Linkage and association analysis of GAW15 simulated data: fine-mapping of chromosome 6 region

We performed linkage and family-based association analysis across chromosomes 1–22 in Replicates 1–5 of the Genetic Analysis Workshop 15 simulated data. Linkage analysis was performed using the Kong and Cox allele-sharing test as implemented in the program Merlin. Association analysis was performed using the transmission/disequilibrium test (TDT). A region on chromosome 6 was consistently highlighted as showing significant linkage to and association with the disease trait. We focused in on this region and performed fine-mapping using stepwise regression approaches using the case/control and family-based data. In this region, we also applied several new methods, implemented in the computer programs LAMP and Graphminer, respectively, that have recently been proposed for association analysis with family and/or case/control data. All methods confirmed the highly significant associations previously observed. Differentiating between potentially causal single nucleotide polymorphisms (SNPs) and other non-causal loci (associated with disease merely due to linkage disequilibrium) proved to be problematic. However, in most replicates we did identify two SNPs (either SNPs 3437 and 3439 from the dense SNP set, or SNPs 153 and 3437 from the combined non-dense/dense SNP set) that together explain most of the observed disease association in the DR/C locus region, and an additional SNP (3931 or 3933) that accounts for the association 5 cM away at locus D

Linkage analysis of GAW14 simulated data: comparison of multimarker, multipoint, and conditional approaches

The purposes of this study were 1) to examine the performance of a new multimarker regression approach for model-free linkage analysis in comparison to a conventional multipoint approach, and 2) to determine the whether a conditioning strategy would improve the performance of the conventional multipoint method when applied to data from two interacting loci. Linkage analysis of the Kofendrerd Personality Disorder phenotype to chromosomes 1 and 3 was performed in three populations for all 100 replicates of the Genetic Analysis Workshop 14 simulated data. Three approaches were used: a conventional multipoint analysis using the Zlr statistic as calculated in the program ALLEGRO; a conditioning approach in which the per-family contribution on one chromosome was weighted according to evidence for linkage on the other chromosome; and a novel multimarker regression approach. The multipoint and multimarker approaches were generally successful in localizing known susceptibility loci on chromosomes 1 and 3, and were found to give broadly similar results. No advantage was found with the per-family conditioning approach. The effect on power and type I error of different choices of weighting scheme (to account for different numbers of affected siblings) in the multimarker approach was examined

Increased Power for Detection of Parent-of-Origin Effects via the Use of Haplotype Estimation

Parent-of-origin (or imprinting) effects relate to the situation in which traits are influenced by the allele inherited from only one parent and the allele from the other parent has little or no effect. Given SNP genotype data from case-parent trios, the parent of origin of each allele in the offspring can often be deduced unambiguously; however, this is not true when all three individuals are heterozygous. Most existing methods for investigating parent-of-origin effects operate on a SNP-by-SNP basis and either perform some sort of averaging over the possible parental transmissions or else discard ambiguous trios. If the correct parent of origin at a SNP could be determined, this would provide extra information and increase the power for detecting the effects of imprinting. We propose making use of the surrounding SNP information, via haplotype estimation, to improve estimation of parent of origin at a test SNP for case-parent trios, case-mother duos, and case-father duos. This extra information is then used in a multinomial modeling approach for estimating parent-of-origin effects at the test SNP. We show through computer simulations that our approach has increased power over previous approaches, particularly when the data consist only of duos. We apply our method to two real datasets and find a decrease in significance of p values in genomic regions previously thought to possibly harbor imprinting effects, thus weakening the evidence that such effects actually exist in these regions, although some regions retain evidence of significant effects

A genome-wide scan for type 1 diabetes susceptibility genes in nuclear families with multiple affected siblings in Finland

<p>Abstract</p> <p>Background</p> <p>A genome-wide search for genes that predispose to type 1 diabetes using linkage analysis was performed using 900 microsatellite markers in 70 nuclear families with affected siblings from Finland, a population expected to be more genetically homogeneous than others, and having the highest incidence of type 1 diabetes in the world and, yet, the highest proportion in Europe of cases (10%) carrying neither of the highest risk <it>HLA </it>haplotypes that include DR3 or DR4 alleles.</p> <p>Results</p> <p>In addition to the evidence of linkage to the <it>HLA </it>region on 6p21 (nominal p = 4.0 × 10^-6), significant evidence of linkage in other chromosome regions was not detected with a single-locus analysis. The two-locus analysis conditional on the <it>HLA </it>gave a maximum lod score (MLS) of 3.1 (nominal p = 2 × 10^-4) on chromosome 9p13 under an additive model; MLS of 2.1 (nominal p = 6.1 × 10^-3) on chromosome 17p12 and MLS of 2.5 (nominal p = 2.9 × 10^-3) on chromosome 18p11 under a general model.</p> <p>Conclusion</p> <p>Our genome scan data confirmed the primary contribution of the <it>HLA </it>genes also in the high-risk Finnish population, and suggest that non-<it>HLA </it>genes also contribute to the familial clustering of type 1 diabetes in Finland.</p

Common polymorphism in H19 associated with birthweight and cord blood IGF-II levels in humans.

BACKGROUND: Common genetic variation at genes that are imprinted and exclusively maternally expressed could explain the apparent maternal-specific inheritance of low birthweight reported in large family pedigrees. We identified ten single nucleotide polymorphisms (SNPs) in H19, and we genotyped three of these SNPs in families from the contemporary ALSPAC UK birth cohort (1,696 children, 822 mothers and 661 fathers) in order to explore associations with size at birth and cord blood IGF-II levels. RESULTS: Both offspring's and mother's H19 2992C>T SNP genotypes showed associations with offspring birthweight (P = 0.03 to P = 0.003) and mother's genotype was also associated with cord blood IGF-II levels (P = 0.0003 to P = 0.0001). The offspring genotype association with birthweight was independent of mother's genotype (P = 0.01 to P = 0.007). However, mother's untransmitted H19 2992T allele was also associated with larger birthweight (P = 0.04) and higher cord blood IGF-II levels (P = 0.002), suggesting a direct effect of mother's genotype on placental IGF-II expression and fetal growth. The association between mother's untransmitted allele and cord blood IGF-II levels was more apparent in offspring of first pregnancies than subsequent pregnancies (P-interaction = 0.03). Study of the independent Cambridge birth cohort with available DNA in mothers (N = 646) provided additional support for mother's H19 2992 genotype associations with birthweight (P = 0.04) and with mother's glucose levels (P = 0.01) in first pregnancies. CONCLUSION: The common H19 2992T allele, in the mother or offspring or both, may confer reduced fetal growth restraint, as indicated by associations with larger offspring birth size, higher cord blood IGF-II levels, and lower compensatory early postnatal catch-up weight gain, that are more evident among mother's smaller first-born infants.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Chromosome 11q13.5 variant associated with childhood eczema:an effect supplementary to filaggrin mutations

BackgroundAtopic eczema is a common inflammatory skin disease with multifactorial etiology. The genetic basis is incompletely understood; however, loss of function mutations in the filaggrin gene (FLG) are the most significant and widely replicated genetic risk factor reported to date. The first genome-wide association study in atopic eczema recently identified 2 novel genetic variants in association with eczema susceptibility: a single nucleotide polymorphism on chromosome 11q13.5 (rs7927894) and a single nucleotide polymorphism (rs877776) within the gene encoding hornerin on chromosome 1q21.ObjectiveTo test the association of these 2 novel variants with pediatric eczema and to investigate their interaction with FLG null mutations.MethodsCase-control study to investigate the association of rs7927894, rs877776 and the 4 most prevalent FLG null mutations with moderate-severe eczema in 511 Irish pediatric cases and 1000 Irish controls. Comprehensive testing for interaction between each of the loci was also performed.ResultsThe association between rs7927894 and atopic eczema was replicated in this population (P = .0025, χ2 test; odds ratio, 1.27; 95% CI, 1.09-1.49). The 4 most common FLG null variants were strongly associated with atopic eczema (P = 1.26 × 10−50; combined odds ratio, 5.81; 95% CI, 4.51-7.49). Interestingly, the rs7927894 association was independent of the well-established FLG risk alleles and may be multiplicative in its effect. There was no significant association between rs877776 and pediatric eczema in this study.ConclusionSingle nucleotide polymorphism rs7927894 appears to mark a genuine eczema susceptibility locus that will require further elucidation through fine mapping and functional analysis