LanceOtron: a deep learning peak caller for genome sequencing experiments.

MOTIVATION: Genome sequencing experiments have revolutionized molecular biology by allowing researchers to identify important DNA-encoded elements genome wide. Regions where these elements are found appear as peaks in the analog signal of an assay's coverage track, and despite the ease with which humans can visually categorize these patterns, the size of many genomes necessitates algorithmic implementations. Commonly used methods focus on statistical tests to classify peaks, discounting that the background signal does not completely follow any known probability distribution and reducing the information-dense peak shapes to simply maximum height. Deep learning has been shown to be highly accurate for many pattern recognition tasks, on par or even exceeding human capabilities, providing an opportunity to reimagine and improve peak calling. RESULTS: We present the peak calling framework LanceOtron, which combines deep learning for recognizing peak shape with multifaceted enrichment calculations for assessing significance. In benchmarking ATAC-seq, ChIP-seq and DNase-seq, LanceOtron outperforms long-standing, gold-standard peak callers through its improved selectivity and near-perfect sensitivity. AVAILABILITY AND IMPLEMENTATION: A fully featured web application is freely available from LanceOtron.molbiol.ox.ac.uk, command line interface via python is pip installable from PyPI at https://pypi.org/project/lanceotron/, and source code and benchmarking tests are available at https://github.com/LHentges/LanceOtron. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Gene-environment interaction in dyslipidemia.

PURPOSE OF REVIEW: Recent genome-wide association studies have identified numerous common genetic variants associated with plasma lipid traits and have provided new insights into the regulation of lipoprotein metabolism including the identification of novel biological processes. These findings add to a body of existing data on dietary and environmental factors affecting plasma lipids. Here we explore how interactions between genetic risk factors and other phenotypes may explain some of the missing heritability of plasma lipid traits. RECENT FINDINGS: Recent studies have identified true statistical interaction between several environmental and genetic risk factors and their effects on plasma lipid fractions. These include interactions between behaviors such as smoking or exercise as well as specific dietary nutrients and the effect size of specific genetic variants on plasma lipid traits risk and modifying effects of measures of adiposity on the cumulative impact of a number of common genetic variants on each of plasma triglycerides and HDL cholesterol. SUMMARY: Interactions between genetic risk factors and clinical phenotypes may account for some of the unexplained heritability of plasma lipid traits. Recent studies provide biological insight into specific genetic associations and may aid in the identification of dyslipidemic patients for whom specific lifestyle interventions are likely to be most effective.

Adiposity significantly modifies genetic risk for dyslipidemia.

Recent genome-wide association studies have identified multiple loci robustly associated with plasma lipids, which also contribute to extreme lipid phenotypes. However, these common genetic variants explain <12% of variation in lipid traits. Adiposity is also an important determinant of plasma lipoproteins, particularly plasma TGs and HDL cholesterol (HDLc) concentrations. Thus, interactions between genes and clinical phenotypes may contribute to this unexplained heritability. We have applied a weighted genetic risk score (GRS) for both plasma TGs and HDLc in two large cohorts at the extremes of BMI. Both BMI and GRS were strongly associated with these lipid traits. A significant interaction between obese/lean status and GRS was noted for each of TG (P(Interaction) = 2.87 × 10(-4)) and HDLc (P(Interaction) = 1.05 × 10(-3)). These interactions were largely driven by SNPs tagging APOA5, glucokinase receptor (GCKR), and LPL for TG, and cholesteryl ester transfer protein (CETP), GalNAc-transferase (GALNT2), endothelial lipase (LIPG), and phospholipid transfer protein (PLTP) for HDLc. In contrast, the GRSLDL cholesterol × adiposity interaction was not significant. Sexual dimorphism was evident for the GRSHDL on HDLc in obese (P(Interaction) = 0.016) but not lean subjects. SNP by BMI interactions may provide biological insight into specific genetic associations and missing heritability.

RfaL is required for Yersinia pestis type III secretion and virulence.

Yersinia pestis, the causative agent of plague, uses a type III secretion system (T3SS) to inject cytotoxic Yop proteins directly into the cytosol of mammalian host cells. The T3SS can also be activated in vitro at 37°C in the absence of calcium. The chromosomal gene rfaL (waaL) was recently identified as a virulence factor required for proper function of the T3SS. RfaL functions as a ligase that adds the terminal N-acetylglucosamine to the lipooligosaccharide core of Y. pestis. We previously showed that deletion of rfaL prevents secretion of Yops in vitro. Here we show that the divalent cations calcium, strontium, and magnesium can partially or fully rescue Yop secretion in vitro, indicating that the secretion phenotype of the rfaL mutant may be due to structural changes in the outer membrane and the corresponding feedback inhibition on the T3SS. In support of this, we found that the defect can be overcome by deleting the regulatory gene lcrQ. Consistent with a defective T3SS, the rfaL mutant is less virulent than the wild type. We show here that the virulence defect of the mutant correlates with a decrease in both T3SS gene expression and ability to inject innate immune cells, combined with an increased sensitivity to cationic antimicrobial peptides.

SMAC Mimetics Synergistically Cooperate with HDAC Inhibitors Enhancing TNF-α Autocrine Signaling.

The overexpression of inhibitor of apoptosis (IAP) proteins is strongly related to poor survival of women with ovarian cancer. Recurrent ovarian cancers resist apoptosis due to the dysregulation of IAP proteins. Mechanistically, Second Mitochondrial Activator of Caspases (SMAC) mimetics suppress the functions of IAP proteins to restore apoptotic pathways resulting in tumor death. We previously conducted a phase 2 clinical trial of the single-agent SMAC mimetic birinapant and observed minimal drug response in women with recurrent ovarian cancer despite demonstrating on-target activity. Accordingly, we performed a high-throughput screening matrix to identify synergistic drug combinations with birinapant. SMAC mimetics in combination with an HDAC inhibitor showed remarkable synergy and was, therefore, selected for further evaluation. We show here that this synergy observed both in vitro and in vivo results from multiple convergent pathways to include increased caspase activation, HDAC inhibitor-mediated TNF-α upregulation, and alternative NF-kB signaling. These findings provide a rationale for the integration of SMAC mimetics and HDAC inhibitors in clinical trials for recurrent ovarian cancer where treatment options are still limited.

First-in-human phase 1 clinical trial of anti-core 1 O-glycans targeting monoclonal antibody NEO-201 in treatment-refractory solid tumors.

BACKGROUND: NEO201 is a humanized IgG1 monoclonal antibody (mAb) generated against tumor-associated antigens from patients with colorectal cancer. NEO-201 binds to core 1 or extended core 1 O-glycans expressed by its target cells. Here, we present outcomes from a phase I trial of NEO-201 in patients with advanced solid tumors that have not responded to standard treatments. METHODS: This was a single site, open label 3 + 3 dose escalation clinical trial. NEO-201 was administered intravenously every two weeks in a 28-day cycle at dose level (DL) 1 (1 mg/kg), DL 1.5 (1.5 mg/kg) and DL 2 (2 mg/kg) until dose limiting toxicity (DLT), disease progression, or patient withdrawal. Disease evaluations were conducted after every 2 cycles. The primary objective was to assess the maximum tolerated dose (MTD) and recommended phase 2 dose (RP2D) of NEO-201. The secondary objective was to assess the antitumor activity by RECIST v1.1. The exploratory objectives assessed pharmacokinetics and the effect of NEO-201 administration on immunologic parameters and their impact on clinical response. RESULTS: Seventeen patients (11 colorectal, 4 pancreatic and 2 breast cancers) were enrolled; 2 patients withdrew after the first dose and were not evaluable for DLT. Twelve of the 15 patients evaluable for safety discontinued due to disease progression and 3 patients discontinued due to DLT (grade 4 febrile neutropenia [1 patient] and prolonged neutropenia [1 patient] at DL 2, and grade 3 prolonged (> 72 h) febrile neutropenia [1 patient] at DL 1.5). A total of 69 doses of NEO-201 were administered (range 1-15, median 4). Common (> 10%) grade 3/4 toxicities occurred as follows: neutropenia (26/69 doses, 17/17 patients), white blood cell decrease (16/69 doses, 12/17 patients), lymphocyte decrease (8/69 doses, 6/17 patients). Thirteen patients were evaluable for disease response; the best response was stable disease (SD) in 4 patients with colorectal cancer. Analysis of soluble factors in serum revealed that a high level of soluble MICA at baseline was correlated with a downregulation of NK cell activation markers and progressive disease. Unexpectedly, flow cytometry showed that NEO-201 also binds to circulating regulatory T cells and reduction of the quantities of these cells was observed especially in patients with SD. CONCLUSIONS: NEO-201 was safe and well tolerated at the MTD of 1.5 mg/kg, with neutropenia being the most common adverse event. Furthermore, a reduction in the percentage of regulatory T cells following NEO-201 treatment supports our ongoing phase II clinical trial evaluating the efficiency of the combination of NEO-201 with the immune checkpoint inhibitor pembrolizumab in adults with treatment-resistant solid tumors. TRIAL REGISTRATION: NCT03476681 . Registered 03/26/2018.

Intraperitoneal Monocytes plus IFNs as a Novel Cellular Immunotherapy for Ovarian Cancer: Mechanistic Characterization and Results from a Phase I Clinical Trial.

PURPOSE: Ovarian cancer is the most lethal gynecologic cancer and intrinsically resistant to checkpoint immunotherapies. We sought to augment innate immunity, building on previous work with IFNs and monocytes. PATIENTS AND METHODS: Preclinical experiments were designed to define the mechanisms of cancer cell death mediated by the combination of IFNs α and γ with monocytes. We translated these preclinical findings into a phase I trial of autologous IFN-activated monocytes administered intraperitoneally to platinum-resistant or -refractory ovarian cancer patients. RESULTS: IFN-treated monocytes induced caspase 8-dependent apoptosis by the proapoptotic TRAIL and mediated by the death receptors 4 and 5 (DR4 and DR5, respectively) on cancer cells. Therapy was well tolerated with evidence of clinical activity, as 2 of 9 evaluable patients had a partial response by RECIST criteria, and 1 additional patient had a CA-125 response. Upregulation of monocyte-produced TRAIL and cytokines was confirmed in peripheral blood. Long-term responders had alterations in innate and adaptive immune compartments. CONCLUSIONS: Given the mechanism of cancer cell death, and the acceptable tolerability of the clinical regimen, this platform presents a possibility for future combination therapies to augment anticancer immunity. See related commentary by Chow and Dorigo, p. 299.

Demographic inference from multiple whole genomes using a particle filter for continuous Markov jump processes.

Demographic events shape a population's genetic diversity, a process described by the coalescent-with-recombination model that relates demography and genetics by an unobserved sequence of genealogies along the genome. As the space of genealogies over genomes is large and complex, inference under this model is challenging. Formulating the coalescent-with-recombination model as a continuous-time and -space Markov jump process, we develop a particle filter for such processes, and use waypoints that under appropriate conditions allow the problem to be reduced to the discrete-time case. To improve inference, we generalise the Auxiliary Particle Filter for discrete-time models, and use Variational Bayes to model the uncertainty in parameter estimates for rare events, avoiding biases seen with Expectation Maximization. Using real and simulated genomes, we show that past population sizes can be accurately inferred over a larger range of epochs than was previously possible, opening the possibility of jointly analyzing multiple genomes under complex demographic models. Code is available at https://github.com/luntergroup/smcsmc.

Driving Immune Responses in the Ovarian Tumor Microenvironment.

Ovarian cancer is the leading cause of death among gynecological neoplasms, with an estimated 14,000 deaths in 2019. First-line treatment options center around a taxane and platinum-based chemotherapy regimen. However, many patients often have recurrence due to late stage diagnoses and acquired chemo-resistance. Recent approvals for bevacizumab and poly (ADP-ribose) polymerase inhibitors have improved treatment options but effective treatments are still limited in the recurrent setting. Immunotherapy has seen significant success in hematological and solid malignancies. However, effectiveness has been limited in ovarian cancer. This may be due to a highly immunosuppressive tumor microenvironment and a lack of tumor-specific antigens. Certain immune cell subsets, such as regulatory T cells and tumor-associated macrophages, have been implicated in ovarian cancer. Consequently, therapies augmenting the immune response, such as immune checkpoint inhibitors and dendritic cell vaccines, may be unable to properly enact their effector functions. A better understanding of the various interactions among immune cell subsets in the peritoneal microenvironment is necessary to develop efficacious therapies. This review will discuss various cell subsets in the ovarian tumor microenvironment, current immunotherapy modalities to target or augment these immune subsets, and treatment challenges.

A community-maintained standard library of population genetic models.

The explosion in population genomic data demands ever more complex modes of analysis, and increasingly, these analyses depend on sophisticated simulations. Recent advances in population genetic simulation have made it possible to simulate large and complex models, but specifying such models for a particular simulation engine remains a difficult and error-prone task. Computational genetics researchers currently re-implement simulation models independently, leading to inconsistency and duplication of effort. This situation presents a major barrier to empirical researchers seeking to use simulations for power analyses of upcoming studies or sanity checks on existing genomic data. Population genetics, as a field, also lacks standard benchmarks by which new tools for inference might be measured. Here, we describe a new resource, stdpopsim, that attempts to rectify this situation. Stdpopsim is a community-driven open source project, which provides easy access to a growing catalog of published simulation models from a range of organisms and supports multiple simulation engine backends. This resource is available as a well-documented python library with a simple command-line interface. We share some examples demonstrating how stdpopsim can be used to systematically compare demographic inference methods, and we encourage a broader community of developers to contribute to this growing resource.

Genome-wide association study of a nicotine metabolism biomarker in African American smokers: impact of chromosome 19 genetic influences.

BACKGROUND AND AIMS: The activity of CYP2A6, the major nicotine-inactivating enzyme, is measurable in smokers using the nicotine metabolite ratio (NMR; 3'hydroxycotinine/cotinine). Due to its role in nicotine clearance, the NMR is associated with smoking behaviours and response to pharmacotherapies. The NMR is highly heritable (~80%), and on average lower in African Americans (AA) versus whites. We previously identified several reduce and loss-of-function CYP2A6 variants common in individuals of African descent. Our current aim was to identify novel genetic influences on the NMR in AA smokers using genome-wide approaches. DESIGN: Genome-wide association study (GWAS). SETTING: Multiple sites within Canada and the United States. PARTICIPANTS: AA smokers from two clinical trials: Pharmacogenetics of Nicotine Addiction Treatment (PNAT)-2 (NCT01314001; n = 504) and Kick-it-at-Swope (KIS)-3 (NCT00666978; n = 450). MEASUREMENTS: Genome-wide SNP genotyping, the NMR (phenotype) and population substructure and NMR covariates. FINDINGS: Meta-analysis revealed three independent chromosome 19 signals (rs12459249, rs111645190 and rs185430475) associated with the NMR. The top overall hit, rs12459249 (P = 1.47e-39; beta = 0.59 per C (versus T) allele, SE = 0.045), located ~9.5 kb 3' of CYP2A6, remained genome-wide significant after controlling for the common (~10% in AA) non-functional CYP2A6*17 allele. In contrast, rs111645190 and rs185430475 were not genome-wide significant when controlling for CYP2A6*17. In total, 96 signals associated with the NMR were identified; many were not found in prior NMR GWASs in individuals of European descent. The top hits were also associated with the NMR in a third cohort of AA (KIS2; n = 480). None of the hits were in UGT or OCT2 genes. CONCLUSIONS: Three independent chromosome 19 signals account for ~20% of the variability in the nicotine metabolite ratio in African American smokers. The hits identified may contribute to inter-ethnic variability in nicotine metabolism, smoking behaviours and tobacco-related disease risk.

Case Report: Mass Casualty Lightning Strike at Ranger Training Camp.

BACKGROUND: Although lightning strikes are a rare occurrence, their significance cannot be ignored given military operations in the field during all types of weather. With proper medical management, patients with lightning injuries can return to duty. METHODS: Information for this case report comes from eyewitness account at the 6th Ranger Training Battalion and from review of physician documentation from the 96th Medical Group, Eglin Air Force Base, Florida. RESULTS: A lightning strike injured 44 Ranger School participants during a training exercise on August 12, 2015, at Camp Rudder, Florida. These patients were triaged in the field and transported to emergency department of Eglin Air Force Base. Of the 44 casualties, 20 were admitted. All were returned to duty the following day. One patient had cardiac arrest. This patient, along with two others, was admitted to the intensive care unit. Seventeen other patients were admitted for observation for rhabdomyolysis and/or cardiac arrhythmias. One patient was admitted with suspected acute kidney injury indicated by an elevated creatinine. All patients, including those admitted to the intensive care unit, were released on the day following the lightning strike without restrictions and were allowed to return to duty with increased medical monitoring. DISCUSSION: This case report highlights the need for proper triage and recognition of lightning strike injury, coordination of care between field operations and emergency department personnel, and close follow-up for patients presenting with lightning injury. Symptoms, physical exam, and laboratory findings from rigorous training can be difficult to distinguish from those resulting from lightning injury. Secondary injuries resulting from blunt trauma from falls may have been prevented by the use of the lightning strike posture. Further analysis of procedures and standard operating protocols to mitigate risk during thunderstorms may be required to prevent lightning's effects on large groups of military personnel.

Haploinsufficiency for DNA methyltransferase 3A predisposes hematopoietic cells to myeloid malignancies.

The gene that encodes de novo DNA methyltransferase 3A (DNMT3A) is frequently mutated in acute myeloid leukemia genomes. Point mutations at position R882 have been shown to cause a dominant negative loss of DNMT3A methylation activity, but 15% of DNMT3A mutations are predicted to produce truncated proteins that could either have dominant negative activities or cause loss of function and haploinsufficiency. Here, we demonstrate that 3 of these mutants produce truncated, inactive proteins that do not dimerize with WT DNMT3A, strongly supporting the haploinsufficiency hypothesis. We therefore evaluated hematopoiesis in mice heterozygous for a constitutive null Dnmt3a mutation. With no other manipulations, Dnmt3a+/- mice developed myeloid skewing over time, and their hematopoietic stem/progenitor cells exhibited a long-term competitive transplantation advantage. Dnmt3a+/- mice also spontaneously developed transplantable myeloid malignancies after a long latent period, and 3 of 12 tumors tested had cooperating mutations in the Ras/MAPK pathway. The residual Dnmt3a allele was neither mutated nor downregulated in these tumors. The bone marrow cells of Dnmt3a+/- mice had a subtle but statistically significant DNA hypomethylation phenotype that was not associated with gene dysregulation. These data demonstrate that haploinsufficiency for Dnmt3a alters hematopoiesis and predisposes mice (and probably humans) to myeloid malignancies by a mechanism that is not yet clear.

Polygenic risk score prediction of antipsychotic dosage in schizophrenia.

OBJECTIVE: Genetic variants have yet to be identified as reliable predictors of antipsychotic dosage. The purpose of this study is to quantify significant genetic risk variants prioritized from the Psychiatric GWAS Consortium (PGC2) study for schizophrenia as a polygenic score to test our hypothesis that it may represent symptom severity in patients and therefore predict antipsychotic dosage. METHODS: Antipsychotic medication and dosage were collected in our sample of 83 patients with schizophrenia spectrum disorders of a homogeneous European background. Antipsychotic dosage was standardized according to the Product Monograph (PM%), chlorpromazine equivalents (CPZe), and Defined Daily Dose (DDD). We calculated polygenic risk scores (PRS) for the significant risk loci identified from the PGC2 GWAS to predict dosage using a linear regression model. RESULTS: In our analysis, the PRS showed no significant association with PM%, CPZe, and DDD dosage. Considering symptom severity and overall functioning, our PRS was similarly not significantly associated with Global Assessment of Functioning (GAF) scores. DISCUSSION: Our results do not provide evidence for a polygenic inheritance of schizophrenia that influences levels of antipsychotic dosage. To the best of our knowledge, this is one of the first studies of its kind to use the PRS from the PGC2 significant risk variants to predict a clinically relevant phenotype. The PRS offers a novel approach to analyzing the genetic liability for many clinically relevant phenotypes in schizophrenia.

Increased genetic risk for obesity in premature coronary artery disease.

There is ongoing controversy as to whether obesity confers risk for CAD independently of associated risk factors including diabetes mellitus. We have carried out a Mendelian randomization study using a genetic risk score (GRS) for body mass index (BMI) based on 35 risk alleles to investigate this question in a population of 5831 early onset CAD cases without diabetes mellitus and 3832 elderly healthy control subjects, all of strictly European ancestry, with adjustment for traditional risk factors (TRFs). We then estimated the genetic correlation between these BMI and CAD (rg) by relating the pairwise genetic similarity matrix to a phenotypic covariance matrix between these two traits. GRSBMI significantly (P=2.12 × 10(-12)) associated with CAD status in a multivariate model adjusted for TRFs, with a per allele odds ratio (OR) of 1.06 (95% CI 1.042-1.076). The addition of GRSBMI to TRFs explained 0.75% of CAD variance and yielded a continuous net recombination index of 16.54% (95% CI=11.82-21.26%, P<0.0001). To test whether GRSBMI explained CAD status when adjusted for measured BMI, separate models were constructed in which the score and BMI were either included as covariates or not. The addition of BMI explained ~1.9% of CAD variance and GRSBMI plus BMI explained 2.65% of CAD variance. Finally, using bivariate restricted maximum likelihood analysis, we provide strong evidence of genome-wide pleiotropy between obesity and CAD. This analysis supports the hypothesis that obesity is a causal risk factor for CAD.

PML-RARA requires DNA methyltransferase 3A to initiate acute promyelocytic leukemia.

The DNA methyltransferases DNMT3A and DNMT3B are primarily responsible for de novo methylation of specific cytosine residues in CpG dinucleotides during mammalian development. While loss-of-function mutations in DNMT3A are highly recurrent in acute myeloid leukemia (AML), DNMT3A mutations are almost never found in AML patients with translocations that create oncogenic fusion genes such as PML-RARA, RUNX1-RUNX1T1, and MLL-AF9. Here, we explored how DNMT3A is involved in the function of these fusion genes. We used retroviral vectors to express PML-RARA, RUNX1-RUNX1T1, or MLL-AF9 in bone marrow cells derived from WT or DNMT3A-deficient mice. Additionally, we examined the phenotypes of hematopoietic cells from Ctsg-PML-RARA mice, which express PML-RARA in early hematopoietic progenitors and myeloid precursors, with or without DNMT3A. We determined that the methyltransferase activity of DNMT3A, but not DNMT3B, is required for aberrant PML-RARA-driven self-renewal ex vivo and that DNMT3A is dispensable for RUNX1-RUNX1T1- and MLL-AF9-driven self-renewal. Furthermore, both the PML-RARA-driven competitive transplantation advantage and development of acute promyelocytic leukemia (APL) required DNMT3A. Together, these findings suggest that PML-RARA requires DNMT3A to initiate APL in mice.

Rapporteur summaries of plenary, symposia, and oral sessions from the XXIIIrd World Congress of Psychiatric Genetics Meeting in Toronto, Canada, 16-20 October 2015.

The XXIIIrd World Congress of Psychiatric Genetics meeting, sponsored by the International Society of Psychiatric Genetics, was held in Toronto, ON, Canada, on 16-20 October 2015. Approximately 700 participants attended to discuss the latest state-of-the-art findings in this rapidly advancing and evolving field. The following report was written by trainee travel awardees. Each was assigned one session as a rapporteur. This manuscript represents the highlights and topics that were covered in the plenary sessions, symposia, and oral sessions during the conference, and contains major notable and new findings.