Multivisceral intestinal transplantation: Surgical pathology

We report the diagnostic surgical pathology of two children who underwent multivisceral abdominal transplantation and survived for 1 month and 6 months. There is little relevant literature, and diagnostic criteria for the various clinical possibilities are not established; this is made more complicated by the simultaneous occurrence of more than one process. We based our interpretations on conventional histology, augmented with immunohistology, including HLA staining that distinguished graft from host cells in situ. In some instances functional analysis of T cells propagated from the same biopsies was available and was used to corroborate morphological interpretations. A wide spectrum of changes was encountered. Graft-versus-host disease, a prime concern before surgery, was not seen. Rejection was severe in 1 patient, not present in the other, and both had evidence of lymphoproliferative disease, which was related to Epstein-Barr virus. Bacterial translocation through the gut wall was also a feature in both children. This paper documents and illustrates the various diagnostic possibilities.. © 1989 Informa UK Ltd All rights reserved: reproduction in whole or part not permitted

Residue management in double-crop systems: Impact on soybean growth and yield

Double-crop soybeans [Glycine max(L.) Merr.] have the potential to be a productive and profitable system. However, due to delayed planting, double-crop soybeans frequently experience lower yields and higher stress. Because planting is a major production constraint, a critical practice is the management of previous wheat residue. Trials were established in 2012, 2013, and 2014 in Saint Joseph, LA, and in 2013 and 2014 in Winnsboro, LA. The four residue management treatments investigated included conventionally tilled, planted into burned residue, planted into mowed residue, and planted into standing wheat residue. Vegetative and reproductive growth parameters, as well as yield, were used to evaluate the influence of residue management on productivity. Overall, residue management did not have a significant impact on early season growth parameters, except for plant height in 2012 at St. Joseph; however, it did significantly influence yield at both locations. In Saint Joseph in 2012, yields from planting into wheat residue were significantly lower than burned and mowed plots (1.2 compared with 2.8 and 2.7 Mg ha-1, respectively), and tilled treatments yielded significantly less than all three nontilled treatments in 2013 and 2014. In Winnsboro, planting into residue left on the soil surface resulted in significantly higher yields than when residue was removed. Overall, leaving residue on the soil surface provided stable yields across years and locations; however, not managing the residue can result in diminished yields. Therefore, practices such as mowing of wheat residue prior to planting provide an alternative to traditional no-till planting.Peer reviewedPlant and Soil Science

A genome-wide scan for common alleles affecting risk for autism

Although autism spectrum disorders (ASDs) have a substantial genetic basis, most of the known genetic risk has been traced to rare variants, principally copy number variants (CNVs). To identify common risk variation, the Autism Genome Project (AGP) Consortium genotyped 1558 rigorously defined ASD families for 1 million single-nucleotide polymorphisms (SNPs) and analyzed these SNP genotypes for association with ASD. In one of four primary association analyses, the association signal for marker rs4141463, located within MACROD2, crossed the genome-wide association significance threshold of P < 5 × 10−8. When a smaller replication sample was analyzed, the risk allele at rs4141463 was again over-transmitted; yet, consistent with the winner's curse, its effect size in the replication sample was much smaller; and, for the combined samples, the association signal barely fell below the P < 5 × 10−8 threshold. Exploratory analyses of phenotypic subtypes yielded no significant associations after correction for multiple testing. They did, however, yield strong signals within several genes, KIAA0564, PLD5, POU6F2, ST8SIA2 and TAF1C

Discovering joint associations between disease and gene pairs with a novel similarity test

Genes in a functional pathway can have complex interactions. A gene might activate or suppress another gene, so it is of interest to test joint associations of gene pairs. To simultaneously detect the joint association between disease and two genes (or two chromosomal regions), we propose a new test with the use of genomic similarities. Our test is designed to detect epistasis in the absence of main effects, main effects in the absence of epistasis, or the presence of both main effects and epistasis. Results: The simulation results show that our similarity test with the matching measure is more powerful than the Pearson's chi(2) test when the disease mutants were introduced at common haplotypes, but is less powerful when the disease mutants were introduced at rare haplotypes. Our similarity tests with the counting measures are more sensitive to marker informativity and linkage disequilibrium patterns, and thus are often inferior to the similarity test with the matching measure and the Pearson 's chi(2) test. Conclusions: In detecting joint associations between disease and gene pairs, our similarity test is a complementary method to the Pearson's chi(2) test

Testing gene-environment interactions in gene-based association studies

Gene-based and single-nucleotide polymorphism (SNP) set association studies provide an important complement to SNP analysis. Kernel-based nonparametric regression has recently emerged as a powerful and flexible tool for this purpose. Our goal is to explore whether this approach can be extended to incorporate and test for interaction effects, especially for genes containing rare variant SNPs. Here, we construct nonparametric regression models that can be used to include a gene-environment interaction effect under the framework of the least-squares kernel machine and examine the performance of the proposed method on the Genetic Analysis Workshop 17 unrelated individuals data set. Two hundred simulated replicates were used to explore the power for detecting interaction. We demonstrate through a genome scan of the quantitative phenotype Q1 that the simulated gene-environment interaction effect in the data can be detected with reasonable power by using the least-squares kernel machine method

Haplotype association analyses in resources of mixed structure using Monte Carlo testing

<p>Abstract</p> <p>Background</p> <p>Genomewide association studies have resulted in a great many genomic regions that are likely to harbor disease genes. Thorough interrogation of these specific regions is the logical next step, including regional haplotype studies to identify risk haplotypes upon which the underlying critical variants lie. Pedigrees ascertained for disease can be powerful for genetic analysis due to the cases being enriched for genetic disease. Here we present a Monte Carlo based method to perform haplotype association analysis. Our method, hapMC, allows for the analysis of full-length and sub-haplotypes, including imputation of missing data, in resources of nuclear families, general pedigrees, case-control data or mixtures thereof. Both traditional association statistics and transmission/disequilibrium statistics can be performed. The method includes a phasing algorithm that can be used in large pedigrees and optional use of pseudocontrols.</p> <p>Results</p> <p>Our new phasing algorithm substantially outperformed the standard expectation-maximization algorithm that is ignorant of pedigree structure, and hence is preferable for resources that include pedigree structure. Through simulation we show that our Monte Carlo procedure maintains the correct type 1 error rates for all resource types. Power comparisons suggest that transmission-disequilibrium statistics are superior for performing association in resources of only nuclear families. For mixed structure resources, however, the newly implemented pseudocontrol approach appears to be the best choice. Results also indicated the value of large high-risk pedigrees for association analysis, which, in the simulations considered, were comparable in power to case-control resources of the same sample size.</p> <p>Conclusions</p> <p>We propose hapMC as a valuable new tool to perform haplotype association analyses, particularly for resources of mixed structure. The availability of meta-association and haplotype-mining modules in our suite of Monte Carlo haplotype procedures adds further value to the approach.</p

Regulation of immune responses in primary biliary cholangitis: a transcriptomic analysis of peripheral immune cells

BACKGROUND AIMS: In patients with primary biliary cholangitis (PBC), the serum liver biochemistry measured during treatment with ursodeoxycholic acid-the UDCA response-accurately predicts long-term outcome. Molecular characterization of patients stratified by UDCA response can improve biological understanding of the high-risk disease, thereby helping to identify alternative approaches to disease-modifying therapy. In this study, we sought to characterize the immunobiology of the UDCA response using transcriptional profiling of peripheral blood mononuclear cell subsets. METHODS: We performed bulk RNA-sequencing of monocytes and TH1, TH17, TREG, and B cells isolated from the peripheral blood of 15 PBC patients with adequate UDCA response ("responders"), 16 PBC patients with inadequate UDCA response ("nonresponders"), and 15 matched controls. We used the Weighted Gene Co-expression Network Analysis to identify networks of co-expressed genes ("modules") associated with response status and the most highly connected genes ("hub genes") within them. Finally, we performed a Multi-Omics Factor Analysis of the Weighted Gene Co-expression Network Analysis modules to identify the principal axes of biological variation ("latent factors") across all peripheral blood mononuclear cell subsets. RESULTS: Using the Weighted Gene Co-expression Network Analysis, we identified modules associated with response and/or disease status (q<0.05) in each peripheral blood mononuclear cell subset. Hub genes and functional annotations suggested that monocytes are proinflammatory in nonresponders, but antiinflammatory in responders; TH1 and TH17 cells are activated in all PBC cases but better regulated in responders; and TREG cells are activated-but also kept in check-in responders. Using the Multi-Omics Factor Analysis, we found that antiinflammatory activity in monocytes, regulation of TH1 cells, and activation of TREG cells are interrelated and more prominent in responders. CONCLUSIONS: We provide evidence that adaptive immune responses are better regulated in patients with PBC with adequate UDCA response

Consequences of epistasis on growth in an erhualian × white duroc pig cross

Epistasis describes an interaction between the effects of loci. We included epistasis in quantitative trait locus (QTL) mapping of growth at a series of ages in a cross of a Chinese pig breed, Erhualian, with a commercial line, White Duroc. Erhualian pigs have much lower growth rates than White Duroc. We improved a method for genomewide testing of epistasis and present a clear analysis workflow. We also suggest a new approach for interpreting epistasis results where significant additive and dominance effects of a locus in specific backgrounds are determined. In total, seventeen QTL were found and eleven showed epistasis. Loci on chromosomes 2, 3, 4 and 7 were highlighted as affecting growth at more than one age or forming an interaction network. Epistasis resulted in both the QTL on chromosomes 3 and 7 having effects in opposite directions. We believe it is the first time for the chromosome 7 locus that an allele from a Chinese breed has been found to decrease growth. The consequences of epistasis were diverse. Results were impacted by using growth rather than body weight as the phenotype and by correcting for an effect of mother. Epistasis made a considerable contribution to growth in this population and modelling epistasis was important for accurately determining QTL effects

A cooperative interaction between LPHN3 and 11q doubles the risk for ADHD

In previous studies of a genetic isolate, we identified significant linkage of attention deficit hyperactivity disorder (ADHD) to 4q, 5q, 8q, 11q and 17p. The existence of unique large size families linked to multiple regions, and the fact that these families came from an isolated population, we hypothesized that two-locus interaction contributions to ADHD were plausible. Several analytical models converged to show significant interaction between 4q and 11q (P<1 × 10−8) and 11q and 17p (P<1 × 10−6). As we have identified that common variants of the LPHN3 gene were responsible for the 4q linkage signal, we focused on 4q–11q interaction to determine that single-nucleotide polymorphisms (SNPs) harbored in the LPHN3 gene interact with SNPs spanning the 11q region that contains DRD2 and NCAM1 genes, to double the risk of developing ADHD. This interaction not only explains genetic effects much better than taking each of these loci effects by separated but also differences in brain metabolism as depicted by proton magnetic resonance spectroscopy data and pharmacogenetic response to stimulant medication. These findings not only add information about how high order genetic interactions might be implicated in conferring susceptibility to develop ADHD but also show that future studies of the effects of genetic interactions on ADHD clinical information will help to shape predictive models of individual outcome