Impact of Hardy-Weinberg equilibrium deviation on allele-based risk effect of genetic association studies and meta-analysis

• Published in: European journal of epidemiology Vol. 25; no. 8; pp. 553 - 560
• Main Author: Zintzaras, Elias
• Format: Journal Article
• Language: English
• Published: Dordrecht Dordrecht : Springer Netherlands 01.08.2010; Springer; Springer Netherlands; Springer Nature B.V; Springer Verlag
• Subjects: Adjustment; Alleles; Association; Bias; Bias (Epidemiology); Biological and medical sciences; Cardiology; Epidemiology; General aspects; genes; Genetic Association Studies; Genetic Association Studies - methods; Genetic association study; Genetic effects; GENETIC EPIDEMIOLOGY; Genetic equilibrium; Genetic Markers; Genomics; Genotype; Genotype & phenotype; Genotypes; Hardy Weinberg law; Hardy-Weinberg equilibrium; Heterogeneity; Humans; HWE; Infectious Diseases; Linkage Disequilibrium; Medical genetics; Medical sciences; Medicine; Medicine & Public Health; Meta analysis; Meta-Analysis as Topic; methods; Miscellaneous; Molecular Epidemiology; Molecular Epidemiology - methods; odds ratio; Oncology; P values; Polymorphism; Power; Public Health; Public health. Hygiene; Public health. Hygiene-occupational medicine; Risk factors; Sensitivity analysis; Statistical variance; variance; Genetic association study; Association; Hardy–Weinberg equilibrium; Adjustment; Gene; Bias; HWE; Odds ratio; Power; Variance; Meta-analysis; Polymorphism; Human; Evidence-based practice; Risk; Epidemiology; Population genetics; Evidence-based medicine; Metaanalysis; Allele; Risk factor; Hardy-Weinberg equilibrium; Deviation; Public health
• ISSN: 0393-2990; 1573-7284; 1573-7284
• DOI: 10.1007/s10654-010-9467-z

Deviations from Hardy-Weinberg equilibrium (HWE) in control subjects may bias the estimates of genetic effects in genetic association studies (GAS) and meta-analysis. A large empirical evaluation was carried out to evaluate the impact of HWE deviation and explore the effect of variance adjustment for the allele-based odds ratio in 833 individual GAS and 72 meta-analyses. In individual GAS, the variance adjustment for any deviation from HWE resulted in stronger associations, and 10 GAS (1%) became significant (P < 0.05). One hundred sixteen GAS (14%) showed significant deviation from HWE (P HWE < 0.05); however, only 37 GAS (4%) had more than 90% power to detect significant deviation from HWE at the 5% level. In meta-analyses, adjustment for any deviation from HWE improved the significance in 53 meta-analyses (74%). Then, a formal statistical significance (P < 0.05) was revealed for one previously negative meta-analyses whereas one meta-analysis lost its significance. Between-study heterogeneity was enhanced in 50 meta-analyses (69%). None of the meta-analyses lost the significance of heterogeneity (P Q < 0.10) whereas in one meta-analysis, the non significant heterogeneity became significant. Sensitivity analysis for studies not conforming to HWE (P HWE < 0.05) was applied to 45 meta-analyses (69%). Then, the significance of association was increased in 26 the meta-analyses (58%) and one meta-analysis became significant (P < 0.05) whereas seven meta-analyses (16%) were no longer significant. Adjustment for HWE deviation could be an effective strategy for dealing with HWE violations in GAS and meta-analyses.