H3ABioNet, a sustainable pan-African bioinformatics network for human heredity and health in Africa

The application of genomics technologies to medicine and biomedical research is increasing in popularity, made possible by new high-throughput genotyping and sequencing technologies and improved data analysis capabilities. Some of the greatest genetic diversity among humans, animals, plants, and microbiota occurs in Africa, yet genomic research outputs from the continent are limited. The Human Heredity and Health in Africa (H3Africa) initiative was established to drive the development of genomic research for human health in Africa, and through recognition of the critical role of bioinformatics in this process, spurred the establishment of H3ABioNet, a pan-African bioinformatics network for H3Africa. The limitations in bioinformatics capacity on the continent have been a major contributory factor to the lack of notable outputs in highthroughput biology research. Although pockets of high-quality bioinformatics teams have existed previously, the majority of research institutions lack experienced faculty who can train and supervise bioinformatics students. H3ABioNet aims to address this dire need, specifically in the area of human genetics and genomics, but knock-on effects are ensuring this extends to other areas of bioinformatics. Here, we describe the emergence of genomics research and the development of bioinformatics in Africa through H3ABioNet.</p

Factors affecting retention and compliance in a longitudinal study of connected, low income, urban, primiparous mothers

poster abstractAbstract Background/Aims Longitudinal obstetrics studies are vital to our understanding of the physiological and social changes that occur during pregnancy and the early postpartum period in the mother and baby. Variables collected in a longitudinal obstetrics study were analyzed to identify factors affecting retention and compliance within a low-income, primiparous population. Methods Primiparous women were recruited for a prospective cohort longitudinal study. Two study arms were used. The first collected survey data on mood, sleep, and night time eating and actigraphic data for seven days during weeks 22 and 32 of gestation and one week postpartum. The second was identical but had an additional 24 hour sampling of saliva. In addition, breast fullness surveys were administered each day for the first five days postpartum. Pick up and drop off of study materials at the research site were required for each time point. Results Ninety-two women were recruited; 45% (n=41) were retained and compliant for the entire study. The majority of subjects (88%) had daily internet access, completed surveys on-line (81.4%), and preferred to receive text messages (93.5%) for study reminders over other methods of communication. Longitudinal time (P<0.001), increased number of reminders (P<0.001), and increased length of time to complete surveys (P<0.001) had a significant negative effect on study retention, whereas enrollment in the study arm with greater sampling and communication (P<0.001) and earning a higher percentage of available compensation (P<0.001) had a significant positive effect on study retention. Conclusions The high rate of daily internet access and preference for text messaging for primary means of communication with research staff suggests a high rate of smart-device technology use among young, urban-dwelling, low-income women. Designing studies that can be completed via internet and using text message reminders may be a preferable and practical means of conducting longitudinal obstetrics studies

Design considerations for workflow management systems use in production genomics research and the clinic

Abstract The changing landscape of genomics research and clinical practice has created a need for computational pipelines capable of efficiently orchestrating complex analysis stages while handling large volumes of data across heterogeneous computational environments. Workflow Management Systems (WfMSs) are the software components employed to fill this gap. This work provides an approach and systematic evaluation of key features of popular bioinformatics WfMSs in use today: Nextflow, CWL, and WDL and some of their executors, along with Swift/T, a workflow manager commonly used in high-scale physics applications. We employed two use cases: a variant-calling genomic pipeline and a scalability-testing framework, where both were run locally, on an HPC cluster, and in the cloud. This allowed for evaluation of those four WfMSs in terms of language expressiveness, modularity, scalability, robustness, reproducibility, interoperability, ease of development, along with adoption and usage in research labs and healthcare settings. This article is trying to answer, which WfMS should be chosen for a given bioinformatics application regardless of analysis type?. The choice of a given WfMS is a function of both its intrinsic language and engine features. Within bioinformatics, where analysts are a mix of dry and wet lab scientists, the choice is also governed by collaborations and adoption within large consortia and technical support provided by the WfMS team/community. As the community and its needs continue to evolve along with computational infrastructure, WfMSs will also evolve, especially those with permissive licenses that allow commercial use. In much the same way as the dataflow paradigm and containerization are now well understood to be very useful in bioinformatics applications, we will continue to see innovations of tools and utilities for other purposes, like big data technologies, interoperability, and provenance

Unveiling the therapeutic potential of exogenous β-hydroxybutyrate for chronic colitis in rats: novel insights on autophagy, apoptosis, and pyroptosis

Ulcerative colitis (UC) is a chronic relapsing inflammatory disease of the colorectal area that demonstrates a dramatically increasing incidence worldwide. This study provides novel insights into the capacity of the exogenous β-hydroxybutyrate and ketogenic diet (KD) consumption to alleviate dextran sodium sulfate (DSS)-induced UC in rats. Remarkably, both interventions attenuated disease activity and colon weight-to-length ratio, and improved macro and microstructures of the damaged colon. Importantly, both β-hydroxybutyrate and KD curbed the DSS-induced aberrant NLRP3 inflammasome activation as observed in mRNA and protein expression analysis. Additionally, inhibition of the NLRP3/NGSDMD-mediated pyroptosis was detected in response to both regimens. In parallel, these modalities attenuated caspase-1 and its associated consequences of IL-1β and IL-18 overproduction. They also mitigated apoptosis as indicated by the inactivation of caspase-3. The anti-inflammatory effects of BHB and KD were confirmed by the reported decline in the levels of inflammatory markers including MPO, NFκB, IL-6, and TNF-α. Moreover, these interventions exhibited antioxidative properties by reducing ROS production and improving antioxidative enzymes. Their effectiveness in mitigating UC was also evident in the renovation of normal intestinal epithelial barrier function, as shown by correcting the discrepancies in the levels of tight junction proteins ZO-1, OCLN, and CLDN5. Furthermore, their effects on the intestinal microbiota homeostasis were investigated. In terms of autophagy, exogenous β-hydroxybutyrate upregulated BECN-1 and downregulated p62, which may account for its superiority over KD in attenuating colonic damage. In conclusion, this study provides experimental evidence supporting the potential therapeutic use of β-hydroxybutyrate or β-hydroxybutyrate-boosting regimens in UC

A crowdsourced set of curated structural variants for the human genome.

Funder: U.S. Food and Drug Administration; funder-id: http://dx.doi.org/10.13039/100000038A high quality benchmark for small variants encompassing 88 to 90% of the reference genome has been developed for seven Genome in a Bottle (GIAB) reference samples. However a reliable benchmark for large indels and structural variants (SVs) is more challenging. In this study, we manually curated 1235 SVs, which can ultimately be used to evaluate SV callers or train machine learning models. We developed a crowdsourcing app-SVCurator-to help GIAB curators manually review large indels and SVs within the human genome, and report their genotype and size accuracy. SVCurator displays images from short, long, and linked read sequencing data from the GIAB Ashkenazi Jewish Trio son [NIST RM 8391/HG002]. We asked curators to assign labels describing SV type (deletion or insertion), size accuracy, and genotype for 1235 putative insertions and deletions sampled from different size bins between 20 and 892,149 bp. 'Expert' curators were 93% concordant with each other, and 37 of the 61 curators had at least 78% concordance with a set of 'expert' curators. The curators were least concordant for complex SVs and SVs that had inaccurate breakpoints or size predictions. After filtering events with low concordance among curators, we produced high confidence labels for 935 events. The SVCurator crowdsourced labels were 94.5% concordant with the heuristic-based draft benchmark SV callset from GIAB. We found that curators can successfully evaluate putative SVs when given evidence from multiple sequencing technologies

Helicobacter pylori infection might be responsible for the interconnection between type 1 diabetes and autoimmune thyroiditis

<p>Abstract</p> <p>Background</p> <p>Higher serological prevalence rates of helicobacter pylori (H. pylori) infection have been reported in patients with type 1 diabetes (T1DM) and autoimmune thyroiditis (AT). Patients with T1DM are at increased risk for developing other autoimmune diseases, most commonly AT. It is unknown whether H. pylori infection could explain the high prevalence of thyroid autoantibodies and AT in T1DM. The aim of the current study was to evaluate anti-thyroid peroxidase (anti-TPO) and anti-thyroglobulin (anti-Tg) autoantibodies in correlation with anti-H. pylori IgG and IgA in young patients with T1DM.</p> <p>Methods</p> <p>Anti-H. Pylori IgG, IgA, anti-TPO and anti-Tg antibodies titers were measured in 162 euthyroid patients with T1DM and 80 healthy controls matched for age, sex and socioeconomic status.</p> <p>Results</p> <p>Seroprevalence of H. pylori was significantly higher in patients with T1DM than in healthy controls; 79% vs. 51.2%, p < 0.001. Anti H. pylori IgG was positive in 61.1% of patients with T1DM and 30% of controls, p < 0.001, anti H. pylori IgA was positive in 74% of patients with T1DM and 32.5% of controls, p < 0.001. Thyroid autoimmunity was also significantly higher in patients with T1DM than in controls; 56.7% vs. 6.2%, p < 0.001. Anti-TPO was positive in 25.3% of patients with T1DM and 3.7% of controls, p < 0.001, anti-Tg was positive in 47.5% of patients with T1DM and 6.2% of controls, p < 0.001. With simple and multiple regression analysis anti-H. pylori IgG and IgA titers were positively and significantly correlated with Anti-TPO and anti-Tg titers in patients with T1DM.</p> <p>Conclusion</p> <p>our results support the idea of a connection between H. pylori infection and the occurrence of anti-TPO, anti-Tg autoantibodies and AT in young patients with T1DM. So, H. pylori infection could be considered as an environmental trigger for development of AT in T1DM. Young patients with T1DM should be screened for H. pylori infection.</p

Global Retinoblastoma Presentation and Analysis by National Income Level.

Importance: Early diagnosis of retinoblastoma, the most common intraocular cancer, can save both a child's life and vision. However, anecdotal evidence suggests that many children across the world are diagnosed late. To our knowledge, the clinical presentation of retinoblastoma has never been assessed on a global scale. Objectives: To report the retinoblastoma stage at diagnosis in patients across the world during a single year, to investigate associations between clinical variables and national income level, and to investigate risk factors for advanced disease at diagnosis. Design, Setting, and Participants: A total of 278 retinoblastoma treatment centers were recruited from June 2017 through December 2018 to participate in a cross-sectional analysis of treatment-naive patients with retinoblastoma who were diagnosed in 2017. Main Outcomes and Measures: Age at presentation, proportion of familial history of retinoblastoma, and tumor stage and metastasis. Results: The cohort included 4351 new patients from 153 countries; the median age at diagnosis was 30.5 (interquartile range, 18.3-45.9) months, and 1976 patients (45.4%) were female. Most patients (n = 3685 [84.7%]) were from low- and middle-income countries (LMICs). Globally, the most common indication for referral was leukocoria (n = 2638 [62.8%]), followed by strabismus (n = 429 [10.2%]) and proptosis (n = 309 [7.4%]). Patients from high-income countries (HICs) were diagnosed at a median age of 14.1 months, with 656 of 666 (98.5%) patients having intraocular retinoblastoma and 2 (0.3%) having metastasis. Patients from low-income countries were diagnosed at a median age of 30.5 months, with 256 of 521 (49.1%) having extraocular retinoblastoma and 94 of 498 (18.9%) having metastasis. Lower national income level was associated with older presentation age, higher proportion of locally advanced disease and distant metastasis, and smaller proportion of familial history of retinoblastoma. Advanced disease at diagnosis was more common in LMICs even after adjusting for age (odds ratio for low-income countries vs upper-middle-income countries and HICs, 17.92 [95% CI, 12.94-24.80], and for lower-middle-income countries vs upper-middle-income countries and HICs, 5.74 [95% CI, 4.30-7.68]). Conclusions and Relevance: This study is estimated to have included more than half of all new retinoblastoma cases worldwide in 2017. Children from LMICs, where the main global retinoblastoma burden lies, presented at an older age with more advanced disease and demonstrated a smaller proportion of familial history of retinoblastoma, likely because many do not reach a childbearing age. Given that retinoblastoma is curable, these data are concerning and mandate intervention at national and international levels. Further studies are needed to investigate factors, other than age at presentation, that may be associated with advanced disease in LMICs

Developing reproducible bioinformatics analysis workflows for heterogeneous computing environments to support African genomics

Background: The Pan-African bioinformatics network, H3ABioNet, comprises 27 research institutions in 17 African countries. H3ABioNet is part of the Human Health and Heredity in Africa program (H3Africa), an African-led research consortium funded by the US National Institutes of Health and the UK Wellcome Trust, aimed at using genomics to study and improve the health of Africans. A key role of H3ABioNet is to support H3Africa projects by building bioinformatics infrastructure such as portable and reproducible bioinformatics workflows for use on heterogeneous African computing environments. Processing and analysis of genomic data is an example of a big data application requiring complex interdependent data analysis workflows. Such bioinformatics workflows take the primary and secondary input data through several computationally-intensive processing steps using different software packages, where some of the outputs form inputs for other steps. Implementing scalable, reproducible, portable and easy-to-use workflows is particularly challenging. Results: H3ABioNet has built four workflows to support (1) the calling of variants from high-throughput sequencing data; (2) the analysis of microbial populations from 16S rDNA sequence data; (3) genotyping and genome-wide association studies; and (4) single nucleotide polymorphism imputation. A week-long hackathon was organized in August 2016 with participants from six African bioinformatics groups, and US and European collaborators. Two of the workflows are built using the Common Workflow Language framework (CWL) and two using Nextflow. All the workflows are containerized for improved portability and reproducibility using Docker, and are publicly available for use by members of the H3Africa consortium and the international research community. Conclusion: The H3ABioNet workflows have been implemented in view of offering ease of use for the end user and high levels of reproducibility and portability, all while following modern state of the art bioinformatics data processing protocols. The H3ABioNet workflows will service the H3Africa consortium projects and are currently in use. All four workflows are also publicly available for research scientists worldwide to use and adapt for their respective needs. The H3ABioNet workflows will help develop bioinformatics capacity and assist genomics research within Africa and serve to increase the scientific output of H3Africa and its Pan-African Bioinformatics Network