Iranian Journal of

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Background: Numerous studies have confirmed the association between type 1 diabetes mellitus (DM1) and polymorphisms of HLA genes on chromosome 6p21. Controlled DNA studies in Belgium recently have found a statistically significant association between DM1 and certain HLA class II genes, especially DRB1Lys71+.
Methods: 81 Danish families (each with at least 2 members with DM1) and 82 healthy controls were assessed for HLA polymorphisms. 54 of the 81 diabetic families were also assessed for polymorphisms at the HLA-B-DQB1, HLA-B-DQA1, and TNF-A and TNF-B loci. Affected sib-pair analysis was used to study correlation between DM1 and DRB1 alleles encoding Lys71+.
Results: Homozygous expression of DRB1Lys71+ carried a relative risk (RR) of 103.5 for DM1. There was a very strong correlation (p<1×10-6) between DM1 and DRB1 alleles encoding Lys71+. Family-based association studies showed that DRB1Lys71+ was the most important determinant of DM1 in carriers (haplotype relative risk = 8.38). Haplotype analysis confirmed this.
Conclusion: The DRB1Lys71+ allele confers genetic predisposition to DM1 most strongly of all.

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The P-Value cannot present a complete measure of association in medical studies considering the association between categorical variables. In such situations, measures are required to reveal the clinical importance of relation along with their statistical significance, as the effect size. This paper aims to introduce the measures of associations for categorical variables and inferences about them in these studies. Principles and method of calculating measures of associations and inference about them including confidence interval and hypothesis testing were presented to assess the relationship between qualitative variables for all types of medical studies taking into account relevant considerations. Additionaly, the method of reporting of findings were introduced in the context of contingency tables. To investigate the relationship between two binary qualitative variables, should be used the Odds Ratio in cross-sectional or case-control studies, the relative risk in cohort studies, and prevalence ratio in cross-sectional studies and risk difference in all type of studies along with their confidence intervals and/or their significance tests considering the independent or related groups of studies. Additionally, for bigger than 2 by 2 tables, the method of calculating of above mentioned measures considering a reference category and other measures such as Phi, Crammers V, contingency and uncertainty coefficients , Lambda, Gamma, Summers D, Kendals tau-b and tau-c would be recommended. In each of these situations, based on research based examples, calculations of tests were performed and their results were presented. To investigate the relationship between a set of risk factors and binary and multi-category qualitative variables, the introduced analyses are recommended considering the situation and purpose of the proposed study.