Utilization of Molecular Inversion Probes in Malaria Sequencing

While massively parallel sequencing of whole genomes shed light on many previously puzzling genetic questions, the high costs associated with this approach makes its use impractical when large cohorts need to be sequenced at high coverage. Available capture technologies reduces the sequencing costs by enriching template material for the regions of interest. However, these technologies are also prohibitively costly at high sample numbers. Capture methods utilizing molecular inversion probes (MIPs) offer a flexible alternative to enrich template material that multiplex well for thousands of samples and require minimal resources. Here, for our work in malaria, we extend the utility of MIPs, improving the capture length and efficiency. We have also dramatically decreased the capture time from 24-48 h to 1 h. Combined, these improvements allow the potential for rapid and reliable application of MIP captures in research and, importantly, clinical settings

Differential Gene Expression Analysis and Clinical Correlations within Endemic Burkitt Lymphoma

Endemic Burkitt lymphoma (eBL) is the most common pediatric cancer in equatorial Africa and is associated with malaria and Epstein-Barr virus co-infections. Molecular alterations within the eBL tumor genome and transcriptome have not been adequately investigated or compared to sporadic Burkitt lymphoma (sBL). Given that eBL has distinct clinical presentations in the jaw as opposed to the abdomen which are associated with survival, we hypothesize that transcriptome sequencing (RNA-seq) and potentially underlying genetic alterations will enhance our understanding of pathogenesis. Our results compare genome-wide RNA transcript abundances between eBL tumors from children (ages 6-7 yrs) with Stage I (Jaw tumor, n=14) and Stage II (abdominal, n=24) disease from Western Kenya to previously published work analyzing sBL which present in older children residing in developed countries and that tend not to be associated with EBV. Our initial analysis confirms mutational changes with likely functional alterations in the genes ID3 and TCF3, the key regulators of oncogenic pathways implicated in BL. However, the specific mutations observed in sBL are at lower frequency within eBL cases. This work represents the first comprehensive gene expression profile analysis of different eBL tumors. Hierarchical clustering, gene ontology and pathway analysis will provide insight into pathogenesis and new targets for chemotherapy

Prediction of tumour pathological subtype from genomic profile using sparse logistic regression with random effects

The purpose of this study is to highlight the application of sparse logistic regression models in dealing with prediction of tumour pathological subtypes based on lung cancer patients' genomic information. We consider sparse logistic regression models to deal with the high dimensionality and correlation between genomic regions. In a hierarchical likelihood (HL) method, it is assumed that the random effects follow a normal distribution and its variance is assumed to follow a gamma distribution. This formulation considers ridge and lasso penalties as special cases. We extend the HL penalty to include a ridge penalty (called ‘HLnet’) in a similar principle of the elastic net penalty, which is constructed from lasso penalty. The results indicate that the HL penalty creates more sparse estimates than lasso penalty with comparable prediction performance, while HLnet and elastic net penalties have the best prediction performance in real data. We illustrate the methods in a lung cancer study

Integrative microRNA and mRNA deep-sequencing expression profiling in endemic Burkitt lymphoma

BACKGROUND: Burkitt lymphoma (BL) is characterized by overexpression of the c-myc oncogene, which in the vast majority of cases is a consequence of an IGH/MYC translocation. While myc is the seminal event, BL is a complex amalgam of genetic and epigenetic changes causing dysregulation of both coding and non-coding transcripts. Emerging evidence suggest that abnormal modulation of mRNA transcription via miRNAs might be a significant factor in lymphomagenesis. However, the alterations in these miRNAs and their correlations to their putative mRNA targets have not been extensively studied relative to normal germinal center (GC) B cells. METHODS: Using more sensitive and specific transcriptome deep sequencing, we compared previously published small miRNA and long mRNA of a set of GC B cells and eBL tumors. MiRWalk2.0 was used to identify the validated target genes for the deregulated miRNAs, which would be important for understanding the regulatory networks associated with eBL development. RESULTS: We found 211 differentially expressed (DE) genes (79 upregulated and 132 downregulated) and 49 DE miRNAs (22 up-regulated and 27 down-regulated). Gene Set enrichment analysis identified the enrichment of a set of MYC regulated genes. Network propagation-based method and correlated miRNA-mRNA expression analysis identified dysregulated miRNAs, including miR-17~95 cluster members and their target genes, which have diverse oncogenic properties to be critical to eBL lymphomagenesis. Central to all these findings, we observed the downregulation of ATM and NLK genes, which represent important regulators in response to DNA damage in eBL tumor cells. These tumor suppressors were targeted by multiple upregulated miRNAs (miR-19b-3p, miR-26a-5p, miR-30b-5p, miR-92a-5p and miR-27b-3p) which could account for their aberrant expression in eBL. CONCLUSION: Combined loss of p53 induction and function due to miRNA-mediated regulation of ATM and NLK, together with the upregulation of TFAP4, may be a central role for human miRNAs in eBL oncogenesis. This facilitates survival of eBL tumor cells with the IGH/MYC chromosomal translocation and promotes MYC-induced cell cycle progression, initiating eBL lymphomagenesis. This characterization of miRNA-mRNA interactions in eBL relative to GC B cells provides new insights on miRNA-mediated transcript regulation in eBL, which are potentially useful for new improved therapeutic strategies

Epstein Barr virus genomes reveal population structure and type 1 association with endemic Burkitt lymphoma [preprint]

Endemic Burkitt lymphoma (eBL), the most prevalent pediatric cancer in sub-Saharan Africa, is associated with malaria and Epstein Barr virus (EBV). In order to better understand the role of EBV in eBL, we improved viral DNA enrichment methods and generated a total of 98 new EBV genomes from both eBL cases (N=58) and healthy controls (N=40) residing in the same geographic region in Kenya. Comparing cases and controls, we found that EBV type 1 was significantly associated with eBL with 74.5% of patients (41/55) versus 47.5% of healthy children (19/40) carrying type 1 (OR=3.24, 95% CI=1.36 - 7.71, P=0.007). Controlling for EBV type, we also performed a genome-wide association study identifying 6 nonsynonymous variants in the genes EBNA1, EBNA2, BcLF1, and BARF1 that were enriched in eBL patients. Additionally, we observed that viruses isolated from plasma of eBL patients were identical to their tumor counterpart consistent with circulating viral DNA originating from the tumor. We also detected three intertypic recombinants carrying type 1 EBNA2 and type 2 EBNA3 regions as well as one novel genome with a 20 kb deletion resulting in the loss of multiple lytic and virion genes. Comparing EBV types, genes show differential variation rates as type 1 appears to be more divergent. Besides, type 2 demonstrates novel substructures. Overall, our findings address the complexities of EBV population structure and provide new insight into viral variation, which has the potential to influence eBL oncogenesis

FLT1 and transcriptome-wide polyadenylation site (PAS) analysis in preeclampsia

Maternal symptoms of preeclampsia (PE) are primarily driven by excess anti-angiogenic factors originating from the placenta. Chief among these are soluble Flt1 proteins (sFlt1s) produced from alternatively polyadenylated mRNA isoforms. Here we used polyadenylation site sequencing (PAS-Seq) of RNA from normal and PE human placentae to interrogate transcriptome-wide gene expression and alternative polyadenylation signatures associated with early-onset PE (EO-PE; symptom onset 34 weeks) cohorts. While we observed no general shift in alternative polyadenylation associated with PE, the EO-PE and LO-PE cohorts do exhibit gene expression profiles distinct from both each other and from normal placentae. The only two genes upregulated across all transcriptome-wide PE analyses to date (microarray, RNA-Seq and PAS-Seq) are NRIP1 (RIP140), a transcriptional co-regulator linked to metabolic syndromes associated with obesity, and Flt1. Consistent with sFlt1 overproduction being a significant driver of clinical symptoms, placental Flt1 mRNA levels strongly correlate with maternal blood pressure. For Flt1, just three mRNA isoforms account for > 94% of all transcripts, with increased transcription of the entire locus driving Flt1 upregulation in both EO-PE and LO-PE. These three isoforms thus represent potential targets for therapeutic RNA interference (RNAi) in both early and late presentations

Quantifying the Storm Time Thermospheric Neutral Density Variations Using Model and Observations

Accurate determination of thermospheric neutral density holds crucial importance for satellite drag calculations. The problem is twofold and involves the correct estimation of the quiet time climatology and storm time variations. In this work, neutral density estimations from two empirical and three physicsâ based models of the ionosphereâ thermosphere are compared with the neutral densities along the Challenging Microâ Satellite Payload satellite track for six geomagnetic storms. Storm time variations are extracted from neutral density by (1) subtracting the mean difference between model and observation (bias), (2) setting climatological variations to zero, and (3) multiplying model data with the quiet time ratio between the model and observation. Several metrics are employed to evaluate the model performances. We find that the removal of bias or climatology reveals actual performance of the model in simulating the storm time variations. When bias is removed, depending on event and model, storm time errors in neutral density can decrease by an amount of 113% or can increase by an amount of 12% with respect to error in models with quiet time bias. It is shown that using only average and maximum values of neutral density to determine the model performances can be misleading since a model can estimate the averages fairly well but may not capture the maximum value or vice versa. Since each of the metrics used for determining model performances provides different aspects of the error, among these, we suggest employing mean absolute error, prediction efficiency, and normalized root mean square error together as a standard set of metrics for the neutral density.Plain Language SummaryThermospheric neutral density is the largest source of uncertainty in atmospheric drag calculations. Consequently, mission and maneuver planning, satellite lifetime predictions, collision avoidance, and orbit determination depend on the accurate estimation of the thermospheric neutral density. Thermospheric neutral density varies in different timescales. In short timescales, the largest variations occur due to the geomagnetic storms. Several empirical and physicsâ based models of the ionosphereâ thermosphere system are used for estimating the variations in the neutral density. However, the storm time responses from the models are clouded by the climatology (background variations), upon which the effect of geomagnetic storms is superimposed. In this work, we show that it is critical to use reference levels for the neutral density to extract the true performance of the models for the evaluation of the storm time performances. We demonstrate that mean absolute error, prediction efficiency, and normalized root mean square error should be considered together for the performance evaluations, since each of them provides different aspects of the error.Key PointsUsing the average and maximum values of neutral densities to determine the model performances can be misleadingRemoving the quiet time trend from the neutral density reveals the actual performance of the model in simulating the storm time variationsMean absolute error, prediction efficiency, and normalized root mean square error should be considered together for the evaluationsPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/148396/1/swe20816_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/148396/2/swe20816-sup-0001-2018SW002033-SI.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/148396/3/swe20816.pd

Packages of Care for Depression in Low- and Middle-Income Countries

In the first in a series of six articles on packages of care for mental disorders in low- and middle-income countries, Neerja Chowdary and colleagues discuss the treatment of depression

MESSENGER and Mariner 10 flyby observations of magnetotail structure and dynamics at Mercury

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94896/1/jgra21525.pd

Disrupting the rhythm of depression: design and protocol of a randomized controlled trial on preventing relapse using brief cognitive therapy with or without antidepressants

Background: Maintenance treatment with antidepressants is the leading strategy to prevent relapse and recurrence in patients with recurrent major depressive disorder (MDD) who have responded to acute treatment with antidepressants (AD). However, in clinical practice most patients (up to 70-80%) are not willing to take this medication after remission or take too low dosages. Moreover, as patients need to take medication for several years, it may not be the most cost-effective strategy. The best established effective and available alternative is brief cognitive therapy (CT). However, it is unclear whether brief CT while tapering antidepressants (AD) is an effective alternative for long term use of AD in recurrent depression. In addition, it is unclear whether the combination of AD to brief CT is beneficial.Methods/design: Therefore, we will compare the effectiveness and cost-effectiveness of brief CT while tapering AD to maintenance AD and the combination of CT with maintenance AD. In addition, we examine whether the prophylactic effect of CT was due to CT tackling illness related risk factors for recurrence such as residual symptoms or to its efficacy to modify presumed vulnerability factors of recurrence (e.g. rigid explicit and/or implicit dysfunctional attitudes). This is a multicenter RCT comparing the above treatment scenarios. Remitted patients on AD with at least two previous depressive episodes in the past five years (n = 276) will be recruited. The primary outcome is time related proportion of depression relapse/recurrence during minimal 15 months using DSM-IV-R criteria as assessed by the Structural Clinical Interview for Depression. Secondary outcome: economic evaluation (using a societal perspective) and number, duration and severity of relapses/recurrences.Discussion: This will be the first trial to investigate whether CT is effective in preventing relapse to depression in recurrent depression while tapering antidepressant treatment compared to antidepressant treatment alone and the combination of both. In addition, we explore explicit and implicit mediators of CT.Trial registration: Netherlands Trial Register (NTR): NTR1907