Incorporation of covariates into multipoint linkage disequilibrium mapping in case-control studies

Graves' disease and Hashimoto's thyroiditis are organ-specific autoimmune disorders of multifactorial aetiology with a polygenic mode of inheritance. Familial clustering and twin studies provide evidence for a genetic predisposition. Three main approaches have been used in the search for susceptibility loci: population-based case-control studies, classical linkage analysis, and intrafamilial linkage disequilibrium. Case-control studies are a sensitive method of gene detection and the collection of subjects is resource-efficient. However, they require prior knowledge of a candidate gene and are prone to inconsistent results due to false positives that may arise from population mismatch. Linkage analysis is a powerful tool for detecting 'major' genes that does not require a candidate gene and is, therefore, a means of genome screening. This method, however, has limited power to detect genes of 'modest' effect, and the collection of sibpairs and multiple family members may be difficult. Intrafamilial linkage disequilibrium analysis is more sensitive than classical linkage analysis, requires only one affected offspring, and eliminates population mismatch. This approach has confirmed linkage disequilibrium of the HLA region with Graves' disease, previously not detected by linkage analysis. Knowledge of a candidate locus is required, however, and this method cannot, therefore, at present be used for genome screening. It is likely that a combination of all three approaches will be required to identify susceptibility loci for autoimmune thyroid disease.

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Multipoint Linkage-Disequilibrium–Mapping Approach Based on the Case-Parent Trio Design

The American Journal of Human Genetics ◽

10.1086/319504 ◽

2001 ◽

Vol 68 (4) ◽

pp. 937-950 ◽

Cited By ~ 15

Author(s):

Kung-Yee Liang ◽

Fang-Chi Hsu ◽

Terri H. Beaty ◽

Kathleen C. Barnes

Keyword(s):

Linkage Disequilibrium ◽

Linkage Disequilibrium Mapping ◽

Mapping Approach ◽

Multipoint Linkage

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New insights of the correlation between AXIN2 polymorphism and cancer risk and susceptibility: evidence from 72 studies

BMC Cancer ◽

10.1186/s12885-021-08092-0 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Xi Li ◽

Yiming Li ◽

Guodong Liu ◽

Wei Wu

Keyword(s):

Linkage Disequilibrium ◽

Cancer Risk ◽

Risk Allele ◽

Cancer Susceptibility ◽

Case Control ◽

Dominant Model ◽

Case Control Studies ◽

Contrast Model ◽

Different Populations ◽

Allele Contrast

Abstract Background Numerous studies have reported the correlation between AXIN2 polymorphism and cancer risk, but the results seem not consistent. In order to get an overall, accurate and updated results about AXIN2 polymorphism and cancer risk, we conducted this study. Methods An updated analysis was performed to analyze the correlation between AXIN2 polymorphisms and cancer risk. Linkage disequilibrium (LD) analysis was also used to show the associations. Results Seventy-two case-control studies were involved in the study, including 22,087 cases and 18,846 controls. The overall results showed rs11079571 had significant association with cancer risk (allele contrast model: OR = 0.539, 95%CI = 0.478–0.609, PAdjust = 0.025; homozygote model: OR = 0.22, 95% CI = 0.164–0.295, PAdjust< 0.001; heterozygote model: OR = 0.292, 95% CI = 0.216–0.394, PAdjust< 0.001; dominant model: OR = 0.249, 95% CI = 0.189–0.33, PAdjust< 0.001). The same results were obtained with rs1133683 in homozygote and recessive models (PAdjust< 0.05), and in rs35285779 in heterozygote and dominant models (PAdjust< 0.05). LD analysis revealed significant correlation between rs7210356 and rs9915936 in the populations of CEU, CHB&CHS, ESN and JPT (CEU: r2 = 0.91; CHB&CHS: r2 = 0.74; ESN: r2 = 0.62, JPT: r2 = 0.57), and a significant correlation between rs9915936 and rs7224837 in the populations of CHB&CHS, ESN and JPT (r2>0.5), between rs7224837 and rs7210356 in the populations of CEU, CHB&CHS, JPT (r2>0.5), between rs35435678 and rs35285779 in the populations of CEU, CHB&CHS and JPT (r2>0.5). Conclusions AXIN2 rs11079571, rs1133683 and rs35285779 polymorphisms have significant correlations with overall cancer risk. What’s more, two or more polymorphisms such as rs7210356 and rs9915936, rs9915936 and rs7224837, rs7224837 and rs7210356, rs35435678 and rs35285779 have significant correlation with cancer susceptibility in different populations.

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