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Increased immunoglobulin G (IgG) response to dietary antigens can be associated with gastrointestinal dysfunction and autoimmunity. The underlying processes contributing to these adverse reactions remain largely unknown, and it is likely that genetic factors play a role. Here, we estimate heritability and attempt to localize genetic factors influencing IgG antibody levels against food-derived antigens using an integrative genomics approach. IgG antibody levels were determined by ELISA in >1,300 Mexican Americans for the following food antigens: wheat gliadin; bovine casein; and two forms of bovine serum albumin (BSA-a and BSA-b). Pedigree-based variance components methods were used to estimate additive genetic heritability (h(2) ), perform genome-wide association analyses, and identify transcriptional signatures (based on 19,858 transcripts from peripheral blood lymphocytes). Heritability estimates were significant for all traits (0.15-0.53), and shared environment (based on shared residency among study participants) was significant for casein (0.09) and BSA-a (0.33). Genome-wide significant evidence of association was obtained only for antibody to gliadin (P = 8.57 × 10(-8) ), mapping to the human leukocyte antigen II region, with HLA-DRA and BTNL2 as the best candidate genes. Lack of association of known celiac disease risk alleles HLA-DQ2.5 and -DQ8 with antigliadin antibodies in the studied population suggests a separate genetic etiology. Significant transcriptional signatures were found for all IgG levels except BSA-b. These results demonstrate that individual genetic differences contribute to food antigen antibody measures in this population. Further investigations may elucidate the underlying immunological processes involved., (© 2014 WILEY PERIODICALS, INC.)

The phenomenon of synthetic association raises the possibility that common variant genetic markers may be coupled with functional rare variants sufficiently often to allow the rare variants to be tagged by the common ones. Using human exome sequence data from the 1000 Genomes Project, two investigative teams in Group 12 of Genetic Analysis Workshop 17 found that stochastic coupling between rare and common variants does occur, although perhaps not sufficiently often that we can expect common variant signals to reflect synthetic association; other teams considered methods for detecting association using both rare and common variants. Common themes were that synthetic association is more apparent in population strata (ancestral or familial) and that careful selection of the unit of analysis (gene, gene network, or other genomic subset) is likely to be crucial to the discovery of rare variants that contribute to risk of disease., (© 2011 Wiley Periodicals, Inc.)

Positional gene discovery on pedigree data typically involves initial gross localization by linkage analysis with subsequent finer localization by association analysis in areas that show evidence of linkage. We examine the effect of including linkage information when testing for association in the context of variance-components-based pedigree analysis. We present simulation experiments showing that, at least in the extreme case of a rare private allele, failing to include the linkage variance component in the association model results in excessive Type I error that increases with allele copy number and/or quantitative trait locus (QTL) effect size. Joint estimation of the linkage variance component in the association model reduces Type I error to nominal expectations. This holds whether allele-sharing probabilities are estimated from a polymorphic marker or from the very single-nucleotide polymorphism (SNP) being tested for association, although the latter provides much less power. These results support the idea that an appropriate association analysis must test both the random effect of shared marker alleles (linkage) and the mean effects of the marker genotypes (association).

We propose a method for efficient estimation of the additive genetic effect of the X chromosome with explicit modeling of eutherian-type dosage compensation. The theoretical derivation of the variance-components model for X-linked loci is reviewed in detail. We develop a model of dosage compensation that allows for both incomplete and heterogeneous lyonization, the existence of which is suggested by recent expression studies. Modeling this relationship, especially in the limit cases of complete or absent compensation, allows estimation of the X effect as a single parameter for ease of comparison to other sources of variance. We present simulation studies to estimate the power and computational efficiency of our proposed method.