An interaction quantitative trait loci tool implicates epistatic functional variants in an apoptosis pathway in smallpox vaccine eQTL data

Lycopene from tomatoes and tomato products exerts renoprotective effects by ameliorating oxidative stress, apoptosis, pyroptosis, fibrosis, and inflammatory injury in calcium oxalate nephrolithiasis: the underlying mechanisms

Several mechanisms underlying nephrolithiasis, one of the most common urological diseases, involve calcium oxalate formation, including oxidative stress, inflammatory reactions, fibrosis, pyroptosis, and apoptosis. Although lycopene has strong antioxidant activity, its protective effects against CaOx-induced injury have not yet been reported. This study aimed to systematically investigate the protective effects of lycopene and explore its mechanisms and molecular targets. Crystal deposition, renal function, oxidative stress, inflammatory response, fibrosis, pyroptosis, and apoptosis were assessed to evaluate the renoprotective effects of lycopene against crystal formation in a CaOx rat model and oxalate-stimulated NRK-52E and HK-2 cells. Lycopene markedly ameliorated crystal deposition, restored renal function, and suppressed kidney injury by reducing oxidative stress, apoptosis, inflammation, fibrosis, and pyroptosis in the rats. In cell models, lycopene pretreatment reversed reactive oxygen species increase, apoptotic damage, intracellular lactate dehydrogenase release, cytotoxicity, pyroptosis, and extracellular matrix deposition. Network pharmacology and proteomic analyses were performed to identify lycopene target proteins under CaOx-exposed conditions, and the results showed that Trappc4 might be a pivotal target gene for lycopene, as identified by cellular thermal shift assay and surface plasmon resonance analyses. Based on molecular docking, molecular dynamics simulations, alanine scanning mutagenesis, and saturation mutagenesis, we observed that lycopene directly interacts with Trappc4 via hydrophobic bonds, which may be attributed to the PHE4 and PHE142 residues, preventing ERK1/2 or elevating AMPK signaling pathway phosphorylation events. In conclusion, lycopene might ameliorate oxalate-induced renal tubular epithelial cell injury via the Trappc4/ERK1/2/AMPK pathway, indicating its potential for the treatment of nephrolithiasis.

SCFD1 expression quantitative trait loci in amyotrophic lateral sclerosis are differentially expressed

Evidence indicates that common variants found in genome-wide association studies increase risk of disease through gene regulation via expression Quantitative Trait Loci. Using multiple genome-wide methods, we examined if Single Nucleotide Polymorphisms increase risk of Amyotrophic Lateral Sclerosis through expression Quantitative Trait Loci, and whether expression Quantitative Trait Loci expression is consistent across people who had Amyotrophic Lateral Sclerosis and those who did not. In combining public expression Quantitative Trait Loci data with Amyotrophic Lateral Sclerosis genome-wide association studies, we used Summary-data-based Mendelian Randomization to confirm that SCFD1 was the only gene that was genome-wide significant in mediating Amyotrophic Lateral Sclerosis risk via expression Quantitative Trait Loci (Summary-data-based Mendelian Randomization beta = 0.20, standard error = 0.04, P-value = 4.29 × 10-6). Using post-mortem motor cortex, we tested whether expression Quantitative Trait Loci showed significant differences in expression between Amyotrophic Lateral Sclerosis (n = 76) and controls (n = 25), genome-wide. Of 20 757 genes analysed, the two most significant expression Quantitative Trait Loci to show differential in expression between Amyotrophic Lateral Sclerosis and controls involve two known Amyotrophic Lateral Sclerosis genes (SCFD1 and VCP). Cis-acting SCFD1 expression Quantitative Trait Loci downstream of the gene showed significant differences in expression between Amyotrophic Lateral Sclerosis and controls (top expression Quantitative Trait Loci beta = 0.34, standard error = 0.063, P-value = 4.54 × 10-7). These SCFD1 expression Quantitative Trait Loci also significantly modified Amyotrophic Lateral Sclerosis survival (number of samples = 4265, hazard ratio = 1.11, 95% confidence interval = 1.05-1.17, P-value = 2.06 × 10-4) and act as an Amyotrophic Lateral Sclerosis trans-expression Quantitative Trait Loci hotspot for a wider network of genes enriched for SCFD1 function and Amyotrophic Lateral Sclerosis pathways. Using gene-set analyses, we found the genes that correlate with this trans-expression Quantitative Trait Loci hotspot significantly increase risk of Amyotrophic Lateral Sclerosis (beta = 0.247, standard deviation = 0.017, P = 0.001) and schizophrenia (beta = 0.263, standard deviation = 0.008, P-value = 1.18 × 10-5), a disease that genetically correlates with Amyotrophic Lateral Sclerosis. In summary, SCFD1 expression Quantitative Trait Loci are a major factor in Amyotrophic Lateral Sclerosis, not only influencing disease risk but are differentially expressed in post-mortem Amyotrophic Lateral Sclerosis. SCFD1 expression Quantitative Trait Loci show distinct expression profiles in Amyotrophic Lateral Sclerosis that correlate with a wider network of genes that also confer risk of the disease and modify the disease's duration.

Scaling tree-based automated machine learning to biomedical big data with a feature set selector

Motivation

Automated machine learning (AutoML) systems are helpful data science assistants designed to scan data for novel features, select appropriate supervised learning models and optimize their parameters. For this purpose, Tree-based Pipeline Optimization Tool (TPOT) was developed using strongly typed genetic programing (GP) to recommend an optimized analysis pipeline for the data scientist’s prediction problem. However, like other AutoML systems, TPOT may reach computational resource limits when working on big data such as whole-genome expression data.

Results

We introduce two new features implemented in TPOT that helps increase the system’s scalability: Feature Set Selector (FSS) and Template. FSS provides the option to specify subsets of the features as separate datasets, assuming the signals come from one or more of these specific data subsets. FSS increases TPOT’s efficiency in application on big data by slicing the entire dataset into smaller sets of features and allowing GP to select the best subset in the final pipeline. Template enforces type constraints with strongly typed GP and enables the incorporation of FSS at the beginning of each pipeline. Consequently, FSS and Template help reduce TPOT computation time and may provide more interpretable results. Our simulations show TPOT-FSS significantly outperforms a tuned XGBoost model and standard TPOT implementation. We apply TPOT-FSS to real RNA-Seq data from a study of major depressive disorder. Independent of the previous study that identified significant association with depression severity of two modules, TPOT-FSS corroborates that one of the modules is largely predictive of the clinical diagnosis of each individual.

Availability and implementation

Detailed simulation and analysis code needed to reproduce the results in this study is available at https://github.com/lelaboratoire/tpot-fss. Implementation of the new TPOT operators is available at https://github.com/EpistasisLab/tpot.

Supplementary information

Supplementary data are available at Bioinformatics online.

Evidence for Residual Immunity to Smallpox After Vaccination and Implications for Re-emergence

INTRODUCTION

Smallpox has been eradicated but advances in synthetic biology have increased the risk of its re-emergence. Residual immunity in individuals who were previously vaccinated may mitigate the impact of an outbreak, but there is a high degree of uncertainty about the duration and degree of residual immunity. Both cell-mediated and humoral immunity are thought to be important but the exact mechanisms of protection are unclear. Guidelines usually suggest vaccine-induced immunity wanes to zero after 3-10 years post vaccination, whereas other estimates show long term immunity over decades.

MATERIALS AND METHODS

A systematic review of the literature was conducted to quantify the duration and extent of residual immunity to smallpox after vaccination.

RESULTS

Twenty-nine papers related to quantifying residual immunity to smallpox after vaccination were identified: neutralizing antibody levels were used as immune correlates of protection in 11/16 retrospective cross-sectional studies, 2/3 epidemiological studies, 6/7 prospective vaccine trials and 0/3 modeling studies. Duration of protection of >20 years was consistently shown in the 16 retrospective cross-sectional studies, while the lowest estimated duration of protection was 11.7 years among the modeling studies. Childhood vaccination conferred longer duration of protection than vaccination in adulthood, and multiple vaccinations did not appear to improve immunity.

CONCLUSIONS

Most studies suggest a longer duration of residual immunity (at least 20 years) than assumed in smallpox guidelines. Estimates from modeling studies were less but still greater than the 3-10 years suggested by the WHO Committee on International Quarantine or US CDC guidelines. These recommendations were probably based on observations and studies conducted while smallpox was endemic. The cut-off values for pre-existing antibody levels of >1:20 and >1:32 reported during the period of endemic smallpox circulation may not be relevant to the contemporary population, but have been used as a threshold for identifying people with residual immunity in post-eradication era studies. Of the total antibodies produced in response to smallpox vaccination, neutralizing antibodies have shown to contribute significantly to immunological memory. Although the mechanism of immunological memory and boosting is unclear, revaccination is likely to result in a more robust response. There is a need to improve the evidence base for estimates on residual immunity to better inform planning and preparedness for re-emergent smallpox.

Serological Immunity to Smallpox in New South Wales, Australia

The re-emergence of smallpox is an increasing and legitimate concern due to advances in synthetic biology. Vaccination programs against smallpox using the vaccinia virus vaccine ceased with the eradication of smallpox and, unlike many other countries, Australia did not use mass vaccinations. However, vaccinated migrants contribute to population immunity. Testing for vaccinia antibodies is not routinely performed in Australia, and few opportunities exist to estimate the level of residual population immunity against smallpox. Serological data on population immunity in Australia could inform management plans against a smallpox outbreak. Vaccinia antibodies were measured in 2003 in regular plasmapheresis donors at the Australian Red Cross Blood Service from New South Wales (NSW). The data were analysed to estimate the proportion of Australians in NSW with detectable serological immunity to vaccinia. The primary object of this study was to measure neutralising antibody titres against vaccinia virus. Titre levels in donor samples were determined by plaque reduction assay. To estimate current levels of immunity to smallpox infection, the decline in geometric mean titres (GMT) over time was projected using two values for the antibody levels estimated on the basis of different times since vaccination. The results of this study suggest that there is minimal residual immunity to the vaccinia virus in the Australian population. Although humoral immunity is protective against orthopoxvirus infections, cell-mediated immunity and immunological memory likely also play roles, which are not quantified by antibody levels. These data provide an immunological snapshot of the NSW population, which could inform emergency preparedness planning and outbreak control, especially concerning the stockpiling of vaccinia vaccine.

The role of systems biology approaches in determining molecular signatures for the development of more effective vaccines

INTRODUCTION

Emerging infectious diseases are a major threat to public health, and while vaccines have proven to be one of the most effective preventive measures for infectious diseases, we still do not have safe and effective vaccines against many human pathogens, and emerging diseases continually pose new threats. The purpose of this review is to discuss how the creation of vaccines for these new threats has been hindered by limitations in the current approach to vaccine development. Recent advances in high-throughput technologies have enabled scientists to apply systems biology approaches to collect and integrate increasingly large datasets that capture comprehensive biological changes induced by vaccines, and then decipher the complex immune response to those vaccines.

AREAS COVERED

This review covers advances in these technologies and recent publications that describe systems biology approaches to understanding vaccine immune responses and to understanding the rational design of new vaccine candidates.

EXPERT OPINION

Systems biology approaches to vaccine development provide novel information regarding both the immune response and the underlying mechanisms and can inform vaccine development.

Transition-transversion encoding and genetic relationship metric in ReliefF feature selection improves pathway enrichment in GWAS

BACKGROUND

ReliefF is a nearest-neighbor based feature selection algorithm that efficiently detects variants that are important due to statistical interactions or epistasis. For categorical predictors, like genotypes, the standard metric used in ReliefF has been a simple (binary) mismatch difference. In this study, we develop new metrics of varying complexity that incorporate allele sharing, adjustment for allele frequency heterogeneity via the genetic relationship matrix (GRM), and physicochemical differences of variants via a new transition/transversion encoding.

METHODS

We introduce a new two-dimensional transition/transversion genotype encoding for ReliefF, and we implement three ReliefF attribute metrics: 1.) genotype mismatch (GM), which is the ReliefF standard, 2.) allele mismatch (AM), which accounts for heterozygous differences and has not been used previously in ReliefF, and 3.) the new transition/transversion metric. We incorporate these attribute metrics into the ReliefF nearest neighbor calculation with a Manhattan metric, and we introduce GRM as a new ReliefF nearest-neighbor metric to adjust for allele frequency heterogeneity.

RESULTS

We apply ReliefF with each metric to a GWAS of major depressive disorder and compare the detection of genes in pathways implicated in depression, including Axon Guidance, Neuronal System, and G Protein-Coupled Receptor Signaling. We also compare with detection by Random Forest and Lasso as well as random/null selection to assess pathway size bias.

CONCLUSIONS

Our results suggest that using more genetically motivated encodings, such as transition/transversion, and metrics that adjust for allele frequency heterogeneity, such as GRM, lead to ReliefF attribute scores with improved pathway enrichment.

Identification and replication of RNA-Seq gene network modules associated with depression severity

Genomic variation underlying major depressive disorder (MDD) likely involves the interaction and regulation of multiple genes in a network. Data-driven co-expression network module inference has the potential to account for variation within regulatory networks, reduce the dimensionality of RNA-Seq data, and detect significant gene-expression modules associated with depression severity. We performed an RNA-Seq gene co-expression network analysis of mRNA data obtained from the peripheral blood mononuclear cells of unmedicated MDD (n = 78) and healthy control (n = 79) subjects. Across the combined MDD and HC groups, we assigned genes into modules using hierarchical clustering with a dynamic tree cut method and projected the expression data onto a lower-dimensional module space by computing the single-sample gene set enrichment score of each module. We tested the single-sample scores of each module for association with levels of depression severity measured by the Montgomery-Åsberg Depression Scale (MADRS). Independent of MDD status, we identified 23 gene modules from the co-expression network. Two modules were significantly associated with the MADRS score after multiple comparison adjustment (adjusted p = 0.009, 0.028 at 0.05 FDR threshold), and one of these modules replicated in a previous RNA-Seq study of MDD (p = 0.03). The two MADRS-associated modules contain genes previously implicated in mood disorders and show enrichment of apoptosis and B cell receptor signaling. The genes in these modules show a correlation between network centrality and univariate association with depression, suggesting that intramodular hub genes are more likely to be related to MDD compared to other genes in a module.

The Integration of Epistasis Network and Functional Interactions in a GWAS Implicates RXR Pathway Genes in the Immune Response to Smallpox Vaccine

Although many diseases and traits show large heritability, few genetic variants have been found to strongly separate phenotype groups by genotype. Complex regulatory networks of variants and expression of multiple genes lead to small individual-variant effects and difficulty replicating the effect of any single variant in an affected pathway. Interaction network modeling of GWAS identifies effects ignored by univariate models, but population differences may still cause specific genes to not replicate. Integrative network models may help detect indirect effects of variants in the underlying biological pathway. In this study, we used gene-level functional interaction information from the Integrative Multi-species Prediction (IMP) tool to reveal important genes associated with a complex phenotype through evidence from epistasis networks and pathway enrichment. We test this method for augmenting variant-based network analyses with functional interactions by applying it to a smallpox vaccine immune response GWAS. The integrative analysis spotlights the role of genes related to retinoid X receptor alpha (RXRA), which has been implicated in a previous epistasis network analysis of smallpox vaccine.