A simple nonparametric multipoint procedure to test for linkage through mothers or fathers as well as imprinting effects in the presence of linkage

A simple multipoint procedure to test for parent-of-origin effects in samples of affected siblings is discussed. The procedure consists of artificially changing all full sibs to half-sibs, with distinct mothers or fathers depending on the parental origin to be evaluated, then analyzing these families with commonly used statistics and software. The procedure leads to tests for linkage through mothers or fathers and also leads to a test for imprinting effects in the presence of linkage. Moreover, simulations illustrate that in regions unlinked to susceptibility genes this multipoint procedure does not have an inflated type I error if a sex-averaged genetic map is used, even when large differences exist between male-specific and female-specific maps. In regions linked with susceptibility genes, the test of imprinting is biased under the null hypothesis if differences exist between sex-specific maps, irrespective of the map used in the analysis. The procedure is applied to the Collaborative Study on the Genetics of Alcoholism dataset from the Genetic Analysis Workshop 14. Results indicate that brothers categorized as affected according to the DMS-III-R and Feighner classification show evidence of linkage through fathers to the 6q25 region (p = 0.00038) as well as modest evidence of imprinting (p = 0.018). This region harbors OPRM1, a candidate gene for substance dependence

Using a higher criticism statistic to detect modest effects in a genome-wide study of rheumatoid arthritis

In high-dimensional studies such as genome-wide association studies, the correction for multiple testing in order to control total type I error results in decreased power to detect modest effects. We present a new analytical approach based on the higher criticism statistic that allows identification of the presence of modest effects. We apply our method to the genome-wide study of rheumatoid arthritis provided in the Genetic Analysis Workshop 16 Problem 1 data set. There is evidence for unknown bias in this study that could be explained by the presence of undetected modest effects. We compared the asymptotic and empirical thresholds for the higher criticism statistic. Using the asymptotic threshold we detected the presence of modest effects genome-wide. We also detected modest effects using 90th percentile of the empirical null distribution as a threshold; however, there is no such evidence when the 95th and 99th percentiles were used. While the higher criticism method suggests that there is some evidence for modest effects, interpreting individual single-nucleotide polymorphisms with significant higher criticism statistics is of undermined value. The goal of higher criticism is to alert the researcher that genetic effects remain to be discovered and to promote the use of more targeted and powerful studies to detect the remaining effects

Successful identification of rare variants using oligogenic segregation analysis as a prioritizing tool for whole-exome sequencing studies

We aim to identify rare variants that have large effects on trait variance using a cost-efficient strategy. We use an oligogenic segregation analysis as a prioritizing tool for whole-exome sequencing studies to identify families more likely to harbor rare variants, by estimating the mean number of quantitative trait loci (QTLs) in each family. We hypothesize that families with additional QTLs, relative to the other families, are more likely to segregate functional rare variants. We test the association of rare variants with the traits only in regions where at least modest evidence of linkage with the trait is observed, thereby reducing the number of tests performed. We found that family 7 harbored an estimated two, one, and zero additional QTLs for traits Q1, Q2, and Q4, respectively. Two rare variants (C4S4935 and C6S2981) segregating in family 7 were associated with Q1 and explained a substantial proportion of the observed linkage signal. These rare variants have 31 and 22 carriers, respectively, in the 128-member family and entered through a single but different founder. For Q2, we found one rare variant unique to family 7 that showed small effect and weak evidence of association; this was a false positive. These results are a proof of principle that prioritizing the sequencing of carefully selected extended families is a simple and cost-efficient design strategy for sequencing studies aiming at identifying functional rare variants

Exome-wide association study of pancreatic cancer risk

We conducted a case-control exome-wide association study to discover germline variants in coding regions that affect risk for pancreatic cancer, combining data from 5 studies. We analyzed exome and genome sequencing data from 437 patients with pancreatic cancer (cases) and 1922 individuals not known to have cancer (controls). In the primary analysis, BRCA2 had the strongest enrichment for rare inactivating variants (17/437 cases vs 3/1922 controls) (P=3.27x10(-6); exome-wide statistical significance threshold P<2.5x10(-6)). Cases had more rare inactivating variants in DNA repair genes than controls, even after excluding 13 genes known to predispose to pancreatic cancer (adjusted odds ratio, 1.35, P=.045). At the suggestive threshold (P<.001), 6 genes were enriched for rare damaging variants (UHMK1, AP1G2, DNTA, CHST6, FGFR3, and EPHA1) and 7 genes had associations with pancreatic cancer risk, based on the sequence-kernel association test. We confirmed variants in BRCA2 as the most common high-penetrant genetic factor associated with pancreatic cancer and we also identified candidate pancreatic cancer genes. Large collaborations and novel approaches are needed to overcome the genetic heterogeneity of pancreatic cancer predisposition

On the Classification of Diagonal Coset Modular Invariants

We relate in a novel way the modular matrices of GKO diagonal cosets without fixed points to those of WZNW tensor products. Using this we classify all modular invariant partition functions of $su(3)_k\oplus su(3)_1/su(3)_{k+1}$ for all positive integer level $k$, and $su(2)_k\oplus su(2)_\ell/su(2)_{k+\ell}$ for all $k$ and infinitely many $\ell$ (in fact, for each $k$ a positive density of $\ell$). Of all these classifications, only that for $su(2)_k\oplus su(2)_1/su(2)_{k+1}$ had been known. Our lists include many new invariants.Comment: 24 pp (plain tex

SUP: an extension to SLINK to allow a larger number of marker loci to be simulated in pedigrees conditional on trait values

BACKGROUND: With the recent advances in high-throughput genotyping technologies that allow for large-scale association mapping of human complex traits, promising statistical designs and methods have been emerging. Efficient simulation software are key elements for the evaluation of the properties of new statistical tests. SLINK is a flexible simulation tool that has been widely used to generate the segregation and recombination processes of markers linked to, and possibly associated with, a trait locus, conditional on trait values in arbitrary pedigrees. In practice, its most serious limitation is the small number of loci that can be simulated, since the complexity of the algorithm scales exponentially with this number. RESULTS: I describe the implementation of a two-step algorithm to be used in conjunction with SLINK to enable the simulation of a large number of marker loci linked to a trait locus and conditional on trait values in families, with the possibility for the loci to be in linkage disequilibrium. SLINK is used in the first step to simulate genotypes at the trait locus conditional on the observed trait values, and also to generate an indicator of the descent path of the simulated alleles. In the second step, marker alleles or haplotypes are generated in the founders, conditional on the trait locus genotypes simulated in the first step. Then the recombination process between the marker loci takes place conditionally on the descent path and on the trait locus genotypes. This two-step implementation is often computationally faster than other software that are designed to generate marker data linked to, and possibly associated with, a trait locus. CONCLUSION: Because the proposed method uses SLINK to simulate the segregation process, it benefits from its flexibility: the trait may be qualitative with the possibility of defining different liability classes (which allows for the simulation of gene-environment interactions or even the simulation of multi-locus effects between unlinked susceptibility regions) or it may be quantitative and normally distributed. In particular, this implementation is the only one available that can generate a large number of marker loci conditional on the set of observed quantitative trait values in pedigrees

Genetic variants and susceptibility to neurological complications followingWest Nile virus infection

To determine genetic factors predisposing to neurological complications following West Nile virus infection, we analyzed a cohort of 560 neuroinvasive case patients and 950 control patients for 13 371 mostly nonsynonymous single-nucleotide polymorphisms (SNPs). The top 3 SNPs on the basis of statistical significance were also in genes of biological plausibility: rs2066786 in RFC1 (replication factor C1) (P 5 1

Identification of genes expressed by immune cells of the colon that are regulated by colorectal cancer-associated variants.

A locus on human chromosome 11q23 tagged by marker rs3802842 was associated with colorectal cancer (CRC) in a genome-wide association study; this finding has been replicated in case-control studies worldwide. In order to identify biologic factors at this locus that are related to the etiopathology of CRC, we used microarray-based target selection methods, coupled to next-generation sequencing, to study 103 kb at the 11q23 locus. We genotyped 369 putative variants from 1,030 patients with CRC (cases) and 1,061 individuals without CRC (controls) from the Ontario Familial Colorectal Cancer Registry. Two previously uncharacterized genes, COLCA1 and COLCA2, were found to be co-regulated genes that are transcribed from opposite strands. Expression levels of COLCA1 and COLCA2 transcripts correlate with rs3802842 genotypes. In colon tissues, COLCA1 co-localizes with crystalloid granules of eosinophils and granular organelles of mast cells, neutrophils, macrophages, dendritic cells and differentiated myeloid-derived cell lines. COLCA2 is present in the cytoplasm of normal epithelial, immune and other cell lineages, as well as tumor cells. Tissue microarray analysis demonstrates the association of rs3802842 with lymphocyte density in the lamina propria (p = 0.014) and levels of COLCA1 in the lamina propria (p = 0.00016) and COLCA2 (tumor cells, p = 0.0041 and lamina propria, p = 6 × 10(-5)). In conclusion, genetic, expression and immunohistochemical data implicate COLCA1 and COLCA2 in the pathogenesis of colon cancer. Histologic analyses indicate the involvement of immune pathways