recessive or dominant model linking haplotypes to disease, and estimates of haplotype effects among haplotypes with a frequency greater than 10%. The methodology is most useful with candidate genotype pairs or for searching through pairs of genotypes when scenarios (i) and (ii) are likely. An example without a covariate illustrates the importance of modeling a departure from Hardy-Weinberg equilibrium in controls.

scholarly journals A likelihood ratio test of population Hardy-Weinberg equilibrium for case-control studies

2009 ◽  
Vol 33 (3) ◽  
pp. 275-280 ◽  
Author(s):  
Chang Yu ◽  
Sanguo Zhang ◽  
Chuan Zhou ◽  
Saba Sile
Keyword(s):  
Likelihood Ratio ◽  
Likelihood Ratio Test ◽  
Case Control ◽  
Ratio Test ◽  
Case Control Studies ◽  
Weinberg Equilibrium ◽  
Hardy Weinberg Equilibrium

Significance of Hardy-Weinberg Equilibrium in Case Control

2004 ◽  
Vol 73 (1) ◽  
pp. 95-95
Author(s):  
Hemant Kumar Bid ◽  
Rama D. Mittal
Keyword(s):  
Case Control ◽  
Weinberg Equilibrium ◽  
Hardy Weinberg Equilibrium

scholarly journals Association of IL-6 -174G>C (rs1800795) polymorphism with cervical cancer susceptibility

2018 ◽  
Vol 38 (5) ◽  
Author(s):  
Hai-Xia Duan ◽  
You-Yi Chen ◽  
Juan-Zi Shi ◽  
Nan-Nan Ren ◽  
Xiao-Juan Li
Keyword(s):  
Cervical Cancer ◽  
Large Scale ◽  
Cancer Susceptibility ◽  
Meta Analysis ◽  
Case Control ◽  
Case Control Studies ◽  
Cervical Cancer Risk ◽  
Hardy Weinberg Equilibrium ◽  
The Relationship ◽  
Multifunctional Cytokine

Interleukin-6 (IL-6) is a multifunctional cytokine that has been implicated in the etiology of cancer. Several case–control studies have been conducted to assess the association of IL-6 -174G>C (rs1800795) polymorphism with the risk of cervical cancer, yet with conflicting conclusions. To derive a more precise estimation of the relationship, we performed this meta-analysis updated to June 2018. A total of seven original publications were identified covering IL-6 -174G>C (rs1800795) polymorphism. Odds ratios (ORs) and 95% confidence intervals (CIs) were used to assess the relationship strengths. Statistically significant relationship was observed between IL-6 -174G>C polymorphism and cervical cancer risk (OR = 0.61, 95% CI: 0.40–0.94 for GG vs. CC, and OR = 0.77, 95% CI: 0.64–0.93 for G vs. C). Moreover, the significant association was found among Asians (OR = 0.46, 95% CI: 0.29–0.75 for GG vs. CC, and OR = 0.70, 95% CI: 0.57–0.89 for G vs. C); hospital-based subgroup (OR = 0.53, 95% CI: 0.38–0.72 for GG vs. CC, and OR = 0.73, 95% CI: 0.61–0.87 for G vs. C); and Hardy–Weinberg equilibrium ≤0.05 (OR = 0.56, 95% CI: 0.37–0.86 for GG vs. GC, and OR = 0.66, 95% CI: 0.47–0.93 for G vs. C). This meta-analysis showed the evidence that the IL-6 -174G>C polymorphism was a low-penetrance susceptibility variant for cervical cancer. Further large-scale case–control studies are needed to confirm these results.

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