Developmental pyrethroid exposure disrupts molecular pathways for MAP kinase and circadian rhythms in mouse brain.

Neurodevelopmental disorders (NDDs) are a category of pervasive disorders of the developing nervous system with few or no recognized biomarkers. A significant portion of the risk for NDDs, including attention deficit hyperactivity disorder (ADHD), is contributed by the environment, and exposure to pyrethroid pesticides during pregnancy has been identified as a potential risk factor for NDD in the unborn child. We recently showed that low-dose developmental exposure to the pyrethroid pesticide deltamethrin in mice causes male-biased changes to ADHD- and NDD-relevant behaviors as well as the striatal dopamine system. Here, we used an integrated multiomics approach to determine the broadest possible set of biological changes in the mouse brain caused by developmental pyrethroid exposure (DPE). Using a litter-based, split-sample design, we exposed mouse dams during pregnancy and lactation to deltamethrin (3 mg/kg or vehicle every 3 days) at a concentration well below the EPA-determined benchmark dose used for regulatory guidance. We raised male offspring to adulthood, euthanized them, and pulverized and divided whole brain samples for split-sample transcriptomics, kinomics and multiomics integration. Transcriptome analysis revealed alterations to multiple canonical clock genes, and kinome analysis revealed changes in the activity of multiple kinases involved in synaptic plasticity, including the mitogen-activated protein (MAP) kinase ERK. Multiomics integration revealed a dysregulated protein-protein interaction network containing primary clusters for MAP kinase cascades, regulation of apoptosis, and synaptic function. These results demonstrate that DPE causes a multi-modal biophenotype in the brain relevant to ADHD and identifies new potential mechanisms of action.

Developmental pyrethroid exposure disrupts folate metabolism in mouse brain.

Environmental and genetic risk factors, and their interactions, contribute significantly to the etiology of neurodevelopmental disorders (NDDs). Recent epidemiology studies have implicated pyrethroid pesticides as an environmental risk factor for autism and developmental delay. Our previous research showed that low-dose developmental exposure to the pyrethroid pesticide deltamethrin in mice caused male-biased changes in the brain and in NDD-relevant behaviors in adulthood. Here, we used a metabolomics approach to determine the broadest possible set of metabolic changes in the adult male mouse brain caused by low-dose pyrethroid exposure during development. Using a litter-based design, we exposed mouse dams during pregnancy and lactation to deltamethrin (3 mg/kg or vehicle every 3 days) at a concentration well below the EPA-determined benchmark dose used for regulatory guidance. We raised male offspring to adulthood and collected whole brain samples for untargeted high-resolution metabolomics analysis. Developmentally exposed mice had disruptions in 116 metabolites which clustered into pathways for folate biosynthesis, retinol metabolism, and tryptophan metabolism. As a cross-validation, we integrated metabolomics and transcriptomics data from the same samples, which confirmed previous findings of altered dopamine signaling. These results suggest that pyrethroid exposure during development leads to disruptions in folate metabolism in the adult brain, which may inform both prevention and therapeutic strategies.

Developmental pyrethroid exposure causes a neurodevelopmental disorder phenotype in mice.

Neurodevelopmental disorders (NDDs) are a widespread and growing public health challenge, affecting as many as 17% of children in the United States. Recent epidemiological studies have implicated ambient exposure to pyrethroid pesticides during pregnancy in the risk for NDDs in the unborn child. Using a litter-based, independent discovery-replication cohort design, we exposed mouse dams orally during pregnancy and lactation to the Environmental Protection Agency's reference pyrethroid, deltamethrin, at 3 mg/kg, a concentration well below the benchmark dose used for regulatory guidance. The resulting offspring were tested using behavioral and molecular methods targeting behavioral phenotypes relevant to autism and NDD, as well as changes to the striatal dopamine system. Low-dose developmental exposure to the pyrethroid deltamethrin (DPE) decreased pup vocalizations, increased repetitive behaviors, and impaired both fear conditioning and operant conditioning. Compared with control mice, DPE mice had greater total striatal dopamine, dopamine metabolites, and stimulated dopamine release, but no difference in vesicular dopamine capacity or protein markers of dopamine vesicles. Dopamine transporter protein levels were increased in DPE mice, but not temporal dopamine reuptake. Striatal medium spiny neurons showed changes in electrophysiological properties consistent with a compensatory decrease in neuronal excitability. Combined with previous findings, these results implicate DPE as a direct cause of an NDD-relevant behavioral phenotype and striatal dopamine dysfunction in mice and implicate the cytosolic compartment as the location of excess striatal dopamine.

Augmenting control arms with real-world data for cancer trials: Hybrid control arm methods and considerations.

Background: Hybrid controlled trials with real-world data (RWD), where the control arm is composed of both trial and real-world patients, could facilitate research when the feasibility of randomized controlled trials (RCTs) is challenging and single-arm trials would provide insufficient information. Methods: We propose a frequentist two-step borrowing method to construct hybrid control arms. We use parameters informed by a completed randomized trial in metastatic triple-negative breast cancer to simulate the operating characteristics of dynamic and static borrowing methods, highlighting key trade-offs and analytic decisions in the design of hybrid studies. Results: Simulated data were generated under varying residual-bias assumptions (no bias: HRRWD = 1) and experimental treatment effects (target trial scenario: HRExp = 0.78). Under the target scenario with no residual bias, all borrowing methods achieved the desired 88% power, an improvement over the reference model (74% power) that does not borrow information externally. The effective number of external events tended to decrease with higher bias between RWD and RCT (i.e. HRRWD away from 1), and with weaker experimental treatment effects (i.e. HRExp closer to 1). All dynamic borrowing methods illustrated (but not the static power prior) cap the maximum Type 1 error over the residual-bias range considered. Our two-step model achieved comparable results for power, type 1 error, and effective number of external events borrowed compared to other borrowing methodologies. Conclusion: By pairing high-quality external data with rigorous simulations, researchers have the potential to design hybrid controlled trials that better meet the needs of patients and drug development.

Acid-sensing ion channel 1a regulates the specificity of reconsolidation of conditioned threat responses.

Recent research on altering threat memory has focused on a reconsolidation window. During reconsolidation, threat memories are retrieved and become labile. Reconsolidation of distinct threat memories is synapse dependent, whereas the underlying regulatory mechanism of the specificity of reconsolidation is poorly understood. We designed a unique behavioral paradigm in which a distinct threat memory can be retrieved through the associated conditioned stimulus. In addition, we proposed a regulatory mechanism by which the activation of acid-sensing ion channels (ASICs) strengthens the distinct memory trace associated with the memory reconsolidation to determine its specificity. The activation of ASICs by CO2 inhalation, when paired with memory retrieval, triggers the reactivation of the distinct memory trace, resulting in greater memory lability. ASICs potentiate the memory trace by altering the amygdala-dependent synaptic transmission and plasticity at selectively targeted synapses. Our results suggest that inhaling CO2 during the retrieval event increases the lability of a threat memory through a synapse-specific reconsolidation process.

Emulating Control Arms for Cancer Clinical Trials Using External Cohorts Created From Electronic Health Record-Derived Real-World Data.

Electronic health record (EHR)-derived real-world data (RWD) can be sourced to create external comparator cohorts to oncology clinical trials. This exploratory study assessed whether EHR-derived patient cohorts could emulate select clinical trial control arms across multiple tumor types. The impact of analytic decisions on emulation results was also evaluated. By digitizing Kaplan-Meier curves, we reconstructed published control arm results from 15 trials that supported drug approvals from January 1, 2016, to April 30, 2018. RWD cohorts were constructed using a nationwide EHR-derived de-identified database by aligning eligibility criteria and weighting to trial baseline characteristics. Trial data and RWD cohorts were compared using Kaplan-Meier and Cox proportional hazards regression models for progression-free survival (PFS) and overall survival (OS; individual cohorts) and multitumor random effects models of hazard ratios (HRs) for median endpoint correlations (across cohorts). Post hoc, the impact of specific analytic decisions on endpoints was assessed using a case study. Comparing trial data and weighted RWD cohorts, PFS results were more similar (HR range = 0.63-1.18, pooled HR = 0.84, correlation of median = 0.91) compared to OS (HR range = 0.36-1.09, pooled HR = 0.76, correlation of median = 0.85). OS HRs were more variable and trended toward worse for RWD cohorts. The post hoc case study had OS HR ranging from 0.67 (95% confidence interval (CI): 0.56-0.79) to 0.92 (95% CI: 0.78-1.09) depending on specific analytic decisions. EHR-derived RWD can emulate oncology clinical trial control arm results, although with variability. Visibility into clinical trial cohort characteristics may shape and refine analytic approaches.

Real-World Outcomes of Patients with Metastatic Non-Small Cell Lung Cancer Treated with Programmed Cell Death Protein 1 Inhibitors in the Year Following U.S. Regulatory Approval.

BACKGROUND: Evidence from cancer clinical trials has strong internal validity but can be difficult to generalize to real-world patient populations. Here we analyzed real-world outcomes of patients with metastatic non-small cell lung cancer (mNSCLC) treated with programmed cell death protein 1 (PD-1) inhibitors in the first year following U.S. regulatory approval. MATERIALS AND METHODS: This retrospective study leveraged electronic health record (EHR) data collected during routine patient care in community cancer care clinics. The cohort included patients with mNSCLC who had received nivolumab or pembrolizumab for metastatic disease (n = 1,344) with >1 EHR-documented visit from January 1, 2011, to March 31, 2016. Patients with a > 90-day gap between advanced disease diagnosis and first EHR structured data entry were excluded. RESULTS: Estimated median overall survival (OS) was 8.0 months (95% confidence interval 7.4-9.0 months). Estimated median OS was 4.7 months (3.4-6.6) for patients with anaplastic lymphoma kinase rearrangement- and epidermal growth factor receptor mutation-positive tumors, and 8.6 months (7.7-10.6) for patients without such mutations. Age at PD-1 inhibitor initiation or line of therapy did not impact OS. CONCLUSION: This analysis suggests OS in real-world patients may be shorter than in conventional clinical trial patient cohorts, potentially due to narrow trial eligibility criteria. The lack of difference in OS by line of therapy or age at immunotherapy initiation suggests sustained benefit of PD-1 inhibitors in multitreated patients with mNSCLC and that age is not a predictor of outcome. Further studies are underway in patients with comorbidities, organ dysfunction, and multiple prior therapies. IMPLICATIONS FOR PRACTICE: This study evaluated data derived from electronic health records of patients with metastatic non-small cell lung cancer treated with programmed cell death protein 1 (PD-1) inhibitors in the year following regulatory approval. This real-world cohort had shorter overall survival (OS) indexed to PD-1 inhibitor initiation than reported in clinical trials. Late-line treatment did not influence OS, and patients aged >75 at immunotherapy initiation did not have worse outcomes than younger patients. As new therapies enter clinical practice, real-world data can complement clinical trial evidence providing information on generalizability and helping inform clinical treatment decisions.

Development and Validation of a High-Quality Composite Real-World Mortality Endpoint.

OBJECTIVE: To create a high-quality electronic health record (EHR)-derived mortality dataset for retrospective and prospective real-world evidence generation. DATA SOURCES/STUDY SETTING: Oncology EHR data, supplemented with external commercial and US Social Security Death Index data, benchmarked to the National Death Index (NDI). STUDY DESIGN: We developed a recent, linkable, high-quality mortality variable amalgamated from multiple data sources to supplement EHR data, benchmarked against the highest completeness U.S. mortality data, the NDI. Data quality of the mortality variable version 2.0 is reported here. PRINCIPAL FINDINGS: For advanced non-small-cell lung cancer, sensitivity of mortality information improved from 66 percent in EHR structured data to 91 percent in the composite dataset, with high date agreement compared to the NDI. For advanced melanoma, metastatic colorectal cancer, and metastatic breast cancer, sensitivity of the final variable was 85 to 88 percent. Kaplan-Meier survival analyses showed that improving mortality data completeness minimized overestimation of survival relative to NDI-based estimates. CONCLUSIONS: For EHR-derived data to yield reliable real-world evidence, it needs to be of known and sufficiently high quality. Considering the impact of mortality data completeness on survival endpoints, we highlight the importance of data quality assessment and advocate benchmarking to the NDI.

The genetic diversity of hepatitis A genotype I in Bulgaria.

The purpose of this study was to analyze sequences of hepatitis A virus (HAV) Ia and Ib genotypes from Bulgarian patients to investigate the molecular epidemiology of HAV genotype I during the years 2012 to 2014. Around 105 serum samples were collected by the Department of Virology of the National Center of Infectious and Parasitic Diseases in Bulgaria. The sequenced region encompassed the VP1/2A region of HAV genome. The sequences obtained from the samples were 103. For the phylogenetic analyses, 5 datasets were built to investigate the viral gene in/out flow among distinct HAV subpopulations in different geographic areas and to build a Bayesian dated tree, Bayesian phylogenetic and migration pattern analyses were performed. HAV Ib Bulgarian sequences mostly grouped into a single clade. This indicates that the Bulgarian epidemic is partially compartmentalized. It originated from a limited number of viruses and then spread through fecal-oral local transmission. HAV Ia Bulgarian sequences were intermixed with European sequences, suggesting that an Ia epidemic is not restricted to Bulgaria but can affect other European countries. The time-scaled phylogeny reconstruction showed the root of the tree dating in 2008 for genotype Ib and in 1999 for genotype Ia with a second epidemic entrance in 2003. The Bayesian skyline plot for genotype Ib showed a slow but continuous growth, sustained by fecal-oral route transmission. For genotype Ia, there was an exponential growth followed by a plateau, which suggests better infection control. Bidirectional viral flow for Ib genotype, involving different Bulgarian areas, was observed, whereas a unidirectional flow from Sofia to Ihtiman for genotype Ia was highlighted, suggesting the fecal-oral transmission route for Ia.

Characteristics of Real-World Metastatic Non-Small Cell Lung Cancer Patients Treated with Nivolumab and Pembrolizumab During the Year Following Approval.

BACKGROUND: Evidence from cancer clinical trials can be difficult to generalize to real-world patient populations, but can be complemented by real-world evidence to optimize personalization of care. Further, real-world usage patterns of programmed cell death protein 1 (PD-1) inhibitors following approval can inform future studies of subpopulations underrepresented in clinical trials. MATERIALS AND METHODS: We performed a multicenter analysis using electronic health record data collected during routine care of patients treated in community cancer care clinics in the Flatiron Health network. Real-world metastatic non-small cell lung cancer (NSCLC) patients who received nivolumab or pembrolizumab in the metastatic setting (n = 1,344) were selected from a starting random sample of 55,969 NSCLC patients with two or more documented visits from January 1, 2011, through March 31, 2016. The primary study outcome measurement was demographic and treatment characteristics of the cohort. RESULTS: Median age at PD-1 inhibitor initiation was 69 years (interquartile range 61-75). Patients were 56% male, 88% smokers, 65% nonsquamous histology, and 64% diagnosed at stage IV. Of 1,344 patients, 112 (8%) were tested for programmed death-ligand 1 expression. Overall, 50% received nivolumab or pembrolizumab in the second line, with a substantial proportion of third and later line use that began to decline in Q4 2015. CONCLUSION: During the year following U.S. regulatory approval of PD-1 inhibitors for treatment of NSCLC, real-world patients receiving nivolumab or pembrolizumab were older at treatment initiation and more had smoking history relative to clinical trial cohorts. Studies of outcomes in underrepresented subgroups are needed to inform real-world treatment decisions. IMPLICATIONS FOR PRACTICE: Evidence gathered in conventional clinical trials used to assess safety and efficacy of new therapies is not necessarily generalizable to real-world patients receiving these drugs following regulatory approval. Real-world evidence derived from electronic health record data can yield complementary evidence to enable optimal clinical decisions. Examined here is a cohort of programmed cell death protein 1 inhibitor-treated metastatic non-small cell lung cancer patients in the first year following regulatory approval of these therapies in this indication. The analysis revealed how the real-world cohort differed from the clinical trial cohorts, which will inform which patients are underrepresented and warrant additional studies.

Coordination of Cell Cycle Progression and Mitotic Spindle Assembly Involves Histone H3 Lysine 4 Methylation by Set1/COMPASS.

Methylation of histone H3 lysine 4 (H3K4) by Set1 complex/COMPASS is a hallmark of eukaryotic chromatin, but it remains poorly understood how this post-translational modification contributes to the regulation of biological processes like the cell cycle. Here, we report a H3K4 methylation-dependent pathway in Saccharomyces cerevisiae that governs toxicity toward benomyl, a microtubule destabilizing drug. Benomyl-sensitive growth of wild-type cells required mono- and dimethylation of H3K4 and Pho23, a PHD-containing subunit of the Rpd3L complex. Δset1 and Δpho23 deletions suppressed defects associated with ipl1-2 aurora kinase mutant, an integral component of the spindle assembly checkpoint during mitosis. Benomyl resistance of Δset1 strains was accompanied by deregulation of all four tubulin genes and the phenotype was suppressed by tub2-423 and Δtub3 mutations, establishing a genetic link between H3K4 methylation and microtubule function. Most interestingly, sine wave fitting and clustering of transcript abundance time series in synchronized cells revealed a requirement for Set1 for proper cell-cycle-dependent gene expression and Δset1 cells displayed delayed entry into S phase. Disruption of G1/S regulation in Δmbp1 and Δswi4 transcription factor mutants duplicated both benomyl resistance and suppression of ipl1-2 as was observed with Δset1 Taken together our results support a role for H3K4 methylation in the coordination of cell-cycle progression and proper assembly of the mitotic spindle during mitosis.

Opportunities and challenges in leveraging electronic health record data in oncology.

The widespread adoption of electronic health records (EHRs) and the growing wealth of digitized information sources about patients is ushering in an era of 'Big Data' that may revolutionize clinical research in oncology. Research will likely be more efficient and potentially more accurate than the current gold standard of manual chart review studies. However, EHRs as they exist today have significant limitations: important data elements are missing or are only captured in free text or PDF documents. Using two case studies, we illustrate the challenges of leveraging the data that are routinely collected by the healthcare system in EHRs (e.g., real-world data), specific challenges encountered in the cancer domain and opportunities that can be achieved when these are overcome.