Evaluation of IDDM8 susceptibility locus in a Russian simplex family data set

Type 1 diabetes (TID) susceptibility locus, IDDM8, has been accurately mapped to 200 kilobases at the terminal end of chromosome 6q27. This is within the region which harbours a cluster of three genes encoding proteasome subunit beta 1 (PMSB1), TATA-box binding protein (TBP) and a homologue of mouse programming cell death activator 2 (PDCD2). In this study, we evaluated whether these genes contribute to TID susceptibility using the transmission disequilibrium test of the data set from 114 affected Russian simplex families. The A allele of the G/A1180 single nucleotide polymorphism (SNP) at the PDCD2 gene, which was significant in its preferential transfer from parents to diabetic children (75 transmissions vs. 47 non-transmissionS, x(2) = 12.85, P corrected = 0.0038), was found to be associated with T1D. G/A1180 dimorphism and two other SNPs, C/T771 TBP and G/T(-271) PDCD2, were shown to share three common haplotypes, two of which (A-T-G and A-T-T) have been associated with higher development risk of TID. The third haplotype (G-T-G) was related to having a lower risk of disease. These findings suggest that the PDCD2 gene is a likely susceptibility gene for TID within IDDM8. However, it was not possible to exclude the TBP gene from being another putative susceptibility gene in this region. (c) 2005 Elsevier Ltd. All rights reserved.

The v-MFG test: Investigating maternal, offspring and maternal-fetal genetic incompatibility effects on disease and viability

The MFG test is a family-based association test that detects genetic effects contributing to disease in offspring, including offspring allelic effects, maternal allelic effects and MFG incompatibility effects. Like many other family-based association tests, it assumes that the offspring survival and the offspring-parent genotypes are conditionally independent provided the offspring is affected. However, when the putative disease-increasing locus can affect another competing phenotype, for example, offspring viability, the conditional independence assumption fails and these tests could lead to incorrect conclusions regarding the role of the gene in disease. We propose the v-MFG test to adjust for the genetic effects on one phenotype, e.g., viability, when testing the effects of that locus on another phenotype, e.g., disease. Using genotype data from nuclear families containing parents and at least one affected offspring, the v-MFG test models the distribution of family genotypes conditional on offspring phenotypes. It simultaneously estimates genetic effects on two phenotypes, viability and disease. Simulations show that the v-MFG test produces accurate genetic effect estimates on disease as well as on viability under several different scenarios. It generates accurate type-I error rates and provides adequate power with moderate sample sizes to detect genetic effects on disease risk when viability is reduced. We demonstrate the v-MFG test with HLA-DRB1 data from study participants with rheumatoid arthritis (RA) and their parents, we show that the v-MFG test successfully detects an MFG incompatibility effect on RA while simultaneously adjusting for a possible viability loss.