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Missingness in the T1DGC MHC fine-mapping SNP data: association with HLA genotype and potential influence on genetic association studies.

ABSTRACT: The absence or 'missingness' of single nucleotide polymorphism (SNP) assay values because of genotype or related factors of interest may bias association and other studies. Missingness was determined for the Type 1 Diabetes Genetics Consortium (T1DGC) Major Histocompatibility Complex (MHC) data and was found to vary across the region, ranging up to 11.1% of the non-null proband SNPs, with a median of 0.3%. We consider factors related to missingness in the T1DGC data and briefly assess its possible influence on association studies.We assessed associations of missingness in the SNP assay data with human leucocyte antigen (HLA) genotype of the individual and with SNP genotypes of the parents. Within-cohort analyses were combined (over all cohorts) using (i) Mantel-Haenszel tests for two-by-two tables or (ii) by combining test statistics for larger tables and regression models. Mixed effect regression models were used to assess association of the SNP genotypes with affected status of the offspring after adjustment for parental SNP genotypes, cohort membership and HLA genotypes. Log-linear models were used to assess association of missingness in the unaffected sib assays with SNP genotypes of the probands.Missingness of SNP values near the HLA class I (A, B and C) and class II (DR, DQ and DP) loci is strongly associated with carriage of corresponding HLA genotypes within these groups. Similar associations pertain to missing values among the microsatellite data. In at least some of these cases, regions of missingness coincided with known deletion regions corresponding to the associated HLA haplotype. We conjecture that other regions of associated missingness may point to similar haplotypic deletions. Analysis of association patterns of SNP genotypes with affected status of offspring does not indicate strong informative missingness. However, association of missingness in proband data with parental SNP genotypes may impact transmission disequilibrium test (TDT)-type analyses. Comparisons of affected and unaffected siblings point to possible susceptibility regions additional to the classical HLA-DR3/4 alleles near BAT4-LY6G5B-BAT5 and NOTCH4.Potentially informative missingness in SNP assay values in the MHC region may impact on association and related analyses based on the T1DGC data. These results suggest that it would be prudent to assess the degree to which missingness may abrogate assessed SNP disease markers in such studies. Initial analyses based on comparison of affected and unaffected status in offspring suggest that at least these may be little affected.

SUBMITTER: James I

PROVIDER: S-EPMC2755067 | biostudies-literature | 2009 Feb

REPOSITORIES: biostudies-literature

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Missingness in the T1DGC MHC fine-mapping SNP data: association with HLA genotype and potential influence on genetic association studies.

James I I McKinnon E E Gaudieri S S Morahan G G

Diabetes, obesity & metabolism 20090201

<h4>Aim</h4>The absence or 'missingness' of single nucleotide polymorphism (SNP) assay values because of genotype or related factors of interest may bias association and other studies. Missingness was determined for the Type 1 Diabetes Genetics Consortium (T1DGC) Major Histocompatibility Complex (MHC) data and was found to vary across the region, ranging up to 11.1% of the non-null proband SNPs, with a median of 0.3%. We consider factors related to missingness in the T1DGC data and briefly asses ...[more]

PMID: 19143822

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Project description:AimThe Major Histocompatibility Complex (MHC) is a highly polymorphic region on chromosome 6 encompassing the human leucocyte antigen (HLA)-DQ/DR loci most predictive of susceptibility to type 1 diabetes (T1D). To assess the contribution of other MHC genes, in this exploratory analysis of Type 1 Diabetes Genetics Consortium (T1DGC) family data we characterize association between susceptibility and MHC single nucleotide polymorphism (SNP) genotype, with an emphasis on effects of genetic variation additional to carriage of predisposing or protective MHC haplotypes.MethodsWe use Cox regression analyses of age of onset, stratified by family, to jointly test both linkage and association. Analysis is restricted to children from families having both affected and unaffected siblings and is conducted with and without adjustment for known HLA class I and II effects. Model fits provide scores for each individual that are based on estimates of the probability of being affected by the age of 35, given the individual's SNP genotype. The mean within-family variation in these scores provides a measure that closely reflects the relative size of the likelihood ratio test statistics, and their covariation provides a means of mapping patterns of association that incorporate both effect size and commonality of effect that is attributable to the strong linkage disequilibrium (LD) extending across the region.ResultsUnivariate analyses yielded strong associations with T1D susceptibility that are dominated by SNPs in the class II HLA-DR/DQ region but extend across the MHC. Similar effects are frequently observed across SNPs within multiple genes, sometimes spanning hundreds of kilobases. SNPs within a region at the telomeric end of the class II gene HLA-DRA yielded significant associations with and without adjustment for carriage of the predictive DR3, DR4, DR2 and DR7 HLA haplotypes, and remained highly prominent in a secondary analysis that was restricted to 66 families in whom at least one of the affected siblings carried neither the DR3 nor DR4 haplotype.ConclusionsWhile many of the associations can be attributed to LD between the SNPs and the dominant HLA-DRB/DQA/DQB loci, there is also evidence of additional modifying effects.

Dataset Information

Missingness in the T1DGC MHC fine-mapping SNP data: association with HLA genotype and potential influence on genetic association studies.

Publications

Missingness in the T1DGC MHC fine-mapping SNP data: association with HLA genotype and potential influence on genetic association studies.

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