Hepatic artery thrombosis in pediatric liver transplantation

Purpose. Children have been reported to be at greater risk for hepatic artery thrombosis when compared to adults due to small arterial size, nonuse of intraoperative microscope, and postoperative hypercoagulable state. Methods. We evaluated arterial anastomosis type, intraoperative field magnification, and hepatic artery complications and how they were managed. All patients underwent ultrasound, anticoagulation consisted of 41 mg aspirin once a day, and 35 patients received alprostadil (PGE) for the first 7 days after transplantation. No patients were administered intravenous heparin following liver transplantation. Results. Of the 74 livers transplanted, 36 grafts (48.6%) were whole organ transplants and 38 grafts (51.4%) were partial livers. We observed HAT in 1 of 74 (1.35%) transplants in our pediatric liver transplant population. The only patient with HAT was a young girl with a history of biliary atresia. The occurrence of a hepatic artery thrombosis on day 7 was caused by the migration of an intimal plaque dissection within the artery graft. She was emergently taken back into the operating room for graft revision. This individual currently has a survival time of 426 days following her last transplant. Conclusion. Hepatic artery thrombosis may be minimized in pediatric liver transplantation without the use of microsurgery. Anticoagulation utilizing ASA and alprostadil is sufficient to avoid HAT. Accurate use of ultrasound is crucial to avoid this complication. Graft and patient salvage is possible with expedient surgical treatment; microsurgery, anticoagulant therapy, site of arterial inflow, and recipient size and weight

Pediatric liver transplantation with daclizumab induction therapy

Background. A new class of monoclonal antibodies (non-T-cell depleting) has gained favor for induction therapy after transplantation. This study evaluated the non-T-cell depleting antibody to the CD25 cell, daclizumab, as a single-dose induction agent immediately after pediatric liver transplantation to spare the use of the calcineurin inhibitor, tacrolimus, for 7 days in respect to both efficacy and renal function. Methods. From January 1998 to November 2001, 81 pediatric orthotopic liver transplant recipients receiving 89 liver grafts were evaluated. The treatment arm (n=61) received daclizumab 1 mg/kg immediately after liver transplantation along with mycophenolate, steroids, and, on postoperative day 7, tacrolimus. The control group did not receive induction therapy, whereas tacrolimus, mycophenolate, and steroids were started immediately after surgery. Results. The induction group had fewer patients with rejection within the first 30 days after liver transplantation (9 [14.8%] vs. 10 [50%]; P=0.003). The mean time to first rejection was similar between groups (12.1 [±7.8] days vs. 18.5 [±8.1] days; P=not significant). There was a 3.39 increase in relative risk to develop rejection within the first 30 days after orthotopic liver transplantation if the patient did not receive induction therapy (relative risk=3.39; 95% confidence interval [1.61, 7.14]). Two-year actuarial survival for the induction group was 93.2% compared with 85% in the control; graft survival was also similar between groups (87.8% vs. 72.7%) at 2 years. Conclusion. Daclizumab 1 mg/kg given immediately after pediatric liver transplantation and withholding tacrolimus, is safe, efficacious, and reduces rejections within the first 30 days after surgery

Adult and pediatric liver transplantation for autoimmune hepatitis

Background. Due to the early age that pediatric patients with autoimmune hepatitis (AIH) are transplanted, it is theorized that older AIH patients may have different outcomes than pediatric patients following liver transplantation. Methods This is a retrospective review of both the adult and pediatric liver transplant programs consisting of 56 patients. Rejection and recurrence of AIH were determined by biopsy. Results. The autoimmune patient having rejection episodes had a 1.76-fold increase in relative risk to develop autoimmune recurrence when compared to patients without rejection [RR = 1.76; 95% CIRR (1.08, 2.86)]. The pediatric group had a 6.62-fold increase in relative risk to develop colitis following liver transplantation [RR = 6.62; 95% C.I.R.R. (1.36, 32.13); P = .02]. Mean days to recurrence of AIH were similar in both groups (1364 ± 1074 vs 936; P = NS). There were more hospitalized days in the pediatric group compared to the adults (20.5 ± 13.3 days vs 51.7 ± 22.2 days, P = .039). OKT-3 was rarely used (n = 5) in either group (9.3% vs 7.7%, P = NS) and was not correlated with which patients would be weaned from steroids or recurrence. Conclusions. Based on this review, pediatric patients were more likely to develop ulcerative colitis following liver transplantation and they incurred longer hospital stays than adults. The adult group was more likely to be weaned from steroids, with AIH recurrence unrelated to weaning

Perm-seq: Mapping Protein-DNA Interactions in Segmental Duplication and Highly Repetitive Regions of Genomes with Prior-Enhanced Read Mapping

<div><p>Segmental duplications and other highly repetitive regions of genomes contribute significantly to cells’ regulatory programs. Advancements in next generation sequencing enabled genome-wide profiling of protein-DNA interactions by chromatin immunoprecipitation followed by high throughput sequencing (ChIP-seq). However, interactions in highly repetitive regions of genomes have proven difficult to map since short reads of 50–100 base pairs (bps) from these regions map to multiple locations in reference genomes. Standard analytical methods discard such multi-mapping reads and the few that can accommodate them are prone to large false positive and negative rates. We developed Perm-seq, a prior-enhanced read allocation method for ChIP-seq experiments, that can allocate multi-mapping reads in highly repetitive regions of the genomes with high accuracy. We comprehensively evaluated Perm-seq, and found that our prior-enhanced approach significantly improves multi-read allocation accuracy over approaches that do not utilize additional data types. The statistical formalism underlying our approach facilitates supervising of multi-read allocation with a variety of data sources including histone ChIP-seq. We applied Perm-seq to 64 ENCODE ChIP-seq datasets from GM12878 and K562 cells and identified many novel protein-DNA interactions in segmental duplication regions. Our analysis reveals that although the protein-DNA interactions sites are evolutionarily less conserved in repetitive regions, they share the overall sequence characteristics of the protein-DNA interactions in non-repetitive regions.</p></div

Comparison of uni-read, CSEM, and Perm-seq analysis.

<p>(a) Comparison of Ctcf optimal peak lists from uni-read, CSEM, and Perm-seq analyses. Numbers in parentheses denote comparisons of the optimal peak lists with the relaxed peak lists. For example, there are 1320 peaks identified by the Perm-seq and CSEM analyses and missed by the uni-read analyses. 664 of these peaks are still missed by the uni-read analysis even if we consider comparison of the Perm-seq and CSEM optimal peak lists with the uni-read relaxed lists. (b) Circos plots of CSEM (left) and Perm-seq (right) read allocation for reads mapping to four segmental duplication regions with coordinates chr1:143,880,003–143,978,943, chr1:206,072,707–206,171,611, and chr1:143,880,003–144,005,301, chr1:120,872,119–249,250,621. (c) Percentages of Perm-seq specific and CSEM specific peaks with the most significant motifs identified from the <i>de novo</i> sequence analysis of the intersection peaks, i.e., peaks common to uni-read, CSEM, and Perm-seq analysis. (d) Comparison of the Ctcf peak sets from GM12878 between Perm-seq, CSEM, Gibbs-based [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004491#pcbi.1004491.ref002" target="_blank">2</a>], and Lonut [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004491#pcbi.1004491.ref004" target="_blank">4</a>]. x.vs.Perm-seq denotes optimal peaks of method “x” not identified by Perm-seq. Similarly, Perm-seq.vs.x denotes optimal peaks of Perm-seq not identified by method “x”. (e) Annotation of the K562 peaks with respect to segmental duplications. Categories are: Prom.Dup: peaks that are in promoter regions (± 2500 bps of TSS) of RefSeq genes that reside in segmental duplications; Prom: Peaks in promoter regions (excludes peaks in Prom.Dup); Genic.Dup: peaks that are within [-10000 bps of TSS, +1000 bps of TES] of RefSeq genes that are in segmental duplications (excludes peaks in Prom.Dup); Genic: peaks that are within [-10000 bps of TSS, +1000 bps of TES] of RefSeq genes (excludes peaks in Genic.Dup, Prom.Dup); Dup: peaks that are in segmental duplications (excludes Prom.Dup and Genic.Dup); None: peaks that do not fall into any of the other defined categories. (f) Genes are ordered with respect to RNA-seq transcripts per million (TPM) values. Genes with a Common Pol2 peak in their promoters are depicted with green whereas genes with only Perm-seq-only peaks are depicted in blue.</p

Conservation analysis of the common and Perm-seq-exclusive peak sets.

<p>(a) Empirical cumulative distribution functions (CDFs) for average phyloP scores of Usf1 binding sites from the Common and Perm-seq-exclusive Usf1 peaks in GM12878 and K562 cells, respectively. Positive scores indicate conservation and negative scores indicate acceleration. (b) Mean position-specific phyloP scores of the Usf1 binding sites for Common and Perm-seq-exclusive Usf1 peaks in GM12878 and K562, respectively. Shaded areas denote ± one standard error of the mean profile. (c) Pearson correlations between the mean position-specific phyloP scores of the binding sites from the Common and Perm-seq-exclusive peak sets. Purple and red circles indicate that correlations are not significantly different than zero only in GM12878 and in both GM12878 and K562 cells, respectively. (d) Mean position-specific phyloP scores of the Zbtb33 binding sites from the Common and Perm-seq-exclusive Zbtb33 peaks in GM12878 and K562 cells, respectively.</p