Building a schizophrenia genetic network: transcription factor 4 regulates genes involved in neuronal development and schizophrenia risk.

The transcription factor 4 (TCF4) locus is a robust association finding with schizophrenia (SCZ), but little is known about the genes regulated by the encoded transcription factor. Therefore, we conducted chromatin immunoprecipitation sequencing (ChIP-seq) of TCF4 in neural-derived (SH-SY5Y) cells to identify genome-wide TCF4 binding sites, followed by data integration with SCZ association findings. We identified 11 322 TCF4 binding sites overlapping in two ChIP-seq experiments. These sites are significantly enriched for the TCF4 Ebox binding motif (>85% having ≥1 Ebox) and implicate a gene set enriched for genes downregulated in TCF4 small-interfering RNA (siRNA) knockdown experiments, indicating the validity of our findings. The TCF4 gene set was also enriched among (1) gene ontology categories such as axon/neuronal development, (2) genes preferentially expressed in brain, in particular pyramidal neurons of the somatosensory cortex and (3) genes downregulated in postmortem brain tissue from SCZ patients (odds ratio, OR = 2.8, permutation P < 4x10-5). Considering genomic alignments, TCF4 binding sites significantly overlapped those for neural DNA-binding proteins such as FOXP2 and the SCZ-associated EP300. TCF4 binding sites were modestly enriched among SCZ risk loci from the Psychiatric Genomic Consortium (OR = 1.56, P = 0.03). In total, 130 TCF4 binding sites occurred in 39 of the 108 regions published in 2014. Thirteen genes within the 108 loci had both a TCF4 binding site ±10kb and were differentially expressed in siRNA knockdown experiments of TCF4, suggesting direct TCF4 regulation. These findings confirm TCF4 as an important regulator of neural genes and point toward functional interactions with potential relevance for SCZ.

Alcohol consumption is associated with the severity and outcome of acute liver injury/failure.

BACKGROUND & AIMS: Non-medical factors which contribute to the severity of acute liver failure (ALF) remain poorly defined. The association of alcohol consumption on the severity of presentation and outcome were determined in patients with ALF and acute liver injury (ALI) in a large, multicentre registry. METHODS: Alcohol consumption during the 6 months prior to study entry was analysed in 1170 patients enrolled in the ALF Study Group Registry. Consumption was categorized as none/minimal (<3 alcoholic beverages/week) or at least moderate (≥3/week). Clinical characteristics, the severity of liver injury at presentation (ALI or ALF) and outcome were compared. RESULTS: In patients with acetaminophen (APAP) overdose, at least moderate alcohol consumption was associated with higher peak aminotransferases, bilirubin, creatinine and INR on admission, compared to no/minimal consumption. In patients with non-APAP ALI/ALF, at least moderate alcohol consumption was associated with higher peak aminotransferases and creatinine. In APAP, non-APAP or all aetiologies, at least moderate alcohol consumption was associated with a 75%, 89% and 82% higher odds, respectively, of presenting as ALF rather than ALI (all P < .005). At least moderate alcohol consumption increased the odds of death by 45% (P = .01) across all aetiologies. In multivariate analysis, older age, non-Caucasian race, peak INR, peak bilirubin and at least moderate alcohol consumption were significantly associated with death. Finally, in Kaplan-Meier analysis of patients with all aetiologies, at least moderate alcohol consumption was associated with decreased time-dependent survival (P = .002). CONCLUSION: Alcohol consumption adversely affects the presentation and outcome of both APAP- and non-APAP-induced ALI/ALF.

WITHDRAWN: The chromatin remodeling complex NURF localizes to gene bodies and is required for mRNA processing.

This article has been withdrawn by Aiman Alhazmi, Marissa Mack, Tiffany Rolle, Jordan Hiegel, Syed Haqqani, Nga Dao, Farheen Zaman, Nak-Kyeong Kim, Neel Scarsdale, Charles Lyons, and Joseph Landry. Some of the genome-wide data sets were flawed and were not analyzed correctly. The withdrawing authors are in the process of correcting the data sets and re-analyzing them for resubmission.

NEXT-peak: a normal-exponential two-peak model for peak-calling in ChIP-seq data.

BACKGROUND: Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) can locate transcription factor binding sites on genomic scale. Although many models and programs are available to call peaks, none has dominated its competition in comparison studies. RESULTS: We propose a rigorous statistical model, the normal-exponential two-peak (NEXT-peak) model, which parallels the physical processes generating the empirical data, and which can naturally incorporate mappability information. The model therefore estimates total strength of binding (even if some binding locations do not map uniquely into a reference genome, effectively censoring them); it also assigns an error to an estimated binding location. The comparison study with existing programs on real ChIP-seq datasets (STAT1, NRSF, and ZNF143) demonstrates that the NEXT-peak model performs well both in calling peaks and locating them. The model also provides a goodness-of-fit test, to screen out spurious peaks and to infer multiple binding events in a region. CONCLUSIONS: The NEXT-peak program calls peaks on any test dataset about as accurately as any other, but provides unusual accuracy in the estimated location of the peaks it calls. NEXT-peak is based on rigorous statistics, so its model also provides a principled foundation for a more elaborate statistical analysis of ChIP-seq data.

Adjuvant radiation therapy for T4 non-rectal colon adenocarcinoma provides a cause-specific survival advantage: A SEER database analysis.

PURPOSE: While there is no level 1 evidence supporting the use of adjuvant radiotherapy (RT) for non-rectal colon cancer in the modern chemotherapy era, there are studies that suggest a local control benefit. This treatment modality is not part of standard treatment recommendations, and we hypothesized that adjuvant RT provides a benefit in locally advanced disease. Due to the limited number who receive post-operative RT, a national database was searched to provide sufficient power. MATERIALS AND METHODS: A retrospective analysis using the Surveillance, Epidemiology, and End Results (SEER) database was performed. Inclusion criteria were: non-rectal colon cancer, AJCC 6th or 7th edition T4 and M0, oncologic resection, and 1st cancer site. Patients were excluded for RT prior to or during surgery, or if the sequence of RT was unknown. Using a Cox proportional hazard model, the relative risk of cause-specific mortality for "RT after surgery" versus "No RT" was calculated. RESULTS: 21,789 patients were identified who met the inclusion criteria. Of these, only 1001 received adjuvant RT, and 64% were node-positive (53% RT vs. 65% no RT). When comparing RT vs. no RT, after adjusting for sex, age, N stage, and grade, we determined the relative risk of death from cancer was 0.8849 (95% CI: 0.8008-0.9779; p = 0.0165), suggesting that only 14 patients with T4 disease need receive adjuvant radiation to spare a cancer-related death. CONCLUSIONS: Adjuvant RT is not routinely utilized for definitive treatment of T4 non-rectal colon cancer, but this analysis shows a significant cause-specific survival benefit.

Finding sequence motifs with Bayesian models incorporating positional information: an application to transcription factor binding sites.

BACKGROUND: Biologically active sequence motifs often have positional preferences with respect to a genomic landmark. For example, many known transcription factor binding sites (TFBSs) occur within an interval [-300, 0] bases upstream of a transcription start site (TSS). Although some programs for identifying sequence motifs exploit positional information, most of them model it only implicitly and with ad hoc methods, making them unsuitable for general motif searches. RESULTS: A-GLAM, a user-friendly computer program for identifying sequence motifs, now incorporates a Bayesian model systematically combining sequence and positional information. A-GLAM's predictions with and without positional information were compared on two human TFBS datasets, each containing sequences corresponding to the interval [-2000, 0] bases upstream of a known TSS. A rigorous statistical analysis showed that positional information significantly improved the prediction of sequence motifs, and an extensive cross-validation study showed that A-GLAM's model was robust against mild misspecification of its parameters. As expected, when sequences in the datasets were successively truncated to the intervals [-1000, 0], [-500, 0] and [-250, 0], positional information aided motif prediction less and less, but never hurt it significantly. CONCLUSION: Although sequence truncation is a viable strategy when searching for biologically active motifs with a positional preference, a probabilistic model (used reasonably) generally provides a superior and more robust strategy, particularly when the sequence motifs' positional preferences are not well characterized.

Patients with integrated HPV16 in head and neck cancer show poor survival.

OBJECTIVES: We previously reported identifying three categories of HPV16-positive head and neck tumors based on The Cancer Genome Atlas (TCGA) RNA and DNA sequence data. Category 1 had truly integrated HPV16 genomes, category 2 had simple episomal genomes, and category 3 had novel episomes that were a hybrid between viral and human DNA. Using our categorization, we investigated in this study survival of patients with integrated HPV16 tumors versus patients with episomal HPV16 tumors. MATERIALS AND METHODS: The TCGA RNA-Seq sequence reads were used to quantify HPV E2 and E7 gene expression, which was used as a marker for HPV integration. RESULTS: The results demonstrate that integration is associated with poor survival; those patients with integrated HPV tumors fared no better than non-HPV tumors in their five-year survival. Integrated HPV in tumors was found strikingly to be prevalent in patients born earlier while episomal HPV was prevalent in patients born later. We also observed a fairly constant incidence of all HPV forms among head and neck cancer patients over the last eight years of this study (2006-2013). CONCLUSION: We propose our characterization of HPV integrated and episomal state is more accurate than previous studies that may have mischaracterized the hybrid HPV-human DNA episomes as integrated. The state of integrated HPV is associated with a poor clinical outcome. Results suggest that the incidence of integrated HPV among all HPV forms peaked and is decreasing. We discuss the importance of our findings for the management of HPV positive head and neck cancer.

Adding sequence context to a Markov background model improves the identification of regulatory elements.

MOTIVATION: Many computational methods for identifying regulatory elements use a likelihood ratio between motif and background models. Often, the methods use a background model of independent bases. At least two different Markov background models have been proposed with the aim of increasing the accuracy of predicting regulatory elements. Both Markov background models suffer theoretical drawbacks, so this article develops a third, context-dependent Markov background model from fundamental statistical principles. RESULTS: Datasets containing known regulatory elements in eukaryotes provided a basis for comparing the predictive accuracies of the different background models. Non-parametric statistical tests indicated that Markov models of order 3 constituted a statistically significant improvement over the background model of independent bases. Our model performed slightly better than the previous Markov background models. We also found that for discriminating between the predictive accuracies of competing background models, the correlation coefficient is a more sensitive measure than the performance coefficient. AVAILABILITY: Our C++ program is available at ftp://ftp.ncbi.nih.gov/pub/spouge/papers/archive/AGLAM/2006-07-19

Protein multiple alignment incorporating primary and secondary structure information.

Identifying common local segments, also called motifs, in multiple protein sequences plays an important role for establishing homology between proteins. Homology is easy to establish when sequences are similar (sharing an identity > 25%). However, for distant proteins, it is much more difficult to align motifs that are not similar in sequences but still share common structures or functions. This paper is a first attempt to align multiple protein sequences using both primary and secondary structure information. A new sequence model is proposed so that the model assigns high probabilities not only to motifs that contain conserved amino acids but also to motifs that present common secondary structures. The proposed method is tested in a structural alignment database BAliBASE. We show that information brought by the predicted secondary structures greatly improves motif identification. A website of this program is available at www.stat.purdue.edu/~junxie/2ndmodel/sov.html.

Effects of Curtailed Juvenile State on Cardiac Structure and Function in Adulthood: The Fels Longitudinal Study.

OBJECTIVE: Previous studies have shown associations between body mass index and cardiac structure in both childhood and adulthood. Using Fels Longitudinal Study measurements, we investigate the relationships between a curtailed juvenile state and both adult cardiac structure and function. METHODS: A linear mixed-effect repeated measure analysis of variance model is used to test if there is a relationship between juvenile state and each echocardiographic measurement. RESULTS: The curtailed juvenile state is significantly associated with adult left ventricular mass index for both males and females. It is also significantly associated with the interventricular septal wall thickness index and relative wall thickness index for females. In both cases, early juvenile states led to more abnormal structural estimates in adulthood than did late juvenile states. Among cardiac function measurements such as left ventricular ejection fraction and left ventricular shortening fraction, left ventricular ejection fraction is significantly associated with the juvenile state for females. CONCLUSION: The curtailed juvenile state at the childhood may have a long-term adverse effect on adult cardiac structure and function abnormalities.

Bayesian models and Markov chain Monte Carlo methods for protein motifs with the secondary characteristics.

Statistical methods have been developed for finding local patterns, also called motifs, in multiple protein sequences. The aligned segments may imply functional or structural core regions. However, the existing methods often have difficulties in aligning multiple proteins when sequence residue identities are low (e.g., less than 25%). In this article, we develop a Bayesian model and Markov chain Monte Carlo (MCMC) methods for identifying subtle motifs in protein sequences. Specifically, a motif is defined not only in terms of specific sites characterized by amino acid frequency vectors, but also as a combination of secondary characteristics such as hydrophobicity, polarity, etc. Markov chain Monte Carlo methods are proposed to search for a motif pattern with high posterior probability under the new model. A special MCMC algorithm is developed, involving transitions between state spaces of different dimensions. The proposed methods were supported by a simulated study. It was then tested by two real datasets, including a group of helix-turn-helix proteins, and one set from the CATH Protein Structure Classification Database. Statistical comparisons showed that the new approach worked better than a typical Gibbs sampling approach which is based only on an amino acid model.

Analysis of biological features associated with meiotic recombination hot and cold spots in Saccharomyces cerevisiae.

Meiotic recombination is not distributed uniformly throughout the genome. There are regions of high and low recombination rates called hot and cold spots, respectively. The recombination rate parallels the frequency of DNA double-strand breaks (DSBs) that initiate meiotic recombination. The aim is to identify biological features associated with DSB frequency. We constructed vectors representing various chromatin and sequence-based features for 1179 DSB hot spots and 1028 DSB cold spots. Using a feature selection approach, we have identified five features that distinguish hot from cold spots in Saccharomyces cerevisiae with high accuracy, namely the histone marks H3K4me3, H3K14ac, H3K36me3, and H3K79me3; and GC content. Previous studies have associated H3K4me3, H3K36me3, and GC content with areas of mitotic recombination. H3K14ac and H3K79me3 are novel predictions and thus represent good candidates for further experimental study. We also show nucleosome occupancy maps produced using next generation sequencing exhibit a bias at DSB hot spots and this bias is strong enough to obscure biologically relevant information. A computational approach using feature selection can productively be used to identify promising biological associations. H3K14ac and H3K79me3 are novel predictions of chromatin marks associated with meiotic DSBs. Next generation sequencing can exhibit a bias that is strong enough to lead to incorrect conclusions. Care must be taken when interpreting high throughput sequencing data where systematic biases have been documented.